This page lists past seminars and presentations by STAR
scientists and visiting scientists. These seminars include the STAR
Science Forum and similar events. Presentation materials for
seminars will be provided when available.
James G. (Jim) Yoe serves in the Office of the Director of the National Centers for Environmental Prediction as NCEP's Research Transition Manager. In this capacity he coordinates NCEP's activities for the Science and Technology Integration portfolio and the Observations portfolio, and he serves as the Chief Administrative Officer of the Joint Center for Satellite Data Assimilation (JCDSA.) Prior to joining NCEP, he spent 14 years with the National Environmental Satellite Data and Information Service, as a member of the NPOESS Data Exploitation Project, after working in STAR and serving as Deputy Director of the JCSDA, and developing applications for space-based remote sensors including Doppler Wind lidar and GPS Radio Occultation. He earned BS and PhD degrees in physics from the University of the South and Clemson University, respectively, and conducted post-doctoral research investigating winds, waves, and turbulence using MST Doppler radar and UV lidar at the Max Planck Institute for Aeronomy in Germany. His hobbies include gardening, playing the guitar, and archery. Dogs love him.
Presenter(s): Michael Jacox, NOAA Southwest Fisheries Science Center
Seminar
Sponsor(s): NOAA Ocean Color Coordinating Group (NOCCG). This seminar will not be recorded. Slides may be shared upon request (send email to the POC listed below).
Abstract: The National Marine Fisheries Service (NMFS) and fisheries management councils are increasingly striving to implement ecosystem-based fishery management. A key need in support of this effort is the provision of accurate, reliable environmental data at temporal and spatial resolutions that are consistent with ecosystem dynamics and management objectives. In this respect, synergistic use of satellites and ocean models is highly beneficial; satellites provide observations to constrain models and ensure fidelity to nature, while models fill data gaps, resolve the ocean subsurface, and provide a consistent product across periods of changing observation assets. Here we describe biophysical ocean reanalyses including the details of our ocean models and satellite data assimilation, how these reanalyses improve estimates of ocean conditions relative to satellites or models alone, and how they are being used to develop fisheries-relevant products and tools.
Bio(s): Mike Jacox is a research oceanographer at NOAA's Southwest Fisheries Science Center and Earth System Research Laboratory. His research addresses physical-biological interactions in the ocean and their connections to climate,particularly in the northeast Pacific. He uses ocean models in conjunction with satellite and other observations to assess ocean variability off the US West Coast and its impacts on marine species ranging from phytoplankton to top predators. Mike holds a PhD in Ocean Sciences from the University of California Santa Cruz and a BS in Aerospace Engineering from the University of Colorado.
Presenter(s): Dr. William Blackwell, MIT Lincoln Laboratory
Seminar
Sponsor(s): ESSIC Seminar Series.
Abstract: Recent technology advances in miniature microwave radiometers that can be hosted on very small satellites have made possible a new class of constellation missions that provide very high revisit rates of tropical cyclones and other severe weather. The Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats (TROPICS) mission was selected by NASA as part of the Earth Venture"Instrument (EVI-3) program and is now in development with planned launch readiness in late 2019. The overarching goal for TROPICS is to provide nearly all-weather observations of 3-D temperature and humidity, as well as cloud ice and precipitation horizontal structure, at high temporal resolution to conduct high-value science investigations of tropical cyclones (TCs), including: (1) relationships of rapidly evolving precipitation and upper cloud structures to upper-level warm-core intensity and associated storm intensity changes; (2) evolution (including diurnal variability) of precipitation structure and storm intensification in relationship to environmental humidity fields; and (3) the impact of rapid-update observations on numerical and statistical intensity forecasts of tropical cyclones.
TROPICS will provide rapid-refresh microwave measurements (median refresh rate better than 60 minutes for the baseline mission) over the tropics that can be used to observe the thermodynamics of the troposphere and precipitation structure for storm systems at the mesoscale and synoptic scale over the entire storm lifecycle. TROPICS will comprise a constellation of six 3U CubeSats in three low-Earth orbital planes. Each CubeSat will host a high performance scanning radiometer to provide temperature profiles using seven channels near the 118.75 GHz oxygen absorption line, water vapor profiles using three channels near the 183 GHz water vapor absorption line, imagery in a single channel near 90 GHz for precipitation measurements (when combined with higher resolution water vapor channels), and a single channel at 205 GHz that is more sensitive to precipitation-sized ice particles and low-level moisture. This observing system offers an unprecedented combination of horizontal and temporal resolution in the microwave spectrum to measure environmental and inner-core conditions for TCs on a nearly global scale and is a major leap forward in the temporal resolution of several key parameters needed for assimilation into advanced data assimilation systems capable of utilizing rapid-update radiance or retrieval data.
This presentation will provide an overview of the mission and an update on current status, with a focus on recent performance simulations on a range of observables to be provided by the constellation, including temperature, water vapor, rain rate, and TC intensity indicators.
Bio(s): Bill Blackwell received the B.E.E. degree in electrical engineering from the Georgia Institute of Technology, Atlanta, GA, USA, in 1994, and the S.M. and Sc.D. degrees in electrical engineering and computer science from the Massachusetts Institute of Technology (MIT), Cambridge, MA, USA, in 1995 and 2002, respectively. Since 2002, he has been with the Lincoln Laboratory, MIT, where he is currently an Associate Leader of the Applied Space Systems Group. He serves or has previously served on the NASA Atmospheric Infrared Sounder and NPP science teams, the Joint Polar Satellite System Sounding Operational Algorithm Team, and the National Academy of Sciences Committee on Radio Frequencies. He was the Integrated Program Office Sensor Scientist for the Advanced Technology Microwave Sounder on the Suomi National Polar Partnership launched in 2011 and the Atmospheric Algorithm Development Team Leader for the National Polar-Orbiting Environmental Satellite System Microwave Imager/Sounder. He has served as the Principal Investigator on the MicroMAS-1, MicroMAS-2, and MiRaTA microwave sounding CubeSat missions and is currently PI on the NASA TROPICS Earth Venture mission (https://tropics.ll.mit.edu/CMS/tropics/). His current research interests include atmospheric remote sensing, including the development and calibration of airborne and spaceborne microwave and hyperspectral infrared sensors, retrieval of geophysical products from remote radiance measurements, and the application of electromagnetic, signal processing, and estimation theory. Dr. Blackwell is a fellow of IEEE and the recipient of the 2009 NOAA David Johnson Award for his research in neural network retrievals and microwave calibration and was selected as a 2012 recipient of the IEEE Region 1 Managerial Excellence in Engineering Organization Award for outstanding leadership of the multidisciplinary technical teams developing innovative future microwave remote sensing systems.
Seminar POC for questions or access to slides:
For IT assistance ------------------------------------------------------- Cazzy Medley: cazzy@umd.edu Travis Swaim: tswaim1@umd.edu
Abstract: The purpose of the National Oceanic and Atmospheric Administration (NOAA) CoastWatch/OceanWatch/PolarWatch Program (a.k.a. CoastWatch, https://coastwatch.noaa.gov) is to improve decision outcomes by facilitating the use of ocean satellite data in applications and research. NOAA CoastWatch provides free and open access to global and regional satellite data products for use in understanding, managing and protecting ocean and coastal resources and for assessing impacts of environmental change in ecosystems, weather, and climate. The seed for what later was to become CoastWatch was an unusual algal bloom off the coast of North Carolina in 1987. Dr. Pat Tester, of the NOAA Beaufort Laboratory, used satellite sea surface temperature imagery to investigate the cause (Tester et al., 1991). The printed images were delivered to her by mail. With time and in response to the continual development of ocean observations from space, the CoastWatch scope has expanded to include multiple environmental parameters such as sea surface temperature, ocean color (chlorophyll, etc.), sea surface height (altimetry), ocean winds, surface roughness (synthetic aperture radar), salinity and sea ice. These products have global and regional coverage and near real-time as well as delayed-mode, higher quality and longer term time series datasets. CoastWatch customizes, serves, monitors, and provides user training for ocean and coastal remote sensing data products from NOAA and non-NOAA satellite missions to several audiences who use those products in research and in operational oceanographic applications. The program is organized as a hub and spokes. The hub has the primary processing responsibilities and is co-located with the NOAA ocean satellite environmental data record (EDR; i.e., Level 2) science team producers. The spokes are regional Nodes that are distributed geographically and across NOAA mission line offices. With this arrangement, CoastWatch is well-positioned to bridge upstream ocean EDR producers with downstream user needs. This presentation will give an overview of the data, tools, and services provided by CoastWatch, and show some examples of user applications.
Bio(s): Trained as a biological oceanographer, Veronica Lance spent much of her early research career at sea studying phytoplankton assemblages, phytoplankton photophysiology and primary productivity in relation to geo-physico-chemical environments, especially in regions where iron is a regulating micro-nutrient. After earning her PhD from Duke University and a PostDoc at Lamont-Doherty Earth Observatory at Columbia University, her interests expanded to using satellite remote sensing of ocean color to understand spatial and temporal patterns of ocean productivity as researcher working with NASA Goddard Space Flight Center. Lance began working with the NOAA Ocean Color Science team in 2014. Currently, in her position as a research scientist with the Earth System Science Interdisciplinary Center, Cooperative Institute for Satellite Earth System Studies at the University of Maryland, she serves as Program Scientist for NOAACoastWatch/OceanWatch/PolarWatch and works closely with the Center for Satellite Applications and Research, Satellite Oceanography and Climatology Division at NOAA/NESDIS in several functions.
Abstract: Brian will present recent work using machine learning to analyze time series data from chaotic systems. Most of the results concern learning the systems dynamics to facilitate forecasting and climate simulation, but I will also discuss potential applications in data assimilation. First I will show successful application of a particular form of machine learning called reservoir computing to data from relatively low-dimensional systems, and discuss a partial theory for how the method works. Then I will present extensions of the method to handle high-dimensional, spatially-extended systems using parallel computing, and to a hybrid approach using machine learning to improve an imperfect physics-based model.
Bio(s): Brian R. Hunt received a master's degree in mathematics from the University of Maryland in 1983. He went on to study applied mathematics at Stanford University, receiving a Ph.D. in 1989 for research in fluid dynamics and geometric optics. He has since returned to the University of Maryland to pursue research in dynamical systems and fractal geometry, where he is currently a Professor of Mathematics with a joint appointment in the Institute for Physical Science and Technology.
Abstract: Artificial neural networks (ANNs) have emerged as an important tool for many environmental science applications. However, ANNs are not naturally transparent and are thus often used as a black box, i.e. without detailed understanding of their reasoning. Fortunately, new tools for the interpretation of ANN models are becoming available from the field of explainable AI. Such tools can provide great benefits for earth science researchers. In this tutorial we first provide a general overview, including methods for both ANN visualization and ANN attribution. Then we focus on one method in detail, namely layer-wise relevance propagation (LRP; sometimes known as Deep Taylor decomposition), and show how it can be used to identify the specific elements of the input that were most important for the ANN's prediction. Thus, this method helps "open the black box" and attribute specific predictions to specific predictands. We find LRP methods to be particularly useful, yet few in the earth science community seem to have discovered them. We demonstrate the use of LRP methods for a variety of applications related to weather and climate, and show their use for tasks ranging from debugging and designing ANN networks to gaining new scientific insights for atmospheric science applications.
Bio(s): Imme Ebert-Uphoff received B.S. and M.S. degrees in Mathematics from the Technical University of Karlsruhe (known today as Karlsruhe Institute of Technology or KIT). She received M.S and Ph.D. degrees in Mechanical Engineering from the Johns Hopkins University. She was a faculty member in Mechanical Engineering at Georgia Tech for over 10 years, before joining the Electrical & Computer Engineering department at Colorado State in 2011 as research professor. Her research interests are in applying data science methods to climate applications. She is also very involved in activities to build bridges between the AI community and the earth science community, including serving on the steering committee of the annual Climate Informatics workshop, and of the NSF sponsored research coordination network (RCN) on Intelligent Systems for the Geosciences. Starting July 1, 2019, she is spending 50% of her time with CIRA to support their machine learning activities.
Dr. Elizabeth (Libby) Barnes is an associate professor of Atmospheric Science at Colorado State University. She joined the CSU faculty in 2013 after obtaining dual B.S. degrees (Honors) in Physics and Mathematics from the University of Minnesota, obtaining her Ph.D. in Atmospheric Science from the University of Washington, and spending a year as a NOAA Climate & Global Change Fellow at the Lamont-Doherty Earth Observatory. Professor Barnes' research is focused on large scale atmospheric variability and the data analysis tools used to understand its dynamics. Topics of interest include jet-stream dynamics, Arctic-midlatitude connections, subseasonal-to-seasonal (S2S) prediction of extreme weather events (she is currently Task Force Lead for the NOAA MAPP Subseasonal-to-Seasonal (S2S) Prediction Task Force), health-related climate impacts, and data science methods for climate research (e.g. machine learning, causal discovery). She teaches graduate courses on fundamental atmospheric dynamics and data science and statistical analysis methods.
Ben Toms is a fourth year PhD student in the Barnes research group in the Department of Atmospheric Science at Colorado State University. His PhD research focuses on using neural networks to improve our understanding of decadal predictability within the climate system. This research requires a fundamental understanding of neural networks and techniques for their interpretation, so he enjoys testing which methods proposed by the computer science community are transferrable to atmospheric science.
Abstract: I am completing a 1-year research visit program sponsored by the Japanese Government at the NOAA Satellite and Information Service (NESDIS) Cooperative Institute for Climate and Satellites (CICS), which is now the Cooperative Institute for Satellite Earth System Studies (CISESS). My research at CICS has primarily focused on evaluating the Geostationary Lightning Mapper (GLM) Level 2 product. In this study, the GLM Level 2 product was validated using ground-based lightning observations, in terms of flash geographical distribution and flash detection efficiency, as well as group timing and geolocation accuracy.
The presentation will provide an overview of JMA's Himawari satellites, results of the GLM product validation, and highlights of other studies I have conducted at CICS, such as cost benefit analysis of weather satellites.
Bio(s): Mr. Yoshida's is a Scientific Officer at the Satellite Program Division, Japan Meteorological Agency (JMA). His work at JMA has been concerned with the Himawari series satellites. He developed Himawari-8/9 image navigation and registration processing operating on the ground system. He was also responsible for development and implementation of Himawari-8/9 level 2 products at the Meteorological Satellite Center of JMA. Mr. Yoshida received B.S. and M.S. degrees in geophysics from Tohoku University, in 2007 and 2009, respectively.
Conference Room # 2552-2553, NOAA Center for Weather and Climate Prediction, 5830 University Research Court, College Park, MD, NCWCP - Large Conf Rm - 2552-2553
Abstract: We propose a novel Bayesian Monte Carlo Integration (BMCI) technique to retrieve the profiles of temperature, water vapor, and cloud liquid/ice water content from microwave cloudy measurements in the rainbands of tropical cyclones (TC). These retrievals then can either be directly used by meteorologists to analyze the structure of TCs or be assimilated into numerical models to provide accurate initial conditions for the NWP models. The BMCI technique is applied to the data from the Advanced Technology Microwave Sounder (ATMS) onboard Suomi National Polar-orbiting Partnership (NPP) and Global Precipitation Measurement (GPM) Microwave Imager (GMI).
Bio(s): Dr. Isaac Moradi is a remote sensing scientist with over fifteen years of experience specializing in radiative transfer modeling; Observing System Simulation Experiments (OSSE); data assimilation; satellite data analysis and bias correction; atmospheric humidity and ice clouds; inverse methods and retrieving geophysical variables from satellite observations; solar radiation resource assessment; quality assurance of solar radiation and in-situ radiosonde measurements; and developing new instrument concepts especially for measuring tropospheric humidity. Please also see https://science.gsfc.nasa.gov/sed/bio/isaac.moradi
Conference Room # 2552-2553, NOAA Center for Weather and Climate Prediction, 5830 University Research Court, College Park, MD, NCWCP - Large Conf Rm - 2552-2553
Abstract: A high elevation rain gauge network, known as the Duke Great Smoky Mountains Rain Gauge Network (Duke GSMRGN), has been collecting rainfall observations since 2007 in the Pigeon River Basin located in the Southern Appalachian Mountains. The presentation will focus on the founding, funding, findings, and future of the Duke GSMRGN and their associated fellowships. The findings portion will examine the influence of atmospheric rivers on extreme rainfall events observed by the Duke GSMRGN over an eight-year period commencing 1 July 2009.
Bio(s): Douglas Miller is a professor at the University of North Carolina, Asheville. He received his Ph.D. in atmospheric sciences from Purdue University. His research expertise is in mesoscale and synoptic meteorology, mountain meteorology, coastal meteorology, boundary layer meteorology, and numerical weather prediction/forecasting. He has been involved with a collaborative project extending the Great Smoky Mountain rain gauge mesonet and exploring the origins of extreme precipitation events in the southern Appalachian Mountains and their signatures as observed by the GOES-R satellite.
NOCCG Seminar crosslisted with OneNOAA and STAR Seminars
Presenter(s): Mari Smith, Natural Resources & Environment Unit, Council for Scientific and Industrial Research (CSIR), Cape Town, South Africa Seminar
Sponsor(s): NOAA Ocean Color Coordinating Group (NOCCG). This seminar will not be recorded. Slides may be shared upon request (send email to the POC listed below).
Abstract: This seminar aims to highlight some of the research and development taking place as part of two projects: 1) the South African Oceans and Coasts Information Management System (OCIMS) project, and 2) the Marine and Coastal Service Development for Southern Africa (MarCoSouth) project, i.e. the southern African consortium of the Global Monitoring for Environment and Security (GMES) Africa Grant. OCIMS is an innovative web-based platform offering a variety of decision support tools intended to empower decision-makers and support effective governance and growth of South Africa's blue economy. OCIMS has consolidated South African observational and forecasting expertise through the development of a range of services that are very similar in scope to those proposed for GMES & Africa. The MarCoSouth project is strongly aligned with (and will effectively provide a platform for the regional expansion of) the services developed through OCIMS. Within GMES & Africa the MarCoSouth project will maintain, further develop and provide a sustainable platform for local, institutional, human and technical capabilities in the African partner countries (i.e. Namibia, Mozambique, Tanzania, Kenya and South Africa) through the development of services focused on sustainable socio-economic development, empowering a wide range of users in the public and private sectors through the application of regionally-optimized satellite observations and model based forecasts in the South and East African Marine and Coastal domains
Bio(s): Dr. Mari Smith is a Postdoc (soon to be senior researcher) in the Marine Earth Observation Unit of the Council for Scientific and Industrial Research (CSIR) in Cape Town, South Africa. She has a PhD in physical oceanography from the University of Cape Town and has specialized in marine remote sensing for 11 years. Her main areas of interest are optical water type classification and ocean color algorithm development, particularly for coastal marine applications. She is the lead on operational earth observation product development for harmful algal bloom (HAB) detection, aquaculture, fisheries and water quality decision support for the OCIMS and MarCoSouth projects. She is also actively involved in post-graduate student supervision and training in Africa.
Conference Room # 2552-2553, NOAA Center for Weather and Climate Prediction, 5830 University Research Court, College Park, MD, NCWCP - Large Conf Rm - 2552-2553
Abstract: One of the most striking, and widely publicized, environmental changes underway in the Earth system is the disappearance of the Arctic sea ice cover. Since sea ice is a key component of the climate system, its ongoing loss has serious, and wide-ranging, socio-economic implications. Increasing year-to-year variability in the geographic location, concentration and thickness of Arctic ice will pose both challenges and opportunities. Advancing our understanding of how the sea ice cover varies, and why, is key to characterizing the physical processes governing change, and for advancing model predictions. An emerging need is short-time-critical sea ice data products to support safety and security for maritime operations in ice-infested waters.
Altimeter instruments on satellite and aircraft platforms have revolutionized our understanding of Arctic sea ice mass balance over the last two decades. Satellite laser and radar altimeters on NASA's ICESat and ICESat-2 satellites, and ESA's CryoSat-2, provide unique measurements of sea ice elevation, from which ice thickness may be derived, across basin scales. Meanwhile altimeters deployed on aircraft such as the Operation IceBridge Mission, together with coincident digital imagery, provide a range of novel, high-resolution observations that describe key features of the ice cover including its snow cover, surface morphology and deformation characteristics, and summer melt features. We will explore the novel sea ice data products developed at the NOAA Laboratory for Satellite Altimetry that describe changes in the Arctic ice cover during the last two decades. We will also discuss efforts to advance access to polar ocean remote sensing observations and improve communication with Arctic stakeholders through the NOAA PolarWatch initiative, which is designed to deliver data products that best address societal needs (polarwatch.noaa.gov).
Bio(s): Sinad Louise Farrell is an associate professor with the Department of Geographical Sciences at the University of Maryland, and a visiting scientist at the NOAA / NESDIS / STAR / SOCD Laboratory for Satellite Altimetry, College Park, Maryland. Dr. Farrell received her Ph.D. in Space and Climate Physics from University College London in 2007. Her primary fields of study are cryospheric sciences and remote sensing. She is a principal investigator on the NASA ICESat-2 Science Team and a member of the Mission Advisory Group for the EU Copernicus Polar Ice and Snow Topography Altimeter. Prior to joining the Department of Geographical Sciences, Dr. Farrell was with the Earth System Science Interdisciplinary Center (ESSIC), at the University of Maryland.
Conference Room # 2554-2555, NOAA Center for Weather and Climate Prediction, 5830 University Research Court, College Park, MD, NCWCP - Large Conf Rm - 2554-2555
Science posters are a fundamental unit for disseminating and communicating our work in the sciences. For most researchers, however, drafting and producing posters is crammed into the last minute before important meetings and conferences, and few are educated about the basics of layout, color, type selection, and design. In this talk I'll introduce concepts, techniques, and tools to help you design and produce better posters and presentations. You don't have to be an artist to create an attractive, effective, easy to read poster that draws visitors to learn about your work.
Bio(s): Lori Brown has been a graphic designer and web developer for over 20 years, and STAR webmaster since 2006. Ms. Brown has a strong understanding of workflow and form design, usability principles, information design, and accessibility standards. Lori is the UI designer / developer for the STAR GOES Imagery site, which, since its launch in December 2017, has averaged about 10 million image downloads and 100,000 page views per day.
Abstract: NOAA PolarWatch is the newest satellite data distribution portal of NOAA's CoastWatch program. The portal offers a single location for federal agencies, research groups, and private industry to obtain the most recent and historical satellite observations of Arctic and Antarctic waters, including measurements of sea ice cover, ocean temperature, and winds. We will provide an overview of the data and services provided by PolarWatch with examples that demonstrate supporting safety at sea, navigation, fishing, transportation, tourism, and recreation. We will also highlight user training materials and training courses that are designed to encourage broad usage of polar satellite data.
Bio(s): Jennifer Sevadjian is the Operations Manager for PolarWatch a regional node of NOAA's CoastWatch. She has a background in ocean data management, data integration and web development. She began her career at NOAA CO-OPS Ocean System Test and Evaluation Program, in 2002, collecting in-situ data and performing data analysis, and has gone on to work in many different sectors including the military, academia, private industry and non-profit communities. She joined NOAA PolarWatch in 2017, after serving as the information manager for CeNCOOS (a U.S. IOOS regional association). She is particularly passionate about data discovery, data integration and increasing the use of ocean data and is currently enjoying building solutions to address the challenges associated with polar ocean data.
Conference Room # 2552-2553, NOAA Center for Weather and Climate Prediction, 5830 University Research Court, College Park, MD, NCWCP - Large Conf Rm - 2552-2553
Abstract: Distributing large global or regional datasets to a targeted user community is challenging, particularly if the users require data from many data providers and are interested in discrete geographical and temporal ranges. The ERDDAP data server addresses these challenges, acting as middleman between disparate remote data servers, to provide a single unified pathway for data access that offers 1) a simple, consistent way to download data, 2) subsetting by user-defined areas and time periods, and 3) downloads in over 30 data, image, and metadata formats that are compatible with analysis tools such as R, MATLAB, and Python. The ERDDAP GUI allows users to visualize data and refine download requests. Download requests are completely defined within a URL, allowing machine-to-machine data exchange, bringing data directly into analysis tools, and using ERDDAP as a backend to drive customized online interfaces.
ERDDAP was developed by Bob Simons at the NMFS/SWFSC Environmental Research Division and has been installed by over 80 organizations worldwide. The ERDDAP servers at CoastWatch Regional Nodes and other NOAA offices provide access to thousands of satellite data, model output, and climatology products, as well as ocean-related ancillary datasets (e.g. buoy, shipboard oceanographic, animal track, and in situ data). NOAA's Data Access Procedural Directive includes ERDDAP in its list of recommended data servers for use by groups within NOAA.
In this seminar we will describe the features of ERDDAP, including subsetting and downloading data, creating mapped images, visualizing wind vector fields, and generating timeseries and Hovmller diagrams. A live demonstration of these capabilities will be given. A tutorial explaining how to use ERDDAP is also available on the website of the West Coast Regional node of CoastWatch at https://coastwatch.pfeg.noaa.gov/projects/erddap/. >
Bio(s): Cara Wilson is a satellite oceanographer for the Environmental Research Division (ERD) at NOAA's Southwest Fisheries Science Center in Monterey CA and is the PI of two regional nodes of NOAA's CoastWatch program - the West Coast Regional Node and PolarWatch, which are both housed at ERD. Her research interests are in using satellite data to examine bio-physical coupling in the surface ocean, with a particular focus on determining the biological and physical causes of the large chlorophyll blooms that often develop in late summer in the oligotrophic Pacific near 30N. She received a Ph.D. in oceanography from Oregon State University in 1997, where she examined the physical dynamics of hydrothermal plumes. After getting her PhD she worked as the InterRidge Coordinator at the University Pierre et Marie Curie in Paris, France. Her introduction to remote sensing came with a post-doc at NASA's Goddard Space Flight Center which involved analyzing TOPEX and SeaWiFS data. She joined NOAA in 2002 and has been active in increasing the satellite usage within the National Marine Fisheries Service. She is also the treasurer for PORSEC (Pan Ocean Remote Sensing Conference) and the current chair of the IOCCG (International Ocean Colour Coordinating Group).
Conference Room # 2552-2553, NOAA Center for Weather and Climate Prediction, 5830 University Research Court, College Park, MD, NCWCP - Large Conf Rm - 2552-2553
Abstract: The Low Earth Orbit (LEO) sun-synchronous operational constellation missions have been evolving rapidly in recent years. The Visible-Infrared Imaging Radiometer Suite (VIIRS) has replaced the Advanced Very High Resolution Radiometer (AVHRR) in the afternoon orbit on the Joint Polar-Satellite System (JPSS) satellites, which will provide sustained earth observations till 2031 and beyond. Meanwhile, the last AVHRR, launched on MetOp-C in late 2018, will be replaced by the METimage around 2022, to provide continued observations of the earth in the morning orbit.
This seminar provides an overview of METimage, including its major instrument capabilities, and expected radiometric, spatial, and spectral performance. While VIIRS and METimage have similar characteristics, significant differences exist as well. For example, METimage includes water vapor channels, while VIIRS supports ocean color product generation with dual gain capabilities, and low light imaging with the Day/Night Band. The potential impacts of these differences on product generation will be discussed. Characteristics of the METImage datasets simulated and provided by EUMETSAT will be introduced. The goals are to support the Metop-SG product development at NOAA, facilitate advanced planning and user readiness, as well as collaboration between NOAA and EUMETSAT teams to provide sustained support to the operational global earth observations with a variety of land, ocean, and atmosphere products.
Bio(s): Dr. Changyong Cao specializes in the calibration and validation of radiometers onboard NOAA's Operational environmental satellites. He initially joined NOAA in 1999 as the infrared sounder instrument scientist, became the VIIRS sensor team lead since 2011, and the branch chief for the Satellite Calibration and Data Assimilation Branch (SCDAB) of NESDIS/STAR/SMCD in 2018. In addition, he is actively involved in the Metop-SG(METImage), small satellite data exploitation, and GNSS radio occultation.
In addition to the operational pre&post instrument calibration support, Changyong is responsible for developing and refining the methodology for inter-satellite calibration using the Simultaneous Nadir Overpass (SNO) method, which has been used for the performance monitoring of satellite radiometers, and for developing long-term time series. He has made significant contributions to the international and inter-agency satellite instrument calibration/validation community, including the Committee on Earth Observation Satellites (CEOS) Working Group on Calibration/Validation, and World Meteorological Organization (WMO) Global Space-based Inter-Calibration System (GSICS).
Before joining NOAA in 1999, Changyong was a senior scientist with five years of aerospace industry experience supporting NASA small satellite technology initiative and commercial remote sensing program. He was the recipient of two gold and one silver medals honored by the U.S. Department of Commerce for his scientific and professional achievements. He has served as the reviewer and editor for professional journals, published many peer-reviewed papers, as well as a book on the calibration and validation of visible infrared imaging radiometers. Changyong received his Ph.D., and B.S. degrees in geography from Louisiana State University and Peking University respectively.
Abstract: SCDR is a roughly 1.5-petabyte central repository of selected satellite, numerical model, and ground validation data for use by STAR scientists for research and development, validation, and other activities. This talk will describe SCDR and explain how to use it.
Bio(s): Bob Kuligowski has worked on satellite estimation of rainfall at STAR for nearly 20 years. He also serves as the Chair of the STAR IT Advisory Committee (ITAC), which serves as an interface between STAR science and IT personnel, and of the Data Management Group (DMG), which manages SCDR.
NOCCG Seminar crosslisted with OneNOAA and STAR Seminars
Presenter(s): William Hernandez, Executive Director of Environmental Mapping Consultants and faculty at University of Puerto Rico-Mayaguez Seminar
Sponsor(s): NOAA Ocean Color Coordinating Group (NOCCG). This seminar will not be recorded. Slides may be shared upon request.
Abstract: In this presentation we highlight some examples of the integration of scientific research by Academia, NOAA, and local NGO's to support current ocean color research from satellite and field instrumentation for sites and Puerto Rico and West Maui, HI. Also, we will discuss the development of data portals and workshops to provide easier access to managers from Puerto Rico, US Virgin Islands and Hawaii to the remote sensing and geographic information system (GIS) data. We will also present the integration of drones for supporting observations and address new threats, like Sargassum accumulations and sea level rise. Examples and results from this work will be presented.
Bio(s): Dr. Hernndez is currently working as a private consultant and as an Adjunct Professor of the University of Puerto Rico Mayaguez. He was previously appointed as a Post-Doctoral Researcher for the NOAA CREST City College City University of New York and has more than 12 years of experience in the analysis and processing of remotely sensed data and Geographic Information Systems (GIS). His education consists of a Bachelor's degree in Biology, a Master's degree in Environmental Science (Water Resources) and a Ph.D. in Marine Sciences (Biological Oceanography) from the University of Puerto Rico-Mayaguez. His doctoral dissertation was entitled: Benthic Habitat Mapping and Bio-Optical Characterization La Parguera Marine Reserve using Passive and Active Remote Sensing Data. He has worked in multiple industries including academia, government and private sector, performing duties as an environmental consultant, research scientist, fish and wildlife biologist in government agencies dedicated to conservation, and developer of information systems technology in environmental science and infrastructure management. Dr. Hernndez is currently a collaborator of the NOAA NESDIS STAR Coral Reef Watch Ocean Color Projects and the US Coral Reef Task Force Guanica watershed management. He has also been collecting bio-optical and water quality data in La Parguera and the Gunica area for the past 8 years
Christina Kumler, CIRES and Imme Ebert-Uphoff, CIRA
Date & Time:
8 August 2019
11:30 am - 12:30 pm ET
Location:
Conference Room # 2552-2553, NOAA Center for Weather and Climate Prediction, 5830 University Research Court, College Park, MD, NCWCP - Large Conf Rm - 2552-2553
Abstract: Machine learning is becoming more and more accessible to the scientific community, with high performance computing capabilities, data collection, and increasing availability of free and highly efficient software packages. Part 1 of this talk discusses machine learning projects that are currently ongoing within NOAA ESRL's Global System Division (GSD). GSD has several active projects applying different methods of ML to satellite data that will be covered briefly in this talk. One project in particular, a Regions of Interest (ROI) project that uses deep learning to detect cyclonic ROI from water vapor satellite data, will be highlighted. Part 2 takes a bigger view and discusses some challenges of using machine learning for climate and weather applications. Challenges include the perceived lack of transparency and the potential for incorrect generalization of these methods. We then discuss strategies for overcoming these challenges, including i) leveraging physics in the AI approach and ii) utilizing visualization tools to help understand the reasoning of these algorithms.
Bio(s):
Christina Kumler comes from an applied mathematics, meteorology, and oceanic science background. She completed her B.S. degree at CU Boulder in applied mathematics in 2013 and then completed her M.S. at University of Miami Florida RSMAS in meteorology and physical oceanography in 2015. She is currently a CIRES scientist and specializes in computational aspects of weather modeling. Over the last two years, her time has been dedicated to applying machine learning techniques to big data problems in the field of weather and climate. In her spare time, she races triathlons, hikes, does semi-professional photography, and loves to cook/bake/eat with friends, family, husband, and dog.
Imme Ebert-Uphoff received B.S. and M.S. degrees in Mathematics from the Technical University of Karlsruhe (known today as Karlsruhe Institute of Technology or KIT). She received M.S and Ph.D. degrees in Mechanical Engineering from the Johns Hopkins University. She was a faculty member in Mechanical Engineering at Georgia Tech for over 10 years, before joining the Electrical & Computer Engineering department at Colorado State in 2011 as research professor. Her research interests are in applying data science methods to climate applications. She is also very involved in activities to build bridges between the AI community and the earth science community, including serving on the steering committee of the annual Climate Informatics workshop, and of the NSF sponsored research coordination network (RCN) on Intelligent Systems for the Geosciences. Starting July 1, 2019, she is spending 50% of her time with CIRA to support their machine learning activities.
NOCCG Seminar crosslisted with OneNOAA and STAR Seminars
Presenter(s): Yusuke Kuwayama, Fellow at Resources for the Future, and VALUABLES Consortium Director Seminar
Sponsor(s): NOAA Ocean Color Coordinating Group (NOCCG). This seminar will not be recorded. Slides may be shared upon request.
Abstract: National and international organizations are placing greater emphasis on the societal and economic benefits that are derived from applications of satellite data, yet improvements are needed to connect the decision processes that produce actions with direct societal benefits. Quantifying the socioeconomic benefits of Earth observations can (a) demonstrate return on investment in satellites and data products, (b) help satellite programs make informed choices about how to invest limited resources, (c) give Earth scientists an effective tool for communicating the value of the their work in socioeconomically meaningful terms, and (d) increase the likelihood that a satellite or satellite data application produces socioeconomic benefits by requiring Earth scientist to think about how project outcomes will be evaluated.
To encourage the use of impact assessments to quantify the value of Earth science information energy and environmental economists at Resources for the Future (RFF) are collaborating with NASA Scientists through the VALUABLES Consortium (Consortium for the Valuation of Applications Benefits Linked with Earth Science). I will summarize the consortium's ongoing impact assessments, which quantify the value of using satellite data to enforce air quality standards, regulate air emissions from oil and gas development, detect harmful algal blooms, inform post-wildfire response, and predict ice sheet decline.
Bio(s): Yusuke Kuwayama is a Fellow at Resources for the Future (RFF). Kuwayama's research focuses on the economics of water resource management and the societal value of Earth science information. Kuwayama is also the Director of the Consortium for the Valuation of Applications Benefits Linked with Earth Science (VALUABLES).
Kuwayama's research is often interdisciplinary in nature, involving collaboration with hydrologists, ecologists, and engineers. He has been PI or co-PI on grants supported by a variety of funders including NASA, the Environmental Protection Agency (EPA), and the Bill & Melinda Gates Foundation. His work has been published in outlets such as the Journal of Environmental Economics and Management, Land Economics, Environmental and Resource Economics, the American Journal of Agricultural Economics, Regional Environmental Change, and Hydrogeology Journal. He received his Ph.D. in Agricultural and Applied Economics and M.S. in Economics from the University of Illinois at Urbana-Champaign, and an A.B. in Economics from Amherst College.
Conference Room # 2552-2553, NOAA Center for Weather and Climate Prediction, 5830 University Research Court, College Park, MD, NCWCP - Large Conf Rm - 2552-2553
Abstract: After more than four decades of international research and development in Doppler Wind Lidar, the Atmospheric LAser Doppler INstrument (ALADIN) on ESA's Aeolus mission is the first system to demonstrate direct measurement of vertically resolved wind profiles from space. While international studies are already demonstrating the positive impact of Aeolus lidar observations on weather forecasts, the ALADIN mission life is limited to a maximum of three years. The same year as the Aeolus launch, the NOAA Satellite Observing System Architecture (NSOSA) study listed 3D-Winds as one of the top observational objectives for future weather architectures and the National Academies Earth Science Decadal Survey (ESDS) listed Atmospheric Winds as one of the top targeted observables. The Optical Autocovariance Wind Lidar (OAWL) approach developed at Ball Aerospace, with funding support from NASA, provides a validated, high-TRL, and reduced-risk U.S. option for an Aeolus follow-on. This seminar will discuss the characteristics of Doppler wind lidar observations, compare wind lidar to other wind-observing methods used in numerical weather prediction, describe what the OAWL approach offers relative to Aeolus, and provide a roadmap for achieving a U.S. space-based wind lidar as part of a future operational weather architecture.
Bio(s): Sara Tucker is technical lead of Operational Weather in Civil Space and Technologies at Ball Aerospace where she focuses on development of advanced remote-sensing techniques and system architectures to meet next-generation operational weather requirements and Earth science objectives. She also serves as the Principal Investigator for the Optical Autocovariance Wind Lidar (OAWL) system. At Ball, and previously at NOAA/CIRES, Sara has managed Doppler lidar development and participation in several ground, ship- and aircraft-based field campaigns to study atmospheric winds. She has written and contributed to publications on Doppler lidar instrument and data product development, planetary boundary layer dynamics, cloud processes, and dust/pollution transport and mixing processes. Sara graduated from the University of Colorado with M.S. and Ph.D. in Electrical Engineering with a focus on digital signal processing and optics.
Imme Ebert-Uphoff, CIRA and Christina Kumler, CIRES
Date & Time:
18 July 2019
11:30 am - 12:30 pm ET
Location:
Conference Room # 2552-2553, NOAA Center for Weather and Climate Prediction, 5830 University Research Court, College Park, MD, NCWCP - Large Conf Rm - 2552-2553
Abstract: Machine learning is becoming more and more accessible to the scientific community, with high performance computing capabilities, data collection, and increasing availability of free and highly efficient software packages. Part 1 of this talk discusses the great potential as well as some challenges of using machine learning for climate and weather applications. Challenges include the perceived lack of transparency and the potential for incorrect generalization of these methods. We then discuss strategies for overcoming these challenges, including i) leveraging physics in the AI approach and ii) utilizing visualization tools to help understand the reasoning of these algorithms. Part 2 then discusses machine learning projects that are currently ongoing within NOAA ESRL's Global System Division (GSD). GSD has several active projects applying different methods of ML to satellite data that will be covered briefly in this talk. One project in particular, a Regions of Interest (ROI) project that uses deep learning to detect cyclonic ROI from water vapor satellite data, will be highlighted at the end.
Bio(s): Imme Ebert-Uphoff received B.S. and M.S. degrees in Mathematics from the Technical University of Karlsruhe (known today as Karlsruhe Institute of Technology or KIT). She received M.S and Ph.D. degrees in Mechanical Engineering from the Johns Hopkins University. She was a faculty member in Mechanical Engineering at Georgia Tech for over 10 years, before joining the Electrical & Computer Engineering department at Colorado State in 2011 as research professor. Her research interests are in applying data science methods to climate applications. She is also very involved in activities to build bridges between the AI community and the earth science community, including serving on the steering committee of the annual Climate Informatics workshop, and of the NSF sponsored research coordination network (RCN) on Intelligent Systems for the Geosciences. Starting July 1, 2019, she is spending 50% of her time with CIRA to support their machine learning activities.
Christina Kumler comes from an applied mathematics, meteorology, and oceanic science background. She completed her B.S. degree at CU Boulder in applied mathematics in 2013 and then completed her M.S. at University of Miami Florida RSMAS in meteorology and physical oceanography in 2015. She is currently a CIRES scientist and specializes in computational aspects of weather modeling. Over the last two years, her time has been dedicated to applying machine learning techniques to big data problems in the field of weather and climate. In her spare time, she races triathlons, hikes, does semi-professional photography, and loves to cook/bake/eat with friends, family, husband, and dog.
Presenter(s): Ralph Ferraro, Branch Chief, Satellite Climate Studies Branch, NOAA
Sponsor(s): Virtual Alaska Weather Symposium. Alaska Center for Climate Assessment and Policy (ACCAP) and NOAA CPO RISA Program
Abstract: Passive microwave sensors on low earth orbiting satellites have the ability to monitor several parameters associated with the Earth's hydrological cycle - falling precipitation, snow and ice parameters, soil moisture, etc. These observations are particularly useful for high latitude locations where geostationary satellites have limited coverage. In this presentation, a review of the methodology used to retrieve this information will be given, then followed by several practical applications for weather forecasting and climate monitoring. Available in-person at: Room 407 in the Akasofu Building on the UAF Campus in Fairbanks
Conference Room # 2552-2553, NOAA Center for Weather and Climate Prediction, 5830 University Research Court, College Park, MD, NCWCP - Large Conf Rm - 2552-2553
The MetNet Alliance is currently developing a network of LEO small weather satellite constellations including imagers, upper atmosphere dynamics, microwave, space weather, and Hyperspectral IR Sounding. These small satellites shall provide key commercial weather data to NOAA, Department of Defense agencies, and weather analytics companies. For MetNet, Hyperspectral Infrared Sounding has been identified as one of the top observations needed for improving weather forecasts by providing temperature profiles, moisture profiles, and atmospheric motion vector (AMV) 3D winds. Brandywine's proposed solution is to provide global, high-resolution, hyperspectral infrared (LWIR) sounding data through a constellation of 24-36 small LEO satellites using modified commercial interferometers. A Small Business Innovation Research Phase I contract has been funded by Air Force Research Labs to evaluate the customer interest in CHISI to fill in key gaps in Defense global weather models. This talk will discuss the advantage of small satellites, more recent enabling technologies, and the roadmap to an observational infrared sounding capability.
KEYWORDS: Infrared Sounding, Longwave Infrared, Atmospheric Motion Vectors, 3D Winds, Temperature Sounding, Moisture Sounding, Commercial Data Pilot Program.
Bio(s): John Fisher is the President and CTO for Brandywine Photonics, whose mission is to Save Lives and Homes through Better Weather Data. After working as an optical engineer at the U.S. Naval Research Labs, John founded Brandywine Photonics in 1999 to build his own airborne sensors. His work in oceanography culminated in the delivery of the Hyperspectral Instrument for Coastal Observing (HICO) spectrometer, which operated on the International Space Station from 2010-2015. In 2015, John transitioned Brandywine Photonics to weather satellite payload development, with currently three payloads in early stage development, and one funded for launch in late 2020. John is the Co-Founder of the MetNet Alliance which teams with other payload and data analytics companies in developing lower-cost, higher performance, small weather satellites. He graduated from Penn State with a BS and MS in Electrical Engineering in 1986 and 1987 respectively, with a specialization in optics. John lives in Exton, Pennsylvania with his wife and family, and enjoys camping with his two sons in the Cub Scouts and watching his daughter's ballet recitals.
OneNOAA Science Seminar Series cross-listed to the STAR Seminar Series
Presenter(s):
Tim Schmit, Research Satellite Meteorologist NOAA NESDIS STAR at the University of Wisconsin
Seminar
Sponsor(s):
Alaska Center for Climate Assessment and Policy (ACCAP) and NOAA CPO RISA Program
Abstract: There have been many recent changes to better observe Alaska from the Geostationary Operational Environmental Satellite (GOES) perspective. The most significant change was on February 12, 2019 when GOES-17 became NOAA's operational West geostationary satellite. The Advanced Baseline Imager (ABI) has spectral bands covering the visible, near-infrared and infrared portions of the electro-magnetic spectrum. The ABI represents a major improvement from the legacy GOES imagers for many attributes, such as those relating to: spectral, spatial, temporal, radiometric, and image navigation/registration. An on-board cooling issue associated with the Loop Heat Pipe on GOES-17 causes degradation for certain periods of the year, at certain times, mostly at night. The affected spectral bands are those with wavelengths greater than 4 micrometers with effects that start with biasing, striping, banding, and ultimately complete saturation for the most affected bands. In order to mitigate the impacts of this issue, improvements to the calibration procedures are improving the image quality before and after saturation occurs. These improvements include a modification to the ABI timeline in the 10-min Full Disk flex mode, predictive calibration, and other changes. Once a spectral band is saturated, there is little that can be done to better calibrate the data. The current status of Level 2 or derived products, such as cloud heights or atmospheric motion vectors, from the GOES-17 ABI will also be covered.
Available in-person at: Room 407 in the Akasofu Building on the UAF Campus in Fairbanks, Alaska
Mark Brusberg, Eric Luebehusen and Harlan Shannon, USDA
Date & Time:
15 May 2019
10:00 am - 11:00 am ET
Location:
Conference Room # 2552-2553, NOAA Center for Weather and Climate Prediction, 5830 University Research Court, College Park, MD, NCWCP - Large Conf Rm - 2552-2553
Abstract: The Vegetative Health Index (VHI), derived from the new generation of NOAA polar-orbiting satellites, is being used operationally by USDA as a method of depicting the vigor of crops on a global scale. Following years of successful collaboration between the developers of the product and experts on international crop production and weather, the VHI has become an integral analytical tool used in preparation of the World Agricultural Supply and Demand Estimates Report, a monthly estimate of global crop production and key economic indicator. Meteorologists from USDA's Office of the Chief Economist will be on hand to show examples of their work and answer questions regarding future directions of the partnership that has produced this important tool.
Conference Room # 2552-2553, NOAA Center for Weather and Climate Prediction, 5830 University Research Court, College Park, MD, NCWCP - Large Conf Rm - 2552-2553
Abstract: The 2017-2027 Decadal Survey for Earth Science and Applications from Space identifies six Science & Applications Topic, two of which are Extending & Improving Weather and Air Quality Forecasts and Reducing Climate Uncertainty & Informing Societal Response. NASA Jet Propulsion Laboratory (JPL) has been developing the Panchromatic imaging Fourier Transform Spectrometer (PanFTS) to address different atmospheric measurements related to these two applications. PanFTS is envisioned as a hosted payload on a geostationary (GEO) communication satellite. This offers the access to GEO with a fee, vs the costs associated with a dedicated launch vehicle and spacecraft. In parallel, the NOAA Satellite Observing System Architecture Study (NSOSA) report calls for a small number of GEO hosted instruments.
Similar to CrIS, PanFTS is a Fourier transform spectrometer (FTS). CrIS is a point mapping spectrometer. It has three different spectral bands of 3 x 3 photo detectors, mapping 9 ground pixels simultaneously. PanFTS is an imaging spectrometer. It has 1 - 3 imaging cameras, mapping 0.3 - 1 million ground pixels simultaneously. The several orders of improved observation throughput is enabled by the high speed cameras and the matching high speed onboard data processing electronics. PanFTS successfully completed a NASA Earth Science Technology Office Instrument Incubator Program (ESTO IIP) task in 2011. An engineering model (EM) was built. PanFTS - EM spanned 0.29 - 16 um wavelength, and it could achieve a spectral resolution DeltaR = 0.05 cm-1. PanFTS - EM performances were characterized in a thermal vacuum chamber at 110K, and the results were independently reviewed. However, PanFTS - EM occupied a ~1.5 m3 volume. We propose to miniaturize PanFTS (uPanFTS) into a ~6 - 12 U volume using a 2-color camera technology. This camera technology has been developed by the DOD sponsors over the last two decades, and it is currently deployed in the fields.
Bio(s): Mr. Yen-Hung (James) Wu is an optical system engineer at the NASA Jet Propulsion Laboratory. He has worked on a variety of NASA and non-NASA projects, ranging from a cubsat imager to a deep UV spectrometer on the Mars 2020 Rover to a laser metrology for the NuSTAR x-ray space telescope. He has been working with the team to develop PanFTS since its conception in 2007. Currently, he is leading two JPL internally funded strategic R&D tasks to 1). miniaturize the front end PanFTS instrument hardware suitable for the future solar system and planetary exploration missions, and 2). advance the PanFTS back end data interface / real-time processing to the operational science quality.
D. Masters, Spire Global, Inc, United States Co-authors V. Nguyen (Spire Global, Inc, US), T. Yuasa (Spire Global Singapore PTE Ltd), O. Nogus-Correig (Spire Global UK Ltd), L. Tan (Spire Global Singapore PTE Ltd), S. Esterhuizen (Spire Global Luxembourg S.a.r.l.), P. Jales (Spire Global UK Ltd), T. Duly (Spire Global, Inc, US), V. Irisov (Spire Global, Inc US), J. Cappaert (Spire Global UK Ltd), J. Spark (Spire Global UK Ltd)
Sponsor(s): LSA Science Seminar Series
Audio: +1 314-925-1794 PIN: 186 986#
Abstract: Spire Global, Inc. operates a large and rapidly growing constellation of CubeSats performing GNSS-based science and Earth observation. In a few short years, Spire has grown from a modest CubeSat kickstarter campaign to a paradigm-shifting provider of satellite data to NOAA, NASA, and other customers of Earth observations. Spire specializes in using science-quality observations of GNSS signals (e.g., GPS, GLONASS, Galileo, QZSS, etc.) to derive valuable information about the Earth environment. Currently, these observations include radio occultations to profile the neutral atmosphere with high accuracy and vertical resolution for applications such as NWP assimilation and climate monitoring, as well as ionosphere slant total electron content and scintillation indices for space weather applications. Currently, the Spire constellation consists of 76, 3U CubeSats, with many of these satellites performing GNSS science and with plans to grow the GNSS-enabled constellation to over 100 satellites. Beginning in 2018, Spire began an accelerated effort to add the capability to perform GNSS bistatic radar (reflectometry or GNSS-R) for Earth surface observations targeting a variety of applications, including soil moisture, wetlands and flood inundation mapping, sea surface roughness and winds, and sea ice characterization. This effort has two parallel paths: 1) build dedicated GNSS-R CubeSats to perform operational scatterometry (akin to the NASA CYGNSS mission), with the first satellites to be launched later in 2019, and 2) already harnessing existing orbiting Spire satellites used for radio occultation to additionally perform grazing angle GNSS-R measurements and to test the concept of phase-delay altimetry.
This presentation will introduce the Spire constellation of CubeSats for GNSS-enabled Earth observation and will focus on the unique experience of adapting the current constellation of radio occultation satellites to perform new and potentially valuable GNSS-R Earth observations. We will introduce the concept of phase-delay altimetry and its potential to estimate surface heights on the order of 10 cm using observations of coherent GNSS signals reflected from various Earth surfaces. We will summarize the agile steps Spire took to collect these observations on-orbit within just a couple of months of conceptualization, as well as the initial inversion technique to estimate surface reflector heights with high precision. We will show some promising initial results of estimating sea surface height and sea ice draft using this technique and discuss plans for further investigation and calibration/validation activities. Finally, we will discuss Spire's potential to rapidly proceed with these measurements from research to operations and to make them available as a new set of Earth observations. Screen reader support enabled.
Bio(s): Dr. Dallas Masters has been active in the field of remote sensing since helping to develop the first all-composite satellite, FORTE, at the Los Alamos National Laboratory in 1995, followed by a doctorate in Aerospace Engineering Sciences from the University of Colorado in 2004. Dr. Masters joined Spire Global, Inc. in January of 2018, to lead the development of a GNSS passive bistatic radar mission based on Spire's existing GNSS science receiver and 3U CubeSat bus. He recently merged the existing GNSS radio occultation and bistatic radar remote sensing programs and now directs Spire's single GNSS science program. His teams develop all aspects of Spire's GNSS payload instruments and science processing systems for various applications ranging from atmospheric profiling and ionosphere monitoring via radio occultation to ocean wind and soil moisture mapping via passive bistatic radar. Prior to joining Spire, Dr. Masters was involved in a number of NASA remote sensing and Earth science projects, first at the National Center for Atmospheric Research in Boulder, and later at the Colorado Center for Astrodynamics at the University of Colorado. Dr. Masters has worked in many areas of satellite remote sensing, with emphasis on the science and applications of GNSS bistatic radar and both conventional and SAR altimetry. He has participated in a number of NASA science teams, including the Ocean Surface Topography Science Team, Sea Level Change Team, CYGNSS Science Team, and the SWOT Science Definition Team.
STAR Science Seminars cross posted for ESSIC Seminars
Presenter(s): Dr. Thomas Neumman, NASA Goddard Flight Space Center
Sponsor(s): ESSIC Seminars
Slides, Recordings Other Materials:
Abstract:
The Ice, Cloud, and land Elevation Satellite -- 2 (ICESat-2) observatory was launched on 15 September 2018 to measure ice sheet and glacier elevation change, sea ice freeboard, and enable the determination of the heights of Earth's forests. ICESat-2 current orbit inclination allows data collection between 88 degrees north latitude and 88 degrees south latitude from nominally 500km elevation above Earth's surface. ICESat-2's laser altimeter, the Advanced Topographic Laser Altimetry System (ATLAS) uses green (532 nm) laser light and single-photon sensitive detection to measure elevation along each of its six beams ten thousand times per second. In this presentation, I describe the major components of the observatory and the ATLAS instrument. I summarize the first six months of on orbit data collection and present the status of the observatory and the ATLAS instrument. I'll present on the status of the lower-level data products including the Level-2A data product (ATL03), which provides the geodetic location (i.e. the latitude, longitude and elevation) of the ground bounce point of photons detected by ATLAS. The ATL03 data product is the primary product used for higher-level (Level 3A) surface-specific data products such as glacier and ice sheet elevation, sea ice freeboard, vegetation canopy height, ocean surface topography, and inland water body elevation. This presentation will also present the plans for future data collection, the geolocation uncertainty of the ATL03 global geolocated photon data product, the status of data product availability, and plans for data reprocessing.
Bio(s): Tom Neumann is a cryospheric scientist who focuses on the development of ICESat-2, the next-generation laser altimeter scheduled for launch in 2018. His research includes both theoretical and experimental studies of the chemical, physical, and thermodynamic properties of polar snow and ice. He has been involved extensively in field work on the Greenland and Antarctic ice sheets, leading four expeditions and participating in five others between the two poles. Recent work has involved studies of snow chemistry on the East Antarctic plateau and calibrating ICESat altimetry data using ground-based GPS surveys in Antarctica.
Tom joined NASA Goddard Space Flight Center in October 2008. Prior to that, he was an assistant professor in the Geology Department at the University of Vermont. He remains an Affiliate Assistant Professor in Earth and Space Sciences at the University of Washington. He earned a B.A. in geophysical science from the University of Chicago, and a Ph.D. in geophysics from the University of Washington.
Presenter(s): Michael Ondrusek, Eric Stengel, and Charles Kovach, SOCD
Sponsor(s): STAR Science Seminar Series NOAA Ocean Color Coordinating Group Seminar
Abstract: In situ validation of ocean color satellite products is critical in determining the accuracy and reliability of the distributed products. NOAA STAR has been conducting ocean color validation measurements in all types of waters for over 25 years working with international, government and academic partners. With the operation of NPP and NOAA20 VIIRS satellites, the validation work has expanded to include annual dedicated validation cruises aboard NOAA research vessels with the goal of providing the best validation for VIIRS, determining the uncertainties for the in situ/satellite matchups, and characterizing natural optical variability in the ocean. This presentation will highlight recent calibration/validation activities, discuss identified in situ measurement uncertainties and evaluate VIIRS performance.
Bio(s): Michael Ondrusek is an Oceanographer for the NOAA Center for Satellite Applications and Research (STAR) He served as the Division Ocean Color Science Team Lead and the Ocean Color Product Oversight Panel Co-Chair from 2006 to 2011 and the Marine Optical Buoy PI from 2007 to 2010. His research interest includes ocean color calibration and validation, satellite ocean color product algorithm development, primary productivity, phytoplankton pigments, and phytoplankton ecology. He has extensive sea-going experience including the MOBY/MOCE projects, the IronEx experiments, and the JGOF programs. He has served as Chief Scientist on four annual NOAA dedicated Cal/Val cruises since FY2015.
Conference Room # 2552-2553, NOAA Center for Weather and Climate Prediction, 5830 University Research Court, College Park, MD, NCWCP - Large Conf Rm - 2552-2553
As part of the EUMETSAT-NOAA Initial Joint Polar System EUMETSAT operates today three EUMETSAT Polar System (EPS) Metop satellites. The last satellite, Metop-C, was only launched in November 2018, whereas the first satellite, Metop-A, has now been in orbit for more than 12 years. Whilst Metop-A is now slowly drifting out its nominal orbit is still allows EUMETSAT to operate three satellites in the morning orbit until 2021, providing unique opportunities for deriving multi-satellite data and assessing their impact on global NWP. The second back-bone of the EUMETSAT meteorological satellite fleet is the Meteosat Second Generation system, today a constellation of four geostationary satellites. These satellites provide full-disc service over the European/African/Atlantic region, rapid scan data over Europe and full disk coverage over the Indian Ocean. Both of the aforementioned systems will be continued with next generation satellites throught the EPS-Second Generation (EPS-SG) and Meteosat Third Generation Programmes. Both systems consist of six satellites, EPS-SG by three sets of two platforms for imaging, sounding and microwave observations, MTG by four imaging platforms including lightning observations and two sounding platforms. In addition to the meteorological satellite systems EUMETSAT operates and provides data services for oceanography and marine meteorology through the Jason altimetry missions and the Copernicus Sentinel-3 satellites, with the latter also providing observations for SST and ocean colour. The EUMETSAT data and products services, which also include reprocessing activities supporting climate services, are provided through a distributed network including Satellite Application Facilities. This presentation will give an overview of these satellite systems, their products and current impact on various application areas.
Bio(s): Dr. Kenneth Holmlund is the Chief Scientist at EUMETSAT.
Xiaolei Zou - Earth System Science Interdisciplinary Center, University of Maryland
Date & Time:
4 April 2019
12:00 pm - 1:00 pm ET
Location:
Conference Room # 2552-2553, NOAA Center for Weather and Climate Prediction, 5830 University Research Court, College Park, MD, NCWCP - Large Conf Rm - 2552-2553
Abstract: The Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC-2) has more powerful GPS receiver antennas, a twice higher sampling rate of 100 Hz, and a three times smaller inclination of 24o than those of COSMIC-1. COSMIC-2 will, therefore, provide an unprecedented ample number of radio occultation (RO) data in the tropics. Assimilation of RO data in the tropics is challenging due to unique features such as large horizontal gradients of refractivity, spherical asymmetry, and impact multipath in the moist tropical lower troposphere. In this talk, I'll first show occurrences of multipath in the tropical lower troposphere using the National Centers for Environmental Prediction/Global Forecast System analysis as input to a 2D raytracing operator for COSMIC ROs in March and April 2017. An up to 600-m lift in the impact parameter is observed for simulated RO rays in the presence of a strong horizontal gradient of refractivity over 250-km distances from the perigee, rendering the simulation bending angles multivalued functions of impact parameter. An impact multipath quality control (QC) procedure is developed to effectively identify the multipath simulations. Second, the accuracy and precision of a two-dimensional (2D) limited-ray-path raytracing operator is tested against the 2D raytracing operator that simulates global ray paths. Finally, bending angle data assimilation in the tropical lower troposphere is done using the 2D limited-ray-path raytracing operator and a one-dimensional (1D) Abel transform operator. The impact multipath QC is incorporated to eliminate occurrences of impact multipath in bending angle simulations. The fractional differences in bending angle simulations between the limited-path-length raytracing operators and the original 2D raytracing operator have zero bias, and their standard deviations are more than three times smaller than those between the 1D Abel transform operator and the 2D raytracing operator. The highest accuracy and precision are achieved for the 2D limited-ray-path raytracing operator if the ray path is confined within 400 km. Use of the physically based impact multipath QC is shown to improve COSMIC data assimilation and forecast results using either the 1D Abel transform or the 2D limited-ray-path observation operators of bending angle in the tropical lower troposphere.
Bio(s): Dr. Xiaolei Zou received a PhD in Meteorology is a research professor at ESSIC at University of Maryland.
Presenter(s): Dr. Cheng-Zhi Zou, NOAA/NESDIS/Center for Satellite Applications and Research
Sponsor(s): ESSIC Seminar Series, crosslisted with the STAR Science Seminar Series
For IT assistance ------------------------------------------------------- Contact Travis Swaim at: tswaim1@umd.edu
Abstract: Global warming theory predicts increasing surface and tropospheric temperatures and decreasing stratospheric temperatures when anthropogenic atmospheric carbon dioxide concentration and other greenhouse gases increase. Satellite-borne sensors are the only means available for providing global temperature observations in the atmosphere for climate trend monitoring and verifying the global warming theory. During the past two decades, scientists have been developing atmospheric temperature climate data records (CDRs) using satellite observations from the Microwave Sounding Unit (MSU), Advanced Microwave Sounding Unit- A (AMSU-A), and Stratospheric Sounding Unit (SSU) onboard NOAA/NASA/MetOp historical and currently operational polar-orbiting satellites. These CDRs allow scientists to study the size, significance, and causes of the global atmospheric temperature trends and variability, to evaluate climate model performance, to assess the consistency between observed surface and tropospheric temperature changes, and to investigate the impact of ozone depletion and recovery on the stratospheric temperature changes. Overall, atmospheric temperature CDRs provided improved understanding on the anthropogenic impact on climate change.
Changes in diurnal sampling over time and calibration drift have been the main sources of uncertainties in the satellite measured temperature trends. We have recently examined observations from the Advanced Technology Microwave Sounder (ATMS) that has been flying onboard the NOAA/NASA Suomi National Polar-orbiting Partnership (SNPP) environmental satellite since late 2011. The SNPP satellite has a stable afternoon orbit that has close to the same local observation time as NASA's Aqua satellite that has been carrying the heritage microwave sounder, the AMSU-A, from 2002 until the present. The similar overpass timing naturally removes most of their diurnal differences. Direct comparison of temperature anomalies between the two instruments shows little or no relative calibration drift for most channels. Our results suggest that both ATMS and AMSU-A instruments have achieved absolute stability in the measured atmospheric temperatures within 0.04 Kelvin per decade.
The high radiometric stability in the SNPP/ATMS and Aqua/AMSU-A observations could have broad implication and impact on the climate trend observations from the microwave sounders as well as other instruments. It provides an opportunity for using these instruments as references to calibrate and recalibrate other observations and help resolve debates on observed differences in the climate trends. In this talk, we review the status of the currently available atmospheric temperature CDRs in climate change detection and present detailed analyses of the radiometric stability in the SNPP/ATMS and Aqua/AMSU-A observations. We discuss why and how these instrument observations could be used as references for improving the accuracy of CDRs in climate change monitoring. We present examples in using these reference observations to recalibrate microwave sounders onboard other satellites and provide a perspective on future applications of such a concept.
About the speaker: Cheng-Zhi Zou is a Physical Scientist at the NOAA/Center for Satellite Applications and Research (STAR) located in College Park, Maryland. Dr. Zou received his PhD from the University of Oklahoma in 1995 and worked in NOAA/STAR since 1997. He has been mainly engaged in measuring long-term changes in the atmospheric temperatures using satellite observations and evaluation of data products for climate change studies from different sources including those from satellite retrievals, climate reanalyses, and climate model simulations. He has developed a set of atmospheric temperature climate data records capable of detecting climate trends from the lower troposphere to the upper stratosphere during the satellite era. He conducted satellite retrievals to derive climate products such as polar winds. He also collaborated with colleagues on using mesoscale models to simulate and analyze a variety of atmospheric clouds and costal wave phenomena observed by satellites. He has published over 50 articles in AMS, AGU, and other leading journals including Nature, Science, and PNAS. He has received Department of Commerce Silver Medal Award and NOAA Administrator's Award for advancement of satellite calibration and development of atmospheric temperature climate data records. He is a referred reviewer for many journals in the atmospheric science field.
Seminar POC: Dr. John Yang ESSIC Seminar Coordinator University of Maryland 5825 University Research Court, College Park, MD 20740-3823 Email: jxyang@umd.edu Tel: 301-405-2819 Fax:301-405-8468
STAR Science Seminars with SOCD / NOAA Ocean Color Coordinating Group
Presenter(s): Dr. Sheekela Baker-Yeboah - University of Maryland, ESSIC & CICS
Sponsor(s):
SOCD / NOAA Ocean Color Coordinating Group The NOCCG is a NOAA organization founded in 2011 by Dr. Paul DiGiacomo, Chief of the Satellite Oceanography and Climatology Division at NOAA/NESDIS/STAR. The purpose of the NOCCG is to keep members up to date about developments in the field of satellite ocean color and connect ocean color science development with users and applications. We have representatives from all the NOAA line offices, including National Marine Fisheries Service, Office of Oceanic and Atmospheric Research, National Ocean Service, National Weather Service and from several levels of the National Environmental and Satellite Data and Information Service (where Paul is housed). Dr. Cara Wilson of South East Fisheries Science Center is our current chair. We meet bi-weekly on Wednesday afternoons, 3 PM Eastern Time in room 3555 at the National Center for Weather and Climate Prediction building in College Park, MD with teleconferencing and Webex for out of town members and guests. We host a guest speaker, usually about once a month.
Abstract:
Using the strong correlation between altimeter and in situ pressure sensor-equipped inverted echo sounder (PIES) data, an analysis is done using current altimeter data in conjunction with Visible Infrared Imaging Radiometer Suite Ocean Color and Sea Surface Temperature data to gain further insight into the physical and biological implications of mesoscale eddies associated with rings off of South Africa. A comparison is done with the California Current system, another major upwelling regime in the World Ocean, to assess the the relationship of slope eddies in upwelling regions to open ocean eddy signatures.
Bio(s):
Dr. Sheekela Baker-Yeboah is a Physical Oceanographer/Research Scientist at the University of Maryland (ESSIC & CICS), currently doing research and product development using Ocean Color, Altimetry, and Sea Surface Temperature data in collaboration with Paul DiGiacomo of Satellite, Oceanography and Climate Division (SOCD) and previously held the position of Satellite Team Lead at NOAA/NESDIS/NCEI in collaboration with the University of Maryland. She received her Ph. D. in Oceanography from the University of Rhode Island then Post Doctoral training at the Massachusetts Institute of Technology (MIT). Her professional appointments include Research Scientist at MIT, a visiting Professor at Worcester Polytechnic Institute of Massachusetts, and visiting Professor at Lesley University of Cambridge, Massachusetts. Her background experiences include training in Remote Sensing Oceanographer (satellite data processing and analysis using SAR, AVHRR SST, Altimeter SSH, Ocean Color/SeaWifs), as well as seagoing, teaching, modeling, and laboratory experience. She has worked with in situ oceanographic data (with training in statistics, ship CTD, oxygen titration, ADCP and XBT data, data analysis, training in and consulting on field research techniques for Pressure Inverted Echo Sounders, and recently Ocean Color in situ data. Dr. Baker-Yeboah has ongoing collaborations (1) with the SOCD Altimeter Sea Surface Height Laboratory, (2) as Co-PI on NSF Arctic Data Center Project, and (3) international collaborations (France, South Africa, Germany, Russia, and the US) on the South Atlantic Meridional Overturning Circulation (SAMOC) program in the South Atlantic.
Conference Room # 2554-2555, NOAA Center for Weather and Climate Prediction, 5830 University Research Court, College Park, MD, NCWCP - Large Conf Rm - 2554-2555
Presenter(s): Chris Barnet (STC) with Co-Authors: Thomas S. Pagano, NASA Jet Propulsion Lab., Sid Boukabara (STAR), Kevin Garrett (STAR), Kayo Ide (Univ. Maryland), Erin Jones (UMD), Yingtao Ma (UMD), Nadia Smith (STC), Rebekah Esmaili (STC)
Sponsor(s): STAR Science Seminar Series
Audio: USA participants: 866-832-9297 Passcode: 6070416
Abstract: Advanced hyperspectral sounders such as the Advanced Infrared Sounder (AIRS), Interferometric Atmospheric Infrared Sounder (IASI) and the Cross-track Infrared Sounder (CrIS) all invested heavily in providing high signal-to-noise measurements in the short-wave infrared (SWIR) spectral region (defined here as from 3.8 to 5 microns).
The use of this spectral region is complicated by the need to handle solar radiation that is both reflected from the surface and also excites molecules in the upper stratosphere and lower mesosphere into non-equilibrium emission. The AIRS Science Team demonstrated how to properly use the SWIR to derive high-quality temperature, moisture, and trace gases with the launch of Aqua/AIRS in 2002. The NOAA-Unique Combined Atmospheric Processing System (NUCAPS) operationally deployed the AIRS algorithm for the Metop-A/IASI, S-NPP/CrIS, Metop-B/IASI, and the NOAA-20/CrIS instruments since 2008, 2011, 2012, and 2018, respectively.
This presentation will focus on the lessons learned from the NUCAPS experience and discuss the advantages, and disadvantages, of using SWIR channels. The high sensitivity (at higher operating temperatures) and uniformity of detector arrays could enable lower cost and more compact concepts to be deployed in low-Earth and geostationary orbits. This has led to the following question: could the SWIR channels replace the long-wave channels currently used within numerical weather prediction? This presentation will conclude with a discussion of an experiment to help answer that question.
Bio(s):
Chris Barnet's early career was a random walk kind of process which allowed him to be involved with many interesting topics that required finding a practical solution to the problem of the day. He started as a welder at Fermilab - an accelerator for protons - and that led to working with waveguides, superconductors, holography, radio telescopes, quasi-stellar objects, array processors, observing and modeling of the outer planets, and finally Earth remote sounding. This mixture of engineering and science may be the reason why he is now interested in finding ways to transition new algorithm concepts into operational applications.
Conference Room # 2552-2553, NOAA Center for Weather and Climate Prediction, 5830 University Research Court, College Park, MD, NCWCP - Large Conf Rm - 2552-2553
Abstract: Multi-temporal imagery from a single geostationary (GEO) satellite such as NOAA's Geostationary Operational Environmental Satellite (GOES) are routinely used to derive Atmospheric Motion Vectors (AMVs) that represent winds in the atmosphere. The AMV method generally assumes that the cloud or moisture feature being tracked is undergoing horizontal motion that is observed by the displacement of the feature in a sequence of images. Observations from a single vantage point provide no geometric information about the height of an AMV in the atmosphere; therefore, AMV heights are generally assigned using IR temperatures and an a priori model atmosphere. Such height assignments can have large uncertainties and are error prone in the presence of multiple cloud layers. Multi-angle, multi-satellite stereo imaging is a powerful tool for observing atmospheric dynamics in three dimensions. When a tracked feature is viewed from multiple vantage points, additional information in the form of geometric parallax enables accurate determination of feature height and even the possibility of measuring vertical motion. This talk describes our work in this area using LEO-GEO combinations under NASA sponsorship and GEO-GEO combinations under NOAA sponsorship, and includes results combining imagery from the GOES-R satellites paired with each other and paired with imagery from the Multi-angle Imaging SpectroRadiometer (MISR) instrument on NASA's Terra spacecraft. The advanced Image Navigation and Registration (INR) of GOES-R is the key to very accurate coupled retrievals of wind velocities and wind heights. We show that adding GOES-R improves AMV measurements from a single LEO (e.g., MISR), for which separating in-track cloud motion and height-induced parallax is difficult. Our methods are generally applicable to all LEO-GEO, LEO-LEO, and GEO-GEO combinations, including combinations with GOES, Meteosat, Himawari, MODIS, VIIRS, and others, and requires no synchronization between observing systems. Wind retrievals using these methods should play an important role in addressing the 2017 Earth Science Decadal Survey objectives to observe 3D atmospheric dynamics as well as for improving NOAA operational capabilities with existing and future assets.
Bio(s):
Dr. Carr is the founder and CEO of Carr Astronautics, a science and technology firm working in the NASA, NOAA, and international space arenas, with an emphasis on atmospheric remote sensing. Dr. Carr functions as both a scientist and a senior executive and strives to spend at least 50% of his time as a scientific leader on the programs within his company's business portfolio. Dr. Carr enjoys building mathematical models of complex systems and finding innovative and entrepreneurial solutions to complex problems. Dr. Carr earned a Ph.D. in Physics from the University of Maryland in 1989. Dr. Carr founded his company in 1991 to help design the European Meteosat Second Generation (MSG) weather satellite, during which he resided in France for five years with his family. After returning to the U.S., he became a leader in the development of the GOES-NOP and GOES-R weather satellite systems. Dr. Carr is a Co-Investigator on the NASA TEMPO mission, which is a hosted payload for remote sensing of the atmosphere from geostationary orbit. TEMPO will retrieve trace gas concentrations for O3, NO2, H2CO, SO2, and C2H2O2 species, hourly across Greater North America, at fine spatial resolution, to enable the study of the sources, sinks, and propagation of atmospheric pollutants. Dr. Carr is the lead investigator on two 3D Winds projects, one funded by NASA and the other by NOAA, exploiting observations from multiple satellites to resolve cloud-motion winds in 3D. POC: Stacy Bunin, stacy.bunin@noaa.gov
STAR Science Seminars with SOCD / NOAA Ocean Color Coordinating Group
Presenter(s): Dr. Chuanmin Hu - University of South Florida College of Marine Science, St. Petersburg, FL, USA
Sponsor(s):
SOCD / NOAA Ocean Color Coordinating Group The NOCCG is a NOAA organization founded in 2011 by Dr. Paul DiGiacomo, Chief of the Satellite Oceanography and Climatology Division at NOAA/NESDIS/STAR. The purpose of the NOCCG is to keep members up to date about developments in the field of satellite ocean color and connect ocean color science development with users and applications. We have representatives from all the NOAA line offices, including National Marine Fisheries Service, Office of Oceanic and Atmospheric Research, National Ocean Service, National Weather Service and from several levels of the National Environmental and Satellite Data and Information Service (where Paul is housed). Dr. Cara Wilson of South East Fisheries Science Center is our current chair. We meet bi-weekly on Wednesday afternoons, 3 PM Eastern Time in room 3555 at the National Center for Weather and Climate Prediction building in College Park, MD with teleconferencing and Webex for out of town members and guests. We host a guest speaker, usually about once a month.
Abstract:
To be provided.
Bio(s):
Chuanmin Hu received a BS degree in physics from the University of Science and Technology of China in 1989 and a PhD degree in physics (environmental optics) from the University of Miami (Florida, USA) in 1997. He is currently a professor of optical oceanography at the University of South Florida (USA), who also directs the Optical Oceanography Lab[HC1] . He uses laboratory, field, and remote sensing techniques to study marine algal blooms (harmful and non-harmful, macroalgae and microalgae), oil spills, coastal and inland water quality, and global changes. His expertise is in the development of remote sensing algorithms and data products as well as application of these data products to address earth science questions. He has authored and co-authored >250 refereed articles, many of which have been highlighted on journal covers and by AGU and NASA. His research has led to the establishment of a Virtual Antenna System to generate and distribute customized data products in near real-time, from which unique coastal observing systems have been developed to address specific monitoring and research needs. These include a Virtual Buoy System (VBS[HC2] ) to monitor coastal and estuarine water quality, an Integrated Redtide Information System (IRIS[HC3] ) to provide near real-time information on harmful algal blooms, and a Sargassum Watch System (SaWS[HC4] ) to combine remote sensing and numerical modeling to track macroalgae. Between 2009 and 2014 he served as a topical editor on ocean optics and ocean color remote sensing at Applied Optics, and between 2015 and 2017 he served as a chief editor at Remote Sensing of Environment.
Conference Room # 2552-2553, NOAA Center for Weather and Climate Prediction, 5830 University Research Court, College Park, MD, NCWCP - Large Conf Rm - 2552-2553
Abstract: The Geostationary Lightning Mapper (GLM) is the first sensor of its kind, and this technological advancement now allows continuous operational monitoring of lightning on time and space scales never before available. This has led to a golden age of lightning observations, which will spur more rapid progress toward synthesis of these observations with other meteorological datasets and forecasting tools. This study documents the first nine months of GLM observations, illustrating that the GLM captures similar spatial patterns of lightning occurrence to many previous studies. The present study shows that GLM flashes are less common over the oceans, but that the oceanic flashes are larger, brighter, and last longer than flashes over land. The GLM characteristics also help diagnose and document data quality artifacts that diminish in time with tuning of the instrument and filters. The GLM presents profound possibilities, with countless new applications anticipated over the coming decades. The baseline values reported herein aim to guide the early development and application of the GLM observations.
Bio(s):
Dr. Scott Rudlosky is a NOAA/NESDIS physical scientist in the Center for Satellite Applications and Research (STAR) Cooperative Research Program (CoRP). He is co-located with the Cooperative Institute for Climate and Satellites (CICS) in College Park, Maryland. Scott is the NESDIS Subject Matter Expert on lightning and science lead for the Geostationary Lightning Mapper (GLM). He originally joined CICS as a Research Associate in January 2011 following completion of his M.S. (2007) and Ph.D. (2011) in Meteorology at Florida State University. He obtained his B.S. (2004) in Geography with a specialization in Atmospheric Science from Ohio State University.
Abstract: The Global HydroEstimator (GHE) precipitation estimates constitute a critical source of low-latency operational data that feed the Flash Flood Guidance system (FFGS), which supports forecasters in 64 countries (currently) by providing to them products relevant to assessments for flash flood occurrence in an operational environment. The system integrates and quality controls data from a variety of remote and on-site sensors to support forecaster products. The talk will discuss the processing of precipitation data and provide information on validation of precipitation estimates from diverse regions.
Bio(s): Konstantine P. Georgakakos, M.S. and Sc.D. (MIT 1980, 1982). Director of HRC and Adjunct Professor at Scripps Institution of Oceanography, UCSD, and at Dept. of Civil and Environmental Engineering, The University of Iowa. Fellow of the American Association for the Advancement of Science (2016), Fellow of the AMS (2006).
