STAR Seminars

STAR Science Seminars

Presenter:
James L. Carr, Carr Astronautic Corp., jcarr@carrastro.com

Sponsor:
STAR Science Seminar Series

Remote Access:
WebEx:
Event Number:    903 968 181
Password: STARSeminar

Event address for attendees:
https://noaa-nesdis-star.webex.com/noaa-nesdis-star/j.php?MTID=mc7b8262cf3d07c33edd7b7c2a663910d

Audio:  
USA participants: 866-832-9297
Passcode:  6070416



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.
About the Speaker:

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

Presenter:
Xiaolei Zou, Earth System Science Interdisciplinary Center, University of Maryland

Sponsor:
STAR Science Seminar Series

Remote Access:
WebEx:
Event Number:    901 608 434
Password: STARSeminar

Event address for attendees:
    https://noaa-nesdis-star.webex.com/noaa-nesdis-star/j.php?MTID=mf8cfbc9d27001bbf30fd54ca92a5423a

Audio:  
USA participants: 866-832-9297
Passcode:  6070416



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.
About the Speaker:
Dr. Xiaolei Zou received a PhD in Meteorology is a research professor at ESSIC at University of Maryland. 



POC:
Stacy Bunin, stacy.bunin@noaa.gov