2006 STAR Seminars

The Cooperative Institute for Climate and Satellites (CICS) was established in 1983 to advance collaborative research into climate monitoring and prediction between NOAA and University of Maryland scientists. The scientific vision of CICS centers on the observation, using instruments on Earth-orbiting satellites, and prediction, using realistic mathematical models, of the present and future behavior of the Earth System. CICS research focuses on three major themes:

• The Global Energy and Water Cycles
• Climate Diagnostics and Prediction
• Atmospheric Chemistry

CICS scientists work closely with STAR scientists as well as other NOAA researchers to investigate improvements in remotely- sensed rainfall estimation, radiation algorithms and data sets, aerosol retrievals, and data assimilation. They continually apply these data in climate diagnostic studies, and incorporate them into stand-alone and coupled models. Newly emerging thematic areas for CICS include regional ecosystems within a coupled context and observational analysis and synthesis. In this presentation, I will review recent research accomplishments in CICS and discuss future plans.

The accuracy of analyses produced by modern data assimilation systems depends strongly on the precision of forecast error covariances specified as input. Typically, these errors are synoptically dependent, anisotropic, and and inhomogeneous. This talk will begin with a review of techniques used to date to represent flow-dependent errors in variational data assimilation systems. Current NCAR efforts in this direction are based on the WRF model, and are two-fold. Firstly, the application of 4D-Var implicitly introduces flow-dependent covariances via the use of a linearised forecast model (and its adjoint). Secondly, the use of ensemble-based forecast error covariances in 3/4D-Var via additional control variables in a hybrid approach is seen as a way to practically combine the best of both variational and ensemble approaches to data assimilation for operational NWP. Preliminary results from WRF applications for both 4D-Var and the hybrid will be presented.

The atmospheric limb sounding technique making use of radio signals transmitted by the Global Position System (GPS) has emerged as a promising approach for global atmospheric measurements. As demonstrated by the proof-of-concept GPS Meteorology (GPS/MET) experiment and more recently by the CHAMP and SAC-C missions, the GPS radio occultation (RO) sounding data are shown to be of high accuracy and high vertical resolution. On 15 April 2006, the joint U.S.-Taiwan COSMIC/FORMOSAT-3 mission, a constellation of six microsatellites, was launched into a 500 km polar orbit from the Vandenberg Air Force Base. These satellites are being deployed to their final orbits at 800 km, which would take about a year. During the early phase of the deployment, the satellites are closely located. This offers a unique opportunity to examine the precision of the GPS RO measurements.

Since mid-August, COSMIC/FORMOSAT-3 has been providing large number (averaging ~1,350 GPS RO soundings per day, and at times exceeding 1,600 GPS RO soundings per day) of GPS radio occultation (RO) soundings to support the research and operational communities. The number of GPS RO soundings will be increased as the satellites are further separated and deployed into their final orbits. Preliminary evaluation study has shown that the GPS RO data from COSMIC/FORMOSAT-3 are of better quality than those from the previous missions. Several global operational centers (e.g. NCEP, ECMWF, CMC and UKMO) have already started testing the COSMIC/FORMOSAT-3 data for operational use, and have already reported encouraging results. The COSMIC/FORMOSAT-3 data have been shown to be very useful for evaluating weather prediction and ionospheric models. With the ability to penetrate deep into the lower troposphere with the advanced open-loop tracking technique, FORMOSAT-3/COSMIC data have shown capability to detect tropical atmospheric boundary layer. Such information is very useful for weather prediction and climate studies. This presentation will review the status of the COSMIC/FORMOSAT-3 mission, and present highlights of scientific research making use of GPS RO observations obtained over the first six months of the mission.

The (mid-visible) aerosol optical depth (AOD) is probably the most important optical property to quantify atmospheric aerosol. When observing aerosol from space retrievals have been developed mainly to provide data for this property. However, influenced by sensor and algorithm capabilities, individual satellite retrievals have regional and seasonal strengths and weaknesses (to a point that no reliable retrieval is possible). In order to provide a superior product, in terms of accuracy and global coverage, over that of any individual retrieval, regional and seasonal advantages of available global satellite data-sets are combined to a recommended data-set. The necessary retrieval assessment is based on quality ground remote sensing by AERONET. Recommended composites will be discussed and presented for the mid-visible aerosol optical depth (representing aerosol amount) and for the Angstrom parameter which describes the spectral dependence of the visible aerosol optical depth (representing aerosol size).

A suite of products has been developed and evaluated to assess meteorological hazards to aircraft in flight derived from the current generation of Geostationary Operational Environmental Satellite (GOES) (I-Q). The existing suite of products includes derived images to address five major aviation hazards: fog, aircraft icing, microbursts, turbulence and volcanic ash. The products are developed under the premise of eventual inclusion into the National Weather Service Advanced Weather Interactive Processing System (AWIPS). The fog, icing, and volcanic ash products, derived from the GOES imager, are generated utilizing algorithms that employ temperature differencing techniques to highlight regions of elevated risk to aircraft. In contrast, the GOES microburst products employ the GOES sounder to calculate microburst risk based on conceptual models of favorable environmental profiles for convective downburst generation. It is expected that the current suite of aviation products will be adapted for GOES-R with modifications and enhancements to the algorithms. This presentation will highlight progress and recent developments with the Aviation Product suite with emphasis on the products designed to assess risk of turbulence, microbursts and volcanic ash.

The Land Information System software (LIS; http://lis.gsfc.nasa.gov/) has been developed to support high performance land surface modeling and data assimilation. LIS integrates parallel and distributed computing technologies with modern land surface modeling capabilities, and establishes a framework for easy interchange of subcomponents, such as land surface physics, input/output conventions, and data assimilation routines. The software includes multiple land surface models that can be run as a multi-model ensemble on global or regional domains with horizontal resolutions ranging from 2.5 degrees to 1km. The software may execute serially or in parallel on various high performance computing platforms. In addition, the software has well defined, standard-conforming interfaces and data structures to interface and interoperate with other earth system models. Originally developed with support from NASA, and co-winner of NASA's 2005 Software of the Year, LIS is now being supported by JCSDA partners including NASA, AFWA and NCEP to help transition research to operations.

An adjoint-based method is being used to monitor in near real-time the impact of atmospheric observations assimilated in the operational NAVDAS. The technique uses adjoint versions of NAVDAS and NOGAPS and has been developed and tested at NRL-Monterey over the last 2-3 years. This talk will describe the mathematical approach and accuracy of the method, and present some specific examples in which the procedure has been used to identify observing system issues relevant to the NAVDAS operational data assimilation.

The DMSP SSM/I and SSM/IS form the longest passive microwave imager time series (19 years and continuing) that has been used to study various components of the Earth's hydrological cycle. Products such as rain rate, snow cover and total precipitable water are routinely used to support NOAA's mission goals such as "Weather and Water" and "Climate". However, to improve the robustness of the data, special care must be taken to improve the absolute and intersatellite calibration of the DMSP sensors. Additionally, several issues such as the diurnal variability, satellite drift and averaging methods must be addressed before improved climate data records (CDRs) can be generated from the SSM/I.

This two-part talk will first present details on the satellite calibration effort being undertaken at STAR, then will illustrate some of the issues involved for proper CDR generation.

Estimating the errors in the data and model are critical aspects of data assimilation. In this I will present a reduced state space optimal interpolation (RSSOI) scheme to assimilate satellite remotely sensed sea surface temperature into a coarse resolution general circulation model of the North Pacific Ocean. Using statistical tests on the principal components of a multi-decadal model simulation and the misfits between model simulation and the remotely sensed data, I will show that the model and data have a small number of independent degrees of freedom (approximately 30-40) which is much less than the dimension of the model or data. The small number of degrees of freedom makes a reduced state space filter appropriate. However, the RSSOI scheme results in only a modest improvement in the analysis. Taking the difference between the model-data misfit and a fit to the model-data misfit using the principal components of the model, an estimate the model representation error can be made. The techniques presented in this talk can be adapted for other models and data sources. Implications of the model representation error on coupled models will be discussed.

From April 2003, the split window 12µm channel has not been available on the GOES imagers and will not be available until about 2013. The 12um channel, used in the Geostationary Operational Environmental Satellite (GOES)-11 (or GOES-West) Imager has been replaced by a 13.3µm channel in the GOES-12 (or GOES-East) Imager. There has been concern that the 13.3µm channel will not be as accurate in collecting volcanic ash data, especially when there is a significant amount of high cirrus cover or diffuse ash. This is of great importance because volcanic ash clouds, if undetected, can be dangerous for aircraft. If the ash is ingested into the jet engines, volcanic ash decreases their efficiency. Furthermore, the plane's leading edge surfaces can be damaged. Recently, the increased amount of air traffic in the circumpacific region of the globe where the most potentially active volcanoes are located has increased the need for accurate volcanic ash data. There is also expected to be degradation in the detection of low clouds. Differences in cloud data have important implications for future weather forecasting and interpretation. This research effort provides a comparison of various types of cloud data as detected in infrared (IR) images for GOES-11 and GOES-12 for the Mexican volcanoes Colima and Popocatepetl. The IR images from GOES-11 and GOES-12 are compared to visible (VIS) images generated by GOES-12. In addition, scatter plots of brightness temperature vs. brightness count are used for both satellite imagers to help determine patterns and data correlations. The data indicates that, in general, the GOES-11 volcanic ash algorithm with the 12µm band provides much better data for various types of clouds. It emphasizes the importance of the 12µm band and provides scope for future research in this area.

The MSU instrument on board the National Oceanic and Atmospheric Administration (NOAA) polar-orbiting satellite series was designed to measure the atmospheric temperature from the surface to the lower stratosphere under all weather conditions, excluding precipitation. Due to their continuity and long time stability, MSU instruments offer a unique opportunity for monitoring long-term changes in tropospheric temperature. During the last 15 years, various studies have been conducted to determine the long-term atmospheric temperature trend from MSU measurements. However, the trends derived from these measurements are a subject of debate because different groups yield different results. Calibration errors are one of the major sources of uncertainties in the MSU- derived temperature trends. In an effort to reconcile the problem, we have recently re-calibrated the multiple MSU satellites using simultaneous nadir overpasses and obtained a new set of well-merged MSU 1b data for climate studies. For the new calibration, the global ocean-averaged MSU channel 2 anomaly trends are 0.19 K per decade for the 17-year period from 1987 to 2003 containing observations from NOAA 10, 11, 12, and 14. In this talk, we will discuss the SNO calibration technique and how the trend can be obtained from the new calibration. We will also review different techniques in obtaining the MSU trend and discuss if a consensus trend can be obtained.

Terrestrial ecosystems north of 45°N have experienced earlier and more dramatic environmental changes from global warming compared with lower-latitude ecosystems. These changes include higher mean annual air temperatures, increases in precipitation, and melting of permafrost. The warmer temperatures and the alterations of hydrology in the region have resulted in changes in the magnitude and timing of CH₄ emissions and consumption. Here I present results using a new version of the Terrestrial Ecosystem Model (TEM) to study how rates of CH₄ emissions and consumption in high-latitude soils of the Northern Hemisphere have changed and will change over the 20^th and 21^st century in response to observed changes in the region's climate and plausible future climate change scenarios. Model simulations indicate that the net emissions of CH₄ (emissions minus consumption) from these soils have increased by an average 0.08 Tg CH₄ yr-1 during the 20^th century. Our estimate of the annual net emission rate at the end of the 20^th century for the region is 51 Tg CH₄ yr-1. For the 21^st century, the land ecosystems of the northern high latitudes continue to be a net source of CH₄. By the end of the 21^st century, the region will approximately double the amount of current net emissions. Russia, Canada, and Alaska are the major CH₄ regional sources to the atmosphere; responsible for 64%, 11%, and 7% of the current wetland CH₄ emissions, respectively. The large inter-annual variability in net CH₄ emissions occur due to changes of climate conditions. The analyses of the responses of net CH₄ emissions to the past and future climate change suggest that there might be a positive feedback between net CH₄ emissions from the Pan-Arctic region and the climate system.

Currently, satellite remote sensing plays predominated roles in global atmosphere and surface parameters for both operational and research purposes. Even though, surface-based remote sensing of the atmospheric parameters is still of significance. Powerful MW radar, wind profilers, etc. have proved their ability in mesoscale meteorology. In the area of operational surface meteorological observation, cloud visibility and weather phenomena are still observed by human eyes and with unsatisfactory information. In principle, satellite optical remote sensing is difficult to sense the cloud base; aerosols and surface under the cloud. In this sense, surface optical and infrared remote sensing are still significant for cloud, aerosol, and downward radiation. It will be useful to the validation of satellite remote sensing and also for combined retrieval. In this presentation, we will introduce a ground-based system of all sky imaging observation for sky radiation distribution, cloud distribution and cloud base height determination. This system is consisted of a calibrated all sky visible camera and a scanning thermal infrared thermometer. The sky visible radiation distribution and infrared brightness temperature are used to retrieve the cloud fraction and cloud base heights by using radiative transfer modeling. Field observation at 4 different sites has shown some preliminary result.

The analysis distributions produced by ensemble-based approaches to data assimilation form a basis for ensemble forecasting, but also define state-dependent, dynamic relationships amongst prognostic and diagnostic variables that can be used for traditional dynamic analysis. These data assimilation approaches rely on the assumption that errors are Gaussian, an assumption that is easily violated when forecast fields contain "features" (cyclones, fronts, etc.) that are in the wrong position. A framework is presented in which the impact of such alignment errors on data assimilation can be ameliorated through a sensible choice of error model and a two-step approach (position, then amplitude) to ensemble-based data assimilation.

Quasi-uniform (QU) spherical grids represent attractive alternatives to the standard longitude-latitude spherical grids for application in global models of the atmospheres and oceans. These grids have smooth topologies of near equally distributed grid points, by which they avoid excessive resolution in the areas around geographical poles and related computational problems of the longitude-latitude grid.

This talk describes research on a global expansion of NCEP's regional, step-coordinate, Eta model through a framework of QU grids with rectangular base elements. In this research, only cubic and octagonal grids are considered including their different variations such as conformal, smoothed, and variable resolution grids. The original numerical schemes of the regional Eta model for discretization of the governing equations are modified in general curvilinear form. In this way, the single code is applicable to all grids within the framework in spite of different mapping of the computational domain.

The derived global version of the Eta model is successfully tested with idealized benchmark tests as well as in simulations with real data. The results compare well with the analysis, the results of the regional Eta model, and the results of other global models, in terms of both forecasted fields and computational efficiency.

Relationships between anthropogenic aerosols and low-level water clouds were discussed to better understand the aerosol indirect effect over East Asia. Results from numerical simulations yielded the anthropogenic aerosol concentration Ma. Satellite-derived products yielded information on low-level water cloud properties (cloud optical depth t, effective particle radius re, vertically integrated cloud droplet number Nc). Comparisons of monthly means for aerosols and clouds showed that t increased and re decreased as Ma increased.

Such tendencies were consistent with the Twomey effect, which describes how aerosols affect cloud properties. Nevertheless, comparisons of Ma with t in April and October would suggest the importance of dynamic effects on cloud formation and maintaining processes. Values of Nc that were calculated from t and re also increased as Ma increased. This result also agreed with the Twomey effect by indicating that additional aerosols generated more cloud droplets. A comparison of Ma with lower and middle clouds revealed similar tendencies to the previous case (i.e., total water cloud case), but differences in re (i.e., larger for middle and smaller for lower clouds) reflected the vertical profile of aerosol numbers. However, differences in t (i.e., thicker for middle and thinner for lower clouds) might have been influenced by the vertical extent.

If time permits, other examples of aerosol indirect effects, cloud-precipitation relationships will be also described.

The STAR Regional and Mesoscale Meteorology (RAMM) Branch has a number of on-going projects to better utilize satellite data for tropical cyclone analysis and forecasting. Five papers on this topic that will be presented at the upcoming AMS conference on Hurricanes and Tropical Meteorology. Applications include tropical cyclone intensity and wind structure forecasting, diagnosis of a special type of storm called an annular hurricane, tropical cyclone genesis studies and the impact of pressure wind relationships on the detection long term trends in tropical cyclone intensity. Three of these papers will be presented at the Science Forum, and the other two will be briefly summarized.

The STAR Regional and Mesoscale Meteorology (RAMM) Branch has a number of on-going projects to better utilize satellite data for tropical cyclone analysis and forecasting. Five papers on this topic that will be presented at the upcoming AMS conference on Hurricanes and Tropical Meteorology. Applications include tropical cyclone intensity and wind structure forecasting, diagnosis of a special type of storm called an annular hurricane, tropical cyclone genesis studies and the impact of pressure wind relationships on the detection long term trends in tropical cyclone intensity. Three of these papers will be presented at the Science Forum, and the other two will be briefly summarized.

The use of remotely sensed trace gas and aerosol data for surface air quality monitoring and forecasting has evolved tremendously in the last decade. NOAA/NESDIS has been active in developing near real time satellite products for air quality applications from its geostationary and polar-orbiting satellites for users such as the EPA and the NWS. Satellite derived aerosol optical depths, ozone, and PM2.5 emissions in near real time are currently being used by the NWS in air quality forecast verification and in air quality modeling to improve forecasts.

Plans are underway to expand the operational product development to trace gases such as NO₂, H₂CO, SO₂, CO, and absorption/scattering optical depths with the launch of IJPS GOME-2 and IASI instruments in 2006. The launch of NPP, NPOESS, and GOES-R sensors in the next decade will strengthen and expand the early progress. We will present examples of air quality applications of current operational satellite data and discuss potential applications with future satellite sensors.

Various noxious marine organisms, such as jellyfish and harmful algal blooms, periodically afflict the waters of the Chesapeake Bay and the coastal U.S. Knowing when and where these organisms are present in the bay may help in mitigating their deleterious effects. Multiple interacting physical, chemical, and biotic factors lead to the development and persistence of these biotic events. Information on many of these factors is accessible in near-real time from geographic databases, numerical circulation models, and operational satellites. Over the past several years, we have developed and implemented a system that generates daily maps illustrating the relative abundance of the toxic dinoflagellate, Karlodinium micrum, and the probability of encountering sea nettles, a stinging jellyfish, in Chesapeake Bay and its major tributaries. These ecological nowcasts are generated by flagging the geographic locations where ambient conditions coincide with the organism's preferred environment. In the seminar, I will discuss the present system, the nowcasts products, and our plans for the future.

• Overview of the high spectral resolution instruments and products.
• Advantages of high spectral resolution, multi-spectral observations.
• Overview of trace gas products
  • Ozone
  • Carbon monoxide
  • Methane
  • Carbon dioxide
• Overview of product web page