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JCSDA News and Newsletters
Center NewsScience Update - The Community Radiative Transfer ModelA major achievement of the JCSDA has been the development of a Community Radiative Transfer Model (CRTM), portions of which are now used by all the partner agencies. The CRTM makes possible the rapid assimilation of millions of satellite observations at over a thousand spectral wavelengths from dozens of different instruments each day. 
A rapid, accurate radiative transfer model is one of the keys to success in assimilating satellite observed radiances. Realizing its importance, the JCSDA, at its inception in 2002, initiated the construction of a Community Radiative Transfer Model (CRTM), engaging internal and external developers. The CRTM is a software library for computing satellite instrument radiances from atmospheric and surface state variables. It emphasizes modularity and code reuse and is independent of computing platform or assimilation system. Its current capabilities include Forward, Tangent-linear, Adjoint and Jacobian models for assimilation of clear and cloudy IR and MW radiance observations from satellites over ocean, land, snow, and ice surfaces. CRTM modules include: Gaseous absorption, including H2O, O3 (model variables), CO2, CH4, N2O, CO, and O2 (gas concentrations specified); Atmospheric aerosols for eight different aerosol types; Clouds and precipitation for liquid phase (liquid water and rain) and solid phase (ice, snow, graupel, and hail); Microwave land and ocean emissivity; and Infrared land and ocean emissivity. While current assimilations are limited to observations from clear regions of the atmosphere, the CRTM is ready for integration into assimilation schemes for cloudy and precipitating areas as these are developed. It is also ready to be coupled with air quality and NWP models that treat CO2, CH4, N2O, and CO as variable gasses. This capability will enable, for example, monitoring of greenhouse gases within the context of an NWP model based on observations from hyperspectral IR sounders such as AIRS and IASI. Fuzhong Weng, JCSDA Impact of Satellite Altimetry on JCSDA Ocean Data Assimilation and Seasonal Climate Forecasts(From the March 2008 JCSDA Quarterly)Since the ocean provides a significant memory for the climate system, a critical element in climate forecasting with coupled models is the initialization of the ocean with states from an ocean data assimilation system (ODAS). Since October 1992 global ocean surface topography has been observed with TOPEX/Poseidon (1992-2005) and Jason-1 (2001-present) altimeters, both joint NASA/CNES missions. These satellites monitor changes in ocean heat storage and ocean currents.  Figure 1. Impact of altimetry assimilation on GODAS state estimates is assessed through the RMS differences (cm) from Topex/Poseidon and Jason-1 SSH anomalies for 1993 to 2007. The right- (left-) hand figure shows the RMS difference with (without) altimetry assimilation.Figure 2. The anomaly correlation skill score for heat content in the upper 300 m from the GMAO CGCMv1 for 6-month forecasts from 1 July initial conditions. The ocean is initialized from the EnKF with (left panel) and without (right panel) assimilation of satellite SSH anomalies. Only correlations higher than 0.6 are shown. The forecasts are validated against their own analyses.Both NOAA/NCEP and the NASA/GMAO use sea surface height (SSH) anomalies from these altimeters in their ODAS with the goal of improving global ocean state estimates and also seasonal climate forecast skill. The NCEP global ocean data assimilation system (GODAS), which currently provides initial conditions for the NCEP coupled Climate Forecast System (CFS), uses 3dVAR with the GFDL MOMv3. The GMAO system uses an Ensemble Kalman Filter (EnKF) with the Poseidon ocean model to initialize their CGCMv1. Both systems, although global, focus on the tropical oceans. In addition to the altimetry data, which provides information only at the surface, the ODAS assimilates temperature profiles from XBTs, fixed tropical moorings (TAO, TRITON, and PIRATA arrays) and the global Argo array. Both assimilation methods are designed to modify the mass field of the ocean model through corrections to temperature and salinity. Differences between the model SSH and observed SSH are translated into corrections to the temperature and salinity throughout the water column through the specification of background error covariances. Figure 1 shows the RMS differences between the altimeter observations and the GODAS dynamic heights. The area of low RMS differences (grey regions) is increased substantially with the assimilation of the altimeter data. In the tropics the RMS differences remain somewhat larger (4-5 cm) in the region of the tropical instability waves and the recirculation of the Brazil current. Outside of the tropics in the Gulf Stream and Kuroshio, which are not well resolved by climate-scale models like GODAS, the RMS differences are larger still. The GMAO's ODAS, the EnKF with online bias correction, has also been used to initialize seasonal forecasts with and without assimilation of altimeter data. As for other coupled models, the forecast skill varies seasonally. It is difficult to discern significant differences in skill from the different ocean initializations for January starts. The skill for July starts is longer-lived and there are discernable differences in performance for the two ocean initializations. Figure 2 shows that the skill of 6-month forecasts of upper-ocean heat content in the tropical oceans is improved with the assimilation of SSH anomalies. We are now anticipating the joint NOAA/NASA/CNES/EUMETSAT Ocean Surface Topography Mission (OSTM), or Jason-2, which will be launched in June 2008, to extend the time series of sea surface topography measurements to two decades. (David Behringer, NOAA/NCEP/Environmental Modeling Center, and Michele Rienecker, NASA/GSFC/GMAO) Dr. Lidia Cucurull Named NOAA Team Member of the Month for November 2007
Dr. Lidia Cucurull led the effort at the Joint Center for Satellite Data Assimilation in conducting testing and exploitation of Constellation Observing System for Meteorology, the Ionosphere and Climate (COSMIC) data in the Global Forecast System, following its launch in April 2006. By December 2006, Dr. Cucurull and her colleagues demonstrated the benefits of COSMIC data on numerical weather prediction forecasts, and its implementation was scheduled for the next operational upgrade of the Global Forecast System, in the third quarter FY07. Due to Dr. Cucurull's exemplary efforts, five-day global upper air forecasts improved by three percent, and this new satellite data was ready for operational use in models less than one year after launch. This is extremely fast for a significantly new technology to be made useful to operations. The Constellation Observing System for Meteorology, the Ionosphere
and Climate (COSMIC) |
JCSDA Quarterly NewsletterPlease send news items for the JCSDA Quarterly
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Dr. Lidia
Cucurull was named 
is a high profile international mission to
produce new satellite observations that complement conventional ones
to improve weather and climate analyses and forecasts. COSMIC, a
U.S.-Taiwan partnership is a constellation of six satellites that
probe the atmosphere using radio occultation. Each COSMIC satellite
intercepts a GPS satellite signal as it passes through the atmosphere
close to the horizon. Variations in electron density, air density,
temperature, and moisture bend the signal and change its speed. By
measuring these shifts in the signal, scientists can determine the
atmospheric conditions that produced them. Dr. Lidia Cucurull led the
effort at the Joint Center for Satellite Data Assimilation in
conducting testing and exploitation of COSMIC data in the Global
Forecast System, following the launch in April 2006. By December
2006, the beneficial impact of COSMIC data on numerical weather
prediction forecasts was demonstrated by Dr. Cucurull and her
colleagues, and implementation was scheduled for the next operational
upgrade of the Global Forecast System, which was in the third quarter
FY07. Due to Dr. Cucurull's exemplary efforts, 5-day global upper air
forecasts improved by 3% and this new satellite data was ready for
operational use in models less than 1 year after launch. This is
extremely fast for a significantly new technology to be made useful to
operations.
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