James A. Jung

Improving Global Analysis and Forecasting with AIRS

AMERICAN METEOROLOGICAL SOCIETY | 891 AFFILIATIONS : LE MARSHALL, JUNG, DERBER, TREADON, LORD, GOLDBERG, WOLF, LIU, JOINER, WOOLLEN, TODLING, VAN DELST, AND TAHARA—NASA, NOAA, and U.S. Department of Defense Joint Center for Satellite Data Assimilation, Camp Springs, Maryland; CHAHINE—NASA Jet Propulsion Laboratory, Pasadena, California CORRESPONDING AUTHOR: John Le Marshall, Joint Center for Satellite Data Assimilation, NOAA Science Center, 5200 Auth Road, Camp Springs, MD 20746 E-mail: John.Lemarshall@noaa.gov

A Two-Season Impact Study of Satellite and In Situ Data in the NCEP Global Data Assimilation System

Abstract Observing system experiments are used to quantify the contributions to the forecast made by conventional in situ and remotely sensed satellite data. The impact of each data type is assessed by comparing the analyses and forecasts based on an observing system using all data types. The analysis and forecast model used for these observing system experiments is the National Centers for Environmental Prediction (NCEP) Global Data Assimilation/Forecast System (GDAS/GFS). The case studies chosen consist of 45-day periods during January–February 2003 and August–September 2003. During these periods, a T254–64 layer version of NCEP’s Global Spectral Model was used. The control run utilizes NCEP’s operational database and consists of all data types routinely assimilated in the GDAS. The two experimental runs have either all the conventional in situ data denied (NoCon) or all the remotely sensed satellite data denied (NoSat). Differences between the control and experimental runs are accumulated over the 45-d...

A Two-Season Impact Study of Four Satellite Data Types and Rawinsonde Data in the NCEP Global Data Assimilation System

Abstract Extended-length observing system experiments (OSEs) during two seasons are used to quantify the contributions made to forecast quality by conventional rawinsonde data and four types of remotely sensed satellite data. The impact is measured by comparing the analysis and forecast results from an assimilation–forecast system using all data types with those excluding a particular observing system. The impact of the particular observing system is assessed by comparing the forecast results over extended periods. For these observing system experiments, forecast results are compared through 168 h for periods covering more than a month during both the summer and winter seasons of each hemisphere. The assimilation–forecast system used for these experiments is the National Centers for Environmental Prediction (NCEP) Global Data Assimilation System (GDAS) and the Global Forecast System (GFS). The case studies chosen consist of periods during January–February 2003 and August–September 2003. During these perio...

Validation and use of GOES sounder moisture information

Abstract The Geostationary Operational Environmental Satellite (GOES) sounders have provided quality hourly radiances and derived products over the continental United States and adjacent oceans for more than five years. The products derived from the radiances include temperature and moisture profiles; total precipitable water vapor (TPW); atmospheric stability indices, such as convective available potential energy (CAPE) and lifted index (LI); cloud-top properties; total column ozone; and midlevel motion. This paper focuses on validation and use of moisture profiles derived in clear regions. Validations are made with respect to collocated radiosondes, a microwave radiometer, and parallel runs of the regional Eta Model system. The ground-based microwave radiometer enables comparisons throughout the day, instead of only at conventional radiosonde launch times (0000 and 1200 UTC). The validations show that the sounder products provide unique information about the state of the atmosphere. The GOES sounder moi...

A Case Study of the Sensitivity of the Eta Data Assimilation System

Abstract A case study is utilized to determine the sensitivity of the Eta Data Assimilation System (EDAS) to all operational observational data types used within it. The work described in this paper should be of interest to Eta Model users trying to identify the impact of each data type and could benefit other modelers trying to use EDAS analyses and forecasts as initial conditions for other models. The case study chosen is one characterized by strong Atlantic and Pacific maritime cyclogenesis, and is shortly after the EDAS began using three-dimensional variational analysis. The control run of the EDAS utilizes all 34 of the operational data types. One of these data types is then denied for each of the subsequent experimental runs. Differences between the experimental and control runs are analyzed to demonstrate the sensitivity of the EDAS system to each data type for the analysis and subsequent 48-h forecasts. Results show the necessity of various nonconventional observation types, such as aircraft data,...

An Impact Study of Five Remotely Sensed and Five In Situ Data Types in the Eta Data Assimilation System

Abstract The impact of 10 data types used in the Eta Data Assimilation/Forecast System (EDAS) is studied for extended-length time periods during three seasons. Five of the data types are remotely sensed satellite data, and the other five are in situ. The satellite data types include three-layer and vertically integrated precipitable water, temperature data down to cloud top, infrared cloud-drift winds, and water vapor cloud-top winds. The five in situ data types consist of two rawinsonde and two aircraft observation types along with surface land observations. The work described in this paper is relevant for Eta Model users trying to identify the impact of remotely sensed, largely maritime data types and in situ, largely land-based data types. The case studies chosen consist of 11-day periods during December 1998, April 1999, and July 1999. During these periods, 11 EDAS runs were executed twice daily. The 11 runs include a control run, which utilizes all data types used in the EDAS, and 10 experimental run...

A Four-Season Impact Study of Rawinsonde, GOES, and POES Data in the Eta Data Assimilation System. Part II: Contribution of the Components

Abstract The impact of in situ rawinsonde observations (raob), remotely sensed Geostationary Operational Environmental Satellite (GOES), and Polar-Orbiting Operational Environmental Satellite (POES) observations routinely used in NCEP’s Eta Data Assimilation/Forecast System (EDAS) is studied for extended-length time periods during four seasons. This work examines the contribution of nine individual components of the total observing system. The nine data types examined include rawinsonde mass and wind observations, GOES mass and wind observations, POES observations from the Microwave Sounding Unit (MSU), the Advanced Microwave Sounding Unit (AMSU-A and AMSU-B), the High Resolution Infrared Radiation Sounder (HIRS), and column total precipitable water and low-level wind observations from the Special Sensor Microwave Imager (SSM/I). The results are relevant for users of the Eta Model trying to compare/contrast the overall forecast impact of traditional, largely land-based rawinsonde observations against remo...

A four-season impact study of rawinsonde, GOES, and POES Data in the Eta Data Assimilation System. Part I: The total contribution

Abstract The impact of in situ rawinsonde (raob) data, remotely sensed Geostationary Operational Environmental Satellite (GOES), and Polar Operational Environmental Satellite (POES) data routinely used in NCEP’s Eta Data Assimilation/Forecast System (EDAS) is studied for extended-length time periods during four seasons. The work described in this paper is relevant for users of the Eta Model trying to compare and contrast the overall forecast impact of traditional, mostly land-based rawinsonde data with remotely sensed data that are available domainwide. The case studies chosen consist of 15-day periods during fall 2001, winter 2001/02, spring 2002, and summer 2002. During these periods, a 32-km/60-layer November 2001 version of the EDAS is run four times at both 0000 and 1200 UTC. The four runs include a control run, which utilizes all data types routinely used in the EDAS, and three experimental runs in which either all rawinsonde, GOES, or POES data are denied. Differences between the experimental and c...

Assimilation of clear sky Atmospheric Infrared Sounder radiances in short-term regional forecasts using community models

Abstract Regional assimilation experiments of clear-sky Atmospheric Infrared Sounder (AIRS) radiances were performed using the gridpoint statistical interpolation three-dimensional variational assimilation system coupled to the weather research and forecasting model. The data assimilation system and forecast model used in this study are separate community models; it cannot be assumed that the coupled systems work optimally. Tuning was performed on the data assimilation system and forecast model. Components tuned included the background error covariance matrix, the satellite radiance bias correction, the quality control procedures for AIRS radiances, the forecast model resolution, and the infrared channel selection. Assimilation metrics and diagnostics from the assimilation system were used to identify problems when combining separate systems. Forecasts initiated from analyses after assimilation were verified with model analyses, rawinsondes, nonassimilated satellite radiances, and 24 h–accumulated precipitation. Assimilation of clear sky AIRS radiances showed the largest improvement in temperature and radiance brightness temperature bias when compared with rawinsondes and satellite observations, respectively. Precipitation skill scores displayed minor changes with AIRS radiance assimilation. The 00 and 12 coordinated universal time (UTC) forecasts were typically of better quality than the 06 and 18 UTC forecasts, possibly due to the amount of AIRS data available for each assimilation cycle.

A Two-Season Impact Study of NOAA Polar-Orbiting Satellites in the NCEP Global Data Assimilation System

Abstract Observing system experiments (OSEs) during two seasons are used to quantify the important contributions made to forecast quality from the use of the National Oceanic and Atmospheric Administration’s (NOAA) polar-orbiting satellites. The impact is measured by comparing the analysis and forecast results from an assimilation–forecast system using one NOAA polar-orbiting satellite with results from using two and three polar-orbiting satellites in complementary orbits. The assimilation–forecast system used for these experiments is the National Centers for Environmental Prediction (NCEP) Global Data Assimilation System–Global Forecast System (GDAS–GFS). The case studies chosen consist of periods during January–February and August–September 2003. Differences between the forecasts are accumulated over the two seasons and are analyzed to demonstrate the impact of these satellites. Anomaly correlations (ACs) and geographical forecasts (FIs) are evaluated for all experimental runs during both seasons. The a...