10.5
Potential Impacts of Advanced Technology Microwave Sounder (ATMS) and Microwave Imager/Sounder (MIS) in NCEP Global Forecast System

- Indicates paper has been withdrawn from meeting
- Indicates an Award Winner
Thursday, 21 January 2010: 4:30 PM
B313 (GWCC)
Banghua Yan Sr., University of Maryland/ESSIC, Camp Springs, MD; and F. Weng and J. Derber

Presentation PDF (1.1 MB)

Advanced Technology Microwave Sounder (ATMS) and Microwave Imager/Sounder (MIS) are two microwave instruments on the National Polar-orbiting Operational Environmental Satellite System (NPOESS). To prepare uses of observations from these two instruments in Numerical Weather Prediction (NWP) models, we use Advanced Microwave Sounding Unit (AMSU) and Special Sensor Microwave Imager/Sounder (SSMIS) as their proxy data to understand their potential impacts on global medium-range forecasts. AMSU has nearly similar sounding channel allocations as ATMS, while SSMIS has similar sounding channel allocations as MIS. Also, a series of operational observations with diverse Equatorial Crossing Time (ECT) are available from current AMSU and SSMIS. The assimilation impacts of future ATMS and MIS data can be understood from different combinations of current AMSU and/or SSMIS observations abroad on the above satellites. In this study, a control and a series of test observation system experiments (OSPs) with different ECT combinations of current AMSU and/or SSMIS observations will be carried out in Environmental Prediction (NCEP) Global Forecast System (GFS). Here, the control OSP includes the NCEP's operational databases of both conventional in situ data and non-microwave satellite data. The impacts of the data on forecast skill, analysis fields, and hurricane track will be analyzed for understanding of potential impacts from assimilations of future ATMS and MIS data. Currently, it is still critical to improve bias correction, land emissivity and cloud detection schemes. To more effectively use satellite data, improved microwave land emissivity, bias correction and cloud detection schemes will be addressed. It is thus expected that the appropriate emissivity simulation algorithm, bias correction scheme and quality control criteria will be developed for assimilation of ATMS and MIS data into the NCEP GFS.