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Applications of AMSU-Based Hydrological Products for Climate Studies. Ralph Ferraro 1 (Government Principal Investigator) , Huan Meng 1 , Fuzhong Weng 2 , Daniel Vila 3 1 NOAA/NESDIS/STAR/CoRP, 2 NOAA/NESDIS/STAR/SMCD, 3 Cooperative Institute for Climate and Satellites (CICS).
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Applications of AMSU-Based Hydrological Products for Climate Studies Ralph Ferraro1 (Government Principal Investigator), Huan Meng1, Fuzhong Weng2, Daniel Vila3 1NOAA/NESDIS/STAR/CoRP, 2 NOAA/NESDIS/STAR/SMCD, 3Cooperative Institute for Climate and Satellites (CICS) Requirement:1) Weather and Water Goal –Improve water resources forecasting capabilities. 2) Climate Goal - Develop an integrated global observation & data management system for routine delivery of information, including attribution of the state of the climate. Science:How do we utilize cross-track passive microwave sensors to retrieve parameters that are useful for weather and climate? How do we utilize high-frequency observations to improve the retrievals? Benefit:The utilization of AMSU/MHS for weather & climate applications is well beyond the original purpose of the instrument (i.e., Temp. & Moisture profiling) and greatly supplements similar date from other satellites & in-situ measurements. • 2. Methodology and Applications • The physical basis for the AMSU products stems from the work of Weng et al (2003) and further detailed in Ferraro et al (2005). There have also been over 15 publications that focus on individual products. The retrievals are based on physical models that are parameterized to be operationally efficient. The ten years of AMSU measurements can be utilized in a number of “climate” applications, as both stand alone products and in conjunction with other products. The orbital retrievals are simply aggregated to pentad and monthly values on both 1 and 2.5 degree grid boxes. Some examples presented include: • Figure 1 – Seasonal mean precipitation. The POES satellites provide ~4 hr sampling which allows for a better depiction of the diurnal cycle of rainfall as compared to similar products derived from the SSM/I. • Figure 2 – Interannual precipitation of “Nino4” region – (A) AMSU; (B) SSMI; (C) SST. AMSU and SSM/I provide similar variations that correspond with SST anomalies. • Figure 3 – Snow and Ice Cover seasonal means. • Additionally, the AMSU products have become key components to several blended products that are widely used by the scientific community, including the CMORPH, TMPA, and PERSIANN precipitation products. • Ferraro, R.R., F. Weng, N. Grody, L. Zhao, H. Meng, C. Kongoli, P. Pellegrino, S. Qiu and C. Dean, 2005: NOAA operational hydrological products derived from the AMSU. IEEE Trans. Geo. Rem. Sens., 43, 1036 – 1049. • Weng, F, L. Zhao, G. Poe, R. Ferraro, X. Li and N. Grody, 2003; AMSU cloud and precipitation algorithms. Radio Science, 38(4), 8068-8079. Figure 1 1. Introduction The Advanced Microwave Sounding Unit (AMSU) was first placed into operation on the NOAA-15 satellite in July 1998. Since then, AMSU’s (and its successor, MHS), have collectively flown on five more satellites and continue to operate today. Although primarily used for temperature and moisture sounding, STAR scientists used their experience from products developed from the DMSP Special Sensor Microwave/Imager (SSM/I) to develop a new, operational product suite for AMSU that generates Hydrological Products (Table 1). With over 10 years of AMSU measurements (Table 2), these products can be used to look at global, seasonal to interannual climate signals. It is the purpose of this poster to present some of the AMSU-Derived Climate Products. Figure 2 Table 1 Science Challenges: Advancing the state-of-the-art in algorithm retrievals, using microwave sounder data. Also, integrating all available measurements into seamless product for users (weather and climate). Next Steps: Secure funding from NOAA SDS/CDR program for AMSU; continue to evolve product line through MIRS; continue to build time series. Transition Path: Weather products through SPSRB with MIRS; CDR’s through NCDC’s SDS/CDR program.. Table 2 Figure 3