Influence of surface temperature and emissivity on AMSU-A assimilation over land
- 748 Downloads
AMSU-A (Advanced Microwave Sounding Unit-A) measurements for channels that are sensitive to the surface over land have not been widely assimilated into numerical weather prediction (NWP) models due to complicated land surface features. In this paper, the impact of AMSU-A assimilation over land in Southwest Asia is investigated with the Weather Research and Forecasting (WRF) model. Four radiance assimilation experiments with different land-surface schemes are designed, then compared and verified against radiosonde observations and global analyses. Besides the surface emissivity calculated from the emissivity model and surface temperature from the background field in current WRF variational data assimilation (WRF-VAR) system, the surface parameters from the operational Microwave Surface and Precipitation Products System (MSPPS) are introduced to understand the influence of surface parameters on AMSU-A assimilation over land.
The sensitivity of simulated brightness temperatures to different surface configurations shows that using MSPPS surface alternatives significantly improves the simulation with reduced root mean square error (RMSE) and allows more observations to be assimilated. Verifications of 24-h temperature forecasts from experiments against radiosonde observations and National Centers for Environmental Prediction (NCEP) global analyses show that the experiments using MSPPS surface alternatives generate positive impact on forecast temperatures at lower atmospheric layers, especially at 850 hPa. The spatial distribution of RMSE for forecast temperature validation indicates that the experiments using MSPPS surface temperature obviously improve forecast temperatures in the mountain areas. The preliminary study indicates that using proper surface temperature is important when assimilating lower sounding channels of AMSU-A over land.
Key wordsAMSU-A surface temperature microwave surface emissivity radiance assimilation
Unable to display preview. Download preview PDF.
- Baker, N. L., T. F. Hogan, W. F. Campbell, R. L. Pauley, and S. D. Swadley, 2005: The impact of AMSU-A radiance assimilation in the U. S. Navy’s Operational Global Atmospheric Prediction System (NOGAPS), NRL Memorandum Report Memo. Rep. (NRL/MR/7530-05-8836), 18pp Naval Res. Lab., Monterey, CA, 93943-5502.Google Scholar
- He Wenying and Chen Hongbin, 2009: The characteristics of microwave land emissivity over Chinese Jianghuai-Huanghuai Region. Remote Sens. Tech. Appl., 24, 297–303. (in Chinese)Google Scholar
- Gu Songqiang, Wang Zhenhui, Weng Fuzhong, Xue Jishan, and Dong Peiming, 2006: A study for improving microwave land surface emissivity model with NOAA/AMSU data and the GRAPES 3DVar system. Plateau Meteorology, 25, 1101–1106. (in Chinese)Google Scholar
- Jones, A. S., and T. H. Vonder Haar, 1997: Retrieval of microwave surface emittance over land using coincident microwave and infrared satellite measurements. J. Geophys. Res., 102, D12, 13609-13626299-310.Google Scholar
- —, F. Rabier, J. -P. Lafore, J. -L. Redelsperger, and O. Bock, 2010b: Global 4DVAR assimilation and forecast experiments using AMSU observations over land. Part II: Impacts of assimilating surface-sensitive channels on the African monsoon during AMMA. Wea. Forecasting, 25, 20–36.CrossRefGoogle Scholar
- Liu Z.-Q., X. Zhang, T. Auligne, and H. -C. Lin, 2009: Variational Analysis of Hydrometeors with Satellite Radiance Observations: A Simulated Study. 10th WRF Users Workshop, June 23–26, 2009, Boulder, Colorado.Google Scholar
- —, and D. M. Barker, 2006: Radiance Assimilation in WRF-Var: Implementation and Initial Results. 7th WRF Users Workshop, June 19–22, 2006, Boulder, Colorado.Google Scholar
- Weng, F., 2007: Advances in radiative transfer modeling in support of satellite data assimilation. J. Atmos. Sci., 64, 3803–3811.Google Scholar