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College Park, MD, United States

Zou X.,Florida State University | Weng F.,The Center for Satellite Applications and Research | Zhang B.,Earth Resources Technology Inc. | Lin L.,Earth Resources Technology Inc. | And 4 more authors.
Journal of Geophysical Research: Atmospheres | Year: 2013

This study demonstrates the added benefits of assimilating the Advanced Technology Microwave Sounder (ATMS) radiances in the Hurricane Weather Research and Forecasting (HWRF) system to forecasts of four Atlantic hurricane cases that made landfall in 2012. In the National Centers for Environmental Prediction (NCEP) Gridpoint Statistical Interpolation data assimilation system, the HWRF model top is raised to ~0.5 hPa and the cold start embedded in the HWRF system is changed to a warm start. The ATMS data quality control (QC) procedure is examined and illustrated for its effectiveness in removing cloudy radiances of all the 22 ATMS channels using primarily the information from ATMS channels 1 and 2. For each hurricane case, two pairs of data assimilation and forecasting experiments are carried out and compared with and without including ATMS data. The only difference between the two pairs of experiments is that the second pair also includes data from several other polar-orbiting satellite instruments. It is shown that ATMS data assimilation in HWRF results in a consistent positive impact on the track and intensity forecasts of the four landfall hurricanes. Key Points The HWRF model top is raised to 0.5 hPa for an effective ATMS data assimilation The HWRF cold start is changed to warm start to avoid double use of data A consistent positive impact of ATMS data for TC track and intensity forecasts ©2013 The Authors. Journal of Geophysical Research: Atmospheres published by Wiley on behalf of the American Geophysical Union. Source


Liu Q.,Joint Center for Satellite Data Assimilation | Liu Q.,Perot Systems | Weng F.,The Center for Satellite Applications and Research | English S.J.,UK Met Office
IEEE Transactions on Geoscience and Remote Sensing | Year: 2011

Satellite measurements from microwave instruments have made a significant contribution to the skill of numerical weather forecasting, on both global and regional scales. A FAST microwave Emissivity Model (FASTEM), which was developed by the Met Office, U.K., has been widely utilized to compute the surface emitted radiation in forward calculations. However, the FASTEM model was developed for frequencies in the range of 20-60 GHz, and it is biased at higher and lower frequencies. Several critical components such as variable sea surface salinity and full Stokes vector have not been generally taken into account. In this paper, the effects of the permittivity models are investigated, and a new permittivity model is generated by using the measurements for fresh and salt water at frequencies between 1.4 and 410 GHz. A modified sea surface roughness model from Durden and Vesecky is applied to the detailed two-scale surface emissivity calculations. This ocean emissivity model at microwave is now being used in the Community Radiative Transfer Model, and it has resulted in some major improvements in microwave radiance simulations. This paper is a joint effort of the Met Office, U.K., and the Joint Center for the Satellite Data Assimilation, U.S. The model is called as FASTEM-4 in the Radiative Transfer for TIROS Operational Vertical Sounder model. © 2006 IEEE. Source


Chen Y.,The Interdisciplinary Center | Han Y.,The Center for Satellite Applications and Research | Delst P.V.,IMSG Inc. | Delst P.V.,Joint Center for Satellite Data Assimilation | Weng F.,The Center for Satellite Applications and Research
Journal of Atmospheric and Oceanic Technology | Year: 2013

The nadir-viewing satellite radiances at shortwave infrared channels from 3.5 to 4.6 mm are not currently assimilated in operational numerical weather prediction data assimilation systems and are not adequately corrected for applications of temperature retrieval at daytime. For satellite observations over the ocean during the daytime, the radiance in the surface-sensitive shortwave infrared is strongly affected by the reflected solar radiance, which can contribute as much as 20.0K to the measured brightness temperatures (BT). The nonlocal thermodynamic equilibrium (NLTE) emission in the 4.3-μm CO2 band can add a further 10K to the measured BT. In this study, a bidirectional reflectance distribution function (BRDF) is developed for the ocean surface and an NLTE radiance correction scheme is investigated for the hyperspectral sensors. Both effects are implemented in the Community Radiative Transfer Model (CRTM). The biases of CRTM simulations to Infrared Atmospheric Sounding Interferometer (IASI) observations and the standard deviations of the biases are greatly improved during daytime (about a 1.5-K bias for NLTE channels and a 0.3-Kbias for surface-sensitive shortwave channels) and are very close to the values obtained during the night. These improved capabilities in CRTM allow for effective uses of satellite data at short infrared wavelengths in data assimilation systems and in atmospheric soundings throughout the day and night. © 2013 American Meteorological Society. Source


Bi L.,University Corporation for Atmospheric Research | Jung J.A.,University of Wisconsin - Madison | Jung J.A.,Joint Center for Satellite Data Assimilation | Morgan M.C.,University of Wisconsin - Madison | Le Marshall J.F.,Center for Australian Weather and Climate Research
Monthly Weather Review | Year: 2011

A two-season Observing System Experiment (OSE) was used to quantify the impacts of assimilating the Advanced Scatterometer (ASCAT) surface winds product distributed by the European Organization for the Exploitation of Meteorological Satellites (EUMESAT) and the National Environmental Satellite, Data, and Information Service (NESDIS). The ASCAT wind retrievals were provided by the Royal Netherlands Meteorological Office (KNMI) and the 50-km resolution ASCAT products were assimilated. The impact of assimilating the ASCAT surface wind product in the National Centers for Environmental Prediction (NCEP) Global Data Assimilation/Global Forecast System (GDAS/GFS) was assessed by comparing the forecast results through 168 h for the months of August 2008 and January 2009. The NCEP GDAS/GFS was used, at a resolution of T382-64 layers, as the assimilation system and forecast model for these experiments. A control simulation utilizing all the data types assimilated in the operational GDAS was compared to an experimental simulation that added the ASCAT surface winds. Quality control procedures required to assimilate the ASCAT surface winds are discussed. Anomaly correlations (ACs) of geopotential height forecasts as well as geographic distribution of AC of geopotential height forecasts at 1000 and 500 hPa were evaluated for the control and experiment during both seasons. The geographical distribution of forecast impact (FI) on the wind and temperature fields near the surface is also presented. The results of this study showthat assimilation of the surfacewind retrievals fromtheASCAT sensor improve the NCEP GFS wind and temperature forecasts. A positive FI, which suggests the error growth of the experiment is slower than the control, has been realized in the NCEP GDAS/GFS wind and temperature forecasts through 24 h. The ASCAT experiment AC scores show modest forecast improvements from days 4 through 7. © 2011 American Meteorological Society. Source


Liu Z.,U.S. National Center for Atmospheric Research | Liu Q.,Joint Center for Satellite Data Assimilation | Lin H.-C.,U.S. National Center for Atmospheric Research | Schwartz C.S.,U.S. National Center for Atmospheric Research | And 2 more authors.
Journal of Geophysical Research: Atmospheres | Year: 2011

Assimilation of the Moderate Resolution Imaging Spectroradiometer (MODIS) total aerosol optical depth (AOD) retrieval products (at 550nm wavelength) from both Terra and Aqua satellites have been developed within the National Centers for Environmental Prediction (NCEP) Gridpoint Statistical Interpolation (GSI) three-dimensional variational (3DVAR) data assimilation system. This newly developed algorithm allows, in a one-step procedure, the analysis of 3-D mass concentration of 14 aerosol variables from the Goddard Chemistry Aerosol Radiation and Transport (GOCART) module. The Community Radiative Transfer Model (CRTM) was extended to calculate AOD using GOCART aerosol variables as input. Both the AOD forward model and corresponding Jacobian model were developed within the CRTM and used in the 3DVAR minimization algorithm to compute the AOD cost function and its gradient with respect to 3-D aerosol mass concentration. The impact of MODIS AOD data assimilation was demonstrated by application to a dust storm from 17 to 24 March 2010 over East Asia. The aerosol analyses initialized Weather Research and Forecasting/Chemistry (WRF/Chem) model forecasts. Results indicate that assimilating MODIS AOD substantially improves aerosol analyses and subsequent forecasts when compared to MODIS AOD, independent AOD observations from the Aerosol Robotic Network (AERONET) and Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) instrument, and surface PM10 (particulate matter with diameters less than 10m) observations. The newly developed AOD data assimilation system can serve as a tool to improve simulations of dust storms and general air quality analyses and forecasts. Copyright 2011 by the American Geophysical Union. Source

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