Air quality has become a social issue that is causing great concern to humankind across the globe, but particularly in developing countries. Even though the Weather Research and Forecasting with Chemistry (WRF-Chem) model has been applied in many regions, the resolution for inputting meteorology field analysis still impacts the accuracy of forecast. This article describes the application of the CIMSS Regional Assimilation System (CRAS) in East China, and its capability to assimilate the direct broadcast (DB) satellite data for obtaining more detailed meteorological information, including cloud top pressure (CTP) and total precipitation water (TPW) from MODIS. Performance evaluation of CRAS is based on qualitative and quantitative analyses. Compared with data collected from ERA-Interim, Radiosonde, and the Tropical Rainfall Measuring Mission (TRMM) precipitation measurements using bias and Root Mean Square Error (RMSE), CRAS has a systematic error due to the impact of topography and other factors; however, the forecast accuracy of all elements in the model center area is higher at various levels. The bias computed with Radiosonde reveals that the temperature and geopotential height of CRAS are better than ERA-Interim at first guess. Moreover, the location of the 24 h accumulated precipitation forecast are highly consistent with the TRMM retrieval precipitation, which means that the performance of CRAS is excellent. In summation, the newly built Vtable can realize the function of inputting the meteorology field from CRAS output into WRF, which couples the CRAS with WRF-Chem. Therefore, this study not only provides for forecast accuracy of CRAS, but also increases the capability of running the WRF-Chem model at higher resolutions in the future.
Significant improvements have been made to the MODIS cloud mask (MOD35) in preparation for Collection 5 reprocessing and forward stream data production. Most of the modifications are realized for nighttime scenes where polar and oceanic regions will see marked improvement. For polar night scenes, two new spectral tests using the 7.2 μm water vapor absorption band have been added as well as updates to the 3.9-12 μm and 11-12 μm cloud tests. More non-MODIS ancillary data has been added for nighttime processing. Land and sea surface temperature maps provide crucial information for middle and low-level cloud detection and lessen dependence on ocean variability tests. Sun-glint areas are also improved by use of sea surface temperatures to aid in resolving observations with conflicting cloud vs. clear-sky signals, where visible and NIR reflectances are high, but infrared brightness temperatures are relatively warm. Details and examples of new and modified cloud tests are shown and various methods employed to evaluate the new cloud mask results. Day vs. night sea surface temperatures derived from MODIS radiances and using only the MODIS cloud mask for cloud screening are contrasted. Frequencies of cloud from sun-glint regions will be shown as a function of sun-glint angle to gain a sense of cloud mask quality in those regions.
The 36 channel Moderate Resolution Imaging Spectroradiometer (MODIS) offers the opportunity for multispectral approaches to cloud detection. The MODIS cloud mask developed at the Cooperative Institute for Meteorological Satellite Studies (CIMSS) uses several cloud detection tests to indicate a level of confidence that the MODIS is observing clear skies. The MODIS cloud mask algorithm identifies several conceptual domains according to surface type and solar illumination, including land, water, snow/ice, desert, and coast for both day and night. The updated cloud mask has many improvements, such as improved cloud/surface discrimination over desert regions, sun glint processing and thin cirrus detection. For non-snow-covered land areas, a clear sky confidence of 0.96 (probably clear) will be assigned if thresholds are met for three tests: 3.9-11 μm and 3.75-3.9 μm brightness temperature differences and a 1.24/0.55 μm reflectance ratio test. Values of these must be <15K, <11K and >2.0, respectively. A change has been made to the NIR (band 2) reflectance test for sun glint processing. The updated method is to calculate a cloud threshold as a linear function of sun-glint angle in three separate ranges. A new clear-sky restoral test was added where the ratio of band 17/18 reflectance is utilized to discriminate between low clouds and water surfaces. The thin cirrus thresholds using corrected band 26 (1.38 μm) reflectances were also modified.
The algorithm for retrieving atmospheric temperature, moisture, and total column ozone using the Moderate Resolution Imaging Spectroradiometer (MODIS) longwave infrared radiances is presented. The operational MODIS algorithm performs clear sky retrievals globally over land and ocean for both day and night. The algorithm is based on a regression and has an option to follow the statistical retrieval with a nonlinear physical retrieval. The regression coefficients are determined from an extension of the NOAA-88 data set containing more than 8400 global radiosonde measurements of atmospheric temperature, moisture and ozone profiles. Evaluation of atmospheric products is performed by a comparison with data from
ground-based instrumentation, geostationary infrared sounders, and polar orbiting microwave sounders. MODIS moisture products are in general agreement with the gradients and distributions from the other satellites, while MODIS depicts more detailed structure with its improved spatial resolution.
The MODerate resolution Imaging Spectroradiometer (MODIS) instrument provides high spatial and spectral resolution views of each point on the earth four times per day. Both Terra and Aqua platforms have a direct broadcast X-band downlink that allows MODIS (Terra) and MODIS/AIRS (Aqua) data to be received in real time by sites having the proper reception hardware. In order to facilitate use of the data, science production software is being freely distributed through the International MODIS/AIRS processing package (IMAPP). The current suite of IMAPP MODIS products includes navigation and calibration (L1B), cloud mask and cloud top properties, including thermodynamic phase, and atmospheric profiles and water vapor retrievals. The applications have been modified from the operational versions running at the Goddard Distributed Active Archive Center (DAAC) such that the only required external toolkit is NCSA HDF4. Distribution of this software provides scientists around the world with the capability to produce local real-time high spatial resolution science products. MODIS data produced from the University of Wisconsin direct broadcast automated processing is used for a variety of science applications, including calibration and product validation. The data is also being used by other institutions for a range of purposes including assisting USA National Weather Service forecasters and the monitoring of Hudson Bay shipping routes by the Canadian Ice Service. The science software is being implemented globally from Australia to South America. IMAPP has been successful in providing a portable, relatively easy to install and user friendly software package for converting direct broadcast MODIS data into valuable science products.
Several MODIS cloud product algorithms are being developed at the University of Wisconsin for the generation of day-1 products after the launch of MODIS. MODIS Airborne Simulator (MAS) radiometric data collected form NASA's ER-2 platform is being used to simulate MODIS spectral bands for testing and refinement of the cloud product algorithms. Spectral characterization is an important component of the MAS calibration. MAS LWIR bands are spectrally characterized in ambient conditions using a monochromator and are corrected for source spectral shape and atmospheric attenuation. An atmospheric correction based on LBLRTM forward model transmittances demonstrates that strong spectral absorption features, such as Q-branch CO<SUB>2</SUB> absorption near 13.9 micrometers , are effectively removed from the spectral measurements with the aid of a small spectral position correction. Comparisons of MAS in-flight data to well- calibrated HIS instrument data indicate that MAS LWIR spectral calibration drift over time is less than 5 percent of FWHM. The MODIS CO<SUB>2</SUB> cloud top height retrieval shows small dependence on the spectral characterization, with retrieved cloud top height changing by less than 0.5 km in response to a 5 percent spectral position change. This is within the tolerance of other error sources in the cloud top properties algorithm.