The two day session on Remote Sensing and Modeling of the Atmosphere and Oceans will focus on assessing the present status of satellite data assimilation, interpretation and validation of satellite remote sensing data, application to atmospheric and ocean modeling at different scales, from mesoscale to climate. The WIND LIDAR is being considered as an important forthcoming remote sensing instrument from satellites. Several data sets from different satellites are currently available for research on the impacts on the modeling of atmosphere and oceans. Some specific areas of interest for this workshop may include data and algorithms with regards to the sensors/missions such as AIRS/AQUA, HIRIS (NASA), METEOSAT, GOES, AQUA/TERRA-MODIA, NOAA Satellites, GOMOS, MIPAS, ENVISAT, DMSP, INSAT, KALPANA TRMM/ forthcoming GPM, CLOUDSAT,CALIPSO The focus will also be placed on data assimilation and model forecasts impacts where other international satellites data products are being used. Because of the major recognition of mesoscale for problems on hurricanes/typhoons, floods and extreme events arising from major rainstorms such as monsoon and related river basin scale hydrological budgets, newly emerging areas of mesoscale modeling and high resolution satellite data impacts will be encouraged. The list below on satellite platforms and data sets can serve as a guide for your paper presentation. Data from geostationary satellites (METEOSAT and GOES) and polar orbital satellites (AQUA/TERRA) are available from IR, VIS and WV (cloudy only, clear-sky only, or mixed) channels. Time series and maps of time-averaged mean fields are used to compute the atmospheric motion vectors. The following satellite datasets are currently used to monitor the atmospheric motion fields: METEOSAT_5,7,8, MTSAT_1, GOES 9,10,12, and MODIS. We also encourage papers on OSSES that address possible impacts from future satellite observing systems, especially the WIND LIDAR. Aerosol impacts from the direct and indirect effects, where models exploit the use of satellites data sets such as those from MODIS are also encouraged. There is considerable interest in the topic of moist rivers and heavy rains. This is also a topic that can invite a combination of modeling and remote sensing. Papers in this area are encouraged. We encourage both regional and global models including ensemble methodologies for addressing the impacts of new data sets from satellites.