21~(st) Century Atmospheric Forecasting for Space Based Applications

摘要

Many space based applications from imaging to communications are impacted by the atmosphere. Atmospheric impacts such as optical turbulence and clouds are the main drivers for these types of systems. For example, in space based optical communications, clouds will produce channel fades on the order of many hundreds of decibels (dB) thereby breaking the communication link. Optical turbulence can also produce fades but these can be compensated for by adaptive optics. The ability to forecast the current and future location and optical thickness of clouds for space to ground Electro Optical or optical communications is therefore critical in order to achieve a highly reliable system. We have developed an innovative method for producing such forecasts. These forecasts are intended to provide lead times on the order of several hours to days so that communication links can be transferred from a currently cloudy ground location to another more desirable ground site. The system uses high resolution Numerical Weather Prediction (NWP) along with a variational data assimilation (DA) scheme to improve the initial conditions and forecasts. DA is used to provide an improved estimate of the atmospheric state by combining meteorological observations with NWP products and their respective error statistics. Variational DA accomplishes this through the minimization of a prescribed cost function, whereby differences between the observations and analysis are damped according to their perceived error. The NWP model is a fully three-dimensional (3D) physics-based model of the atmosphere initialized with gridded atmospheric data obtained from a global scale model. The global model input data has a horizontal resolution of approximately 25km, which is insufficient for the desired atmospheric forecasts required at near 1km resolution. Therefore, a variational DA system is used to improve the quality and resolution of the initial conditions first prescribed by the global model. Data used by the DA system are local surface observations of temperature, pressure, winds and moisture (also known as the Standard Meteorological Variables, SMV), local vertical soundings of SMV, and local radar reflectivities from the National Weather Service NEXRAD radar network. A series of DA experiments have been set up and conducted on the Maui High Performance Computing System, Riptide supercomputer. Initial results show a marked improvement of the cloud and optical turbulence forecasts over the control run without data assimilation. Detailed results will be presented at the conference.