REMOTE SENSING: Climate Modeling

Professor Daniel Kirk-Davidoff is leading research efforts in this exciting subject. Satellite climate observations offer broad and consistent spatial sampling, complementing surface-based observations, which may be compromised by correlations with anthropogenic or natural changes in surface conditions near observation sites, and which may be spatially biased by ease or difficulty of access to a given location on the surface.  However, imperfect temporal sampling introduces random errors (due to aperiodic weather noise) and biases that can substantially reduce the accuracy of satellite observations of the state of the atmosphere.   Selection of the number of satellites, their orbital configuration, and their scanning pattern all contribute to satellite sampling for climate studies.   Dr. Daniel Kirk-Davidoff is using geostationary satellite brightness temperature data as a proxy to determine the sensitivity of bias and random errors to the choice of orbit for LEO climate monitoring satellites.   He has shown that a single precessing polar orbiter is capable of producing very high accuracy annual mean brightness temperature records.