HR: 09:00h
AN: NG41A-05    [PDF]
TI: Mesoscale Variability, Representativeness of Meteorological Observations and Assimilation of Observations into models
AU: * Gage, K S
EM: Kenneth.S.Gage@noaa.gov
AF: NOAA Aeronomy Laboratory, 325 Broadway, Boulder, CO 80305-3337
AB: This review is concerned with issues related to the assimilation of meteorological observations into numerical models in the presence of mesoscale variability that may limit the representativeness of the observation on the resolution scale of the model. Models provide an essential tool for synthesizing diverse observations from many sources. They provide us with a means to specify the state of the atmosphere or ocean at any particular time and allow us to forecast the future state of the atmosphere or ocean. Observations assimilated into models may be in situ point measurements, remotely sensed direct measurements such as are provided by wind profilers, or indirect remotely Sensed measurements provided by satellites. While the issues considered in this review are very general, there is a pressing need to assimilate remotely sensed data into models. From developments in data assimilation it is well known that for optimal performance models require information on the error covariance of the parameter being measured. In general, this means information is required on the measurement error of instruments as well as the representativeness of the measurements themselves. The representativeness error is often the dominant component of error covariance. Specification of representativeness error requires knowledge of the variability of the field being measured.This review examines sources of mesoscale atmospheric variability and some means for specifying variability quantitatively.
DE: 3329 Mesoscale meteorology
DE: 3337 Numerical modeling and data assimilation
DE: 3360 Remote sensing
DE: 3394 Instruments and techniques
SC: Nonlinear Geophysics [NG]
MN: 2003 Fall Meeting