HR: 0800h
AN: B21A-0026    [Abstracts]
TI: Comparison of Kriging and LOCFIT methods for interpolating gridded passive microwave brightness temperatures
AU: * Brodzik, M J
EM: brodzik@nsidc.org
AF: NSIDC/CIRES, University of Colorado at Boulder, 449 UCB, Boulder, CO 80309, United States
AU: Savoie, M H
EM: savoie@nsidc.org
AF: NSIDC/CIRES, University of Colorado at Boulder, 449 UCB, Boulder, CO 80309, United States
AU: Armstrong, R L
EM: rlax@nsidc.org
AF: NSIDC/CIRES, University of Colorado at Boulder, 449 UCB, Boulder, CO 80309, United States
AB: Satellite passive microwave brightness temperatures (TBs) are used as the basis for measuring various land surface properties, including soil moisture and snow water equivalent. The current satellite record of brightness temperatures includes data from the SMMR, SSM/I and AMSR-E instruments, beginning in 1978 and continuing to the present day. These sensors fly on satellite platforms in sun-synchronous, polar orbits, providing near-daily global coverage of the Earth. Due to the satellite geometry, surface locations at high latitudes receive better than daily coverage, while locations at lower latitudes are observed less frequently. We have compiled a nearly 30- year record of daily, gridded passive microwave temperatures, but the lack of daily coverage from the respective sensors makes the compilation of daily derived products complicated. Techniques we have used in the past have been performed after deriving the desired geophysical parameter, and have included last-in compilations and piecewise, linear interpolation of missing snow water equivalent between days with legitimate observations. The advantages of these methods are that they are relatively simple to implement, but they suffer from not making use of any known physical spatial correlations at the brightness temperature level with neighboring locations for the data being interpolated. Our study will compare two spatial interpolation methods at the gridded brightness temperature level that take advantage of spatial and temporal correlation: kriging methods and local polynomial (LOCFIT) fitting. Our study area includes a subset of Equal-Area Scalable Earth Grid (EASE-Grid) brightness temperatures, for a region that includes portions of the Western United States and Canada, for two weeks in both January and July, for the period of record. Results of this analysis will ultimately increase our skill in filling in the gaps in microwave coverage, thus improving existing gridded brightness temperature data sets and the geophysical products derived from them.
DE: 0700 CRYOSPHERE (4540)
DE: 0758 Remote sensing
SC: Biogeosciences [B]
MN: 2007 Fall Meeting