Seasonal, Diurnal, and Weather Related Variations of Clear Sky Land Surface Temperature: A Statistical Assessment
Konstantin Y. Vinnikov, University of Maryland, College Park, MD; and Y. Yu, M. K. Rama Varma Raja, J. D. Tarpley, and M. D. Goldberg
Geostationary satellites provide opportunity for long-term monitoring of temporal and spatial variations of clear sky Land Surface Temperature (LST). Such monitoring is an important component of the GOES-R satellites observational program. Clear sky LST is a relatively new variable for meteorologists and needs to be studied theoretically and empirically. The results of statistical assessment of seasonal, diurnal, and weather related components in observed variations of clear sky land surface temperature will be presented in this paper.
LSTs estimated from infrared broad-band (3 to 50 microns) upwelling and downwelling irradiance measurements at six sites of Surface Radiation Network (SURFRAD) over Contiguous United States during the year 2001 are used as ground truth. GOES-8 and GOES-10 hourly observed IR brightness temperatures in atmospheric thermal split window channels for pixels closest to the site locations are used to retrieve the clear sky LSTs. The LST algorithm applied in this study is developed by Yu et al. (Yu et al., 2007). Clear sky conditions have been determined using an original manual cloud screening technique (Rama Varma Raja et al., 2007). The first two harmonics of diurnal and annual cycles are used to approximate the expected value and the variance of clear sky land surface temperature. The technique is described in (Vinnikov et al., 2004. http:/www.atmos.umd.edu/~kostya/Pdf/arbitrary.grl.pdf).
We found that the largest components in temporal variation of the clear sky LST are annual and diurnal cycles. The ranges of these variations may exceed 25K. Systematic differences, up to a few degrees K, between satellite and surface-observed clear sky LST are discussed. The weather-related components of clear sky LST variability (residuals) are much smaller than the amplitudes of seasonal and diurnal variations. These residuals estimated for SURFRAD stations and for coincident satellite observations are correlated, with correlation coefficients of about 0.9. The root mean squared difference of satellite and SURFRAD observed residuals does not exceed 1.5K. This means that GOES satellites are able to monitor satisfactorily, the weather-related temporal variations of clear sky LST.
A physical nature of weather related variation of clear sky LST and its statistical properties will be discussed.
Poster Session 1, Fifth GOES Users' Confererence Poster Session
Wednesday, 23 January 2008, 2:30 PM-4:00 PM, Exhibit Hall B
Previous paper Next paper
Browse or search entire meeting
AMS Home Page