A DYNAMIC WATER-VAPOR CORRECTION METHOD FOR THE RETRIEVAL OF LAND-SURFACE TEMPERATURES FROM THE ADVANCED VERY HIGH-RESOLUTION RADIOMETER

We present a method which permits retrievals of land surface temperatu res (LSTs) from AVHRR (advanced very high resolution radiometer) radia nces sensed through atmospheres which may contain a large and strongly varying water vapor content. This new method is an extension of the d ynamic water vapor (DWV) algorithm which was designed to retrieve sea surface temperatures. The generalization to LST retrievals recognizes that in general, land emissivities are unknown, may be spectrally depe ndent, and are less than unity. Because the LST retrieval problem is i nherently underconstrained (there are more unknowns than radiative tra nsfer equations), some knowledge of surface emissivity is required in order to establish upper and lower bounds on surface temperature. We d emonstrate our method by comparing DWV-LST retrievals with point surfa ce measurements made by a cluster of eight infrared thermometers (IRTs ) deployed over a grasslands prairie site in eastern Kansas in July an d August 1989; this deployment was part of the First International Sat ellite Land Surface Climatology Project (ISLSCP) Field Experiment (FIF E). We find that several of the AVHRR images supplied on FIFE CD-ROM c ontain navigation errors of similar to 30 km, consistent with a miside ntification of the Tuttle Reservoir ground control point. After correc ting the navigation, we identified the IRT pixels and computed the bia s and rms errors for a DWV-IRT comparison. For night passes we obtaine d agreement to +0.39+/-1.11 K, while for day passes the comparison yie lded +4.09+/-3.10 K. The large daytime bias is probably the result of the IRT readings not being representative of the similar to 1 km(2)-sc ale areas sensed by AVHRR (the IRT views vegetation; the AVHRR field o f view includes warmer, less well vegetated surfaces). Our results sho w that while a fixed-coefficient, global split-window algorithm does n ot perform well in the relatively moist FIFE atmosphere, it is quite f easible to use the DWV-LST to derive a local split-window algorithm wh ose coefficient is tuned on a per-pass basis.