Uncertainties of satellite-derived surface skin temperatures in the polar oceans: MODIS, AIRS/AMSU, and AIRS only

Abstract

Abstract. Uncertainties in the satellite-derived surface skin temperature (SST) data in the polar oceans during two periods (16-24 April and 15-23 September) 2003-2014 were investigated and the three data sets were intercompared as follows: MODerate Resolution Imaging Spectroradiometer Ice Surface Temperature (MODIS IST), the SST of the Atmospheric Infrared Sounder/Advanced Microwave Sounding Unit-A (AIRS/AMSU), and AIRS only. The AIRS only algorithm was developed in preparation for the degradation of the AMSU-A. MODIS IST was systematically warmer up to 1.65 K at the sea ice boundary and colder down to −2.04 K in the polar sea ice regions of both the Arctic and Antarctic than that of the AIRS/AMSU. This difference in the results could have been caused by the surface classification method. The spatial correlation coefficient of the AIRS only to the AIRS/AMSU (0.992-0.999) method was greater than that of the MODIS IST to the AIRS/AMSU (0.968-0.994). The SST of the AIRS only compared to that of the AIRS/AMSU had a bias of 0.168 K with a RMSE of 0.590 K over the Northern Hemisphere high latitudes and a bias of −0.109 K with a RMSE of 0.852 K over the Southern Hemisphere high latitudes. There was a systematic disagreement between the AIRS retrievals at the boundary of the sea ice, because the AIRS only algorithm utilized a less accurate GCM forecast over the seasonally varying frozen oceans than the microwave data. The three data sets (MODIS, AIRS/AMSU and AIRS only) showed significant warming rates (2.3 ± 1.7 ∼ 2.8 ± 1.9 K decade −1 ) in the northern high regions (70-80 • N) as expected from the icealbedo feedback. The systematic temperature disagreement associated with surface type classification had an impact on the resulting temperature trends.

Observed differences between near-surface air and skin temperatures using satellite and ground-based data

“…Recently, Sheng et al (2017) investigated the spatio-temporal relationship between T a and T s and its dependence on land cover types and elevation comprehensively over the southeastern China. T s estimates from the MODIS were compared with other satellite-based estimates (Lee et al, 2013;Urban et al, 2013;Kang et al, 2015), however the evaluation of T s and T a products from the Aqua satellite against ground-based observations is rather lacking. Furthermore, the quantification of differences among T s , T a , and upper-layer soil temperature is crucial for a wide range of applications (Gallo et al, 2011;Moncet et al, 2011;Norouzi et al, 2015;Prakash et al, 2017;Shati et al, 2018).…”