Algorithm update of the GOSAT/TANSO-FTS thermal infrared CO2 product (version 1) and validation of the UTLS CO2 data using CONTRAIL measurements

摘要

The Thermal and Near Infrared Sensor for Carbon Observation (TANSO)–FourierTransform Spectrometer (FTS) on board the Greenhouse Gases ObservingSatellite (GOSAT) has been observing carbon dioxide (CO)concentrations in several atmospheric layers in the thermal infrared (TIR)band since its launch. This study compared TANSO-FTS TIR version 1 (V1) CO dataand CO data obtained in the Comprehensive Observation Network forTRace gases by AIrLiner (CONTRAIL) project in the upper troposphere andlower stratosphere (UTLS), where the TIR band of TANSO-FTS is most sensitiveto CO concentrations, to validate the quality of the TIR V1 UTLSCO data from 287 to 162 hPa. We first evaluated the impact ofconsidering TIR CO averaging kernel functions on COconcentrations using CO profile data obtained by the CONTRAILContinuous CO Measuring Equipment (CME), and found that the impact ataround the CME level flight altitudes (∼ 11 km) was on averageless than 0.5 ppm at low latitudes and less than 1 ppm at middle and highlatitudes. From a comparison made during flights between Tokyo and Sydney,the averages of the TIR upper-atmospheric CO data were within 0.1 %of the averages of the CONTRAIL CME CO data with and without TIRCO averaging kernels for all seasons in the Southern Hemisphere. Theresults of comparisons for all of the eight airline routes showed that theagreements of TIR and CME CO data were worse in spring and summer thanin fall and winter in the Northern Hemisphere in the upper troposphere.While the differences between TIR and CME CO data were on averagewithin 1 ppm in fall and winter, TIR CO data had a negative bias up to2.4 ppm against CME CO data with TIR CO averaging kernels at thenorthern low and middle latitudes in spring and summer. The negative bias atthe northern middle latitudes resulted in the maximum of TIR COconcentrations being lower than that of CME CO concentrations, whichled to an underestimate of the amplitude of CO seasonal variation.