Abstract
The long-term variations in snow depth are important in hydrological, meteorological, and ecological implications and climatological studies. The series of Special Sensor Microwave/Imager (SSM/I) and Special Sensor Microwave Imager Sounder (SSMIS) instruments onboard the Defense Meteorological Satellite Program (DMSP) platforms has provided a consistent 30+ year data record of global observations that is well-suited for the estimation of snow cover, snow depth, and snow water equivalent (SWE). To maximize the use of this continuous microwave observation dataset in long-term snow analysis and obtain an objective result, consistency among the SSM/I and SSMIS sensors is required. In this paper, we evaluated the consistency between the SSM/I and SSMIS concerning the observed brightness temperature (Tb) and the retrieved snow cover area and snow depth from January 2007 to December 2008, where the F13 SSM/I and the F17 SSMIS overlapped. Results showed that Tb bias at 19 GHz spans from −2 to −3 K in snow winter seasons, and from −4 to −5 K in non-snow seasons. There is a slight Tb bias at 37 GHz from −2 to 2 K, regardless of season. For 85 (91) GHz, the bias presents some uncertainty from the scattering effect of the snowpack and atmospheric emission. The overall consistency between SSM/I and SSMIS with respect to snow cover detection is between 80% and 100%, which will result in a maximum snow cover area difference of 25 × 104 km2 in China. The inconsistency in Tb between SSM/I and SSMIS can result in a −2 and −0.67 cm snow depth bias for the dual-channel and multichannel algorithms, respectively. SSMIS tends to yield lower snow depth estimates than SSM/I. Moreover, there are notable bias differences between SSM/I- and SSMIS-estimated snow depths in the tundra and taiga snow classes. Our results indicate the importance of considering the Tb bias in microwave snow cover detection and snow depth retrieval and point out that, due to the sensitivity of bias to seasons, it is better to do the intercalibration with a focus on snow-covered winter seasons. Otherwise, the bias in summer will disturb the calibration coefficients and introduce more error into the snow retrievals if the seasonal difference is not carefully evaluated and separated.
Highlights
Seasonal snow covers a considerable portion of the land in the Northern Hemisphere during winter [1,2]
Only pixels where ground-measured snow depths are greater than 3 cm are considered as snow cover
We evaluated the consistency in satellite Tb, snow cover detection, and snow depth esIntimthaitsiosntufdroym, wdeiffeevraelnutagteednetrhaeticoonnssoisftseenncsyorins cthoavtehr addetteecmtipoonr,aalnadndsnsopwatidael pth estimovaetriloanp.frRoemsuldtsifdfeermenont sgterantertahtaiot naslthoofusgehnsthoersSS(SMS/MI a/nI dvsS.SMSSIMS sIeSn) stohrastahreadsimteimlarp, othrearleaanrde sstpillatial overdliaffpe.reRnecseus litnstderemmsoonfstthreatoebstheravteadltThbosucgauhsethdebSyStMhe/irI dainffderSenStMcaISlibsreantisoonrspraorceedsiumreisl,airn,ttehrperoelaatiroenstill diffemreetnhcoedss,ianndtesremnssorosfpetchieficaotbiosnersv. eFdortTubnsateclay,utsheedbibaysesthbeetiwr edeniffSeSrMen/tI acnadlibSSraMtiIoSnareprroelcaetdedures, intetroposelaastioonns,mweitthhoredlsa,tiavnedlysgeonosdorcosnpseicstiefinccaytiionnssn. oFworwtuinnatetrelsye,asthonesbaiagsaeinssbt entowne-sennoSwSsMea/Isoannsd
Summary
Seasonal snow covers a considerable portion of the land in the Northern Hemisphere during winter [1,2]. It plays an important role in the Earth’s hydrological cycle, energy balance, and climate system [1,2,3,4]. It can be used to provide nearly real-time snow cover data [5,6,16,17]. These advantages make SWE estimation from satellite PMW remote sensing an attractive option
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
