Inter-Calibrating SMMR, SSM/I and SSMI/S Data to Improve the Consistency of Snow-Depth Products in China

Long-term snow depth/snow water equivalent (SWE) products derived from passive microwave remote sensing data are fundamental for climatological and hydrological studies. However, the temporal continuity of the products is affected by the updating or replacement of passive microwave sensors or satellite platforms. In this study, we inter-calibrated brightness temperature (Tb) data obtained from the Special Sensor Microwave Imager (SSM/I) and the Special Sensor Microwave Imager/Sounder (SSMI/S). Then, we evaluated the consistency of the snow cover area (SCA) and snow depth derived from the Scanning Multichannel Microwave Radiometer (SMMR), SSM/I and SSMI/S. The results indicated that (1) the spatial pattern of the SCA derived from the SMMR and SSM/I data was more consistent after calibration than before; (2) the relative biases in the SCA and snow depth in China between the SSM/I and SSMI/S data decreased from 42.42% to 1.65% and from 66.18% to −1.5%, respectively; and (3) the SCA and snow depth derived from the SSM/I data carried on F08, F11 and F13 were highly consistent. To obtain consistent snow depth and SCA products, inter-sensor calibrations between SMMR, SSM/I and SSMI/S are important. In consideration of the snow data product continuation, we suggest that the brightness temperature data from all sensors be calibrated based on SSMI/S.

[1]  Dorothy K. Hall,et al.  Nimbus-7 SMMR derived global snow cover parameters , 1987 .

[2]  Julienne C. Stroeve,et al.  An Intercomparison of DMSP F11- and F13-Derived Sea Ice Products , 1998 .

[3]  Kenneth C. Jezek,et al.  Comparison of SMMR and SSM/I passive microwave data collected over Antarctica , 1993 .

[4]  Tiyip Tashpolat,et al.  Long‐term change of seasonal snow cover and its effects on river runoff in the Tarim River basin, northwestern China , 2009 .

[5]  Liu Shiyin,et al.  Snow Cover Distribution, Variability, and Response to Climate Change in Western China , 2006 .

[6]  Roger G. Barry,et al.  Changes in North American snowpacks for 1979–2007 detected from the snow water equivalent data of SMMR and SSM/I passive microwave and related climatic factors , 2010 .

[7]  Jouni Pulliainen,et al.  Mapping of snow water equivalent and snow depth in boreal and sub-arctic zones by assimilating space-borne microwave radiometer data and ground-based observations , 2006 .

[8]  Richard Kelly,et al.  The AMSR-E Snow Depth Algorithm: Description and Initial Results , 2009 .

[9]  Konrad Steffen,et al.  Comparison of brightness temperatures from SSMI instruments on the DMSP F8 and FII satellites for Antarctica and the Greenland ice sheet , 1995 .

[10]  Guangqian Wang,et al.  Spatiotemporal distribution of snow in eastern Tibet and the response to climate change , 2012 .

[11]  Thomas R. Karl,et al.  Observed Impact of Snow Cover on the Heat Balance and the Rise of Continental Spring Temperatures , 1994, Science.

[12]  T. Barnett,et al.  Potential impacts of a warming climate on water availability in snow-dominated regions , 2005, Nature.

[13]  B. Ramsay,et al.  The interactive multisensor snow and ice mapping system , 1998 .

[14]  Johannes J. Feddema,et al.  Role of snow and glacier melt in controlling river hydrology in Liddar watershed (western Himalaya) under current and future climate , 2012 .

[15]  Chris Derksen,et al.  Influence of Sensor Overpass Time on Passive Microwave-Derived Snow Cover Parameters , 2000 .

[16]  Norman C. Grody,et al.  Global identification of snowcover using SSM/I measurements , 1996, IEEE Trans. Geosci. Remote. Sens..

[17]  George H. Leavesley,et al.  Evaluation of gridded snow water equivalent and satellite snow cover products for mountain basins in a hydrologic model , 2006 .

[18]  Donald J. Cavalieri,et al.  Intersensor Calibration Between F13 SSMI and F17 SSMIS for Global Sea Ice Data Records , 2012, IEEE Geoscience and Remote Sensing Letters.

[19]  R. Armstrong,et al.  Snow depth derived from passive microwave remote-sensing data in China , 2008, Annals of Glaciology.

[20]  Hongjie Xie,et al.  Spatio-Temporal Change of Snow Cover and Its Response to Climate over the Tibetan Plateau Based on an Improved Daily Cloud-Free Snow Cover Product , 2014, Remote. Sens..

[21]  Liyun Dai,et al.  Cross-platform calibration of SMMR, SSM/I and AMSR-E passive microwave brightness temperature , 2010, International Symposium on Digital Earth.

[22]  Damon S. Hartley,et al.  Effects of seasonal snow on the growing season of temperate vegetation in China , 2013, Global change biology.

[23]  Xiaoli Chang,et al.  Prediction of permafrost changes in Northeastern China under a changing climate , 2011 .

[24]  Peter Toose,et al.  Development of a tundra-specific snow water equivalent retrieval algorithm for satellite passive microwave data , 2010 .

[25]  Chris Derksen,et al.  Identification of systematic bias in the cross-platform (SMMR and SSM/I) EASE-Grid brightness temperature time series , 2003, IEEE Trans. Geosci. Remote. Sens..

[26]  Parag S. Narvekar,et al.  Assessment of the NASA AMSR-E SWE Product , 2010, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[27]  Jian Wang,et al.  Snow depth and snow water equivalent estimation from AMSR-E data based on a priori snow characteristics in Xinjiang, China , 2012 .

[28]  Jiawen Ren,et al.  Initial estimate of the contribution of cryospheric change in China to sea level rise , 2011 .

[29]  A. Walker,et al.  Development of a cross-platform (SMMR and SSM/I) passive microwave derived snow water equivalent dataset for climatological applications , 2003, IGARSS 2003. 2003 IEEE International Geoscience and Remote Sensing Symposium. Proceedings (IEEE Cat. No.03CH37477).

[30]  K. Moffett,et al.  Remote Sens , 2015 .