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

Liyun Dai,Yongjian Ding,Tao Che

doi:10.3390/rs70607212

Abstract

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.

Highlights

Snow cover is an important indicator for climate change and the main source of fresh water in arid and semiarid regions [1,2,3]
When the calibration results were used in the snow cover area (SCA) and snow depth product retrieval in China, the relative biases of the SCA and snow volume during the short overlap time between F08 and the Scanning Multichannel Microwave Radiometer (SMMR) decreased from 134.9% and 112.3% to −33.1% and −29.2%, respectively, after the calibration based on group one of the calibration results and to −32.2% and −43.7% based on group two of the calibration results, respectively
We inter-calibrated the brightness temperatures from Sensor Microwave Imager (SSM/I)(F13) and Sensor Microwave Imager/Sounder (SSMI/S)(F17), and we evaluated the consistency of the snow cover area (SCA) and snow depth products in China derived from SMMR, SSM/I and SSMI/S data

Summary

Introduction

Snow cover is an important indicator for climate change and the main source of fresh water in arid and semiarid regions [1,2,3]. Long-term snow datasets are fundamental to climatological and hydrological studies. The snow water equivalent (SWE) or snow depth is a key variable in hydrological models [6,7]. Passive microwave (PMW) remote sensing is the most efficient method of retrieving snow depth or SWE data on a regional or global scale due to its ability to penetrate clouds and its high temporal resolution. There are three daily PMW SWE or snow depth products covering China: the global SWE product from the National Snow and Ice Data Center (NSIDC) [8,9], the Northern

Results

Discussion

Conclusion