TY - JOUR
T1 - A new approach to satellite-based estimation of precipitation over snow cover
AU - Tian, Yudong
AU - Liu, Yuqiong
AU - Arsenault, Kristi R.
AU - Behrangi, Ali
N1 - Funding Information:
This research was supported by the NASA Earth System Data Records Uncertainty Analysis Program (Martha E. Maiden) [grant number NNX11AO22G].
PY - 2014/7
Y1 - 2014/7
N2 - Current satellite-based remote-sensing approaches are largely incapable of estimating precipitation over snow cover. This note reports a proof-of-concept study of a new satellite-based approach to the estimation of precipitation over snow-covered surfaces. The method is based on the principle that precipitation can be inferred from the changes in the snow water equivalent of the snowpack. Using satellite-based snow water equivalent measurements, we derived daily precipitation amounts for the northern hemisphere for three snow-accumulation seasons, and evaluated these against independent reference datasets. The new precipitation estimates captured realistic-looking storm events over largely un-instrumented regions. However, the data are noisy and, on a seasonal scale, the amount of precipitation is believed to be underestimated. Nevertheless, current uncertainty in snow measurements, albeit large (50-100%), is still lower than direct precipitation measurements over snow (100-140%) and therefore this approach is still useful. The method will become more feasible as the quality of remotely sensed snow measurements improves.
AB - Current satellite-based remote-sensing approaches are largely incapable of estimating precipitation over snow cover. This note reports a proof-of-concept study of a new satellite-based approach to the estimation of precipitation over snow-covered surfaces. The method is based on the principle that precipitation can be inferred from the changes in the snow water equivalent of the snowpack. Using satellite-based snow water equivalent measurements, we derived daily precipitation amounts for the northern hemisphere for three snow-accumulation seasons, and evaluated these against independent reference datasets. The new precipitation estimates captured realistic-looking storm events over largely un-instrumented regions. However, the data are noisy and, on a seasonal scale, the amount of precipitation is believed to be underestimated. Nevertheless, current uncertainty in snow measurements, albeit large (50-100%), is still lower than direct precipitation measurements over snow (100-140%) and therefore this approach is still useful. The method will become more feasible as the quality of remotely sensed snow measurements improves.
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U2 - 10.1080/01431161.2014.930208
DO - 10.1080/01431161.2014.930208
M3 - Article
AN - SCOPUS:84905021430
SN - 0143-1161
VL - 35
SP - 4940
EP - 4951
JO - International Journal of Remote Sensing
JF - International Journal of Remote Sensing
IS - 13
ER -