Impact Analysis of Climate Change on Snow over a Complex Mountainous Region Using Weather Research and Forecast Model (WRF) Simulation and Moderate Resolution Imaging Spectroradiometer Data (MODIS)-Terra Fractional Snow Cover Products

Xiaoduo Pan,Kuolin Hsu,Rensheng Chen,Guodong Cheng,Xin Li

doi:10.3390/rs9080774

Abstract

Climate change has a complex effect on snow at the regional scale. The change in snow patterns under climate change remains unknown for certain regions. Here, we used high spatiotemporal resolution snow-related variables simulated by a weather research and forecast model (WRF) including snowfall, snow water equivalent and snow depth along with fractional snow cover (FSC) data extracted from Moderate Resolution Imaging Spectroradiometer Data (MODIS)-Terra to evaluate the effects of climate change on snow over the Heihe River Basin (HRB), a typical inland river basin in arid northwestern China from 2000 to 2013. We utilized Empirical Orthogonal Function (EOF) analysis and Mann-Kendall/Theil-Sen trend analysis to evaluate the results. The results are as follows: (1) FSC, snow water equivalent, and snow depth across the entire HRB region decreased, especially at elevations over 4500 m; however, snowfall increased at mid-altitude ranges in the upstream area of the HRB. (2) Total snowfall also increased in the upstream area of the HRB; however, the number of snowfall days decreased. Therefore, the number of extreme snow events in the upstream area of the HRB may have increased. (3) Snowfall over the downstream area of the HRB decreased. Thus, ground stations, WRF simulations and remote sensing products can be used to effectively explore the effect of climate change on snow at the watershed scale.

Highlights

According to the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report, historical temperature records show that atmospheric temperatures increased up to 0.83 degreesCelsius from 1880 to 2012 [1]
The spatial distribution and the peak of fractional snow cover (FSC) extracted from the remote sensing data agree well with the variables simulated by the weather research and forecast model (WRF) model, which indicates that the satellite-retrieved data used in this study and that simulated by the model are both reasonable and effective
This study evaluated the effects of climate change on snow based on both the long-term high spatial-temporal resolution snowfall simulated by the WRF model and the long-term high spatial resolution monthly FSC attained by the Moderate Resolution Imaging Spectroradiometer Data (MODIS)-Terra product over the past 14 years, supplemented by temperature and precipitation data

Summary

Introduction

According to the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report, historical temperature records show that atmospheric temperatures increased up to 0.83 degreesCelsius from 1880 to 2012 [1]. Climate change is expected to accelerate the hydrologic cycle: as temperatures increase, a greater fraction of precipitation falls as rain rather than snow and more accumulated snowpack melts, resulting in greater runoff in the winter, less snowpack in the spring, and less runoff in the summer [2]. The enhanced hydrological cycle is expected to increase snowfall amounts through increased moisture availability [3]. Both Burnett et al [4] and Wright et al [5] have indicated that lake-effect snowfall increases along with temperatures over the Great Lakes, they used different methods to study the sensitivity of snowfall to climate change; the former used historical records of oxygen isotopes from the twentieth century, while the latter used the Advanced Research Weather Research and Forecasting Model (WRF-ARW).

Methods

Results

Discussion

Conclusion