Abstract

Spatial and temporal patterns of snow cover extent (SCE) and snow water equivalent (SWE) over the terrestrial Arctic are analyzed based on multiple observational datasets and an ensemble of CMIP5 models during 1979–2005. For evaluation of historical simulations of the Coupled Model Intercomparison Project (CMIP5) ensemble, we used two reanalysis products, one satellite-observed product and an ensemble of different datasets. The CMIP5 models tend to significantly underestimate the observed SCE in spring but are in better agreement with observations in autumn; overall, the observed annual SCE cycle is well captured by the CMIP5 ensemble. In contrast, for SWE, the annual cycle is significantly biased, especially over North America, where some models retain snow even in summer, in disagreement with observations. The snow margin position (SMP) in the CMIP5 historical simulations is in better agreement with observations in spring than in autumn, when close agreement across the CMIP5 models is only found in central Siberia. Historical experiments from most CMIP5 models show negative pan-Arctic trends in SCE and SWE. These trends are, however, considerably weaker (and less statistically significant) than those reported from observations. Most CMIP5 models can more accurately capture the trend pattern of SCE than that of SWE, which shows quantitative and qualitative differences with the observed trends over Eurasia. Our results demonstrate the importance of using multiple data sources for the evaluation of snow characteristics in climate models. Further developments should focus on the improvement of both dataset quality and snow representation in climate models, especially ESM-SnowMIP.

Highlights

  • Snow is a critical component of the Arctic climate system

  • Analysis of the CMIP5 ensemble spread in the estimates of snow cover extent (SCE) and snow water equivalent (SWE) is summarized in Tables 3 and 4, which present the long-term means over the terrestrial Arctic

  • We analyzed the representation of SCE (1979–2005) and SWE (1981–2005) in the Arctic during the onset (October–November) and melting season (March–April) in the historical runs of CMIP5 climate models on the basis of two reanalysis products, one satellite-observed product and an ensemble of different datasets

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Summary

Introduction

Snow is a critical component of the Arctic climate system. Over northern Eurasia and North America, the duration of snow cover ranges from 7 to 10 months per year (Brown et al 2017), with the maximum snow extent covering over 40% of the Northern Hemisphere land area (approximately 47 × 106 km2 ) each year Several studies have evaluated snow characteristics (SWE, SCE and snowfall) in climate models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) (Brutel-Vuilmet et al 2013; Kapnick and Delworth 2013; Terzago et al 2014; Connolly et al 2019). Snow regimes in autumn have received less attention than those in spring In this respect, the representation of snow-associated feedbacks in climate models, especially during the shoulder seasons (when Arctic snow cover exhibits the strongest variability), is of special importance. There is a need for a comprehensive evaluation of snow characteristics in climate models using available observations over the last decades to demonstrate which Arctic snow features are most robust across different models and which are not well represented.

Models and observational data sets
Preprocessing and methods
Snow cover extent
Snow water equivalent
Annual cycle
Snow margin position
Summary of evaluation of climatologies
Interannual variability of snow characteristics
Seasonal trend analysis
Findings
Summary and conclusion
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