Abstract
Abstract. The 2015 Paris Agreement set a goal to pursue a global mean temperature below 1.5 °C and well below 2 °C above preindustrial levels. Although it is an important surface hydrology variable, the response of snow under different warming levels has not been well investigated. This study provides a comprehensive assessment of the snow cover fraction (SCF) and snow area extent (SAE), as well as the associated land surface air temperature (LSAT) over the Northern Hemisphere (NH) based on the Community Earth System Model Large Ensemble project (CESM-LE), the CESM 1.5 and 2 °C projects, and the CMIP5 historical RCP2.6 and RCP4.5 products. The results show that the spatiotemporal variations in those modeled products are grossly consistent with observations. The projected SAE magnitude change in RCP2.6 is comparable to that in 1.5 °C, but lower than that in 2 °C. The snow cover differences between 1.5 and 2 °C are prominent during the second half of the 21st century. The signal-to-noise ratios (SNRs) of both SAE and LSAT over the majority of land areas are greater than 1, and for the long-term period, the dependences of SAE on LSAT changes are comparable for different ensemble products. The contribution of an increase in LSAT to the reduction of snow cover differs across seasons, with the greatest occurring in boreal autumn (49–55 %) and the lowest occurring in boreal summer (10–16 %). The snow cover uncertainties induced by the ensemble variability are invariant over time across CESM members but show an increase in the warming signal between the CMIP5 models. This feature reveals that the physical parameterization of the model plays the predominant role in long-term snow simulations, while they are less affected by internal climate variability.
Highlights
Snow mass on the ground is one of the most important surface hydrology elements
Based on the previously mentioned Community Earth System Model (CESM) simulations, CMIP5 model outputs, and the observed snow cover fraction datasets, this study extensively investigates the spatiotemporal change in snow cover over the Northern Hemisphere (NH) land area for both historical (1920–2005) and future (2006–2100) periods under 1.5 and 2.0 ◦C warming levels, as well as under RCP2.6 and RCP4.5 scenarios
We find that the ensemble annual mean snow cover fraction (SCF) from both CMIP5 and Community Earth System Model Large Ensemble project (CESM-large ensemble (LE)) simulations can broadly capture the MODIS spatial pattern, with a slight underestimation in CMIP5 and an overestimation in CESM-LE
Summary
Snow mass on the ground is one of the most important surface hydrology elements. Due to its unique physical properties, such as high albedo, emissivity and absorptivity, low thermal conductivity, and roughness length, snow strongly affects the energy and water exchange between land and atmosphere over cold regions (Zhang, 2005). To achieve 1.5 and 2.0 ◦C goals in line with the IPCC special report, the Community Earth System Model (CESM) research group at the National Center for Atmospheric Research (NCAR) has performed a set of ensemble modeling experiments under the emulated concentration pathway leading to the stable 1.5 and 2 ◦C warming targets by 2100 (Sanderson et al, 2017). Based on the previously mentioned CESM simulations, CMIP5 model outputs, and the observed snow cover fraction datasets, this study extensively investigates the spatiotemporal change in snow cover over the NH land area for both historical (1920–2005) and future (2006–2100) periods under 1.5 and 2.0 ◦C warming levels, as well as under RCP2.6 and RCP4.5 scenarios. A prominent advantage is that the CESM ensemble simulations provide insight into the impacts of internal climate variability on those surface variables, which is addressed in this study
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