Articles | Volume 16, issue 3
Research article
15 Mar 2022
Research article |  | 15 Mar 2022

Evaluation of Northern Hemisphere snow water equivalent in CMIP6 models during 1982–2014

Kerttu Kouki, Petri Räisänen, Kari Luojus, Anna Luomaranta, and Aku Riihelä

Data sets

GlobSnow v3.0 snow water equivalent (SWE) Kari Luojus, Jouni Pulliainen, Matias Takala, Juha Lemmetyinen, and Mikko Moisander

Climate Data Dashboard of the ESA Climate Change Initiative European Space Agency

MERRA-2 tavg1_2d_lnd_Nx: 2d,1-Hourly,Time-Averaged,Single-Level,Assimilation,Land Surface Diagnostics V5.12.4 (M2T1NXLND) Global Modeling and Assimilation Office (GMAO)

MERRA-2 tavgM_2d_slv_Nx: 2d,Monthly mean,Time-Averaged,Single-Level,Assimilation,Single-Level Diagnostics V5.12.4 (M2TMNXSLV) Global Modeling and Assimilation Office (GMAO)

GPCC Full Data Monthly Product Version 2018 Udo Schneider, Andreas Becker, Peter Finger, Anja Meyer-Christoffer, and Markus Ziese

Short summary
We analyze state-of-the-art climate models’ ability to describe snow mass and whether biases in modeled temperature or precipitation can explain the discrepancies in snow mass. In winter, biases in precipitation are the main factor affecting snow mass, while in spring, biases in temperature becomes more important, which is an expected result. However, temperature or precipitation cannot explain all snow mass discrepancies. Other factors, such as models’ structural errors, are also significant.