Evaluation of surface albedo over the Tibetan Plateau simulated by CMIP5 models using in‐situ measurements and MODIS
Author(s) -
An Yingying,
Meng Xianhong,
Zhao Lin,
Li Zhaoguo,
Wang Shaoying,
Shang Lunyu,
Chen Hao,
Lyu Shihua
Publication year - 2022
Publication title -
international journal of climatology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.58
H-Index - 166
eISSN - 1097-0088
pISSN - 0899-8418
DOI - 10.1002/joc.7281
Subject(s) - albedo (alchemy) , environmental science , climatology , snow , atmospheric sciences , coupled model intercomparison project , plateau (mathematics) , climate model , meteorology , climate change , geology , geography , art , mathematical analysis , oceanography , mathematics , performance art , art history
Abstract Surface albedo plays a key role in the energy and water cycles, and reasonable parameterizations of surface albedo will be greatly helpful to improve the simulation of radiation partition in climate models. In‐situ measurements of albedo from five sites over the Tibetan Plateau (TP) and MODIS albedo product are used to evaluate monthly, annual, and seasonal variations of the surface albedo simulated by 24 Global Climate Models (GCMs) archived by the Coupled Model Intercomparison Project Phase 5 (CMIP5). Potential factors contributing to the bias of simulated albedo were investigated. The results show that the monthly albedo of 24 GCMs varied across models, and the difference among the models was smaller in the June–July–August period than the December–January–February period. The ensemble mean albedo of the 24 GCMs was more consistent with the in‐situ measurements than the individual model. The albedo calculated from the BNU‐ESM, GFDL‐CM3, INM‐CM4, MIROC4h, MIROC‐ESM, and MIROC‐ESM‐CHEM models coincided with the observations from June to September, increasing rapidly to above 0.4 from November. However, the annual cycle of surface albedo was insignificant when simulated by some models, such as CanESM2, CSIRO‐Mk3.6.0, CMCC‐CMS, IPSL‐CM5A‐MR, and MPI‐ESM‐MR. Additionally, the surface albedo was overestimated by CMIP5 multi‐model ensemble mean—with a smaller amplitude of daily albedo—compared with the values estimated from in‐situ observations and MCD43A3. In all 24 models, snow albedo parameterization schemes were found to variably fit the attenuation of snow albedo over time. The cold temperature, relatively more precipitation, fresh snow density, and albedo in these models led to large biases in snow depth and ablation. The surface albedo tends to increase without the influence of blowing snow and withered grass on the model's albedo.