DOI: 10.5194/tc-14-4719-2020
论文题名: Scoring Antarctic surface mass balance in climate models to refine future projections
作者: Gorte T. ; Lenaerts J.T.M. ; Medley B.
刊名: Cryosphere
ISSN: 19940416
出版年: 2020
卷: 14, 期: 12 起始页码: 4719
结束页码: 4733
语种: 英语
英文关键词: climate change
; climate modeling
; CMIP
; data set
; discharge
; mass balance
; numerical model
; snow accumulation
; Antarctic Ice Sheet
; Antarctica
英文摘要: An increase in Antarctic Ice Sheet (AIS) surface mass balance (SMB) has the potential to mitigate future sea level rise that is driven by enhanced solid ice discharge from the ice sheet. For climate models, AIS SMB provides a difficult challenge, as it is highly susceptible to spatial, seasonal, and interannual variability. Here we use a reconstructed data set of AIS snow accumulation as "true" observational data, to evaluate the ability of the CMIP5 and CMIP6 suites of models in capturing the mean, trends, temporal variability, and spatial variability in SMB over the historical period (1850-2000). This gives insight into which models are most reliable for predicting SMB into the future. We found that the best scoring models included the National Aeronautics and Space Administration (NASA) GISS model and the Max Planck Institute (MPI) for Meteorology's model for CMIP5, as well as one of the Community Earth System Model v2 (CESM2) models and one MPI model for CMIP6. Using a scoring system based on SMB mean value, trend, and temporal variability across the AIS, as well as spatial SMB variability, we selected a subset of the top 10th percentile of models to refine 21st century (2000-2100) AIS-integrated SMB projections to 2274 ± 282 Gt yr-1, 2358 ± 286 Gt yr-1, and 2495 ± 291 Gt yr-1 for Representative Concentration Pathways (RCPs) 2.6, 4.5, and 8.5, respectively. We also reduced the spread in AIS-integrated mean SMB by 79 %, 79 %, and 74 % in RCPs 2.6, 4.5, and 8.5, respectively. Notably, we find that there is no improvement from CMIP5 to CMIP6 in overall score. In fact, CMIP6 performed slightly worse on average compared to CMIP5 at capturing the aforementioned SMB criteria. Our results also indicate that model performance scoring is affected by internal climate variability (particularly the spatial variability), which is illustrated by the fact that the range in overall score between ensemble members within the CESM1 Large Ensemble is comparable to the range in overall score between CESM1 model simulations within the CMIP5 model suite. We also find that a higher horizontal resolution does not yield to a conclusive improvement in score. © 2020 Royal Society of Chemistry. All rights reserved. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/164468
Appears in Collections: 气候变化与战略
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作者单位: Department of Atmospheric and Oceanic Sciences, University of Colorado, Boulder, CO, United States; Cryospheric Sciences Laboratory, National Aeronautics and Space Administration's, Goddard Space Flight Center, Greenbelt, MD, United States
Recommended Citation:
Gorte T.,Lenaerts J.T.M.,Medley B.. Scoring Antarctic surface mass balance in climate models to refine future projections[J]. Cryosphere,2020-01-01,14(12)