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Open AccessJournal ArticleDOI

Faster Arctic sea ice retreat in CMIP5 than in CMIP3 due to volcanoes

TLDR
In this paper, the authors examine simulations from both CMIP3 and CMIP5 and find that simulated historical sea ice trends are influenced by volcanic forcing, which was included in all of the models but in only about half of the previous generation of models (CMIP3).
Abstract
The downward trend in Arctic sea ice extent is one of the most dramatic signals of climate change during recent decades. Comprehensive climate models have struggled to reproduce this, typically simulating a slower rate of sea ice retreat than has been observed. However, this bias has been widely noted to have decreased in models participating in the most recent phase of the Coupled Model Intercomparison Project (CMIP5) compared with the previous generation of models (CMIP3). Here we examine simulations from both CMIP3 and CMIP5. We find that simulated historical sea ice trends are influenced by volcanic forcing, which was included in all of the CMIP5 models but in only about half of the CMIP3 models. The volcanic forcing causes temporary simulated cooling in the 1980s and 1990s, which contributes to raising the simulated 1979-2013 global-mean surface temperature trends to values substantially larger than observed. We show that this warming bias is accompanied by an enhanced rate of Arctic sea ice retreat and hence a simulated sea ice trend that is closer to the observed value, which is consistent with previous findings of an approximately linear relationship between sea ice extent and global-mean surface temperature. We find that both generations of climate models simulate Arctic sea ice that is substantially less sensitive to global warming than has been observed. The results imply that the much of the difference in Arctic sea ice trends between CMIP3 and CMIP5 occurred due to the inclusion of volcanic forcing, rather than improved sea ice physics or model resolution.

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Journal ArticleDOI

Enhanced simulated early 21st century Arctic sea ice loss due to CMIP6 biomass burning emissions

TL;DR: In this paper , the authors show that variability in boreal biomass burning emissions strongly influences simulated Arctic sea ice on multidecadal time scales, and that more than half of the reported improvement in sea ice sensitivity to CO2 emissions and global warming from CMIP5 to CMIP6 can be attributed to the increased BB variability, at least in the CESM.
Journal ArticleDOI

Nudging observed winds in the Arctic to quantify associated sea ice loss from 1979 to 2020

TL;DR: In this article , a coupled high-resolution modeling framework with observed winds nudged over the Arctic was used to compare wind-induced effects with observations and simulated effects forced by anthropogenic forcing.
Journal ArticleDOI

Observed Winds Crucial for September Arctic Sea Ice Loss

TL;DR: In this paper , the authors find that atmospheric circulation plays a crucial role in September Arctic sea ice loss and sea ice interannual variability, and that trends in the observed atmospheric circulation that are not part of the modeled forced response cause approximately 20% to 25% of modeled September sea ice decline, in close agreement with the observed trend.
Journal ArticleDOI

An optimal atmospheric circulation mode in the Arctic favoring strong summertime sea ice melting and ice-albedo feedback

Ian Baxter, +1 more
- 28 Jun 2022 - 
TL;DR: In this article , a suite of simulations in which atmospheric circulation is constrained by nudging tropospheric Arctic (60-90°N) winds within the Community Earth System Model (CESM1) to those from reanalysis were conducted.
References
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Journal ArticleDOI

An Overview of CMIP5 and the Experiment Design

TL;DR: The fifth phase of the Coupled Model Intercomparison Project (CMIP5) will produce a state-of-the- art multimodel dataset designed to advance the authors' knowledge of climate variability and climate change.
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Global analyses of sea surface temperature, sea ice, and night marine air temperature since the late nineteenth century

TL;DR: HadISST1 as mentioned in this paper replaces the global sea ice and sea surface temperature (GISST) data sets and is a unique combination of monthly globally complete fields of SST and sea ice concentration on a 1° latitude-longitude grid from 1871.
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Global surface temperature change

TL;DR: The authors used satellite-observed night lights to identify measurement stations located in extreme darkness and adjust temperature trends of urban and periurban stations for nonclimatic factors, verifying that urban effects on analyzed global change are small.
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Arctic sea ice decline: Faster than forecast

TL;DR: In this paper, a multi-model ensemble mean time series provides a true representation of forced change by greenhouse gas (GHG) loading, 33-38% of the observed September trend from 1953-2006 is externally forced, growing to 47-57% from 1979-2006.
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Climate extremes indices in the CMIP5 multimodel ensemble: Part 1. Model evaluation in the present climate

TL;DR: In this article, the authors provide an overview of the performance of state-of-the-art global climate models participating in the Coupled Model Intercomparison Project Phase 5 (CMIP5) in simulating climate extremes indices defined by the Expert Team on Climate Change Detection and Indices (ETCCDI), and compare it to that in the previous model generation.
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