Short-Lived Climate Forcers over the Arctic between 1995 and 2015 as simulated by the GISS modelE2.1

2020 ◽  
Author(s):  
Ulas Im ◽  
Kostas Tsigaridis ◽  
Cynthia H. Whaley ◽  
Gregory S. Faluvegi ◽  
Zbigniew Klimont ◽  
...  
Keyword(s):  
Coupled Model ◽  
The Arctic ◽  
Mixing State ◽  
State Matrix ◽  
Microphysics Scheme ◽  
Natural Emissions ◽  
Intercomparison Project ◽  
The One ◽  
Goddard Institute ◽  
Space Sciences

<p>The Arctic Monitoring and Assessment Programme (AMAP) is currently assessing the impacts of Short-Lived Climate Forcers (SLCF) on Arctic climate and air quality. In support of the assessment, we used the NASA Goddard Institute of Space Sciences (GISS) Earth System Model (modelE2.1), with prescribed sea surface temperature and sea-ice fraction, to simulate SLCF concentrations globally between 1995 and 2015. Two simulations were conducted, using the One-Moment Aerosol (OMA) and the Multiconfiguration Aerosol TRacker of mIXing state (MATRIX) aerosol modules. OMA is a mass-based scheme in which aerosols are assumed to remain externally mixed and have a prescribed and constant size distribution, while MATRIX is an aerosol microphysics scheme based on the quadrature method of moments, which is able to explicitly simulate the mixing state of aerosols. Anthropogenic emissions from the ECLIPSE v6b emissions database were used, along with emissions from aircrafts and open biomass burning from the Coupled Model Intercomparison Project Phase 6 (CMIP6), while the natural emissions of sea salt, DMS, isoprene and dust are calculated interactively. The simulated monthly surface concentrations of sulfate (SO<sub>4</sub>), black carbon (BC), organic carbon (OA), and ozone (O<sub>3</sub>) are compared with observations from a set of Arctic stations, extracted from the EBAS and IMPROVE databases, as well as a few additional locations. Simulated aerosol optical depths (AOD) are also compared with Advanced Very-High Resolution Radiometer (AVHRR). The study will present the evaluation of the modelE2.1 in simulating SLCF levels over the Arctic using different aerosol schemes, along with observed and simulated trends of SLCFs over the Arctic between 1995 and 2015.</p><div> <div> <div> </div> </div> </div>

Greenhouse-gas contribution to Arctic sea-ice loss

2021 ◽  
Author(s):  
Yeon-Hee Kim ◽  
Seung-Ki Min
Keyword(s):  
Sea Ice ◽  
Greenhouse Gas ◽  
Coupled Model ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Detection Analysis ◽  
External Forcings ◽  
Arctic Sea ◽  
Intercomparison Project ◽  
Arctic Sea Ice Loss

<p>Arctic sea-ice area (ASIA) has been declining rapidly throughout the year during recent decades, but a formal quantification of greenhouse gas (GHG) contribution remains limited. This study conducts an attribution analysis of the observed ASIA changes from 1979 to 2017 by comparing three satellite observations with the Coupled Model Intercomparison Project Phase 6 (CMIP6) multi-model simulations using an optimal fingerprint method. The observed ASIA exhibits overall decreasing trends across all months with stronger trends in warm seasons. CMIP6 anthropogenic plus natural forcing (ALL) simulations and GHG-only forcing simulations successfully capture the observed temporal trend patterns. Results from detection analysis show that ALL signals are detected robustly for all calendar months for three observations. It is found that GHG signals are detectable in the observed ASIA decrease throughout the year, explaining most of the ASIA reduction, with a much weaker contribution by other external forcings. We additionally find that the Arctic Ocean will occur ice-free in September around the 2040s regardless of the emission scenario.</p>

scholarly journals Intercomparison of temperature trends in IPCC CMIP5 simulations with observations, reanalyses and CMIP3 models

2013 ◽  
Vol 6 (5) ◽  
pp. 1705-1714 ◽  
Author(s):  
J. Xu ◽  
L. Zhao ◽  
Keyword(s):  
Coupled Model ◽  
Temperature Trend ◽  
The Arctic ◽  
Cmip5 Models ◽  
Model Intercomparison ◽  
Model Simulations ◽  
Temperature Trends ◽  
Intercomparison Project ◽  
Stratospheric Cooling ◽  
The Tropics

Abstract. On the basis of the fifth Coupled Model Intercomparison Project (CMIP5) and the climate model simulations covering 1979 through 2005, the temperature trends and their uncertainties have been examined to note the similarities or differences compared to the radiosonde observations, reanalyses and the third Coupled Model Intercomparison Project (CMIP3) simulations. The results show noticeable discrepancies for the estimated temperature trends in the four data groups (radiosonde, reanalysis, CMIP3 and CMIP5), although similarities can be observed. Compared to the CMIP3 model simulations, the simulations in some of the CMIP5 models were improved. The CMIP5 models displayed a negative temperature trend in the stratosphere closer to the strong negative trend seen in the observations. However, the positive tropospheric trend in the tropics is overestimated by the CMIP5 models relative to CMIP3 models. While some of the models produce temperature trend patterns more highly correlated with the observed patterns in CMIP5, the other models (such as CCSM4 and IPSL_CM5A-LR) exhibit the reverse tendency. The CMIP5 temperature trend uncertainty was significantly reduced in most areas, especially in the Arctic and Antarctic stratosphere, compared to the CMIP3 simulations. Similar to the CMIP3, the CMIP5 simulations overestimated the tropospheric warming in the tropics and Southern Hemisphere and underestimated the stratospheric cooling. The crossover point where tropospheric warming changes into stratospheric cooling occurred near 100 hPa in the tropics, which is higher than in the radiosonde and reanalysis data. The result is likely related to the overestimation of convective activity over the tropical areas in both the CMIP3 and CMIP5 models. Generally, for the temperature trend estimates associated with the numerical models including the reanalyses and global climate models, the uncertainty in the stratosphere is much larger than that in the troposphere, and the uncertainty in the Antarctic is the largest. In addition, note that the reanalyses show the largest uncertainty in the lower tropical stratosphere, and the CMIP3 simulations show the largest uncertainty in both the south and north polar regions.

scholarly journals Evaluating permafrost physics in the Coupled Model Intercomparison Project 6 (CMIP6) models and their sensitivity to climate change

2020 ◽  
Vol 14 (9) ◽  
pp. 3155-3174 ◽  
Author(s):  
Eleanor J. Burke ◽  
Yu Zhang ◽  
Gerhard Krinner
Keyword(s):  
Climate Change ◽  
Air Temperature ◽  
High Latitude ◽  
Soil Profile ◽  
Coupled Model ◽  
The Arctic ◽  
Model Intercomparison ◽  
Model Ensemble ◽  
Northern High Latitude ◽  
Intercomparison Project

Abstract. Permafrost is a ubiquitous phenomenon in the Arctic. Its future evolution is likely to control changes in northern high-latitude hydrology and biogeochemistry. Here we evaluate the permafrost dynamics in the global models participating in the Coupled Model Intercomparison Project (present generation – CMIP6; previous generation – CMIP5) along with the sensitivity of permafrost to climate change. Whilst the northern high-latitude air temperatures are relatively well simulated by the climate models, they do introduce a bias into any subsequent model estimate of permafrost. Therefore evaluation metrics are defined in relation to the air temperature. This paper shows that the climate, snow and permafrost physics of the CMIP6 multi-model ensemble is very similar to that of the CMIP5 multi-model ensemble. The main differences are that a small number of models have demonstrably better snow insulation in CMIP6 than in CMIP5 and a small number have a deeper soil profile. These changes lead to a small overall improvement in the representation of the permafrost extent. There is little improvement in the simulation of maximum summer thaw depth between CMIP5 and CMIP6. We suggest that more models should include a better-resolved and deeper soil profile as a first step towards addressing this. We use the annual mean thawed volume of the top 2 m of the soil defined from the model soil profiles for the permafrost region to quantify changes in permafrost dynamics. The CMIP6 models project that the annual mean frozen volume in the top 2 m of the soil could decrease by 10 %–40 %∘C-1 of global mean surface air temperature increase.

scholarly journals Intercomparison of temperature trends in IPCC CMIP5 simulations with observations, reanalyses and CMIP3 models

2012 ◽  
Vol 5 (4) ◽  
pp. 3621-3645 ◽  
Author(s):  
J. Xu ◽  
A. M. Powell
Keyword(s):  
Coupled Model ◽  
Temperature Trend ◽  
The Arctic ◽  
Cmip5 Models ◽  
Model Intercomparison ◽  
Model Simulations ◽  
Temperature Trends ◽  
Intercomparison Project ◽  
Stratospheric Cooling ◽  
The Tropics

Abstract. On the basis of the fifth Coupled Model Intercomparison Project (CMIP5) and the climate model simulations covering 1979 through 2005, the temperature trends and their uncertainties have been examined to note the similarities or differences compared to the radiosonde observations, reanalyses and the third Coupled Model Intercomparison Project (CMIP3) simulations. The results show noticeable discrepancies for the estimated temperature trends in the four data groups (Radiosonde, Reanalysis, CMIP3 and CMIP5) although similarities can be observed. Compared to the CMIP3 model simulations, the simulation in some of CMIP5 models were improved. The CMIP5 models displayed a negative temperature trend in the stratosphere closer to the strong negative trend seen in the observations. However, the positive tropospheric trend in the tropics is overestimated by the CMIP5 models relative to CMIP3 models. While some of the models produce temperature trend patterns more highly correlated with the observed patterns in CMIP5, the other models (such as CCSM4 and IPSL_CM5A-LR) exhibit the reverse tendency. The CMIP5 temperature trend uncertainty was significantly reduced in most areas, especially in the Arctic and Antarctic stratosphere, compared to the CMIP3 simulations. Similar to the CMIP3, the CMIP5 simulations overestimated the tropospheric warming in the tropics and Southern Hemisphere and underestimated the stratospheric cooling. The crossover point where tropospheric warming changes into stratospheric cooling occurred near 100 hPa in the tropics, which is higher than in the radiosonde and reanalysis data. The result is likely related to the overestimation of convective activity over the tropical areas in both the CMIP3 and CMIP5 models. Generally, for the temperature trend estimates associated with the numerical models including the reanalyses and global climate models, the uncertainty in the stratosphere is much larger than that in the troposphere, and the uncertainty in the Antarctic is the largest. In addition, note that the reanalyses show the largest uncertainty in the lower tropical stratosphere, and the CMIP3 simulations show the largest uncertainty in both the south and north polar regions.

scholarly journals GCAP 2.0: A global 3-D chemical-transport model framework for past, present, and future climate scenarios

2021 ◽  
Author(s):  
Lee Thomas Murray ◽  
Eric M. Leibensperger ◽  
Clara Orbe ◽  
Loretta J. Mickley ◽  
Melissa Sulprizio
Keyword(s):  
General Circulation ◽  
Transport Model ◽  
Coupled Model ◽  
Circulation Model ◽  
Chemical Transport ◽  
Recent Past ◽  
Chemical Transport Model ◽  
Model Framework ◽  
Intercomparison Project ◽  
Goddard Institute

Abstract. This manuscript describes version 2.0 of the Global Change and Air Pollution (GCAP 2.0) model framework, a one-way offline coupling between version E2.1 of the NASA Goddard Institute for Space Studies (GISS) general circulation model (GCM) and the GEOS-Chem global 3-D chemical-transport model (CTM). Meteorology for driving GEOS-Chem has been archived from the E2.1 contributions to Phase 6 of the Coupled Model Intercomparison Project (CMIP6) for the preindustrial and recent past. In addition, meteorology is available for the near future and end-of-the century for seven future scenarios ranging from extreme mitigation to extreme warming. Emissions and boundary conditions have been prepared for input to GEOS-Chem that are consistent with the CMIP6 experimental design. The model meteorology, emissions, transport and chemistry are evaluated in the recent past and found to be largely consistent with GEOS-Chem driven by the Modern-Era Retrospective analysis for Research and Applications Version 2 (MERRA-2) product and with observational constraints.

scholarly journals Edge Detection Reveals Abrupt and Extreme Climate Events

2020 ◽  
Vol 33 (15) ◽  
pp. 6399-6421
Author(s):  
Sebastian Bathiany ◽  
Johan Hidding ◽  
Marten Scheffer
Keyword(s):  
Coupled Model ◽  
The Arctic ◽  
Edge Detector ◽  
Extreme Climate Events ◽  
Extreme Climate ◽  
New Strategy ◽  
Intercomparison Project ◽  
Abrupt Shifts ◽  
Climate Events ◽  
Impacts Of Climate Change

AbstractThe most discernible and devastating impacts of climate change are caused by events with temporary extreme conditions (“extreme events”) or abrupt shifts to a new persistent climate state (“tipping points”). The rapidly growing amount of data from models and observations poses the challenge to reliably detect where, when, why, and how these events occur. This situation calls for data-mining approaches that can detect and diagnose events in an automatic and reproducible way. Here, we apply a new strategy to this task by generalizing the classical machine-vision problem of detecting edges in 2D images to many dimensions (including time). Our edge detector identifies abrupt or extreme climate events in spatiotemporal data, quantifies their abruptness (or extremeness), and provides diagnostics that help one to understand the causes of these shifts. We also publish a comprehensive toolset of code that is documented and free to use. We document the performance of the new edge detector by analyzing several datasets of observations and models. In particular, we apply it to all monthly 2D variables of the RCP8.5 scenario of the Coupled Model Intercomparison Project (CMIP5). More than half of all simulations show abrupt shifts of more than 4 standard deviations on a time scale of 10 years. These shifts are mostly related to the loss of sea ice and permafrost in the Arctic. Our results demonstrate that the edge detector is particularly useful to scan large datasets in an efficient way, for example multimodel or perturbed-physics ensembles. It can thus help to reveal hidden “climate surprises” and to assess the uncertainties of dangerous climate events.

scholarly journals Comments on “Current GCMs' Unrealistic Negative Feedback in the Arctic”

2013 ◽  
Vol 26 (19) ◽  
pp. 7783-7788 ◽  
Author(s):  
Felix Pithan ◽  
Thorsten Mauritsen
Keyword(s):  
Permutation Test ◽  
Coupled Model ◽  
Lapse Rate ◽  
The Arctic ◽  
Model Ensemble ◽  
Cmip3 Model ◽  
Rate Feedback ◽  
Intercomparison Project ◽  
Arctic Temperature ◽  
Temperature Inversions

Abstract In contrast to prior studies showing a positive lapse-rate feedback associated with the Arctic inversion, Boé et al. reported that strong present-day Arctic temperature inversions are associated with stronger negative longwave feedbacks and thus reduced Arctic amplification in the model ensemble from phase 3 of the Coupled Model Intercomparison Project (CMIP3). A permutation test reveals that the relation between longwave feedbacks and inversion strength is an artifact of statistical self-correlation and that shortwave feedbacks have a stronger correlation with intermodel spread. The present comment concludes that the conventional understanding of a positive lapse-rate feedback associated with the Arctic inversion is consistent with the CMIP3 model ensemble.

scholarly journals GCAP 2.0: a global 3-D chemical-transport model framework for past, present, and future climate scenarios

2021 ◽  
Vol 14 (9) ◽  
pp. 5789-5823
Author(s):  
Lee T. Murray ◽  
Eric M. Leibensperger ◽  
Clara Orbe ◽  
Loretta J. Mickley ◽  
Melissa Sulprizio
Keyword(s):  
General Circulation ◽  
Transport Model ◽  
Coupled Model ◽  
Circulation Model ◽  
Chemical Transport ◽  
Recent Past ◽  
Chemical Transport Model ◽  
Model Framework ◽  
Intercomparison Project ◽  
Goddard Institute

Abstract. This paper describes version 2.0 of the Global Change and Air Pollution (GCAP 2.0) model framework, a one-way offline coupling between version E2.1 of the NASA Goddard Institute for Space Studies (GISS) general circulation model (GCM) and the GEOS-Chem global 3-D chemical-transport model (CTM). Meteorology for driving GEOS-Chem has been archived from the E2.1 contributions to phase 6 of the Coupled Model Intercomparison Project (CMIP6) for the pre-industrial era and the recent past. In addition, meteorology is available for the near future and end of the century for seven future scenarios ranging from extreme mitigation to extreme warming. Emissions and boundary conditions have been prepared for input to GEOS-Chem that are consistent with the CMIP6 experimental design. The model meteorology, emissions, transport, and chemistry are evaluated in the recent past and found to be largely consistent with GEOS-Chem driven by the Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA-2) product and with observational constraints.

scholarly journals The sea ice model component of HadGEM3-GC3.1

2018 ◽  
Vol 11 (2) ◽  
pp. 713-723 ◽  
Author(s):  
Jeff K. Ridley ◽  
Edward W. Blockley ◽  
Ann B. Keen ◽  
Jamie G. L. Rae ◽  
Alex E. West ◽  
...  
Keyword(s):  
Sea Ice ◽  
Coupled Model ◽  
The Arctic ◽  
Coupling Scheme ◽  
Model Intercomparison ◽  
Model Component ◽  
Intercomparison Project ◽  
The Stability ◽  
Ice Model

Abstract. A new sea ice configuration, GSI8.1, is implemented in the Met Office global coupled configuration HadGEM3-GC3.1 which will be used for all CMIP6 (Coupled Model Intercomparison Project Phase 6) simulations. The inclusion of multi-layer thermodynamics has required a semi-implicit coupling scheme between atmosphere and sea ice to ensure the stability of the solver. Here we describe the sea ice model component and show that the Arctic thickness and extent compare well with observationally based data.

scholarly journals New climate models reveal faster and larger increases in Arctic precipitation than previously projected

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Michelle R. McCrystall ◽  
Julienne Stroeve ◽  
Mark Serreze ◽  
Bruce C. Forbes ◽  
James A. Screen
Keyword(s):  
Global Warming ◽  
Sea Ice ◽  
Climate Models ◽  
Hydrological Cycle ◽  
Coupled Model ◽  
Open Water ◽  
The Arctic ◽  
Arctic Warming ◽  
Increased Sensitivity ◽  
Intercomparison Project

AbstractAs the Arctic continues to warm faster than the rest of the planet, evidence mounts that the region is experiencing unprecedented environmental change. The hydrological cycle is projected to intensify throughout the twenty-first century, with increased evaporation from expanding open water areas and more precipitation. The latest projections from the sixth phase of the Coupled Model Intercomparison Project (CMIP6) point to more rapid Arctic warming and sea-ice loss by the year 2100 than in previous projections, and consequently, larger and faster changes in the hydrological cycle. Arctic precipitation (rainfall) increases more rapidly in CMIP6 than in CMIP5 due to greater global warming and poleward moisture transport, greater Arctic amplification and sea-ice loss and increased sensitivity of precipitation to Arctic warming. The transition from a snow- to rain-dominated Arctic in the summer and autumn is projected to occur decades earlier and at a lower level of global warming, potentially under 1.5 °C, with profound climatic, ecosystem and socio-economic impacts.

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