Twenty-year temperature and precipitation extremes and their projected future changes are evaluated in an ensemble of climate models participating in the Coupled Model Intercomparison Project Phase 5 ...(CMIP5), updating a similar study based on the CMIP3 ensemble. The projected changes are documented for three radiative forcing scenarios. The performance of the CMIP5 models in simulating 20-year temperature and precipitation extremes is comparable to that of the CMIP3 ensemble. The models simulate late 20th century warm extremes reasonably well, compared to estimates from reanalyses. The model discrepancies in simulating cold extremes are generally larger than those for warm extremes. Simulated late 20th century precipitation extremes are plausible in the extratropics but uncertainty in extreme precipitation in the tropics and subtropics remains very large, both in the models and the observationally-constrained datasets. Consistent with CMIP3 results, CMIP5 cold extremes generally warm faster than warm extremes, mainly in regions where snow and sea-ice retreat with global warming. There are tropical and subtropical regions where warming rates of warm extremes exceed those of cold extremes. Relative changes in the intensity of precipitation extremes generally exceed relative changes in annual mean precipitation. The corresponding waiting times for late 20th century extreme precipitation events are reduced almost everywhere, except for a few subtropical regions. The CMIP5 planetary sensitivity in extreme precipitation is about 6 %/°C, with generally lower values over extratropical land.
The Canadian Earth System Model version 5 (CanESM5) is a global
model developed to simulate historical climate change and variability, to
make centennial-scale projections of future climate, and to ...produce
initialized seasonal and decadal predictions. This paper describes the model
components and their coupling, as well as various aspects of model
development, including tuning, optimization, and a reproducibility strategy.
We also document the stability of the model using a long control simulation,
quantify the model's ability to reproduce large-scale features of the
historical climate, and evaluate the response of the model to external
forcing. CanESM5 is comprised of three-dimensional atmosphere (T63 spectral
resolution equivalent roughly to 2.8∘) and ocean (nominally 1∘) general
circulation models, a sea-ice model, a land surface scheme, and explicit
land and ocean carbon cycle models. The model features relatively coarse
resolution and high throughput, which facilitates the production of large
ensembles. CanESM5 has a notably higher equilibrium climate sensitivity
(5.6 K) than its predecessor, CanESM2 (3.7 K), which we briefly discuss, along
with simulated changes over the historical period. CanESM5 simulations
contribute to the Coupled Model Intercomparison Project phase 6 (CMIP6)
and will be employed for climate science and service applications in Canada.
This study provides an overview of projected changes in climate extremes indices defined by the Expert Team on Climate Change Detection and Indices (ETCCDI). The temperature‐ and precipitation‐based ...indices are computed with a consistent methodology for climate change simulations using different emission scenarios in the Coupled Model Intercomparison Project Phase 3 (CMIP3) and Phase 5 (CMIP5) multimodel ensembles. We analyze changes in the indices on global and regional scales over the 21st century relative to the reference period 1981–2000. In general, changes in indices based on daily minimum temperatures are found to be more pronounced than in indices based on daily maximum temperatures. Extreme precipitation generally increases faster than total wet‐day precipitation. In regions, such as Australia, Central America, South Africa, and the Mediterranean, increases in consecutive dry days coincide with decreases in heavy precipitation days and maximum consecutive 5 day precipitation, which indicates future intensification of dry conditions. Particularly for the precipitation‐based indices, there can be a wide disagreement about the sign of change between the models in some regions. Changes in temperature and precipitation indices are most pronounced under RCP8.5, with projected changes exceeding those discussed in previous studies based on SRES scenarios. The complete set of indices is made available via the ETCCDI indices archive to encourage further studies on the various aspects of changes in extremes.
Key Points
We give a first overview of projected changes in extreme indices in CMIP5We see most pronounced changes in minimum temperature extremesExtreme precipitation increases faster than the total wet-day precipitation
This paper provides a first 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 compares it to that in the previous model generation (CMIP3). For the first time, the indices based on daily temperature and precipitation are calculated with a consistent methodology across multimodel simulations and four reanalysis data sets (ERA40, ERA‐Interim, NCEP/NCAR, and NCEP‐DOE) and are made available at the ETCCDI indices archive website. Our analyses show that the CMIP5 models are generally able to simulate climate extremes and their trend patterns as represented by the indices in comparison to a gridded observational indices data set (HadEX2). The spread amongst CMIP5 models for several temperature indices is reduced compared to CMIP3 models, despite the larger number of models participating in CMIP5. Some improvements in the CMIP5 ensemble relative to CMIP3 are also found in the representation of the magnitude of precipitation indices. We find substantial discrepancies between the reanalyses, indicating considerable uncertainties regarding their simulation of extremes. The overall performance of individual models is summarized by a “portrait” diagram based on root‐mean‐square errors of model climatologies for each index and model relative to four reanalyses. This metric analysis shows that the median model climatology outperforms individual models for all indices, but the uncertainties related to the underlying reference data sets are reflected in the individual model performance metrics.
Key PointsWe calculate indices in a consistent manner across models and reanalysesMulti‐model ensembles compare reasonably well with observation‐based indicesThere are large uncertainties in the representation of extremes in reanalyses
Changes in temperature and precipitation extremes are examined in transient climate change simulations performed with the second-generation coupled global climate model of the Canadian Centre for ...Climate Modelling and Analysis. Three-member ensembles were produced for the time period 1990–2100 using the IS92a, A2, and B2 emission scenarios of the Intergovernmental Panel on Climate Change. The return values of annual extremes are estimated from a fitted generalized extreme value distribution with time-dependent location and scale parameters by the method of maximum likelihood. The L-moment return value estimates are revisited and found to be somewhat biased in the context of transient climate change simulations.
The climate response is of similar magnitude in the integrations with the IS92a and A2 emission scenarios but more modest for the B2 scenario. Changes in temperature extremes are largely associated with changes in the location of the distribution of annual extremes without substantial changes in its shape over most of the globe. Exceptions are regions where land and ocean surface properties change drastically, such as the regions that experience sea ice and snow cover retreat. Globally averaged changes in warm extremes are comparable to the corresponding changes in annual mean daily maximum temperature, while globally averaged cold extremes warm up faster than annual mean daily minimum temperature. There are considerable regional differences between the magnitudes of changes in temperature extremes and the corresponding annual means. Changes in precipitation extremes are due to changes in both the location and scale of the extreme value distribution and exceed substantially the corresponding changes in the annual mean precipitation. Generally speaking, the warmer model climate becomes wetter and hydrologically more variable. The probability of precipitation events that are considered extreme at the beginning of the simulations is increased by a factor of about 2 by the end of the twenty-first century.
The response of the second‐generation Canadian earth system model (CanESM2) to historical (1850–2005) and future (2006–2100) natural and anthropogenic forcing is assessed using the newly‐developed ...representative concentration pathways (RCPs) of greenhouse gases (GHGs) and aerosols. Allowable emissions required to achieve the future atmospheric CO2 concentration pathways, are reported for the RCP 2.6, 4.5 and 8.5 scenarios. For the historical 1850–2005 period, cumulative land plus ocean carbon uptake and, consequently, cumulative diagnosed emissions compare well with observation‐based estimates. The simulated historical carbon uptake is somewhat weaker for the ocean and stronger for the land relative to their observation‐based estimates. The simulated historical warming of 0.9°C compares well with the observation‐based estimate of 0.76 ± 0.19°C. The RCP 2.6, 4.5 and 8.5 scenarios respectively yield warmings of 1.4, 2.3, and 4.9°C and cumulative diagnosed fossil fuel emissions of 182, 643 and 1617 Pg C over the 2006–2100 period. The simulated warming of 2.3°C over the 1850–2100 period in the RCP 2.6 scenario, with the lowest concentration of GHGs, is slightly larger than the 2°C warming target set to avoid dangerous climate change by the 2009 UN Copenhagen Accord. The results of this study suggest that limiting warming to roughly 2°C by the end of this century is unlikely since it requires an immediate ramp down of emissions followed by ongoing carbon sequestration in the second half of this century.
Temperature and precipitation extremes and their potential future changes are evaluated in an ensemble of global coupled climate models participating in the Intergovernmental Panel on Climate Change ...(IPCC) diagnostic exercise for the Fourth Assessment Report (AR4). Climate extremes are expressed in terms of 20-yr return values of annual extremes of near-surface temperature and 24-h precipitation amounts. The simulated changes in extremes are documented for years 2046–65 and 2081–2100 relative to 1981–2000 in experiments with the Special Report on Emissions Scenarios (SRES) B1, A1B, and A2 emission scenarios.
Overall, the climate models simulate present-day warm extremes reasonably well on the global scale, as compared to estimates from reanalyses. The model discrepancies in simulating cold extremes are generally larger than those for warm extremes, especially in sea ice–covered areas. Simulated present-day precipitation extremes are plausible in the extratropics, but uncertainties in extreme precipitation in the Tropics are very large, both in the models and the available observationally based datasets.
Changes in warm extremes generally follow changes in the mean summertime temperature. Cold extremes warm faster than warm extremes by about 30%–40%, globally averaged. The excessive warming of cold extremes is generally confined to regions where snow and sea ice retreat with global warming. With the exception of northern polar latitudes, relative changes in the intensity of precipitation extremes generally exceed relative changes in annual mean precipitation, particularly in tropical and subtropical regions. Consistent with the increased intensity of precipitation extremes, waiting times for late-twentieth-century extreme precipitation events are reduced almost everywhere, with the exception of a few subtropical regions. The multimodel multiscenario consensus on the projected change in the globally averaged 20-yr return values of annual extremes of 24-h precipitation amounts is that there will be an increase of about 6% with each kelvin of global warming, with the bulk of models simulating values in the range of 4%–10% K−1. The very large intermodel disagreements in the Tropics suggest that some physical processes associated with extreme precipitation are not well represented in models. This reduces confidence in the projected changes in extreme precipitation.
Arctic sea ice loss may influence midlatitude climate by changing large‐scale circulation. The extent to which climate change can be understood as greenhouse gas‐induced changes that are modulated by ...this loss depends on how additive the responses to the separate influences are. A novel sea ice nudging methodology in a fully coupled climate model reveals that the separate effects of doubled atmospheric carbon dioxide (CO2) concentrations and associated Arctic sea ice loss are remarkably additive and insensitive to the mean climate state. This separability is evident in several fields throughout most of the year, from hemispheric to synoptic scales. The extent to which the regional response to sea ice loss sometimes agrees with and sometimes cancels the response to CO2 is quantified. The separability of the responses might provide a means to better interpret the diverse array of modeling and observational studies of Arctic change and influence.
Plain Language Summary
The decrease in Arctic sea ice area may influence midlatitude climate and weather by changing hemispheric‐scale winds. Whether the change in winds due to this Arctic sea ice loss can be cleanly separated from the wind changes due to human‐induced greenhouse gas increase remains a question. Here using a global climate computer model, we explicitly separate the climate response to Arctic sea ice loss from the climate response to a doubling of atmospheric carbon dioxide (CO2) concentration with fixed Arctic sea ice. We show that the two separate responses add up to the full climate response to a doubling of CO2 concentration. We also show that it is not important whether CO2 is doubled with a large amount of Arctic sea ice or a small amount or whether Arctic sea ice decreases in a warm climate or in a cold climate. These results imply that some features of human‐induced climate change may be explained by Arctic sea ice melting and may help to explain the many different greenhouse gas‐induced wind changes found in modeling and observational studies.
Key Points
New framework to isolate response to Arctic sea ice loss and greenhouse gas forcing in a coupled system
Response to Arctic sea ice loss and CO2 doubling is very additive, even at small spatial scales
Areas where sea ice loss amplifies or cancels response to doubled CO2 can be quantified
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