Perspectives on CMIP5 model performance in the Nile River headwaters regions
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Partha S. Bhattacharjee↗
SEARCH · Engineering Papers
Results for “CMIP5”
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Predictability of phases and magnitudes of natural decadal climate variability phenomena in CMIP5 experiments with the UKMO HadCM3, GFDL-CM2.1, NCAR-CCSM4, and MIROC5 global earth system models
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Vikram M. Mehta↗
Projections of Declining Surface-Water Availability for the Southwestern United States
16 of the CMIP5 models had all the data needed for this work for at least one simulation that was continuous from 1950 to 2040. Details of the models analyzed here are provided in Table S1. The model data analyzed here are available at http://strega.ldeo.columbia.edu:81/expert/home/.naomi/.AR5/.v2/.historical:rcp85/.mmm16/ a. Assessing the climatology of the models Despite increases in horizontal resolution of many models compared to their CMIP3 counterparts none of these models can adequately resolve the topography of the south west United States, such as the Sierra Nevada and Rocky Mountains and the associated orographic precipitation. This requires that caution be used when interpreting the results presented here. To assess the ability of the models to simulate the current hydroclimate, in Figure S1 we show the observed (from the Global Precipitation Climatology Centre gridded rain gauge data, (1)) monthly climatology of precipitation and the same for all the models and the multimodel mean for the California-Nevada, Colorado headwaters and Texas regions. The GPCC data uses rain gauges only and interpolates to regular grids of which we used the 1◦ by 1◦ one. Details of the data set can be found in (2). While the models apparently overestimate precipitation in California and Nevada the seasonal cycle with wet winters and dry summers is very well represented. It is also possible that the rain gauge observations are biased low by inadequately sampling the higher mountain regions. How ever the models might also be expected to underestimate orographic precipitation due to inadequate horizontal resolution. The 25 models are also too wet in the Colorado headwaters region but correctly represent the quite even distribution though the year. The bimodal distribution of precipitation in Texas, with peaks in May and September, and the absolute amounts, are well modeled but with the September peak too weak. The positive precipitation bias translates into a positive runoff bias for the Colorado headwaters as also shown in Figure S1. Here the observed runoff values are taken from simulations of the Variable Infiltration Capacity (VIC) land surface-hydrology model (3) forced by observed meteorology (5) that were conducted as part of the North American Land Data Assimilation System project phase 2 ( (NLDAS-2), http://www.emc.ncep.noaa.gov/mmb/nldas/. Runoff for California-Nevada is better simulated but there is a positive bias over Texas despite no strong precipitation bias. To check whether regional climate models better simulate P and runoff in these regions we analyzed the historical simulation with the Regional Climate Model version 3 driven by the National Centers for Environmental Prediction-Department of Energy Reanalysis 2 available from the North American Regional Climate Change Assessment Program (http://www.narccap.ucar.edu). This model configuration retained these biases in P and runoff although they were reduced in amplitude. Given these varying biases we plot P and P − E changes in actual values but apply the simplest bias correction possible to the runoff and soil moisture values and show the modeled changes in terms of percentages of the 20th Century model climatologies. A thorough assessment of the simulation of North American climate in CMIP5 models is conducted in Sheffield at al. (North American Climate in CMIP5 Experiments. Part I: Evaluation of 20th Century Continental and Regional Climatology, manuscript submit ted to J. Climate, available at http://www.climate.noaa.gov/index.jsp?pg=./cpo pa/ mapp/cmip5 publications.html). Sheffield et al. analyze the climatology of precipitation, surface air temperature, low level winds, moisture fluxes, runoff etc. and conclude that the main features of the hydrological cycle, including characteristics of the atmospheric moisture balance and its seasonality, are captured in the CMP5 models subject to biases in total precipitation amounts. We chose to use all available models instead of selecting some and rejecting others based on an assessment of model realism. This is in accord with the suggestions of Mote et al. for CMIP3 (4) but future work needs to revisit this matter for the case of the CMIP5 ensemble.
Seager, Richard↗
The PMIP4 Last Glacial Maximum experiments: preliminary results and comparison with the PMIP3 simulations
The Last Glacial Maximum (LGM, ∼ 21 000 years ago) has been a major focus for evaluating how well state-of-the-art climate models simulate climate changes as large as those expected in the future using paleoclimate reconstructions. A new generation of climate models has been used to generate LGM simulations as part of the Paleoclimate Modelling Intercomparison Project (PMIP) contribution to the Coupled Model Intercomparison Project (CMIP). Here, we provide a preliminary analysis and evaluation of the results of these LGM experiments (PMIP4, most of which are PMIP4-CMIP6) and compare them with the previous generation of simulations (PMIP3, most of which are PMIP3-CMIP5). We show that the global averages of the PMIP4 simulations span a larger range in terms of mean annual surface air temperature and mean annual precipitation compared to the PMIP3-CMIP5 simulations, with some PMIP4 simulations reaching a globally colder and drier state. However, the multi-model global cooling average is similar for the PMIP4 and PMIP3 ensembles, while the multi-model PMIP4 mean annual precipitation average is drier than the PMIP3 one. There are important differences in both atmospheric and oceanic circulations between the two sets of experiments, with the northern and southern jet streams being more poleward and the changes in the Atlantic Meridional Overturning Circulation being less pronounced in the PMIP4-CMIP6 simulations than in the PMIP3-CMIP5 simulations. Changes in simulated precipitation patterns are influenced by both temperature and circulation changes. Differences in simulated climate between individual models remain large. Therefore, although there are differences in the average behaviour across the two ensembles, the new simulation results are not fundamentally different from the PMIP3-CMIP5 results. Evaluation of large-scale climate features, such as land–sea contrast and polar amplification, confirms that the models capture these well and within the uncertainty of the paleoclimate reconstructions. Nevertheless, regional climate changes are less well simulated: the models underestimate extratropical cooling, particularly in winter, and precipitation changes. These results point to the utility of using paleoclimate simulations to understand the mechanisms of climate change and evaluate model performance.
Last Glacial Maximum↗
The Response of the Ozone Layer Under Abrupt 4xCO2 in CMIP6
Previous studies indicate a possible role of stratospheric ozone chemistry feedbacks in the climate response to 4xCO2, either via a reduction in equilibrium climate sensitivity (ECS) (Nowack et al., 2015), or via changes in the tropospheric circulation (Chiodo and Polvani, 2017). However, these effects are subject to uncertainty. Part of the uncertainty may stem from the dependency of the feedback on the pattern of the ozone response, as the radiative efficiency of ozone largely depends on its vertical distribution (Lacis et al., 1990). Here, an analysis is presented of the ozone layer response to 4xCO2 in chemistry–climate models (CCMs) which participated to CMIP intercomparisons. In a previous study using CMIP5 models, it has been shown that under 4xCO2, ozone decreases in the tropical lower stratosphere, and increases over the high latitudes and throughout the upper stratosphere. It was also found that a substantial portion of the spread in the tropical column ozone is tied to inter-model spread in tropical upwelling, which is in turn partly tied to ECS (Chiodo et al., 2018). Here, we revisit this connection using4xCO2 data from CMIP6, thereby exploiting the larger number of CCMs than in CMIP5. In addition, we explore the linearity of the ozone response, by complementing the analysis with simulations using transient CO2 forcing (1pc/year). We show that the pattern of the ozone response in is similar to CMIP5. In some models (e.g. WACCM), we find larger ozone responses in CMIP6 than in CMIP5, partly because of the larger ECS and thus larger upwelling response in the tropical pipe. In this presentation, we will discuss the relationship between radiative forcing, transport and ozone, as well as further implications for CMIP6 models.
Ozone layer↗
The Response of the Ozone Layer Under Abrupt 4xCO2 in CMIP6
Previous studies indicate a possible role of stratospheric ozone chemistry feedbacks in the climate response to 4xCO2, either via a reduction in equilibrium climate sensitivity (ECS) (Nowack et al.,2015), or via changes in the tropospheric circulation (Chiodo and Polvani, 2017). However, these effects are subject to uncertainty. Part of the uncertainty may stem from the dependency of the feedback on the pattern of the ozone response, as the radiative efficiency of ozone largely depends on its vertical distribution (Lacis et al., 1990). Here, an analysis is presented of the ozone layer response to 4xCO2 in chemistry–climate models (CCMs) which participated to CMIP intercomparisons. In a previous study using CMIP5 models, it has been shown that under 4xCO2, ozone decreases in the tropical lower stratosphere, and increases over the high latitudes and throughout the upper stratosphere. It was also found that a substantial portion of the spread in the tropical column ozone is tied to inter-model spread in tropical upwelling, which is in turn tied to ECS (Chiodo et al., 2018). Here, we revisit this connection using 4xCO2 data from CMIP6, thereby exploiting the larger number of CCMs than in CMIP5. In addition, we explore the linearity of the ozone response, by complementing the analysis with simulations using lower CO 2 forcing levels (2xCO2). We show that the pattern of the ozone response in is similar to CMIP5. In some models (e.g. WACCM), we find larger ozone responses in CMIP6 than in CMIP5, partly because of the larger ECS and thus larger upwelling response in the tropical pipe. In this presentation, we will discuss the relationship between radiative forcing, transport and ozone, as well as further implications for CMIP6 models.
Ozone layer↗
Radiative Forcing in the ACCMIP Historical and Future Climate Simulations
A primary goal of the Atmospheric Chemistry and Climate Model IntercomparisonProject (ACCMIP) was to characterize the short-lived drivers of preindustrial to 2100climate change in the current generation of climate models. Here we evaluate historicaland 5 future radiative forcing in the 10 ACCMIP models that included aerosols, 8 of whichalso participated in the Coupled Model Intercomparison Project phase 5 (CMIP5).The models generally reproduce present-day climatological total aerosol opticaldepth (AOD) relatively well. components to this total, however, and most appear to underestimate AOD over East10 Asia. The models generally capture 1980-2000 AOD trends fairly well, though theyunderpredict AOD increases over the YellowEastern Sea. They appear to strongly underestimate absorbing AOD, especially in East Asia, South and Southeast Asia, SouthAmerica and Southern Hemisphere Africa.We examined both the conventional direct radiative forcing at the tropopause (RF) and the forcing including rapid adjustments (adjusted forcing AF, including direct andindirect effects). The models calculated all aerosol all-sky 1850 to 2000 global meanannual average RF ranges from 0.06 to 0.49 W m(sup -2), with a mean of 0.26 W m(sup -2) and a median of 0.27 W m(sup -2. Adjusting for missing aerosol components in some modelsbrings the range to 0.12 to 0.62W m(sup -2), with a mean of 0.39W m(sup -2). Screen20ing the models based on their ability to capture spatial patterns and magnitudes ofAOD and AOD trends yields a quality-controlled mean of 0.42W m(sup -2) and range of0.33 to 0.50 W m(sup -2) (accounting for missing components). The CMIP5 subset of ACCMIPmodels spans 0.06 to 0.49W m(sup -2), suggesting some CMIP5 simulations likelyhave too little aerosol RF. A substantial, but not well quantified, contribution to histori25cal aerosol RF may come from climate feedbacks (35 to 58). The mean aerosol AF during this period is 1.12W m(sup -2) (median value 1.16W m(sup -2), range 0.72 to1.44W m(sup -2), indicating that adjustments to aerosols, which include cloud, water vaporand temperature, lead to stronger forcing than the aerosol direct RF.
Climate Models↗
Reducing Spread in Climate Model Projections of a September Ice-Free Arctic
This paper addresses the specter of a September ice-free Arctic in the 21st century using newly available simulations from the Coupled Model Intercomparison Project Phase 5 (CMIP5). We find that large spread in the projected timing of the September ice-free Arctic in 30 CMIP5 models is associated at least as much with different atmospheric model components as with initial conditions. Here we reduce the spread in the timing of an ice-free state using two different approaches for the 30 CMIP5 models: (i) model selection based on the ability to reproduce the observed sea ice climatology and variability since 1979 and (ii) constrained estimation based on the strong and persistent relationship between present and future sea ice conditions. Results from the two approaches show good agreement. Under a high-emission scenario both approaches project that September ice extent will drop to approx. 1.7 million sq km in the mid 2040s and reach the ice-free state (defined as 1 million sq km) in 2054-2058. Under a medium-mitigation scenario, both approaches project a decrease to approx.1.7 million sq km in the early 2060s, followed by a leveling off in the ice extent.
simulation↗
External Influences on Modeled and Observed Cloud Trends
Understanding the cloud response to external forcing is a major challenge for climate science. This crucial goal is complicated by intermodel differences in simulating present and future cloud cover and by observational uncertainty. This is the first formal detection and attribution study of cloud changes over the satellite era. Presented herein are CMIP5 (Coupled Model Intercomparison Project - Phase 5) model-derived fingerprints of externally forced changes to three cloud properties: the latitudes at which the zonally averaged total cloud fraction (CLT) is maximized or minimized, the zonal average CLT at these latitudes, and the height of high clouds at these latitudes. By considering simultaneous changes in all three properties, the authors define a coherent multivariate fingerprint of cloud response to external forcing and use models from phase 5 of CMIP (CMIP5) to calculate the average time to detect these changes. It is found that given perfect satellite cloud observations beginning in 1983, the models indicate that a detectable multivariate signal should have already emerged. A search is then made for signals of external forcing in two observational datasets: ISCCP (International Satellite Cloud Climatology Project) and PATMOS-x (Advanced Very High Resolution Radiometer (AVHRR) Pathfinder Atmospheres - Extended). The datasets are both found to show a poleward migration of the zonal CLT pattern that is incompatible with forced CMIP5 models. Nevertheless, a detectable multivariate signal is predicted by models over the PATMOS-x time period and is indeed present in the dataset. Despite persistent observational uncertainties, these results present a strong case for continued efforts to improve these existing satellite observations, in addition to planning for new missions.
clouds (meteorology)↗
Long-Term Changes/Trends in Surface Temperature and Precipitation During the Satellite Era (1979-2012)
During the post-1979 period in which the satellite-based precipitation measurements with global coverage are available, global mean surface temperature rapidly increased up to late 1990s, followed by a period of temperature hiatus after about 19981999. Comparing observed surface temperature trends against the simulated ones by the CMIP5 historical experiments especially in the zonal mean context suggests that although the anthropogenic greenhouse-gases (GHG) forcing has played a major role, in addition to the anthropogenic aerosols and various natural forcings, the effects from decadal-to-interdecadal scale internal modes specifically the Pacific Decadal Oscillation(PDO) are also very strong. Evident temperature changes associated with the PDOs phase shift are seen in the Pacific basin, with decadal-scale cooling in the tropical central-eastern Pacific and most of the east basin and concurrent warming in the subtropics of both hemispheres,even though the PDOs net effect on global mean temperature is relatively weak. The Atlantic Multidecadal Oscillation(AMO) also changed its phase in the mid-1990s, and hence its possible impact is estimated and assessed as well.However, comparisons with CMIP5 simulations suggest that the AMO may have not contributed as significantly as the PDO in terms of the changes trends in global surface temperature, even though the data analysis technique used here suggests otherwise. Long-term precipitation changes or trends during the post-1979 period are further shown to have been modulated by the two major factors:anthropogenic GHG and PDO, in addition to the relatively weak effects from aerosols and natural forcings. The spatial patterns of observed precipitation trends in the Pacific,including reductions in the tropical central-eastern Pacific and increases in the tropical western Pacific and along the South Pacific Convergence Zone, manifest the PDOs contributions.Removing the PDO effect from the total precipitation trends makes the spatial structures of precipitation trends more similar to those simulated by CMIP5 historical full forcing experiments particularly in the context of zonal-mean results. This also confirms that in spite of the PDO effect specifically on regional scales, the anthropogenic GHG signals are still discernible in observed precipitation during the time period. Following the increase of GHG, precipitation tends to increase roughly along the climatological ITCZ and decrease south of the equator and in the subtropics of both hemispheres.
GPCP↗
TPSAS-NF1676L-27659-DND
The Arctic is warming fast, a trend expected to continue. Rapid Arctic warming has far-reaching implications affecting the global energy budget, sea level rise, the global carbon cycle, and potentially the atmospheric and oceanic circulation. Our understanding of the forcing mechanisms driving Arctic climate change has rapidly evolved in the last decade. For 40 years, the melting of sea ice and snow has been implicated as the primary driver of amplified Arctic warming, however our results indicate a shift, whereby changes in the atmospheric temperature, humidity, and clouds have surpassed the warming effects of snow and sea ice loss in the latest CMIP5 model simulations. We examine the impacts of climate feedbacks on the Arctic surface energy budget: namely surface albedo, clouds, shortwave clear-sky feedbacks, longwave clear-sky feedbacks, ocean heat content, and surface turbulent fluxes. Simulations from 16 CMIP5 models running RCP8.5, a high-emission scenario are used. We employ the methodology used in Lu and Cai (2009) on a single CMIP3 model allowing an analysis of changes between CMIP3 and CMIP5.
Robyn C Boeke↗
ISMIP6 Antarctica: A Multi-Model Ensemble of the Antarctic Ice Sheet Evolution Over the 21st Century
Ice flow models of the Antarctic ice sheet are commonly used to simulate its future evolution in response to different climate scenarios and assess the mass loss that would contribute to future sea level rise. However, there is currently no consensus on estimates of the future mass balance of the ice sheet, primarily because of differences in the representation of physical processes, forcings employed and initial states of ice sheet models. This study presents results from ice flow model simulations from 13 international groups focusing on the evolution of the Antarctic ice sheet during the period 2015–2100 as part of the Ice Sheet Model Intercomparison for CMIP6 (ISMIP6). They are forced with outputs from a subset of models from the Coupled Model Intercomparison Project Phase 5 (CMIP5), representative of the spread in climate model results. Simulations of the Antarctic ice sheet contribution to sea level rise in response to increased warming during this period varies between -7:8 and 30.0 cm of sea level equivalent (SLE) under Representative Concentration Pathway (RCP) 8.5 scenario forcing. These numbers are relative to a control experiment with constant climate conditions and should therefore be added to the mass loss contribution under climate conditions similar to present-day conditions over the same period. The simulated evolution of the West Antarctic ice sheet varies widely among models, with an overall mass loss, up to 18.0 cm SLE, in response to changes in oceanic conditions. East Antarctica ass change varies between -6.1 and 8.3 cm SLE in the simulations, with a significant increase in surface mass balance outweighing the increased ice discharge under most RCP 8.5 scenario forcings. The inclusion of ice shelf collapse, here assumed to be caused by large amounts of liquid water ponding at the surface of ice shelves, yields an additional simulated mass loss of 28mm compared to simulations without ice shelf collapse. The largest sources of uncertainty come from the climate forcing, the ocean-induced melt rates, the calibration of these melt rates based on oceanic conditions taken outside of ice shelf cavities and the ice sheet dynamic response to these oceanic changes. Results under RCP 2.6 scenario based on two CMIP5 climate models show an additional mass loss of 0 and 3 cm of SLE on average compared to simulations done under present-day conditions for the two CMIP5 forcings used and display limited mass gain in East Antarctica.
Hélène Seroussi↗
Large-scale features and evaluation of the PMIP4-CMIP6 midHolocene simulations
The mid-Holocene (6000 years ago) is a standard time period for the evaluation of the simulated response of global climate models using palaeoclimate reconstructions. The latest mid-Holocene simulations are a palaeoclimate entry card for the Palaeoclimate Model Intercomparison Project (PMIP4) component of the current phase of the Coupled Model Intercomparison Project (CMIP6) – hereafter referred to as PMIP4-CMIP6. Here we provide an initial analysis and evaluation of the results of the experiment for the mid-Holocene. We show that state-of-the-art models produce climate changes that are broadly consistent with theory and observations, including increased summer warming of the Northern Hemisphere and associated shifts in tropical rainfall. Many features of the PMIP4-CMIP6 simulations were present in the previous generation (PMIP3-CMIP5) of simulations. The PMIP4-CMIP6 ensemble for the mid-Holocene has a global mean temperature change of −0.3 K, which is −0.2 K cooler than the PMIP3-CMIP5 simulations predominantly as a result of the prescription of realistic greenhouse gas concentrations in PMIP4-CMIP6. Biases in the magnitude and the sign of regional responses identified in PMIP3-CMIP5, such as the amplification of the northern African monsoon, precipitation changes over Europe, and simulated aridity in mid-Eurasia, are still present in the PMIP4-CMIP6 simulations. Despite these issues, PMIP4-CMIP6 and the mid-Holocene provide an opportunity both for quantitative evaluation and derivation of emergent constraints on the hydrological cycle, feedback strength, and potentially climate sensitivity.
mid-Holocene simulations↗
Climate model projections from the Scenario Model Intercomparison Project (ScenarioMIP) of CMIP6
The Scenario Model Intercomparison Project (ScenarioMIP) defines and coordinates the main set of future climate projections, based on concentration-driven simulations, within the Coupled Model Intercomparison Project phase 6 (CMIP6). This paper presents a range of its outcomes by synthesizing results from the participating global coupled Earth system models. We limit our scope to the analysis of strictly geophysical outcomes: mainly global averages and spatial patterns of change for surface air temperature and precipitation. We also compare CMIP6 projections to CMIP5 results, especially for those scenarios that were designed to provide continuity across the CMIP phases, at the same time highlighting important differences in forcing composition, as well as in results. The range of future temperature and precipitation changes by the end of the century (2081–2100) encompassing the Tier 1 experiments based on the Shared Socioeconomic Pathway (SSP) scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0 and SSP5-8.5) and SSP1-1.9 spans a larger range of outcomes compared to CMIP5, due to higher warming (by close to 1.5 °C) reached at the upper end of the 5 %–95 % envelope of the highest scenario (SSP5-8.5). This is due to both the wider range of radiative forcing that the new scenarios cover and the higher climate sensitivities in some of the new models compared to their CMIP5 predecessors. Spatial patterns of change for temperature and precipitation averaged over models and scenarios have familiar features, and an analysis of their variations confirms model structural differences to be the dominant source of uncertainty. Models also differ with respect to the size and evolution of internal variability as measured by individual models' initial condition ensemble spreads, according to a set of initial condition ensemble simulations available under SSP3-7.0. These experiments suggest a tendency for internal variability to decrease along the course of the century in this scenario, a result that will benefit from further analysis over a larger set of models. Benefits of mitigation, all else being equal in terms of societal drivers, appear clearly when comparing scenarios developed under the same SSP but to which different degrees of mitigation have been applied. It is also found that a mild overshoot in temperature of a few decades around mid-century, as represented in SSP5-3.4OS, does not affect the end outcome of temperature and precipitation changes by 2100, which return to the same levels as those reached by the gradually increasing SSP4-3.4 (not erasing the possibility, however, that other aspects of the system may not be as easily reversible). Central estimates of the time at which the ensemble means of the different scenarios reach a given warming level might be biased by the inclusion of models that have shown faster warming in the historical period than the observed. Those estimates show all scenarios reaching 1.5 °C of warming compared to the 1850–1900 baseline in the second half of the current decade, with the time span between slow and fast warming covering between 20 and 27 years from present. The warming level of 2 °C of warming is reached as early as 2039 by the ensemble mean under SSP5-8.5 but as late as the mid-2060s under SSP1-2.6. The highest warming level considered (5 °C) is reached by the ensemble mean only under SSP5-8.5 and not until the mid-2090s.d-2090s.
Scenario Model Intercomparison Project (ScenarioMI↗
Future Climate Change Under SSP Emission Scenarios with GISS-E2.1
This paper presents the response to anthropogenic forcing in the GISS-E2.1 climate models for the 21st century Shared Socioeconomic Pathways emission scenarios within the Coupled Model Intercomparison Project Phase 6 (CMIP6). The experiments were performed using an updated and improved version of the NASA Goddard Institute for Space Studies (GISS) coupled general circulation model that includes two different versions for atmospheric composition: A non-interactive version (NINT) with prescribed composition and a tuned aerosol indirect effect and the One-Moment Aerosol model (OMA) version with fully interactive aerosols which includes a parameterized first indirect aerosol effect on clouds. The effective climate sensitivities are 3.0°C and 2.9°C for the NINT and OMA models, respectively. Each atmospheric version is coupled to two different ocean general circulation models: The GISS ocean model (E2.1-G) and HYCOM (E2.1-H). We describe the global mean responses for all future scenarios and spatial patterns of change for surface air temperature and precipitation for four of the marker scenarios: SSP1-2.6, SSP2-4.5, SSP4-6.0, and SSP5-8.5. By 2100, global mean warming ranges from 1.5°C to 5.2°C relative to 1,850–1,880 mean temperature. Two high-mitigation scenarios SSP1-1.9 and SSP1-2.6 limit the surface warming to below 2°C by the end of the 21st century, except for the NINT E2.1-H model that simulates 2.2°C of surface warming. For the high emission scenario SSP5-8.5, the range is 4.6–5.2°C at 2100. Due to about 15% larger effective climate sensitivity and stronger transient climate response in both NINT and OMA CMIP6 models compared to CMIP5 versions, there is a stronger warming by 2100 in the SSP emission scenarios than in the comparable Representative Concentration Pathway (RCP) scenarios in CMIP5. Changes in sea ice area are highly correlated to global mean surface air temperature anomalies and show steep declines in both hemispheres, with the largest sea ice area decreases occurring during September in the Northern Hemisphere in both E2.1-G (−1.21 × 106 km2/°C) and E2.1-H models (−0.94 × 106 km2/°C). Both coupled models project decreases in the Atlantic overturning stream function by 2100. The largest decrease of 56%–65% in the 21st century overturning stream function is produced in the warmest scenario SSP5-8.5 in the E2.1-G model, comparable to the reduction in the corresponding CMIP5 GISS-E2 RCP8.5 simulation. Both low-end scenarios SSP1-1.9 and SSP1-2.6 also simulate substantial reductions of the overturning (9%–37%) with slow recovery of about 10% by the end of the 21st century (relative to the maximum decrease at the middle of the 21st century).
climate models↗
Evaluation of the Surface Representation of the Greenland Ice Sheet in a General Circulation Model
Simulated surface conditions of the Goddard Earth Observing System model, version 5 (GEOS 5) atmospheric general circulation model (AGCM) are examined for the contemporary Greenland Ice Sheet (GrIS). A surface parameterization that explicitly models surface processes including snow compaction, meltwater percolation and refreezing, and surface albedo is found to remedy an erroneous deficit in the annual net surface energy flux and provide an adequate representation of surface mass balance (SMB) in an evaluation using simulations at two spatial resolutions. The simulated 1980-2008 GrIS SMB average is 24.7+/-4.5 cm yr(- 1) water-equivalent (w.e.) at.5 degree model grid spacing, and 18.2+/-3.3 cm yr(- 1) w.e. for 2 degree grid spacing. The spatial variability and seasonal cycle of the simulation compare favorably to recent studies using regional climate models, while results from 2 degree integrations reproduce the primary features of the SMB field. In comparison to historical glaciological observations, the coarser resolution model overestimates accumulation in the southern areas of the GrIS, while the overall SMB is underestimated. These changes relate to the sensitivity of accumulation and melt to the resolution of topography. The GEOS-5 SMB fields contrast with available corresponding atmospheric models simulations from the Coupled Model Intercomparison Project (CMIP5). It is found that only a few of the CMIP5 AGCMs examined provide significant summertime runoff, a dominant feature of the GrIS seasonal cycle. This is a condition that will need to be remedied if potential contributions to future eustatic change from polar ice sheets are to be examined with GCMs.
AGCM↗
Land–Atmosphere Feedbacks Exacerbate Concurrent Soil Drought and Atmospheric Aridity
Compound extremes such as cooccurring soil drought (low soil moisture) and atmospheric aridity (high vapor pressure deficit) can be disastrous for natural and societal systems. Soil drought and atmospheric aridity are 2 main physiological stressors driving widespread vegetation mortality and reduced terrestrial carbon uptake. Here, we empirically demonstrate that strong negative coupling between soil moisture and vapor pressure deficit occurs globally, indicating high probability of cooccurring soil drought and atmospheric aridity. Using the Global Land Atmosphere Coupling Experiment (GLACE)-CMIP5 experiment, we further show that concurrent soil drought and atmospheric aridity are greatly exacerbated by land– atmosphere feedbacks. The feedback of soil drought on the atmosphere is largely responsible for enabling atmospheric aridity extremes. In addition, the soil moisture–precipitation feedback acts to amplify precipitation and soil moisture deficits in most regions. CMIP5 models further show that the frequency of concurrent soil drought and atmospheric aridity enhanced by land–atmosphere feedbacks is projected to increase in the 21st century. Importantly, land– atmosphere feedbacks will greatly increase the intensity of both soil drought and atmospheric aridity beyond that expected from changes in mean climate alone.
Compound extreme events↗
Sensitivity to Factors Underlying the Hiatus
Recent trends in global mean surface air temperature fall outside the 90 range predicted by models using the CMIP5 forcings and scenarios; this recent period of muted warming is dubbed the hiatus. The hiatus has attracted broad attention in both the popular press and the scientific literature, primarily because of its perceived implications for understanding long-term trends. Many hypotheses have been offered to explain the warming slowdown during the hiatus, and comprehensive studies of this period across multiple variables and spatial scales will likely improve our understanding of the physical mechanisms driving global temperature change and variability.We argue, however, that decadal temperature trends by themselves are unlikely to constrain future trajectories of global mean temperature and that the hiatus does not significantly revise our understanding of overall climate sensitivity. Instead, we demonstrate that, because of the poorly constrained nature of the hiatus, model-observation disagreements over this period may be resolvable via uncertainties in the observations, modeled internal variability, forcing estimates, or (more likely) some combination of all three factors. We define the hiatus interval as 1998-2012, endpoints judiciously chosen to minimize observed warming by including the large 1998 El Nio event and excluding 2014, an exceptionally warm year. Such choices are fundamentally subjective and cannot be considered random, so any probabilistic statements regarding the likelihood of this occurring need to be made carefully. Using this definition, the observed global temperature trend estimates from four datasets fall outside the 5-95 interval predicted by the CMIP5 models. Here we explore some of the plausible explanations for this discrepancy, and show that no unique explanation is likely to fully account for the hiatus.
trends↗