Statistisches Downscaling von CMIP6 Projektionen mit EPISODES  

2020 ◽  
Author(s):  
Philip Lorenz ◽  
Frank Kreienkamp ◽  
Tobias Geiger
Keyword(s):  
Climate Sensitivity ◽  
Coupled Model ◽  
Model Intercomparison ◽  
Equilibrium Climate Sensitivity ◽  
Intercomparison Project

<p>Die Ergebnisse der Klimamodellierung, die im Rahmen des jüngsten Coupled Model Intercomparison Project (CMIP6) durchgeführt wurden, zeigen signifikante Veränderungen der modellspezifischen Gleichgewichtsklimaempfindlichkeit (Equilibrium Climate Sensitivity, ECS) im Vergleich zum Vorgängerprojekt CMIP5. Die neueren Versionen vieler globaler Klimamodelle (GCMs) weisen höhere ECS-Werte auf, die zu einer stärkeren globalen Erwärmung führen als zuvor berechnet. Gleichzeitig ist die Multi-GCM-Streuung von ECS unter CMIP6 deutlich größer als unter CMIP5.</p> <p>Ein Teil der im Rahmen von CMIP6 durchgeführten Klimaprojektionen wurden mittels der am DWD entwickelten statistisch-empirischen Downscaling-Methode EPISODES für das Gebiet von Deutschland regionalisiert. Diese Ergebnisse wurden mit vergleichbaren Datensätzen der CMIP5-Läufe verglichen. Die Ergebnisse dieser Analysen werden vorgestellt.</p>

scholarly journals Estimating Remaining Carbon Budgets Using Emulators of CMIP6 Models

2020 ◽  
Author(s):  
Martin Rypdal ◽  
Niklas Boers ◽  
Hege-Beate Fredriksen ◽  
Kai-Uwe Eiselt ◽  
Andreas Johansen ◽  
...  
Keyword(s):  
Climate Sensitivity ◽  
Carbon Budget ◽  
Climate Models ◽  
Coupled Model ◽  
Model Intercomparison ◽  
Equilibrium Climate Sensitivity ◽  
Uncertainty Range ◽  
The Public ◽  
Intercomparison Project ◽  
Specific Temperature

Abstract A remaining carbon budget (RCB) estimates how much CO2 we can emit and still reach a specific temperature target. The RCB concept is attractive since it easily communicates to the public and policymakers, but RCBs are also subject to uncertainties. The expected warming levels for a given carbon budget has a wide uncertainty range, which we show here to increase with less ambitious targets, i.e., with higher CO2 emissions and temperatures. We demonstrate that the leading cause of the revealed RCB uncertainty is the spread in the equilibrium climate sensitivity (ECS) among climate models. In the Coupled Model Intercomparison Project Phase 6 (CMIP6) ensemble, the models with the lower ECS predict an RCB that is twice as high as that of models with the higher ECS, for temperature targets between 1.5-3.0°C.

scholarly journals Effective radiative forcing and adjustments in CMIP6 models

2020 ◽  
Vol 20 (16) ◽  
pp. 9591-9618 ◽  
Author(s):  
Christopher J. Smith ◽  
Ryan J. Kramer ◽  
Gunnar Myhre ◽  
Kari Alterskjær ◽  
William Collins ◽  
...  
Keyword(s):  
Climate Sensitivity ◽  
Radiative Forcing ◽  
Climate Models ◽  
Coupled Model ◽  
Internal Variability ◽  
Cmip5 Models ◽  
Model Intercomparison ◽  
Aerosol Forcing ◽  
Intercomparison Project ◽  
Effective Radiative Forcing

Abstract. The effective radiative forcing, which includes the instantaneous forcing plus adjustments from the atmosphere and surface, has emerged as the key metric of evaluating human and natural influence on the climate. We evaluate effective radiative forcing and adjustments in 17 contemporary climate models that are participating in the Coupled Model Intercomparison Project (CMIP6) and have contributed to the Radiative Forcing Model Intercomparison Project (RFMIP). Present-day (2014) global-mean anthropogenic forcing relative to pre-industrial (1850) levels from climate models stands at 2.00 (±0.23) W m−2, comprised of 1.81 (±0.09) W m−2 from CO2, 1.08 (± 0.21) W m−2 from other well-mixed greenhouse gases, −1.01 (± 0.23) W m−2 from aerosols and −0.09 (±0.13) W m−2 from land use change. Quoted uncertainties are 1 standard deviation across model best estimates, and 90 % confidence in the reported forcings, due to internal variability, is typically within 0.1 W m−2. The majority of the remaining 0.21 W m−2 is likely to be from ozone. In most cases, the largest contributors to the spread in effective radiative forcing (ERF) is from the instantaneous radiative forcing (IRF) and from cloud responses, particularly aerosol–cloud interactions to aerosol forcing. As determined in previous studies, cancellation of tropospheric and surface adjustments means that the stratospherically adjusted radiative forcing is approximately equal to ERF for greenhouse gas forcing but not for aerosols, and consequentially, not for the anthropogenic total. The spread of aerosol forcing ranges from −0.63 to −1.37 W m−2, exhibiting a less negative mean and narrower range compared to 10 CMIP5 models. The spread in 4×CO2 forcing has also narrowed in CMIP6 compared to 13 CMIP5 models. Aerosol forcing is uncorrelated with climate sensitivity. Therefore, there is no evidence to suggest that the increasing spread in climate sensitivity in CMIP6 models, particularly related to high-sensitivity models, is a consequence of a stronger negative present-day aerosol forcing and little evidence that modelling groups are systematically tuning climate sensitivity or aerosol forcing to recreate observed historical warming.

scholarly journals Time Variation of Effective Climate Sensitivity in GCMs

2008 ◽  
Vol 21 (19) ◽  
pp. 5076-5090 ◽  
Author(s):  
K. D. Williams ◽  
W. J. Ingram ◽  
J. M. Gregory
Keyword(s):  
Climate Sensitivity ◽  
Time Scale ◽  
General Circulation ◽  
Coupled Model ◽  
Circulation Model ◽  
Equilibrium Climate Sensitivity ◽  
Mixed Layer Ocean ◽  
Intercomparison Project ◽  
Apparent Variation ◽  
Centennial Time Scale

Abstract Effective climate sensitivity is often assumed to be constant (if uncertain), but some previous studies of general circulation model (GCM) simulations have found it varying as the simulation progresses. This complicates the fitting of simple models to such simulations, as well as having implications for the estimation of climate sensitivity from observations. This study examines the evolution of the feedbacks determining the climate sensitivity in GCMs submitted to the Coupled Model Intercomparison Project. Apparent centennial-time-scale variations of effective climate sensitivity during stabilization to a forcing can be considered an artifact of using conventional forcings, which only allow for instantaneous effects and stratospheric adjustment. If the forcing is adjusted for processes occurring on time scales that are short compared to the climate stabilization time scale, then there is little centennial-time-scale evolution of effective climate sensitivity in any of the GCMs. Here it is suggested that much of the apparent variation in effective climate sensitivity identified in previous studies is actually due to the comparatively fast forcing adjustment. Persistent differences are found in the strength of the feedbacks between the coupled atmosphere–ocean (AO) versions and their atmosphere–mixed layer ocean (AML) counterparts (the latter are often assumed to give the equilibrium climate sensitivity of the AOGCM). The AML model can typically only estimate the equilibrium climate sensitivity of the parallel AO version to within about 0.5 K. The adjustment to the forcing to account for comparatively fast processes varies in magnitude and sign between GCMs, as well as differing between AO and AML versions of the same model. There is evidence from one AOGCM that the forcing adjustment may take a couple of decades, with implications for observationally based estimates of equilibrium climate sensitivity. It is suggested that at least some of the spread in twenty-first-century global temperature predictions between GCMs is due to differing adjustment processes, hence work to understand these differences should be a priority.

scholarly journals Context for interpreting equilibrium climate sensitivity and transient climate response from the CMIP6 Earth system models

2020 ◽  
Vol 6 (26) ◽  
pp. eaba1981 ◽  
Author(s):  
Gerald A. Meehl ◽  
Catherine A. Senior ◽  
Veronika Eyring ◽  
Gregory Flato ◽  
Jean-Francois Lamarque ◽  
...  
Keyword(s):  
Climate Sensitivity ◽  
Coupled Model ◽  
Cmip5 Models ◽  
Climate Response ◽  
Earth System ◽  
Transient Climate Response ◽  
Equilibrium Climate Sensitivity ◽  
System Models ◽  
Intercomparison Project ◽  
Earth System Models

For the current generation of earth system models participating in the Coupled Model Intercomparison Project Phase 6 (CMIP6), the range of equilibrium climate sensitivity (ECS, a hypothetical value of global warming at equilibrium for a doubling of CO2) is 1.8°C to 5.6°C, the largest of any generation of models dating to the 1990s. Meanwhile, the range of transient climate response (TCR, the surface temperature warming around the time of CO2 doubling in a 1% per year CO2 increase simulation) for the CMIP6 models of 1.7°C (1.3°C to 3.0°C) is only slightly larger than for the CMIP3 and CMIP5 models. Here we review and synthesize the latest developments in ECS and TCR values in CMIP, compile possible reasons for the current values as supplied by the modeling groups, and highlight future directions. Cloud feedbacks and cloud-aerosol interactions are the most likely contributors to the high values and increased range of ECS in CMIP6.

scholarly journals Could the Pliocene constrain the equilibrium climate sensitivity?

2016 ◽  
Vol 12 (8) ◽  
pp. 1591-1599 ◽  
Author(s):  
J. C. Hargreaves ◽  
J. D. Annan
Keyword(s):  
Climate Sensitivity ◽  
Atmospheric Carbon Dioxide ◽  
Climate Models ◽  
Climate Model ◽  
Temperature Anomaly ◽  
Model Intercomparison ◽  
Equilibrium Climate Sensitivity ◽  
Intercomparison Project ◽  
First Time ◽  
Industrial State

Abstract. The mid-Pliocene Warm Period (mPWP) is the most recent interval in which atmospheric carbon dioxide was substantially higher than in modern pre-industrial times. It is, therefore, a potentially valuable target for testing the ability of climate models to simulate climates warmer than the pre-industrial state. The recent Pliocene Model Intercomparison Project (PlioMIP) presented boundary conditions for the mPWP and a protocol for climate model experiments. Here we analyse results from the PlioMIP and, for the first time, discuss the potential for this interval to usefully constrain the equilibrium climate sensitivity. We observe a correlation in the ensemble between their tropical temperature anomalies at the mPWP and their equilibrium sensitivities. If the real world is assumed to also obey this relationship, then the reconstructed tropical temperature anomaly at the mPWP can in principle generate a constraint on the true sensitivity. Directly applying this methodology using available data yields a range for the equilibrium sensitivity of 1.9–3.7 °C, but there are considerable additional uncertainties surrounding the analysis which are not included in this estimate. We consider the extent to which these uncertainties may be better quantified and perhaps lessened in the next few years.

Is 1.5 °C of global warming inevitable and if so, when?

2021 ◽  
Author(s):  
Sebastian Milinski ◽  
Erich Fischer ◽  
Piers Forster ◽  
John C. Fyfe ◽  
June-Yi Lee ◽  
...  
Keyword(s):  
Global Warming ◽  
Climate Sensitivity ◽  
Coupled Model ◽  
Internal Variability ◽  
Balance Model ◽  
Model Intercomparison ◽  
The Core ◽  
Emissions Scenarios ◽  
Intercomparison Project ◽  
New Framework

<p>The likelihood of exceeding 1.5 °C of global warming relative to preindustrial depends on the warming observed so far, anthropogenic warming that may occur in the future, and the degree to which internal variability will either temporarily amplify or attenuate future anthropogenic warming.  Here, we introduce a new framework that estimates the likelihood of exceeding 1.5 °C of global warming wherein uncertainties in each one of these factors is explicitly accounted for.</p><p>In this new framework, we estimate the historical warming, and its uncertainty, from preindustrial to present using the recently-minted HadCRUT5 dataset. Future anthropogenic warming is estimated using an energy balance model tuned to an assessed range of climate sensitivity and applied to each of the core emissions scenarios (i.e. SSPs) underlying the Sixth Phase of the Coupled Model Intercomparison Project (CMIP6). Finally, we estimate the influence of internal variability using a large ensemble of initial condition simulations. On this basis, we find that the largest uncertainty in estimates of the likelihood of exceeding 1.5°C of global warming is due to model-to-model differences in estimates of future anthropogenic warming, followed by historical warming uncertainty, and then uncertainty due to internal variability.</p><p>Based on our analysis, we find that the earliest time for crossing 1.5 °C of global warming, here defined as the 5% likelihood, is approximately emissions-scenario independent. We define the 1.5 °C threshold without any overshoot: if a time series warms by more than 1.5 °C during any 20-year period before 2100, it is counted as having crossed 1.5 °C. In each considered scenario except SSP5-8.5, the 20-year average period that crosses the 1.5 °C threshold with a 5% likelihood is 2013 to 2032. On the other hand, the 50% likelihood does depend on the scenario, with the SSP5-8.5 crossing occurring in 2018 to 2037 and SSP1-1.9 crossing in 2022 to 2041. All scenarios except SSP1-1.9 have a likelihood close to 100% to cross 1.5 °C global warming before 2100. Even in SSP1-1.9, the scenario with the strongest emission reductions, there is a 71% likelihood to cross 1.5 °C by the end of this century. This implies that even in SSP1-1.9, the world may stay below 1.5 °C only if both climate sensitivity and historical warming are near the lower end of their respective distributions.</p><p>These estimates, with their associated uncertainties, may have major implications for policy decisions.</p>

scholarly journals Higher mass loss over Greenland and Antarctic ice sheets projected in CMIP6 than CMIP5 by high resolution regional downscaling EC-Earth

2020 ◽  
Author(s):  
Fredrik Boberg ◽  
Ruth Mottram ◽  
Nicolaj Hansen ◽  
Shuting Yang ◽  
Peter L. Langen
Keyword(s):  
Climate Model ◽  
Global Climate ◽  
Ice Sheet ◽  
Coupled Model ◽  
Surface Mass Balance ◽  
Model Intercomparison ◽  
Surface Mass ◽  
Equilibrium Climate Sensitivity ◽  
Intercomparison Project ◽  
The Mean

Abstract. The future rates of ice sheet melt in Greenland and Antarctica are an important factor when making estimates of the likely rate of sea level rise. Global climate models that took part in the fifth Coupled Model Intercomparison Project (CMIP5) have generally been unable to replicate observed rates of ice sheet melt. With the advent of the sixth Coupled Model Intercomparison Project (CMIP6), with a general increase in the equilibrium climate sensitivity, we here compare two versions of the global climate model EC-Earth using the regional climate model HIRHAM5 downscaling EC-Earth for Greenland and Antarctica. One version (v2) of EC-Earth is taken from CMIP5 for the high-emissions Representative Concentration Pathways (RCP8.5) scenario and the other (v3) from CMIP6 for the comparable high-emissions Shared Socioeconomic Pathways (SSP5-8.5) scenario). For Greenland, we downscale the two versions of EC-Earth for the historical period 1991–2010 and for the scenario period 2081–2100. For Antarctica, the periods are 1971–2000 and 2071–2100, respectively. For the Greenland Ice Sheet, we find that the mean change in temperature is 5.9 °C when downscaling EC-Earth v2 and 6.8 °C when downscaling EC-Earth v3. Corresponding values for Antarctica are 4.1 °C for v2 and 4.9 °C for v3. The mean change in surface mass balance at the end of the century under these high emissions scenarios is found to be −210 Gt yr−1 (v2) and −1150 Gt yr−1 (v3) for Greenland and +150 Gt yr−1 (v2) and −710 Gt yr−1 (v3) for Antarctica. These distinct differences in temperature change and particularly surface mass balance change are a result of the higher equilibrium climate sensitivity in EC-Earth v3 (4.3 K) compared with 3.3 K in EC-Earth v2 and the differences in greenhouse gas concentrations between the RCP8.5 and the SSP5-8.5 scenarios.

scholarly journals Overview of the Norwegian Earth System Model (NorESM2) and key climate response of CMIP6 DECK, historical, and scenario simulations

2020 ◽  
Vol 13 (12) ◽  
pp. 6165-6200
Author(s):  
Øyvind Seland ◽  
Mats Bentsen ◽  
Dirk Olivié ◽  
Thomas Toniazzo ◽  
Ada Gjermundsen ◽  
...  
Keyword(s):  
Sea Ice ◽  
Climate Sensitivity ◽  
Time Window ◽  
Coupled Model ◽  
Momentum Conservation ◽  
Earth System Model ◽  
System Model ◽  
Earth System ◽  
Model Intercomparison ◽  
Intercomparison Project

Abstract. The second version of the coupled Norwegian Earth System Model (NorESM2) is presented and evaluated. NorESM2 is based on the second version of the Community Earth System Model (CESM2) and shares with CESM2 the computer code infrastructure and many Earth system model components. However, NorESM2 employs entirely different ocean and ocean biogeochemistry models. The atmosphere component of NorESM2 (CAM-Nor) includes a different module for aerosol physics and chemistry, including interactions with cloud and radiation; additionally, CAM-Nor includes improvements in the formulation of local dry and moist energy conservation, in local and global angular momentum conservation, and in the computations for deep convection and air–sea fluxes. The surface components of NorESM2 have minor changes in the albedo calculations and to land and sea-ice models. We present results from simulations with NorESM2 that were carried out for the sixth phase of the Coupled Model Intercomparison Project (CMIP6). Two versions of the model are used: one with lower (∼ 2∘) atmosphere–land resolution and one with medium (∼ 1∘) atmosphere–land resolution. The stability of the pre-industrial climate and the sensitivity of the model to abrupt and gradual quadrupling of CO2 are assessed, along with the ability of the model to simulate the historical climate under the CMIP6 forcings. Compared to observations and reanalyses, NorESM2 represents an improvement over previous versions of NorESM in most aspects. NorESM2 appears less sensitive to greenhouse gas forcing than its predecessors, with an estimated equilibrium climate sensitivity of 2.5 K in both resolutions on a 150-year time frame; however, this estimate increases with the time window and the climate sensitivity at equilibration is much higher. We also consider the model response to future scenarios as defined by selected Shared Socioeconomic Pathways (SSPs) from the Scenario Model Intercomparison Project defined under CMIP6. Under the four scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5), the warming in the period 2090–2099 compared to 1850–1879 reaches 1.3, 2.2, 3.0, and 3.9 K in NorESM2-LM, and 1.3, 2.1, 3.1, and 3.9 K in NorESM-MM, robustly similar in both resolutions. NorESM2-LM shows a rather satisfactory evolution of recent sea-ice area. In NorESM2-LM, an ice-free Arctic Ocean is only avoided in the SSP1-2.6 scenario.

scholarly journals Future Changes in Simulated Evapotranspiration across Continental Africa Based on CMIP6 CNRM-CM6

2021 ◽  
Vol 18 (13) ◽  
pp. 6760
Author(s):  
Isaac Kwesi Nooni ◽  
Daniel Fiifi T. Hagan ◽  
Guojie Wang ◽  
Waheed Ullah ◽  
Jiao Lu ◽  
...  
Keyword(s):  
Extreme Events ◽  
Coupled Model ◽  
Baseline Period ◽  
Model Intercomparison ◽  
Additional Information ◽  
Intercomparison Project ◽  
Key Drivers ◽  
Model Ensembles ◽  
Projected Changes ◽  
Near Future

The main goal of this study was to assess the interannual variations and spatial patterns of projected changes in simulated evapotranspiration (ET) in the 21st century over continental Africa based on the latest Shared Socioeconomic Pathways and the Representative Concentration Pathways (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5) provided by the France Centre National de Recherches Météorologiques (CNRM-CM) model in the Sixth Phase of Coupled Model Intercomparison Project (CMIP6) framework. The projected spatial and temporal changes were computed for three time slices: 2020–2039 (near future), 2040–2069 (mid-century), and 2080–2099 (end-of-the-century), relative to the baseline period (1995–2014). The results show that the spatial pattern of the projected ET was not uniform and varied across the climate region and under the SSP-RCPs scenarios. Although the trends varied, they were statistically significant for all SSP-RCPs. The SSP5-8.5 and SSP3-7.0 projected higher ET seasonality than SSP1-2.6 and SSP2-4.5. In general, we suggest the need for modelers and forecasters to pay more attention to changes in the simulated ET and their impact on extreme events. The findings provide useful information for water resources managers to develop specific measures to mitigate extreme events in the regions most affected by possible changes in the region’s climate. However, readers are advised to treat the results with caution as they are based on a single GCM model. Further research on multi-model ensembles (as more models’ outputs become available) and possible key drivers may provide additional information on CMIP6 ET projections in the region.

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