scholarly journals Two Approaches to Quantifying Uncertainty in Global Temperature Changes

2006 ◽  
Vol 19 (19) ◽  
pp. 4785-4796 ◽  
Author(s):  
Ana Lopez ◽  
Claudia Tebaldi ◽  
Mark New ◽  
Dave Stainforth ◽  
Myles Allen ◽  
...  
Keyword(s):  
General Circulation ◽  
Regional Climate ◽  
Regional Climate Change ◽  
General Circulation Models ◽  
Temperature Changes ◽  
Global Mean Temperature ◽  
Statistical Approaches ◽  
Quantifying Uncertainty ◽  
Global Mean ◽  
Probabilistic Projections

Abstract A Bayesian statistical model developed to produce probabilistic projections of regional climate change using observations and ensembles of general circulation models (GCMs) is applied to evaluate the probability distribution of global mean temperature change under different forcing scenarios. The results are compared to probabilistic projections obtained using optimal fingerprinting techniques that constrain GCM projections by observations. It is found that, due to the different assumptions underlying these statistical approaches, the predicted distributions differ significantly in particular in their uncertainty ranges. Results presented herein demonstrate that probabilistic projections of future climate are strongly dependent on the assumptions of the underlying methodologies.

scholarly journals A Scaling Approach to Probabilistic Assessment of Regional Climate Change

2012 ◽  
Vol 25 (9) ◽  
pp. 3117-3144 ◽  
Author(s):  
Katja Frieler ◽  
Malte Meinshausen ◽  
Matthias Mengel ◽  
Nadine Braun ◽  
William Hare
Keyword(s):  
Climate Change ◽  
Regional Climate ◽  
Regional Climate Change ◽  
New Approach ◽  
Global Mean Temperature ◽  
Temperature And Precipitation ◽  
Mean Temperature ◽  
Precipitation Changes ◽  
Global Mean ◽  
Probabilistic Projections

A new approach to probabilistic projections of regional climate change is introduced. It builds on the already established quasi-linear relation between global-mean temperature and regional climate change found in atmosphere–ocean general circulation models (AOGCMs). The new approach simultaneously 1) takes correlations between temperature- and precipitation-related uncertainty distributions into account, 2) enables the inclusion of predictors other than global-mean temperature, and 3) checks for the interscenario and interrun variability of the scaling relationships. This study tests the effectiveness of SOx and black carbon emissions and greenhouse gas forcings as additional predictors of precipitation changes. The future precipitation response is found to deviate substantially from the linear relationship with global-mean temperature change in some regions; thereby, the two main limitations of a simple linear scaling approach, namely having to rely on exogenous aerosol experiments (or ignoring their regional effect), and ignoring changes in scaling coefficients when approaching equilibrium conditions, are addressed. The additional predictors can markedly improve the emulation of AOGCM simulations. In some regions, variations in hydrological sensitivity (the percentage change of precipitation per degree of warming) across different scenarios can be reduced by more than 50%. Coupled to probabilistic projections of global-mean temperatures and greenhouse gas forcings, bidimensional distributions of regional temperature and precipitation changes accounting for multiple uncertainties are derived. Based on 20 Fourth Assessment Report AOGCMs (AR4 AOGCMs), probabilistic projections are provided for two representative concentration pathway (RCP) scenarios and 31 world regions (online database at www.pik-potsdam.de/primap/regional_temp_and_precip ). As an example application of the projections for climate adaptation and vulnerability studies, future changes in the surface mass balance of the Greenland Ice Sheet are computed.

scholarly journals Extreme Precipitation Spatial Analog: In Search of an Alternative Approach for Future Extreme Precipitation in Urban Hydrological Studies

Water ◽  
2019 ◽  
Vol 11 (5) ◽  
pp. 1032 ◽  
Author(s):  
Ariel Wang ◽  
Francina Dominguez ◽  
Arthur Schmidt
Keyword(s):  
Extreme Precipitation ◽  
General Circulation ◽  
Climate Models ◽  
Regional Climate ◽  
Regional Climate Change ◽  
Regional Climate Models ◽  
General Circulation Models ◽  
Precipitation Frequency ◽  
Spatio Temporal ◽  
Climate Change Assessment

In this paper, extreme precipitation spatial analog is examined as an alternative method to adapt extreme precipitation projections for use in urban hydrological studies. The idea for this method is that real climate records from some cities can serve as “analogs” that behave like potential future precipitation for other locations at small spatio-temporal scales. Extreme precipitation frequency quantiles of a 3.16 km 2 catchment in the Chicago area, computed using simulations from North American Regional Climate Change Assessment Program (NARCCAP) Regional Climate Models (RCMs) with L-moment method, were compared to National Oceanic and Atmospheric Administration (NOAA) Atlas 14 (NA14) quantiles at other cities. Variances in raw NARCCAP historical quantiles from different combinations of RCMs, General Circulation Models (GCMs), and remapping methods are much larger than those in NA14. The performance for NARCCAP quantiles tend to depend more on the RCMs than the GCMs, especially at durations less than 24-h. The uncertainties in bias-corrected future quantiles of NARCCAP are still large compared to those of NA14, and increase with rainfall duration. Results show that future 3-h and 30-day rainfall in Chicago will be similar to historical rainfall from Memphis, TN and Springfield, IL, respectively. This indicates that the spatial analog is potentially useful, but highlights the fact that the analogs may depend on the duration of the rainfall of interest.

Interpreting Results from the NARCCAP and NA-CORDEX Ensembles in the Context of Uncertainty in Regional Climate Change Projections

2018 ◽  
Vol 99 (10) ◽  
pp. 2093-2106 ◽  
Author(s):  
Ambarish V. Karmalkar
Keyword(s):  
Climate Change ◽  
North America ◽  
General Circulation ◽  
Climate Models ◽  
Regional Climate ◽  
Regional Climate Change ◽  
Internal Variability ◽  
General Circulation Models ◽  
Eastern United States ◽  
The Impact

AbstractTwo ensembles of dynamically downscaled climate simulations for North America—the North American Regional Climate Change Assessment Program (NARCCAP) and the Coordinated Regional Climate Downscaling Experiment (CORDEX) featuring simulations for North America (NA-CORDEX)—are analyzed to assess the impact of using a small set of global general circulation models (GCMs) and regional climate models (RCMs) on representing uncertainty in regional projections. Selecting GCMs for downscaling based on their equilibrium climate sensitivities is a reasonable strategy, but there are regions where the uncertainty is not fully captured. For instance, the six NA-CORDEX GCMs fail to span the full ranges produced by models in phase 5 of the Coupled Model Intercomparison Project (CMIP5) in summer temperature projections in the western and winter precipitation projections in the eastern United States. Similarly, the four NARCCAP GCMs are overall poor at spanning the full CMIP3 ranges in seasonal temperatures. For the Southeast, the NA-CORDEX GCMs capture the uncertainty in summer but not in winter projections, highlighting one consequence of downscaling a subset of GCMs. Ranges produced by the RCMs are often wider than their driving GCMs but are sensitive to the experimental design. For example, the downscaled projections of summer precipitation are of opposite polarity in two RCM ensembles in some regions. Additionally, the ability of the RCMs to simulate observed temperature trends is affected by the internal variability characteristics of both the RCMs and driving GCMs, and is not systematically related to their historical performance. This has implications for adequately sampling the impact of internal variability on regional trends and for using model performance to identify credible projections. These findings suggest that a multimodel perspective on uncertainties in regional projections is integral to the interpretation of RCM results.

An Improved Daily Weather Generator for the Assessment of Regional Climate Change Impacts

2021 ◽  
Author(s):  
Mohammad Reza Khazaei ◽  
Mehraveh Hasirchian ◽  
Bagher Zahabiyoun
Keyword(s):  
Climate Change ◽  
General Circulation ◽  
Regional Climate ◽  
Low Frequency ◽  
Climate Change Impacts ◽  
Regional Climate Change ◽  
General Circulation Models ◽  
Weather Generator ◽  
Weather Data ◽  
Monthly Precipitation

Abstract Weather Generators (WGs) are one of the major downscaling tools for assessing regional climate change impacts. However, some deficiencies in the performance of WGs have limited their usage. This paper presents a method for correcting the low-frequency variability (LFV) of precipitation in the Improved Weather Generator (IWG) model. The method is based on bias correction in the monthly precipitation distribution of the generated daily series. The performance of the modified model was tested directly by comparing the statistics of generated and observed weather data for 14 stations, and also indirectly by comparing the characteristics of simulated stream-flows of a basin from the simulations run based on generated and observed weather data. The results showed that the method not only corrected the LFV of precipitation but also improved the reproduction of many other statistics. The provided IWG2 model can serve as a useful tool for the downscaling of General Circulation Models (GCMs) scenarios to assess regional climate change impacts, especially hydrological effects.

Simulating present and future climates of southern Africa using general circulation models

1997 ◽  
Vol 21 (1) ◽  
pp. 51-78 ◽  
Author(s):  
A.M. Joubert ◽  
B.C. Hewitson
Keyword(s):  
Climate Change ◽  
Southern Africa ◽  
General Circulation ◽  
Regional Climate ◽  
Daily Rainfall ◽  
Regional Climate Change ◽  
Summer Rainfall ◽  
General Circulation Models ◽  
Empirical Downscaling ◽  
Projected Changes

The current state of regional climate and climate change modelling using GCMs is reviewed for southern Africa, and several approaches to regional climate change prediction which have been applied to southern Africa are assessed. Confidence in projected regional changes is based on the ability of a range of models to simulate present regional climate, and is greatest where intermodel consensus in terms of the nature of projected changes is highest. Both equil ibrium and transient climate change projections for southern Africa are considered. Warming projected over southern Africa is within the range of globally averaged estimates. Uncertainties associated with the parameterization of convection ensure that projected changes in rainfall at GCM grid scales remain unreliable. However, empirical downscaling approaches produce rainfall changes consistent with synoptic-scale circulation. Both downscaling and grid-scale approaches indicate a 10-15% decrease in summer rainfall over the central interior which may have important implications for surface hydrology. Climate change may be manifested as a change in variability, and not in mean climate. Over southern Africa, increases in the variability and intensity of daily rainfall events are indicated.

scholarly journals An Assessment of GCM Performance at a Regional Scale Using a Score-Based Method

2018 ◽  
Vol 2018 ◽  
pp. 1-12 ◽  
Author(s):  
Fangxin Shi ◽  
Zhihui Wang ◽  
Liang Qi ◽  
Rongxu Chen
Keyword(s):  
General Circulation ◽  
Regional Climate ◽  
Regional Scale ◽  
Regional Climate Change ◽  
General Circulation Models ◽  
Study Region ◽  
Simulated Precipitation ◽  
Rank Score ◽  
Change Impact ◽  
Grubbs Test

A multicriteria score-based method was developed to assess the performances of 18 general circulation models (GCMs) in the study region from 1970 to 2005. The results indicate the following. (1) GCMs simulate temperature better than rainfall. The temporal and spatial distributions of simulated temperature performed well compared with those from the observations. In comparison to temperature, the spatial distribution of simulated precipitation performed poorly. Most of the GCMs underestimated temperature and overestimated precipitation. (2) The Grubbs test was used to detect anomalous moving changes in the rank score (RS) results; the inm-cm4 and ipsl-cm5b-lr models were rejected when simulating temperature, while the bnu-esm and canesm2 models performed poorly when simulating precipitation. (3) Adding or removing any criterion does not significantly influence the RS result, which indicates that the multicriteria score-based method is robust. The advantages of using multicriteria score-based method to assess GCMs performance were demonstrated, and this method also provides a more comprehensive assessment when compared with the single-criterion method. The multicriteria method could replace other criteria as the research requirements and could be easily extended to different study regions; the results could be used for better informed regional climate change impact analyses.

scholarly journals A new climate dataset for systematic assessments of climate change impacts as a function of global warming

2013 ◽  
Vol 6 (5) ◽  
pp. 1689-1703 ◽  
Author(s):  
J. Heinke ◽  
S. Ostberg ◽  
S. Schaphoff ◽  
K. Frieler ◽  
C. Müller ◽  
...  
Keyword(s):  
Climate Change ◽  
Temperature Change ◽  
General Circulation ◽  
Climate Model ◽  
Climate Change Impacts ◽  
General Circulation Models ◽  
Climate Change Scenarios ◽  
Global Mean Temperature ◽  
Mean Temperature ◽  
Global Mean

Abstract. In the ongoing political debate on climate change, global mean temperature change (ΔTglob) has become the yardstick by which mitigation costs, impacts from unavoided climate change, and adaptation requirements are discussed. For a scientifically informed discourse along these lines, systematic assessments of climate change impacts as a function of ΔTglob are required. The current availability of climate change scenarios constrains this type of assessment to a narrow range of temperature change and/or a reduced ensemble of climate models. Here, a newly composed dataset of climate change scenarios is presented that addresses the specific requirements for global assessments of climate change impacts as a function of ΔTglob. A pattern-scaling approach is applied to extract generalised patterns of spatially explicit change in temperature, precipitation and cloudiness from 19 Atmosphere–Ocean General Circulation Models (AOGCMs). The patterns are combined with scenarios of global mean temperature increase obtained from the reduced-complexity climate model MAGICC6 to create climate scenarios covering warming levels from 1.5 to 5 degrees above pre-industrial levels around the year 2100. The patterns are shown to sufficiently maintain the original AOGCMs' climate change properties, even though they, necessarily, utilise a simplified relationships between ΔTglob and changes in local climate properties. The dataset (made available online upon final publication of this paper) facilitates systematic analyses of climate change impacts as it covers a wider and finer-spaced range of climate change scenarios than the original AOGCM simulations.

scholarly journals The relevance of mid-Holocene Arctic warming to the future

2019 ◽  
Vol 15 (4) ◽  
pp. 1375-1394 ◽  
Author(s):  
Masakazu Yoshimori ◽  
Marina Suzuki
Keyword(s):  
Surface Temperature ◽  
General Circulation ◽  
Temperature Response ◽  
Longwave Radiation ◽  
General Circulation Models ◽  
Cross Model ◽  
Arctic Warming ◽  
Temperature Changes ◽  
The Future ◽  
Arctic Climate Change

Abstract. There remain substantial uncertainties in future projections of Arctic climate change. There is a potential to constrain these uncertainties using a combination of paleoclimate simulations and proxy data, but such a constraint must be accompanied by physical understanding on the connection between past and future simulations. Here, we examine the relevance of an Arctic warming mechanism in the mid-Holocene (MH) to the future with emphasis on process understanding. We conducted a surface energy balance analysis on 10 atmosphere and ocean general circulation models under the MH and future Representative Concentration Pathway (RCP) 4.5 scenario forcings. It is found that many of the dominant processes that amplify Arctic warming over the ocean from late autumn to early winter are common between the two periods, despite the difference in the source of the forcing (insolation vs. greenhouse gases). The positive albedo feedback in summer results in an increase in oceanic heat release in the colder season when the atmospheric stratification is strong, and an increased greenhouse effect from clouds helps amplify the warming during the season with small insolation. The seasonal progress was elucidated by the decomposition of the factors associated with sea surface temperature, ice concentration, and ice surface temperature changes. We also quantified the contribution of individual components to the inter-model variance in the surface temperature changes. The downward clear-sky longwave radiation is one of major contributors to the model spread throughout the year. Other controlling terms for the model spread vary with the season, but they are similar between the MH and the future in each season. This result suggests that the MH Arctic change may not be analogous to the future in some seasons when the temperature response differs, but it is still useful to constrain the model spread in the future Arctic projection. The cross-model correlation suggests that the feedbacks in preceding seasons should not be overlooked when determining constraints, particularly summer sea ice cover for the constraint of autumn–winter surface temperature response.

scholarly journals Large methane releases lead to strong aerosol forcing and reduced cloudiness

2011 ◽  
Vol 11 (3) ◽  
pp. 9057-9081
Author(s):  
T. Kurtén ◽  
L. Zhou ◽  
R. Makkonen ◽  
J. Merikanto ◽  
P. Räisänen ◽  
...  
Keyword(s):  
Radiative Forcing ◽  
General Circulation ◽  
Cloud Droplet ◽  
Fold Increase ◽  
General Circulation Models ◽  
Large Temperature ◽  
Atmospheric Lifetime ◽  
Temperature Changes ◽  
Aerosol Forcing ◽  
Rapid Amplification

Abstract. The release of vast quantities of methane into the atmosphere as a result of clathrate destabilization is a potential mechanism for rapid amplification of global warming. Previous studies have calculated the enhanced warming based mainly on the radiative effect of the methane itself, with smaller contributions from the associated carbon dioxide or ozone increases. Here, we study the effect of strongly elevated methane (CH4) levels on oxidant and aerosol particle concentrations using a combination of chemistry-transport and general circulation models. A 10-fold increase in methane concentrations is predicted to significantly decrease hydroxyl radical (OH) concentrations, while moderately increasing ozone (O3). These changes lead to a 70% increase in the atmospheric lifetime of methane, and an 18% decrease in global mean cloud droplet number concentrations (CDNC). The CDNC change causes a radiative forcing that is comparable in magnitude to the longwave radiative forcing ("enhanced greenhouse effect") of the added methane. Together, the indirect CH4-O3 and CH4-OH-aerosol forcings could more than double the warming effect of large methane increases. Our findings may help explain the anomalously large temperature changes associated with historic methane releases.

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