Projected precipitation and air temperature over Europe using a performance-based selection method of CMIP5 GCMs

2015 ◽  
Vol 7 (1) ◽  
pp. 103-113 ◽  
Author(s):  
Dmitry Basharin ◽  
Alexander Polonsky ◽  
Gintautas Stankūnavičius
Keyword(s):  
Climate Change ◽  
Air Temperature ◽  
21St Century ◽  
General Circulation ◽  
Climate Models ◽  
Surface Air Temperature ◽  
General Circulation Models ◽  
Selection Method ◽  
Regional Warming ◽  
A Performance

An assessment of the plausible climate change in precipitation and surface air temperature (SAT) over the European region by the end of the 21st century is provided. The assessment is based on the results of output of the ocean–atmosphere models participating in the Coupled Model Intercomparison Project, phase 5 (CMIP5). Six climate models that best reproduce the historical behaviour of SAT over greater Europe were selected from the CMIP5 project using a performance-based selection method of CMIP5 general circulation models for further assessments. The analysis of historical simulations within the scope of the CMIP5 project reveals that six models (namely, CNRM-CM5, HadGEM2ES, GFDL-CM3, CanESM2, MIROC5 and MPI-ESM-LR) sufficiently reproduce historical tendencies and natural variability over the region of interest. The climate change in SAT and precipitation by the end of the 21st century (2070–2099) was examined within the scope of RCP4.5 and RCP8.5 scenarios for these selected models. Typical regional warming due to RCP4.5 (RCP8.5) scenario is assessed as 3–4.5 °C (as 4–8 °C) in summer and winter, while a significant reduction of precipitation (typically 20–40%) is obtained only in summer.

scholarly journals Evaluating the effects of climate change on precipitation and temperature for Iran using RCP scenarios

2020 ◽  
Author(s):  
Shahab Doulabian ◽  
Saeed Golian ◽  
Amirhossein Shadmehri Toosi ◽  
Conor Murphy
Keyword(s):  
Climate Change ◽  
General Circulation ◽  
Climate Models ◽  
Surface Air Temperature ◽  
General Circulation Models ◽  
Skill Score ◽  
Climatic Conditions ◽  
Historical Period ◽  
Rcp Scenarios ◽  
Wide Range

Abstract Climate change has caused many changes in hydrologic processes and climatic conditions globally, while extreme events are likely to occur more frequently at a global scale with continued warming. Given the importance of general circulation models (GCMs) as an essential tool for climate studies at global/regional scales, together with the wide range of GCMs available, selecting appropriate models is of great importance. In this study, six synoptic weather stations were selected as representative of different climatic zones over Iran. Utilizing monthly data for 20 years (1981–2000), the outputs of 25 GCMs for surface air temperature (SAT) and precipitation were evaluated for the historical period. The root-mean-square error and skill score were chosen to evaluate the performance of GCMs in capturing observed seasonal climate. Finally, the outputs of selected GCMs for the three Representative Concentration Pathways emission scenarios (RCPs), namely RCP2.6, RCP4.5, and RCP8.5, were downscaled using the change factor method for each station for the period 2046–2065. Results indicate that SAT in all months is likely to increase for each region, while for precipitation, large uncertainties emerge, despite the selection of climate models that best capture the observed seasonal cycle. These results highlight the importance of selecting a representative ensemble of GCMs for assessing future hydro-climatic changes for Iran.

scholarly journals Optimal Determination of Time-Varying Climate Change Signals

2012 ◽  
Vol 25 (20) ◽  
pp. 7122-7137 ◽  
Author(s):  
Liwei Jia ◽  
Timothy DelSole
Keyword(s):  
Climate Change ◽  
Air Temperature ◽  
General Circulation ◽  
Extreme Values ◽  
Time Lag ◽  
Surface Air Temperature ◽  
Volcanic Eruptions ◽  
General Circulation Models ◽  
Optimal Method ◽  
Precipitation Anomalies

Abstract This paper proposes an optimal method for estimating time-dependent climate change signals from general circulation models. The basic idea is to identify vectors that maximize the mean-square detection statistic derived from optimal fingerprinting techniques. The method also provides an objective and systematic procedure for identifying the limit to which a signal can be restricted in space and time without losing detectability. As an illustration, the method is applied to the Coupled Model Intercomparison Project, phase 3 multimodel dataset to determine the continental seasonal-mean anomaly in surface air temperature and precipitation that is most detectable, on average, in these models. Anomalies in seasonal-mean surface air temperature are detectable in all seasons by almost all models on all continents but Europe; seasonal-mean anomalies over Europe are undetectable for some models, though this does not preclude other expressions of the signal, such as those that include longer time averages or time-lag information, from being detectable. Detectability in seasonal-mean temperature is found not only for multidecadal warming trends but also for cooling after major volcanic eruptions. In contrast, seasonal-mean precipitation anomalies are detectable in only a few models for averages over 5 yr or more, suggesting that the signal should include more spatiotemporal detail to be detectable across more models. Nevertheless, of the precipitation anomalies that are detectable, the signal appears to be of two characters: a systematic trend and enhanced frequency of extreme values. These results derived from twentieth-century simulations appear to be consistent with previous studies based on twenty-first-century simulations with larger signal-to-noise ratios.

scholarly journals Future Changes in Precipitation and Drought Characteristics over Bangladesh Under CMIP5 Climatological Projections

Water ◽  
2019 ◽  
Vol 11 (11) ◽  
pp. 2219 ◽  
Author(s):  
Kamruzzaman ◽  
Jang ◽  
Cho ◽  
Hwang
Keyword(s):  
Climate Change ◽  
21St Century ◽  
General Circulation ◽  
General Circulation Models ◽  
Northern Region ◽  
Medium Term ◽  
Rcp Scenarios ◽  
Drought Characteristics ◽  
The Future ◽  
Northwestern Region

: The impacts of climate change on precipitation and drought characteristics over Bangladesh were examined by using the daily precipitation outputs from 29 bias-corrected general circulation models (GCMs) under the representative concentration pathway (RCP) 4.5 and 8.5 scenarios. A precipitation-based drought estimator, namely, the Effective Drought Index (EDI), was applied to quantify the characteristics of drought events in terms of the severity and duration. The changes in drought characteristics were assessed for the beginning (2010–2039), middle (2040–2069), and end of this century (2070–2099) relative to the 1976–2005 baseline. The GCMs were limited in regard to forecasting the occurrence of future extreme droughts. Overall, the findings showed that the annual precipitation will increase in the 21st century over Bangladesh; the increasing rate was comparatively higher under the RCP8.5 scenario. The highest increase in rainfall is expected to happen over the drought-prone northern region. The general trends of drought frequency, duration, and intensity are likely to decrease in the 21st century over Bangladesh under both RCP scenarios, except for the maximum drought intensity during the beginning of the century, which is projected to increase over the country. The extreme and medium-term drought events did not show any significant changes in the future under both scenarios except for the medium-term droughts, which decreased by 55% compared to the base period during the 2070s under RCP8.5. However, extreme drought days will likely increase in most of the cropping seasons for the different future periods under both scenarios. The spatial distribution of changes in drought characteristics indicates that the drought-vulnerable areas are expected to shift from the northwestern region to the central and the southern region in the future under both scenarios due to the effects of climate change.

Ensemble climate predictions using climate models and observational constraints

2007 ◽  
Vol 365 (1857) ◽  
pp. 2029-2052 ◽  
Author(s):  
Peter A Stott ◽  
Chris E Forest
Keyword(s):  
Climate Change ◽  
General Circulation ◽  
Climate Changes ◽  
Climate Models ◽  
State Of The Art ◽  
General Circulation Models ◽  
Computationally Efficient ◽  
Temperature Changes ◽  
Large Ensembles ◽  
Past Climate Change

Two different approaches are described for constraining climate predictions based on observations of past climate change. The first uses large ensembles of simulations from computationally efficient models and the second uses small ensembles from state-of-the-art coupled ocean–atmosphere general circulation models. Each approach is described and the advantages of each are discussed. When compared, the two approaches are shown to give consistent ranges for future temperature changes. The consistency of these results, when obtained using independent techniques, demonstrates that past observed climate changes provide robust constraints on probable future climate changes. Such probabilistic predictions are useful for communities seeking to adapt to future change as well as providing important information for devising strategies for mitigating climate change.

scholarly journals Future Changes in Precipitation and Drought Characteristics over Bangladesh under CMIP5 Climatological Projections

2019 ◽  
Author(s):  
Mohammad Kamruzzaman ◽  
Min-Won Jang ◽  
Jaepil Cho ◽  
Syewoon Hwang
Keyword(s):  
Climate Change ◽  
21St Century ◽  
General Circulation ◽  
General Circulation Models ◽  
Northern Region ◽  
Medium Term ◽  
Rcp Scenarios ◽  
Drought Characteristics ◽  
The Future ◽  
Northwestern Region

The impacts of climate change on precipitation and drought characteristics over Bangladesh were examined by using the daily precipitation outputs from 29 bias-corrected general circulation models (GCMs) under the representative concentration pathway (RCP) 4.5 and 8.5 scenarios. A precipitation-based drought estimator, namely, the Effective Drought Index (EDI), was applied to quantify the characteristics of drought events in terms of the severity and duration. The changes in drought characteristics were assessed for the beginning (2010–2039), middle (2040–2069), and end of this century (2070–2099) relative to the 1976–2005 baseline. The GCMs were limited in regard to forecasting the occurrence of future extreme droughts. Overall, the findings showed that the annual precipitation will increase in the 21st century over Bangladesh; the increasing rate was comparatively higher under the RCP8.5 scenario. The highest increase of rainfall is expected to happen over the drought-prone northern region. The general trends of drought frequency, duration, and intensity are likely to decrease in the 21st century over Bangladesh under both RCP scenarios, except for the maximum drought intensity during the beginning of the century, which is projected to increase over the country. The extreme and medium-term drought events did not show any significant changes in the future under both scenarios except for the medium-term droughts, which decreased by 55% compared to the base period during the 2070s under RCP8.5. However, extreme drought days will likely increase in most of the cropping seasons for the different future periods under both scenarios. The spatial distribution of changes in drought characteristics indicates that the drought-vulnerable areas are expected to shift from the northwestern region to the central and the southern region in the future under both scenarios due to the effects of climate change.

scholarly journals Global Circulation Models (GCMs) Simulate the Current Temperature Only If the Shortwave Radiation Anomaly of the 2000s Has Been Omitted

2021 ◽  
pp. 45-52
Author(s):  
Antero Ollila
Keyword(s):  
Climate Change ◽  
General Circulation ◽  
Climate Models ◽  
Coupled Model ◽  
General Circulation Models ◽  
Scientific Basis ◽  
Shortwave Radiation ◽  
Global Circulation ◽  
Global Circulation Models ◽  
Paris Climate Agreement

The research article of Gillett et al. was published in Nature Climate Change (NCC) in March 2021. The objective of the NCC study was to simulate human-induced forcings to warming by applying 13 CMIP6 (Coupled Model Intercomparison Project Phase 6) climate models. NCC did not accept the author’s remarks as a “Matters arising” article. The purpose of this article is to detail the original three remarks and one additional remark: 1) the discrepancy between the graphs and reported numerical values, 2) the forcings of aerosols and clouds, 3) the positive water feedback, and 4) the calculation basis of the Paris agreement. The most important finding is that General Circulation Models (GCMs) used in simulations omit the significant shortwave anomaly from 2001 to 2019, which causes a temperature error of 0.3°C according to climate change physics of Gillett et al. For the year 2019, this error is 0.8°C showing the magnitude of shortwave anomaly impact. The main reason for this error turns out to be the positive water feedback generally applied in climate models. The scientific basis of the Paris climate agreement is faulty for the same reason.

scholarly journals The Effects of Gridding Algorithms on the Statistical Moments and Their Trends of Daily Surface Air Temperature*

2015 ◽  
Vol 28 (23) ◽  
pp. 9188-9205 ◽  
Author(s):  
Nicholas R. Cavanaugh ◽  
Samuel S. P. Shen
Keyword(s):  
Climate Change ◽  
Air Temperature ◽  
Climate Models ◽  
Decadal Variability ◽  
Surface Air Temperature ◽  
Higher Order ◽  
Statistical Moments ◽  
Weighted Sums ◽  
Higher Order Moments ◽  
Station Data

Abstract This paper explores the effects from averaging weather station data onto a grid on the first four statistical moments of daily minimum and maximum surface air temperature (SAT) anomalies over the entire globe. The Global Historical Climatology Network–Daily (GHCND) and the Met Office Hadley Centre GHCND (HadGHCND) datasets from 1950 to 2010 are examined. The GHCND station data exhibit large spatial patterns for each moment and statistically significant moment trends from 1950 to 2010, indicating that SAT probability density functions are non-Gaussian and have undergone characteristic changes in shape due to decadal variability and/or climate change. Comparisons with station data show that gridded averages always underestimate observed variability, particularly in the extremes, and have altered moment trends that are in some cases opposite in sign over large geographic areas. A statistical closure approach based on the quasi-normal approximation is taken to explore SAT’s higher-order moments and point correlation structure. This study focuses specifically on relating variability calculated from station data to that from gridded data through the moment equations for weighted sums of random variables. The higher-order and nonlinear spatial correlations up to the fourth order demonstrate that higher-order moments at grid scale can be determined approximately by functions of station pair correlations that tend to follow the usual Kolmogorov scaling relation. These results can aid in the development of constraints to reduce uncertainties in climate models and have implications for studies of atmospheric variability, extremes, and climate change using gridded observations.

scholarly journals Evaluation of data-driven models to downscale rainfall parameters from global climate models outputs: the case study of Latyan watershed

2018 ◽  
Vol 11 (1) ◽  
pp. 200-216 ◽  
Author(s):  
Reza Haji Hosseini ◽  
Saeed Golian ◽  
Jafar Yazdi
Keyword(s):  
Climate Change ◽  
General Circulation ◽  
Climate Models ◽  
Fuzzy Inference ◽  
Global Climate ◽  
General Circulation Models ◽  
Global Climate Models ◽  
Data Driven ◽  
Observation Data ◽  
Inference System

Abstract Assessment of climate change in future periods is considered necessary, especially with regard to probable changes to water resources. One of the methods for estimating climate change is the use of the simulation outputs of general circulation models (GCMs). However, due to the low resolution of these models, they are not applicable to regional and local studies and downscaling methods should be applied. The purpose of the present study was to use GCM models' outputs for downscaling precipitation measurements at Amameh station in Latyan dam basin. For this purpose, the observation data from the Amameh station during the 1980–2005 period, 26 output variables from two GCM models, namely, HadCM3 and CanESM2 were used. Downscaling was performed by three data-driven methods, namely, artificial neural network (ANN), nonparametric K-nearest neighborhood (KNN) method, and adaptive network-based fuzzy inference system method (ANFIS). Comparison of the monthly results showed the superiority of KNN compared to the other two methods in simulating precipitation. However, all three, ANN, KNN, and ANFIS methods, showed satisfactory results for both HadDCM3 and CanESM2 GCM models in downscaling precipitation in the study area.

Twentieth-Century Surface Air Temperature over China and the Globe Simulated by Coupled Climate Models

2006 ◽  
Vol 19 (22) ◽  
pp. 5843-5858 ◽  
Author(s):  
Tianjun Zhou ◽  
Rucong Yu
Keyword(s):  
Climate Change ◽  
Twentieth Century ◽  
Air Temperature ◽  
Climate Models ◽  
Eastern China ◽  
Surface Air Temperature ◽  
Future Climate Change ◽  
Intergovernmental Panel ◽  
Coupled Climate Models ◽  
Anthropogenic Forcings

Abstract This paper examines variations of the surface air temperature (SAT) over China and the globe in the twentieth century simulated by 19 coupled climate models driven by historical natural and anthropogenic forcings. Most models perform well in simulating both the global and the Northern Hemispheric mean SAT evolutions of the twentieth century. The inclusion of natural forcings improves the simulation, in particular for the first half of the century. The reproducibility of the SAT averaged over China is lower than that of the global and hemispheric averages, but it is still acceptable. The contribution of natural forcings to the SAT over China in the first half of the century is not as robust as that to the global and hemispheric averages. No model could successfully produce the reconstructed warming over China in the 1920s. The prescribed natural and anthropogenic forcings in the coupled climate models mainly produce the warming trends and the decadal- to interdecadal-scale SAT variations with poor performances at shorter time scales. The prominent warming trend in the last half of the century over China and its acceleration in recent decades are weakly simulated. There are discrepancies between the simulated and observed regional features of the SAT trend over China. Few models could produce the summertime cooling over the middle part of eastern China (27°–36°N), while two models acceptably produce the meridional gradients of the wintertime warming trends, with north China experiencing larger warming. Limitations of the current state-of-the-art coupled climate models in simulating spatial patterns of the twentieth-century SAT over China cast a shadow upon their capability toward projecting credible geographical distributions of future climate change through Intergovernmental Panel on Climate Change (IPCC) scenario simulations.

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.

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