Coupled Model Intercomparison Project Phase 5 Simulations Research Articles

Climate change impact on sea surface winds in Southeast Asia

AbstractNumerical representation and climate projections of sea surface winds over Southeast Asia (SEA) are assessed here using an ensemble of the Coupled Model Intercomparison Project Phase 5 (CMIP5) downscaled simulations performed over the 20th and 21st centuries under Representative Concentration Pathways (RCPs) 4.5 and 8.5 scenarios within the Coordinated Regional Climate Downscaling EXperiment (CORDEX)‐SEA project. The ensemble is based on two regional climate models (RCMs: RegCM4 and RCA4), and CMIP5 simulations are performed with five global climate models (GCMs: CNRM_CM5, HadGEM2, GFDL, MPI‐ESM‐MR, EC‐Earth). Comparison with QuikSCAT satellite data shows that dynamical downscaling improves sea surface wind speed representation, mainly by reducing its underestimation. The level of improvement depends on the RCM choice, GCM performance, and wind strength. Our results reveal significant differences in modelled projections of sea surface wind, depending on the model, RCP, region, and season. GCMs simulate weak and contrasted changes, stronger for RCP8.5, with no clear common trend. RCA4 simulates weak changes, with high similarities between pairs, but contrasted results between RCPs. RegCM4 simulate stronger changes, with a weakening of average and intense winds for all seasons, stronger in June–August, and in RCP8.5 than in RCP4.5. RCA4 and RegCM4 simulate different changes, with no clear common trend except a weakening of seasonal and intense winds and an increase of seasonal wind interannual variability for June–August in RCP4.5, stronger for RegCM4. This corresponds to a weakening of the boreal summer monsoon and a slight increase of its interannual variability and presumably to a decrease of the tropical cyclone frequency. Differences in seasonal sea surface wind changes between models are related to differences in sea level pressure gradient changes. For a given RCM, those differences are partly related to the differences between parent GCMs. Finally, results suggest that uncertainties related to the RCM choice are larger than those related to the GCM choice.

An assessment of the CMIP5 models in simulating the Argo geostrophic meridional transport in the North Pacific Ocean

Eleven climate system models that participate in the Coupled Model Intercomparison Project phase 5 (CMIP5) were evaluated based on an assessment of their simulated meridional transports in comparison with the Sverdrup transports. The analyses show that the simulated North Pacific Ocean circulation is essentially in Sverdrup balance in most of the 11 models while the Argo geostrophic meridional transports indicate significant non-Sverdrup gyre circulation in the tropical North Pacific Ocean. The climate models overestimated the observed tropical and subtropical volume transports significantly. The non-Sverdrup gyre circulation leads to non-Sverdrup heat and salt transports, the absence of which in the CMIP5 simulations suggests deficiencies of the CMIP5 model dynamics in simulating the realistic meridional volume, heat, and salt transports of the ocean.

Consecutive dry and wet days over South America and their association with ENSO events, in CMIP5 simulations

The assessment of ENSO influence on extreme rainfall events over South America will provide useful information to climate services. This research analyzes the performance of eleven global climate models (GCMs) from the Coupled Model Intercomparison Project Phase 5 (CMIP5) using skill score metrics to simulate two climate extreme rainfall indices: maximum number of consecutive dry days (CDD) and wet days (CWD). Additionally, another objective of this study is to characterize the spatial relationship between different types of El Nino–Southern Oscillation (ENSO)–El Nino Modoki Index (EMI) and Oceanic Nino Index (ONI)– and those indices of climate extremes of rainfall. The development of this research is carried out in South America, in the trimester October–December from “historical” experiment for the period 1979–2005. In general terms, the mean fields of CDD and CWD indices tend to be opposite, with main differences in Amazonas, Atacama Desert, and northeast of Brazil. The CDD–EMI and CDD–ONI correlations show a greater signal than CWD in South America. The CDD–EMI correlation is negative; nevertheless, the CDD-El Nino Modoki composite shows positive values in the northeast of Buenos Aires province. It can be concluded that most models are able to reproduce the gridded observed spatial pattern of extreme rainfall indices and their association with ENSO events. The results of this investigation could be a tool for new studies to analyze and compare the “historical” period with future projections in a context of climate change.

Analysis of CMIP 5 simulations of key climate indices associated with the South America monsoon system

AbstractAssessing the regional and local impacts of climate changes on rainfall and streamflow patterns is often challenging, as most results tend to be very dispersed and inconsistent across models. We offer a complementary alternative for climate change impact studies by focusing primarily on climate indices. In particular, we analyse the historical and future variability of key climate indices associated with the South America Monsoon System (SAMS) as simulated by Coupled Model Intercomparison Project—Phase 5 (CMIP5) models. We use climate indices related to the tropical Atlantic interhemispheric surface temperature gradient, associated with the meridional position of the Intertropical Convergence Zone (ITCZ), as well as the land‐ocean temperature contrast in the tropical Atlantic‐South America region, and the intensity and position of the South Atlantic Subtropical High (SASH). We selected 14 CMIP5 models to estimate climate indices for the retrospective period (1980–2005) and future period (2006–2099), the latter under the RCP 4.5 and RCP 8.5 scenarios. For comparison purposes during the retrospective period, the indices were also calculated using data from the Era‐Interim reanalysis. The seasonal behaviour of the Era‐Interim based indices is well reproduced by CMIP5 models, although the magnitude is significantly higher. For the future period, most models under both scenarios showed a consistent and asymmetrical intensification of the dipole index, suggesting, in a future climate, a potential wider displacement of the ITCZ during its seasonal cycle. As for the land‐ocean contrast index, the CMIP5 simulations indicated consistent increase in the magnitude for the positive phase (land warmer than ocean) and a decrease for the negative phase (land colder than ocean). Finally, CMIP5 models consistently predict a strengthening and southward displacement of the SASH centre. To the best of our knowledge, this is the first study to reveal future changes in climate indices associated with the SAMS that shows relevant coherences across models and scenarios.

Comparisons and evaluation of aerosol burden and optical depth in CMIP5 simulations over East Asia

Aerosol plays an important role in the climate system by affecting the radiative and energy balances. Hence, in this paper, the spatial patterns of aerosol burden and aerosol optical properties (AOD) in four the Coupled Model Intercomparison Project phase 5 (CMIP5) models over East Asia during 2001–2005 are compared to quantify inter-model differences and to evaluate AOD simulations against observations. The evaluation of AOD against Moderate Resolution Imaging Spectroradiometer (MODIS) satellite retrievals shows that CMIP5 models can reproduce the spatial pattern of MODIS AOD reasonably well. The mean AOD over eastern China shows that NorESM1-M underestimates MODIS AOD by 40%, due to the lack of emissions of some aerosol components, such as nitrate, biogenic aerosol, and non-desert mineral dust. In contrast to that, CSIRO-Mk3.6.0 overestimates annual mean of MODIS AOD over eastern China by 20%, partially caused by larger aerosol emissions and burden. Compared to MODIS AOD, GFDL-CM3 performs the best in simulating AOD in eastern China, because ammonium and nitrate are included in this model. The comparisons of CMIP5 and Aerosol Robotic Network (AERONET) AOD show similar results. In addition, the simulated AOD values are closer to AERONET AOD in Mongolia, China, Japan and Korea than that in India. The results also reveal that there are some inter-model differences of aerosol burden over East Asia, caused by the inter-model differences of aerosol emissions, wet scavenging, and transport. Over eastern and northwestern China and the west Pacific, the inter-model differences of anthropogenic aerosol burden and spatial variabilities are smaller than that of natural aerosol burden.

Application of the Bias Correction and Spatial Downscaling Algorithm on the Temperature Extremes From CMIP5 Multimodel Ensembles in China

AbstractThe Bias Correction and Spatial Downscaling (BCSD) is a trend‐preserving statistical downscaling algorithm, which has been widely used to generate accurate and high‐resolution data set. We employ the BCSD technique to statistically downscale projected daily maximum temperature (DMT) over China from 13 general circulation models in Coupled Model Intercomparison Project Phase 5 (CMIP5) project to supplement the National Aeronautics and Space Administration Earth Exchange Global Daily Downscaled Projections data set under the Representative Concentration Pathway 2.6 (RCP2.6) scenario. We then compare the differences of DMT and four DMT‐related indices (i.e., summer days (SU), annual maximum value of DMT (TXx), intensity, and frequency of heat wave) between before and after downscaling over eight subregions of China. The results indicate that the BCSD method reduces the cool bias of the DMT over the whole China compared with original CMIP5 simulations, especially over the Qinghai‐Tibet plateau. The SU increases after downscaling for both China as a whole and most subregions except for South China. The BCSD also affects the mean value of TXx, intensity, and frequency of heat wave at subregional scales, although it shows little impact on China as a whole. Besides, the BCSD reduces the temporal variability of most indices except for the heat wave frequency. The most striking finding is that the intermodel spreads of DMT, SU, TXx, and heat wave intensity are dramatically reduced after downscaling compared with raw CMIP5 simulations. In summary, the BCSD method shows significant improvements to original CMIP5 climate projections under RCP2.6 scenario.

Identifying teleconnections and multidecadal variability of East Asian surface temperature during the last millennium in CMIP5 simulations

Abstract. We examine the relationships in models and reconstructions between the multidecadal variability of surface temperature in East Asia and two extratropical modes of variability: the Atlantic Multidecadal Oscillation (AMO) and the Pacific Decadal Oscillation (PDO). We analyse the spatial, temporal and spectral characteristics of the climate modes in the last millennium, historical and pre-industrial control simulations of seven Coupled Model Intercomparison Project phase 5 (CMIP5)/Paleoclimate Model Intercomparison Project phase 3 (PMIP3) global climate models (GCMs) to assess the relative influences of external forcing and unforced variability. These models produce PDO and AMO variability with realistic spatial patterns but widely varying spectral characteristics. AMO internal variability significantly influences East Asian temperature in five models (MPI, HadCM3, MRI, IPSL and CSIRO) but has a weak influence in the other two (BCC and CCSM4). In most models, external forcing greatly strengthens these statistical associations and hence the apparent teleconnection with the AMO. PDO internal variability strongly influences East Asian temperature in two out of seven models, but external forcing makes this apparent teleconnection much weaker. This indicates that the AMO–East Asian temperature relationship is partly driven by external forcing, whereas the PDO–temperature relationship is largely from internal variability within the climate system. Our findings suggest that external forcing confounds attempts to diagnose the teleconnections of internal multidecadal variability. Using AMO and PDO indices that represent internal variability more closely and minimising the influence of external forcing on East Asian temperature can partly ameliorate this confounding effect. Nevertheless, these approaches still yield differences between the forced and control simulations and they cannot always be applied to paleoclimate reconstructions. Thus, we recommend caution when interpreting teleconnections diagnosed from reconstructions that contain both forced and internal variations.

Dynamics of Upwelling Annual Cycle in the Equatorial Pacific Ocean

A recent work proposed a simple theory based on the framework of Zebiak–Cane (ZC) ocean model, and successfully characterized the equatorial Atlantic upwelling annual cycle as a combination of the local wind-driven Ekman upwelling and nonlocal wind-driven wave upwelling. In the present work, utilizing the same simple framework, we examined the fidelity of the upwelling Pacific annual cycle using observations and simulations from the Coupled Model Intercomparison Project Phase 5 (CMIP5). We demonstrated that the theoretical upwelling annual cycles generally match the original upwelling annual cycles in the equatorial Pacific in both observations and CMIP5 simulations. Therefore, this simple formulation can be used to represent the upwelling annual cycle in the equatorial Pacific. Observationally, the equatorial Pacific upwelling annual cycle is dominated by the local wind-driven Ekman upwelling, while the remote wave upwelling is confined near the eastern boundary with little contribution. In CMIP5 simulations, though the theoretical-reconstructed upwelling well-reproduces the original upwelling, the contribution is totally different compared to the observation. The wave upwelling serves as the main contributor instead of the Ekman upwelling. We further demonstrated that such discrepancy is attributable to the bias of the central to eastern equatorial thermocline depth patterns. This amplified, westward-shift wave upwelling weakened the impacts of the Ekman upwelling, and contributes to the entire Pacific equatorial upwelling annual cycle substantially. This implies that a realistic simulation of the equatorial Pacific upwelling annual cycle in models is very sensitive to the careful simulation of the equatorial thermocline depth annual evolutions.

Diagnosing the representation and causes of the ENSO persistence barrier in CMIP5 simulations

In this study, the persistence barrier (PB) of the El Nino–Southern Oscillation (ENSO) phenomenon is investigated using reanalysis data and historical simulations of the Coupled Model Intercomparison Project Phase 5 (CMIP5) models. Both the timing and intensity of the ENSO PB can be quantified using the maximum gradient of autocorrelation decline of Nino sea surface temperature (SST) anomaly indices. Most of the CMIP5 models were found to reasonably reproduce the observed timing of the ENSO PB that typically occurs during the boreal late spring to early summer, and underestimated the PB intensity compared to observations. Furthermore, the PB properties of the Eastern Pacific (EP) ENSO indices were much better represented by the models than those of the Central Pacific (CP) ENSO indices, probably because CP ENSO events are more challenging to simulate than their counterparts. Approximately half of the models can satisfyingly reflect the intensity and timing of PB for indices of EP ENSO and their distinctions from those of the CP ENSO, with a larger uncertainty for the modeled PB timing than intensity. Further diagnosis has revealed the relationship between the ENSO PB intensity and the factors associated with the tropical Pacific background state. The PB intensity exhibits a stronger relationship with the seasonality of the SST amplitude in CP, compared to the SST amplitude, and the strength of seasonal synchronization of EP SST anomalies is highly correlated with the PB intensity. These results suggest that the seasonality of tropical SST variability may fundamentally contribute to the ENSO PB.

Impact of surface temperature biases on climate change projections of the South Pacific Convergence Zone

The South Pacific Convergence Zone (SPCZ) is poorly represented in global coupled simulations from the Coupled Model Intercomparison Project Phase 5 (CMIP5), with trademark biases such as the tendency to form a “double Intertropical convergence zone” and an equatorial cold tongue that extends too far westward. Such biases limit our confidence in projections of the future climate change for this region. In this study, we use a downscaling strategy based on a regional atmospheric general circulation model that accurately captures the SPCZ present-day climatology and interannual variability. More specifically, we investigate the sensitivity of the projected rainfall response to either just correcting present-day CMIP5 Sea Surface Temperature (SST) biases or correcting projected SST changes using an emergent constraint approach. While the equatorial western Pacific projected rainfall increase is robust in our experiments and CMIP5, correcting the projected CMIP5 SST changes yields a considerably larger reduction (~ 25%) than in CMIP5 simulations (~ + 3%) in the southwestern Pacific. Indeed, correcting the projected CMIP5 warming pattern yields stronger projected SST gradients, and more humidity convergence reduction under the SPCZ. Finally, our bias-corrected set of experiments yields an increase in equatorial rainfall and SPCZ variability in the future, but does not support the future increase in the frequency of zonal SPCZ events simulated by CMIP5 models. This study hence suggests that atmospheric downscaling studies should not only correct CMIP5 present-day SST biases but also projected SST changes to improve the reliability of their projections. Additional simulations with different physical parameterizations yield robust results.

Relation Between Arctic Moisture Flux and Tropical Temperature Biases in CMIP5 Simulations and Its Fingerprint in RCP8.5 Projections

AbstractArctic moisture intrusions have played an important role in warming the Arctic over the past few decades. A prior study found that Coupled Model Intercomparison Project Phase 5 (CMIP5) models exhibit large regional biases in the moisture flux across 70°N. It is shown here that the systematic misrepresentation of the moisture flux is related to the models' overprediction of zonal wavenumber k = 2 contribution and underprediction of k = 1 contribution to the flux. Models with a warmer tropical upper troposphere and El‐Niño‐like tropical surface temperature tend to simulate stronger k = 2 flux, while k = 1 flux is uncorrelated with tropical upper tropospheric temperature and is associated with La‐Niña‐like surface temperature. The models also overpredict the transient eddy moisture flux while underpredicting the stationary eddy flux. Moreover, future projections in Representative Concentration Pathway 8.5 (RCP8.5) simulations show trends in moisture flux that is consistent with biases in historical simulations, suggesting that these CMIP5 projections reflect the same error(s) that cause the model biases.

Do CMIP5 Models Reproduce Observed Low‐Frequency North Atlantic Jet Variability?

AbstractThe magnitude of observed multidecadal variations in the North Atlantic Oscillation (NAO) in winter is at the upper end of the range simulated by climate models and a clear explanation for this remains elusive. Recent research shows that observed multidecadal winter NAO variability is more strongly associated with North Atlantic (NA) jet strength than latitude, thus motivating a comprehensive comparison of NA jet and NAO variability across the Coupled Model Intercomparison Project Phase 5 (CMIP5) models. Our results show that the observed peak in multidecadal jet strength variability is even more unusual than NAO variability when compared to the model‐simulated range across 133 historical CMIP5 simulations. Some CMIP5 models appear capable of reproducing the observed low‐frequency peak in jet strength, but there are too few simulations of each model to clearly identify which. It is also found that an observed strong multidecadal correlation between jet strength and NAO since the mid‐nineteenth century may be specific to this period.

Ensemble-based CMIP5 simulations of West African summer monsoon rainfall: current climate and future changes

The West African summer monsoon (WASM) rainfall is of significant socioeconomic importance. Therefore, its response to climate change is of great concern to climate scientists. Based on observations, reanalysis, and multi-model ensemble mean (EnsMean) simulations of Coupled Model Intercomparison Project phase 5 (CMIP5) models, the responses of WASM rainfall, as well as some relevant atmospheric features, to global warming are investigated. Results from the historical period (1980–2005) indicate that EnsMean reasonably reproduced the characteristics of WASM rainfall, and the strength and position of the upper-level Tropical Easterly Jet (TEJ) and mid-level African Easterly Jet (AEJ). Under global warming, EnsMean exhibits localized future changes in spatial rainfall pattern; specifically, a statistically significant increase (decrease) is evident over the central-eastern (western) Sahel subregion. Similarly, the annual cycle exhibits a decrease (increase) in pre-monsoon (post-monsoon) rainfall over the region, evident over the Sahel subregion. Increased surface evaporation and enhanced atmospheric moisture convergence are notable over the region of increasing WASM rainfall, while a weakened and possible alteration of large-scale atmospheric circulation features is evident over the study area.

Underestimated interannual variability of East Asian summer rainfall under climate change

This study evaluates the performance of climate models in simulating the climatological mean and interannual variability of East Asian summer rainfall (EASR) using Coupled Model Intercomparison Project Phase 5 (CMIP5). Compared to the observation, the interannual variability of EASR during 1979–2005 is underestimated by the CMIP5 with a range of 0.86~16.08%. Based on bias correction of CMIP5 simulations with historical data, the reliability of future projections will be enhanced. The corrected EASR under representative concentration pathways (RCPs) 4.5 and 8.5 increases by 5.6 and 7.5% during 2081–2100 relative to the baseline of 1986–2005, respectively. After correction, the areas with both negative and positive anomalies decrease, which are mainly located in the South China Sea and central China, and southern China and west of the Philippines, separately. In comparison to the baseline, the interannual variability of EASR increases by 20.8% under RCP4.5 but 26.2% under RCP8.5 in 2006–2100, which is underestimated by 10.7 and 11.1% under both RCPs in the original CMIP5 simulation. Compared with the mean precipitation, the interannual variability of EASR is notably larger under global warming. Thus, the probabilities of floods and droughts may increase in the future.

The relation between climate change in the Mediterranean region and global warming

The recent (twentieth century) and future (twenty-first century) climate evolution in the Mediterranean region is analyzed in relation to annual mean global surface temperature change. The CMIP5 (Coupled Model Intercomparison Project, Phase 5) simulations, the CRU (Climate Research Unit) observational gridded dataset, and two twentieth century reanalyzes (ECMWF, European Center for Medium range Weather Forecasts) and NOAA ESRL (National Oceanic and Atmospheric Administration-Earth System Research Laboratory) are used. These datasets to large extent agree that in the twentieth century: (a) Mediterranean regional and global temperatures have warmed at a similar rate until the 1980s and (b) decadal variability determines a large uncertainty that prevents to identify long-term links between precipitation in the Mediterranean region and global temperature. However, in the twenty-first century, as mean global temperature increases, in the Mediterranean region, precipitation will decrease at a rate around − 20 mm/K or − 4%/K and temperature will warm 20% more than the global average. Warming will be particularly large in summer (approximately 50% larger than global warming) and for the land areas located north of the basin (locally up to 100% larger than global warming). Reduction of precipitation will affect all seasons in the central and southern Mediterranean areas, with maximum reduction for winter precipitation (− 7 mm/K or − 7%/K for the southern Mediterranean region). For areas along the northern border of the Mediterranean region, reduction will be largest in summer (− 7 mm/K or − 9%/K for the whole northern Mediterranean region), while they will not experience a significant reduction of precipitation in winter.

Analysis of the variability of the North Atlantic eddy-driven jet stream in CMIP5

The North Atlantic eddy-driven jet is a dominant feature of extratropical climate and its variability is associated with the large-scale changes in the surface climate of midlatitudes. Variability of this jet is analysed in a set of General Circulation Models (GCMs) from the Coupled Model Inter-comparison Project phase-5 (CMIP5) over the North Atlantic region. The CMIP5 simulations for the 20th century climate (Historical) are compared with the ERA40 reanalysis data. The jet latitude index, wind speed and jet persistence are analysed in order to evaluate 11 CMIP5 GCMs and to compare them with those from CMIP3 integrations. The phase of mean seasonal cycle of jet latitude and wind speed from historical runs of CMIP5 GCMs are comparable to ERA40. The wind speed mean seasonal cycle by CMIP5 GCMs is overestimated in winter months. A positive (negative) jet latitude anomaly in historical simulations relative to ERA40 is observed in summer (winter). The ensemble mean of jet latitude biases in historical simulations of CMIP3 and CMIP5 with respect to ERA40 are -2.43^circ and -1.79^circ respectively. Thus indicating improvements in CMIP5 in comparison to the CMIP3 GCMs. The comparison of historical and future simulations of CMIP5 under RCP4.5 and RCP8.5 for the period 2076–2099, shows positive anomalies in the jet latitude implying a poleward shifted jet. The results from the analysed models offer no specific improvements in simulating the trimodality of the eddy-driven jet.

Evaluation of soil moisture in CMIP5 simulations over the contiguous United States using in situ and satellite observations

Abstract. This study provides a comprehensive evaluation of soil moisture simulations in the Coupled Model Intercomparison Project Phase 5 (CMIP5) extended historical experiment (2003 to 2012). Soil moisture from in situ and satellite sources is used to evaluate CMIP5 simulations in the contiguous United States (CONUS). Both near-surface (0–10 cm) and soil column (0–100 cm) simulations from more than 14 CMIP5 models are evaluated during the warm season (April–September). Multimodel ensemble means and the performance of individual models are assessed at a monthly timescale. Our results indicate that CMIP5 models can reproduce the seasonal variability in soil moisture over CONUS. However, the models tend to overestimate the amount of both near-surface and soil column soil moisture in the western US and underestimate it in the eastern US. There are large variations across models, especially for the near-surface soil moisture. There are significant regional variations in performance as well. Results of a regional analysis show that in the deeper soil layers, the CMIP5 soil moisture simulations tend to be most skillful in the southern US. Based on both the satellite-derived and in situ soil moisture, CESM1, CCSM4 and GFDL-ESM2M perform best in the 0–10 cm soil layer and CESM1, CCSM4, GFDL-ESM2M and HadGEM2-ES perform best in the 0–100 cm soil layer.

Assessing the Impacts of Climate Change on Future Precipitation Trends Based on Downscaled CMIP5 Simulations Data

This study investigates future changes in precipitation over the CRB (Columbia River Basin) in both wet (DJF) and dry (JJA) seasons under RCP85 GHG emission scenario. The simulations from four climate models which participated in CMIP5 (Coupled Model Intercomparison Project Phase-5) were downscaled using the BCSD (Bias Correction and Spatial Disaggregation) method. After downscaling, extreme value analysis and MME (Multi Model Ensemble) averaging is performed. This study focuses on computing 2, 5, 10 and 25 years return levels for both winter (DJF) and summer (JJA) seasons. The maximum winter precipitation values for 2, 5, 10 and 25 years return periods have been estimated to be about 112, 127, 148 and 171 mm/day respectively whereas the maximum summer precipitation values for 2, 5, 10 and 25 years return periods are observed to be about 56, 81, 96 and 126 mm/day respectively. The MME average outperformed the individual models in simulating the historical precipitation in both seasons. The MME results showed a consistent and significant increase in the extreme precipitation and decrease in mean precipitation in both future wet and dry seasons. Largest increase in precipitation occurs over the higher elevations of the Cascades Range, Coast Range and the Mountainous Range.

Aerosol forcing of extreme summer drought over North China

The frequency of extreme summer drought has been increasing in North China during the past sixty years, which has caused serious water shortages. It remains unclear whether anthropogenic forcing has contributed to the increasing extreme droughts. Using the National Centers for Environmental Prediction and the National Center for Atmospheric Research (NCEP/NCAR) re-analysis data and Coupled Model Intercomparison Project Phase 5 (CMIP5) model simulations with various combinations of historical forcings, the authors investigated the driving mechanism behind the observed changes. Metrological drought is usually measured by precipitation anomalies, which show lower fidelity in current climate models compared to large-scale circulation patterns. Based on NCEP/NCAR re-analysis, a linear relationship is firstly established between the weakest regional average 850 hPa southerly winds and extreme summer drought. This meridional winds index (MWI) is then used as a proxy for attribution of extreme North China drought using CMIP5 outputs. Examination of the CMIP5 simulations reveals that the probability of the extreme summer droughts with the first percentile of MWI for 1850–2004 under anthropogenic forcing has increased by 100%, on average, relative to a pre-industrial control run. The more frequent occurrence of extremely weak MWIs or drought over North China is ascribed from weakened climate and East Asian summer monsoon (EASM) circulation due to the direct cooling effect from increased aerosol.

Trends of surface solar radiation in unforced CMIP5 simulations

AbstractWe consider decadal scale trends of annual mean all‐sky surface solar radiation (SSR) that occur solely because of internal variability of the climate system. We give statistical estimates of their magnitude and probability of occurrence. The estimates are based on 43 preindustrial control (piControl) experiments of the Coupled Model Intercomparison Project phase 5 (CMIP5). Trends are found to depend strongly on geographical region and on whether they are quantified in absolute units or relative to the long‐term mean SSR. We find it to be sufficient to provide one map for absolute and one for relative trends, as approximate analytical relations are shown to hold between trends of different length and likelihood and the standard deviation of the underlying SSR time series. We estimate that a positive trend over 30 years and with 25% chance of occurrence (75th percentile of all possible trends) has a magnitude between 0.15 and 1.7 W/m2/decade or 0.11 and 1.4% of long‐term mean SSR per decade, depending on geographical location. Comparison with present‐day observations and intermodel spread suggests an average uncertainty of these estimates of about 30%. Intermodel spread suggests that regional uncertainties can be up to about 3 times larger or smaller. We give examples of how these results may be used to obtain statistical estimates of how (un)likely it is that observed SSR trends or part thereof are due to internal variability alone.