An attempt to deconstruct recent climate change in the Baltic Sea basin

Satellite-derived products and reanalyses show consistent increases in downward surface solar radiation (SSR) and decreases in cloud cover over North America and Europe from the 1980s to 2010s. These trends show a strong seasonality, with the largest changes in boreal summer. A set of timeslice experiments with an atmospheric general circulation model (AGCM) forced with prescribed changes in sea surface temperature/sea ice extent (SST/SIE), greenhouse gas (GHG) concentrations, and anthropogenic aerosol (AA) emissions, together and separately, is performed to assess the relative roles of different forcings in these observed trends. The model reproduces the main observed features over Europe and North America, including the seasonality of trends, suggesting a dominant role of forced changes in the recent trends in SSR and cloud cover. Responses to individual forcings indicate that recent decadal trends in SSR over Europe are predominantly driven by AA emission reductions, with an additional influence from SST/SIE and GHG changes. In contrast, changes in AA, SST/SIE, and GHG contribute more equally to simulated decadal trends in SSR and cloud cover over North America, although SST/SIE play the most important role. In our simulations, responses of SSR to AA emission reductions are primarily governed by aerosol-radiation interactions. Responses to SST/SIE and GHG changes are predominantly due to cloud cover changes, which are driven by atmospheric circulation and humidity changes. This process level understanding of how different forcing factors influence decadal trends in SSR and cloud cover is valuable for understanding past changes and future projections in global and regional surface energy budgets, surface warming, and global and regional hydrological cycles.

Observations show that the tropical belt has widened over the past few decades, a phenomenon associated with poleward migration of subtropical dry zones and large‐scale atmospheric circulation. Although part of this signal is related to natural climate variability, studies have identified an externally forced contribution primarily associated with greenhouse gases (GHGs) and stratospheric ozone loss. Here we show that the increase in aerosols over the twentieth century has led to contraction of the northern tropical belt, thereby offsetting part of the widening associated with the increase in GHGs. Over the 21st century, however, when aerosol emissions are projected to decrease, the effects of aerosols and GHGs reinforce one another, both contributing to widening of the northern tropical belt. Models that have larger aerosol forcing, by including aerosol indirect effects on cloud albedo and lifetime, yield significantly larger Northern Hemisphere (NH) tropical widening than models with direct aerosol effects only. More targeted simulations show that future reductions in aerosols can drive NH tropical widening as large as greenhouse gases, and idealized simulations show the importance of NH midlatitude aerosol forcing. Mechanistically, the 21st century reduction in aerosols peaks near 40°N, which results in a corresponding maximum increase in surface solar radiation, NH midlatitude tropospheric warming amplification, and a poleward shift in the latitude of maximum baroclinicity, implying a corresponding shift in atmospheric circulation. If models with aerosol indirect effects better represent the real world, then future aerosol changes are likely to be an important—if not dominant—driver of NH tropical belt widening.

Based on the solar radiation information and climatic observation data from 1961 to 2011 in both East and West China, the interannual trends of surface solar radiation are investigated. By combining with cloud cover, sunshine percentage, sunshine duration, wind speed, atmospheric turbidity, and relative humidity, the causes affecting the variations of the total surface solar radiation in East China and West China are analyzed. The results show that the surface solar radiation decreased from 1961 to 2010 in both East and West China, but there was an abrupt change, which occurred in the early 1990s, followed by sustained increase. The surface solar radiation decreased from 1961 to 2010 in East China, and the decrease of surface solar radiation in the eastern region was greater than in the western region. The surface solar radiation is significantly correlated with sunshine duration in both East and West China. In East China, the surface solar radiation is significantly positively correlated with the percentage of sunshine. It indicates that the percentage of sunshine duration is the main factor affecting the total surface solar radiation in East China. The decrease of the total surface solar radiation is influenced by many factors. In East China, the percentage of sunshine and the atmospheric turbidity factor are the main factors affecting the surface solar radiation reduction. There is no correlation between cloud and ground solar total radiation. However, the percentage of sunshine is affected mainly by cloud cover and air pollution. In West China, no significant correlation is found between surface solar radiation and cloud cover, but significant correlation is detected between surface solar radiation and sunshine percentage. These indicate that the sunshine percentage could be a main factor affecting surface solar radiation. Wind becomes an important factor affecting the total surface solar radiation, since wind is a main factor expelling troposphere air pollution such as smog. A comparison of the variation in ground solar radiation between the East and West China shows that the aerosol particles of air pollution are the main factor affecting the reduction of total surface solar radiation in East China. Many scholars have found that the significant reduction of the surface solar radiation is mainly due to the absorption and scattering atmospheric aerosols. All these findings suggest that the air pollution has become an important factor affecting the surface solar total radiation, especially in East China.

Evaluation of surface solar radiation trends over China since the 1960s in the CMIP6 models and potential impact of aerosol emissions

Global average trends in solar radiation reaching the Earth's surface show a transition from dimming to brightening that occurred in about 1990. We show that the inter‐annual trend in solar radiation between 1980 and 2000 mirrors the trend in primary emissions of SO2 and black carbon, which together contribute about one‐third of global average aerosol optical depth. Combined global emissions of these two species peaked in 1988–1989. The two‐decadal rate of decline in aerosol loading resulting from these emission changes, 0.13% yr−1, can be compared with the reported increase in solar radiation of 0.10% yr−1 in 1983–2001. Regional patterns of aerosol and radiation changes are also qualitatively consistent. We conclude that changes in the aerosol burden due to changing patterns of anthropogenic emissions are likely contributing to the trends in surface solar radiation.

Assessing the contribution of different factors in regional climate model projections using the factor separation method

Quantile-quantile bias-correction has been used in several northern hemisphere studies to improve the utility of regional climate model (RCM) outputs, however the technique is rarely used in Australia. The technique has the advantage of preserving complex changes in the RCM projections - e.g. to weather systems, dry spells, rainfall intensities, mean rainfalls, rainfall extremes - in hydrological modelling. The technique also has the advantage of retaining the physical correlation between rainfall and evapotranspiration. We apply a quantile-quantile bias-correction to an ensemble of six fine-scale (10 km) regional climate simulations for 1961-2100 over Tasmania generated by the Climate Futures for Tasmania project (http://www.acecrc.org.au/Research/Climate%20Futures). The regional climate simulations show a high degree of skill in replicating spatial patterns of mean annual rainfall (spatial correlation R 2 =0.75) and require relatively modest bias-corrections. Multiplicative bias-corrections are calculated for daily values of rainfall and evapotranspiration for the calibration period 1961-2007. Bias-corrections are calculated independently for each grid cell, for each season and for each percentile. The bias-correction substantially improves spatial correlation between modelled and observed seasonal and annual rainfall (spatial correlation R 2 >0.99). We use split sample cross-validation to find that the projected changes to rainfall are insensitive to the period chosen to train the bias-correction. Spatial relationships of daily rainfalls are not explicitly accounted for by the bias-correction. To test the simulation of spatial relationships of rainfall we aggregate rainfalls to the seven Tasmanian Bureau of Meteorology forecast zones. The behaviour of biases of aggregated rainfall for each zone is compared to the behaviour of biases in individual grid cells within that zone. These comparisons indicate that the bias- corrected RCM outputs tend to overestimate large regional rainfall events and underestimate small regional rainfall events. We test the performance of the bias-correction by using bias-corrected rainfall and evapotranspiration as inputs to five hydrological models (AWBM, IHACRES, Sacramento, SIMHYD, SMAR-G). Performance of the hydrological models is assessed at 86 flow gauges across Tasmania. Performance of hydrological models with bias-corrected RCM inputs varies between models. AWBM, Sacramento, SIMHYD and SMAR-G simulate runoff realistically with bias-corrected RCM inputs, while IHACRES does not. The SIMHYD model gives the most realistic results (median bias -3%) while the IHACRES model gives the poorest results (median bias -21%). Our study supports the findings of northern-hemisphere studies that quantile-quantile bias-correction can effectively couple RCM outputs to hydrological models. Historical Tasmanian stream flows are realistically simulated with bias-corrected RCM outputs, while the climate change signal is successfully retained.

Variations in the intensity of the global hydrological cycle can have far-reaching effects on living conditions on our planet. While climate change discussions often revolve around possible consequences of future temperature changes, the adaptation to changes in the hydrological cycle may pose a bigger challenge to societies and ecosystems. Floods and droughts are already today amongst the most damaging natural hazards, with floods being globally the most significant disaster type in terms of loss of human life (Jonkman 2005). From an economic perspective, changes in the hydrological cycle can impose great pressures and damages on a variety of industrial sectors, such as water management, urban planning, agricultural production and tourism. Despite their obvious environmental and societal importance, our understanding of the causes and magnitude of the variations of the hydrological cycle is still unsatisfactory (e.g., Ramanathan et al 2001, Ohmura and Wild 2002, Allen and Ingram 2002, Allan 2007, Wild et al 2008, Liepert and Previdi 2009).

The characteristics of the mesoscale Mistral and Tramontane winds under changing climate conditions are of great interest for risk assessments. In this study, a classification algorithm is applied to identify Mistral and Tramontane-permitting sea-level pressure patterns, thus allowing for estimates of their future characteristics. Five simulations with three regional climate models on a 0.44^circ grid and five global circulation models are assessed for the representative concentration pathways (RCPs) 4.5 and 8.5. Regional climate simulations driven by ERA-Interim are used to test the classification algorithm and to estimate its accuracy. The derived Mistral and Tramontane time series are discussed. The results for the ERA-Interim period show that the classification algorithm and the regional climate models work well in terms of the number of Mistral and Tramontane days per year, but the results overestimate the average length of such events. For both the RCPs, only small changes in Mistral frequency were found in both regional and global climate simulations. Most simulations show a decrease in Tramontane frequencies and average period lengths during the 21st century. Regional climate simulations using RCP8.5 show fewer Tramontane events than those using RCP4.5.

In the second part of this study, possible impacts of climate change on Surface Solar Radiation (SSR) in Southern Africa (SA) are evaluated. We use outputs from 20 regional climate simulations from five Regional Climate Models (RCM) that participate in the Coordinated Regional Downscaling Experiment program over the African domain (CORDEX-Africa) along with their 10 driving Global Climate Models (GCM) from the Coupled Model Intercomparison Project Phase 5 (CMIP5). Multi-model mean projections of SSR trends are consistent between the GCMs and their nested RCMs. However, this consistency is not found for each GCM/RCM setup. Over the centre of SA, GCMs and RCMs project a statistically significant increase in SSR by 2099 of about + 1 W/m2 per decade in RCP4.5 (+ 1.5 W/m2 per decade in RCP8.5) during the DJF season in their multi-model means. Over Eastern Equatorial Africa (EA-E) a statistically significant decrease in SSR of about − 1.5 W/m2 per decade in RCP4.5 (− 2 W/m2 per decade in RCP8.5) is found in the ensemble means in DJF, whereas in JJA SSR is predicted to increase by about + 0.5 W/m2 per decade under RCP4.5 (+ 1 W/m2 per decade in RCP8.5). SSR projections are fairly similar between RCP8.5 and RCP4.5 before 2050 and then the differences between those two scenarios increase up to about 1 W/m2 per decade with larger changes in RCP8.5 than in RCP4.5 scenario. These SSR evolutions are generally consistent with projected changes in Cloud Cover Fraction over SA and may also related to the changes in atmosphere water vapor content. SSR change signals emerge earlier out of internal variability estimated from reanalyses (European Centre for Medium-Range Weather Forecasts Reanalysis ERA-Interim, ERAIN) in DJF in RCMs than in GCMs, which suggests a higher sensitivity of RCMs to the forcing RCP scenarios than their driving GCMs in simulating SSR changes. Uncertainty in SSR change projections over SA is dominated by the internal climate variability before 2050, and after that model and scenario uncertainties become as important as internal variability until the end of the 21st century.

The long-term trends of total surface solar radiation (SSR), surface diffuse radiation, and surface air temperature were analyzed in this study based on updated 48-yr data from 55 observational stations in China, and then the correlation between SSR and the diurnal temperature range (DTR) was studied. The effect of total solar radiation on surface air temperature in China was investigated on the basis of the above analyses. A strong correlation between SSR and DTR was found for the period 1961–2008 in China. The highest correlation and steepest regression line slope occurred in winter, indicating that the solar radiation effect on DTR was the largest in this season. Clouds and water vapor have strong influences on both SSR and DTR, and hence on their relationship. The largest correlations between SSR and DTR occurred in wintertime in northern China, regardless of all-day (including clear days and cloudy days) or clear-day cases. Our results also showed that radiation arriving at the surface in China decreased significantly during 1961–1989 (dimming period), but began to increase during 1990–2008 (brightening period), in agreement with previous global studies. The reduction of total SSR offset partially the greenhouse warming during 1961–1989. However, with the increase of SSR after 1990, this offsetting effect vanished; on the contrary, it even made a contribution to the accelerated warming. Nonetheless, the greenhouse warming still played a controlling role because of the increasing of minimum and mean surface temperatures in the whole study period of 1961–2008. We estimated that the greenhouse gases alone may have caused surface temperatures to rise by 0.31–0.46°C (10 yr)−1 during 1961–2008, which is higher than previously estimated. Analysis of the corresponding changes in total solar radiation, diffuse radiation, and total cloud cover indicated that the dimming and brightening phenomena in China were likely attributable to increases in absorptive and scattering aerosols in the atmosphere, respectively.

China has experienced warming and a pattern of southern flood and northern drought in precipitation in recent decades. Attributable contributions of greenhouse gas emissions and natural climate variability to these phenomena are discussed for China and the main hydrological basins, based on a comparison of historical and attribution simulation tests using a regional climate model (RegCM4.0). Two tests are performed at a resolution of 50 km, driven by the results of BCC_CSM1.1 historical and attribution simulation tests of CMIP5 in 1961-2005, respectively. The forcing of greenhouse gas emissions and natural climate variability are included in the historical test, and greenhouse gas emission is excluded in the attribution test. Results show that the simulated trends of temperature and precipitation from RegCM4.0 are more reasonable than from BCC_CSM1.1 for 1961-2005, and the warming during this period was mainly caused by the emission of greenhouse gases, although natural climate variability also led to regional warming in most areas except the Tibetan Plateau. The warming magnitude from greenhouse gas emissions was much larger than from natural climate variability over most basins and China as a whole, with 80% of the warming attributable to forcing by greenhouse gases. The southern flood and northern drought pattern of precipitation in Eastern China may be largely due to natural climate variability, and greenhouse gas emission to some extent weakens the strength of this change; increased precipitation in Northwest China is mainly induced by increased greenhouse gas emission, while natural climate variability, in contrast, leads to reduced precipitation. The assessments of temperature are more reliable than those of precipitation, because model limitations and the complex relationship between precipitation and external factors result in large remaining uncertainties in precipitation assessments. It should be pointed out that attribution studies of climate change on the regional scale are very complex, and only preliminary modeling results of aerosol and land use forcing in the absence are shown in this study. An ensemble of multiple models and samples with statistical significance and confidence is needed for comprehensive detection and attribution studies, and the limitations associated with all these factors lead to large uncertainties in the conclusions. The aim of this study is to provide a detection and attribution method for studying regional climate change. A more comprehensive and accurate understanding of the causes of climate change in China would require further regional climate simulations and analyses.

Radley Horton,1,a Daniel Bader,1,a Yochanan Kushnir,2 Christopher Little,3 Reginald Blake,4 and Cynthia Rosenzweig5 1Columbia University Center for Climate Systems Research, New York, NY. 2Ocean and Climate Physics Department, Lamont-Doherty Earth Observatory, Columbia University, Palisades, NY. 3Atmospheric and Environmental Research, Lexington, MA. 4Physics Department, New York City College of Technology, CUNY, Brooklyn, NY. 5Climate Impacts Group, NASA Goddard Institute for Space Studies; Center for Climate Systems Research, Columbia University Earth Institute, New York, NY

近50年来中国地面太阳辐射变化及其空间分布研究

[1] Observational evidence indicates significant regional trends in solar radiation at the surface in both all-sky and cloud-free conditions. Negative trends in the downwelling solar surface irradiance (SSI) have become known as ‘dimming’ while positive trends have become known as ‘brightening’. We use the Met Office Hadley Centre HadGEM2 climate model to model trends in cloud-free and total SSI from the pre-industrial to the present-day and compare these against observations. Simulations driven by CMIP5 emissions are used to model the future trends in dimming/brightening up to the year 2100. The modeled trends are reasonably consistent with observed regional trends in dimming and brightening which are due to changes in concentrations in anthropogenic aerosols and, potentially, changes in cloud cover owing to the aerosol indirect effects and/or cloud feedback mechanisms. The future dimming/brightening in cloud-free SSI is not only caused by changes in anthropogenic aerosols: aerosol impacts are overwhelmed by a large dimming caused by increases in water vapor. There is little trend in the total SSI as cloud cover decreases in the climate model used here, and compensates the effect of the change in water vapor. In terms of the surface energy balance, these trends in SSI are obviously more than compensated by the increase in the downwelling terrestrial irradiance from increased water vapor concentrations. However, the study shows that while water vapor is widely appreciated as a greenhouse gas, water vapor impacts on the atmospheric transmission of solar radiation and the future of global dimming/brightening should not be overlooked.