We analyze data of 27 global climate models from the sixth phase of the Coupled Model Intercomparison Project (CMIP6), and examine projected changes in temperature and precipitation over the African continent during the twenty-first century. The temperature and precipitation changes are computed for two future time slices, 2030–2059 (near term) and 2070–2099 (long term), relative to the present climate (1981–2010), for the entire African continent and its eight subregions. The CMIP6 multi-model ensemble projected a continuous and significant increase in the mean annual temperature over all of Africa and its eight subregions during the twenty-first century. The mean annual temperature over Africa for the near (long)-term period is projected to increase by 1.2 °C (1.4 °C), 1.5 °C (2.3 °C), and 1.8 °C (4.4 °C) under the Shared Socioeconomic Pathways (SSPs) for weak, moderate, and strong forcing, referenced as SSP1-2.6, SSP2-4.5, and SSP5-8.5, respectively. The future warming is not uniform over Africa and varies regionally. By the end of the twenty-first century, the largest rise in mean annual temperature (5.6 °C) is projected over the Sahara, while the smallest rise (3.5 °C) is over Central East Africa, under the strong forcing SSP5-8.5 scenario. The projected boreal winter and summer temperature patterns for the twenty-first century show spatial distributions similar to the annual patterns. Uncertainty associated with projected temperature over Africa and its eight subregions increases with time and reaches a maximum by the end of the twenty-first century. On the other hand, the precipitation projections over Africa during the twenty-first century show large spatial variability and seasonal dependency. The northern and southern parts of Africa show a reduction in precipitation, while the central parts of Africa show an increase, in future climates under the three reference scenarios. For the near (long)-term periods, the area-averaged precipitation over Africa is projected to increase by 6.2 (4.8)%, 6.8 (8.5)%, and 9.5 (15.2)% under SSP1-2.6, SSP2-4.5, and SSP5-8.5, respectively. The median warming simulated by the CMIP6 model ensemble remains higher than the CMIP5 ensemble over most of Africa, reaching as high as 2.5 °C over some regions, while precipitation shows a mixed spatial pattern.

The latest Coupled Model Intercomparison Project phase 6 (CMIP6) dataset was analyzed to examine the projected changes in temperature and precipitation over six South Asian countries during the twenty-first century. The CMIP6 model simulations reveal biases in annual mean temperature and precipitation over South Asia in the present climate. In the historical period, the median of the CMIP6 model ensemble systematically underestimates the annual mean temperature for all the South Asian countries, while a mixed behavior is shown in the case of precipitation. In the future climate, the CMIP6 models display higher sensitivity to greenhouse gas emissions over South Asia compared with the CMIP5 models. The multimodel ensemble from 27 CMIP6 models projects a continuous increase in the annual mean temperature over South Asia during the twenty-first century under three future scenarios. The projected temperature shows a large increase (over 6 °C under SSP5-8.5 scenario) over the northwestern parts of South Asia, comprising the complex Karakorum and Himalayan mountain ranges. Any large increase in the mean temperature over this region will most likely result in a faster rate of glacier melting. By the end of the twenty-first century, the annual mean temperature (uncertainty range) over South Asia is projected to increase by 1.2 (0.7–2.1) °C, 2.1 (1.5–3.3) °C, and 4.3 (3.2–6.6) °C under the SSP1-2.6, SSP2-4.5, and SSP5-8.5 scenarios, respectively, relative to the present (1995–2014) climate. The warming over South Asia is also continuous on the seasonal time scale. The CMIP6 models projected higher warming in the winter season than in the summer over South Asia, which if verified will have repercussions for snow/ice accumulations as well as winter cropping patterns. The annual mean precipitation is also projected to increase over South Asia during the twenty-first century under all scenarios. The rate of change in the projected annual mean precipitation varies considerably between the South Asian countries. By the end of the twenty-first century, the country-averaged annual mean precipitation (uncertainty range) is projected to increase by 17.1 (2.2–49.1)% in Bangladesh, 18.9 (−4.9 to 72)% in Bhutan, 27.3 (5.3–160.5)% in India, 19.5 (−5.9 to 95.6)% in Nepal, 26.4 (6.4–159.7)% in Pakistan, and 25.1 (−8.5 to 61.0)% in Sri Lanka under the SSP5-8.5 scenario. The seasonal precipitation projections also shows large variability. The projected winter precipitation reveals a robust increase over the western Himalayas, with a corresponding decrease over the eastern Himalayas. On the other hand, the summer precipitation shows a robust increase over most of the South Asia region, with the largest increase over the arid region of southern Pakistan and adjacent areas of India, under the high-emission scenario. The results presented in this study give detailed insights into CMIP6 model performance over the South Asia region, which could be extended further to develop adaptation strategies, and may act as a guideline document for climate change related policymaking in the region.

[1] The Indian subcontinent is one of the most intensely irrigated regions of the world and state of the art climate models do not account for the representation of irrigation. Sensitivity studies with the regional climate model REMO show distinct feedbacks between the simulation of the monsoon circulation with and without irrigation processes. We find that the temperature and mean sea level pressure, where the standard REMO version without irrigation shows a significant bias over the areas of Indus basin, is highly sensitive to the water used for irrigation. In our sensitivity test we find that removal of this bias has caused less differential heating between land and sea masses. This in turns reduces the westerlies entering into land from Arabian Sea, hence creating conditions favorable for currents from Bay of Bengal to intrude deep into western India and Pakistan that have been unrealistically suppressed before. We conclude that the representation of irrigated water is unavoidable for realistic simulation of south Asian summer monsoon and its response under global warming.

The transferability of the regional climate model REMO with a standard setup over different regions of the world has been evaluated. The study is based on the idea that the modeling parameters and parameterizations in a regional climate model should be robust to adequately simulate the major climatic characteristic of different regions around the globe. If a model is not able to do that, there might be a chance of an “overtuning” to the “home-region”, which means that the model physics are tuned in a way that it might cover some more fundamental errors, e.g., in the dynamics. All simulations carried out in this study contribute to the joint effort by the international regional downscaling community called COordinated Regional climate Downscaling EXperiment (CORDEX). REMO has been integrated over six CORDEX domains forced with the so-called perfect boundary conditions obtained from the global reanalysis dataset ERA-Interim for the period 1989 to 2008. These six domains include Africa, Europe, North America, South America, West Asia and the Mediterranean region. Each of the six simulations was conducted with the identical model setup which allows investigating the transferability of a single model to regions with substantially different climate characteristics. For the consistent evaluation over the different domains, a new evaluation framework is presented by combining the Köppen-Trewartha climate classification with temperature-precipitation relationship plots and a probability density function (PDF) skill score method. The evaluation of the spatial and temporal characteristics of simulated precipitation and temperature, in comparison to observational datasets, shows that REMO is able to simulate the mean annual climatic features over all the domains quite reasonably, but still some biases remain. The regions over the Amazon and near the coast of major upwelling regions have a significant warm bias. Wet and dry biases appear over the mountainous regions and East Africa, respectively. The temperature over South America and precipitation over the tundra and highland climate of West Asia are misrepresented. The probable causes leading to these biases are discussed and ideas for improvements are suggested. The annual cycle of precipitation and temperature of major catchments in each domain are also well represented by REMO. The model has performed well in simulating the inter- and intra-seasonal characteristics of different climate types in different regions. Moreover, the model has a high ability in representing the general characteristics of different climate types as measured by the probability density function (PDF) skill score method. Although REMO seems to perform best over its home domain in Europe (domain of development and testing), the model has simulated quite well the climate characteristics of other regions with the same set of parameterization options. Therefore, these results lead us to the conclusion that REMO is well suited for long-term climate change simulations to examine projected future changes ...

The Coupled Model Intercomparison Project Phase 6 (CMIP6) dataset is used to examine projected changes in temperature and precipitation over the United States (U.S.), Central America and the Caribbean. The changes are computed using an ensemble of 31 models for three future time slices (2021–2040, 2041–2060, and 2080–2099) relative to the reference period (1995–2014) under three Shared Socioeconomic Pathways (SSPs; SSP1-2.6, SSP2-4.5, and SSP5-8.5). The CMIP6 ensemble reproduces the observed annual cycle and distribution of mean annual temperature and precipitation with biases between − 0.93 and 1.27 °C and − 37.90 to 58.45%, respectively, for most of the region. However, modeled precipitation is too large over the western and Midwestern U.S. during winter and spring and over the North American monsoon region in summer, while too small over southern Central America. Temperature is projected to increase over the entire domain under all three SSPs, by as much as 6 °C under SSP5-8.5, and with more pronounced increases in the northern latitudes over the regions that receive snow in the present climate. Annual precipitation projections for the end of the twenty-first century have more uncertainty, as expected, and exhibit a meridional dipole-like pattern, with precipitation increasing by 10–30% over much of the U.S. and decreasing by 10–40% over Central America and the Caribbean, especially over the monsoon region. Seasonally, precipitation over the eastern and central subregions is projected to increase during winter and spring and decrease during summer and autumn. Over the monsoon region and Central America, precipitation is projected to decrease in all seasons except autumn. The analysis was repeated on a subset of 9 models with the best performance in the reference period; however, no significant difference was found, suggesting that model bias is not strongly influencing the projections.

The ability of four regional climate models (RCMs) to represent the Indian monsoon was verified in a consistent framework for the period 1981-2000 using the 45-yr European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA-40) as lateral boundary forcing data. During the monsoon period, the RCMs are able to capture the spatial distribution of precipitation with a maximum over the central and west coast of India, but with important biases at the regional scale on the east coast of India in Bangladesh and Myanmar. Most models are too warm in the north of India compared to the observations. This has an impact on the simulated mean sea level pressure from the RCMs, being in general too low compared to ERA-40. Those biases perturb the land-sea temperature and pressure contrasts that drive the monsoon dynamics and, as a consequence, lead to an overestimation of wind speed, especially over the sea. The timing of the monsoon onset of the RCMs is in good agreement with the one obtained from observationally based gridded datasets, while the monsoon withdrawal is less well simulated. A Hovmö ller diagram representation of the mean annual cycle of precipitation reveals that the meridional motion of the precipitation simulated by the RCMs is comparable to the one observed, but the precipitation amounts and the regional distribution differ substantially between the four RCMs. In summary, the spread at the regional scale between the RCMs indicates that important feedbacks and processes are poorly, or not, taken into account in the state-of-the-art regional climate models.

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We evaluate the performance of a large ensemble of Global Climate Models (GCMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6) over South America for a recent past reference period and examine their projections of twenty-first century precipitation and temperature changes. The future changes are computed for two time slices (2040–2059 and 2080–2099) relative to the reference period (1995–2014) under four Shared Socioeconomic Pathways (SSPs, SSP1–2.6, SSP2–4.5, SSP3–7.0 and SSP5–8.5). The CMIP6 GCMs successfully capture the main climate characteristics across South America. However, they exhibit varying skill in the spatiotemporal distribution of precipitation and temperature at the sub-regional scale, particularly over high latitudes and altitudes. Future precipitation exhibits a decrease over the east of the northern Andes in tropical South America and the southern Andes in Chile and Amazonia, and an increase over southeastern South America and the northern Andes—a result generally consistent with earlier CMIP (3 and 5) projections. However, most of these changes remain within the range of variability of the reference period. In contrast, temperature increases are robust in terms of magnitude even under the SSP1–2.6. Future changes mostly progress monotonically from the weakest to the strongest forcing scenario, and from the mid-century to late-century projection period. There is an increase in the seasonality of the intra-annual precipitation distribution, as the wetter part of the year contributes relatively more to the annual total. Furthermore, an increasingly heavy-tailed precipitation distribution and a rightward shifted temperature distribution provide strong indications of a more intense hydrological cycle as greenhouse gas emissions increase. The relative distance of an individual GCM from the ensemble mean does not substantially vary across different scenarios. We found no clear systematic linkage between model spread about the mean in the reference period and the magnitude of simulated sub-regional climate change in the future period. Overall, these results could be useful for regional climate change impact assessments across South America.