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The Baltic Sea is a shallow, semi-enclosed brackish sea suffering like many other coastal seas from eutrophication caused by human impact. Hence, nutrient load abatement strategies are intensively discussed. With the help of a high-resolution, coupled physical-biogeochemical circulation model we investigate the combined impact of changing nutrient loads from land and changing climate during the 21st century as projected from a global climate model regionalized to the Baltic Sea region. Novel compared to previous studies are an extraordinary spin-up based upon historical reconstructions of atmospheric, nutrient load and runoff forcing, revised nutrient load scenarios and a comparison of nutrient load scenario simulations with and without changing climate. We found in almost all scenario simulations, with differing nutrient inputs, reduced eutrophication and improved ecological state compared to the reference period 1976–2005. This result is a long-lasting consequence of ongoing nutrient load reductions since the 1980s. Only in case of combined high-end nutrient load and climate scenarios, eutrophication is reinforced. Differences compared to earlier studies are explained by the experimental setup including nutrient loads during the historical period and by the projected nutrient loads. We found that the impact of warming climate may amplify the effects of eutrophication and primary production. However, effects of changing climate, within the range of considered greenhouse gas emission scenarios, are smaller than effects of considered nutrient load changes, in particular under low nutrient conditions. Hence, nutrient load reductions following the Baltic Sea Action Plan will lead to improved environmental conditions independently of future climate change.

The three leading modes of the North Atlantic atmospheric circulation explain about 70% of the winter climate variability. Although climate models generally can capture these modes, biases may induce large uncertainties in regional climate predictions. Here, we evaluate the leading winter modes simulated by CMIP5‐PMIP3 and CMIP6‐PMIP4 models from the last millennium to future scenarios in comparison with historical reanalysis and paleo‐reconstructions. The models generally have a good representation of the average spatial pattern of the North Atlantic Oscillation (NAO) while showing a larger spread in performance for the East Atlantic and Scandinavian patterns. In contrast to historical reanalysis, the simulated NAO pattern tends to be rather stationary under various climate states over the years 861–2100. Such underestimated spatial variability in the simulated NAO is directly related to the biased spatial shifts in NAO‐related regional temperature and precipitation changes, inducing uncertainties in climate projections over the North Atlantic sector. Plain Language Summary The North Atlantic Oscillation (NAO) is the most dominant weather pattern over the North Atlantic‐European sector with profound influence on regional climate. The NAO pattern describes the changes in a low‐pressure system over Iceland and a high‐pressure system over the Azores, which are commonly known as the NAO centers of action. However, the NAO centers of action are not always fixed in these two locations, but show spatial movement over time. In this study, we compare the winter weather patterns over the North Atlantic region from the last millennium to future scenarios in climate models with reanalysis products and paleoclimate reconstructions. We find that models generally can capture the spatial structure of the NAO very well but with little changes in its location and shape over time in contrast to historical reanalysis. These biased NAO patterns in climate models can shift the modeled regional temperature and precipitation patterns associated with the NAO. This remains a challenge for the reliability of future climate projections over the North Atlantic region. Key Points We compare the spatial variability of modeled North Atlantic climate modes over the years 861–2100 with reanalysis and reconstructed data The North Atlantic Oscillation (NAO) in 13 Coupled Model Intercomparison Project‐Paleoclimate Modelling Intercomparison Project models shows underestimated spatial variability compared to historical reanalysis Projections of regional temperature and precipitation may show biased patterns due to the underestimated spatial shifts in simulated NAO

Understanding present and future impacts of drought on the terrestrial carbon budget is of great significance to the evaluation of terrestrial ecosystem disturbance and terrestrial carbon sink. Here, we evaluate the effect of vegetation net primary productivity (NPP) associated with drought through the difference between the mean NPP in the drought and normal years during a specific time period (30 years). Then, the NPP effects in different vegetation types and climatic zones under baseline stage (1981–2010) and future climate scenarios (RCP2.6, RCP4.5, and RCP8.5) is assessed. The results indicate that the negative NPP extremes are captured in most regions, except for the high‐latitude in the Northern Hemisphere. The NPP loss caused by extreme droughts in 2071–2100 is largest under RCPs, followed by the effects of severe and moderate droughts. Regionally, central United States, southern Africa, central Asia, India, Amazon tropical rainforest, and Australia are projected to experience a significant increase in negative NPP extremes and most of these regions are in arid and semi‐arid and tropical rain forest areas. In contrast, tropical Asia suffers little drought effects. For different vegetation, Evergreen Broadleaf Forest, Closed Shrubland, Open Shrubland, Croplands, and Grassland are the most affected by drought. The largest NPP loss occurs in most part of regions under RCP4.5 scenario, not RCP8.5. Climate change is projected to play the largest role in aggravating the risk of drought‐induced NPP reduction. And meanwhile, the adverse effects of drought on vegetation may be resisted through rational fertilizer utilization and land management in future. Plain Language Summary Drought is already the most widespread factor affecting terrestrial net primary productivity (NPP) via direct physiological effects, such as water limitation and heat stress. Nevertheless, the effects of drought on terrestrial ecosystems under future climate change are still highly uncertain. In this study, we assess and compare the present and future impact of drought on vegetation net primary productivity. The results suggest that global drought events are projected to be intensified and frequent in the coming decades. Drought‐related NPP reduction is prevalent especially in the arid and semi‐arid areas and tropical regions at the end of 21st century. Extreme drought depresses NPP most under RCPs, followed by severe and moderate droughts. For vegetation, the adverse impact on NPP induced by drought under RCPs is increasingly significant in Evergreen Broadleaf Forest, Grassland, Savanna, and Cropland. Climate change is projected to play the largest role in aggravating the risk of drought‐induced NPP reduction. These results highlight the growing vulnerability of ecosystem productivity to droughts, implying increased adverse impacts of these climate extremes on terrestrial carbon sinks. Key Points Net primary productivity (NPP) reduction associated with drought is prevalent especially in the arid and semi‐arid areas and tropical regions Adverse impact of drought on NPP under RCPs is large in Evergreen Broadleaf Forest, Shrubland, Grassland, and Cropland The largest NPP loss occurs under RCP4.5. Climate change plays the largest role in aggravating the risk of drought‐induced NPP reduction

A regional climate modelling system, the Providing REgional Climates for Impacts Studies developed by the Hadley Centre for Climate Prediction and Research, has been used to study future climate change scenarios over Indus basin for the impact assessment. In this paper we have examined the three Quantifying Uncertainty in Model Predictions simulations selected from 17-member perturbed physics ensemble generated using Hadley Centre Coupled Module. The climate projections based on IPCC SRES A1B scenario are analysed over three time slices, near future (2011–2040), middle of the twenty first century (2041–2070), and distant future (2071–2098). The baseline simulation (1961–1990) was evaluated with observed data for seasonal and spatial patterns and biases. The model was able to resolve features on finer spatial scales and depict seasonal variations reasonably well, although there were quantitative biases. The model simulations suggest a non-uniform change in precipitation overall, with an increase in precipitation over the upper Indus basin and decrease over the lower Indus basin, and little change in the border area between the upper and lower Indus basins. A decrease in winter precipitation is projected, particularly over the southern part of the basin. Projections indicate greater warming in the upper than the lower Indus, and greater warming in winter than in the other seasons. The simulations suggest an overall increase in the number of rainy days over the basin, but a decrease in the number of rainy days accompanied by an increase in rainfall intensity in the border area between the upper and lower basins, where the rainfall amount is highest.

The Sierra de las Nieves high-relief karst aquifer, which is located in the natural park and UNESCO biosphere reserve of the same name, is an area of great interest due to its geological, geomorphological (both at the surface and underground), hydrogeological, and ecological value. The aquifer is not influenced by pumping and is considered to be a natural laboratory for karst research because of how well developed the main karst characteristics are at both the surface (karst depressions and karst springs) and underground (with a large network of caves). The hydrological cycle is sustained by relatively high precipitation (annual mean precipitation of approximately 1000 mm) and moderate temperatures (annual mean temperature of approximately 16 °C). However, these climate parameters are susceptible to significant disruption because of ongoing anthropogenic-driven climate change induced by increased CO2 in the atmosphere. This paper offers an analysis and discussion of the impact that these potential future changes, estimated from the temperature and precipitation projections from regional climate models, may have on this karst aquifer, particularly on its recharge. The projections have been corrected using several techniques based on two hypotheses, bias correction and delta change approaches. We have focus on the future assessment for the horizon 2071–2100 under the most pessimistic emission scenario (RCP 8.5) contemplated within the last published IPCC report (IPCC, Contribution of working group II to the fifth assessment report of the intergovernmental panel on climate change. Cambridge University Press, Cambridge, UK and New York, NY, USA, 2014). It is expected that there will be, on average, a 27% reduction in precipitation and a 19% increase in temperature. This is a dangerous combination that will dramatically decrease recharge and will require new local adaptation measures, in addition to global mitigation measures, to prevent the area’s resources, biodiversity, and geodiversity from being drastically diminished.

Cycads hold important economic and conservation value. Some species are extensively used in landscaping, while others are endangered and legally protected. The Australian cycad-attacking weevil, Siraton internatus , is notably destructive, occasionally causing infestations and invasions across various countries. This study simulated habitat suitability for S. internatus to assess its potential invasion and the impact of climate change. Habitat suitability was evaluated under current climate and four climate change scenarios over two time frames (2050 and 2090). Furthermore, we investigated the threat posed by S. internatus to cycad reserves, using Taiwanese reserves as a representative case. Our MaxEnt predictions demonstrated high accuracy, meeting multiple evaluation criteria. We explored the potential distribution of S. internatus within Australia and internationally, identifying suitable habitats in Africa, the Americas, Asia, and Europe. The case study highlighted the low habitat suitability within the two Taiwanese cycad reserves, which is projected to decrease to unsuitable levels under future climate change scenarios for this weevil species. Moreover, our results revealed that suitable habitat for S. internatus is projected to contract globally under all climate scenarios and time periods, but expansion in Chile and the southern Himalaya (e.g., Nepal). This study provides valuable insights into cycad conservation and pest invasion risks. The results support both global and local efforts to manage the invasion threats from this destructive Australian cycad-attacking weevil species. It also accentuates the urgency for continuous biosecurity inspections and prevention of exporting mature cycad caudexes from Australia.

Climate change can modify regional wind power generation ability, as it may affect wind speed. Here, we developed a multivariate copula downscaling (MvCD) approach to statistically downscale the near-surface wind speed of CMIP5 global climate models (GCMs) to the scale of wind farms in Urumqi, China. The low computational cost and high random analysis capability of this approach allowed the rapid assessment of projected changes and randomness from nine GCMs, spanning a range of potential futures under four scenarios. Simulation data from multiple GCMs and historical data of the study area were incorporated into the MvCD to generate a high dimensional multivariate copula. Thereafter, the high dimensional multivariate copula was further used to identify future wind speed patterns based on multiple GCMs under different CO2 emission scenarios. The estimated amount of wind power generation was obtained using future wind speed data. Results revealed the regional characteristics and periodicity of wind speed for Urumqi in the future. Wind power generation results revealed the impacts of climate changes on regional wind power generation and indicated that high wind speeds would occur from June to September and low wind speeds would occur from December to March in future scenarios. Wind speed would be more extreme under each scenario in the future than before. The highest and lowest wind speeds will increase and decrease, respectively. Sustained high winds would increase the potential of wind power generation in the future. Wind instability based on CO2 emission increases will lead to wind power being curtailed and low wind-power generation.

Climate change is one of the most pressing global issues of the twenty-first century. This phenomenon has an increasingly severe impact on water resources and crop production. The main purpose of this study is to evaluate the impact of climate change on water resources, crop production, and agricultural sustainability in an arid environment in Iran. To this end, the study constructs a new integrated climate-hydrological-economic model to assess the impact of future climate change on water resources and crop production. Furthermore, the agricultural sustainability is evaluated using the multicriteria decision making (MCDM) technique in the context of climate change. The findings regarding the prediction of climate variables show that the minimum and maximum temperatures are expected to increase by about 5.88% and 6.05%, respectively, while precipitation would decrease by approximately 30.68%. The results of the research reveal that water availability will decrease by about 13.79–15.45% under different climate scenarios. Additionally, the findings show that in the majority of cases crop production will reduce in response to climate scenarios so that rainfed wheat will experience the greatest decline (approximately 59.95%). The results of the MCDM model show that climate change can have adverse effects on economic and environmental aspects and, consequently, on the sustainability of the agricultural system of the study area. Our findings can inform policymakers on effective strategies for mitigating the consequences of climate change on water resources and agricultural production in dry regions.

Climate change and human activities have an important impact on the changing environment, leading to significant changes in the basin water cycle process. The Jialing River Basin, the largest tributary of the upper Yangtze River, is selected as the study area. Three different rainfall datasets, the China Meteorological Assimilation Driving (CMAD) dataset, the Tropical Rainfall Measuring Mission data, and gauged observation data, were used as inputs for the MIKE System Hydrological European (MIKE SHE) model. By comparing the simulation results driven by various meteorological data, the applicability of the MIKE SHE model at four stations is evaluated, and the sensitivity and uncertainty of model parameters are analyzed. Meanwhile, the impact of large hydropower stations on the runoff of the Jialing River Basin is assessed, and the influence of human activities on the runoff change is determined. The future climate change of the watershed was analyzed by using the typical representative concentration pathway (RCP) 4.5 and RCP8.5 climate scenarios. Based on the MIKE SHE model, the runoff of the Jialing River Basin in the future climate scenario is predicted, and the corresponding response of the Jialing River Basin is analyzed quantitatively. The results show that the CMAD data-driven model has better Nash–Sutcliffe efficiency and correlation coefficient for each period. By analyzing the influence of the hydropower station on the runoff process at the outlet of the basin, it is found that the hydropower station has a certain regulating effect on the runoff process at the outlet of the basin. In addition, the RCP4.5 scenario is more consistent with the future scenario, indicating that the Jialing River Basin will become colder and drier.

Net zero-energy buildings have become one of the flagships in the path towards the decarbonisation of cities. Even though heating systems, especially in existing buildings, are currently the main consumer in many areas of the world, cooling needs are gaining relevance in several countries, and this is expected to be kept in the focus in the context of increasing temperatures, according to the climate projections identified by the IPCC. This has also additional implications on thermal comfort conditions (and, indirectly, on the derived health issues) in areas where no cooling systems are installed in residential buildings. This research work aims to evaluate the design of shading elements as a design strategy in the path towards net-zero residential buildings in diverse Colombian climates. A parametric analysis is developed, considering a combination of different shading solutions applied in residential buildings. Their effectiveness is evaluated in different climate zones in Colombia considering both the current climate data and future climate data expected according to the projections proposed by the IPCC. A reference building in Bucaramanga (Colombia) was selected for detailed monitoring, and the collected data were used to validate a simulation model developed in DesignBuilder. Almost 1000 alternative scenarios were established and parametrically evaluated, resulting from the combination of different shadings solutions, orientations and climate conditions. The results are evaluated considering two different approaches: cooling demand assuming a standard indoor temperature profile and indoor comfort when no cooling devices are used in the building, showing that some strategies, such as overhangs, involve significant improvements in terms of indoor thermal comfort and a reduction in cooling demand (reaching in some cases savings up to 30%) in the different climate conditions considered; as well, their effectiveness remains similar when future climate projections are considered.