This paper examines the projected changes in rainfall in Southeast Asia (SEA) in the twenty-first century based on the multimodel simulations of the Southeast Asia Regional Climate Downscaling/Coordinated Regional Climate Downscaling Experiment-Southeast Asia (SEACLID/CORDEX-SEA). A total of 11 General Circulation Models (GCMs) have been downscaled using 7 Regional Climate Models (RCMs) to a resolution of 25 km × 25 km over the SEA domain (89.5° E-146.5° E, 14.8° S-27.0° N) for two different representative concentration pathways (RCP) scenarios, RCP4.5 and RCP8.5. The 1976-2005 period is considered as the historical period for evaluating the changes in seasonal precipitation of December-January-February (DJF) and June-July-August (JJA) over future periods of the early (2011-2040), mid (2041-2070) and late twenty-first century (2071-2099). The ensemble mean shows a good reproduction of the SEA climatological mean spatial precipitation pattern with systematic wet biases, which originated largely from simulations using the RegCM4 model. Increases in mean rainfall (10-20%) are projected throughout the twenty-first century over Indochina and eastern Philippines during DJF while a drying tendency prevails over the Maritime Continent. For JJA, projections of both RCPs indicate reductions in mean rainfall (10-30%) over the Maritime Continent, particularly over the Indonesian region by mid and late twenty-first century. However, examination of individual member responses shows prominent inter-model variations, reflecting uncertainty in the projections.

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Six bias correction (BC) methods; delta-method (DT), linear scaling (LS), power transformation of precipitation (PTR), empirical quantile mapping (EQM), gamma quantile mapping (GQM) and gamma-pareto quantile mapping (GPQM) were applied to adjust the biases of historical monthly precipitation outputs from five General Circulation Models (GCMs) dynamically downscaled by two Regional Climate Models (RCMs) for a total of seven different GCM-RCM pairs over Costa Rica. High-resolution gridded precipitation observations were used for the control period 1951-1980 and validated over the period 1981-1995. Results show that considerable biases exist between uncorrected GCM-RCM outputs and observations, which largely depend on GCM-RCM pair, seasonality, climatic region and spatial resolution. After the application of bias correction, substantial biases reductions and comparable performances among most BC methods were observed for most GCM-RCM pairs; with EQM and DT marginally outperforming the remaining methods. Consequently, EQM and DT were selectively applied to correct the biases of precipitation projections from each individual GCM-RCM pair for a near-future (2011-2040), mid-future (2041-2070) and far-future (2071-2100) period under Representative Concentration Pathways (RCPs) 2.6, 4.5 and 8.5 using the control period . Results from the bias-corrected future ensemble-mean anticipate a marked decreasing trend in precipitation from near to far-future periods during the dry season (December, January, February (DJF) and March, April, May (MAM)) for RCP4.5 and 8.5; with pronounced drier conditions for those climatic regions draining towards the Pacific Ocean. In contrast, mostly wetter conditions are expected during the dry season under RCP2.6, particularly for the Caribbean region. In most of the country, the greatest decrease in precipitation is projected at the beginning of the rainy season (June, July, August (JJA)) for the far-future period under RCP8.5, except for the Caribbean region where mostly wetter conditions are anticipated. Regardless of future period, slight increases in precipitation with higher radiative forcing are expected for SON excluding the Caribbean region, where precipitation is likely to increase with increasing radiative forcing and future period. This study demonstrates that bias correction should be considered before direct application of GCM-RCM precipitation projections over complex territories such as Costa Rica.

The Philippines is one of the most exposed countries in the world to tropical cyclones. In order to provide information to help the country build resilience and plan for a future under a warmer climate, we build on previous research to investigate implications of future climate change on tropical cyclone activity in the Philippines. Experiments were conducted using three regional climate models with horizontal resolutions of approximately 12 km (HadGEM3‐RA) and 25 km (HadRM3P and RegCM4). The simulations are driven by boundary data from a subset of global climate model simulations from the CMIP5 ensemble. Here we present the experimental design, the methodology for selecting CMIP5 models, the results of the model validation, and future projections of changes to tropical cyclone frequency and intensity by the mid‐21st century. The models used are shown to represent the key climatological features of tropical cyclones across the domain, including the seasonality and general distribution of intensities, but issues remain in resolving very intense tropical cyclones and simulating realistic trajectories across their life‐cycles. Acknowledging model inadequacies and uncertainties associated with future climate model projections, the results show a range of plausible changes with a tendency for fewer but slightly more intense tropical cyclones. These results are consistent with the basin‐wide results reported in the IPCC AR5 and provide clear evidence that the findings from these previous studies are applicable in the Philippines region.

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Tropical forests are global climate regulators through their interaction with hydrological and biogeochemical cycles. Despite extensive research on deforestation in South America and its global impact, the role of the largely intact Guiana Shield forests, north of the Amazon, has not yet been considered as part of this climate system. We use a regional climate model with a realistic deforestation scenario to test the impact of deforestation in the Guiana Shield on climate throughout South America. We show that replacing ∼28% of the current Guiana Shield rainforest with savannah leads to multi-scale impacts across South America, through vegetation-land-atmosphere interactions that disrupt the initial phase of two major 'atmospheric rivers': the Caribbean low-level Jet and the South American low-level jet (SALLJ). Our climate simulations suggest that following deforestation, locally, precipitation and runoff would more than double in lowland forests, whilst mean annual temperatures would increase by up to 2.2• C in savannahs. Regionally, significant wetting is simulated in northern South America (April−September) and the western Amazon (October-March), while temperatures increase up to 2• C in central and eastern Amazon, causing more dry months in up to 64% of the Amazon basin. Reduction of moisture transfer by the SALLJ of 2.2% of total annual flow causes noticeable and highly diverse spatial changes in simulated monthly rainfall in la plata basin (LPB). These results highlight the potential consequences of land cover change in a sensitive hot-spot with hydro-climatic impacts 1000 km west and 4000 km south. Such multi-scale perturbations can severely impact biodiversity and ecosystem services across South America, including agriculture in LPB. Recognition of the far field effects of localised deforestation in key areas is urgently needed to improve development plans for a sustainable future. Significance statementThe Guiana Shield, at the northern boundary of Amazonia, is located at the start of two atmospheric rivers which carry moisture across South America. We show that deforesting less than a third of the Guiana Shield, in areas currently under threat from mining, logging and agricultural activities, could result in significant changes in the water cycle across the continent. This includes large variations in temperature and precipitation affecting areas 4000 km away, impacting ecosystems and economies, with consequences for society. The study demonstrates how land-use change, even if small in spatial scale, but occurring in particularly sensitive hot-spots, can alter the flow of atmospheric rivers, with large consequences. This pan-continental cascade must be considered when designing trans-national management plans for a sustainable future.

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