Global exposure of population and land‐use to meteorological droughts under different warming levels and SSPs: a CORDEX‐based study

Global warming is likely to cause a progressive drought increase in some regions, but how population and natural resources will be affected is still underexplored. This study focuses on global population, forests, croplands and pastures exposure to meteorological drought hazard in the 21st century, expressed as frequency and severity of drought events. As input, we use a large ensemble of climate simulations from the Coordinated Regional Climate Downscaling Experiment (CORDEX), population projections from the NASA-SEDAC dataset and land-use projections from the Land-Use Harmonization 2 project for 1981–2100. The exposure to drought hazard is presented for five Shared Socioeconomic Pathways (SSP1-SSP5) at four Global Warming Levels (GWLs: 1.5°C to 4°C). Results show that considering only Standardized Precipitation Index (SPI; based on precipitation), the SSP3 at GWL4 projects the largest fraction of the global population (14%) to experience an increase in drought frequency and severity (versus 1981–2010), with this value increasing to 60% if temperature is considered (indirectly included in the Standardized Precipitation-Evapotranspiration Index, SPEI). With SPEI, considering the highest GWL for each SSP, 8 (for SSP2, SSP4, SSP5) and 11 (SSP3) billion people, that is, more than 90%, will be affected by at least one unprecedented drought. For SSP5 at GWL4, approximately 2 × 10$^{6}$ km$^{2}$ of forests and croplands (respectively, 6% and 11%) and 1.5 × 10$^{6}$ km$^{2}$ of pastures (19%) will be exposed to increased drought frequency and severity according to SPI, but for SPEI this extent will rise to 17 × 10$^{6}$ km$^{2}$ of forests (49%), 6 × 10$^{6}$ km$^{2}$ of pastures (78%) and 12 × 10$^{6}$ km$^{2}$ of croplands (67%), being mid-latitudes the most affected. The projected likely increase of drought frequency and severity significantly increases population and land-use exposure to drought, even at low GWLs, thus extensive mitigation and adaptation efforts are needed to avoid the most severe impacts of climate change

High-resolution climate projections for the islands of Lombok and Sumbawa, Nusa Tenggara Barat Province, Indonesia: Challenges and implications

The regional climate of Nusa Tenggara Barat (NTB) Province, eastern Indonesia is simulated for 130 years (1971–2100) for the SRES A2 Delayed Development or ‘Business as Usual’ emissions scenario using the CSIRO conformal-cubic atmospheric model (CCAM). Regional climate simulations are generated using a multiple downscaling technique where a CCAM 200 km uniform-grid global simulation is driven by bias-corrected sea surface temperatures (SSTs) from host coupled Global Climate Models (GCMs). Next, the 200 km resolution CCAM simulations are dynamically downscaled to 14 km resolution for the islands of Lombok and Sumbawa. To provide an ensemble of results, separate simulations are performed from six host GCMs. The present-day model results are validated against available observations. Generally, the CCAM 14 km resolution simulations produce rainfall, maximum and minimum temperatures that are similar to the observations. However, the 14 km simulations have rainfall biases of around 5 mm/day in the wet December–February season and lesser biases in the other seasons. Climate projections are examined for two future time intervals centred on 2030 and 2060. The simulations of rainfall changes by 2060 suggest both increases and decreases of up to 5% in December–February, with more acute declines of 10% in some areas, and decreases of up to 10% in March–May. For the other seasons, generally little change is simulated. The regional temperatures are projected to increase by about 1 °C by 2030 and 1.6–2 °C by 2060. The high-resolution model outputs enable detailed differentiation between locations across the islands. Our results show that due to orographic effects there are steep climate gradients, resulting in significant local differences in climate projections. We discuss the challenges and implications of these results for adaptation planning

Climate projections for southern Australian cool-season rainfall: insights from a downscaling comparison

The projected drying of the extra-tropics under a warmer climate has large implications for natural systems and water security in southern Australia. The downscaling of global climate models can provide insight into regional patterns of rainfall change in the mid-latitudes in the typically wetter cool season. The comparison of statistical and dynamical downscaling model outputs reveals regions of consistent potential added value in the climate-change signal over the 21st century that are largely related to finer resolution. These differences include a stronger and more regionalised rainfall decrease on west coasts in response to a shift in westerly circulation and a different response further from the coast where other influences are important. These patterns have a plausible relationship with topography and regional drivers that are not resolved by coarse global models. However, the comparison of statistical and dynamical downscaling reveals where the method and the configuration of each method makes a difference to the projection. This is an important source of uncertainty for regional rainfall projections. In particular, the simulated change in atmospheric circulation over the century is different in the dynamical downscaling compared to the global climate model inputs, related in part to a different response to patterns of surface warming. The dynamical downscaling places the border between regions with rainfall increase and decrease further north in winter and spring compared to the global climate models and therefore has a different rainfall projection for southeast mainland Australia in winter and for Tasmania in spring

Evaluating reanalysis-driven CORDEX regional climate models over Australia: model performance and errors

[eng] The ability of regional climate models (RCMs) to accurately simulate current and future climate is increasingly important for impact assessment. This is the first evaluation of all reanalysis-driven RCMs within the CORDEX Australasia framework [four configurations of the Weather Forecasting and Research (WRF) model, and single configurations of COSMO-CLM (CCLM) and the Conformal-Cubic Atmospheric Model (CCAM)] to simulate the historical climate of Australia (1981–2010) at 50 km resolution. Simulations of near-surface maximum and minimum temperature and precipitation were compared with gridded observations at annual, seasonal, and daily time scales. The spatial extent, sign, and statistical significance of biases varied markedly between the RCMs. However, all RCMs showed widespread, statistically significant cold biases in maximum temperature which were the largest during winter. This bias exceeded − 5 K for some WRF configurations, and was the lowest for CCLM at ± 2 K. Most WRF configurations and CCAM simulated minimum temperatures more accurately than maximum temperatures, with biases in the range of ± 1.5 K. RCMs overestimated precipitation, especially over Australia’s populous eastern seaboard. Strong negative correlations between mean monthly biases in precipitation and maximum temperature suggest that the maximum temperature cold bias is linked to precipitation overestimation. This analysis shows that the CORDEX Australasia ensemble is a valuable dataset for future impact studies, but improving the representation of land surface processes, and subsequently of surface temperatures, will improve RCM performance. The varying RCM capabilities identified here serve as a foundation for the development of future regional climate projections and impact assessments for Australia