Comparison of daily and sub-daily SWAT models for daily streamflow simulation in the Upper Huai River Basin of China

Despite the significant role of precipitation in the hydrological cycle, few studies have been conducted to evaluate the impacts of the temporal resolution of rainfall inputs on the performance of SWAT (soil and water assessment tool) models in large-sized river basins. In this study, both daily and hourly rainfall observations at 28 rainfall stations were used as inputs to SWAT for daily streamflow simulation in the Upper Huai River Basin. Study results have demonstrated that the SWAT model with hourly rainfall inputs performed better than the model with daily rainfall inputs in daily streamflow simulation, primarily due to its better capability of simulating peak flows during the flood season. The sub-daily SWAT model estimated that 58% of streamflow was contributed by baseflow compared to 34 % estimated by the daily model. Using the future daily and three-hour precipitation projections under the RCP (Representative Concentration Pathways) 4.5 scenario as inputs, the sub-daily SWAT model predicted a larger amount of monthly maximum daily flow during the wet years than the daily model. The differences between the daily and sub-daily SWAT model simulation results indicated that temporal rainfall resolution could have much impact on the simulation of hydrological process, streamflow, and consequently pollutant transport by SWAT models. There is an imperative need for more studies to examine the effects of temporal rainfall resolution on the simulation of hydrological and water pollutant transport processes by SWAT in river basins of different environmental conditions

An ensemble-based assessment of bias adjustment performance, changes in hydrometeorological predictors and compound extreme events in EAS-CORDEX

The effectiveness of adaptive measures tackling the effects of climate change is dependent on robust climate projections. This becomes even more important in the face of intensifying extreme events. One example of these events is flooding, which embodies a major threat to highly vulnerable coastal urban areas. This includes eastern Asia, where multiple coastal megacities are located, e.g. Shanghai and Shenzhen. While the ability of general circulation models (GCMs) and regional climate models (RCMs) to project atmospheric changes associated with these events has improved, systematic errors (biases) remain. This study therefore assess capabilities of improving the quality of regional climate projections for eastern Asia. This is performed by evaluating an ensemble consisting of bias adjustment methods, GCM-RCM model runs and future emission scenarios based on representative concentration pathways (RCP) obtained from EAS-CORDEX. We show that bias adjustment significantly improves the quality of model output and best results are obtained by applying quantile delta mapping. Based on these results we evaluate potential future changes in crucial hydrometeorological predictors, univariate extreme events and compound extreme events, focusing on high wind speeds and extreme precipitation. Key findings include an increase in daily maximum temperature of 1.5 to nearly 4 °C, depending on the scenario, as well as increased levels of precipitation under RCP 8.5. Furthermore, a distinct intensification of extreme events including high temperatures and heavy precipitation is detected and this increase exceeds the increase of the overall mean of these predictors. The annual number of compound events including heavy precipitation and extreme wind speeds shows a significant increase of up to 50% for RCP 8.5 in the South China Sea as well as the adjacent coastal areas

Comparison of CMIP5 and CMIP6 GCM performance for flood projections in the Mekong River Basin

Study region: Mekong River Basin. Study focus: The Coupled Model Intercomparison Project Phase 6 (CMIP6) recently announced an updated version of general circulation models (GCMs). This study investigated the performance of improved CMIP6 over those of CMIP5 with respect to precipitation and flood representations in the Mekong River Basin (MRB). The correlation and error comparison from the referenced precipitation exhibited a significant improvement in the peak value representation. Hence, the impacts of climate change on future floods in the MRB were simulated and assessed using a distributed rainfall–runoff–inundation model. New hydrological insights for the region: The results indicated that precipitation from CMIP6 had a higher correlation and a lower error coefficient than CMIP5. Similarly, the simulation of GCM ensembles of monthly discharge from CMIP6 exhibited a comparable average value to the observations, whereas CMIP5 underestimated the discharge simulations. The performance of the mean annual peak discharge improved from 37, 220 m3/s (CMIP5) to 45, 423 m3/s (CMIP6) compared to 43, 521 m3/s (observation). The projections of future floods in the MRB from CMIP6 exhibited an increase of annual peak discharge at Chiang Saen, Vientiane, Pakse, and Kratie stations by 10–15%, 20–22%, and 24–29% for the SSP2-4.5 scenario, and 10–18%, 24–29%, and 41–54% for the SSP5-8.5 scenario in the near future (2026–2050), mid-future (2051–2075), and far future (2076–2100), respectively. The statistical K-S test showed significant changes in all stations and projected periods with a p-value < 0.01

An ensemble-based assessment of bias adjustment performance, changes in hydrometeorological predictors and compound extreme events in EAS-CORDEX

The effectiveness of adaptive measures tackling the effects of climate change is dependent on robust climate projections. This becomes even more important in the face of intensifying extreme events. One example of these events is flooding, which embodies a major threat to highly vulnerable coastal urban areas. This includes eastern Asia, where multiple coastal megacities are located, e.g. Shanghai and Shenzhen. While the ability of general circulation models (GCMs) and regional climate models (RCMs) to project atmospheric changes associated with these events has improved, systematic errors (biases) remain. This study therefore assess capabilities of improving the quality of regional climate projections for eastern Asia. This is performed by evaluating an ensemble consisting of bias adjustment methods, GCM-RCM model runs and future emission scenarios based on representative concentration pathways (RCP) obtained from EAS-CORDEX. We show that bias adjustment significantly improves the quality of model output and best results are obtained by applying quantile delta mapping. Based on these results we evaluate potential future changes in crucial hydrometeorological predictors, univariate extreme events and compound extreme events, focusing on high wind speeds and extreme precipitation. Key findings include an increase in daily maximum temperature of 1.5 to nearly 4 C, depending on the scenario, as well as increased levels of precipitation under RCP 8.5. Furthermore, a distinct intensification of extreme events including high temperatures and heavy precipitation is detected and this increase exceeds the increase of the overall mean of these predictors. The annual number of compound events including heavy precipitation and extreme wind speeds shows a significant increase of up to 50% for RCP 8.5 in the South China Sea as well as the adjacent coastal areas

Changes in solar resource intermittency and reliability under Australia's future warmer climate

The dependency of photovoltaic (PV) power generation on meteorological parameters can impact power production due to weather-induced variability. During the day, fluctuations in radiation introduce intermittency in power generated, raising reliability and grid stability issues at higher penetration levels. Long-term future resource assessment provides an effective tool for estimating resource reliability and future intermittency essential for pre-feasibility site assessments around the world. Australia has high solar power capacity, with several solar farms in operational and developmental stage. Using Australia as a case study, this research aims to understand Australia's solar resource distribution and variability using regional climate model projections under a high emission scenario. Results indicate an abundance of solar resource power density in Australia, especially in the North (450-500Wm−2). The solar resource will be more reliable in Eastern Australia in the future with ∼ 5% increase in resource density. Results suggest reduction in intermittency (∼20-minute lull periods) in the East with increase in clear-sky days/year in the future (∼20 days/year). Resource assessment of Sun Cable and New England solar farm located in Australia, revealed the future scope of increase in clear-sky days at the sites. This long-term future solar variability analysis can help identify regions in Australia where PV systems will be least susceptible to losses due to intermittency. Furthermore, this study will help in critical decision-making processes like planning storage systems, site selection, opportunities to create hybrid solar farms with the co-existence of solar and wind technology, etc., to mitigate the risks associated with future intermittent PV power generation

Projected changes in extreme temperature and precipitation indices over CORDEX-MENA domain

In this study, projected changes in climate extreme indices defined by the Expert Team on Climate Change Detection and Indices were investigated over Middle East and North Africa. Changes in the daily maximum and minimum temperature-and precipitation-based extreme indices were analyzed for the end of the 21st century compared to the reference period 1971–2000 using regional climate model simulations. Regional climate model, RegCM4.4 was used to downscale two different global climate model outputs to 50 km resolution under RCP4.5 and RCP8.5 scenarios. Results generally indicate an intensification of temperature-and precipitation-based extreme indices with increasing radiative forcing. In particular, an increase in annual minimum of daily minimum temperatures is more pronounced over the northern part of Mediterranean Basin and tropics. High increase in warm nights and warm spell duration all over the region with a pronounced increase in tropics are projected for the period of 2071–2100 together with decrease or no change in cold extremes. According to the results, a decrease in total wet-day precipitation and increase in dry spells are expected for the end of the century.Publisher's Versio

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

A Framework to Project Future Rainfall Scenarios: An Application to Shallow Landslide-Triggering Summer Rainfall in Wanzhou County China

Fatal landslides are a widespread geohazard that have affected millions of people and have claimed the lives of thousands around the globe. A change in climate has significantly increased the frequency and magnitude of rainfall, which affect the susceptibility of slopes to shallow landslides. This paper presents a methodological framework to assess the future changes in extreme and seasonal rainfall magnitudes with climate model projections. This framework was applied to project summer rainfall over Wanzhou County, China, using an ensemble of four regional climate models (RCMs) from the East Asian domain of the Coordinated Downscaling Experiment (CORDEX) under the Phase 5 Coupled Intercomparison Modeling Project (CMIP5). The results find that extreme daily rainfall was projected to decrease in the mid-21st century, with an uncertainty measured by a coefficient of variation between 5% and 25%. The mean seasonal rainfall is projected to increase in the mid-21st century up to a factor of 1.4, and up to a factor of 1.8 in the late-21st century. The variation in the mid21st century ranged from 10% to 35%, and from 30% to 50% in the late-21st century. This case study delivered a proof-of-concept for a methodological framework to derive shallow landslide-triggering rainfall scenarios under climate change conditions. The resulting spatially distributed climate change factors (CCFs) can be used to incorporate future rainfall scenarios in slope susceptibility models and climate impact assessments.Peer ReviewedObjectius de Desenvolupament Sostenible::13 - Acció per al ClimaPostprint (updated version

COSMO-CLM regional climate simulations in the Coordinated Regional Climate Downscaling Experiment (CORDEX) framework: a review

In the last decade, the Climate Limited-area Modeling Community (CLM-Community) has contributed to the Coordinated Regional Climate Downscaling Experiment (CORDEX) with an extensive set of regional climate simulations. Using several versions of the COSMO-CLM-Community model, ERA-Interim reanalysis and eight global climate models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) were dynamically downscaled with horizontal grid spacings of 0.44∘ (∼ 50 km), 0.22∘ (∼ 25 km), and 0.11∘ (∼ 12 km) over the CORDEX domains Europe, South Asia, East Asia, Australasia, and Africa. This major effort resulted in 80 regional climate simulations publicly available through the Earth System Grid Federation (ESGF) web portals for use in impact studies and climate scenario assessments. Here we review the production of these simulations and assess their results in terms of mean near-surface temperature and precipitation to aid the future design of the COSMO-CLM model simulations. It is found that a domain-specific parameter tuning is beneficial, while increasing horizontal model resolution (from 50 to 25 or 12 km grid spacing) alone does not always improve the performance of the simulation. Moreover, the COSMO-CLM performance depends on the driving data. This is generally more important than the dependence on horizontal resolution, model version, and configuration. Our results emphasize the importance of performing regional climate projections in a coordinated way, where guidance from both the global (GCM) and regional (RCM) climate modeling communities is needed to increase the reliability of the GCM–RCM modeling chain