Evaluation and selection of CORDEX-SA datasets and bias correction methods for a hydrological impact study in a humid tropical river basin, Kerala

It is well recognised that the performance of climate model simulations and bias correction methods is region specific, and, therefore, careful validation should always be performed. This study evaluates the performance of five general circulation model–regional climate model (GCM–RCM) combinations selected from CORDEX–SA datasets over a humid tropical river basin in Kerala, India, for climate variables such as precipitation, maximum and minimum temperatures. This involves ranking of the selected climate models based on an EDAS (Evaluation Based on Distance from Average Solution) method and the selection of an appropriate bias correction method for the selected three climate variables. A range of indices are used to evaluate the performance of the bias-corrected climate models to simulate observed climate data. Finally, the hydrological impact of the bias-corrected ranked models is assessed by simulating streamflow over the river basin using individual models and different combinations of models based on rank. According to the findings, hydrological simulation using an average of all GCM–RCM pairs provides the best model output in simulating streamflow, with an NSE value of 0.72. The results confirm the importance of a multimodel ensemble for improving the reliability and minimising the uncertainty of climate predictions for impact studies.

Hydrological impact of the new ECMWF multi-layer snow scheme

<p>Snow processes, with the water stored in the snowpack and released as snowmelt, are very important components of the water balance, in particular in high latitude and mountain regions. The evolution of the snow cover and the timing of the snow melt can have major impact on river discharge. Land surface models are used in Earth System models to compute exchanges of water, energy and momentum between the atmosphere and the surface underneath, and also to compute other components of the hydrological cycle. In order to improve the snow representation, a new multi-layer snow scheme is under development in the HTESSEL land surface model of the European Centre for Medium‐Range Weather Forecasts (ECMWF) Integrated Forecasting System (IFS), to replace the current single-layer snow scheme used in HTESSEL. The new scheme has already been shown to improve snow and 2‐metre temperature, while in this study, the wider hydrological impact is evaluated and documented.</p><p>The analysis is done in the reanalysis context by comparing two ERA5-forced offline HTESSEL experiments. The runoff output of HTESSEL is coupled to the CaMa-Flood hydrodynamic model in order to derive river discharge. The analysis is done globally for the period between 1980-2018. The evaluation was carried out using over 1000 discharge observation time-series with varying catchment size. The hydrological response of the multi-layer snow scheme is generally positive, but in some areas the improvement is not clear and can even be negative with deteriorated signal in river discharge. Further investigation is needed to understand the complex hydrological impact of the new snow scheme, making sure it contributes to an improved description of all hydrological components of the Earth System.</p>

Hydrologic projections for Australia: understanding future changes to water availability and extremes

<p>Australia's large natural hydro-climatic variability has already seen many changes, such as declining rainfall in the southern part of the country. Understanding these shifts and associated impacts on water availability is an important issue for Australia, as water supply is dependent on the generation of surface water resources. Sustainable future urban and agriculture developments will depend on best available knowledge about the risks and vulnerabilities of future water availability.</p><p>To understand those risks and vulnerabilities and to mitigate the impact of a changing climate, Australia's water policy, management and infrastructure decision making needs detailed high-resolution climate and water information. This includes information on multi-decadal timescales from future projections in the context of past climate variabilities. In Australia, currently, hydrologic change information exists in various forms, ranging from multiple regional downscaling efforts, bias-correction methods and different interpretation methods for hydrologic impact assessment – all limiting a national, consistent impact assessment across multiple spatial and temporal scales. These regional downscaling and hydrological impact data collections are either not application-ready or are tailored for specific purposes only, which poses additional barriers to their use across the water and other sectors.</p><p>To overcome these barriers, the Bureau of Meteorology is soon to release a seamless national landscape water service known as the Australian Water Outlook (AWO), combining historical data on water availability with forecast products, as well as hydrological impact projections. This system's core is the Australian Landscape Water Balance model (AWRA-L) modelling hydrologic variables consistently across a large range of spatial and temporal scales. The AWRA-L model is underpinned by substantial scientific development including data assimilation approaches for model calibration as well as model evaluation approaches for past and present time scales. Additionally, consistent downscaling and bias-correction approaches are integrated for the hydrologic projections in the operational framework.</p><p>This presentation will share an overview of the soon to be released Australian Water Outlook seamless service with an emphasis on the Hydrologic Projections part: the methodology, the user centred-design, as well as the development of guidance material containing confidence statements and uncertainty assessments to help decision makers in understanding the service. The presentation will also provide an overview of the tactics we applied to ensure the applicability of the new service including demonstration cases developed in partnership with users.</p>