Differences in hydrological impacts using regional climate model and nested convection-permitting model data

Abstract

Assessing the potential impacts of climate change on river flows is critically important for adaptation. Data from global or nested regional climate models (GCMs/RCMs) are frequently used to drive hydrological models, but now there are also very high-resolution convection-permitting models (CPMs). Here, data from the first CPM climate ensemble for the UK, along with the RCM ensemble within which the CPM is nested, are used to drive a grid-based hydrological model. The performance for simulating baseline (1981–2000) river flows is compared between the RCM and the CPM, and the projections of future changes in seasonal mean flows and peak flows are compared across Britain (1981–2000 to 2061–2080). The baseline performance assessment shows that (before bias correction) the CPM generally performs better than the RCM, and bias correction of precipitation makes both the RCM and CPM perform more similarly to use of observation-based driving data. The analysis of future changes in flows shows that the CPM almost always gives higher flow changes than the RCM. If reliable, these differences in flow projections suggest that adaptation planning for high flows based on use of regional data may be insufficient, although planning for low flows may be slightly over-cautious. However, the availability of CPM data only for one RCM/GCM is a limitation for use in adaptation as it under-samples the uncertainty range. There are significant challenges to the wider application of CPM ensembles, including the high computational and data storage demands.

Soil Erosion in a British Watershed under Climate Change as Predicted Using Convection-Permitting Regional Climate Projections

“…Consequently, they can better capture storm dynamics and how they affect hydrological flows. This is verified in recent research where such projections are adopted to implement distributed hydrological models for studies in the UK [61], in temperate and alpine climates [62], and in south-west Africa [63], as well as semiarid areas [64]. The potentiality of this methodology is also explored in a soil erosion assessment over western Africa (Tanzania) [65] with the use of the RUSLE model (Revised Universal Soil Loss Equation) [66].…”

Spatial downscaling of precipitation for hydrological modelling: Assessing a simple method and its application under climate change in Britain

“…Where CPM data are not available, it may be possible to assess future applicability using coarser resolution data and evaluating, for example, large‐scale circulation changes (e.g., Pope et al, 2022). Although CPMs use spatial resolutions much closer to those typically required for hydrological modelling, they are very expensive, both computationally and in terms of data storage requirements (Kay, 2022). Thus, methods for spatial downscaling will still be needed for modelling the potential impacts of climate change on river flows using ensembles of coarser resolution climate model data.…”

On the application of rainfall projections from a convection-permitting climate model to lumped catchment models

“…Mapping of the Lake Victoria Basin in Fig. 1 incorporates data from the HydroSHEDS version 1 database which is © World Wildlife Fund, Inc. (2006-2022 and has been used herein under license. WWF has not evaluated the data as altered and incorporated within this paper, and therefore gives no warranty regarding its accuracy, completeness, currency or suitability for any particular purpose.…”

“…As convection-permitting models give greater intensification of extreme rainfall under climate change through better capturing the dynamics of storms and their couplings with larger scales, we therefore expect use of convection-permitting model projections of rainfall to affect projections of hydrological flows. The impacts of climate change based on CP projections on river flows based on distributed hydrological models have been evaluated in temperate climates such as the UK and northern and alpine Europe (Kay, 2022;Kay and Davies, 2008;Reszler et al, 2018;Schaller et al, 2020) and semiarid Texas (Wang and Wang, 2019). Recently Miller et al (2022) used CP projections to develop design storms to feed into an urban flood model in Burkina Faso, West Africa.…”