4.5 Article

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

期刊

CLIMATIC CHANGE
卷 173, 期 1-2, 页码 -

出版社

SPRINGER
DOI: 10.1007/s10584-022-03405-z

关键词

Climate change; Hydrological impacts; UK Climate Projections 2018; UKCP18; CPM; RCM

资金

  1. Natural Environment Research Council [NE/S017380/1]

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Assessing the potential impacts of climate change on river flows is crucial for adaptation. A study comparing convection-permitting models (CPMs) and regional climate models (RCMs) for simulating river flows in the UK found that before bias correction, CPMs generally perform better than RCMs. Bias correction of precipitation improved the performance of both models. In terms of future flow projections, CPMs consistently projected higher flow changes than RCMs. However, the limited availability of CPM data in comparison to RCM/GCM data poses challenges for its wider application in adaptation planning.
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.

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