A large set of potential past, present and future hydro-meteorological time series for the UK

ydro-meteorological extremes such as drought and heavy precipitation can have large impacts on society and the economy. With potentially increasing risks associated with such events due to climate change, properly assessing the associated impacts and uncertainties is critical for adequate adaptation...

Mô tả đầy đủ

Đã lưu trong:
Chi tiết thư mục
Tác giả chính: Guillod, B. P., Jones, R. G., Dadson, S. J.
Ngôn ngữ:English
Năm xuất bản: Universitas Gadjah Mada 2018
Chủ đề:
Truy cập Trực tuyến:http://lrc.quangbinhuni.edu.vn:8181/dspace/handle/DHQB_123456789/3692
Tags: Thêm thẻ
Không có thẻ, Hãy là người đầu tiên gắn thẻ bản ghi này!
id oai:localhost:DHQB_123456789-3692
recordtype dspace
spelling oai:localhost:DHQB_123456789-36922018-10-22T08:44:10Z A large set of potential past, present and future hydro-meteorological time series for the UK Guillod, B. P. Jones, R. G. Dadson, S. J. Geography. Anthropology. : Geography Recreation ydro-meteorological extremes such as drought and heavy precipitation can have large impacts on society and the economy. With potentially increasing risks associated with such events due to climate change, properly assessing the associated impacts and uncertainties is critical for adequate adaptation. However, the application of risk-based approaches often requires large sets of extreme events, which are not commonly available. Here, we present such a large set of hydro-meteorological time series for recent past and future conditions for the United Kingdom based on weather@home 2, a modelling framework consisting of a global climate model (GCM) driven by observed or projected sea surface temperature (SST) and sea ice which is downscaled to 25 km over the European domain by a regional climate model (RCM). Sets of 100 time series are generated for each of (i) a historical baseline (1900–2006), (ii) five near-future scenarios (2020–2049) and (iii) five far-future scenarios (2070–2099). The five scenarios in each future time slice all follow the Representative Concentration Pathway 8.5 (RCP8.5) and sample the range of sea surface temperature and sea ice changes from CMIP5 (Coupled Model Intercomparison Project Phase 5) models. Validation of the historical baseline highlights good performance for temperature and potential evaporation, but substantial seasonal biases in mean precipitation, which are corrected using a linear approach. For extremes in low precipitation over a long accumulation period ( > 3 months) and shorter-duration high precipitation (1–30 days), the time series generally represents past statistics well. Future projections show small precipitation increases in winter but large decreases in summer on average, leading to an overall drying, consistently with the most recent UK Climate Projections (UKCP09) but larger in magnitude than the latter. Both drought and high-precipitation events are projected to increase in frequency and intensity in most regions, highlighting the need for appropriate adaptation measures. Overall, the presented dataset is a useful tool for assessing the risk associated with drought and more generally with hydro-meteorological extremes in the UK. 2018-07-19T02:07:58Z 2018-07-19T02:07:58Z 2018 http://lrc.quangbinhuni.edu.vn:8181/dspace/handle/DHQB_123456789/3692 en Universitas Gadjah Mada
institution Trung tâm Học liệu Đại học Quảng Bình (Dspace)
collection Trung tâm Học liệu Đại học Quảng Bình (Dspace)
language English
topic Geography. Anthropology. : Geography
Recreation
spellingShingle Geography. Anthropology. : Geography
Recreation
Guillod, B. P.
Jones, R. G.
Dadson, S. J.
A large set of potential past, present and future hydro-meteorological time series for the UK
description ydro-meteorological extremes such as drought and heavy precipitation can have large impacts on society and the economy. With potentially increasing risks associated with such events due to climate change, properly assessing the associated impacts and uncertainties is critical for adequate adaptation. However, the application of risk-based approaches often requires large sets of extreme events, which are not commonly available. Here, we present such a large set of hydro-meteorological time series for recent past and future conditions for the United Kingdom based on weather@home 2, a modelling framework consisting of a global climate model (GCM) driven by observed or projected sea surface temperature (SST) and sea ice which is downscaled to 25 km over the European domain by a regional climate model (RCM). Sets of 100 time series are generated for each of (i) a historical baseline (1900–2006), (ii) five near-future scenarios (2020–2049) and (iii) five far-future scenarios (2070–2099). The five scenarios in each future time slice all follow the Representative Concentration Pathway 8.5 (RCP8.5) and sample the range of sea surface temperature and sea ice changes from CMIP5 (Coupled Model Intercomparison Project Phase 5) models. Validation of the historical baseline highlights good performance for temperature and potential evaporation, but substantial seasonal biases in mean precipitation, which are corrected using a linear approach. For extremes in low precipitation over a long accumulation period ( > 3 months) and shorter-duration high precipitation (1–30 days), the time series generally represents past statistics well. Future projections show small precipitation increases in winter but large decreases in summer on average, leading to an overall drying, consistently with the most recent UK Climate Projections (UKCP09) but larger in magnitude than the latter. Both drought and high-precipitation events are projected to increase in frequency and intensity in most regions, highlighting the need for appropriate adaptation measures. Overall, the presented dataset is a useful tool for assessing the risk associated with drought and more generally with hydro-meteorological extremes in the UK.
author Guillod, B. P.
Jones, R. G.
Dadson, S. J.
author_facet Guillod, B. P.
Jones, R. G.
Dadson, S. J.
author_sort Guillod, B. P.
title A large set of potential past, present and future hydro-meteorological time series for the UK
title_short A large set of potential past, present and future hydro-meteorological time series for the UK
title_full A large set of potential past, present and future hydro-meteorological time series for the UK
title_fullStr A large set of potential past, present and future hydro-meteorological time series for the UK
title_full_unstemmed A large set of potential past, present and future hydro-meteorological time series for the UK
title_sort large set of potential past, present and future hydro-meteorological time series for the uk
publisher Universitas Gadjah Mada
publishDate 2018
url http://lrc.quangbinhuni.edu.vn:8181/dspace/handle/DHQB_123456789/3692
_version_ 1717292436978401280
score 9,463379