Towards new weather and climate baselines for assessing weather and climate extremes, impacts, and risks

Initiatives to recover (sourcing, imaging, digitizing) historic datasets for generating more accurate longterm climate models have only gained momentum over the last decade, despite a long precedent of compelling arguments as to the value of historic weather observations (Le Roy Ladurie, 1972; Lamb,...

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Main Authors: WILLIAMSON, Fiona, ALLAN, Rob, D'Arrigo, Roseanne
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2017
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Online Access:https://ink.library.smu.edu.sg/cis_research/227
https://ink.library.smu.edu.sg/context/cis_research/article/1226/viewcontent/11_CBA2014_01_pvoa_cc_by.pdf
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spelling sg-smu-ink.cis_research-12262024-12-12T09:09:16Z Towards new weather and climate baselines for assessing weather and climate extremes, impacts, and risks WILLIAMSON, Fiona ALLAN, Rob D'Arrigo, Roseanne Initiatives to recover (sourcing, imaging, digitizing) historic datasets for generating more accurate longterm climate models have only gained momentum over the last decade, despite a long precedent of compelling arguments as to the value of historic weather observations (Le Roy Ladurie, 1972; Lamb, 1977). Although such work is relatively well established in Europe, the United States, China, and Japan; Southeast Asia currently has a dearth of data rescue initiatives with a long historical focus. The reasons behind this include a perception of the paucity of surviving data; the scattered nature of data due to shifts between colonial rule and independence and, later regime changes; a lack of local resources to develop data recovery projects. By way of example, the Southeast Asian Climate Assessment & Dataset (SACA&D) Digitisasi Data Historis (DiDaH) project, now completed, was limited by the fact that the bulk of observations recovered and digitized were in the post 1940s-50s period (apart from Indonesia in the South East Asian region) and, their data rescue was directed at National Meteorological Service (NMS) records only, with generally a heavy focus on temperature and precipitation data. ACRE SEA has a wider scope, with a longer historical timeframe (especially with a pre 1940s-50s observations focus) and broader record collection base, using archives, libraries, and online sources across the region and internationally. In fact, the SACA&D DiDaH project. 2017-11-01T07:00:00Z text application/pdf https://ink.library.smu.edu.sg/cis_research/227 info:doi/10.30852/sb.2017.179 https://ink.library.smu.edu.sg/context/cis_research/article/1226/viewcontent/11_CBA2014_01_pvoa_cc_by.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection College of Integrative Studies eng Institutional Knowledge at Singapore Management University Climate data recovery dynamical reconstructions historic weather re-analyses Asian Studies Environmental Sciences Geographic Information Sciences
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic Climate
data recovery
dynamical reconstructions
historic weather
re-analyses
Asian Studies
Environmental Sciences
Geographic Information Sciences
spellingShingle Climate
data recovery
dynamical reconstructions
historic weather
re-analyses
Asian Studies
Environmental Sciences
Geographic Information Sciences
WILLIAMSON, Fiona
ALLAN, Rob
D'Arrigo, Roseanne
Towards new weather and climate baselines for assessing weather and climate extremes, impacts, and risks
description Initiatives to recover (sourcing, imaging, digitizing) historic datasets for generating more accurate longterm climate models have only gained momentum over the last decade, despite a long precedent of compelling arguments as to the value of historic weather observations (Le Roy Ladurie, 1972; Lamb, 1977). Although such work is relatively well established in Europe, the United States, China, and Japan; Southeast Asia currently has a dearth of data rescue initiatives with a long historical focus. The reasons behind this include a perception of the paucity of surviving data; the scattered nature of data due to shifts between colonial rule and independence and, later regime changes; a lack of local resources to develop data recovery projects. By way of example, the Southeast Asian Climate Assessment & Dataset (SACA&D) Digitisasi Data Historis (DiDaH) project, now completed, was limited by the fact that the bulk of observations recovered and digitized were in the post 1940s-50s period (apart from Indonesia in the South East Asian region) and, their data rescue was directed at National Meteorological Service (NMS) records only, with generally a heavy focus on temperature and precipitation data. ACRE SEA has a wider scope, with a longer historical timeframe (especially with a pre 1940s-50s observations focus) and broader record collection base, using archives, libraries, and online sources across the region and internationally. In fact, the SACA&D DiDaH project.
format text
author WILLIAMSON, Fiona
ALLAN, Rob
D'Arrigo, Roseanne
author_facet WILLIAMSON, Fiona
ALLAN, Rob
D'Arrigo, Roseanne
author_sort WILLIAMSON, Fiona
title Towards new weather and climate baselines for assessing weather and climate extremes, impacts, and risks
title_short Towards new weather and climate baselines for assessing weather and climate extremes, impacts, and risks
title_full Towards new weather and climate baselines for assessing weather and climate extremes, impacts, and risks
title_fullStr Towards new weather and climate baselines for assessing weather and climate extremes, impacts, and risks
title_full_unstemmed Towards new weather and climate baselines for assessing weather and climate extremes, impacts, and risks
title_sort towards new weather and climate baselines for assessing weather and climate extremes, impacts, and risks
publisher Institutional Knowledge at Singapore Management University
publishDate 2017
url https://ink.library.smu.edu.sg/cis_research/227
https://ink.library.smu.edu.sg/context/cis_research/article/1226/viewcontent/11_CBA2014_01_pvoa_cc_by.pdf
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