Jones, Prof. Philip Douglas, (born 22 April 1952), Professor, since 1998, and Director, since 2003, Climatic Research Unit, School of Environmental Sciences, University of East Anglia

2007 ◽  
Keyword(s):  
Research Unit ◽  
Climatic Research Unit ◽  
Environmental Sciences ◽  
East Anglia

Economical exposition to drought events (1980-2001)

2017 ◽  
Author(s):  
Chloé Meyer
Keyword(s):  
World Bank ◽  
Standardized Precipitation Index ◽  
Research Unit ◽  
Precipitation Index ◽  
Climatic Research Unit ◽  
Columbia University ◽  
East Anglia ◽  
Gis Modeling ◽  
The World Bank ◽  
Year 2000

Estimation of the annual economical exposition to drought based on Standardized Precipitation Index. It is based on three sources: 1) A global monthly gridded precipitation dataset obtained from the Climatic Research Unit (University of East Anglia). 2) A GIS modeling of global Standardized Precipitation Index based on Brad Lyon (IRI, Columbia University) methodology. 3) A Global Domestic Product grid for the year 2010, provided by the World Bank. Unit is expected average annual GDP (2007 as the year of reference) exposed in (US $, year 2000 equivalent). For more information, visit: http://preview.grid.unep.ch/ Cost Drought Exposure Risk

Transitions between dry and wet periods in Europe during 1950–2019

2021 ◽  
Author(s):  
Zuzana Bestakova ◽  
Petr Maca ◽  
Jan Kysely ◽  
Ujjwal Singh ◽  
Yannis Markonis ◽  
...  
Keyword(s):  
Potential Evapotranspiration ◽  
Aridity Index ◽  
Research Unit ◽  
Climatic Research Unit ◽  
Energy Availability ◽  
East Anglia ◽  
Weather Forecasts ◽  
Humid Environment ◽  
Medium Range ◽  
Dry Conditions

<p>The study deals with probabilities of transitions from arid to humid environment and vice versa in<br>Europe. Aridity index, defined as a ratio of potential evapotranspiration and precipitation and<br>representing the ratio between energy availability and water availability, is used to characterize humid<br>(wet) and arid (dry) regions and allows us to study transitions between individual periods (wet-wet,<br>wet-dry, dry-dry, dry-wet). Three gridded datasets – CRU (UEA, 2020), E-OBS (ECAD, 2020) and ERA5<br>(ECMWF, 2020) – are used for this purpose. The aim of the study is to compare the three datasets as<br>to transitions between wet and dry conditions, which are determined according to the aridity index,<br>and evaluate the variability in Europe over 1950–2019. The changes in the aridity index since 1950 are<br>found to be most pronounced in Northern and Central Europe.</p><p><br>references:<br>ECAD, 2020: E-OBS gridded dataset, available from<br><https://www.ecad.eu/download/ensembles/download.php>.<br>UEA, 2020: University of East Anglia – Climatic Research Unit, available from<br><https://lr1.uea.ac.uk/cru/data>.<br>ECMWF, 2020: European Centre for Medium-Range Weather Forecasts – ERA5, available from<br><https://www.ecmwf.int/en/forecasts/datasets/reanalysis-datasets/era5>.</p>

scholarly journals Discontinuous Daily Temperatures in the WATCH Forcing Datasets

2015 ◽  
Vol 16 (1) ◽  
pp. 465-472 ◽  
Author(s):  
Henning W. Rust ◽  
Tim Kruschke ◽  
Andreas Dobler ◽  
Madlen Fischer ◽  
Uwe Ulbrich
Keyword(s):  
Land Surface ◽  
Water Cycle ◽  
Research Unit ◽  
Climatic Research Unit ◽  
Daily Maximum ◽  
Monthly Means ◽  
Tropical Africa ◽  
Average Temperature ◽  
Surface Models ◽  
The Tropics

Abstract The Water and Global Change (WATCH) forcing datasets have been created to support the use of hydrological and land surface models for the assessment of the water cycle within climate change studies. They are based on 40-yr ECMWF Re-Analysis (ERA-40) or ECMWF interim reanalysis (ERA-Interim) with temperatures (among other variables) adjusted such that their monthly means match the monthly temperature dataset from the Climatic Research Unit. To this end, daily minimum, maximum, and mean temperatures within one calendar month have been subjected to a correction involving monthly means of the respective month. As these corrections can be largely different for adjacent months, this procedure potentially leads to implausible differences in daily temperatures across the boundaries of calendar months. We analyze day-to-day temperature fluctuations within and across months and find that across-months differences are significantly larger, mostly in the tropics and frigid zones. Average across-months differences in daily mean temperature are typically between 10% and 40% larger than their corresponding within-months average temperature differences. However, regions with differences up to 200% can be found in tropical Africa. Particularly in regions where snowmelt is a relevant player for hydrology, a few degrees Celsius difference can be decisive for triggering this process. Daily maximum and minimum temperatures are affected in the same regions, but in a less severe way.

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