Colin Harpham

University of East Anglia

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P. D. Jones

The University of Texas MD Anderson Cancer Center

C. M. Goodess

University of East Anglia

Robert L. Wilby

Loughborough University

Hayley J. Fowler

Newcastle University

A. Burton

University of Newcastle Australia

Stephen Blenkinsop

Newcastle University

David Lister

Vodafone (United Kingdom)

Chris Kilsby

Newcastle University

Gregor C. Leckebusch

University of Birmingham

Christian Franzke

Pusan National University

Cooperative Institutions

University of East Anglia

Newcastle University

Norwich Research Park

Tyndall Centre

Instituto de Meteorología

University of Newcastle Australia

University of Castilla-La Mancha

Finnish Environment Institute

University of Oxford

Met Office

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A multi-model ensemble of downscaled spatial climate change scenarios for the Dommel catchment, Western Europe

Climatic Change (2011)

Michelle T. H. van Vliet Stephen Blenkinsop Aidan Burton Colin Harpham Hans Peter Broers

10.1007/s10584-011-0131-8

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Citations (17)

Downscaling regional climate model outputs for the Caribbean using a weather generator

International Journal of Climatology (2016)

P. D. Jones Colin Harpham A. Burton C. M. Goodess

ABSTRACT Locally relevant scenarios of daily weather variables that represent the best knowledge of the present climate and projections of future climate change are needed by planners and managers to inform management and adaptation to climate change decisions. Information of this kind for the future is only readily available for a few developed country regions of the world. For many less‐developed regions, it is often difficult to find series of observed daily weather data to assist in planning decisions. This study applies a previously developed single‐site weather generator ( WG ) to the Caribbean, using examples from Belize in the west to Barbados in the east. The purpose of this development is to provide users in the region with generated sequences of possible future daily weather that they can use in a number of impact sectors. The WG is first calibrated for a number of sites across the region and the goodness of fit of the WG against the daily station observations assessed. Particular attention is focussed on the ability of the precipitation component of the WG to generate realistic extreme values for the calibration or control period. The WG is then modified using change factors ( CFs ) derived from regional climate model projections (control and future) to simulate future 30‐year scenarios centred on the 2020s, 2050s and 2080s. Changes between the control period and the three futures are illustrated not just by changes in average temperatures and precipitation amounts but also by a number of well‐used measures of extremes (very warm days/nights, the heaviest 5‐day precipitation total in a month, counts of the number of precipitation events above specific thresholds and the number of consecutive dry days).

10.1002/joc.4624

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Citations (16)

The development of Lamb weather types: from subjective analysis of weather charts to objective approaches using reanalyses

Weather (2014)

P. D. Jones Timothy J. Osborn Colin Harpham Keith R. Briffa

10.1002/wea.2255

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Citations (28)

Evaluation of artificial neural network techniques for flow forecasting in the River Yangtze, China

Hydrology and earth system sciences (2002)

Christian W. Dawson Colin Harpham Robert L. Wilby Y. Chen

Abstract. While engineers have been quantifying rainfall-runoff processes since the mid-19th century, it is only in the last decade that artificial neural network models have been applied to the same task. This paper evaluates two neural networks in this context: the popular multilayer perceptron (MLP), and the radial basis function network (RBF). Using six-hourly rainfall-runoff data for the River Yangtze at Yichang (upstream of the Three Gorges Dam) for the period 1991 to 1993, it is shown that both neural network types can simulate river flows beyond the range of the training set. In addition, an evaluation of alternative RBF transfer functions demonstrates that the popular Gaussian function, often used in RBF networks, is not necessarily the ‘best’ function to use for river flow forecasting. Comparisons are also made between these neural networks and conventional statistical techniques; stepwise multiple linear regression, auto regressive moving average models and a zero order forecasting approach. Keywords: Artificial neural network, multilayer perception, radial basis function, flood forecasting

Flood forecasting

Multilayer perceptron

Perceptron

Yangtze river

10.5194/hess-6-619-2002

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Citations (112)

Downscaling transient climate change with a stochastic weather generator for the Geer catchment, Belgium

Climate Research (2013)

Stephen Blenkinsop Colin Harpham A. Burton Pascal Goderniaux Serge Brouyère

CR Climate Research Contact the journal Facebook Twitter RSS Mailing List Subscribe to our mailing list via Mailchimp HomeLatest VolumeAbout the JournalEditorsSpecials CR 57:95-109 (2013) - DOI: https://doi.org/10.3354/cr01170 Downscaling transient climate change with a stochastic weather generator for the Geer catchment, Belgium S. Blenkinsop1,*, C. Harpham2, A. Burton1, P. Goderniaux3, S. Brouyère4, H. J. Fowler1 1Water Resource Systems Research Laboratory, School of Civil Engineering and Geosciences, Newcastle University, Cassie Building, Newcastle upon Tyne NE1 7RU, UK 2Climatic Research Unit, School of Environmental Sciences, University of East Anglia, Norwich NR47TJ, UK 3Geology and Applied Geology, University of Mons, 7000 Mons, Belgium 4Group of Hydrogeology and Environmental Geology—Aquapôle, University of Liège, 4000 Liège, Belgium *Email: stephen.blenkinsop@ncl.ac.uk ABSTRACT: The coarse resolution of climate models creates the need for future scenarios which are downscaled to an appropriate spatial scale. Considerable effort has been devoted to the development of downscaling methods, but a number of important issues remain to meet users' needs. These include the assessment of uncertainty for future scenarios, and the production of scenarios at time scales relevant to stakeholders. This paper describes a methodology which addresses these issues by producing a multi-model ensemble of transient climate-change scenarios. The method couples an existing stochastic rainfall model to a new, transient implementation of a weather generator, using changes projected by an ensemble of regional climate model experiments. The methodology is demonstrated by the generation of transient scenarios of daily rainfall, temperature and potential evapotranspiration for the Geer catchment in Belgium for the period 2010-2085. The utility of these scenarios is demonstrated by assessing the changes projected by the simulated time series of several temperature indices. The Geer is projected to experience a decrease in the occurrence of frost days with a corresponding shortening of the frost season and lengthening of the growing season. By examining an ensemble of transient scenarios, the range of uncertainty in these projections is assessed, but, further, it is suggested that additional information on the projected timing of specified threshold events or system responses may be provided. This could aid stakeholders in assessing the likely time scales of required interventions and adaptation responses. KEY WORDS: Climate change · Transient scenarios · Weather generator · Downscaling · RCMs Full text in pdf format NextCite this article as: Blenkinsop S, Harpham C, Burton A, Goderniaux P, Brouyère S, Fowler HJ (2013) Downscaling transient climate change with a stochastic weather generator for the Geer catchment, Belgium. Clim Res 57:95-109. https://doi.org/10.3354/cr01170 Export citation RSS - Facebook - Tweet - linkedIn Cited by Published in CR Vol. 57, No. 2. Online publication date: August 20, 2013 Print ISSN: 0936-577X; Online ISSN: 1616-1572 Copyright © 2013 Inter-Research.

Transient (computer programming)

10.3354/cr01170

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Citations (15)

Downscaling heavy precipitation over the United Kingdom: a comparison of dynamical and statistical methods and their future scenarios

International Journal of Climatology (2006)

M. R. Haylock Gavin C. Cawley Colin Harpham Robert L. Wilby C. M. Goodess

Abstract Six statistical and two dynamical downscaling models were compared with regard to their ability to downscale seven seasonal indices of heavy precipitation for two station networks in northwest and southeast England. The skill among the eight downscaling models was high for those indices and seasons that had greater spatial coherence. Generally, winter showed the highest downscaling skill and summer the lowest. The rainfall indices that were indicative of rainfall occurrence were better modelled than those indicative of intensity. Models based on non‐linear artificial neural networks were found to be the best at modelling the inter‐annual variability of the indices; however, their strong negative biases implied a tendency to underestimate extremes. A novel approach used in one of the neural network models to output the rainfall probability and the gamma distribution scale and shape parameters for each day meant that resampling methods could be used to circumvent the underestimation of extremes. Six of the models were applied to the Hadley Centre global circulation model HadAM3P forced by emissions according to two SRES scenarios. This revealed that the inter‐model differences between the future changes in the downscaled precipitation indices were at least as large as the differences between the emission scenarios for a single model. This implies caution when interpreting the output from a single model or a single type of model (e.g. regional climate models) and the advantage of including as many different types of downscaling models, global models and emission scenarios as possible when developing climate‐change projections at the local scale. Copyright © 2006 Royal Meteorological Society

Resampling

10.1002/joc.1318

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Citations (357)

Long‐term trends in gale days and storminess for the Falkland Islands

International Journal of Climatology (2015)

P. D. Jones Colin Harpham David Lister

ABSTRACT Weather typing, based on surface pressure charts, has been one of the principal means of analysis in synoptic climatology. Here, we use an automated scheme to derive weather types ( WTs ) and also calculate Lamb weather types ( LWTs ) for the Falkland Islands. The WTs are based on sea‐level pressure data estimated using two reanalysis products: one that extends from 1948 to 2014 and another that just uses station pressure data as input and extends back to 1871. The WTs can be used to derive counts of gale days and these will be compared with storminess estimates based on the rate of change of daily‐average pressure measurements at the principal observational site (near the capital, Port Stanley) on the islands. A particular emphasis of the paper is the reliability of the results taking into account that we are using reanalysis datasets from a very data‐sparse region of the world. More gale days are estimated during the period from about 1880 to the mid‐1910s and since the 1980s. Fewer gale days are evident during other periods, particularly from the mid‐1910s to 1947. As these changes are not evident in the storminess measure derived from the sub‐daily pressure series for the Port Stanley region, the results in terms of gale‐day counts are very suggestive of being due to differences in the quality of the reanalysis during the different periods. The reanalysis appears better the higher the number of gale days estimated. The opening of the Panama Canal in 1914 dramatically reduced the number of ships, and hence observations, rounding Cape Horn. The paper also relates seasonal counts of the LWTs and WTs to recently developed long series of temperature and precipitation for the Port Stanley region.

10.1002/joc.4434

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Citations (21)

Winter‐responding proxy temperature reconstructions and the North Atlantic Oscillation

Journal of Geophysical Research Atmospheres (2014)

P. D. Jones Colin Harpham Bo Vinther

Abstract Instrumental temperature data for the Northern Hemisphere (30°–90°N) clearly indicate that winter season variability is larger than equivalent measures for summer. This should not be surprising as temperatures in winter are dominated by variability caused by changes in atmospheric circulation features, whereas in summer variability is more dominated by local changes in cloudiness. Here we consider most of the few winter‐responding annually resolved proxy reconstructions of temperature from the northern North Atlantic and northwestern European regions. We find the expected out‐of‐phase relationship between northwest Europe and Greenland due to the North Atlantic Oscillation (NAO), which is stronger when the series from the two locations are formed from more than one series. On 30 year time scales this relationship between the two locations shows no century‐scale variations since 1250 CE (Common Era), the start of our reconstructions, in contrast to the strong positive NAO values before 1400 CE implied by the study of Trouet et al. (2009).

Proxy (statistics)

Atmospheric Circulation

10.1002/2014jd021561

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Citations (15)

Hemispheric and large‐scale land‐surface air temperature variations: An extensive revision and an update to 2010

Journal of Geophysical Research Atmospheres (2012)

P. D. Jones David Lister Timothy J. Osborn Colin Harpham M. Salmon

This study is an extensive revision of the Climatic Research Unit (CRU) land station temperature database that has been used to produce a grid‐box data set of 5° latitude × 5° longitude temperature anomalies. The new database (CRUTEM4) comprises 5583 station records of which 4842 have enough data for the 1961–1990 period to calculate or estimate the average temperatures for this period. Many station records have had their data replaced by newly homogenized series that have been produced by a number of studies, particularly from National Meteorological Services (NMSs). Hemispheric temperature averages for land areas developed with the new CRUTEM4 data set differ slightly from their CRUTEM3 equivalent. The inclusion of much additional data from the Arctic (particularly the Russian Arctic) has led to estimates for the Northern Hemisphere (NH) being warmer by about 0.1°C for the years since 2001. The NH/Southern Hemisphere (SH) warms by 1.12°C/0.84°C over the period 1901–2010. The robustness of the hemispheric averages is assessed by producing five different analyses, each including a different subset of 20% of the station time series and by omitting some large countries. CRUTEM4 is also compared with hemispheric averages produced by reanalyses undertaken by the European Centre for Medium‐Range Weather Forecasts (ECMWF): ERA‐40 (1958–2001) and ERA‐Interim (1979–2010) data sets. For the NH, agreement is good back to 1958 and excellent from 1979 at monthly, annual, and decadal time scales. For the SH, agreement is poorer, but if the area is restricted to the SH north of 60°S, the agreement is dramatically improved from the mid‐1970s.

Cru

Longitude

10.1029/2011jd017139

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Citations (841)

Lamb weather types derived from reanalysis products

International Journal of Climatology (2012)

P. D. Jones Colin Harpham Keith R. Briffa

Abstract Weather typing, based on surface pressure charts, has been one of the principal means of analysis in synoptic climatology. Here, we summarize the history of manual and automated schemes, in the northwest European context, illustrating how the approaches can take advantage of the extended reanalysis products that have recently become available. The British Isles and the associated Lamb weather types (LWTs) are the focus of this study, but the approach can be applied to any mid‐to‐high latitude region to provide series back to 1871. However, caution is advised in the use of the approach where the quality and quantity of input data into the extended reanalysis are known to be temporally and spatially variable and/or poor in early years. This study intercompares the use of automated schemes with operational analyses, reanalyses and earlier manually derived LWTs. Copyright © 2012 Royal Meteorological Society

10.1002/joc.3498

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Citations (179)