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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Estimation of the absolute surface air temperature of the Earth

Journal of Geophysical Research Atmospheres (2013)

P. D. Jones Colin Harpham

Average temperatures for the hemispheres and the globe are generally expressed as anomalies from a base period. Most users of these data and the underlying constituent gridded datasets do not require the values in absolute degrees, but a number of users might require this additional detail. An example group of users are climate modellers, who want to directly compare their simulations with reality in absolute units. Reanalysis datasets offer opportunities of assessing earlier absolute temperature estimates, but until recently their quality over data‐sparse regions of the world was questionable. Here, we assess the latest Reanalysis (ERA‐Interim) which is available from 1979 to the present against earlier direct estimates. Globally averaged ERA‐Interim and the earlier direct estimates of absolute surface temperatures across the world are about 0.55°C different for the 1981–2010 period, with ERA‐Interim cooler. The difference is only 0.29°C for the Northern Hemisphere, but larger at 0.81°C for the Southern Hemisphere. Spatially, the largest differences come from the Polar Regions, particularly the Antarctic.

Interim

Absolute (philosophy)

Globe

Mean absolute error

10.1002/jgrd.50359

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Citations (26)

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

Climate Research (2011)

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

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Simulating climate change in UK cities using a regional climate model, HadRM3

International Journal of Climatology (2011)

Mark McCarthy Colin Harpham C. M. Goodess P. D. Jones

Abstract A regional climate model (RCM) at 25 km resolution, coupled to a simple urban land‐surface scheme has been used to assess the sensitivity of UK urban climates to large‐scale greenhouse gas (GHG) induced climate change, local forcing from urban land use, and anthropogenic heat flux (AHF) resulting from energy use in urban areas. GHG‐induced climate change is similar over both urban and rural land surfaces in the model, suggesting that under a changing climate the relative magnitude of urban heat islands in the UK would remain the same. However, indirect effects from urbanisation or changes in energy consumption within UK cities would contribute to further localized anthropogenic climate change that can be quantified by this model. The presence of the urban heat island also has a significant impact on the frequency of extreme high temperatures both in present and future climates, and will exacerbate the impact of climate change on the urban population. The simple urban land‐surface exchange scheme is a cost effective additional component of the RCM. It is shown to provide a realistic city‐scale urban heat island responding to the dynamical weather of the model at every model time‐step, with a magnitude and variability comparable to observed values. The climate model provides long integrations to derive large samples of heat islands under a full range of simulated dynamical conditions, and in this study sampling more than 100 years of climate change. Copyright © 2011 Royal Meteorological Society and British Crown copyright, the Met Office

Urban Heat Island

Urban climatology

Transient climate simulation

Climate commitment

Land Cover

Forcing (mathematics)

10.1002/joc.2402

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Citations (60)

Past and Projected Weather Pattern Persistence with Associated Multi-Hazards in the British Isles

Atmosphere (2019)

Paolo De Luca Colin Harpham Robert L. Wilby John K. Hillier Christian Franzke

Hazards such as heatwaves, droughts and floods are often associated with persistent weather patterns. Atmosphere-Ocean General Circulation Models (AOGCMs) are important tools for evaluating projected changes in extreme weather. Here, we demonstrate that 2-day weather pattern persistence, derived from the Lamb Weather Types (LWTs) objective scheme, is a useful concept for both investigating climate risks from multi-hazard events as well as for assessing AOGCM realism. This study evaluates the ability of a Coupled Model Intercomparison Project Phase 5 (CMIP5) multi-model sub-ensemble of 10 AOGCMs at reproducing seasonal LWTs persistence and frequencies over the British Isles (BI). Changes in persistence are investigated under two Representative Concentration Pathways (RCP8.5 and RCP4.5) up to 2100. The ensemble broadly replicates historical LWTs persistence observed in reanalyses (1971–2000). Future persistence and frequency of summer anticyclonic LWT are found to increase, implying heightened risk of drought and heatwaves. On the other hand, the cyclonic LWT decreases in autumn suggesting reduced likelihood of flooding and severe gales. During winter, AOGCMs point to increased risk of concurrent fluvial flooding-wind hazards by 2100, however, they also tend to over-estimate such risks when compared to reanalyses. In summer, the strength of the nocturnal Urban Heat Island (UHI) of London could intensify, enhancing the likelihood of combined heatwave-poor air quality events. Further research is needed to explore other multi-hazards in relation to changing weather pattern persistence and how best to communicate such threats to vulnerable communities.

Persistence (discontinuity)

Representative Concentration Pathways

Extreme Weather

Natural hazard

Anticyclone

Weather patterns

10.3390/atmos10100577

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Citations (15)

Long‐term trends in precipitation and temperature across the Caribbean

International Journal of Climatology (2015)

P. D. Jones Colin Harpham Ian Harris C. M. Goodess Aidan Burton

ABSTRACT This study considers long‐term precipitation and temperature variability across the Caribbean using two gridded data sets ( CRU TS 3.21 and GPCCv5 ). We look at trends across four different regions (Northern, Eastern, Southern and Western), for three different seasons (May to July, August to October and November to April) and for three different periods (1901–2012, 1951–2012 and 1979–2012). There are no century‐long trends in precipitation in either data set, although all regions (with the exception of the Northern Caribbean) show decade‐long periods of wetter or drier conditions. The most significant of these is for the Southern Caribbean region which was wetter than the 1961–1990 average from 1940 to 1956 and then drier from 1957 to 1965. Temperature in contrast shows statistically significant warming everywhere for the periods 1901–2012, 1951–2012 and for over half the area during 1979–2012. Data availability is a limiting issue over much of the region and we also discuss the reliability of the series we use in the context of what is known to be available in the CRU TS 3.21 data set. More station data have been collected but have either not been fully digitized yet or not made freely available both within and beyond the region.

Cru

Limiting

10.1002/joc.4557

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Application of a stochastic weather generator to assess climate change impacts in a semi-arid climate: The Upper Indus Basin

Journal of Hydrology (2014)

Nathan Forsythe Hayley J. Fowler Stephen Blenkinsop A. Burton Chris Kilsby

Assessing local climate change impacts requires downscaling from Global Climate Model simulations. Here, a stochastic rainfall model (RainSim) combined with a rainfall conditioned weather generator (CRU WG) have been successfully applied in a semi-arid mountain climate, for part of the Upper Indus Basin (UIB), for point stations at a daily time-step to explore climate change impacts. Validation of the simulated time-series against observations (1961–1990) demonstrated the models' skill in reproducing climatological means of core variables with monthly RMSE of <2.0 mm for precipitation and ⩽0.4 °C for mean temperature and daily temperature range. This level of performance is impressive given complexity of climate processes operating in this mountainous context at the boundary between monsoonal and mid-latitude (westerly) weather systems. Of equal importance the model captures well the observed interannual variability as quantified by the first and last decile of 30-year climatic periods. Differences between a control (1961–1990) and future (2071–2100) regional climate model (RCM) time-slice experiment were then used to provide change factors which could be applied within the rainfall and weather models to produce perturbed 'future' weather time-series. These project year-round increases in precipitation (maximum seasonal mean change:+27%, annual mean change: +18%) with increased intensity in the wettest months (February, March, April) and year-round increases in mean temperature (annual mean +4.8 °C). Climatic constraints on the productivity of natural resource-dependent systems were also assessed using relevant indices from the European Climate Assessment (ECA) and indicate potential future risk to water resources and local agriculture. However, the uniformity of projected temperature increases is in stark contrast to recent seasonally asymmetrical trends in observations, so an alternative scenario of extrapolated trends was also explored. We conclude that interannual variability in climate will continue to have the dominant impact on water resources management whichever trajectory is followed. This demonstrates the need for sophisticated downscaling methods which can evaluate changes in variability and sequencing of events to explore climate change impacts in this region.

Cru

HadCM3

Mean radiant temperature

10.1016/j.jhydrol.2014.06.031

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Citations (66)

A daily weather generator for use in climate change studies

Environmental Modelling & Software (2007)

Chris Kilsby P. D. Jones A. Burton Alistair Ford Hayley J. Fowler

10.1016/j.envsoft.2007.02.005

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Citations (466)

Comparing correction methods of RCM outputs for improving crop impact projections in the Iberian Peninsula for 21st century

Climatic Change (2015)

Margarita Ruiz‐Ramos Alfredo Rodríguez Alessandro Dosio C. M. Goodess Colin Harpham

Orography

Impact assessment

Crop simulation model

Peninsula

10.1007/s10584-015-1518-8

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Citations (33)

Perturbing a Weather Generator using change factors derived from Regional Climate Model simulations

Nonlinear processes in geophysics (2011)

P. D. Jones Colin Harpham C. M. Goodess Chris Kilsby

Abstract. The purpose of this paper is to provide a method for perturbing Weather Generators (WGs) for future decades and to assess its effectiveness. Here the procedure is applied to the WG implemented within the UKCP09 package and assessed using data from a Regional Climate Model (RCM) simulation which provides a significant "climate change" between a control run period and a distant future. The WG is normally calibrated on observed data. For this study, data from an RCM control period (1961–1990) was used, then perturbed using the procedure. Because only monthly differences between the RCM control and scenario periods are used to perturb the WG, the direct daily RCM scenario may be considered as unseen data to assess how well the perturbation procedure reproduces the direct RCM simulations for the future.

10.5194/npg-18-503-2011

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How climate data can help improve planning within the wind sector

HAL (Le Centre pour la Communication Scientifique Directe) (2016)

Alberto Troccoli Colin Harpham P. D. Jones Lucien Wald Thierry Ranchin

The Copernicus Earth Observation Programme is a €4 billion project funded by the European Union providing free data and tools to understand environmental change. This abstract outlines how the European Climatic Energy Mixes (ECEM) project, a pilot project of the Copernicus Climate Change Service (C3S), one of six Copernicus services, is using climate data from the programme to support the wind industry. Approach The Copernicus Programme is a global network of thousands of land, air and marine based sensors, as well as a family of dedicated satellites, making millions of observations a day to build a comprehensive picture of the Earth’s climate. C3S will combine observations of the climate system with the latest science to develop authoritative, quality-assured information about the past, current and future states of the climate in Europe and worldwide. Proof of concepts such as the ECEM are using this data to deve lop demonstrators, as part of the C3S pilot projects, to enable the wind industry to plan for and adapt to Europe’s changing climate. Main body of abstract The ability to use data from thousands of global sensors has a wide range of applications, from identifying prime locations for new wind turbine developments to mitigating climate risk by understanding how windstorms could impact the industry. C3S will help provide innovative solutions to challenges within the industry; in particular how to forecast wind yield and identify viable opportunities for wind development and storage investment within Europe’s generation mix. ECEM is a proof of concept climate service that is working to enable the energy industry and policy makers to assess how different energy supply mixes in Europe will meet demand over different time horizons, from seasonal to long-term planning spanning decades. By assessing the uncertainty of seasonal climate forecasts and projections, ECEM will inform climate-sensitive energy projects, such as wind, about their production under varying climate conditions and how they would meet demand at the European scale under differing energy generation scenarios. The presentation presents an assessment of wind speed and power as produced by essential historical datasets called reanalyses taking many wind speed measurements, including tower data, as reference. Two scaling methods are compared to calibrate the reanalysis, for both on-shore and offshore locations. This calibration is a key first step to providing a benchmark for climate model data such as climate forecasts and projections. An assessment of the physical coherence/co-variability between calibrated wind speed and other climate variables, such as solar radiation, is also carried out to achieve an optimal spatial and temporal co-variability, which is critical when attempting to achieve a balanced energy supply. Conclusion Harnessing data is integral to the future of the wind industry, from identifying the best locations to place turbines and target investment to ensuring that projects and infrastructure are sustainable as Europe’s climate continues to change. The calibration of wind speed as produced by a widely used re-analysis product, ERA-Interim, as the basis wind resource assessments, is discussed with this presentation. Many measurement stations, both on-shore and offshore, are used for this calibration. This work is also important in pointing to the dominant climate drivers influencing overall supply-demand balance at both national and continental scales, such as in the case of winter-time North Atlantic Oscillation, which can have a profound influence on wind power. The outcomes of ECEM’s work can help provide methods for the wind industry to plan its long-term future. Learning objectives • The ways in which energy supply and demand over Europe are affected by the spatial and temporal variations of their climate drivers; • How climate modelling can enable the wind industry to target development and investment.

Copernicus

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