Now showing 1 - 3 of 3
  • Publication
    A high-resolution, multi-model analysis of Irish temperatures for the mid-21st century
    There is a paucity of dynamically downscaled climate model output at a high resolution over Ireland, of temperature projections for the mid-21st century. This study aims to address this shortcoming. A preliminary investigation of global climate model (GCM) data and high-resolution regional climate model (RCM) data shows that the latter exhibits greater variability over Ireland by reducing the dominance of the surrounding seas on the climate signal. This motivates the subsequent dynamical downscaling and analysis of the temperature output from three high-resolution (4–7 km grid size) RCMs over Ireland. The three RCMs, driven by four GCMs from CMIP3 and CMIP5, were run under different Special Report on Emissions Scenarios (SRES) and representative concentration pathway (RCP) future scenarios. Projections of mean and extreme temperature changes are considered for the mid-century (2041–2060) and assessed relative to the control period of 1981–2000. Analysis of the RCM data shows that annual mean temperatures are projected to rise between 0.4 and 1.8 °C above control levels by mid-century. On a seasonal basis, results differ by forcing scenario. Future summers have the largest projected warming under RCP 8.5, where the greatest warming is seen in the southeast of Ireland. The remaining two high emission scenarios (SRESs A1B and A2) project future winters to have the greatest warming, with almost uniform increases of 1.5–2 °C across the island. Changes in the bidecadal 5th and 95th percentile values of daily minimum and maximum temperatures, respectively, are also analysed. The greatest change in daily minimum temperature is projected for future winters (indicating fewer cold nights and frost days), a pattern that is consistent across all scenarios/forcings. An investigation into the distribution of temperature under RCP 8.5 shows a strong summer increase compounded by increased variability, and a winter increase compounded by an increase in skewness.
    Scopus© Citations 11  559
  • Publication
    Ensemble of regional climate model projections for Ireland
    (Environmental Protection Agency (EPA), 2015)
    The method of Regional Climate Modelling (RCM) was employed to assess the impacts of a warming climate on the mid-21st-century climate of Ireland. The RCM simulations were run at high spatial resolution, up to 4 km, thus allowing a better evaluation of the local effects of climate change. Simulations were run for a reference period 1981–2000 and future period 2041–2060. Differences between the two periods provide a measure of climate change. To address the issue of uncertainty, a multi-model ensemble approach was employed. Specifically, the future climate of Ireland was simulated using three different RCMs, driven by four Global Climate Models (GCMs). To account for the uncertainty in future emissions, a number of SRES (B1, A1B, A2) and RCP (4.5, 8.5) emission scenarios were used to simulate the future climate. Through the ensemble approach, the uncertainty in the RCM projections can be partially quantified, thus providing a measure of confidence in the predictions. In addition, likelihood values can be assigned to the projections. The RCMs used in this work are the COnsortium for Small-scale MOdeling–Climate Limited-area Modelling (COSMO-CLM, versions 3 and 4) model and the Weather Research and Forecasting (WRF) model. The GCMs used are the Max Planck Institute’s ECHAM5, the UK Met Office’s HadGEM2-ES, the CGCM3.1 model from the Canadian Centre for Climate Modelling and the EC-Earth consortium GCM. The projections for mid-century indicate an increase of 1–1.6°C in mean annual temperatures, with the largest increases seen in the east of the country. Warming is enhanced for the extremes (i.e. hot or cold days), with the warmest 5% of daily maximum summer temperatures projected to increase by 0.7–2.6°C. The coldest 5% of night-time temperatures in winter are projected to rise by 1.1–3.1°C. Averaged over the whole country, the number of frost days is projected to decrease by over 50%. The projections indicate an average increase in the length of the growing season of over 35 days per year. Results show significant projected decreases in mean annual, spring and summer precipitation amounts by mid-century. The projected decreases are largest for summer, with 'likely' reductions ranging from 0% to 20%. The frequencies of heavy precipitation events show notable increases (approximately 20%) during the winter and autumn months. The number of extended dry periods is projected to increase substantially during autumn and summer. Regional variations of projected precipitation change remain statistically elusive. The energy content of the wind is projected to significantly decrease for the future spring, summer and autumn months. Projected increases for winter were found to be statistically insignificant. The projected decreases were largest for summer, with 'likely' values ranging from 3% to 15%. Results suggest that the tracks of intense storms are projected to extend further south over Ireland relative to those in the reference simulation. As extreme storm events are rare, the storm-tracking research needs to be extended. Future work will focus on analysing a larger ensemble, thus allowing a robust statistical analysis of extreme storm track projections.
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  • Publication
    Reducing errors of wind speed forecasts by an optimal combination of post-processing methods
    (Wiley-Blackwell, 2011-09-13) ; ;
    Seven adaptive approaches to post-processing wind speed forecasts are discussed and compared. 48-hour forecasts are run at horizontal resolutions of 7 km and 3 km for a domain centred over Ireland. Forecast wind speeds over a two year period are compared to observed wind speeds at seven synoptic stations around Ireland and skill scores calculated. Two automatic methods for combining forecast streams are applied. The forecasts produced by the combined methods give bias and root mean squared errors that are better than the numerical weather prediction forecasts at all station locations. One of the combined forecast methods results in skill scores that are equal to or better than all of its component forecast streams. This method is straightforward to apply and should prove beneficial in operational wind forecasting.
    Scopus© Citations 58  975