Rowan Fealy

Evaluation of the Sensitivity of the Weather Research and Forecasting Model to Parameterization Schemes for Regional Climates of Europe over the Period 1990–95

AbstractThe Weather Research and Forecasting model (WRF) is used to downscale interim ECMWF Re-Analysis (ERA-Interim) data for the climate over Europe for the period 1990–95 with grid spacing of 0.44° for 12 combinations of physical parameterizations. Two longwave radiation schemes, two land surface models (LSMs), two microphysics schemes, and two planetary boundary layer (PBL) schemes have been investigated while the remaining physics schemes were unchanged. WRF simulations are compared with Ensemble-Based Predictions of Climate Changes and their Impacts (ENSEMBLES) observations gridded dataset (E-OBS) for surface air temperatures (T2), precipitation, and mean sea level pressure (MSLP) in eight subregions within the model domain to assess the performance of the different parameterizations on widely varying regional climates. This work shows that T2 is modeled well by WRF with high correlation coefficients (0.8 < R < 0.95) and biases less than 4°C. T2 shows greatest sensitivity to land surface models, som...

Statistical downscaling of temperature, radiation and potential evapotranspiration to produce a multiple GCM ensemble mean for a selection of sites in Ireland

Abstract Irish climate is experiencing changes which have been found to be consistent with those occurring at a global scale. Consequently there is now growing confidence that these changes are largely attributable to global warming. Based on the data from four long-term monitoring, synoptic stations, between 1890 and 2004, mean annual temperatures in Ireland rose by 0.7oC. In the absence of strict emissions controls, a doubling of global atmospheric concentrations of CO2 is likely by the end of the twenty-first century. As a consequence, global temperatures are projected to increase by between 1.8oC and 4oC over the same period depending on the climate sensitivity to increased levels of greenhouse gases. In order to determine the likely impact on Irish temperatures and related climatic variables, this paper illustrates a technique for downscaling Global Climate Model (GCM) output for a selection of sites in Ireland. Results of a weighted ensemble mean, derived from multiple GCMs, are presented in an atte...

Land‐atmosphere coupling in EURO‐CORDEX evaluation experiments

The authors like to thank the coordination and the participating institutes of the EURO‐CORDEX initiative for making this study possible. The contribution from Centre de Recherche Public‐Gabriel Lippmann (labeled here as “MIUB”) (now Luxembourg Institute of Science and Technology, LIST) was funded by the Luxembourg National Research Fund (FNR) through grant FNR C09/SR/16 (CLIMPACT). The John von Neumann Institute for Computing and the Forschungszentrum Julich provided the required compute time for the project JJSC15. Work is furthermore sponsored through a research and development cooperation on hydrometeorology between the Federal Institute of Hydrology, Koblenz, Germany, and the Meteorological Institute, University of Bonn, Bonn, Germany. The KNMI‐RACMO simulation was supported by the Dutch Ministry of Infrastructure and the Environment. The simulations of the Universidad de Cantabria were supported by the CORWES project (CGL2010‐22158‐C02), funded by the Spanish R&D Programme and by the FP7 grant 308291 (EUPORIAS). We acknowledge Santander Supercomputacion support group at the University of Cantabria, who provided access to the Altamira Supercomputer at the Institute of Physics of Cantabria (IFCA‐CSIC), member of the Spanish Supercomputing Network. Rowan Fealy acknowledges the financial support provided by the Irish Environmental Protection Agency and the use of Maynooth Universitys high‐performance computer and the Irish Centre for High End Computing (ICHEC) Stokes facility. The work done by Rita M. Cardoso and Pedro M.M. Soares was financed the Portuguese Science Foundation (FCT) under Project SOLAR‐PTDC/GEOMET/7078/2014. The work of University of Hohenheim as part of the Project RU 1695 was funded by German Science Foundation (DFG). WRF‐UHOH simulations were carried out at the supercomputing center HLRS in Stuttgart (Germany). The CLMcom‐CCLM simulation was supported by the German Federal Ministry of Education and Research (BMBF) and the German Climate Computing Centre (DKRZ). AUTH‐DMC acknowledges the technical support of AUTH‐Scientific Computing Center, the HellasGrid/EGI infrastructure, and the financial support of AUTH‐Research Committee (Pr.Nr. 91376 and 87783). This work used eddy covariance data acquired by the FLUXNET community. We acknowledge the financial support to the eddy covariance data harmonization (www.fluxdata.org). The ERA‐Interim data were accessed from http://apps.ecmwf.int/datasets/. The GLEAM data were accessed from www.gleam.eu/#downloads. The analysis results and the underlying RCM data base are available upon request (sknist@uni‐bonn.de). The data are archived at the Julich Supercomputing Centre, Research Centre Julich, Julich, Germany. We thank the anonymous reviewers for their detailed and constructive comments.

Identification of frequency changes in synoptic circulation types and consequences for glacier mass balance in Norway

The cumulative net mass balances of maritime glaciers in Norway display a net surplus during the period 1963–2000. The article seeks to establish the causal mechanisms that resulted in the positive net balances occurring on Norwegian maritime glaciers. To achieve this, a Temporal Synoptic Index (TSI) was derived for a 30-year period for a number of synoptic meteorological stations in Norway. The TSI is derived using Principal Components Analysis (PCA) and subsequent clustering of component scores to classify days for both winter and summer seasons. Findings indicate that the occurrence of ‘warm’ type air masses during the summer months have increased in frequency, particularly since the late 1980s. A reduction in the frequency of ‘cold’ cluster types during the winter months is evident after this period, while the frequency of ‘warm’ types, with an increased moisture carrying capacity, has increased in frequency. The frequency occurrence of these key air mass types is shown to be significantly related to glacier mass balance during both the accumulation and ablation season. Winter air mass types from maritime source regions act to enhance accumulation and suppress ablation, while summer continental source types suppress accumulation and enhance ablation.

Future Changes in European Severe Convection Environments in a Regional Climate Model Ensemble

The occurrence of environmental conditions favorable for severe convective storms was assessed in an ensemble of 14 regional climate models covering Europe and the Mediterranean with a horizontal grid spacing of 0.448. These conditions included the collocated presence of latent instability and strong deep-layer (surface to 500 hPa) wind shear, which is conducive to the severe andwell-organized convective storms. The occurrence of precipitation in the models was used as a proxy for convective initiation. Two climate scenarios (RCP4.5 and RCP8.5) were investigated by comparing two future periods (2021–50 and 2071–2100) to a historical period (1971–2000) for each of these scenarios. The ensemble simulates a robust increase (change larger than twice the ensemble sample standard deviation) in the frequency of occurrence of unstable environments (lifted index 15 m/s) deep-layer shear were found to be small and not robust, except across far northern Europe, where a decrease in shear is projected. By the end of the century, the simultaneous occurrence of latent instability, strong deep-layer shear, andmodel precipitation is simulated to increase by up to 100% across central and eastern Europe in the RCP8.5 and by 30%–50% in the RCP4.5 scenario. Until midcentury, increases in the 10%–25%range are forecast formost regions.Alarge intermodel variability is present in the ensemble and is primarily due to the uncertainties in the frequency of the occurrence of unstable environments.

Modelling the impacts of climate change on future rates of soil erosion: Addressing key limitations

Future climate change is expected to impact the extent, frequency, and magnitude of soil erosion in a variety of ways. The most direct of these impacts is the projected increase in the erosive power of rainfall owing to an increase in the moisture-holding capacity of the atmosphere, but other more indirect impacts include changes in plant biomass and shifts in land use to accommodate the new climatic regime. Given the potential for climate change to increase soil erosion and its associated adverse impacts, modelling future rates of erosion is a crucial step in its assessment as a potential future environmental problem, and as a basis to help advise future conservation strategies. In this study, the Water Erosion Prediction Project (WEPP) model is used to simulate the impacts of climate change on future rates of soil erosion for a case study hillslope in Northern Ireland for three future time periods centered on the 2020s, 2050s and 2080s. Despite the wide range of previous modelling studies, in the majority of cases a number of limitations are apparent with respect to their treatment of the direct impacts (changed climate data), and their failure to factor in the indirect impacts (changing land use and management). In addressing the need for site-specific climate change impacts, for example, many previous studies have attempted to downscale future climate change output from general circulation models (GCMs). The most popular downscaling approach in future soil erosion studies is the change factor method, yet this approach possesses severe limitations with respect to modelling future erosion rates since it incorporates only changes in the mean climate and fails to account for climate variability. In order to address this limitation, statistical downscaling methods are used in this study to downscale future climate change projections using three GCMs and two emissions scenarios, providing daily site-specific climate inputs to WEPP in a manner that incorporates both changes in the mean climate and its variability. The temporal scale of climate change projections is also a key limitation with respect to modelling future erosion rates. The most severe soil losses often occur in high intensity rainfall events that occur over very short time intervals, yet input to soil erosion models tends to be at a daily resolution. Given the decreasing confidence of future climate change projections at a sub-daily temporal resolution, a sensitivity analysis approach is used in this study to perturb the sub-daily rainfall intensity parameter in WEPP. In addition, most previous studies fail to account for the indirect impacts of climate change on soil erosion, with no change in land use and management often assumed. Here, a scenarios-based approach is employed to examine the impacts of changing crop cover and management on future rates of soil erosion. Results indicate a mix of soil erosion increases and decreases, depending on which scenarios are considered. Downscaled climate change projections in isolation generally result in erosion decreases, whereas large increases are projected when land use is changed from the current cover of grass to a row crop which requires annual tillage, and/or where large changes in sub-daily rainfall intensity are applied. The overall findings illustrate the potential for increased soil erosion under future climate change, and illuminate the need to address key limitations in previous studies with respect to the treatment of future climate change projections, and crucially, the factoring in of future land use and management.

Deriving probabilistic based climate scenarios using pattern scaling and statistically downscaled data: A case study application from Ireland

This paper adopts a technique common in the dynamical climate modelling literature, that of pattern scaling, and applies it to previously available statistically downscaled station level data for Ireland for two climatically relevant variables, that of temperature and precipitation. This technique allows for the rapid development of climate scenarios for additional emissions scenarios not previously available from the GCM modelling centres. Having derived the end of century (2080s) change in both these variables for four marker emissions scenarios (A1FI, A2, B2, B1), regional response rates, or the regional rate of warming per °C global warming at each station, were calculated. The estimated ranges in regional responses at each station were then compared to regional response rates for the Irish ‘grid box’ derived from a larger sample of 14 GCMs, in order to determine if the calculated response rates were illustrative of a wider suite of GCMs. A Monte Carlo (MC) resampling approach was then employed to sample regional response rates for selected stations and for different estimates of future warming. On the basis of the MC approach, probability distribution functions (pdfs) of simulated changes in temperature and precipitation were constructed and compared to the original statistically downscaled data. The methodology and results presented represent a significant contribution to the traditional approach of statistical downscaling through the development of associated likelihoods, rather than just a change in the mean value. While the methodology presented should enable the rapid development of probabilistic based climate projections, based on a limited availability of downscaled climate scenarios, caution needs to be exercised in the interpretation of the results. While they provide a basis for risk or policy assessment, estimates of the level of risk are not independent of the method employed.

Simulation of soil carbon efflux from an arable soil using the ECOSSE model: Need for an improved model evaluation framework?

Globally, it is estimated that ~1500PgC of organic carbon is stored in the top meter of terrestrial soils. This represents the largest terrestrial pool of carbon. Appropriate management of soils, to maintain or increase the soil carbon pool, represents a significant climate change mitigation opportunity. To achieve this, appropriate tools and models are required in order to more accurately estimate soil carbon fluxes with a view to informing and developing more effective land use management strategies. Central to this is the evaluation of models currently in use to estimate soil carbon emissions. In the present study, we evaluate the ECOSSE (Estimating Carbon in Organic Soils - Sequestration and Emissions) model which has its origins in both SUNDIAL and RothC and has been widely used globally to model soil CO2 fluxes across different locations and land-use types on both organic and mineral soils. In contrast to previous studies, the model was found to poorly represent observed soil respiration at the study site, an arable cropland on mineral soil located in south-east Ireland. To isolate potential sources of error, the model was decomposed into its component rate equations or modifiers. This investigation highlighted a deficiency in the model simulated soil water, resulting in significant inhibition of the model simulated CO2 flux relative to the observed data. When measured values of soil water at the site were employed, the model simulated soil respiration improved significantly (r2 of 0.775 vs 0.154). This highlighted model deficiency remains to be evaluated at other sites; however, the research highlights the need for a more comprehensive evaluation of soil carbon models prior to their use in informing policy, particularly models which are employed at larger scales and for climate change projections.

Developing regional calibration coefficients for estimation of hourly global solar radiation in Ireland

ABSTRACT This study proposed regional coefficients for estimating hourly global solar radiation through the adaptation of some empirical models that relate radiation to climatological and geographical variables. A total of 10 models were adapted over 7 stations in Ireland. The performance of the models was evaluated using some selected error indicators including the global performance index which combines all other error indices. The results indicated that the sunshine based regional calibration coefficients generated through a polynomial approach was most superior over other models with the lowest RMSE (0.2–0.3 MJm−2 hr−1), MAE (0.1–0.2 MJm−2 hr−1) and Pbias (0–7.0%) and highest R2 and KGE (>0.85). The study found no local effect such as instrumental siting, observational uncertainty and climate on the variations of these coefficients. This outcome will therefore facilitate the design of various local and/or regional solar energy applications at microscale in a temperate region.

Spatial validation of an urban energy balance model using multi-temporal remotely sensed surface temperature

Despite a growing number of urban energy balance (UEB) model applications being undertaken within urban climate literature, the number of independent validation exercises remains very limited. This in turn has raised questions as to the value of model applications without due consideration to the models performance in space and time. The PILPS-URBAN project went some ways towards understanding the general performance of 33 UEB models and highlighted the need for careful treatment of urban and non-urban land surfaces within model parameterization and also the derivation of input parameters. Nevertheless, the need for independent external validation of specific models is now evident. Here we undertake an external evaluation of the SUEWS model in Dublin (Ireland). We present a method for spatially validating the model across the entire Dublin area by employing remotely sensed surface temperatures obtained through the MODIS satellite platform.