The present study investigated future temperature and precipitation changes over Greece using the Weather Research and Forecasting (WRF) model. WRF was driven by EC-EARTH over Greece at very high ...resolution for the historical period (1980–2004), along with projected simulations, in the near future (2025–2049) and far future (2075–2099) under the Representative Concentration Pathways 4.5 (RCP4.5) and 8.5 (RCP8.5). Climatic variables were produced at 5-km grid spacing and 6-h interval. The historical simulation was evaluated against the available station observations. The analysis showed that the model underestimated the maximum temperatures and slightly overestimated the minimum temperatures. Also, the model simulated a small dry bias in precipitation with an excellent representation of the spatial patterns. The model projections for temperature under the two emission scenarios compared to the historical simulation revealed a robust magnitude of future warming with the most pronounced changes predominantly over the eastern areas of the country under the RCP8.5 in the far future. Projected precipitation changes were more evident in the far future with an overall decrease of the annual precipitation all over the eastern part of the country (with islands included) with the most dramatic reductions (above 40%) of seasonal precipitation observed under RCP8.5. Increases in the number of hot days were found everywhere with more pronounced changes over the plain areas under RCP8.5 in the far future. Significant increases of dry days were projected over the eastern part of the mainland and more intensely under RCP8.5 in the far future.
This paper presents a comparison of various forecasting approaches, using time series analysis, on mean hourly wind speed data. In addition to the traditional linear (ARMA) models and the commonly ...used feed forward and recurrent neural networks, other approaches are also examined including the Adaptive Neuro-Fuzzy Inference Systems (ANFIS) and Neural Logic Networks. The developed models are evaluated for their ability to produce accurate and fast forecasts.
This paper presents a novel method for the forecasting of mean hourly wind speed data using time series analysis. The initial point for this approach is mainly the fact that none of the forecasting ...approaches for hourly data, that can be found in the literature, based on time series analysis or meteorological models, gives significantly lower prediction error than the elementary persistent approach. This was combined with the characteristics of the wind speed data, which are determined by the power spectrum values, distinguished by the spectral gap in intervals between 20 minutes and 2 hours. The finally proposed methodology is based on the multi-step forecasting of 10 minutes averaged data and the subsequent averaging to generate mean hourly predictions. When applied to two independent data sets, this approach outperformed by a factor of four, the conventional one which utilizes past mean hourly wind speed values as inputs to the forecasting models.
This study presents the results of high-resolution dynamical downscaling of 5 km on maximum (TX) and minimum (TN) air temperature and precipitation, for Greece, with the Weather Research and ...Forecasting (WRF) model. The ERA-Interim (ERA-I) reanalysis dataset is used for initial and boundary conditions. The model results (WRF_5) are evaluated against available ground observations for the period 1980–2004 through the calculation of mean climatology, statistical metrics, and distributions of extreme events on daily, monthly and seasonal scales. WRF_5 model captures very well the geographical distribution of TX and TN of the study area, and illustrates finely the seasonal differences. Statistical results for TX (TN) indicate a cold (warm) bias of − 0.6 °C (1 °C) regarding WRF_5 and − 3 °C (0.5 °C) for ERA-I. The efficiency metrics for temperatures showed a highly improved performance of the model compared to reanalysis for all temporal scales investigated. The observed mean annual cycle and inter-annual variability of precipitation are also well represented by model simulation. Although WRF_5 overestimates rainfall during most of the year, the seasonal pattern of WRF_5 presented similar correlation coefficients for all stations with a range of 0.6–0.85, showing a good model ability to simulate the precipitation in Greece. The results reveal the capability of the configured WRF high resolution model to reproduce the main climatological variables of the study area, outperforming the coarse resolution ERA-Interim in a region that is dominated by highly variable topographic characteristics. This is deemed necessary for undertaking any further studies concerning future climate change impacts in various sectors.
Climate change is inherently linked to long-term non-stationary changes in the characteristics and frequency of weather patterns. The present study attempts to identify the statistical changes of ...weather patterns in Athens Greece, from the comparative assessment of 96-h backward trajectories between historic (1980–2009) and future (2020–2049) climatology derived from the IPCC RCP4.5 and RCP8.5 scenarios. Arrival heights at 750 m, 1500 m, and 3000 m above sea level are considered to account for the impact of the planetary boundary layer and the lower free troposphere. The analysis of the historic period yields 7 dominant patterns for all heights determined independently, with similar spatial characteristics but varying frequency of occurrence. The classification of backward trajectories under future climate using the same historic clusters reveals percentage changes from locally short-distance travelling patterns to longer-distance ones with a predominant northbound direction. As a second experiment, backward trajectories are re-clustered independently reaching again the same type of clusters but with observable changes in the cluster origins and trajectory lengths.
This study is a first attempt to obtain high resolution simulations of present climate in Greece, by applying dynamical downscaling using the Advanced Weather Research and Forecasting numerical model ...(WRF-ARW). We performed two simulations and thus, the model was set up with two different horizontal resolutions for the European domain (D01), of 20 and 25km, driven by ERA-INTERIM reanalysis data for a total period of one year. For each simulation, the European domain (D01) was dynamically downscaled to the domain of Greece (D02), with grid spacing of 5km. The first objective concerned the selection of the appropriate horizontal resolution of the first domain (at European scale) and the second was to validate the performance of various physics parameterizations of the WRF-ARW at high resolution on temperature and precipitation predictions, in the domain of Greece. In total, seven different sets of physics parameterizations were applied to investigate the model predictions against available observational data, by utilizing appropriate statistical metrics. It was deduced that there were no significant differences in the results imposed by the grid resolution of 25km or 20km of the parent (European) domain. The biases remained systematically negative (underestimation) for maximum temperature and positive (overestimation) for the minimum temperature for all configurations of about 2–2.4°C and 1–1.5°C, respectively. Simulation results in precipitation were not particularly satisfactory for any of the physical schemes, indicating overall a strong overestimation in absolute values, but with similarities found in the precipitation patterns.
•High resolution regional climatology (5×5km2) over Greece•Evaluation of domains' resolution and different parameterization schemes with WRF•Satisfactory model performance for maximum and minimum air temperature simulations•Strong overestimation of precipitation in all model simulations•Best performance of PP3, which consists of WMS6, MYJ and BMJ schemes, for rainfall
Air Pollution control is of major concern for the Greater Athens Area (GAA) of Greece. High concentrations of Particulate Matter with diameter less than 10μm (PM10) have been observed and often ...reported to exceed the currently EU legislated 24-hour limit of 50μg/m3. Efforts therefore have been placed on understanding the PM10 concentration pattern in the area so that mitigation measures can be taken accordingly. The present paper presents a statistical methodology to discover causal relationships between daily PM10 exceedances at a monitoring site, with PM10 concentrations from existing stations from the monitoring network and associated weather patterns. The proposed approach utilised a dimension reduction algorithm, Positive Matrix Factorisation (PMF) algorithm, coupled with the k-means clustering algorithm to identify distinct groups of data. Then for each resulted cluster, the Granger Causality method aided by the Pearson correlation is applied to establish the causal relationships between the meteorological patterns and the observed PM10 exceedances. The study was conducted using 6-years of daily PM10 concentration data from the monitoring network in the GAA, complemented with meteorological data available from the National Centres for Environmental Prediction (NCEP) Global Forecasting System (GFS). The analysis yielded that the PM10 exceedances in the Athens area can be classified into 6 distinct types identified with varying spatial distribution characteristics and air pollution contributors.
The paper introduces a new methodology for the prediction of daily PM10 concentrations, in line with the regulatory framework introduced through the EU Directive 2008/50/EC. The proposed approach is ...based on the efficient utilisation of the data collected over short time intervals (hourly) rather than the daily values used to derive the daily regulatory threshold. It is sufficiently simple and easily applicable in operational forecasting systems with the ability to accept as inputs both historical data and exogenous paraeters, such as meteorological variables. The application of the proposed methodology is demonstrated using data from five monitoring stations of air pollutants located in Athens, over a five year period (2000–2004) as well as compatible meteorological data from the NCEP (National Centers for Environmental Protection). A set of different models have been tested at the same time to reveal the effectiveness of the proposed approach, both univariate and multivariate, and linear and non-linear models. The analysis of all examined datasets has shown conclusive evidence that the introduction of the newly developed procedure which utilises data collected over a shorter horizon can significantly increase the forecasting ability of any developed model using daily historic PM10 data, under all examined metrics.
The present work attempts to provide more accurate estimate of HDD and CDD and investigates the suitability of high resolution downscaled seasonal climatic forecasting models for assessing and ...accurately estimating the energy demands of buildings. The analysis has been established through a series of indices for estimating heating (HDD) and cooling degree days (CDD) using interpolated hourly data which were produced from the model output. The work has considerable potential to provide refined inputs for assessing building sector-specific vulnerability to climate change: energy supply and demand.
In this work the application of the above mentioned methodological approach in the assessment of the energy performance and requirements of buildings on Greece are presented, for a period and with a forecast horizon of 6 months. The ARW-WRF model has been set up and validated to produce downscaled climatological fields for Greece, forced by the output of the CFSv2 model, with a horizontal spatial resolution of 5km×5km. The data, that covered all Greek regions and climatology zones according to the existing building regulations code and the region elevation present a very reasonable correlation with data published in previous studies.
Under its Kyoto and EU obligations, Greece has committed to a greenhouse gas (GHG) emissions increase of at most 25% compared to 1990 levels, to be achieved during the period 2008–2012. Although this ...restriction was initially regarded as being realistic, information derived from GHG emissions inventories shows that an increase of approximately 28% has already taken place between 1990 and 2005, highlighting the need for immediate action. This paper explores the reallocation of production in Greece, on a sector-by-sector basis, in order to meet overall demand constraints and GHG emissions targets. We pose a constrained optimization problem, taking into account the Greek environmental input–output matrix for 2005, the amount of utilized energy and pollution reduction options. We examine two scenarios, limiting fluctuations in sectoral production to at most 10% and 15%, respectively, compared to baseline (2005) values. Our results indicate that (i) GHG emissions can be reduced significantly with relatively limited effects on GVP growth rates, and that (ii) greater cutbacks in GHG emissions can be achieved as more flexible production scenarios are allowed.
