Aristeidis G. Koutroulis

The threat of soil salinity : A European scale review

Soil salinisation is one of the major soil degradation threats occurring in Europe. The effects of salinisation can be observed in numerous vital ecological and non-ecological soil functions. Drivers of salinisation can be detected both in the natural and man-made environment, with climate and the foreseen climate change also playing an important role. This review outlines the state of the art concerning drivers and pressures, key indicators as well as monitoring, modeling and mapping methods for soil salinity. Furthermore, an overview of the effect of salinisation on soil functions and the respective mechanism is presented. Finally, the state of salinisation in Europe is presented according to the most recent literature and a synthesis of consistent datasets. We conclude that future research in the field of soil salinisation should be focused on among others carbon dynamics of saline soil, further exploration of remote sensing of soil properties and the harmonization and enrichment of soil salinity maps across Europe within a general context of a soil threat monitoring system to support policies and strategies for the protection of European soils.

Spatiotemporal Characteristics of Meteorological Drought for the Island of Crete

Abstract A modified drought index, named the spatially normalized–standardized precipitation index (SN-SPI), has been developed for assessing meteorological droughts. The SN–SPI is a variant index to the standardized precipitation index and is based on the probability of precipitation at different time scales, but it is spatially normalized for improved assessment of drought severity. Results of this index incorporate the spatial distribution of precipitation and produce improved drought warnings. This index is applied in the island of Crete, Greece, and the drought results are compared to the ones of SPI. A 30-year-long average monthly precipitation dataset from 130 watersheds of the island is used by the above indices for drought classification in terms of its duration and intensity. Bias-adjusted monthly precipitation estimates from an ensemble of 10 regional climate models were used to quantify the influence of global warming to drought conditions over the period 2010–2100. Results based on both indic...

Evaluation of precipitation and temperature simulation performance of the CMIP3 and CMIP5 historical experiments

Abstract The fifth phase of the Coupled Model Intercomparison Project (CMIP5) is the most recent coordinated experiment of global climate modeling. Compared to its predecessor CMIP3, the fifth phase of the homonymous experiment—CMIP5 involves a greater number of GCMs, run at higher resolutions with more complex components. Here we use daily GCM data from both projects to test their efficiency in representing precipitation and temperature parameters with the use of a state of the art high resolution gridded global dataset for land areas and for the period 1960–2005. Two simple metrics, a comprehensive histogram similarity metric based on the match of simulated and observed empirical pdfs and a metric for the representation of the annual cycle were employed as performance indicators. The metrics were used to assess the skill of each GCM at the entire spectrum of precipitation and temperature pdfs but also for the upper and lower tails of it. Results are presented globally and regionally for 26 land regions that represent different climatic regimes, covering the total earth’s land surface except for Antarctica. Compared to CMIP3, CMIP5 models perform better in simulating precipitation including relatively intense events and the fraction of wet days. For temperature the improvement is not as clear except for the upper and lower hot and cold events of the distribution. The agreement of model simulations is also considerably increased in CMIP5. Substantial improvement in intense precipitation is observed over North Europe, Central and Eastern North America and North East Europe. Nevertheless, in both ensembles some models clearly perform better than others from a histogram similarity point of view. The derived skill score metrics provide essential information for impact studies based on global or regional land area multi-model ensembles.

Tree crown detection on multispectral VHR satellite imagery.

A new method called Arbor Crown Enumerator (ACE) was developed for tree crown detection from multispectral Very High-resolution (VHR) satellite imagery. ACE uses a combination of the Red band and Normalized Difference Vegetation Index (NDVI) thresholding, and the Laplacian of the Gaussian (LOG) blob detection method. This method minimizes the detection shortcomings of its individual components and provides a more accurate estimation of the number of tree crowns captured in an image sample. The ACE was applied successfully to sample images taken from a four-band QuickBird (0.7m 0.7m) scene of Keritis watershed, in the Island of Crete. The method performs very well for different tree types, sizes and densities that may include non vegetation features such as roads and houses. Statistical analysis on the tree crown detection results from the sample images supports the agreement between the measurements and the simulations. The new method reduces considerably the effort of manual tree counting and can be used for environmental applications of fruit orchard, plantation and open forest population monitoring.

Climate Change Impact on Photovoltaic Energy Output: The Case of Greece

Solar power is the third major renewable energy, constituting an increasingly important component of global future—low carbon—energy portfolio. Accurate climate information is essential for the conditions of solar energy production, maximization, and stable regulation and planning. Climate change impacts on energy output projections are thus of crucial importance. In this study the effect of projected changes in irradiance and temperature on the performance of photovoltaic systems in Greece is examined. Climate projections were obtained from 5 regional climate models (RCMs) under the A1B emissions scenario, for two future periods. The RCM data present systematic errors against observed values, resulting in the need of bias adjustment. The projected change in photovoltaic energy output was then estimated, considering changes in temperature and insolation. The spatiotemporal analysis indicates significant increase in mean annual temperature (up to 3.5°C) and mean total radiation (up to 5 W/m2) by 2100. The performance of photovoltaic systems exhibits a negative linear dependence on the projected temperature increase which is outweighed by the expected increase of total radiation resulting in an up to 4% increase in energy output.

Climate-Induced Shifts in Global Soil Temperature Regimes

Abstract Soil temperature is a key factor of plant growth and biological enzyme activities occurring in the soil, affected by the land cover, the evapotranspiration rate, the albedo, and the energy budget of the soil surface. In recent decades, efforts have been made to conserve soils against nonsustainable anthropogenic pressures. Changes in climate can impose additional threats on soil sustainability, as global scale soil temperature regime alterations are expected under global warming. Here, data from three well-established global climate models, spanning from 1981 to as far as 2120, are used to force the JULES (Joint UK Land Environment Simulator) model and produce simulations of soil temperature, calculating the water and energy budgets of the land surface. Modeled soil temperature data are used to estimate the climate-induced changes in the global soil temperature regimes at three different global warming levels. The results show significant shifts in the soil temperature regime for extended areas of the world, especially in the northern hemisphere. Pergelic and Cryic areas are reduced, whereas the Mesic and Thermic soils gain large areas in all three studied scenarios. Implications of the warming patterns might indicate the northward shift of various croplands in regions that until now their cultivation was not possible.

Freshwater vulnerability under high end climate change. A pan-European assessment

As freshwater availability is crucial for securing a sustainable, lower‑carbon future, there is a critical connection between water management and climate policies. Under a rapidly changing climate, it is more important than ever to estimate the degree of future water security. This is a challenging task as it depends on many different variables: the degree of warming and its consequent effects on hydrological resources, the water demand by different sectors, and the possible ameliorations or deteriorations of the effects due to climate change adaptation and mitigation strategies. A simple and transparent conceptual framework has been developed to assess the European vulnerability to freshwater stress under the present hydro-climatic and socioeconomic conditions, in comparison to projections of future vulnerability for different degrees of global warming (1.5°C, 2°C and 4°C), under the high-rate warming scenario (RCP8.5). Different levels of adaptation to climate change are considered in the framework, by employing various relevant pathways of socioeconomic development. A spatially detailed pan-European map of vulnerability to freshwater shortage has been developed at the local administrative level, making this approach extremely useful for supporting regional level policymaking and implementation and strategic planning against future freshwater stress.

Changes in climate extremes, fresh water availability and vulnerability to food insecurity projected at 1.5°C and 2°C global warming with a higher-resolution global climate model

We projected changes in weather extremes, hydrological impacts and vulnerability to food insecurity at global warming of 1.5°C and 2°C relative to pre-industrial, using a new global atmospheric general circulation model HadGEM3A-GA3.0 driven by patterns of sea-surface temperatures and sea ice from selected members of the 5th Coupled Model Intercomparison Project (CMIP5) ensemble, forced with the RCP8.5 concentration scenario. To provide more detailed representations of climate processes and impacts, the spatial resolution was N216 (approx. 60 km grid length in mid-latitudes), a higher resolution than the CMIP5 models. We used a set of impacts-relevant indices and a global land surface model to examine the projected changes in weather extremes and their implications for freshwater availability and vulnerability to food insecurity. Uncertainties in regional climate responses are assessed, examining ranges of outcomes in impacts to inform risk assessments. Despite some degree of inconsistency between components of the study due to the need to correct for systematic biases in some aspects, the outcomes from different ensemble members could be compared for several different indicators. The projections for weather extremes indices and biophysical impacts quantities support expectations that the magnitude of change is generally larger for 2°C global warming than 1.5°C. Hot extremes become even hotter, with increases being more intense than seen in CMIP5 projections. Precipitation-related extremes show more geographical variation with some increases and some decreases in both heavy precipitation and drought. There are substantial regional uncertainties in hydrological impacts at local scales due to different climate models producing different outcomes. Nevertheless, hydrological impacts generally point towards wetter conditions on average, with increased mean river flows, longer heavy rainfall events, particularly in South and East Asia with the most extreme projections suggesting more than a doubling of flows in the Ganges at 2°C global warming. Some areas are projected to experience shorter meteorological drought events and less severe low flows, although longer droughts and/or decreases in low flows are projected in many other areas, particularly southern Africa and South America. Flows in the Amazon are projected to decline by up to 25%. Increases in either heavy rainfall or drought events imply increased vulnerability to food insecurity, but if global warming is limited to 1.5°C, this vulnerability is projected to remain smaller than at 2°C global warming in approximately 76% of developing countries. At 2°C, four countries are projected to reach unprecedented levels of vulnerability to food insecurity. This article is part of the theme issue ‘The Paris Agreement: understanding the physical and social challenges for a warming world of 1.5°C above pre-industrial levels’.

Climate Impacts in Europe Under +1.5°C Global Warming

The Paris Agreement of the United Nations Framework Convention on Climate Change aims not only at avoiding +2°C warming (and even limit the temperature increase further to +1.5°C), but also sets long-term goals to guide mitigation. Therefore, the best available science is required to inform policymakers on the importance of and the adaptation needs in a +1.5°C warmer world. Seven research institutes from Europe and Turkey integrated their competencies to provide a cross-sectoral assessment of the potential impacts at a pan-European scale. The initial findings of this initiative are presented and key messages communicated. The approach is to select periods based on global warming thresholds rather than the more typical approach of selecting time periods (e.g., end of century). The results indicate that the world is likely to pass the +1.5°C threshold in the coming decades. Cross-sectoral dimensions are taken into account to show the impacts of global warming that occur in parallel in more than one sector. Also, impacts differ across sectors and regions. Alongside the negative impacts for certain sectors and regions, some positive impacts are projected. Summer tourism in parts of Western Europe may be favored by climate change; electricity demand decreases outweigh increases over most of Europe and catchment yields in hydropower regions will increase. However, such positive findings should be interpreted carefully as we do not take into account exogenous factors that can and will influence Europe such as migration patterns, food production, and economic and political instability.

A Probabilistic Rain Diagnostic Model Based on Cyclone Statistical Analysis

Data from a dense network of 69 daily precipitation gauges over the island of Crete and cyclone climatological analysis over middle-eastern Mediterranean are combined in a statistical approach to develop a rain diagnostic model. Regarding the dataset, 0.5 × 0.5, 33-year (1979–2011) European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis (ERA-Interim) is used. The cyclone tracks and their characteristics are identified with the aid of Melbourne University algorithm (MS scheme). The region of interest is divided into a grid mesh and for each grid the probability of rain occurrence from passing cyclones is estimated. Such probability maps are estimated for three rain intensity categories. The probability maps are evaluated for random partitions of the data as well as for selected rain periods. Cyclones passing south of Italy are found to have greater probability of producing light rain events in Crete in contrast to medium and heavy rain events which are mostly triggered by cyclones of southern trajectories. The performance of the probability maps is very satisfactory, recognizing the majority of “affecting” cyclones and rejecting most cyclones that do not trigger rain events. Statistical measures of sensitivity and specificity range between 0.5 and 0.8 resulting in effective forecasting potential.