66 research outputs found
Long-term summer sunshine/moisture stress reconstruction from tree-ring widths from Bosnia and Herzegovina
We present the first summer sunshine reconstruction from tree-ring data for the western part of the Balkan Peninsula. Summer sunshine is tightly connected with moisture stress in trees, because the moisture stress and therefore the width of annual tree-rings is under the influence of the direct and interactive effects of sunshine duration (temperature, precipitation, cloud cover and evapotranspiration). The reconstruction is based on a calibrated z-scored mean chronology, calculated from tree-ring width measurements from 7 representative black pine (<i>Pinus nigra</i> Arnold) sites in Bosnia and Herzegovina (BiH). A combined regression and scaling approach was used for the reconstruction of the summer sunshine. We found a significant negative correlation (<i>r</i> = −0.54, <i>p</i> < 0.0001) with mean June–July sunshine hours from Osijek meteorological station (Croatia). The developed model was used for reconstruction of summer sunshine for the time period 1660–2010. We identified extreme summer events and compared them to available documentary historical sources of drought, volcanic eruptions and other reconstructions from the broader region. All extreme summers with low sunshine hours (1712, 1810, 1815, 1843, 1899 and 1966) are connected with volcanic eruptions
When Will Current Climate Extremes Affecting Maize Production Become the Norm?
We estimate the effects of climate anomalies (heat stress and drought) on annual maize production, variability, and trend from the country level to the global scale using a statistical model. Moderate climate anomalies and extremes are diagnosed with two indicators of heat stress and drought computed over maize growing regions during the most relevant period of maize growth. The calibrated model linearly combines these two indicators into a single Combined Stress Index. The Combined Stress Index explains 50% of the observed global production variability in the period 1980?2010. We apply the model on an ensemble of high-resolution global climate model simulations. Global maize losses, due to extreme climate events with 10-year return times during the period 1980?2010, will become the new normal already at 1.5 °C global warming levels (approximately 2020s). At 2 °C warming (late 2030s), maize areas will be affected by heat stress and drought never experienced before, affecting many major and minor production regions.Fil: Zampieri, M.. European Commission Joint Research Centre; ItaliaFil: Ceglar, A.. European Commission Joint Research Centre; ItaliaFil: Dentener, F.. European Commission Joint Research Centre; ItaliaFil: Dosio, A.. European Commission Joint Research Centre; ItaliaFil: Naumann, Gustavo. European Commission Joint Research Centre; Italia. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria; ArgentinaFil: van den Berg, M.. European Commission Joint Research Centre; ItaliaFil: Toreti, A.. European Commission Joint Research Centre; Itali
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Performance of seasonal forecasts for the flowering and veraison of two major Portuguese grapevine varieties
Seasonal phenology forecasts are becoming increasingly demanded by winegrowers and viticulturists. Forecast performance needs to be investigated over space and time before practical applications. We assess seasonal forecast performance (skill, probability and accuracy) in predicting flowering and veraison stages of two representative varieties in Portugal over 1993–2017. The state-of-the-art forecast system ECMWF-SEAS5 provides 7-month seasonal forecasts and is coupled with a locally adapted phenology model. Overall, findings illustrate the dependence of forecast performance on initialization timings, regions and predicting subjects (stages and varieties). Forecast performance improves by delaying the initialization timing and only forecasts initialized on April 1st show better skills than climatology on predicting phenology terciles (early/normal/late). The considerable bias of daily values of seasonal climate predictions can represent the main barrier to accurate forecasts. Better prediction performance is consistently found in Central-Southern regions compared to Northern regions, attributing to an earlier phenology occurrence with a shorter forecast length. Comparable predictive skills between flowering and veraison for both varieties imply better predictability in summer. Consequently, promising seasonal phenology predictions are foreseen in Central-Southern wine regions using forecasts initialized on April 1st with approximately 1–2/3–4 months lead time for flowering/veraison: potential prediction errors are ∼2 weeks, along with an overall moderate forecast skill on categorical events. However, considerable inter-annual variability of forecast performance over the same classified phenology years reflects the substantial influence of climate variability. This may represent the main challenge for reliable forecasts in Mediterranean regions. Recommendations are suggested for methodological innovations and practical applications towards reliable regional phenology forecasts
Evaluation of the high resolution WRF-Chem (v3.4.1) air quality forecast and its comparison with statistical ozone predictions
An integrated modelling system based on the regional online coupled
meteorology–atmospheric chemistry WRF-Chem model configured with two nested
domains with horizontal resolutions of 11.1 and 3.7 km has been applied for
numerical weather prediction and for air quality forecasts in Slovenia. In the
study, an evaluation of the air quality forecasting system has been performed
for summer 2013. In the case of ozone (O3) daily maxima, the first- and
second-day model predictions have been also compared to the operational
statistical O3 forecast and to the persistence. Results of discrete and
categorical evaluations show that the WRF-Chem-based forecasting system is
able to produce reliable forecasts which, depending on monitoring site and
the evaluation measure applied, can outperform the statistical model. For
example, the correlation coefficient shows the highest skill for WRF-Chem
model O3 predictions, confirming the significance of the non-linear
processes taken into account in an online coupled Eulerian model. For some
stations and areas biases were relatively high due to highly complex terrain
and unresolved local meteorological and emission dynamics, which contributed
to somewhat lower WRF-Chem skill obtained in categorical model evaluations.
Applying a bias correction could further improve WRF-Chem model forecasting
skill in these cases
Evaluation of the high resolution WRF-Chem (v3.4.1) air quality forecast and its comparison with statistical ozone predictions
An integrated modelling system based on the regional online coupled
meteorology–atmospheric chemistry WRF-Chem model configured with two nested
domains with horizontal resolutions of 11.1 and 3.7 km has been applied for
numerical weather prediction and for air quality forecasts in Slovenia. In the
study, an evaluation of the air quality forecasting system has been performed
for summer 2013. In the case of ozone (O3) daily maxima, the first- and
second-day model predictions have been also compared to the operational
statistical O3 forecast and to the persistence. Results of discrete and
categorical evaluations show that the WRF-Chem-based forecasting system is
able to produce reliable forecasts which, depending on monitoring site and
the evaluation measure applied, can outperform the statistical model. For
example, the correlation coefficient shows the highest skill for WRF-Chem
model O3 predictions, confirming the significance of the non-linear
processes taken into account in an online coupled Eulerian model. For some
stations and areas biases were relatively high due to highly complex terrain
and unresolved local meteorological and emission dynamics, which contributed
to somewhat lower WRF-Chem skill obtained in categorical model evaluations.
Applying a bias correction could further improve WRF-Chem model forecasting
skill in these cases
Early heat waves over Italy and their impacts on durum wheat yields
In the last decades the Euro-Mediterranean region has experienced an
increase in extreme temperature events such as heat waves. These extreme
weather conditions can strongly affect arable crop growth and final yields.
Here, early heat waves over Italy from 1995 to 2013 are identified and
characterised and their impact on durum wheat yields is investigated. As
expected, results confirm the impact of the 2003 heat wave and highlight a
high percentage of concurrence of early heat waves and significant negative
yield anomalies in 13 out of 39 durum wheat production areas. In
south-eastern Italy (the most important area for durum wheat production),
the percentage of concurrent events exceeds 80 %
PannEx: The Pannonian Basin Experiment
The almost closed structure of the Pannonian Basin makes it an exceptional natural laboratory for the study of the water and energy cycles, focusing on the physical processes of relevance. The Pannonian Basin Experiment, under the umbrella of the Global Energy and Water Exchanges project of the World Climate Research Programme, aims to achieve a better understanding of the Earth System components and their interactions in the Pannonian Basin. The scientific basis of the PannEx supports research that can better translate and deliver relevant climate data, information and knowledge for societal decision making through the national hydro-meteorological and climate services, research institutes and universities. We outline the framework for the development of the PannEx in the light of international efforts to provide scientific support and involve international research community in integrated approach towards identifying and increasing adaptation capacity in the face of climate change in the Pannonian Basin. As such, PannEx dedicated observational and modeling efforts also strive to reach results with the global impact. © 2018 The Author
Co-designed agro-climate indicators identify different future climate effects for grape and olive across Europe
Co-design processes involving the scientific community, practitioners, end users and stakeholders can efficiently characterize harmful weather events during the growing season that potentially result in losses of crop yield and quality. This study builds on the experience of the EU Horizon 2020 project MED-GOLD for grape and olive. The identified agro-climate indicators are extended from the MED-GOLD regions to the entire ones where grape and olive are currently grown in Europe and Turkey, and used to assess climate change impacts with intrinsic adaptation relevance stemming from the co-design process. Before 2000, only a low fraction of the European grape and olive growing areas was exposed to extreme weather events as revealed by the agro-climate indicators, but this has changed rapidly afterward. Projections show increasingly widespread extreme high temperature events from 2020 to 2080. Approximately one-third of grapevine regions and over half of olive cultivation areas are expected to experience extreme drought conditions. Additionally, the frequency of compound extreme events will increase in the future, especially in the Mediterranean region and under the high-end emission scenario RCP8.5. This outcome calls for a new decision-making mindset that embeds expected levels of climate variability and extremes as the “new normal” for grape and olive in Europe. This will facilitate deployment of the required biophysical, economic and policy adaptation tools
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