A high resolution wind&wave forecast model chain for the Mediterranean and Adriatic Sea

DHI (Danish Hydraulic Institute) and HyMOLab (Hydrodynamics and Met-Ocean Laboratory of the Dept. of Engineering and Architecture of the University of Trieste) have undertaken a joint applied research project with the aim to develop a state-of-art wind-wave forecast service at mid resolution for the Mediterranean Sea and at very high resolution for the Adriatic Sea. Weather routing, civil protection, coastal engineering, oil&gas and renewable energy fields, the planning of operations at sea, ... are just few among the multiple potential applications of this service. The meteorological model used in this study is WRF-ARW, one of the most widely used state-of-the-art open-source non-hydrostatic model. Global Forecast System (GFS) dataset provides the boundary and initial conditions. MIKE21-Spectral Waves is used as wave model with resolution ranging from 0.1 to 0.03 approximately. The use of a local area meteorological model guarantees higher levels of resolution and accuracy in an area such as the Mediterranean Sea where the complex orography and coastline induce short-time/small-space weather scales. The model chain runs daily (or twice a day on demand) on the High Performance Computing (HPC) infrastructure of HyMOLab. The validation of the entire model chain and specifically the forecast data obtained for the sea state is continuously updated according to new available data from satellites and buoys. Anyway, a major verification of the performance of the model chain against historic data (hindcast) is almost mandatory. For this aim, we performed a multi-decade test obtaining very good statistical parameters for the entire model chain performance. In this context the hindcast dataset developed by DHI and HyMOLab consists of 35 years of hourly data for the period 1979-2013, with the same model chain. The CFSR d093.0 hourly dataset with a spatial resolution of 0.5 provides the boundary and initial conditions. The atmospheric and wave models performance is checked against six satellite datasets, missions Envisat, ERS-2, Geosat FO, Jason-1, Jason-2, Topex-Poseidon, using a moving window technique procedure. Wave data close to coast are compared with available data from more than 20 buoys. The paper describes the validation procedure adopted for the hindcasted data. Furthermore the forecast service is described too, with specific emphasis to the very high resolution adopted in the Adriatic Sea

Understanding the rapid summer warming and changes in temperature extremes since the mid-1990s over Western Europe

Analysis of observations indicates that there was a rapid increase in summer (June-August, JJA) mean surface air temperature (SAT) since the mid-1990s over Western Europe. Accompanying this rapid warming are significant increases in summer mean daily maximum temperature, daily minimum temperature, annual hottest day temperature and warmest night temperature, and an increase in frequency of summer days and tropical nights, while the change in the diurnal temperature range (DTR) is small. This study focuses on understanding causes of the rapid summer warming and associated temperature extreme changes. A set of experiments using the atmospheric component of the state-of-the-art HadGEM3 global climate model have been carried out to quantify relative roles of changes in sea surface temperature (SST)/sea ice extent (SIE), anthropogenic greenhouse gases (GHGs), and anthropogenic aerosols (AAer). Results indicate that the model forced by changes in all forcings reproduces many of the observed changes since the mid-1990s over Western Europe. Changes in SST/SIE explain 62.2% ± 13.0% of the area averaged seasonal mean warming signal over Western Europe, with the remaining 37.8% ± 13.6% of the warming explained by the direct impact of changes in GHGs and AAer. Results further indicate that the direct impact of the reduction of AAer precursor emissions over Europe, mainly through aerosol-radiation interaction with additional contributions from aerosol-cloud interaction and coupled atmosphere-land surface feedbacks, is a key factor for increases in annual hottest day temperature and in frequency of summer days. It explains 45.5% ± 17.6% and 40.9% ± 18.4% of area averaged signals for these temperature extremes. The direct impact of the reduction of AAer precursor emissions over Europe acts to increase DTR locally, but the change in DTR is countered by the direct impact of GHGs forcing. In the next few decades, greenhouse gas concentrations will continue to rise and AAer precursor emissions over Europe and North America will continue to decline. Our results suggest that the changes in summer seasonal mean SAT and temperature extremes over Western Europe since the mid-1990s are most likely to be sustained or amplified in the near term, unless other factors intervene

Optimizing the procedure of grain nutrient predictions in barley via hyperspectral imaging

Hyperspectral imaging enables researchers and plant breeders to analyze various traits of interest like nutritional value in high throughput. In order to achieve this, the optimal design of a reliable calibration model, linking the measured spectra with the investigated traits, is necessary. In the present study we investigated the impact of different regression models, calibration set sizes and calibration set compositions on prediction performance. For this purpose, we analyzed concentrations of six globally relevant grain nutrients of the wild barley population HEB-YIELD as case study. The data comprised 1,593 plots, grown in 2015 and 2016 at the locations Dundee and Halle, which have been entirely analyzed through traditional laboratory methods and hyperspectral imaging. The results indicated that a linear regression model based on partial least squares outperformed neural networks in this particular data modelling task. There existed a positive relationship between the number of samples in a calibration model and prediction performance, with a local optimum at a calibration set size of ~40% of the total data. The inclusion of samples from several years and locations could clearly improve the predictions of the investigated nutrient traits at small calibration set sizes. It should be stated that the expansion of calibration models with additional samples is only useful as long as they are able to increase trait variability. Models obtained in a certain environment were only to a limited extent transferable to other environments. They should therefore be successively upgraded with new calibration data to enable a reliable prediction of the desired traits. The presented results will assist the design and conceptualization of future hyperspectral imaging projects in order to achieve reliable predictions. It will in general help to establish practical applications of hyperspectral imaging systems, for instance in plant breeding concepts

Stable oxygen isotopes in Romanian oak tree rings record summer droughts and associated large-scale circulation patterns over Europe

We present the first annual oxygen isotope record (1900 – 2016) from the latewood (LW) cellulose of oak trees (Quercus robur) from NW Romania. As expected, the results correlate negatively with summer relative humidity, sunshine duration and precipitation and positively with summer maximum temperature. Spatial correlation analysis reveals a clear signal reflecting drought conditions at a European scale. Interannual variability is influenced by large-scale atmospheric circulation and by surface temperatures in the North Atlantic Ocean and the Mediterranean Sea. There is considerable potential to produce long and well-replicated oak tree ring stable isotope chronologies in Romania which would allow reconstructions of both regional drought and large-scale circulation variability over southern and central Europe

A cloud-to-ground lightning climatology for north-eastern Italy

This study analyzes the spatial distribution and temporal characteristics of cloud-to-ground lightnings (C2G) in the North East of Italy and the neighboring areas of Austria, Slovenia and Croatia. The dataset consists of about 6.5 millions C2G flash records, both positive and negative, observed between January 1995 and December 2011 by the "Centro Elettrotecnico Sperimentale Italiano-Sistema Italiano Rilevamento Fulmini'' (CESI/SIRF), part of the European Cooperation for Lightning Detection (EUCLID) Network. The results show that C2G lightnings concentrate in the foothill regions on the southern flank of the Eastern Alps with a maximum of discharge frequency of 10 lightnings per km2 per year. The number of C2G strokes varies with the period of the year: the most active period for lightning starts in April and lasts through November with the highest number of C2G strokes happening during the summer months of July and August, with maximum spatial density slightly moving from the mountain to the coastal area. The least frequency of C2G strokes is observed during wintertime. The mean diurnal C2G lightning activity for the whole domain shows a peak around 16:00–17:00 UTC and reaches a minimum around 07:00–09:00 UTC; the mean spatial distribution follows different patterns depending on the period of the day