Improved estimation of global solar radiation over rugged terrains by the disaggregation of Satellite Applications Facility on Land Surface Analysis data (LSA SAF)

AbstractThis paper presents a new method to predict global solar radiation over irregular terrain, named Estimation of global solar RADiation (ERAD). The method is based on the disaggregation of Satellite Applications Facility on Land Surface Analysis (LSA SAF) data using a digital elevation model and is applied in Italy with a time step of 1 min and a spatial resolution of 200 m. A quantitative assessment of ERAD is performed in comparison with three other standard methods (Mountain Microclimate Simulation Model [MTCLIM], LSA SAF and Copernicus Atmosphere Monitoring Service [CAMS]) using measurements taken in 43 stations located in Italy or in the surrounding countries, in the years 2005–2016. Such assessment concerns the irradiance incoming on a horizontal surface, which is measured by ground radiation sensors and is summarized by means of four accuracy statistics (i.e. mean absolute error [MAE], root mean square error [RMSE], coefficient of determination [R2] and mean bias error [MBE]). Overall, the average daily global solar radiation estimates obtained by ERAD have RMSE and R2 about 25 W·m−2 and 0.943, respectively. These statistics are similar to those of LSA SAF and better than those of CAMS and, above all, MTCLIM. The bias analysis by elevation ranges shows a slight ERAD overestimation over plains and hills and a slight underestimation over mountains. An additional qualitative assessment shows how the ERAD radiation estimates are more spatially detailed than those of the other methods and are redistributed on inclined surfaces consistently with expectations

Geoportale del Consorzio LaMMA Disseminazione di dati meteo in near real-time tramite standard OGC e software Open Source

This paper describes the spatial data infrastructure (SDI) used by the LaMMA Consortium - Environmental Mod elling and Monitoring Laboratory for Sustainable Developm ent of Tuscany Region for sharing, viewing and cataloguing (metadata and related information) all geospatial data that are daily proc essed and used op erationally in many meteorological and environmental app lications. The SDI was develop ed using Open Source technologies, mo reover the geospatial data has been imp lemented through protoco ls based on ogc (Open Geospatial Consortium) standards such as WMS, WFS and CSW. Geoserver was used for disseminating geospatial data and maps through OGC WMS and WFS protoco ls while GeoNetwork was used as the cataloguing and search po rtal through also the CSW protocol; eventually MapStore was used to implement the mash-up front-end. The innovative aspect of this po rtal is the fact that it currently is ingesting, fusing and disseminating geospatial data related to the MetOcfield from various sources in near real-time in a comp rehensive manner that allows users to create add ed value visualizations for the support of operational use cases as well as to access and download underlying data (where app licable)

Assimilating X- and S-Band Radar Data for a Heavy Precipitation Event in Italy

During the night between 9 and 10 September 2017, multiple flash floods associated with a heavy-precipitation event affected the town of Livorno, located in Tuscany, Italy. Accumulated precipitation exceeding 200 mm in two hours was recorded. This rainfall intensity is associated with a return period of higher than 200 years. As a consequence, all the largest streams of the Livorno municipality flooded several areas of the town. We used the limited-area weather research and forecasting (WRF) model, in a convection-permitting setup, to reconstruct the extreme event leading to the flash floods. We evaluated possible forecasting improvements emerging from the assimilation of local ground stations and X- and S-band radar data into the WRF, using the configuration operational at the meteorological center of Tuscany region (LaMMA) at the time of the event. Simulations were verified against weather station observations, through an innovative method aimed at disentangling the positioning and intensity errors of precipitation forecasts. A more accurate description of the low-level flows and a better assessment of the atmospheric water vapor field showed how the assimilation of radar data can improve quantitative precipitation forecasts

Geoportale del Consorzio LaMMA Disseminazione di dati meteo in near real-time tramite standard OGC e software Open Source

This paper describes the spatial data infrastructure (SDI) used by the LaMMA Consortium - Environmental Mod elling and Monitoring Laboratory for Sustainable Developm ent of Tuscany Region for sharing, viewing and cataloguing (metadata and related information) all geospatial data that are daily proc essed and used op erationally in many meteorological and environmental app lications. The SDI was develop ed using Open Source technologies, mo reover the geospatial data has been imp lemented through protoco ls based on ogc (Open Geospatial Consortium) standards such as WMS, WFS and CSW. Geoserver was used for disseminating geospatial data and maps through OGC WMS and WFS protoco ls while GeoNetwork was used as the cataloguing and search po rtal through also the CSW protocol; eventually MapStore was used to implement the mash-up front-end. The innovative aspect of this po rtal is the fact that it currently is ingesting, fusing and disseminating geospatial data related to the MetOcfield from various sources in near real-time in a comp rehensive manner that allows users to create add ed value visualizations for the support of operational use cases as well as to access and download underlying data (where app licable)

Simulating the Net Primary Production of Even-Aged Forests by the Use of Remote Sensing and Ecosystem Modelling Techniques

A recently proposed modelling strategy predicts the net primary production (NPP) of forest ecosystems by combining the outputs of a NDVI-driven model, Modified C-Fix, and a bio-geochemical model, BIOME-BGC. This combination strategy takes into account the effects of forest disturbances but still assumes the presence of a mixture of differently aged trees. The application of this strategy to even-aged forests, therefore, requires a methodological advancement aimed at properly modifying the modelling of main ecosystem processes. In particular, the adaptation of the method to even-aged forests is based on the use of high-spatial-resolution airborne laser scanning (ALS) datasets, which yields green and woody biomass estimates that regulate the simulation of photosynthetic and respiratory processes, respectively. This approach was experimented in a Mediterranean study area, San Rossore Regional Park (Central Italy), which is covered by even-aged pine stands in different development phases. The modelling strategy is driven by MODIS NDVI images and meteorological data across five years (2011–2015), which are combined with estimates of forest canopy cover and height obtained from ALS data taken in 2015. This allows the production of stand NPP estimates, which, when converted into respective current annual increment (CAI) values, reasonably reproduce the age dependency of the available ground observations. The CAI estimates also show a highly significant correlation with these observations (r = 0.773) and moderate error levels (RMSE = 2.03 m3 ha−1 year−1, MBE = −0.45 m3 ha−1 year−1). These results confirm the potential of the modified simulation method to yield accurate high-spatial-resolution NPP estimates, which can offer valuable insights into C cycling and storage, in even-aged forests