Impact of Initial Soil Temperature Derived from Remote Sensing and Numerical Weather Prediction Datasets on the Simulation of Extreme Heat Events

Extreme heat weather events have received increasing attention and has become of special importance as they can remarkably affect sectors as diverse as public health, energy consumption, water resources, natural biodiversity and agricultural production. In this regard, summer temperatures have become a parameter of essential interest under a framework of a hypothetical increase in the number of intense-heat conditions. Thus, their forecast is a crucial aspect bearing in mind a mitigation of the effects and impacts that these intense-heat situations could produce. The current work tries to reach a better understanding of these sorts of situations that are really common over the Western Mediterranean coast. An extreme heat episode that took place in the Valencia Region in July 2009 is analysed, based on the simulations performed with the Regional Atmospheric Modeling System (RAMS). This event recorded maximum temperatures exceeding 40 °C amply extended over the region besides reaching minimum temperatures up to 25.92 °C. We examine the role of improved skin and soil temperature (ST) initial conditions in the forecast results by means of different modelling and satellite-derived products. The influence of incorporating the Land Surface Temperature (LST) into RAMS is not found to produce a meaningful impact on the simulation results, independently of the resolution of the dataset used in the initial conditions of the model. In contrast, the introduction of the ST in lower levels, not only the skin temperature, has a more marked decisive effect in the simulation. Additionally, we have evaluated the influence of increasing the number of soil levels to spread deeper underground. This sensitivity experiment has revealed that more soil levels do not produce any meaningful impact on the simulation compared to the original one. In any case, RAMS is able to properly capture the observed patterns in those cases where a Western advection is widely extended over the area of study. This region’s variability in orography and in distances to the sea promotes the development of sea-breeze circulations, thus producing a convergence of two opposite wind flows, a Western synoptic advection and a sea-breeze circulation. As a result, the RAMS skill in those cases where a sea breeze is well developed depends on the proper location of the boundary and convergence lines of these two flows.This work has been funded by the Spanish Ministerio de Economía y Competitividad and the European Regional Development Fund (FEDER) through the project CGL2015-64268-R (MINECO/FEDER, UE), by the Regional Government of Valencia through the project PROMETEOII/2014/086 and by the Spanish Ministerio de Economía y Competitividad through the project CGL2011-30433-C02-02 (MINECO)

Improved meteorology and surface fluxes in mesoscale modelling using adjusted initial vertical soil moisture profiles

The Regional Atmospheric Modeling System (RAMS) is being used for different and diverse purposes, ranging from atmospheric and dispersion of pollutants forecasting to agricultural meteorology and ecological modelling as well as for hydrological purposes, among others. The current paper presents a comprehensive assessment of the RAMS forecasts, comparing the results not only with observed standard surface meteorological variables, measured at FLUXNET stations and other portable and permanent weather stations located over the region of study, but also with non-standard observed variables, such as the surface energy fluxes, with the aim of evaluating the surface energy budget and its relation with a proper representation of standard observations and key physical processes for a wide range of applications. In this regard, RAMS is assessed against in-situ surface observations during a selected period within July 2011 over Eastern Spain. In addition, the simulation results are also compared with different surface remote sensing data derived from the Meteosat Second Generation (MSG) Spinning Enhanced Visible and Infrared Imager (SEVIRI) (MSG-SEVIRI) as well as the uncoupled Land Surface Models (LSM) Global Land Data Assimilation System (GLDAS). Both datasets complement the available in-situ observations and are used in the current study as the reference or ground truth when no observations are available on a selected location. Several sensitivity tests have been performed involving the initial soil moisture content, by adjusting this parameter in the vertical soil profile ranging from the most superficial soil layers to those located deeper underground. A refined adjustment of this parameter in the initialization of the model has shown to better represent the observed surface energy fluxes. The results obtained also show an improvement in the model forecasts found in previous studies in relation to standard observations, such as the air temperature and the moisture fields. Therefore, the application of a drier or wetter soil in distinct soil layers within the whole vertical soil profile has been found to be crucial in order to produce a better agreement between the simulation and the observations, thus reiterating the determining role of the initial soil moisture field in mesoscale modelling, but in this case considering the variation of this parameter vertically

Impact of Noah-LSM Parameterizations on WRF Mesoscale Simulations: Case Study of Prevailing Summer Atmospheric Conditions over a Typical Semi-Arid Region in Eastern Spain

The current study evaluates the ability of the Weather Research and Forecasting Model (WRF) to forecast surface energy fluxes over a region in Eastern Spain. Focusing on the sensitivity of the model to Land Surface Model (LSM) parameterizations, we compare the simulations provided by the original Noah LSM and the Noah LSM with multiple physics options (Noah-MP). Furthermore, we assess the WRF sensitivity to different Noah-MP physics schemes, namely the calculation of canopy stomatal resistance (OPT_CRS), the soil moisture factor for stomatal resistance (OPT_BTR), and the surface layer drag coefficient (OPT_SFC). It has been found that these physics options strongly affect the energy partitioning at the land surface in short-time scale simulations. Aside from in situ observations, we use the Meteosat Second Generation (MSG) Spinning Enhanced Visible and Infrared Imager (SEVIRI) sensor to assess the Land Surface Temperature (LST) field simulated by WRF. Regarding multiple options in Noah-MP, WRF has been configured using three distinct soil moisture factors to control stomatal resistance (β factor) available in Noah-MP (Noah, CLM, and SSiB-types), two canopy stomatal resistance (Ball–Berry and Jarvis), and two options for surface layer drag coefficients (Monin–Obukhov and Chen97 scheme). Considering the β factor schemes, CLM and SSiB-type β factors simulate very low values of the latent heat flux while increasing the sensible heat flux. This result has been obtained independently of the canopy stomatal resistance scheme used. Additionally, the surface skin temperature simulated by Noah-MP is colder than that obtained by the original Noah LSM. This result is also highlighted when the simulated surface skin temperature is compared to the MSG-SEVIRI LST product. The largest differences between the satellite data and the mesoscale simulations are produced using the Noah-MP configurations run with the Monin–Obukhov parameterization for surface layer drag coefficients. In contrast, the Chen97 scheme shows larger surface skin temperatures than Monin–Obukhov, but at the expense of a decrease in the simulated sensible heat fluxes. In this regard, the ground heat flux and the net radiation play a key role in the simulation results.This research was funded by the Assistance Programmes of the University of Alicante “Programa de Redes-I3CE de calidad, innovación e investigación en docencia universitaria. Convocatoria 2018–2019. Alicante: Instituto de Ciencias de la Educación (ICE) de la Universidad de Alicante. Ref: [4334].” and “Programa de Redes-I3CE de calidad, innovación e investigación en docencia universitaria. Convocatoria 2020-21. Alicante: Instituto de Ciencias de la Educación (ICE) de la Universidad de Alicante. Ref: [5150].” as well as by Research Group VIGROB-116 (University of Alicante) and by the Spanish Ministerio de Ciencia e Innovación through the project PID2020-118797RB-I00/AEI

Daily grass reference evapotranspiration with Meteosat Second Generation shortwave radiation and reference ET products

This study assesses the accuracy of estimating daily grass reference evapotranspiration (PM-ETo) using daily shortwave radiation (Rs) and reference evapotranspiration (ETREF) products provided by the Meteosat Second Generation (MSG) geostationary satellite delivered by the Satellite Applications Facility on Land Surface Analysis (LSA-SAF) framework. The accuracy of using reanalysis ERA5 shortwave radiation data (Rs ERA5) provided by the European Center for Medium-Range Weather Forecasts (ECMWF) is also evaluated. The assessments were performed using observed weather variables at 37 weather stations distributed across continental Portugal, where climate conditions range from semi-arid to humid, and 12 weather stations located in Azores islands, characterized by humid, windy and often cloudy conditions. This study’s use of data from a variety of climate conditions contributed to a unique and innovative assessment of the usability of LSA-SAF and ERA5 products for ETo estimation. The first assessment focused on comparing LSA-SAF estimates of Rs (Rs LSA-SAF) against ground stations (Rs ground). The results showed a good matching between the two Rs data sets for continental Portugal but a tendency for Rs LSA-SAF to under-estimate Rs ground in the cloudy islands of Azores. ETo values computed using Rs LSA-SAF data and observed temperature, humidity and wind speed (ETo LSA-SAF) were then compared with PMETo estimates with ground-based data, which were used as benchmark; input data of temperature and humidity needed for PM-ETo were quality checked for surface aridity effects. It was observed that ETo LSA-SAF is strongly correlated with PM-ETo (R2 > 0.97) for most locations in continental Portugal, with regression coefficient of a linear regression forced to the origin ranging between 0.95 and 1.05, mean root mean square error (RMSE) of 0.13 mm d 1, and Nash and Sutcliff efficiency of modeling (EF) above 0.95. For most Azores locations, ETo LSA-SAF over-estimated PM-ETo. This is likely a consequence of the high spatio-temporal heterogeneity of weather conditions that occur in these oceanic islands together with the different footprints of satellite (averaged over the pixel) and station observations. Reanalysis ERA5 shortwave radiation data presented similar behavior to the LSA-SAF products, however with slightly lower accuracy. The daily LSA-SAF ETREF product (ETREF LSA-SAF) was assessed and results have shown a good accuracy of this product, with acceptable RMSE and high EF values, for continental Portugal but a low accuracy for the Azores islands. A simplified bias correction approach was shown to improve both ETo derived from the LSA-SAF products, namely for Azores stations, which seem to be representative of smaller areas. The use of the FAO-PM temperature approach (PMT) was also assessed using the Rs LSA-SAF and Rs ERA5 data, which showed a superiority of the LSA-SAF product for ETo estimations (ETo PMT LSA-SAF). No significant differences (p < 0.05) were observed in terms of the median value of the RMSE when adopting ETo PMT and ETREF LSA-SAF. Differently, results showed that using the Rs LSA-SAF in the PMT approach (ETo PMT LSA-SAF) produces significantly better RMSE results than ETo PMT and ETREF LSA-SAF. Overall, the performed assessment allows concluding that the use of Rs LSA-SAF, and to a lesser extent the use of the Rs ERA5, highly improves the accuracy of computation of ETo when Rs observations are not available, including when only temperature data are accessible. The use of the ETREF LSA-SAF product is a good alternative when observed weather data are not availableinfo:eu-repo/semantics/publishedVersio

Modelling the atmospheric controls and climate impact of mineral dust in the Sahara Desert

Mineral dust aerosols play an important role in climate and the Earth's energy budget. The effect of dust on the radiative forcing is uncertain due to the complexity of particle properties and the complexity to quantify and discriminate preferential dust sources. This research considers the potential of two Regional Climate Models (RCM’s): The Weather Research and Forecasting model (WRF-Chem) and the Regional Climate Model (RegCM3) both with an integrated dust module. Numerical sensitivity experiments are performed to quantify the ability of both models to simulate sources, the magnitude of dust emission, the transport in 3-dimensions and the subsequent impact on the radiative forcing. Particular emphasis is given to preferential source regions within the Sahara and Sahel in North Africa including the Bodélé Depression in Northern Chad. To account for the distribution of preferential dust source regions, soil texture characteristics were modified in dust source regions in RegCM3. As for WRF-Chem GOCART scheme, a new higher resolution erodible fraction map is tested. Moreover, the sensitivity of the results to the specification of aerosol optical properties to evaluate the impacts of optical characteristics on the radiative forcing was considered for the RegCM3. Finally, model outputs are compared to in-situ data: weather stations (WMO) and AERONET and satellite estimates: MODIS, MISR, OMI, CALIPSO and SEVIRI. Results show that both models represent the space/time structure of near-surface meteorology well. The tuning of preferential dust sources tested in this research provides a more realistic representation of local dust sources, emissions and resulting AOT. This suggest that in the absence of truly accurate soil maps at high resolution, further refinements to preferential sources map and its implementation in dust models can lead to useful improvements in simulation of dust processes and dust forecast accuracy

The use of satellite data, meteorology and land use data to define high resolution temperature exposure for the estimation of health effects in Italy

Introduction. Despite the mounting evidence on heat-related health risks, there is limited evidence in suburban and rural areas. The limited spatial resolution of temperature data also hinders the evidence of the differential heat effect within cities due to individual and area-based characteristics. Methods. Satellite land surface temperature (LST), observed meteorological and spatial and spatio-temporal land use data were combined in mixed-effects regression models to estimate daily mean air temperature with a 1x1km resolution for the period 2000-2010. For each day, random intercepts and slopes for LST were estimated to capture the day-to-day temporal variability of the Ta–LST relationship. The models were also nested by climate zones to better capture local climates and daily weather patterns across Italy. The daily exposure data was used to estimate the effects and impacts of heat on cause-specific mortality and hospital admissions in the Lazio region at municipal level in a time series framework. Furthermore, to address the differential effect of heat within an urban area and account for potential effect modifiers a case cross-over study was conducted in Rome. Mean temperature was attributed at the individual level to the Rome Population Cohort and the urban heat island (UHI) intensity using air temperature data was calculated for Rome. Results. Exposure model performance was very good: in the stage 1 model (only on grid cells with both LST and observed data) a mean R2 value of 0.96 and RMSPE of 1.1°C and R2 of 0.89 and 0.97 for the spatial and temporal domains respectively. The model was also validated with regional weather forecasting model data and gave excellent results (R2=0.95 RMSPE=1.8°C. The time series study showed significant effects and impacts on cause-specific mortality in suburban and rural areas of the Lazio region, with risk estimates comparable to those found in urban areas. High temperatures also had an effect on respiratory hospital admissions. Age, gender, pre-existing cardiovascular disease, marital status, education and occupation were found to be effect modifiers of the temperature-mortality association. No risk gradient was found by socio-economic position (SEP) in Rome. Considering the urban heat island (UHI) and SEP combined, differential effects of heat were observed by UHI among same SEP groupings. Impervious surfaces and high urban development were also effect modifiers of the heat-related mortality risk. Finally, the study found that high resolution gridded data provided more accurate effect estimates especially for extreme temperature intervals. Conclusions. Results will help improve heat adaptation and response measures and can be used predict the future heat-related burden under different climate change scenarios.Open Acces

Influence of land cover in the atmospheric water vapor content and the generation of summer storms in the Turia River Basin

Les tronades d'estiu representen una font d’aigua important en la conca mediterrània, ja que aporten aigua durant els mesos més secs de l’any, amb la qual cosa ajuden a mantenir els cabdals dels principals rius. Aquests sistemes convectius estan associats a les circulacions de brisa que dominen durant l'estiu. La brisa es canalitza a través de les valls assolint les capçaleres dels principals rius on es generen línies de convergència, és a dir, zones on les masses d’aire superficials s’injecten a capes més altes de l’atmosfera i donen lloc a aquest tipus de fenòmens meteorològics. A part de la topografia, altres factors que poden influenciar la formació de tronades d'estiu són els fluxos superficials de calor latent i sensible, ja que modifiquen les propietats de les masses d'aire advectades amb la brisa i que intervenen en el desenvolupament d'aquests sistemes convectius. En aquest context, en la present tesi s'estudien les interaccions entre el sòl i l’atmosfera amb l'objectiu principal de quantificar el paper que juguen els usos del sòl en la formació i desenvolupament de tronades d'estiu en situacions de brisa. En aquesta tesi doctoral es du a terme un detallat anàlisi de l’impacte de la brisa en les interaccions sòl-vegetació-atmosfera (SVA) emprant diferents tipus d’observacions, i també exercicis de modelització numèrica. La principal eina de treball és el model meteorològic Weather Research and Forecasting amb el qual es duen a terme simulacions a molt alta resolució espacial i temporal. Dues aproximacions s’han utilitzat en aquesta tesi per a estudiar la rellevància de les interaccions SVA i les contribucions de la superfície a la recàrrega de vapor d’aigua atmosfèric i l’escalfament de l’aire en situacions prèvies a la formació de tronades d’estiu. D’una banda, els intercanvis en el sistema SVA s’han calculat amb els diagrames de mescla que representen les variacions de temperatura potencial en funció de la humitat en l’espai energia per unitat de massa. D’altra banda, les contribucions per part de la superfície al contingut en vapor d’aigua atmosfèric i a l’escalfament de les masses d’aire també s’han analitzat des d’un punt de vista Lagrangià. Concretament, s’han extret trajectòries associades a la formació de tronades d’estiu i a circulacions de brisa i s’han calculat les contribucions des de la superfície i l’efecte de l’entrainment. En general els resultats indiquen un marcat impacte dels fluxos de calor en superfície que representen un 40% de l'increment total en temperatura potencial, de mitjana, en contrast amb l'increment d'humitat associats a la evapotranspiració que representen un 7% de la humitat present abans del desenvolupament de les tronades. A més, l'entrainment, la incorporació d'aire més sec al corrent de brisa, és el principal factor en les variacions de temperatura i humitat durant les circulacions de brisa. Respecte als usos del sòl, les contribucions més marcades al vapor d’aigua atmosfèric i l’escalfament de la brisa es produeixen a la zona litoral en reació al menor desenvolupament de la capa límit. Les zones urbanes són les que generen un major escalfament de l’aire, mentre que els camps de cultiu aporten la major part del vapor d’aigua

Characterisation of dust sources in Central Asia using remote sensing

Central Asian deserts are a significant source of dust in the middle latitudes, where economic activity and the health of millions of people are affected by dust storms. Detailed knowledge of sources of dust, controls on their activity, seasonality and atmospheric pathways are of crucial importance but to date, these data are limited. This thesis presents a detailed database ofsources ofdust emissions in Central Asia, from western China to the Caspian Sea, obtained by a multi-scale analysis of the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite data. The multi-scale approach consists of the following steps: 1) MODIS Deep Blue Aerosol Optical Depth (DB AOD) at 10 km resolution, acquired between 2003 and 2014, is used to investigate the spatiotemporal distribution ofdust hotspots. 2) A dust enhancement algorithm was employed to obtain two composite images (Dust Enhancement Product, DEP) per day at 1 km resolution from MODIS Terra/Aqua acquisitions between 2003 and 2012, from which dust point sources (DPS) were detected by visual analysis of dust plumes and recorded in a database together with meteorological variables at each DPS location derived from the ERA-Interim reanalysis dataset. In all, more than 13500 DPS were identified. Using this multi-scale approach we provided a high resolution inventory of dust sources at sub-basin scale for Central Asia. Our analysis revealed several active source regions, the most active of which are the eastern part ofthe Taklmakan desert. An important finding was an increase in dust activity in the newly-formed desert ofthe Aralkum. Several ofthe identified dust source regions were not previously identified (e.g. sources in northern Afghanistan) or were not widely discussed in literature before (e.g. the Pre-Aral region in western Kazakhstan). Investigation of land surface characteristics and meteorological conditions at each source region revealed mechanisms for the formation of dust sources, including rapid desiccation of water bodies (e.g. Aral Sea), deflation of dust from fluvial sources (e.g. the Upper Amudarya region) and post-fire wind erosion (e.g. Pre-Aral and Lake Balkhash basins). Different seasonal patterns of dust emissions were observed as well as inter-annual trends. Comparison of DB AOD and DPS revealed a noticeable spatial bias in the AOD-based methods for detection of dust sources which is attributed to the fact that the highest atmospheric dust loadings are not always observed over the dust point sources