María José Estrela

Torrential precipitations on the Spanish east coast: The role of the Mediterranean sea surface temperature

Abstract Floods constitute one of the most important natural risks on the Spanish Mediterranean coast. Although it is very difficult to avoid them, a correct understanding of their principal cause, which is torrential rain, can facilitate their prediction and in this way avoid, at least partially, their catastrophic effects (both loss of human lives and material damage). The work presented here is part of a more extensive study underway in the CEAM (Centro de Estudios Ambientales del Mediterraneo). Its objective is the analysis of the conditions that produce torrential precipitations. These can be explained by the hypothesis of the Back Door Front, a mechanism which on its own permits the development of a potentially unstable mass above the Mediterranean sea. Among the different factors that are valued in this hypothesis, the Sea Surface Temperature is considered to play an important role. It is studied by means of satellite images since this is the only technique that permits a synoptic view of this parameter. NOAH satellite images have been used, applying the split-window operative technique. This work presents initial results that confirm the importance of the Sea Surface Temperature (SST) as a moisture source in the Mediterranean cyclogenesis.

Design and development of a Java-based graphical user interface to monitor/control a meteorological real-time forecasting system

A regional forecasting system based on the Regional Atmospheric Modeling System (RAMS) is being run at the CEAM Foundation. The operational model involves several processes running in the background at specified times and executing a set of systematic steps. This system is being used as a support for a heat-wave warning system, a wind forecasting system for fire warning and prevention, and for general forecasting tasks. However, it is relatively difficult to use by researchers and forecasters without sophisticated information technology (IT) skill. In this paper, we report an effort to develop a tool to facilitate the monitoring of the system. This tool is based on the client-server architecture and enables those with little IT skill to monitor/control the state of the different processes involved in the real-time simulation. This tool has been successfully used in controlling the RAMS-based applications developed at CEAM since 2006. The design and the functionality and utilities of the tool reviewed in this paper could be exported and customized to be used by other research centres and institutions who offer services based on operational atmospheric models as routine jobs (MM5, WRF, etc.), as e.g. air pollution forecasting systems, other prevention and emergency response systems, etc.

Verification of the RAMS-based operational weather forecast system in the Valencia Region: a seasonal comparison

The meteorological model Regional Atmospheric Modeling System (RAMS) in its version 4.4 has been applied operationally within the Valencia Region. The model output is being used as support for a heat-wave warning system, a wind forecasting system for fire warnings and prevention, and for general forecasting tasks. For the winter period of 2010–2011 and the summer period of 2011, the model version 6.0 has been included within the operational forecast environment. In this study, the verification of the model using both versions has been performed taking advantage of the automatic weather stations from the CEAM network and located within this area. Surface meteorological observations have been compared with the RAMS forecasts in an operational verification focused on computing different statistical data for coastal and inland stations. This verification process has been carried out both for the summer and the winter seasons of the year separately. As a result, it has been revealed that the model presents significant differences in the forecast of the meteorological variables analyzed throughout both periods of the year. Moreover, the model presents different degrees of accuracy between coastal and inland stations as well as for both versions of RAMS for the meteorological variables investigated. On the other hand, we have also found that there is little difference in the magnitudes analyzed within the two daily RAMS cycles and that RAMS is very stable in maintaining skillful forecast results at least for three forecast days, although the performance of the simulation slightly decreases as the simulation moves forward.

Seasonal Characterization of Solar Radiation Estimates Obtained from a MSG-SEVIRI-Derived Dataset and a RAMS-Based Operational Forecasting System over the Western Mediterranean Coast

Solar radiation is a key factor in the Earth’s energy balance and it is used as a crucial input parameter in many disciplines such as ecology, agriculture, solar energy and hydrology. Thus, accurate information of the global downward surface shortwave flux integration into the grid is of significant importance. From the different strategies used for grid integration of the surface solar radiation estimates, satellite-derived and numerical weather prediction forecasts are two interesting alternatives. In the current work, we present a comprehensive evaluation of the global downward solar radiation forecasts provided by the Regional Atmospheric Modeling System (RAMS) and the Downwelling Surface Shortwave Flux (DSSF) product, derived from the Meteosat Second Generation (MSG) Spinning Enhanced Visible and Infrared Imager (SEVIRI). Both solar radiation estimates are compared to thirteen ground-based weather station measurements for the winter 2010–2011 and the summer 2011 seasons. For these periods, the most recent versions of RAMS (4.4 and 6.0) were running in parallel within the real-time weather forecasting system implemented over the Valencia Region. The solar radiation performance and accuracy are evaluated for these datasets segmented into two atmospheric conditions (clear and cloudy skies) and two terrain classes (flat and hilly). DSSF shows a very good agreement over the study area. Statistical daily evaluations show that corresponding errors vary between seasons, with absolute bias ranging from −30 to 40 W·m−2, absolute root mean square errors (RMSE) from 25 to 60 W·m−2, relative bias ranging from −11% to 7% and relative RMSE from 7% to 22%, depending on the sky condition and the terrain location as well, thus reproducing the observations more faithfully than RAMS, which produces higher errors in comparison to the measurements. In this regard, statistical daily evaluations show absolute bias values varying from −50 to 160 W·m−2, absolute RMSE from 60 to 240 W·m−2, relative bias ranging from −30% to 40% and relative RMSE from 10% to 80%, also depending on the daily initialization and the forecast horizon. This bias variability demonstrates that there is a different trend in the deviation of the model results in relation to the observations, both for the DSSF product and RAMS forecasts, and considering the summer and the winter seasons independently. In this regard, although there is an overestimation of the observed solar radiation within the summer months, this magnitude is underestimated during the winter. Finally, comparing this solar radiation estimates for different atmospheric conditions and different terrain classes, the best results are found under clear skies over flat terrain. This result is achieved using both methodologies.

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.

Improvement of the Valencia region ultraviolet index (UVI) forecasting system

The CEAM Foundation (Valencia, Spain) has developed an operational ultraviolet index (UVI) forecasting system based on the Santa Barbara DISORT Atmospheric Radiative Transfer (SBDART) model. The main objective of this system is to provide the general public with a tool to minimize the impact of ultraviolet (UV) radiation, which can cause important human health problems. The system presented in this paper has been developed in collaboration with the Environment Department of the Regional Government of Valencia, and it replaces the one running until 2007. The new system substitutes the previously used Ozone Monitoring Instrument (OMI) observed data with the total ozone column data forecasted from the Global Forecasting System (GFS) model. This has allowed the forecasting period to be increased from only 1 day in the original system to 3 days, with daily updates. The UVI forecast presented herein uses maps to show the hourly daytime evolution of the UV index on selected locations as well as the maximum UVI expected in the area of interest for the following 3 days (D, D+1, and D+2). The locations selected correspond to measurement stations equipped with erythemal radiation instruments. The UVI forecast information, the erythemal radiation experimental data, and other outreach information are supplied to the public through both the CEAM Meteorology and Climatology Program Web page and the Environment Department of the Regional Government of Valencia Web page.

An angular-dependent split-window equation for SST retrieval from off-nadir observations

An angular-dependent split-window equation is proposed for determining the Sea Surface Temperature (SST) at any observation angle, including large viewing angles at the image edges of satellite sensors with wide swaths. The proposed equation takes into account the angular dependences of the atmospheric correction and also the emissivity correction. An explicit dependence on the SSE is considered in an independent term. The inclusion of such a term is not common in the current operational SST algorithms but we consider it appropriate taking into account the non-blackness of the sea surface emission for large angles and also the dependence on wind speed. The equation has been adapted to the Moderate Resolution Imaging Spectrometer (MODIS) on board EOS-Terra and EOS- Aqua, with at surface observation angles up to 65deg, and to the Spinning Enhanced Visible and Infrared Imager (SEVIRI) on board MSG, with even larger observation angles. Angular- dependent coefficients were estimated for the atmospheric and emissivity terms using synthetic data generated from a series of cloud-free, latitude-equally distributed radio sounding profiles. The use of the proposed expression requires as input data: at- sensor brightness temperatures for the split-window bands, the observation angle at each pixel, an estimate of the water vapor content and accurate SSE values for both channels. A comparison of the results of the equation for MODIS with in-situ measurements gathered from different NOAA ships and buoys placed around the world showed an accuracy of about plusmn 0.3 K for any observation angle, including off-nadir viewings, while the MODIS operational algorithm leaded to an error of plusmn 0.7 K at large angles. The proposed technique is mainly recommended to retrieve SST from observations at large viewing angles, since similar values are obtained by the current operational algorithms for nadir viewings.

Improved meteorology and surface energy 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.