SARS-CoV-2 Vaccines and the Skin

Coronavirus SARS-CoV-2; COVID-19; 2019-nCoV; Skin reactions; VacinesCoronavirus SARS-CoV-2; COVID-19; 2019-nCoV; Reacciones cutáneas; VacunasCoronavirus SARS-CoV-2; COVID-19; 2019-nCoV; Reaccions cutànies; VacunesVaccines against the severe acute respiratory coronavirus 2, which are the first to be used in humans against any coronavirus, were developed and produced in record time. Dermatologic adverse effects appeared during clinical trials and have also been described in the population since approval. Just as descriptions and categorization of skin manifestations of the coronavirus disease 2019 proved important for understanding the disease itself, characterizing the effects of vaccines may also further that goal. This paper reviews the properties of the different types of vaccines currently available and under development and describes how they interact with the immune system and the clinical signs they may cause. We focus on dermatologic adverse effects reported to date and recommendations for managing them

An agent-based model of firm location with different regional policies

This paper presents an agent based model of firm location designed to explore the effect of regional policies on the spatial pattern of business activity. New firms are created each period taking into account the sector profitability and entry barriers. Firms choose their location and then they decide sequentially whether change their size or cease their activity accordingly to the profit maximization principle and the limited information they have. Their costs depend not only on the production level and the price of the productive factors but also on the land price. The characteristics of the territory where the firms are located are not static but rather evolve depending on the public policies, demographic variables and the firm localization patterns. The presented model shows endogenous rules of firm localization as well as the effects in the medium and long term of public policies

Predictability of precipitation with Aemet multimodel SREPS: assessment using HR observations (yavtobos)

Presentación realizada para: 30th EWGLAM & 15th SRNWP Meetings celebrado del 6 al 9 de octubre de 2008 en Madrid.This project is partially supported by the Spanish Ministry of Education under research projects CGL2004-04095/CLI and CGL2005-05681

Performance of the INM short-range multi-model ensemble using high resolution precipitation observations

Presentación realizada en: 3rd International Workshop on Verification Methods celebrado del 29 de enero al 2 de febrero de 2007 en Reading, Reino Unido

Predictability of short-range forecasting: a multimodel approach

Numerical weather prediction (NWP) models (including mesoscale) have limitations when it comes to dealing with severe weather events because extreme weather is highly unpredictable, even in the short range. A probabilistic forecast based on an ensemble of slightly differentmodel runs may help to address this issue. Among other ensemble techniques, Multimodel ensemble prediction systems (EPSs) are proving to be useful for adding probabilistic value to mesoscale deterministic models. A Multimodel Short Range Ensemble Prediction System (SREPS) focused on forecasting the weather up to 72 h has been developed at the panishMeteorological Service (AEMET). The system uses five different limited area models (LAMs), namely HIRLAM (HIRLAM Consortium), HRM (DWD), the UM (UKMO), MM5 (PSU/NCAR) and COSMO (COSMO Consortium). These models run with initial and boundary conditions provided by five different global deterministic models, namely IFS (ECMWF), UM (UKMO), GME (DWD), GFS (NCEP) and CMC (MSC). AEMET-SREPS (AE) validation on the large-scale flow, using ECMWF analysis, shows a consistent and slightly underdispersive system. For surface parameters, the system shows high skill forecasting binary events. 24-h precipitation probabilistic forecasts are verified using an up-scaling grid of observations from European high-resolution precipitation networks, and compared with ECMWF-EPS (EC)

Auscultación de presas y su aplicación al estudio de gradientes hidráulicos

Las características morfológicas de la Presa de Las Fitas, presa de materiales sueltos con núcleo de arcilla. Así como las propias del terreno en que se ubica (compuesto por un sustrato terciario dominado por argilitas y limolitas con paquetes intercalados de arenisca de pequeño espesor), obliga a tener controladas en todo momento las filtraciones de agua a través del cimiento de la presa. Para ello se disponen de una serie de elementos de auscultación que de modo continuo están recogiendo información, tanto del cuerpo de presa como de sus interacciones con distintos elementos del contorno. En base a los datos de necesario control para prevenir y salvaguardar la integridad de la presa, se diseñaron unas secciones tipo con la distinta instrumentación que se requería. Del mismo modo, aguas abajo y fuera del cuerpo de presa, se disponen aforadores que permiten controlar las filtraciones a través de la cerrada. Con el análisis de los datos de esta instrumentación, especialmente en la fase de puesta en carga, se obtienen una serie de conclusiones que van a condicionar la futura explotación del embalse

Performance of multi-model AEMET-SREPS precipitation probabilistic forecasts over Mediterranean area

Spanish Meteorological Agency (AEMET) runs a daily experimental multi-model Short-Range Ensemble Prediction System (AEMET-SREPS). The role of the system horizontal resolution (0.25 degrees) on the performance of 24-h precipitation probabilistic forecasts, and its relation with mesoscale events, are assessed comparing the performance over the Mediterranean area and over an European Atlantic area. Gridded high resolution rain observations and standard verification measures have been used at different precipitation thresholds, while studying the dependency on seasons for a one year period (May 2007 to June 2008). As a general result, performance over the Mediterranean area is higher than over the Atlantic one, albeit some relative loss of skill is found in autumn, when mesoscale convective organization is assumed to play a more important role. So it is suggested that AEMET-SREPS system precipitation predictability over the Mediterranean in autumn could be expected to improve if the horizontal and vertical resolution is increased in order to take into account the effect of meso-beta scale, especially important for convective organization.AEMET-SREPS project is partly supported by the Spanish Ministry of Education and Science under research project CGL2008-01271 (MEDICANES)

Assessment of HARMONIE-AROME in the simulation of the convective activity associated to a subtropical transition using satellite data

Producción CientíficaSubtropical transition events (STT) are a challenge for forecasting and research due to the hybrid characteristics they give to the cyclones. The ability and skillfulness of the HARMONIE-AROME model to reproduce the cloud structure and convection associated to the October 2014 STT is here evaluated. Brightness temperature, cloud top height and accumulated precipitation are assessed against satellite data using traditional skill scores and object-based techniques specific to forecasting spatial evaluation. The results present differences in the simulation of the cyclone between the periods before and after the transition. They also show a very good performance of the model in the location of the events and a good simulation of the intensity of the variables. The performance is sub-optimal for the estimation of the sizes of the convective objects. Brightness temperature and cloud top heights yield very good results in general, with a slight overestimation in both cases. However, the model struggles to capture the accumulated precipitation. There is scarce work evaluating the HARMONIE-AROME model in this type of events; nevertheless, the results are in line with those produced by the simulations with other numerical models. The overall performance of the model is very adequate, although it might be hindered by the internal stability of the model produced by the deep-convection computation.Agencia Estatal de Investigación (PID2019-105306RB-I00/AEI/10.13039/501100011033)Ministerio de Ciencia e Innovación de España - FPI program (PRE2020-092343