Un centro de estudios de etnología peninsular en Oporto.

El Centro de Estudio de Etnología Peninsular de Oporto se inauguró en abril de 1945 y se nombró Director al antropólogo y profesor de la Universidad de Oporto, Doctor Mendes Correia, para mostrar el acercamiento existente entre las naciones española y portuguesa. En la inauguración tomó la palabra el profesor Amandio Tavares, que expuso los objetivos culturales del Instituto y homenajeo con sus palabras al Consejo Superior de Investigaciones Científicas. Le siguió en discurso el profesor Albareda, del que se reproduce el discurso. Seguidamente, tomó la palabra el Dtor. del Centro, Dr. Mendes Correira, que expresó la necesidad que existía de un centro como aquel. El Dr. José María Torroja, pronunció una conferencia del cursillo sobre las obras públicas en España después de la guerra. Finalmente, el acto terminó con un discurso del Rector recalcando la importancia de lo que se celebraba.

El proyecto posidonia : un aula flotante para el litoral del sureste peninsular.

La Asociación de Naturistas del Sureste (ANSE) de Cartagena, utiliza un antiguo velero de madera decomisado por tráfico de drogas en la costa cartagenera, con el objetivo de llevar a cabo actividades de la Escuela del Mar: trabajos de investigación relacionados con la gea, vegetación y fauna sumergidas, así como de acciones reivindicativas y de protesta contra la realización de actividades que deterioran el medio ambiente litoral, todo ello enmarcado en un proyecto educativo denominado Posidonia que incluye, además de las mencionadas, actividades de vela tradicional, pesca y observación y estudio de la fauna y flora del tramo costero. El proyecto se dirige a alumnos (secundaria) y profesores (cursos de formación).

Stochastic modelling of rainfall from satellite data

Satellite-based rainfall monitoring is widely used for climatological studies because of its full global coverage but it is also of great importance for operational purposes especially in areas such as Africa where there is a lack of ground-based rainfall data. Satellite rainfall estimates have enormous potential benefits as input to hydrological and agricultural models because of their real time availability, low cost and full spatial coverage. One issue that needs to be addressed is the uncertainty on these estimates. This is particularly important in assessing the likely errors on the output from non-linear models (rainfall-runoff or crop yield) which make use of the rainfall estimates, aggregated over an area, as input. Correct assessment of the uncertainty on the rainfall is non-trivial as it must take account of • the difference in spatial support of the satellite information and independent data used for calibration • uncertainties on the independent calibration data • the non-Gaussian distribution of rainfall amount • the spatial intermittency of rainfall • the spatial correlation of the rainfall field This paper describes a method for estimating the uncertainty on satellite-based rainfall values taking account of these factors. The method involves firstly a stochastic calibration which completely describes the probability of rainfall occurrence and the pdf of rainfall amount for a given satellite value, and secondly the generation of ensemble of rainfall fields based on the stochastic calibration but with the correct spatial correlation structure within each ensemble member. This is achieved by the use of geostatistical sequential simulation. The ensemble generated in this way may be used to estimate uncertainty at larger spatial scales. A case study of daily rainfall monitoring in the Gambia, west Africa for the purpose of crop yield forecasting is presented to illustrate the method.

Evaluation of reanalysis rainfall estimates over Ethiopia

There is a pressing need for good rainfall data for the African continent both for humanitarian and climatological purposes. Given the sparseness of ground-based observations, one source of rainfall information is Numerical Weather Prediction (NWP) model outputs. The aim of this article is to investigate the quality of two NWP products using Ethiopia as a test case. The two products evaluated are the ERA-40 and NCEP reanalysis rainfall products. Spatial, seasonal and interannual variability of rainfall have been evaluated for Kiremt (JJAS) and Belg (FMAM) seasons at a spatial scale that reflects the local variability of the rainfall climate using a method which makes optimum use of sparse gauge validation data. We found that the spatial pattern of the rainfall climatology is captured well by both models especially for the main rainy season Kiremt. However, both models tend to overestimate the mean rainfall in the northwest, west and central regions but underestimate in the south and east. The overestimation is greater for NCEP in Belg season and greater for ERA-40 in Kiremt Season. ERA-40 captures the annual cycle over most of the country better than NCEP, but strongly exaggerates the Kiremt peak in the northwest and west. The overestimation in Kiremt appears to have been reduced since the assimilation of satellite data increased around 1990. For both models the interannual variability is less well captured than the spatial and seasonal variability. Copyright © 2008 Royal Meteorological Society

Geostatistical Tools for Validation of Satellite and NWP Model Rainfall

Influence of south Atlantic sea surface temperatures on rainfall variability and extremes over southern Africa

It is generally agreed that changing climate variability, and the associated change in climate extremes, may have a greater impact on environmentally vulnerable regions than a changing mean. This research investigates rainfall variability, rainfall extremes, and their associations with atmospheric and oceanic circulations over southern Africa, a region that is considered particularly vulnerable to extreme events because of numerous environmental, social, and economic pressures. Because rainfall variability is a function of scale, high-resolution data are needed to identify extreme events. Thus, this research uses remotely sensed rainfall data and climate model experiments at high spatial and temporal resolution, with the overall aim being to investigate the ways in which sea surface temperature (SST) anomalies influence rainfall extremes over southern Africa. Extreme rainfall identification is achieved by the high-resolution microwave/infrared rainfall algorithm dataset. This comprises satellite-derived daily rainfall from 1993 to 2002 and covers southern Africa at a spatial resolution of 0.1° latitude–longitude. Extremes are extracted and used with reanalysis data to study possible circulation anomalies associated with extreme rainfall. Anomalously cold SSTs in the central South Atlantic and warm SSTs off the coast of southwestern Africa seem to be statistically related to rainfall extremes. Further, through a number of idealized climate model experiments, it would appear that both decreasing SSTs in the central South Atlantic and increasing SSTs off the coast of southwestern Africa lead to a demonstrable increase in daily rainfall and rainfall extremes over southern Africa, via local effects such as increased convection and remote effects such as an adjustment of the Walker-type circulation.