Distribución probabilística de los extremos globales de precipitación.

Las precipitaciones máximas mundiales siguen un patrón matemático de distribución temporal, con un índice de precipitación (n) de máxima eficiencia entre el origen convectivo y advectivo. Habitualmente, se estima que la frecuencia de dichas precipitaciones es extraordinariamente baja, según la estadística de cada estación. Sin embargo en la isla de La Réunion se han registrado 6 récords globales desde 1958, lo cual supone una media aproximada de un récord cada 9 años. En este trabajo proponemos un método para estimar la probabilidad de retorno para conjuntos de estaciones, basado en una función potencial de la distribución de probabilidad y de la distribución temporal de la precipitación. Los resultados obtenidos muestran que los récords globales presentan una alta similitud entre sí, con una precipitación equivalente en un minuto de aproximadamente 49 ± 2 mm. Sin embargo, existen algunas diferencias; por ejemplo, el récord de 2007 (4869 mm en 4 días) presenta un valor estimado de 64 mm en un minuto. Finalmente se propone una curva de Intensidad-Duración-Frecuencia para los récords mundiales, estimándose que el retorno esperado para el actual récord es del orden de 100 años, considerando el conjunto de las estaciones que han registrado los récords. The global maximum precipitations behave according to a mathematical pattern of time distribution, with a precipitation index (n) indicating maximum effi ciency between the convective and advective origin. Usually, it is estimated that the frequency of said rainfall is extremely low, according to the statistics of each station. However, in the island of La Réunion there have been recorded 6 global records since 1958, which represents a rate of around one record every 9 years. We propose a method for estimating the probability of return for sets of stations, based on a power function of the probability distribution and temporal distribution of rainfall. The results indicate that global records show a high similarity among themselves, with an equivalent precipitation in one minute of approximately 49 ± 2 mm. However, there are some differences. For example, the record of 2007 (4869 mm in 4 days) has an estimated value of 64 mm in one minute. Finally, we introduce a curve of intensity-duration-frequency for world records, estimated that the expected return for the current record is around 100 years, considering the set of the 18 stations that have measure extreme registers

Estudio climático del exponente “n” de las curvas IDF: aplicación para la Península Ibérica

El análisis de las precipitaciones máximas suele llevarse a cabo mediante curvas IDF (Intensidad-Duración-Frecuencia), que a su vez pueden expresarse como curvas IMM (Intensidades Medias Máximas). En este trabajo, hemos desarrollado un índice “n”, definido a partir del exponente que se obtiene de ajustar las curvas climáticas IDF a las curvas IMM. Dicho índice proporciona información sobre el modo en que se alcanzan las precipitaciones máximas en una determinada zona clim´atica, atendiendo a la distribuci´on temporal relativa de las intensidades m´aximas. A partir del an´alisis clim´atico del ´ındice “n”, en la Pen´ınsula Ib´erica se pueden distinguir grandes zonas caracterizadas por m´aximos de lluvia de origen m´as tormentoso (interior peninsular) y ´areas caracterizadas por m´aximos de lluvia de origen m´as frontal (suroeste, litoral atl´antico y litoral mediterr´aneo). Adem´as, estas ´areas pueden subdividirse m´as espec´ıficamente seg´un la persistencia de las precipitaciones m´[email protected]

Estimación de flujos de energía utilizando un modelo micrometeorológico e imágenes de satélite

El creciente interés de las comunidades científicas meteorológicas, climáticas e hidrológicas por los distintos componentes del balance energético de superficie, y especialmente por la evapotranspiración, ha fomentado el desarrollo de distintos modelos micrometeorológicos para evaluar los flujos de energía de superficie a escala local. Los recientes avances en las técnicas de teledetección satelitaria podrían permitir el seguimiento de estos flujos de energía de superficie sobre zonas extensas. Sin embargo, la mayoría de los modelos actuales requieren calibraje in situ o parámetros derivados empíricamente, cosa que limita su aplicación operacional a gran escala. El objetivo de este trabajo es presentar una aproximación micrometeorológica que potencialmente podría ser usada de modo operacional junto con las imágenes de satélite para hacer un seguimiento de los flujos de energía de superficie a escala regional. En primer lugar, introducimos el marco y los detalles del modelo micrometeorológico propuesto, basado en una representación de parcela de dos fuentes del sistema de suelo-vegetación-atmósfera. La viabilidad del modelo se explora a escala local usando datos recogidos de dos ecosistemas completamente distintos. Por un lado, datos recogidos de un cultivo de maíz en Beltsville, Maryland, EEUU, durante la estación de crecimiento del verano del año 2004. Por el otro, datos de una campaña experimental realizada en un bosque boreal de Finlandia en el 2002. La comparación de los resultados con las medidas del suelo muestra un error de entre 15 y 60 W m-2 para la recuperación de la radiación neta, el flujo del calor del suelo, y los flujos de calor sensible y latentes en los dos [email protected]; [email protected]

Improving RAMS and WRF mesoscale forecasts over two distinct vegetation covers using an apprpiate thermal roughness length parameterization

Land Surface Models (LSM) have shown some difficulties to properly simulate day-time 2-m air and surface skin temperatures. This kind of models are coupled to atmospheric models in mesoscale modelling, such as the Regional Atmospheric Modeling System (RAMS) and the Weather Research and Forecasting (WRF) Model. This model coupling is used within Numerical Weather Prediction Systems (NWP) in order to forecast key physical processes for agricultural meteorology and forestry as well as in ecological modelling. The current study first evaluates the surface energy fluxes and temperatures simulated by these two state-of-the-art NWP models over two distinct vegetated covers, one corresponding to a poor and sparsely vegetated area and the other one corresponding to the tall and well-vegetated area of a forest. On the other hand, the importance of parameterizing the thermal roughness length within the LSM coupled to the corresponding atmospheric model is also evaluated. The LEAF-3 LSM is used within the RAMS modelling environment while the Noah-MP LSM is applied within WRF. Results indicate that the original version of the models underestimates the temperature during the day, more remarkably in the forested area, whereas modifications in the thermal roughness length successfully simulates the temperature and sensible heat flux forecasts over this area. This study highlights the key role of the surface exchange processes when coupling land and atmosphere models. In this regard, incorporating an extra resistance in the surface-layer parameterization through the thermal roughness length is essential to simulate well both temperatures and sensible heat fluxes, which becomes more relevant over tall and well-vegetated areas, such as a forest. This extra resistance for heat exchange prevents effective molecular diffusion in the layer between the momentum roughness length and the thermal roughness length. Additionally, an appropriate description of the canopy height permits to apply an improved surface-layer formulation over different land and vegetation covers

Comparative assessment of RAMS and WRF short-term forecasts over Eastern Iberian Peninsula using various in-situ observations, remote sensing products and uncoupled land surface model datasets

The Regional Atmospheric Modeling System (RAMS) and the Weather Research and Forecasting (WRF) mesoscale models are being used for weather and air quality studies as well as forecasting tools in Numerical Weather Prediction (NWP) systems. In the current study, we perform a comparative assessment of these models under distinct typical atmospheric conditions, classified according to the dominant wind flow and cloudiness, over Eastern Iberian Peninsula. This study is focused on the model representation of key physical processes in terms of meteorology and surface variables during a 7-days period in summer 2011. The hourly outputs produced by these two models are compared not only with observed standard surface variables, measured at different permanent weather stations located over the region of study, but also with different surface remote sensing products and uncoupled Land Surface Models (LSM) datasets. Confronting RAMS and WRF, the current study highlights relevant differences over areas near the coast when mesoscale circulations or Eastern synoptic advections are developed over the region of study. A higher moisture content is observed under these atmospheric conditions, due to the moisture transport by the sea breeze inland. In this regard, it has been found that the Eastern wind field simulated by WRF reaches inland areas and comprises a larger sea breeze extension than RAMS. This sea breeze development impacts meteorology and surface variables in locations not too close to the coast, but still affected by land-sea winds. Additionally, WRF remains more windy and moister than RAMS at night-time, while alike results are found under Western synoptic advections. The results obtained in the current paper show differences under distinct dominant atmospheric conditions, which outline further research in this field in order to achieve more general conclusions

Land surface air temperature retrieval from EOS-MODIS images

The knowledge of the spatial and temporal patterns of Surface Air Temperature (SAT) is essential to monitor a region¿s climate and meteorology, quantify surface exchange processes, improve climatic and meteorological model results, and study health and economic impacts. This work analyzed correlations between SAT and geophysical land surface variables, Land Surface Temperature (LST) mainly, to establish operative techniques to obtain spatially-continuous land SAT maps from satellite data, unlike data provided by meteorological station networks. The correlations were analyzed by using EOS-MODIS images, meteorological station network data, and geographical variables. Linear regressions with MODIS-retrieved LST data gave SAT with uncertainties higher than ±2K during daytime and of ±1.8K at night-time. Nevertheless, SAT uncertainties decreased up to ±1.2K when other satellite-retrieved surface parameters, i.e. vegetation index and albedo, together with meteorological and geographical data were considered as terms of multivariable regressions. The equations finally proposed were shown to work properly for different land covers

RAMS-forecasts comparison of typical summer atmospheric conditions over the Western Mediterranean coast

The Regional Atmospheric Modeling System (RAMS) has been used in order to perform a high-resolution numerical simulation of two meteorological events related to the most common atmospheric environments during the summer over the Western Mediterranean coast: mesoscale circulations and western synoptic advections. In this regard, we take advantage of the operational RAMS configuration running within the real-time forecasting system environment already implemented over this Mediterranean area, precisely in the Valencia Region and nearby areas. The attention of this paper is especially focused on identifying the main features of both events and the ability of the model in resolving the associated characteristics as well as in performing a comprehensive evaluation of the model by means of diverse meteorological observations available within the selected periods over the area of study. Additionally, as this paper is centred in RAMS-based forecasts, two simulations are operated applying the most two recent versions of the RAMS model implemented in the above-mentioned system: RAMS 4.4 and RAMS 6.0. Therefore, a comparison among both versions of the model has been performed as well. Finally, it is our intention to contrast the RAMS forecasts for two completely different atmospheric conditions common with the area of study in the summer. A main difference between the simulation of both meteorological situations has been found in the humidity. In this sense, whilst the model underestimates this magnitude considering the mesoscale event, especially at night time, the model reproduces the daily humidity properly under the western synoptic advection

Effect of Soil Moisture on the Angular Variation of Thermal Infrared Emissivity of Inorganic Soils

Emissivity is influenced by different factors. This study deals with the effect of the soil moisture (SM) content on the zenithal (θ) variation of ratio-to-nadir emissivity (εr), for a wide variety of inorganic bare soils. To retrieve εr, a goniometer assembly was used, together with two identical CIMEL Electronique CE312-2 radiometers working at six spectral bands within 7.7-14.3 μm, performing simultaneous radiance measurements at different combinations of zenith and azimuth angles. The results showed that the effect of SM upon εr(θ) is different depending on the spectral range and textural composition of the sample. Sandy soils showed a decrease of εr(θ) from nadir up to 0.132 for θ ≥ 40° at 8-9.4 μm under dry conditions, but this decrease was reduced to 0.093 with the increase of SM. Clayey samples did not present dependence of εr(θ) on SM. Loamy texture samples presented a more sharp decrease of εr(θ) with the increase of SM, reaching differences between nadir values and 70 ° up to 6%, at all spectral ranges studied. Finally, a parameterization of εr with SM and θ was derived allowing to obtain ratio-to-nadir emissivities with an accuracy of ± 0.011

Landsat and local land surface temperatures in a heterogeneous terrain compared to MODIS values

Land Surface Temperature (LST) as provided by remote sensing onboard satellites is a key parameter for a number of applications in Earth System studies, such as numerical modelling or regional estimation of surface energy and water fluxes. In the case of Moderate Resolution Imaging Spectroradiometer (MODIS) onboard Terra or Aqua, pixels have resolutions near 1 km2 , LST values being an average of the real subpixel variability of LST, which can be significant for heterogeneous terrain. Here, we use Landsat 7 LST decametre-scale fields to evaluate the temporal and spatial variability at the kilometre scale and compare the resulting average values to those provided by MODIS for the same observation time, for the very heterogeneous Campus of the University of the Balearic Islands (Mallorca, Western Mediterranean), with an area of about 1 km2 , for a period between 2014 and 2016. Variations of LST between 10 and 20 K are often found at the sub-kilometre scale. In addition, MODIS values are compared to the ground truth for one point in the Campus, as obtained from a four-component net radiometer, and a bias of 3.2 K was found in addition to a Root Mean Square Error (RMSE) of 4.2 K. An indication of a more elaborated local measurement strategy in the Campus is given, using an array of radiometers distributed in the area

Influence of soil water content on the thermal infrared emissivity of bare soils. Implication for land surface temperature determination.

The influence of soil water content in thermal infrared emissivity is a known fact but has been poorly studied in the past. A laboratory study for quantifying the dependence of emissivity on soil moisture was carried out. Six samples of surface horizons of different soil types were selected for the experiment. The gravimetric method was chosen for determining the soil moisture, whereas the emissivity was measured at different soil water contents using the two-lid variant of the box method. As a result, the study showed that emissivity increases from 1.7% to 16% when water content becomes higher, especially in sandy soils in the 8.29.2 mm range. Accordingly, a set of equations was derived to obtain emissivity from soil moisture at different spectral bands for the analyzed mineral soils. Moreover, results showed that the spectral ratio decreases with increasing soil water content. Finally, the study showed that systematic errors from 0.1 to 2 K can be caused by soil moisture influence on emissivity