Abstract. Extreme weather events, such as droughts, have been increasingly affecting the agricultural sector causing several socio-economic consequences. The growing economy requires improved assessments of drought-related impacts in agriculture, particularly under a climate that is getting drier and warmer. This work proposes a probabilistic model which intends to contribute to the agricultural drought risk management in rainfed cropping systems. Our methodology is based on a bivariate copula-a...

(Instituto Superior de Agronomia)+ 2 AuthorsCarlos Pires9

Estimated H-index: 9

(University of Lisbon)

Abstract This study aims at assessing the accuracy of estimating daily grass reference evapotranspiration (PM-ET o ) computed with ERA-Interim reanalysis products, as well as to assess the quality of reanalysis products as predictors of daily maximum and minimum temperature, net radiation, dew point temperature and wind speed, which are used to compute PM-ET o . With this propose, ET o computed from local observations of weather variables in 24 weather stations distributed across Continental Por...

We propose an expansion of multivariate time-series data into maximally independent source subspaces. The search is made among rotations of prewhitened data which maximize non-Gaussianity of candidate sources. We use a tensorial invariant approximation of the multivariate negentropy in terms of a linear combination of squared coskewness and cokurtosis. By solving a high-order singular value decomposition problem, we extract the axes associated with most non-Gaussianity. Moreover, an estimate of ...

(Instituto Superior de Agronomia)+ 3 AuthorsLuis S. Pereira50

Estimated H-index: 50

(University of Lisbon)

Computing crop reference evapotranspiration (ETo) with the FAO Penman–Monteith method (PM-ETo) requires maximum and minimum air temperature, shortwave radiation, relative air humidity and wind speed. These data are often not available, thus requiring alternative computation procedures. Although some proposed approximations may provide ETo values with small estimation errors, the physics of the ET processes may then not be well described. The use of reanalysis data, which is common in climate stu...

We develop an expansion of space-distributed time series into statistically independent uncorrelated subspaces (statistical sources) of low-dimension and exhibiting enhanced non-Gaussian probability distributions with geometrically simple chosen shapes (projection pursuit rationale). The method relies upon a generalization of the principal component analysis that is optimal for Gaussian mixed signals and of the independent component analysis (ICA), optimized to split non-Gaussian scalar sources....

Abstract Atmospheric forecasting and predictability are important to promote adaption and mitigation measures in order to minimize drought impacts. This study estimates hybrid (statistical–dynamical) long-range forecasts of the regional drought index SPI (3-months) over homogeneous regions from mainland Portugal, based on forecasts from the UKMO operational forecasting system, with lead-times up to 6 months. ERA-Interim reanalysis data is used for the purpose of building a set of SPI predictors ...

We formulate a nonlinear synergistic theory of coevolutionary systems, disentangling and explaining dynamic complexity in terms of fundamental processes for optimised data analysis and dynamic model design: Dynamic Source Analysis (DSA). DSA provides a nonlinear dynamical basis for spatiotemporal datasets or dynamical models, eliminating redundancies and expressing the system in terms of the smallest number of fundamental processes and interactions without loss of information. This optimises mod...

This study aims at predicting the Standard Precipitation Index (SPI) drought class transitions in Portugal, considering the influence of the North Atlantic Oscillation (NAO) as one of the main large-scale atmospheric drivers of precipitation and drought fields across the Western European and Mediterranean areas. Log-linear modeling of the drought class transition probabilities on three temporal steps (dimensions) was used in an SPI time series of six- and 12-month time scales (SPI6 and SPI12) ob...

Abstract. Non-Gaussian multivariate probability distributions, derived from climate and geofluid statistics, allow for nonlinear correlations between linearly uncorrelated components, due to joint Shannon negentropies. Triadic statistical dependence under pair-wise (total or partial) independence is thus possible. Synergy or interaction information among triads is estimated. We formulate an optimization method of triads in the space of orthogonal rotations of normalized principal components, rel...

(Instituto Português do Mar e da Atmosfera), Carlos Pires9

Estimated H-index: 9

(University of Lisbon)

[1] The operational ALADIN-France 3D-Var system is based on static background error covariances calculated off-line during a few week past period. In this study, the impact of an online updated specification of background error covariances is evaluated in the ALADIN-France system. This evaluation is done by comparing three experiments, respectively based on (i) covariances calculated from a monthly average over a past period, (ii) covariances calculated from a monthly average over the period of ...