Linking drought and wet weather in the Jordan catchment with atmospheric circulation patterns

Ponencia presentada en: VI Congreso Internacional de la Asociación Española de Climatología celebrado en Tarragona del 8 al 11 de octubre de 2008.[ES]El alcance de este estudio es la identificación de patrones de circulación sobre el Mediterráneo oriental los cuales están relacionados de una manera significativa con la precipitación extrema en la cuenca hidrográfica del Jordan. A ese fin, un método multi-objetivo de clasificación a base de lógica fuzzy se pone en practica. El método condiciona los datos de la precipitación y patrones de circulación atmosférica a gran escala diariamente. Para comenzar, se realiza la clasificación condicional de la precipitación para el período de 1961-1990 usando presión a nivel del mar y potencial geológico en 500hPa, dispuestos por el proyecto de reanálisis NCEP/NCAR. Se comprueba la plausibilidad de los patrones de circulación obtenidos para situaciones de sequia y humedas. Luego, se realiza un análisis de la frecuencia de su presencia a escala temporal de meses, años y décadas. Por último, se compara la distribución de frecuencia de los patrones de circulación para los años 1961-1990 con la distribución de frecuencia para los años 2011-2040 utilizando ECHAM5 impulsado por A1B. Se presenta y discuta el impacto del cambio climático al cambio de frecuencia en patrones de circulación en situaciones de sequia y humedas.[EN]The scope of this study is to identify circulation patterns (CPs) over the Eastern Mediterranean (EM), which are significantly linked to extreme rainfall events in the Jordan catchment. For this reason, a multi objective fuzzy logic-based classification (MOFRBC) method is applied, which conditions rainfall data to large-scale atmospheric circulation patterns on dthe aily time scale. First, the rainfall conditional classification is performed for the period 1961-1990 using Sea Level Pressure (SLP) and Geopotential Height in 500hPa (GPH500), retrieved from the NCEP/NCAR reanalysis project. The obtained drought and wet circulation patterns are checked for plausibility and a frequency analysis of their occurrence is performed on monthly, interannual and decadal time scales. Second, the CP frequency distribution of the 1961-1990 time slice is then compared to the frequency distribution of the 2011-2040 time slice using the A1B driven ECHAM5. The impact of climate change on the frequency change of droughty and wet circulation patterns is presented and discussed

COST 733 – WG4: Applications of weather type classifications

Presentación realizada para: European Geosciences Union General Assembly celebrado del 19-24 de abril de 2009 en Viena

Using probable maximum precipitation to bound the disaggregation of rainfall

The Multiplicative Discrete Random Cascade (MDRC) class of model is used to temporally disaggregate rainfall volumes through multiplying the volumes by random weights, which is repeated through multiple disaggregation levels. The model development involves the identification of probability density functions from which to sample the weights. The parameters of the probability density functions are known to be dependent on the rainfall volume. This paper characterises the volume dependency over the scarcely observed extreme ranges of rainfall, introducing the concept of volume-bounded MDRC models. Probable maximum precipitation (PMP) estimates are used to define theoretically-based points and asymptotes to which the observation-based estimates of the MDRC model parameters are extrapolated. Alternative models are tested using a case study of rainfall data from Brisbane, Australia covering the period 1908 to 2015. The results show that moving from a baseline model with constant parameters to incorporating the volume dependency of the parameters is essential for acceptable performance in terms of the frequency and magnitude of modelled extremes. As well as providing better estimates of parameters at each disaggregation level, the volume dependency provides an in-built bias correction when moving from one level to the next. A further, relatively small performance gain is obtained by extrapolating the observed dependency to the theoretically-based bounds. The volume dependency of the parameters is found to be reasonably time-scaleable, providing opportunity for advances in the generalisation of MDRC models. Sensitivity analysis shows that the subjectivities and uncertainties in the modelling procedure have mixed effects on the performance. A principal uncertainty, to which the results are sensitive, is the PMP estimate. Therefore, in applications of the bounded approach, the PMP should ideally be described by a probability distribution function