Geostatistical radar-raingauge combination with nonparametric correlograms: methodological considerations and application in Switzerland

Modelling spatial covariance is an essential part of all geostatistical methods. Traditionally, parametric semivariogram models are fit from available data. More recently, it has been suggested to use nonparametric correlograms obtained from spatially complete data fields. Here, both estimation techniques are compared. Nonparametric correlograms are shown to have a substantial negative bias. Nonetheless, when combined with the sample variance of the spatial field under consideration, they yield an estimate of the semivariogram that is unbiased for small lag distances. This justifies the use of this estimation technique in geostatistical applications. Various formulations of geostatistical combination (Kriging) methods are used here for the construction of hourly precipitation grids for Switzerland based on data from a sparse realtime network of raingauges and from a spatially complete radar composite. Two variants of Ordinary Kriging (OK) are used to interpolate the sparse gauge observations. In both OK variants, the radar data are only used to determine the semivariogram model. One variant relies on a traditional parametric semivariogram estimate, whereas the other variant uses the nonparametric correlogram. The variants are tested for three cases and the impact of the semivariogram model on the Kriging prediction is illustrated. For the three test cases, the method using nonparametric correlograms performs equally well or better than the traditional method, and at the same time offers great practical advantages. Furthermore, two variants of Kriging with external drift (KED) are tested, both of which use the radar data to estimate nonparametric correlograms, and as the external drift variable. The first KED variant has been used previously for geostatistical radar-raingauge merging in Catalonia (Spain). The second variant is newly proposed here and is an extension of the first. Both variants are evaluated for the three test cases as well as an extended evaluation period. It is found that both methods yield merged fields of better quality than the original radar field or fields obtained by OK of gauge data. The newly suggested KED formulation is shown to be beneficial, in particular in mountainous regions where the quality of the Swiss radar composite is comparatively low. An analysis of the Kriging variances shows that none of the methods tested here provides a satisfactory uncertainty estimate. A suitable variable transformation is expected to improve this.

Statistical detection of spurious variations in daily raingauge data caused by changes in observation practices, as applied to records from various parts of the world

In the instrumental records of daily precipitation, we often encounter one or more periods in which values below some threshold were not registered. Such periods, besides lacking small values, also have a large number of dry days. Their cumulative distribution function is shifted to the right in relation to that for other portions of the record having more reliable observations. Such problems are examined in this work, based mostly on the two-sample Kolmogorov–Smirnov (KS) test, where the portion of the series with more number of dry days is compared with the portion with less number of dry days. Another relatively common problem in daily rainfall data is the prevalence of integers either throughout the period of record or in some part of it, likely resulting from truncation during data compilation prior to archiving or by coarse rounding of daily readings by observers. This problem is identified by simple calculation of the proportion of integers in the series, taking the expected proportion as 10%. The above two procedures were applied to the daily rainfall data sets from the European Climate Assessment (ECA), Southeast Asian Climate Assessment (SACA), and Brazilian Water Resources Agency (BRA). Taking the statistic D of the KS test >0.15 and the corresponding p-value <0.001 as the condition to classify a given series as suspicious, the proportions of the ECA, SACA, and BRA series falling into this category are, respectively, 34.5%, 54.3%, and 62.5%. With relation to coarse rounding problem, the proportions of series exceeding twice the 10% reference level are 3%, 60%, and 43% for the ECA, SACA, and BRA data sets, respectively. A simple way to visualize the two problems addressed here is by plotting the time series of daily rainfall for a limited range, for instance, 0–10 mm day−1.

Diurnal variability of rainfall in southwest Amazonia during the LBA-TRMM field campaign of the austral summer of 1999

The TRMM-LBA field campaign was held during the austral summer of 1999 in southwestern Amazonia. Among the major objectives, was the identification and description of the diurnal variability of rainfall in the region, associated with the different rain producing weather systems that occurred during the January-February season. By using a network of 40 digital rain gauges implemented in the state of Rondônia, and together with observations and analyses of circulation and convection, it was possible to identify details of the diurnal cycle of rainfall and the associated rainfall mechanisms. Rainfall episodes were characterized by regimes of "low-level easterly" and "westerly" winds in the context of the large-scale circulation. The westerly regime is related to an enhanced South Atlantic Convergence Zone (SACZ) and an intense and/or wide Low Level Jet (LLJ) east of the Andes, which can extend eastward towards Rondônia, even though some westerly regime episodes also show a LLJ that remains close to the foothill of the Andes. The easterly regime is related to easterly propagating systems (e.g. squall-lines) with possible weakened or less frequent LLJs and a suppressed SACZ. Diurnal variability of rainfall during westerly surface wind regime shows a characteristic maximum at late afternoon followed by a relatively weaker second maximum at early evening (2100 Local Standard Time LST). The easterly regime composite shows an early morning maximum followed by an even stronger maximum in the afternoon.

A methodology for the classification of convective structures using meteorological radar: Application to heavy rainfall events on the Mediterranean coast of the Iberian Peninsula

During the period 1996-2000, forty-three heavy rainfall events have been detected in the Internal Basins of Catalonia (Northeastern of Spain). Most of these events caused floods and serious damage. This high number leads to the need for a methodology to classify them, on the basis of their surface rainfall distribution, their internal organization and their physical features. The aim of this paper is to show a methodology to analyze systematically the convective structures responsible of those heavy rainfall events on the basis of the information supplied by the meteorological radar. The proposed methodology is as follows. Firstly, the rainfall intensity and the surface rainfall pattern are analyzed on the basis of the raingauge data. Secondly, the convective structures at the lowest level are identified and characterized by using a 2-D algorithm, and the convective cells are identified by using a 3-D procedure that looks for the reflectivity cores in every radar volume. Thirdly, the convective cells (3-D) are associated with the 2-D structures (convective rainfall areas). This methodology has been applied to the 43 heavy rainfall events using the meteorological radar located near Barcelona and the SAIH automatic raingauge network.

Comparison of TAMSAT and CPC rainfall estimates with raingauges, for southern Africa

Two different TAMSAT (Tropical Applications of Meteorological Satellites) methods of rainfall estimation were developed for northern and southern Africa, based on Meteosat images. These two methods were used to make rainfall estimates for the southern rainy season from October 1995 to April 1996. Estimates produced by both TAMSAT methods and estimates produced by the CPC (Climate Prediction Center) method were then compared with kriged data from over 800 raingauges in southern Africa. This shows that operational TAMSAT estimates are better over plateau regions, with 59% of estimates within one standard error (s.e.) of the kriged rainfall. Over mountainous regions the CPC approach is generally better, although all methods underestimate and give only 40% of estimates within 1 s.e. The two TAMSAT methods show little difference across a whole season, but when looked at in detail the northern method gives unsatisfactory calibrations. The CPC method does have significant overall improvements by building in real-time raingauge data, but only where sufficient raingauges are available.

Importance of resolution and model configuration when downscaling extreme precipitation

Dynamical downscaling is frequently used to investigate the dynamical variables of extra-tropical cyclones, for example, precipitation, using very high-resolution models nested within coarser resolution models to understand the processes that lead to intense precipitation. It is also used in climate change studies, using long timeseries to investigate trends in precipitation, or to look at the small-scale dynamical processes for specific case studies. This study investigates some of the problems associated with dynamical downscaling and looks at the optimum configuration to obtain the distribution and intensity of a precipitation field to match observations. This study uses the Met Office Unified Model run in limited area mode with grid spacings of 12, 4 and 1.5 km, driven by boundary conditions provided by the ECMWF Operational Analysis to produce high-resolution simulations for the Summer of 2007 UK flooding events. The numerical weather prediction model is initiated at varying times before the peak precipitation is observed to test the importance of the initialisation and boundary conditions, and how long the simulation can be run for. The results are compared to raingauge data as verification and show that the model intensities are most similar to observations when the model is initialised 12 hours before the peak precipitation is observed. It was also shown that using non-gridded datasets makes verification more difficult, with the density of observations also affecting the intensities observed. It is concluded that the simulations are able to produce realistic precipitation intensities when driven by the coarser resolution data.

Tracking the uncertainty in flood alerts driven by grand ensemble weather predictions

The incorporation of numerical weather predictions (NWP) into a flood warning system can increase forecast lead times from a few hours to a few days. A single NWP forecast from a single forecast centre, however, is insufficient as it involves considerable non-predictable uncertainties and can lead to a high number of false or missed warnings. Weather forecasts using multiple NWPs from various weather centres implemented on catchment hydrology can provide significantly improved early flood warning. The availability of global ensemble weather prediction systems through the ‘THORPEX Interactive Grand Global Ensemble’ (TIGGE) offers a new opportunity for the development of state-of-the-art early flood forecasting systems. This paper presents a case study using the TIGGE database for flood warning on a meso-scale catchment (4062 km2) located in the Midlands region of England. For the first time, a research attempt is made to set up a coupled atmospheric-hydrologic-hydraulic cascade system driven by the TIGGE ensemble forecasts. A probabilistic discharge and flood inundation forecast is provided as the end product to study the potential benefits of using the TIGGE database. The study shows that precipitation input uncertainties dominate and propagate through the cascade chain. The current NWPs fall short of representing the spatial precipitation variability on such a comparatively small catchment, which indicates need to improve NWPs resolution and/or disaggregating techniques to narrow down the spatial gap between meteorology and hydrology. The spread of discharge forecasts varies from centre to centre, but it is generally large and implies a significant level of uncertainties. Nevertheless, the results show the TIGGE database is a promising tool to forecast flood inundation, comparable with that driven by raingauge observation.

Estimativa da precipitação através de técnicas de sensoriamento remoto : estudo de caso para o estado do Rio Grande do Sul

A quantificação da precipitação é dificultada pela extrema aleatoriedade do fenômeno na natureza. Os métodos convencionais para mensuração da precipitação atuam no sentido de espacializar a precipitação mensurada pontualmente em postos pluviométricos para toda a área de interesse e, desta forma, uma rede com elevado número de postos bem distribuídos em toda a área de interesse é necessária para um resultado satisfatório. No entanto, é notória a escassez de postos pluviométricos e a má distribuição espacial dos poucos existentes, não somente no Brasil, mas em vastas áreas do globo. Neste contexto, as estimativas da precipitação com técnicas de sensoriamento remoto e geoprocessamento pretendem potencializar a utilização dos postos pluviométricos existentes através de uma espacialização baseada em critérios físicos. Além disto, o sensoriamento remoto é a ferramenta mais capaz para gerar estimativas de precipitação nos oceanos e nas vastas áreas continentais desprovidas de qualquer tipo de informação pluviométrica. Neste trabalho investigou-se o emprego de técnicas de sensoriamento remoto e geoprocessamento para estimativas de precipitação no sul do Brasil. Três algoritmos computadorizados foram testados, sendo utilizadas as imagens dos canais 1, 3 e 4 (visível, vapor d’água e infravermelho) do satélite GOES 8 (Geostacionary Operational Environmental Satellite – 8) fornecidas pelo Centro de Previsão de Tempo e Estudos Climáticos do Instituto Nacional de Pesquisas Espaciais. A área de estudo compreendeu todo o estado do Rio Grande do Sul, onde se utilizaram os dados pluviométricos diários derivados de 142 postos no ano de 1998. Os algoritmos citados buscam identificar as nuvens precipitáveis para construir modelos estatísticos que correlacionem as precipitações diária e decendial observadas em solo com determinadas características físicas das nuvens acumuladas durante o mesmo período de tempo e na mesma posição geográfica de cada pluviômetro considerado. Os critérios de decisão que norteiam os algoritmos foram baseados na temperatura do topo das nuvens (através do infravermelho termal), reflectância no canal visível, características de vizinhança e no plano de temperatura x gradiente de temperatura Os resultados obtidos pelos modelos estatísticos são expressos na forma de mapas de precipitação por intervalo de tempo que podem ser comparados com mapas de precipitação obtidas por meios convencionais.

Previsão em tempo atual de cheias com uso de sistema especialista difuso

Sistemas de previsão de cheias podem ser adequadamente utilizados quando o alcance é suficiente, em comparação com o tempo necessário para ações preventivas ou corretivas. Além disso, são fundamentalmente importantes a confiabilidade e a precisão das previsões. Previsões de níveis de inundação são sempre aproximações, e intervalos de confiança não são sempre aplicáveis, especialmente com graus de incerteza altos, o que produz intervalos de confiança muito grandes. Estes intervalos são problemáticos, em presença de níveis fluviais muito altos ou muito baixos. Neste estudo, previsões de níveis de cheia são efetuadas, tanto na forma numérica tradicional quanto na forma de categorias, para as quais utiliza-se um sistema especialista baseado em regras e inferências difusas. Metodologias e procedimentos computacionais para aprendizado, simulação e consulta são idealizados, e então desenvolvidos sob forma de um aplicativo (SELF – Sistema Especialista com uso de Lógica “Fuzzy”), com objetivo de pesquisa e operação. As comparações, com base nos aspectos de utilização para a previsão, de sistemas especialistas difusos e modelos empíricos lineares, revelam forte analogia, apesar das diferenças teóricas fundamentais existentes. As metodologias são aplicadas para previsão na bacia do rio Camaquã (15543 km2), para alcances entre 10 e 48 horas. Dificuldades práticas à aplicação são identificadas, resultando em soluções as quais constituem-se em avanços do conhecimento e da técnica. Previsões, tanto na forma numérica quanto categorizada são executadas com sucesso, com uso dos novos recursos. As avaliações e comparações das previsões são feitas utilizandose um novo grupo de estatísticas, derivadas das freqüências simultâneas de ocorrência de valores observados e preditos na mesma categoria, durante a simulação. Os efeitos da variação da densidade da rede são analisados, verificando-se que sistemas de previsão pluvio-hidrométrica em tempo atual são possíveis, mesmo com pequeno número de postos de aquisição de dados de chuva, para previsões sob forma de categorias difusas.

Análise da precipitação no semi-árido potiguar

The semiarid rainfall regime is northeastern Brazil is highly variable. Climate processes associated with rainfall are complex and their effects may represent extreme situations of drought or floods, which can have adverse effects on society and the environment. The regional economy has a significant agricultural component, which is strongly influenced by weather conditions. Maximum precipitation analysis is traditionally performed using the intensity-duration-frequency (IDF) probabilistic approach. Results from such analysis are typically used in engineering projects involving hydraulic structures such as drainage network systems and road structures. On the other hand, precipitation data analysis may require the adoption of some kind of event identification criteria. The minimum inter-event duration (IMEE) is one of the most used criteria. This study aims to analyze the effect of the IMEE on the obtained rain event properties. For this purpose, a nine-year precipitation time series (2002- 2011) was used. This data was obtained from an automatic raingauge station, installed in an environmentally protected area, Ecological Seridó Station. The results showed that adopted IMEE values has an important effect on the number of events, duration, event height, mean rainfall rate and mean inter-event duration. Furthermore, a higher occurrence of extreme events was observed for small IMEE values. Most events showed average rainfall intensity higher than 2 mm.h-1 regardless of IMEE. The storm coefficient of advance was, in most cases, within the first quartile of the event, regardless of the IMEE value. Time series analysis using partial time series made it possible to adjust the IDF equations to local characteristics

Impacts of the Madden-Julian oscillation on intraseasonal precipitation over northeast Brazil

Este estudo tem como objetivo investigar os impactos da oscilação de Madden-Julian (OMJ) na precipitação da região Nordeste do Brasil (NEB). Para tanto foram utilizados dados diários de precipitação baseados em 492 pluviômetros distribuídos na região e cobrindo um período de 30 anos (1981 − 2010). As análises através de composições de anomalias de precipitação, radiação de onda longa e fluxo de umidade, foram obtidas com base no índice da OMJ desenvolvido por Jones-Carvalho. Para distinguir o sinal da OMJ de outros padrões de variabilidade climática, todos os dados diários foram filtrados na escala de 20 − 90 dias; portanto somente dias classificados como eventos da OMJ foram considerados nas composições. Uma análise preliminar baseada apenas nos dados de precipitação foi feita para uma pequena área localizada no interior semiárido do NEB, conhecida como Seridó. Essa microrregião é uma das áreas mais secas do NEB e foi reconhecida pela Convenção das Nações Unidas para o Combate à Desertificação e Mitigação dos Efeitos das Secas como particularmente vulnerável à desertificação. Composições de anomalias de precipitação foram feitas para cada uma das oito fases da OMJ durante Fevereiro-Maio (principal período chuvoso da microrregião). Os resultados mostraram a existência de variações significativas nos padrões de precipitação (de precipitação excessiva à deficiente) associados à propagação da OMJ. A combinação dos sinais de precipitação obtidos durantes as fases úmidas e secas da OMJ mostrou que a diferença corresponde cerca de 50 − 150% de modulação das chuvas na microrregião. Em seguida, uma investigação abrangente sobre o papel da OMJ sobre toda a região Nordeste foi feita considerando-se as quatro estações do ano. Os resultados mostraram que os impactos da OMJ na precipitação intrassazonal do NEB apresentam forte sazonalidade. A maior coerência espacial dos sinais de precipitação ocorreram durante o verão austral, quando cerca de 80% das estações pluviométricas apresentaram anomalias positivas de precipitação durante as fases 1 − 2 da OMJ e anomalias negativas de precipitação nas fases 5 − 6 da oscilação. Embora impactos da OMJ na precipitação intrassazonal tenham sido encontrados na maioria das localidades e em todas as estações do ano, eles apresentaram variações na magnitude dos sinais e dependem da fase da oscilação. As anomalias de precipitação do NEB observadas são explicadas através da interação existente entre as ondas de Kelvin-Rossby acopladas convectivamente e as características climáticas predominantes sobre a região em cada estação do ano. O aumento de precipitação observado sobre a maior parte do NEB durante o verão e primavera austrais encontra-se associado com o fluxo de umidade de oeste (regime de oeste), o qual favorece a atividade convectiva em amplas áreas da América do Sul tropical. Por outro lado, as anomalias de precipitação durante o inverno e outono austrais apresentaram uma variabilidade espacial mais complexa. Durante estas estações, as anomalias de precipitação observadas nas estações localizadas na costa leste do NEB dependem da intensidade do anticiclone do Atlântico Sul, o qual é modulado em grande parte por ondas de Rossby. As características topográficas do NEB parecem desempenhar um papel importante na variabilidade observada na precipitação, principalmente nestas áreas costeiras. A intensificação do anticiclone aumenta a convergência dos ventos alísios na costa contribuindo para a ocorrência de precipitação observada à barlavento do planalto da Borborema. Por outro lado, o aumento da subsidência parece ser responsável pelos déficits de precipitação observados à sotavento. Tais condições mostraram-se típicas durante o predomínio do regime de leste sobre a região tropical da América do Sul e o NEB, durante o qual ocorre uma diminuição no fluxo de umidade proveniente da Amazônia.

A space-time hybrid hourly rainfall model for derived flood frequency analysis

For derived flood frequency analysis based on hydrological modelling long continuous precipitation time series with high temporal resolution are needed. Often, the observation network with recording rainfall gauges is poor, especially regarding the limited length of the available rainfall time series. Stochastic precipitation synthesis is a good alternative either to extend or to regionalise rainfall series to provide adequate input for long-term rainfall-runoff modelling with subsequent estimation of design floods. Here, a new two step procedure for stochastic synthesis of continuous hourly space-time rainfall is proposed and tested for the extension of short observed precipitation time series. First, a single-site alternating renewal model is presented to simulate independent hourly precipitation time series for several locations. The alternating renewal model describes wet spell durations, dry spell durations and wet spell intensities using univariate frequency distributions separately for two seasons. The dependence between wet spell intensity and duration is accounted for by 2-copulas. For disaggregation of the wet spells into hourly intensities a predefined profile is used. In the second step a multi-site resampling procedure is applied on the synthetic point rainfall event series to reproduce the spatial dependence structure of rainfall. Resampling is carried out successively on all synthetic event series using simulated annealing with an objective function considering three bivariate spatial rainfall characteristics. In a case study synthetic precipitation is generated for some locations with short observation records in two mesoscale catchments of the Bode river basin located in northern Germany. The synthetic rainfall data are then applied for derived flood frequency analysis using the hydrological model HEC-HMS. The results show good performance in reproducing average and extreme rainfall characteristics as well as in reproducing observed flood frequencies. The presented model has the potential to be used for ungauged locations through regionalisation of the model parameters.