Papers by Florian Pappenberger
Hydrology and Earth System Sciences, 2011
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Egu General Assembly Conference Abstracts, May 1, 2014
Hydrological ensemble prediction systems (HEPS) have in recent years been increasingly used for t... more Hydrological ensemble prediction systems (HEPS) have in recent years been increasingly used for the operational forecasting of floods by European hydrometeorological agencies. The most obvious advantage of HEPS is that more of the uncertainty in the modelling system can be assessed. In addition, ensemble prediction systems generally have better skill than deterministic systems both in the terms of the mean forecast performance and the potential forecasting of extreme events. Research efforts have so far mostly been devoted to the improvement of the physical and technical aspects of the model systems, such as increased resolution in time and space and better description of physical processes. Developments like these are certainly needed; however, in this paper we argue that there are other areas of HEPS that need urgent attention. This was also the result from a group exercise and a survey conducted to operational forecasters within the European Flood Awareness System (EFAS) to identify the top priorities of improvement regarding their own system. They turned out to span a range of areas, the most popular being to include verification of an assessment of past forecast performance, a multi-model approach for hydrological modelling, to increase the forecast skill on the medium range (>3 days) and more focus on education and training on the interpretation of forecasts. In light of limited resources, we suggest a simple model to classify the identified priorities in terms of their cost and complexity to decide in which order to tackle them. This model is then used to create an action plan of short-, medium- and long-term research priorities with the ultimate goal of an optimal improvement of EFAS in particular and to spur the development of operational HEPS in general.
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Abstract Forecast consistency is a key property of meteorological forecasts and information on th... more Abstract Forecast consistency is a key property of meteorological forecasts and information on this can be used to complement traditional performance measures in order to aid decision making and forecast system diagnostics. In this paper a probabilistic forecast convergence score is proposed, the pFCS. The properties of the score are illustrated and analysis on ECMWF EPS forecasts is performed. It is shown that the pFCS can be used to give an integrated measure of the consistency of probabilistic forecasts and when used ...
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Natural Hazards and Earth System Science, 2015
ABSTRACT Large-scale fires occur frequently across Indonesia, particularly in the southern region... more ABSTRACT Large-scale fires occur frequently across Indonesia, particularly in the southern region of Kalimantan and eastern Sumatra. They have considerable impacts on carbon emissions, haze production, biodiversity, health, and economic activities. In this study, we demonstrate that severe fire and haze events in Indonesia can generally be predicted months in advance using predictions of seasonal rainfall from the ECMWF System 4 coupled ocean–atmosphere model. Based on analyses of long, up-to-date series observations on burnt area, rainfall, and tree cover, we demonstrate that fire activity is negatively correlated with rainfall and is positively associated with deforestation in Indonesia. There is a contrast between the southern region of Kalimantan (high fire activity, high tree cover loss, and strong non-linear correlation between observed rainfall and fire) and the central region of Kalimantan (low fire activity, low tree cover loss, and weak, non-linear correlation between observed rainfall and fire). The ECMWF seasonal forecast provides skilled forecasts of burnt and fire-affected area with several months lead time explaining at least 70% of the variance between rainfall and burnt and fire-affected area. Results are strongly influenced by El Niño years which show a consistent positive bias. Overall, our findings point to a high potential for using a more physical-based method for predicting fires with several months lead time in the tropics rather than one based on indexes only. We argue that seasonal precipitation forecasts should be central to Indonesia's evolving fire management policy.
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Hydrology and Earth System Sciences, 2015
ABSTRACT
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Flood hazard maps at trans-national and continental scale have potential for a large number of ap... more Flood hazard maps at trans-national and continental scale have potential for a large number of applications ranging from climate change studies, aid to emergency planning for major flood crisis, early damage assessment and urban development, among others. However, such maps are usually available at rather coarse resolution, which limits their applications to rough assessments. At finer resolution, maps are often limited to country boundaries, due to limited data sharing and specific cooperation programs at trans-national level. The European Floods Directive 2007/60/EC requires EU Member States to map the potential flood extent for all water courses by the end of 2013. In this work we derive a pan-European flood hazard map at 100 m resolution, covering most of the European territory. The proposed approach is based on expanding the cascade model presented by Barredo et al. (2007). First, a pan-European distributed rainfall-runoff model with a resolution of 5x5km is set up and calibrat...
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GeoPlanet: Earth and Planetary Sciences, 2015
ABSTRACT Floods and low flows in rivers are seasonal phenomena that may cause several problems to... more ABSTRACT Floods and low flows in rivers are seasonal phenomena that may cause several problems to society. Flow forecasts are crucial to anticipate high and low flow events. The forecasted flow is commonly given as one value, even though it is uncertain. There is an increasing interest to account for uncertainty in flood early warning and decision support systems. In response to that demand, ensemble flood forecasting has been developed using ensembles of numerical weather predictions (NWP) as a driving force for rainfall-runoff models. However, NWPs require bias correction in order to correspond to observations. This study focuses on comparison of two hydrological models and two error reduction techniques of the European Centre for Medium-Range Weather Forecasts (ECMWF). Namely, we compare an application of the conceptual HBV and a data-based mechanistic (DBM) grey-box rainfall-runoff model and two statistical methods of error correction, based on Quantile Mapping (QM), with and without seasonal adjustment. The Biała Tarnowska catchment (southern Poland) is used as a case study. The study shows that a simple, DBM model has similar prediction capabilities as the more complex conceptual HBV model. The use of QM downscaling techniques improves significantly the prediction skills, but seasonality can be neglected.
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ABSTRACT Wildfire is a fundamental Earth System process, affecting almost all biogeochemical cycl... more ABSTRACT Wildfire is a fundamental Earth System process, affecting almost all biogeochemical cycles, and all vegetated biomes. Fires are naturally rare in humid tropical forests, and tropical trees are generally killed by even low-intensity fires. However, fire activity in the tropics has increased markedly over the past 15-20 years, especially in Indonesia, Amazonia, and more recently, central Africa also. Since fire is the prime tool for clearing land in the tropics, it not surprising that the increase in fire activity is strongly associated with increased levels of deforestation, which is driven mainly by world-wide demand for timber and agricultural commodities. The consequences of deforestation fires for biodiversity conservation and emissions of greenhouse gases and aerosols are enormous. For example, carbon emissions from tropical biomass burning are around 20% of annual average global fossil fuel emissions. The destructive fires in Indonesia during the exceptionally strong El Niño-induced drought in late 1997 and early 1998 rank as some of the largest peak emissions events in recorded history. Past studies estimate about 1Gt of carbon was released to the atmosphere from the Indonesian fires in 1997 (which were mostly concentrated in carbon-rich forested peatlands). This amount is equivalent to about 14% of the average global annual fossil fuel emissions released during the 1990s. While not as large as the 1997-98 events, significant emissions from biomass burning have also been recorded in other (less severe) El Niño years across Indonesia, in particular, 2002, 2004, 2006 and 2009-2010. Recent climate modelling studies indicate that the frequency of El Niño events may increase under future climate change, affecting many tropical countries, including Indonesia. An increased drought frequency plus a projected increase in population and land use pressures in Indonesia, imply there will be even more fires and emissions in future across the region. However, while several studies using historical data have established negative relationships between fires and antecedent rainfall, and/or positive relationships between fires and deforestation in regions affected by El Nino, comparatively little work has attempted to predict fires and emissions in such regions. Ensemble seasonal climate forecasts issued with several months lead-time have been applied to support risk assessment systems in many fields, notably agricultural production and natural disaster management of flooding, heat waves, drought and fire. The USA, for example, has a long-standing seasonal fire danger prediction system. Fire danger monitoring systems have been operating in Indonesia for over a decade, but, as of yet, no fire danger prediction systems exist. Given the effort required to mobilise suppression and prevention measures in Indonesia, one could argue that high fire danger periods must be anticipated months in advance for mitigation and response measures to be effective. To address this need, the goal of our work was to examine the utility of seasonal rainfall forecasts in predicting severe fires in Indonesia more than one month in advance, using southern Borneo (comprising the bulk of Kalimantan) as a case study. Here we present the results of comparing seasonal forecasts of monthly rainfall from ECMWF's System 4 against i) observed rainfall (GPCP), and ii) burnt area and deforestation (MODIS, AVHRR and Landsat) across southern Borneo for the period 1997-2010. Our results demonstrate the utility of using ECMWF's seasonal climate forecasts for predicting fire activity in the region. Potential applications include improved fire mitigation and responsiveness, and improved risk assessments of biodiversity and carbon losses through fire. These are important considerations for forest protection programmes (e.g. REDD+), forest carbon markets and forest (re)insurance enterprises.
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Geophysical Research Letters, 2014
ABSTRACT This study applies statistical postprocessing to ensemble forecasts of near-surface temp... more ABSTRACT This study applies statistical postprocessing to ensemble forecasts of near-surface temperature, 24 h precipitation totals, and near-surface wind speed from the global model of the European Centre for Medium-Range Weather Forecasts (ECMWF). The main objective is to evaluate the evolution of the difference in skill between the raw ensemble and the postprocessed forecasts. Reliability and sharpness, and hence skill, of the former is expected to improve over time. Thus, the gain by postprocessing is expected to decrease. Based on ECMWF forecasts from January 2002 to March 2014 and corresponding observations from globally distributed stations, we generate postprocessed forecasts by ensemble model output statistics (EMOS) for each station and variable. Given the higher average skill of the postprocessed forecasts, we analyze the evolution of the difference in skill between raw ensemble and EMOS. This skill gap remains almost constant over time indicating that postprocessing will keep adding skill in the foreseeable future.
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Journal of Hydrometeorology, 2014
ABSTRACT Skillful and timely streamflow forecasts are critically important to water managers and ... more ABSTRACT Skillful and timely streamflow forecasts are critically important to water managers and emergency protection services. To provide these forecasts, hydrologists must predict the behavior of complex coupled human-natural systems using incomplete and uncertain information and imperfect models. Moreover, operational predictions often integrate anecdotal information and unmodeled factors. Forecasting agencies face four key challenges: 1) making the most of available data, 2) making accurate predictions using models, 3) turning hydrometeorological forecasts into effective warnings, and 4) administering an operational service. Each challenge presents a variety of research opportunities, including the development of automated quality-control algorithms for the myriad of data used in operational streamflow forecasts, data assimilation, and ensemble forecasting techniques that allow for forecaster input, methods for using human-generated weather forecasts quantitatively, and quantification of human interference in the hydrologic cycle. Furthermore, much can be done to improve the communication of probabilistic forecasts and to design a forecasting paradigm that effectively combines increasingly sophisticated forecasting technology with subjective forecaster expertise. These areas are described in detail to share a real-world perspective and focus for ongoing research endeavors.
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Climate Vulnerability, 2013
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Hydrology and Earth System Sciences, 2013
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Forecast consistency is a key property of meteorological forecasts and information on this can be... more Forecast consistency is a key property of meteorological forecasts and information on this can be used to complement traditional performance measures in order to aid decision making and forecast system diagnostics. In this paper a probabilistic forecast convergence score is proposed, the pFCS. The properties of the score are illustrated and analysis on ECMWF EPS forecasts is performed. It is shown that the pFCS can be used to give an integrated measure of the consistency of probabilistic forecasts and when used ...
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Journal of Hydrology
In operational hydrological forecasting systems, improvements are directly related to the continu... more In operational hydrological forecasting systems, improvements are directly related to the continuous monitoring of the forecast performance. An efficient evaluation framework must be able to spot issues and limitations and provide feedback to the system developers. In regional systems, the expertise of analysts on duty is a major component of the daily evaluation. On the other hand, large scale systems need to be complemented with semi-automated tools to evaluate the quality of forecasts equitably in every part of their domain. This article presents the current status of the monitoring and evaluation framework of the European Flood Awareness System (EFAS). For each grid point of the European river network, 10-day ensemble streamflow predictions are evaluated against a reference simulation which uses observed meteorological fields as input to a calibrated hydrological model. Performance scores are displayed over different regions, forecast lead times, basin sizes, as well as in time,...
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Journal of Hydrology
The skill of a forecast can be assessed by comparing the relative proximity of both the forecast ... more The skill of a forecast can be assessed by comparing the relative proximity of both the forecast and a benchmark to the observations. Example benchmarks include climatology or a naïve forecast. Hydrological ensemble prediction systems (HEPS) are currently transforming the hydrological forecasting environment but in this new field there is little information to guide researchers and operational forecasters on how benchmarks can be best used to evaluate their probabilistic forecasts. In this study, it is identified that the forecast skill calculated can vary depending on the benchmark selected and that the selection of a benchmark for determining forecasting system skill is sensitive to a number of hydrological and system factors. A benchmark intercomparison experiment is then undertaken using the continuous ranked probability score (CRPS), a reference forecasting system and a suite of 23 different methods to derive benchmarks. The benchmarks are assessed within the operational set-up...
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Papers by Florian Pappenberger