Use of bias correction techniques to improve seasonal forecasts for reservoirs - A case-study in northwestern Mediterranean

In this paper, we have compared different bias correction methodologies to assess whether they could be advantageous for improving the performance of a seasonal prediction model for volume anomalies in the Boadella reservoir (northwestern Mediterranean). The bias correction adjustments have been applied on precipitation and temperature from the European Centre for Middle-range Weather Forecasting System 4 (S4). We have used three bias correction strategies: two linear (mean bias correction, BC, and linear regression, LR) and one non-linear (Model Output Statistics analogs, MOS-analog). The results have been compared with climatology and persistence. The volume-anomaly model is a previously computed Multiple Linear Regression that ingests precipitation, temperature and in-flow anomaly data to simulate monthly volume anomalies. The potential utility for end-users has been assessed using economic value curve areas. We have studied the S4 hindcast period 1981-2010 for each month of the year and up to seven months ahead considering an ensemble of 15 members. We have shown that the MOS-analog and LR bias corrections can improve the original S4. The application to volume anomalies points towards the possibility to introduce bias correction methods as a tool to improve water resource seasonal forecasts in an end-user context of climate services. Particularly, the MOS-analog approach gives generally better results than the other approaches in late autumn and early winter

Comparison of five strategies for seasonal prediction of bioclimatic indicators in the olive sector

This paper assesses the forecast quality of five seasonal forecasting strategies applied to different bioclimatic indicators tailored to the olive sector. In total, five indicators have been selected considering their importance in the management of the olive orchard. As time progresses through the indicator target period, the impact of the increasing share of actual observations included in its computation has been evaluated by examining the variabilities of correlation coefficients and fair rank probability skill scores for each initialization date. The results show that blending either seasonal predictions or climatology with observations enhanced the capability of forecasting the tercile category for all the indicators when compared to the use of climatology or seasonal predictions alone. In fact, for Spring Maximum Temperature and Growing Season Temperature indicators, the combination of observations and SEAS5 predictions could outperform the other methods for most of the start months. As for those threshold-defined indicators, namely Spring Heat Days and Summer Heat Stress Days, the end-users are highly encouraged to use climatology in the first month and combine it with observations as soon as the latter becomes available.Thanks to all the partners of the project MED-GOLD (Turning climate-related information into added value for traditional MEDiterranean Grape, Olive and Durum Wheat food systems, agreement no. 776467) and the project ASPECT (HE-101081460) both funded by the European Union. Thanks to Dcoop as the end-user for providing feedback in the co-development process. The results contain modified Copernicus Climate Change Service information. Neither the European Commission nor ECMWF is responsible for any use that may be made of the Copernicus information or data it contains. One of the coauthors, Raül Marcos-Matamoros, is a Serra Húnter Fellow. Finally, we thank the reviewers, whose comments helped improve the paper substantially.Peer ReviewedPostprint (published version

Trends in flash flood events versus convective precipitation in the Mediterranean region: the case of Catalonia

The aim of this paper is to analyse the potential relationship between flash flood events and convective precipitation in Catalonia, as well as any related trends. The paper starts with an overview of flash floods and their trends in the Mediterranean region, along with their associated factors, followed by the definition of, identification of, and trends in convective precipitation. After this introduction the paper focuses on the north-eastern Iberian Peninsula, for which there is a long-term precipitation series (since 1928) of 1-min precipitation from the Fabra Observatory, as well as a shorter (1996-2011) but more extensive precipitation series (43 rain gauges) of 5-min precipitation. Both series have been used to characterise the degree of convective contribution to rainfall, introducing the β parameter as the ratio between convective precipitation versus total precipitation in any period. Information about flood events was obtained from the INUNGAMA database, with the aim of finding any potential links to convective precipitation. This flood data was gathered using information on damage where flood is treated to as a multifactorial risk, and where any trend or anomaly might have been caused by one or more factors affecting hazard, vulnerability or exposure. Trend analysis has shown an increase in flash flood events. The fact that no trends were detected in terms of extreme values of precipitation on a daily scale, nor on the associated ETCCDI (Expert Team on Climate Change Detection and Indices) extreme index, could point to an increase in vulnerability, an increase in exposure, or changes in land use. However, the summer increase in convective precipitation was concentrated in less torrential events, which could partially explain this positive trend in flash flood events. The β parameter has been also used to characterize the type of flood event according to the features of the precipitation. The highest values correspond to short and local events, usually with daily β values above 0.5, while the minimum threshold of daily β for catastrophic flash floods is 0.31

Characterization of the near surface wind speed distribution at global scale: ERA- Interim reanalysis and ECMWF seasonal forecasting System 4

The present developments in 10 m wind seasonal forecast products have lead to a growth in the number of studies analysing different aspects of both its predictability and applicability. However, there is still a lack of global studies analysing the statistical properties of the probability distribution of 10 m wind speed comparing the seasonal forecast systems with the widely used reanalysis products. To fill this gap we have studied the properties of the probability distributions of 10 m wind speed from the ERA-Interim reanalysis and the European Centre for Medium-Range Weather Forecasts System 4 seasonal forecast system. We have focused on two seasons, JJA and DJF, considering both their interannual and intraseasonal variability. The 10 m wind speed distribution has been characterized in terms of the four main moments of the probability distribution (mean, standard deviation, skewness and kurtosis). We have also computed the coefficient of variation to identify the regions with the higher wind variability and the Shapiro-Wilks goodness of fit test to assess their normality. This set of parameters is important to provide useful climate information in wind energy decision-making processes that use simple assumptions of the wind speed frequency distribution to properly estimate the wind energy potential. Besides, this study also illustrates where the discrepancies of the distributions of the seasonal predictions and the reference dataset are higher and, thus, which might need special attention from a bias adjustment perspective

Flash flood evolution in North-Western Mediterranean

The present paper shows an in-depth analysis of the evolution of floods and precipitation in Catalonia for the period 1981-2010. In order to have homogeneous information, and having in mind that not gauge data was available for all the events, neither for all the rivers and stream flows, daily press from a specific newspaper has been systematically analysed for this period. Furthermore a comparison with a longer period starting in 1900 has been done. 219 flood events (mainly flash flood events) have been identified for the period of 30 years (375 starting in 1900), 79 of them were ordinary, 117 of them were extraordinary and 23 of them were catastrophic, being autumn and summer the seasons with the maxima values. 19% of the events caused a total of 110 casualties. 60% of them died when they tried to cross the street or the stream. Factors like the evolution of precipitation, population density and other socio-economical aspects have been considered. The trend analysis shows an increase of 1 flood/decade that probably has been mainly due to inter-annual and intra-annual changes in population density and in land-use and land-cover

Towards a better understanding of the evolution of the flood risk in Mediterranean urban areas: the case of Barcelona

This contribution explores the evolution of the flood risk in the Metropolitan Area of Barcelona (MAB; Northeast Spain) from 1981 to 2015, and how it has been affected by changes in land use, population and precipitation. To complete this study, we analysed PRESSGAMA and INUNGAMA databases to look for all the information related to the floods and flash floods that have affected the chosen region. The ''Consorcio de Compensación de Seguros'', a state insurance company for extraordinary risks, provided data on economic damage. The extreme precipitation trend was analysed by the Fabra Observatory and El Prat-Airport Observatory, and daily precipitation data were provided by the State Meteorological Agency of Spain (AEMET) and the Meteorological Service of Catalonia (SMC). Population data were obtained from the Statistical Institute of Catalonia (IDESCAT). Changes in land use were estimated from the land use maps for Catalonia corresponding to 1956, 1993, 2000, 2005 and 2009. Prevention measures like rainwater tanks and improvements to the drainage system were also been considered. The specific case of Barcelona is presented, a city recognised by United Nations International Strategy for Disaster Reduction as a model city for urban resilience to floods. The evolution of flood events in the MAB does not show any significant trend for this period. We argue that the evolution in floods can be explained, at least in part, by the lack of trend in extreme precipitation indices, and also by the improvements in flood prevention measures

A method for using monthly average temperatures in phenology models for grapevine (Vitis vinifera L.)

In recent years, there have been increasing efforts to link phenology models with seasonal climate predictions in so-called Decision Support Systems (DSS) to tailor crop management strategies. However, temporal discrepancies between phenology models with temperature data gathered on a daily basis and seasonal forecasting systems providing predictability on monthly scales have limited their use. In this work, we present a novel methodology to use monthly average temperature data in phenology models. Briefly stated, we modelled the timing of the appearance of specific grapevine phenological phases using monthly average temperatures. To do so, we computed the cumulative thermal time (Sf) and the number of effective days per month (effd). The effd is the number of days in a month on which temperatures would be above the minimum value for development (Tb). The calculation of effd is obtained from a normal probability distribution function derived from historical weather records. We tested the methodology on four experimental plots located in different European countries with contrasting weather conditions and for four different grapevine cultivars. The root mean square deviation (RMSD) ranged from 4 to 7 days for all the phenological phases considered, at all the different sites, and for all the cultivars. Furthermore, the bias of observed vs predicted comparisons was not significantly different when using either monthly mean or daily temperature values to model phenology. This new methodology, therefore, provides an easy and robust way to incorporate monthly temperature data into grapevine phenology models.info:eu-repo/semantics/publishedVersio

Trends in flash flood events versus convective precipitation in the Mediterranean region: the case of Catalonia

The aim of this paper is to analyse the potential relationship between flash flood events and convective precipitation in Catalonia, as well as any related trends. The paper starts with an overview of flash floods and their trends in the Mediterranean region, along with their associated factors, followed by the definition of, identification of, and trends in convective precipitation. After this introduction the paper focuses on the north-eastern Iberian Peninsula, for which there is a long-term precipitation series (since 1928) of 1-min precipitation from the Fabra Observatory, as well as a shorter (1996-2011) but more extensive precipitation series (43 rain gauges) of 5-min precipitation. Both series have been used to characterise the degree of convective contribution to rainfall, introducing the β parameter as the ratio between convective precipitation versus total precipitation in any period. Information about flood events was obtained from the INUNGAMA database, with the aim of finding any potential links to convective precipitation. This flood data was gathered using information on damage where flood is treated to as a multifactorial risk, and where any trend or anomaly might have been caused by one or more factors affecting hazard, vulnerability or exposure. Trend analysis has shown an increase in flash flood events. The fact that no trends were detected in terms of extreme values of precipitation on a daily scale, nor on the associated ETCCDI (Expert Team on Climate Change Detection and Indices) extreme index, could point to an increase in vulnerability, an increase in exposure, or changes in land use. However, the summer increase in convective precipitation was concentrated in less torrential events, which could partially explain this positive trend in flash flood events. The β parameter has been also used to characterize the type of flood event according to the features of the precipitation. The highest values correspond to short and local events, usually with daily β values above 0.5, while the minimum threshold of daily β for catastrophic flash floods is 0.31