Catalan Institute of Climate Science IC3

Barcelona, Spain

Catalan Institute of Climate Science IC3

Barcelona, Spain
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Vargas A.,University of Barcelona | Arnold D.,Central Institute for Meteorology and Geodynamics ZAMG | Adame J.A.,El Arenosillo National Institute For Aerospace Technology Inta | Grossi C.,Catalan Institute of Climate Science IC3 | And 2 more authors.
Journal of Environmental Radioactivity | Year: 2015

This paper presents an analysis of one year of hourly radon and meteorological measurements at 10m and 100m a.g.l. at El Arenosillo tall-tower station, in the south-west of the Iberian Peninsula. Whole-year and seasonal composites of the diurnal radon cycle show the expected behaviour, with larger concentrations at 10m than at 100m during the night, due to poor vertical mixing, and similar concentrations at both heights during the daylight hours. Wind speed and wind direction analyses by sector show the prevailing contributions for each season. Sectors with air which has spent a longer period over the ocean and high wind speeds will lead to low concentrations at both levels, whereas inland sectors show a clear increase of the concentrations with similar overall averages for the two levels. The Sierra Morena, Guadalquivir and Bethics System sectors (continental pathways) are the sectors that show higher concentrations for mild to large wind speeds. The daily evolution of radon concentration differences at both heights has been grouped into four clusters by using a K-means algorithm method. The four clusters have been selected so that they sufficiently describe different characteristics in terms of stability. The temporal evolution of the mixing height (MH) and of the bulk diffusivity parameter (Kb) during the nocturnal period has been calculated by using the temporal variation of 222Rn concentration at 10m and the concentration gradient with height, respectively. © 2014 Elsevier Ltd.

Dominguez-Castro F.,University of Extremadura | Vaquero J.M.,University of Extremadura | Rodrigo F.S.,University of Almeria | Farrona A.M.M.,Complutense University of Madrid | And 7 more authors.
International Journal of Climatology | Year: 2014

ABSTRACT: This article summarizes recent efforts on early instrumental data recovery in Spain conducted under the Salvà-Sinobas project. We have retrieved and digitized more than 100000 meteorological observations prior to 1850 in Spain. This data set contains measurements of air temperature, atmospheric pressure, wind direction and state of the atmosphere in 16 places located in Iberia and the Balearic Islands. Most of the observations are made on a daily basis. However, monthly and annual information has also been retrieved. The time coverage of the series is not homogeneous, with the earliest records starting in Seville in 1780. Prior to this work only two series were available in Spain (i.e. Cadiz and Barcelona), so this data set represents a great advance in the early data availability for Spain. Due to the lack of metadata in most of the series, their interpretation must be made with caution. © 2013 Royal Meteorological Society.

van den Hurk B.,Royal Netherlands Meteorological Institute | Doblas-Reyes F.,Catalan Institute of Climate science IC3 | Doblas-Reyes F.,ECMWF | Balsamo G.,ECMWF | And 3 more authors.
Climate Dynamics | Year: 2012

The Second Global Land Atmosphere Coupling Experiment (GLACE2) is designed to explore the improvement of forecast skill of summertime temperature and precipitation up to 8 weeks ahead by using realistic soil moisture initialization. For the European continent, we show in this study that for temperature the skill does indeed increase up to 6 weeks, but areas with (statistically significant) lower skill also exist at longer lead times. The skill improvement is smaller than shown earlier for the US, partly because of a lower potential predictability of the European climate at seasonal time scales. Selection of extreme soil moisture conditions or a subset of models with similar initial soil moisture conditions does improve the forecast skill, and sporadic positive effects are also demonstrated for precipitation. Using realistic initial soil moisture data increases the interannual variability of temperature compared to the control simulations in the South-Central European area at longer lead times. This leads to better temperature forecasts in a remote area in Western Europe. However, the covered range of forecast dates (1986-1995) is too short to isolate a clear physical mechanism for this remote correlation. © 2010 The Author(s).

Prodhomme C.,Catalan Institute of Climate science IC3 | Prodhomme C.,Barcelona Supercomputing Center | Doblas-Reyes F.,Catalan Institute of Climate science IC3 | Doblas-Reyes F.,Catalan Institution for Research and Advanced Studies | And 4 more authors.
Climate Dynamics | Year: 2015

Land surfaces and soil conditions are key sources of climate predictability at the seasonal time scale. In order to estimate how the initialization of the land surface affects the predictability at seasonal time scale, we run two sets of seasonal hindcasts with the general circulation model EC-Earth2.3. The initialization of those hindcasts is done either with climatological or realistic land initialization in May using the ERA-Land re-analysis. Results show significant improvements in the initialized run occurring up to the last forecast month. The prediction of near-surface summer temperatures and precipitation at the global scale and over Europe are improved, as well as the warm extremes prediction. As an illustration, we show that the 2010 Russian heat wave is only predicted when soil moisture is initialized. No significant improvement is found for the retrospective prediction of the 2003 European heat wave, suggesting this event to be mainly large-scale driven. Thus, we confirm that late-spring soil moisture conditions can be decisive in triggering high-impact events in the following summer in Europe. Accordingly, accurate land-surface initial conditions are essential for seasonal predictions. © 2015 Springer-Verlag Berlin Heidelberg

PubMed | Catalan Institute of Climate science IC3, French Institute of Health and Medical Research, World Health Organization and University of Geneva
Type: Journal Article | Journal: International journal of environmental research and public health | Year: 2016

Heat waves have been responsible for more fatalities in Europe over the past decades than any other extreme weather event. However, temperature-related illnesses and deaths are largely preventable. Reliable sub-seasonal-to-seasonal (S2S) climate forecasts of extreme temperatures could allow for better short-to-medium-term resource management within heat-health action plans, to protect vulnerable populations and ensure access to preventive measures well in advance. The objective of this study is to assess the extent to which S2S climate forecasts could be incorporated into heat-health action plans, to support timely public health decision-making ahead of imminent heat wave events in Europe. Forecasts of apparent temperature at different lead times (e.g., 1 day, 4 days, 8 days, up to 3 months) were used in a mortality model to produce probabilistic mortality forecasts up to several months ahead of the 2003 heat wave event in Europe. Results were compared to mortality predictions, inferred using observed apparent temperature data in the mortality model. In general, we found a decreasing transition in skill between excellent predictions when using observed temperature, to predictions with no skill when using forecast temperature with lead times greater than one week. However, even at lead-times up to three months, there were some regions in Spain and the United Kingdom where excess mortality was detected with some certainty. This suggests that in some areas of Europe, there is potential for S2S climate forecasts to be incorporated in localised heat-health action plans. In general, these results show that the performance of this climate service framework is not limited by the mortality model itself, but rather by the predictability of the climate variables, at S2S time scales, over Europe.

Petrova D.,Catalan Institute of Climate science IC3 | Petrova D.,University of Barcelona | Koopman S.J.,VU University Amsterdam | Ballester J.,Catalan Institute of Climate science IC3 | And 3 more authors.
Climate Dynamics | Year: 2016

El Niño (EN) is a dominant feature of climate variability on inter-annual time scales driving changes in the climate throughout the globe, and having wide-spread natural and socio-economic consequences. In this sense, its forecast is an important task, and predictions are issued on a regular basis by a wide array of prediction schemes and climate centres around the world. This study explores a novel method for EN forecasting. In the state-of-the-art the advantageous statistical technique of unobserved components time series modeling, also known as structural time series modeling, has not been applied. Therefore, we have developed such a model where the statistical analysis, including parameter estimation and forecasting, is based on state space methods, and includes the celebrated Kalman filter. The distinguishing feature of this dynamic model is the decomposition of a time series into a range of stochastically time-varying components such as level (or trend), seasonal, cycles of different frequencies, irregular, and regression effects incorporated as explanatory covariates. These components are modeled separately and ultimately combined in a single forecasting scheme. Customary statistical models for EN prediction essentially use SST and wind stress in the equatorial Pacific. In addition to these, we introduce a new domain of regression variables accounting for the state of the subsurface ocean temperature in the western and central equatorial Pacific, motivated by our analysis, as well as by recent and classical research, showing that subsurface processes and heat accumulation there are fundamental for the genesis of EN. An important feature of the scheme is that different regression predictors are used at different lead months, thus capturing the dynamical evolution of the system and rendering more efficient forecasts. The new model has been tested with the prediction of all warm events that occurred in the period 1996–2015. Retrospective forecasts of these events were made for long lead times of at least two and a half years. Hence, the present study demonstrates that the theoretical limit of ENSO prediction should be sought much longer than the commonly accepted “Spring Barrier”. The high correspondence between the forecasts and observations indicates that the proposed model outperforms all current operational statistical models, and behaves comparably to the best dynamical models used for EN prediction. Thus, the novel way in which the modeling scheme has been structured could also be used for improving other statistical and dynamical modeling systems. © 2016 Springer-Verlag Berlin Heidelberg

Marce R.,Catalan Institute for Water Research | Obrador B.,University of Barcelona | Morgui J.-A.,University of Barcelona | Morgui J.-A.,Catalan Institute of Climate science IC3 | And 3 more authors.
Nature Geoscience | Year: 2015

Most lakes and reservoirs have surface CO2 concentrations that are supersaturated relative to the atmosphere. The resulting CO2 emissions from lakes represent a substantial contribution to the continental carbon balance. Thus, the drivers of CO2 supersaturation in lakes need to be understood to constrain the sensitivity of the land carbon cycle to external perturbations. Carbon dioxide supersaturation has generally been attributed to the accumulation of inorganic carbon in lakes where respiration exceeds photosynthesis, but this interpretation has faced challenges. Here we report analyses of water chemistry data from a survey of Spanish reservoirs that represent a range of lithologies, using simple metabolic models. We find that, above an alkalinity threshold of 1 mequiv. l-1, CO2 supersaturation in lakes is directly related to carbonate weathering in the watershed. We then evaluate the global distribution of alkalinity in lakes and find that 57% of the surface area occupied by lakes and reservoirs - particularly in tropical and temperate latitudes - has alkalinity exceeding 1 mequiv. l-1. We conclude that lake inputs of dissolved inorganic carbon from carbonate weathering should be considered for the CO2 supersaturation of lakes at both regional and global scales. © 2015 Macmillan Publishers Limited. All rights reserved

PubMed | Rovira i Virgili University, Catalan Institute of Climate science IC3, University of Barcelona and Aberystwyth University
Type: | Journal: Journal of environmental management | Year: 2015

Conventional wastewater treatment does not completely remove and/or inactive viruses; consequently, viruses excreted by the population can be detected in the environment. This study was undertaken to investigate the distribution and seasonality of human viruses and faecal indicator bacteria (FIB) in a river catchment located in a typical Mediterranean climate region and to discuss future trends in relation to climate change. Sample matrices included river water, untreated and treated wastewater from a wastewater treatment plant within the catchment area, and seawater from potentially impacted bathing water. Five viruses were analysed in the study. Human adenovirus (HAdV) and JC polyomavirus (JCPyV) were analysed as indicators of human faecal contamination of human pathogens; both were reported in urban wastewater (mean values of 10(6) and 10(5) GC/L, respectively), river water (10(3) and 10(2) GC/L) and seawater (10(2) and 10(1) GC/L). Human Merkel Cell polyomavirus (MCPyV), which is associated with Merkel Cell carcinoma, was detected in 75% of the raw wastewater samples (31/37) and quantified by a newly developed quantitative polymerase chain reaction (qPCR) assay with mean concentrations of 10(4) GC/L. This virus is related to skin cancer in susceptible individuals and was found in 29% and 18% of river water and seawater samples, respectively. Seasonality was only observed for norovirus genogroup II (NoV GGII), which was more abundant in cold months with levels up to 10(4) GC/L in river water. Human hepatitis E virus (HEV) was detected in 13.5% of the wastewater samples when analysed by nested PCR (nPCR). Secondary biological treatment (i.e., activated sludge) and tertiary sewage disinfection including chlorination, flocculation and UV radiation removed between 2.22 and 4.52 log10 of the viral concentrations. Climate projections for the Mediterranean climate areas and the selected river catchment estimate general warming and changes in precipitation distribution. Persistent decreases in precipitation during summer can lead to a higher presence of human viruses because river and sea water present the highest viral concentrations during warmer months. In a global context, wastewater management will be the key to preventing environmental dispersion of human faecal pathogens in future climate change scenarios.

Stewart-Ibarra A.M.,New York University | Lowe R.,Catalan Institute of Climate science IC3
American Journal of Tropical Medicine and Hygiene | Year: 2013

We report a statistical mixed model for assessing the importance of climate and non-climate drivers of interannual variability in dengue fever in southern coastal Ecuador. Local climate data and Pacific sea surface temperatures (Oceanic Niño Index [ONI]) were used to predict dengue standardized morbidity ratios (SMRs; 1995-2010). Unobserved confounding factors were accounted for using non-structured yearly random effects. We found that ONI, rainfall, and minimum temperature were positively associated with dengue, with more cases of dengue during El Niño events. We assessed the influence of non-climatic factors on dengue SMR using a subset of data (2001-2010) and found that the percent of households with Aedes aegypti immatures was also a significant predictor. Our results indicate that monitoring the climate and non-climate drivers identified in this study could provide some predictive lead for forecasting dengue epidemics, showing the potential to develop a dengue early-warning system in this region. Copyright © 2013 by The American Society of Tropical Medicine and Hygiene.

Ma S.,Catalan Institute of Climate science IC3 | Rodo X.,Catalan Institute of Climate science IC3 | Rodo X.,Catalan Institution for Research and Advanced Studies | Doblas-Reyes F.J.,Catalan Institute of Climate science IC3 | Doblas-Reyes F.J.,Catalan Institution for Research and Advanced Studies
International Journal of Climatology | Year: 2012

On the basis of the observed all-India rainfall (AIR), Climate Prediction Center (CPC) merged analysis of precipitation (CMAP), and the multimodel rainfall simulated in the Development of a European multimodel ensemble system for seasonal to interannual prediction (DEMETER) project, the model performance in terms of forecast quality of the seasonal mean Indian summer monsoon rainfall (ISMR) was evaluated. The approach used included the individual model (single-model ensemble) comparison as well as its comparison with the multimodel ensemble (MME). The results obtained reveal that systematic biases are the main source of the low skill in predicting the ISMR, while improved reproduction of interannual variability may increase the overall forecast quality for the ISMR. The MME shows superior performance in reproducing AIR features than the single-model ensembles. This improved forecast quality achieved by the MME with respect to the ISMR variations primarily depends on model performance and secondly on ensemble size. The MME has improved capability of simulating the ISMR variations during 1972-1990 decades, whereas it exhibits a lower performance in the 1990s. The reason of this decadal varying forecast quality clearly deserves more investigation. In summary, these results suggest that the MME's increase in skill absolutely depends on enhancing the individual model quality. © 2011 Royal Meteorological Society.

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