Climate change projections for winter streamflow in Douro river

Ponencia presentada en: X Congreso de la Asociación Española de Climatología celebrado en Alicante entre el 5 y el 8 de octubre de 2016.[EN]Climate change projections for the winter streamflow of the Douro River have been obtained for the period 2071-2099, using the Principal Component Regression (PCR) method. The winter streamflow time series (January to March) from eight stations distributed over the basin, covering the period 1950-2011, were used as predictand variables, while the principal components (PCs) of the winter (December to February) anomalies of sea level pressure (SLP) were used as predictors of the streamflow for the development of a statistical downscaling model. The period 1950- 1995 was used for the calibration of the regression model, while 1996-2011 was used as validation period. The statistical downscaling model fitted from the observational SLP data was applied to the SLP outputs of three GCMs for the period 2071-2099, under the climate change scenarios RCP2.6, RCP4.5 and RCP8.5. The main result obtained is that all models and scenarios project a generalized decrease in the winter streamflow of the Douro River.[ES]Se han obtenido proyecciones de cambio climático para el caudal de invierno del Río Duero, para el periodo 2071-2099, usando el método de Regresión por Componentes Principales (PCR). Las series temporales de caudal (de enero a marzo) de ocho estaciones distribuidas a lo largo de la cuenca, cubriendo el periodo 1950-2011, han sido utilizadas como variables predictando, mientras que las componentes principales (PCs) de las anomalías de la presión a nivel del mar (SLP) en invierno (diciembre a febrero) fueron usadas como predictores del caudal para el desarrollo de un modelo de downscaling estadístico.This work has been financed by the projects P11-RNM-7941 (Junta de Andalucía- Spain) and CGL2013-48539-R (MINECO-Spain, FEDER)

Seasonal streamflow forecast in the Iberian Peninsula based on lagged teleconnection indices

Ponencia presentada en: IX Congreso de la Asociación Española de Climatología celebrado en Almería entre el 28 y el 30 de octubre de 2014.[EN]This work assesses the potential of teleconnection indices as predictors of seasonal streamflow in the Iberian Peninsula (IP). The database comprises 382 streamflow time series from gauging stations, covering the period from October 1975 to September 2008. Four forecasting scenarios were developed, considering the information provided by teleconnection indices from one year to the previous season to the seasonal streamflow to be predicted.[ES]En este trabajo se ha evaluado la capacidad predictiva de los índices de teleconexión de estaciones previas sobre el caudal estacional de los ríos en la Península Ibérica. La base de datos de caudal la conforman 382 estaciones de aforo cubriendo el periodo desde octubre de 1975 hasta septiembre de 2008. Adicionalmente, se consideraron cuatro escenarios de predicción, en función de la información climática disponible con cuatro, tres, dos o una estaciones de adelanto.The Spanish Ministry of Science and Innovation, with additional support from the European Community Funds (FEDER), project CGL2010-21188/CLI and the Regional Government of Andalusia, project P11-RNM-7941, which had financed this study

Spatio-temporal analysis of maximum and minimum temperatures over Levant region (1987-2017)

Ponencia presentada en: XI Congreso de la Asociación Española de Climatología celebrado en Cartagena entre el 17 y el 19 de octubre de 2018.[ES]El objetivo de este estudio es analizar los cambios espaciales y temporales en los promedios anuales y estacionales de las temperaturas máxima y mínima en la región del Levante durante 1987-2017. Estos promedios se calcularon a partir de datos diarios para cada estación y para toda la región de Levante. Las tendencias espaciales y temporales para tres variables se calcularon utilizando la prueba no paramétrica de Mann-Kendall. Además, la diferencia de medias anuales y estacionales entre los dos períodos 1987-2000 y 2001-2011 se evaluó mediante el uso de la prueba U no paramétrica de Mann-Whitney. Durante 1987-2017, la región de Levante fue testigo de un calentamiento significativo en las temperaturas máximas y mínimas anuales de 0.33 y 0.30ºC/década, respectivamente. Además, la primavera mostró una tendencia al calentamiento muy fuerte y significativa en comparación con otras estaciones en 0.53ºC/década para la temperatura máxima y en 0.51ºC/década para la temperatura mínima. La temperatura máxima y mínima anual, de primavera y verano han aumentado significativamente en esta región durante 2001-2017 en comparación con el período 1987-2000. Las tendencias decrecientes mostraron un patrón muy aislado y aleatorio en comparación con las tendencias de calentamiento amplias, intensivas y coherentes en los promedios anuales y estacionales de la temperatura máxima y mínima. Las tasas de calentamiento en Jordania fueron generalmente las más altas.[EN]This study aims to analyze the spatial and temporal variability of the annual and seasonal maximum (Tmax) and minimum (Tmin) temperatures, along with the diurnal temperature range (DTR) over the entire Levant region for the period 1987-2017. The temporal trends for these three variables were calculated at the annual and seasonal scales by using the non-parametric Mann-Kendall test. Furthermore, the difference of the means between the two periods (1987-2000 and 2001-2017) were assessed by using the non-parametric Mann-Whitney U test. During 1987-2017, the Levant region suffered a significant warming for the annual maximum and minimum temperatures around 0.33 and 0.30ºC\decade, respectively. In addition, spring showed very strong and significant warming trend (around 0.53ºC/decade for Tmax and 0.51ºC/decade for Tmin) compared with the other seasons. The annual, spring and summer means of Tmax and Tmin have significantly increased over the Levant region during 2001-2017 compared with the period 1987-2000. Spatially, the decreasing trends showed very isolated and random patterns compared with the broad, intensive and coherent warming trends at annual and seasonal time scales. The warming over Jordan was generally the highest.This work has been financed by the projects P11-RNM-7941 (Junta de Andalucía), CGL2013-48539-R (MINECO-Spain, FEDER) and CGL2017-89836-R (MINECO-Spain, FEDER)

Statistical downscaling of summer precipitation in Colombia

Ponencia presentada en: IX Congreso de la Asociación Española de Climatología celebrado en Almería entre el 28 y el 30 de octubre de 2014.[ES]In this study an statistical downscaling (SD) model using principal component regression (PCR) for simulating summer precipitation in Colombia during the period 1950-2005, has been build, and the climate projections during the 2071-2100 period by applying the obtained SD model have been obtained. For these ends the PCs of the SLP reanalysis data from NCEP were used as predictor variables and the observed gridded summer precipitation as predictand variables. The period 1950-1993 was utilized for calibration and 1994-2010 for validation. The Bootstrap with replacement was applied to provide estimations of the statistical errors. All models perform reasonably well at the regional scales, and the spatial distribution of the correlation coefficients between predicted and observed gridded precipitation values show high values (between 0.5 and 0.93) along Andes range, north and north Pacific of Colombia.[EN]En este trabajo se ha construido un modelo de downscaling estadístico (DS) usando el método de regresión de componentes principales (PCR) para simular la precipitación de verano en Colombia durante el periodo 1950-2005, y se han obtenido sus proyecciones durante el periodo 2071-2100 aplicando el modelo obtenido. Para ello, se han usado las PCs de los datos de SLP de reanálisis del NCEP como variables predictoras y las series de precipitación observada en cada punto de rejilla como predictando. El periodo 1950-1993 ha sido utilizado para calibración y el 1994-2010 para validación. Para proporcionar estimaciones del error estadístico, se ha aplicado el método de Bootstrap con reemplazo. Todos los modelos representan razonablemente bien la precipitación a escala regional, y la distribución espacial de los coeficientes de correlación entre las series de valores predichos y observados en rejilla, muestra altos valores (entre 0.5 y 0.93) a lo largo de la cadena de los Andes, norte y Pacífico norte de Colombia.The Spanish Ministry of Science and Innovation, with additional support from the European Community Funds (FEDER), project CGL2010-21188/CLI and the Regional Government of Andalusia, project P11-RNM-7941, which had financed this study

Influence of tropical Pacific SST on seasonal precipitation in Colombia. Prediction using El Niño and El Niño Modoki

Ponencia presentada en: IX Congreso de la Asociación Española de Climatología celebrado en Almería entre el 28 y el 30 de octubre de 2014.[EN]In this paper the forecast skill provided by the tropical Pacific SST associated with El Niño and El Niño Modoki over seasonal precipitation (Pt) in Colombia has been evaluated through a lagged Singular Value Decomposition analysis. This analysis has been made based on the results in a companion paper where the impact of El Niño and El Niño Modoki over the seasonal precipitation in Colombia was analyzed and quantified.[ES]En este estudio se evalúa la capacidad de predicción que posee la SST del Pacífico tropical asociada con los fenómenos El Niño y El Niño Modoki sobre la precipitación (Pt) estacional en Colombia, a través del Análisis de Descomposición del Valor Singular. Este análisis está soportado en los resultados obtenidos en un artículo complementario donde ha sido analizado y cuantificado el impacto de El Niño y El Niño Modoki sobre la precipitación estacional en Colombia.This work has been financed by the projects CGL2010- 21188/CLI (MICINN-Spain, FEDER) and P11-RNM-7941 (Junta de Andalucía-Spain)

Daily gridded datasets of snow depth and snow water equivalent for the Iberian Peninsula from 1980 to 2014

We present snow observations and a validated daily gridded snowpack dataset that was simulated from downscaled reanalysis of data for the Iberian Peninsula. The Iberian Peninsula has long-lasting seasonal snowpacks in its different mountain ranges, and winter snowfall occurs in most of its area. However, there are only limited direct observations of snow depth (SD) and snow water equivalent (SWE), making it difficult to analyze snow dynamics and the spatiotemporal patterns of snowfall. We used meteorological data from downscaled reanalyses as input of a physically based snow energy balance model to simulate SWE and SD over the Iberian Peninsula from 1980 to 2014. More specifically, the ERA-Interim reanalysis was downscaled to 10 km 10 km resolution using the Weather Research and Forecasting (WRF) model. The WRF outputs were used directly, or as input to other submodels, to obtain data needed to drive the Factorial Snow Model (FSM). We used lapse rate coefficients and hygrobarometric adjustments to simulate snow series at 100m elevations bands for each 10 km 10 km grid cell in the Iberian Peninsula. The snow series were validated using data from MODIS satellite sensor and ground observations. The overall simulated snow series accurately reproduced the interannual variability of snowpack and the spatial variability of snow accumulation and melting, even in very complex topographic terrains. Thus, the presented dataset may be useful for many applications, including land management, hydrometeorological studies, phenology of flora and fauna, winter tourism, and risk management. The data presented here are freely available for download from Zenodo (https://doi.org/10.5281/zenodo.854618). This paper fully describes the work flow, data validation, uncertainty assessment, and possible applications and limitations of the database.Esteban Alonso-González is supported by the Spanish Ministry of Economy and Competitiveness (BES- 2015-071466). This study was funded by the Spanish Ministry of Economy and Competitiveness projects CGL2014-52599-P 10 (Estudio del manto de nieve en la montaña española y su respuesta a la variabilidad y cambio climatico) and CGL2017- 82216-R (HIDROIBERNIEVE) and (with additional support from the European Community funds, FEDER) CGL2013-48539-R (Impactos del cambio climático en los recursos hídricos de la cuenca del Duero a alta resolución). Also, the Regional Government of Andalusia has funded this research with the project P11-RNM-7941 (Impactos del Cambio Climático en la cuenca del Guadalquivir, LICUA)

High-resolution boreal winter precipitation projections over tropical America from CMIP5 models

Climate change projections for boreal winter precipitation in Tropical America has been addressed by statistical downscaling (SD) using the principal component regression with sea-level pressure (SLP) as the predictor variable. The SD model developed from the reanalysis of SLP and gridded precipitation GPCC data, has been applied to SLP outputs from 20 CGMS of CMIP5, both from the present climate (1971-2000) and for the future (2071-2100) under the RCP2.6, RCP4.5, and RCP8.5 scenarios. The SD model shows a suitable performance over large regions, presenting a strong bias only in small areas characterized by very dry climate conditions or poor data coverage. The difference in percentage between the projected SD precipitation and the simulated SD precipitation for present climate, ranges from moderate to intense changes in rainfall (positive or negative, depending on the region and the SD GCM model considered), as the radiative forcing increases from the RCP2.6 to RCP8.5. The disparity in the GCMs outputs seems to be the major source of uncertainty in the projected changes, while the scenario considered appears less decisive. Mexico and eastern Brazil are the areas showing the most coherent decreases between SD GCMs, while northwestern and southeastern South America show consistently significant increases. This coherence is corroborated by the results of the ensemble mean which projects positive changes from 10ºN towards the south, with exceptions such as eastern Brazil, northern Chile and some smaller areas, such as the center of Colombia, while projected negative changes are the majority found in the northernmost part.Departamento Física Aplicada, Facultad de Ciencias, Universidad de Granad

Integrated sensitivity analysis of a macroscale hydrologic model in the north of the Iberian Peninsula

Process-based hydrologic models allow to identify the behavior of a basin providing a mathematical description of the hydrologic processes underlying the runoff mechanisms that govern the streamflow generation. This study focuses on a macroscale application of the Variable Infiltration Capacity (VIC) model over 31 headwater subwatersheds belonging to the Duero River Basin, located in the Iberian Peninsula, through a three-part approach: (1) the calibration and validation of the VIC model for all the subwatersheds; (2) an integrated sensitivity analysis concerning the soil parameters chosen for the calibration, and (3) an assessment of equifinality and the efficiency of the calibration algorithm. The calibration and validation processes showed good results for most of the subwatersheds in a computationally efficient way using the Shuffled-Complex-Evolution algorithm. The sensitivity measures were obtained with the Standardized Regression Coefficients method through a post-process of the outputs of a Monte Carlo simulation carried out for 10 000 parameter samples for each subwatershed. This allowed to quantify the sensitivity of the water balance components to the selected parameters for the calibration and understanding the strong dependencies between them. The final assessment of the equifinality hypothesis manifested that there are many parameter samples with performances as good as the optimum, calculated using the calibration algorithm. For almost all the analyzed subwatersheds the calibration algorithm resulted efficient, reaching the optimal fit. Both the Monte Carlo simulation and the use of a calibration algorithm will be of interest for other feasible applications of the VIC model in other river basins.Comment: Published in Journal of Hydrolog