Isabella Zin

Spatial Similarity and Transferability of Analog Dates for Precipitation Downscaling over France

AbstractHigh-resolution weather scenarios generated for climate change impact studies from the output of climate models must be spatially consistent. Analog models (AMs) offer a high potential for the generation of such scenarios. For each prediction day, the scenario they provide is the weather observed for days in a historical archive that are analogous according to different predictors. When the same “analog date” is chosen for a prediction at several sites, spatial consistency is automatically satisfied. The optimal predictors and consequently the optimal analog dates, however, are expected to depend on the location for which the prediction is to be made.In the present work, the predictor (1000- and 500-hPa geopotential heights) domain of a benchmark AM is optimized for the probabilistic daily prediction of 8981 local precipitation “stations” over France. The corresponding 8981 locally domain-optimized AMs are used to explore the spatial transferability and similarity of the optimal analog dates obtai...

Runoff evolution due to land-use change in a small Sahelian catchment

Abstract Land-use changes have been significant these last decades in West Africa, particularly in the Sahel region; in this area, climatic and demographic factors have led to a rise in cropped areas in recent decades causing strong changes in the water cycle and in river regimes. This study compares the rainfall–runoff relationships for two periods (1991–1994 and 2004–2011) in two small and similar neighbouring Sahelian catchments (approx 0.1 km2 each). This allows identification of the different hydrological consequences of land-use/land-cover change, particularly the fallow shortening and the consequent degradation of topsoil. The main land surface change is a 75% increase in crusted soil area. Runoff increased by more than 20% on average between the two periods while flood duration decreased by 50% on average. However, runoff values remained largely constant in the lower part of the northern basin due to a strong increase in in-channel infiltration. Editor D. Koutsoyiannis; Associate editor T. Wagener

Sample Stratification in Verification of Ensemble Forecasts of Continuous Scalar Variables: Potential Benefits and Pitfalls

AbstractIn the verification field, stratification is the process of dividing the sample of forecast–observation pairs into quasi-homogeneous subsets, in order to learn more on how forecasts behave under specific conditions. A general framework for stratification is presented for the case of ensemble forecasts of continuous scalar variables. Distinction is made between forecast-based, observation-based, and external-based stratification, depending on the criterion on which the sample is stratified. The formalism is applied to two widely used verification measures: the continuous ranked probability score (CRPS) and the rank histogram. For both, new graphical representations that synthesize the added information are proposed. Based on the definition of calibration, it is shown that the rank histogram should be used within a forecast-based stratification, while an observation-based stratification leads to significantly nonflat histograms for calibrated forecasts. Nevertheless, as previous studies have warned,...

Improved subpixel monitoring of seasonal snow cover: A case study in the Alps

The snow coverage area (SCA) is one of the most important parameters for cryospheric studies. The use of remote sensing imagery can complement field measurements by providing means to derive SCA with a high temporal frequency and covering large areas. Images acquired by the Moderate Resolution Imaging Spectroradiometer (MODIS) are perhaps the most widely used data to retrieve SCA maps. Some MODIS derived algorithms are available for subpixel SCA estimation, as MODSCAG and MODImLab. Both algorithms make use of spectral unmixing techniques using a fixed set of snow, rocks and other materials spectra (endmembers). We aim to improve the performance of a modified version of MODIm-Lab algorithm by exploring advanced spectral unmixing techniques. Furthermore, we make use of endmember induction algorithms to obtain the endmembers from the data itself instead of using a fixed spectral library. We validate the proposed approach on a case study in the mountainous region of the Alps.

Using Meteorological Analogues for Reordering Postprocessed Precipitation Ensembles in Hydrological Forecasting

Meteorological ensemble forecasts are nowadays widely used as input of hydrological models for probabilistic streamflow forecasting. These forcings are frequently biased and have to be statistically post-processed, using most of the time univariate techniques that apply independently to individual locations, lead time and weather variables. Post-processed ensemble forecasts therefore need to be reordered so as to reconstruct suitable multivariate dependence structures. The Schaake shuffle and ensemble copula coupling are the two most popular methods for this purpose. This paper proposes two adaptations of them that make use of meteorological analogues for reconstructing spatio-temporal dependence structures of precipitation forecasts. Performances of the original and adapted techniques are compared through a multi-step verification experiment using real forecasts from the European Centre for Medium-Range Weather Forecasts. This experiment evaluates multivariate precipitation forecasts but also the corresponding streamflow forecasts that derive from hydrological modeling. Results show that the relative performances of the different reordering methods vary depending on the verification step. In particular, the standard Schaake shuffle is found to perform poorly when evaluated on streamflow. This emphasizes the crucial role of the precipitation spatio-temporal dependence structure in hydrological ensemble forecasting.

Multi-Criteria Evaluation of Snowpack Simulations in Complex Alpine Terrain Using Satellite and In Situ Observations

This work presents an extensive evaluation of the Crocus snowpack model over a rugged and highly glacierized mountain catchment (Arve valley, Western Alps, France) from 1989 to 2015. The simulations were compared and evaluated using in-situ point snow depth measurements, in-situ seasonal and annual glacier surface mass balance, snow covered area evolution based on optical satellite imagery at 250 m resolution (MODIS sensor), and the annual equilibrium-line altitude of glaciers, derived from satellite images (Landsat, SPOT, and ASTER). The snowpack simulations were obtained using the Crocus snowpack model driven by the same, originally semi-distributed, meteorological forcing (SAFRAN) reanalysis using the native semi-distributed configuration, but also a fully distributed configuration. The semi-distributed approach addresses land surface simulations for discrete topographic classes characterized by elevation range, aspect, and slope. The distributed approach operates on a 250-m grid, enabling inclusion of terrain shadowing effects, based on the same original meteorological dataset. Despite the fact that the two simulations use the same snowpack model, being potentially subjected to same potential deviation from the parametrization of certain physical processes, the results showed that both approaches accurately reproduced the snowpack distribution over the study period. Slightly (although statistically significantly) better results were obtained by using the distributed approach. The evaluation of the snow cover area with MODIS sensor has shown, on average, a reduction of the Root Mean Squared Error (RMSE) from 15.2% with the semi-distributed approach to 12.6% with the distributed one. Similarly, surface glacier mass balance RMSE decreased from 1.475 m of water equivalent (W.E.) for the semi-distributed simulation to 1.375 m W.E. for the distribution. The improvement, observed with a much higher computational time, does not justify the recommendation of this approach for all applications; however, for simulations that require a precise representation of snowpack distribution, the distributed approach is suggested.