Benefits from using combined dynamical-statistical downscaling approaches - Lessons from a case study in the Mediterranean region

Abstract. Various downscaling techniques have been developed to bridge the scale gap between global climate models (GCMs) and finer scales required to assess hydrological impacts of climate change. Such techniques may be grouped into two downscaling approaches: the deterministic dynamical downscaling (DD) and the statistical downscaling (SD). Although SD has been traditionally seen as an alternative to DD, recent works on statistical downscaling have aimed to combine the benefits of these two approaches. The overall objective of this study is to assess whether a DD processing performed before the SD permits to obtain more suitable climate scenarios for basin scale hydrological applications starting from GCM simulations. The case study presented here focuses on the Apulia region (South East of Italy, surface area about 20 000 km2), characterised by a typical Mediterranean climate; the monthly cumulated precipitation and monthly mean of daily minimum and maximum temperature distribution were examined for the period 1953–2000. The fifth-generation ECHAM model from the Max-Planck-Institute for Meteorology was adopted as GCM. The DD was carried out with the Protheus system (ENEA), while the SD was performed through a monthly quantile-quantile correction. The SD resulted efficient in reducing the mean bias in the spatial distribution at both annual and seasonal scales, but it was not able to correct the miss-modelled non-stationary components of the GCM dynamics. The DD provided a partial correction by enhancing the spatial heterogeneity of trends and the long-term time evolution predicted by the GCM. The best results were obtained through the combination of both DD and SD approaches

Deep-Ocean dissolved organic matter reactivity along the Mediterranea Sea: does size matter?

Original research paperDespite of the major role ascribed to marine dissolved organic matter (DOM) in the global carbon cycle, the reactivity of this pool in the dark ocean is still poorly understood. Present hypotheses, posed within the size-reactivity continuum (SRC) and the microbial carbon pump (MCP) conceptual frameworks, need further empirical support. Here, we provide field evidence of the soundness of the SRC model. We sampled the high salinity core-of-flow of the Levantine Intermediate Water along its westward route through the entire Mediterranean Sea. At selected sites, DOM was size-fractionated in apparent high (aHMW) and low (aLMW) molecular weight fractions using an efficient ultrafiltration cell. A percentage decline of the aHMW DOM from 68–76% to 40–55% was observed from the Levantine Sea to the Strait of Gibraltar in parallel with increasing apparent oxygen utilization (AOU). DOM mineralization accounted for 30±3% of the AOU, being the aHMW fraction solely responsible for this consumption, verifying the SRC model in the field. We also demonstrate that, in parallel to this aHMW DOM consumption, fluorescent humic-like substances accumulate in both fractions and protein-like substances decline in the aLMW fraction, thus indicating that not only size matters and providing field support to the MCP modelHOTMIX (grant number CTM2011–30010-C02 01-MAR and 02-MAR) and the project FERMIO (MINECO, CTM2014-57334-JIN), both co-financed with FEDER funds; (reference BES-2012- 056175) from the Spanish Ministry of Economy, Industry and Competitivenes; the project MODMED from CSIC (PIE, 201730E020) and CSIC Program “Junta para la Ampliación de Estudios” co-financed by the ESF (reference JAE DOC 040)Versión del editor2,92

Predicting new snow density in the Italian Alps: A variability analysis based on 10\ua0years of measurements

Despite its strong impact on the time evolution of the snowpack, current estimation of new snow density ((hn)) is usually accomplished either by using local empirical techniques or by assuming a constant snow density. Faced with the lack of an estimation model of (hn) valid for a wide spatial scale and supported by a suitable number of observations, this study aims to develop simple monthly linear regression models at scale of the entire Italian Alpine chain based on 12,112 snowfall observations at 122 stations, using only air temperature as predictor. Moreover, the remaining variance is investigated in both time and space, also considering some qualitative features of the snowfall events. The daily (hn) measurements present a mean value of 115kgm(-3) (105 and 159kgm(-3) for dry and wet conditions, respectively). The mean air temperature of the 24hr preceding the snowfall event has been found to be the best predictor of the (hn), within 31% of uncertainty. The analysis of associated residues allows supporting the idea that the adoption of a more local approach than the one analysed here is not able to substantially increase the predictive capabilities of the model. In fact, the main factor explaining the remaining variance over the air temperature is the wind, but in a complex orography, as mountain regions are, supplying realistic local wind fields is particularly challenging. Therefore, we conclude that using only the daily mean temperature as predictor is a good choice for estimating daily new snow density at scale of Italian Alpine chain, as well as at more regional scale

Colonization and extinction dynamics and their link to the distribution of European trees at the continental scale

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Beyond mean fitness: Demographic stochasticity and resilience matter at tree species climatic edges

Aim Linking local population dynamics and species distributions is crucial to predicting the impacts of climate change. Although many studies focus on the mean fitness of populations, theory shows that species distributions can be shaped by demographic stochasticity or population resilience. Here, we examine how mean fitness (measured by invasion rate), demographic stochasticity and resilience (measured by the ability to recover from disturbance) constrain populations at the edges compared with the climatic centre. Location Europe: Spain, France, Germany, Finland and Sweden. Period Forest inventory data used for fitting the models cover the period from 1985 to 2013. Major taxa Dominant European tree species; angiosperms and gymnosperms. Methods We developed dynamic population models covering the entire life cycle of 25 European tree species with climatically dependent recruitment models fitted to forest inventory data. We then ran simulations using integral projection and individual-based models to test how invasion rates, risk of stochastic extinction and ability to recover from stochastic disturbances differ between the centre and edges of the climatic niches of species. Results Results varied among species, but in general, demographic constraints were stronger at warm edges and for species in harsher climates. Conversely, recovery was more limiting at cold edges. In addition, we found that for several species, constraints at the edges were attributable to demographic stochasticity and capacity for recovery rather than mean fitness. Main conclusions Our results highlight that mean fitness is not the only mechanism at play at the edges; demographic stochasticity and population capacity to recover also matter for European tree species. To understand how climate change will drive species range shifts, future studies will need to analyse the interplay between population mean growth rate and stochastic demographic processes in addition to disturbances

New insights into the organic carbon export in the Mediterranean Sea from 3-D modeling

International audienceThe Mediterranean Sea is one of the most oligotrophic regions of the oceans, and nutrients have been shown to limit both phytoplankton and bacterial activities, resulting in a potential major role of dissolved organic carbon (DOC) export in the biological pump. Strong DOC accumulation in surface waters is already well documented, though measurements of DOC stocks and export flux are still sparse and associated with major uncertainties. This study provides the first basin-scale overview and analysis of organic carbon stocks and export fluxes in the MediterraneanSea through a modeling approach based on a coupled model combining a mechanistic biogeochemical model (Eco3M-MED) and a high-resolution (eddy-resolving) hydrodynamic simulation (NEMO-MED12). The model is shown to reproduce the main spatial and seasonal biogeochemical characteristics of the Mediterranean Sea. Model estimations of carbon export are also of the same order of magnitude as estimations from in situ observations, and their respective spatial patterns are mutually consistent. Strong differences between the western and eastern basins are evidenced by the model for organic carbon export. Though less oligotrophic than the eastern basin, the western basin only supports 39 %of organic carbon (particulate and dissolved) export. Another major result is that except for the Alboran Sea, the DOC contribution to organic carbon export is higher than that of particulate organic carbon (POC) throughout the MediterraneanSea, especially in the eastern basin. This paper also investigates the seasonality of DOC and POC exports as well asthe differences in the processes involved in DOC and POC exports in light of intracellular quotas. Finally, according tothe model, strong phosphate limitation of both bacteria and phytoplankton growth is one of the main drivers of DOC accumulation and therefore of export