Seasonal forecasting of snow resources at Alpine sites

Climate warming in mountain regions is resulting in glacier shrinking, seasonal snow cover reduction, and changes in the amount and seasonality of meltwater runoff, with consequences on water availability. Droughts are expected to become more severe in the future with economical and environmental losses both locally and downstream. Effective adaptation strategies involve multiple timescales, and seasonal forecasts can help in the optimization of the available snow and water resources with a lead time of several months. We developed a prototype to generate seasonal forecasts of snow depth and snow water equivalent with a starting date of 1 November and a lead time of 7 months, so up to 31 May of the following year. The prototype has been co-designed with end users in the field of water management, hydropower production and mountain ski tourism, meeting their needs in terms of indicators, time resolution of the forecasts and visualization of the forecast outputs. In this paper we present the modelling chain, based on the seasonal forecasts of the ECMWF and Meteo-France seasonal prediction systems, made available through the Copernicus Climate Change Service (C3S) Climate Data Store. Seasonal forecasts of precipitation, near-surface air temperature, radiative fluxes, wind and relative humidity are bias-corrected and downscaled to three sites in the Western Italian Alps and finally used as input for the physically based multi-layer snow model SNOWPACK. Precipitation is bias-corrected with a quantile mapping method using ERA5 reanalysis as a reference and then downscaled with the RainFARM stochastic procedure in order to allow an estimate of uncertainties due to the downscaling method. The impacts of precipitation bias adjustment and downscaling on the forecast skill have been investigated. The skill of the prototype in predicting the deviation of monthly snow depth with respect to the normal conditions from November to May in each season of the hindcast period 1995-2015 is demonstrated using both deterministic and probabilistic metrics. Forecast skills are determined with respect to a simple forecasting method based on the climatology, and station measurements are used as reference data. The prototype shows good skills at predicting the tercile category, i.e. snow depth below and above normal, in the winter (lead times: 2-3-4 months) and spring (lead times: 5-6-7 months) ahead: snow depth is predicted with higher accuracy (Brier skill score) and higher discrimination (area under the relative operating characteristics (ROC) curve skill score) with respect to a simple forecasting method based on the climatology. Ensemble mean monthly snow depth forecasts are significantly correlated with observations not only at short lead times of 1 and 2 months (November and December) but also at lead times of 5 and 6 months (March and April) when employing the ECMWFS5 forcing. Moreover the prototype shows skill at predicting extremely dry seasons, i.e. seasons with snow depth below the 10th percentile, while skills at predicting snow depth above the 90th percentile are model-, station- and score-dependent.The bias correction of precipitation forecasts is essential in the case of large biases in the global seasonal forecast system (MFS6) to reconstruct a realistic snow depth climatology; however, no remarkable differences are found among the skill scores when the precipitation input is bias-corrected, downscaled, or bias-corrected and downscaled, compared to the case in which raw data are employed, suggesting that skill scores are weakly sensitive to the treatment of the precipitation input

Temperature and precipitation seasonal forecasts over the Mediterranean region: added value compared to simple forecasting methods

This study considers a set of state-of-the-art seasonal forecasting systems (ECMWF, MF, UKMO, CMCC, DWD and the corresponding multi-model ensemble) and quantifies their added value (if any) in predicting seasonal and monthly temperature and precipitation anomalies over the Mediterranean region compared to a simple forecasting method based on the ERA5 climatology (CTRL) or the persistence of the ERA5 anomaly (PERS). This analysis considers two starting dates, May 1st and November 1st and the forecasts at lead times up to 6 months for each year in the period 1993–2014. Both deterministic and probabilistic metrics are employed to derive comprehensive information on the forecast quality in terms of association, reliability/resolution, discrimination, accuracy and sharpness. We find that temperature anomalies are better reproduced than precipitation anomalies with varying spatial patterns across different forecast systems. The Multi-Model Ensemble (MME) shows the best agreement in terms of anomaly correlation with ERA5 precipitation, while PERS provides the best results in terms of anomaly correlation with ERA5 temperature. Individual forecast systems and MME outperform CTRL in terms of accuracy of tercile-based forecasts up to lead time 5 months and in terms of discrimination up to lead time 2 months. All seasonal forecast systems also outperform elementary forecasts based on persistence in terms of accuracy and sharpness

Seasonal forecasting of snow resources at Alpine sites

Climate warming in mountain regions is resulting in glacier shrinking, seasonal snow cover reduction, and changes in the amount and seasonality of meltwater runoff, with consequences on water availability. Droughts are expected to become more severe in the future with economical and environmental losses both locally and downstream. Effective adaptation strategies involve multiple timescales, and seasonal forecasts can help in the optimization of the available snow and water resources with a lead time of several months. We developed a prototype to generate seasonal forecasts of snow depth and snow water equivalent with a starting date of 1 November and a lead time of 7 months, so up to 31 May of the following year. The prototype has been co-designed with end users in the field of water management, hydropower production and mountain ski tourism, meeting their needs in terms of indicators, time resolution of the forecasts and visualization of the forecast outputs. In this paper we present the modelling chain, based on the seasonal forecasts of the ECMWF and Météo-France seasonal prediction systems, made available through the Copernicus Climate Change Service (C3S) Climate Data Store. Seasonal forecasts of precipitation, near-surface air temperature, radiative fluxes, wind and relative humidity are bias-corrected and downscaled to three sites in the Western Italian Alps and finally used as input for the physically based multi-layer snow model SNOWPACK. Precipitation is bias-corrected with a quantile mapping method using ERA5 reanalysis as a reference and then downscaled with the RainFARM stochastic procedure in order to allow an estimate of uncertainties due to the downscaling method. The impacts of precipitation bias adjustment and downscaling on the forecast skill have been investigated. The skill of the prototype in predicting the deviation of monthly snow depth with respect to the normal conditions from November to May in each season of the hindcast period 1995–2015 is demonstrated using both deterministic and probabilistic metrics. Forecast skills are determined with respect to a simple forecasting method based on the climatology, and station measurements are used as reference data. The prototype shows good skills at predicting the tercile category, i.e. snow depth below and above normal, in the winter (lead times: 2–3–4 months) and spring (lead times: 5–6–7 months) ahead: snow depth is predicted with higher accuracy (Brier skill score) and higher discrimination (area under the relative operating characteristics (ROC) curve skill score) with respect to a simple forecasting method based on the climatology. Ensemble mean monthly snow depth forecasts are significantly correlated with observations not only at short lead times of 1 and 2 months (November and December) but also at lead times of 5 and 6 months (March and April) when employing the ECMWFS5 forcing. Moreover the prototype shows skill at predicting extremely dry seasons, i.e. seasons with snow depth below the 10th percentile, while skills at predicting snow depth above the 90th percentile are model-, station- and score-dependent. The bias correction of precipitation forecasts is essential in the case of large biases in the global seasonal forecast system (MFS6) to reconstruct a realistic snow depth climatology; however, no remarkable differences are found among the skill scores when the precipitation input is bias-corrected, downscaled, or bias-corrected and downscaled, compared to the case in which raw data are employed, suggesting that skill scores are weakly sensitive to the treatment of the precipitation input.</p

On the increased climate sensitivity in the EC-Earth model from CMIP5 to CMIP6

Many modelling groups that contribute to CMIP6 (Coupled Model Intercomparison Project Phase 6) have found a larger equilibrium climate sensitivity (ECS) with their latest model versions compared with the values obtained with the earlier versions used in CMIP5. This is also the case for the EC-Earth model. Therefore, in this study, we investigate what developments since the CMIP5 era could have caused the increase in the ECS in this model. Apart from increases in the horizontal and vertical resolution, the EC-Earth model has also substantially changed the representation of aerosols; in particular, it has introduced a more sophisticated description of aerosol indirect effects. After testing the model with some of the recent updates switched off, we find that the ECS increase can be attributed to the more advanced treatment of aerosols, with the largest contribution coming from the effect of aerosols on cloud microphysics (cloud lifetime or second indirect effect). The increase in climate sensitivity is unrelated to model tuning, as all experiments were performed with the same tuning parameters and only the representation of the aerosol effects was changed. These results cannot be generalised to other models, as their CMIP5 and CMIP6 versions may differ with respect to aspects other than the aerosol-cloud interaction, but the results highlight the strong sensitivity of ECS to the details of the aerosol forcing

Impacts of a weakened AMOC on precipitation over the Euro-Atlantic region in the EC-Earth3 climate model

Given paleoclimatic evidence that the Atlantic Meridional Overturning Circulation (AMOC) may affect the global climate system, we conduct model experiments with EC-Earth3, a state-of-the-art GCM, to specifically investigate, for the first time, mechanisms of precipitation change over the Euro-Atlantic sector induced by a weakened AMOC. We artificially weaken the strength of the AMOC in the model through the release of a freshwater anomaly into the Northern Hemisphere high latitude ocean, thereby obtaining a similar to 57% weaker AMOC with respect to its preindustrial strength for 60 model years. Similar to prior studies, we find that Northern Hemisphere precipitation decreases in response to a weakened AMOC. However, we also find that the frequency of wet days increases in some regions. By computing the atmospheric moisture budget, we find that intensified but drier storms cause less precipitation over land. Nevertheless, changes in the jet stream tend to enhance precipitation over northwestern Europe. We further investigate the association of precipitation anomalies with large-scale atmospheric circulations by computing weather regimes through clustering of geopotential height daily anomalies. We find an increase in the frequency of the positive phase of the North Atlantic Oscillation (NAO+), which is associated with an increase in the occurrence of wet days over northern Europe and drier conditions over southern Europe. Since a similar to 57% reduction in the AMOC strength is within the inter-model range of projected AMOC declines by the end of the twenty-first century, our results have implications for understanding the role of AMOC in future hydrological changes

The sensitivity of Euro-Atlantic regimes to model horizontal resolution

There is growing evidence that the atmospheric dynamics of the Euro-Atlantic sector during winter is driven in part by the presence of quasi-persistent regimes. However, general circulation models typically struggle to simulate these with, for example, an overly weakly persistent blocking regime. Previous studies have showed that increased horizontal resolution can improve the regime structure of a model but have so far only considered a single model with only one ensemble member at each resolution, leaving open the possibility that this may be either coincidental or model dependent. We show that the improvement in regime structure due to increased resolution is robust across multiple models with multiple ensemble members. However, while the high-resolution models have notably more tightly clustered data, other aspects of the regimes may not necessarily improve and are also subject to a large amount of sampling variability that typically requires at least three ensemble members to surmount

11 years of limnological research in the Gran Paradiso National Park (GPNP, Torino, Italy): between research and conservation

Established in 1921, the Gran Paradiso National Park (Western Italian Alps, Torino) is the oldest protected area in Italy and one of the oldest in the world. During its nearly century-old history it was able to conserve most of the terrestrial alpine biodiversity and have the invaluable merit of having saved from extinction the Alpine ibex (Capra ibex), the symbol of the GPNP as well as of the alpine wilderness. However in the last decades, at a local level, most of the dangers to the integrity of the GPNP biodiversity derived from exploitation and mismanagement of water resources (e.g. dams and connected infrastructures construction, rivers channelization, alien fish introductions, water eutrophication). To address these relatively new conservation issues the GPNP had to fill a gap in its body of knowledge. In 2006 a long term monitoring campaign of alpine lakes began, starting a 11-years long research season on aquatic ecosystems, which turned out to influence the conservation policies of the GPNP. In the following years (1) the participation of the GPNP as a partner of the EU financed FP7 ACQWA (Assessing Climate Impacts on the Quantity and Quality of Water) project, (2) the obtainment of an important co-financing within the LIFE+ Project BIOAQUAE (Biodiversity Improvement Of Alpine Aquatic Ecosystems, www.bioaquae.eu), as well as (3) the collaboration with an increasing number of research centers and universities, fueled for a long time (2008-2017) the research and conservation activities in aquatic habitats. The most prominent characteristic of the limnological research carried out in the GPNP is its strong connection to applied conservation issues, often providing feasible indications which convinced the GPNP authorities to take the path of active conservation. The BIOAQUAE project and its conservation actions (the eradication of alien fish from alpine lakes, the re-oligotrophication of aquatic habitats through the use of phyto-depuration plans, and the conservation actions for the Marble trout Salmo marmoratus) represent a first important achievement of this new attitude of GPNP towards the conservation of aquatic environments. At the same time the long-term limnological studies are progressively creating a database of ecological variables which will provide a reference against which to quantify the effects of the global change, inevitably affecting the protected area. The aim of this presentation is to tell about the history of the limnological research and of its achievements in the GPNP as an example of integration between biodiversity conservation and scientific research, in a protected area which is just an hour's drive from the conference venue

Aquifer recharge in the Piedmont Alpine zone: Historical trends and future scenarios

The spatial and temporal variability of air temperature, precipitation, actual evapotranspiration (AET) and their related water balance components, as well as their responses to anthropogenic climate change, provide fundamental information for an effective management of water resources and for a proactive involvement of users and stakeholders, in order to develop and apply adaptation and mitigation strategies at the local level. In this study, using an interdisciplinary research approach tailored to water management needs, we evaluate the past, present and future quantity of water potentially available for drinking supply in the water catchments feeding the about 2.3 million inhabitants of the Turin metropolitan area (the former Province of Turin, north-western Italy), considering climatologies at the quarterly and yearly timescales. Observed daily maximum surface air temperature and precipitation data from 1959 to 2017 were analysed to assess historical trends, their significance and the possible cross-correlations between the water balance components. Regional climate model (RCM) simulations from a small ensemble were analysed to provide mid-century projections of the difference between precipitation and AET for the area of interest in the future CMIP5 scenarios RCP4.5 (stabilization) and RCP8.5 (business as usual). Temporal and spatial variations in recharge were approximated with variations of drainage. The impact of irrigation, and of snowpack variability, on the latter was also assessed. The other terms of water balance were disregarded because they are affected by higher uncertainty. The analysis over the historical period indicated that the driest area of the study region displayed significant negative annual (and spring) trends of both precipitation and drainage. Results from field experiments were used to model irrigation, and we found that relatively wetter watersheds in the northern and in the southern parts behave differently, with a significant increase of AET due to irrigation. The analysis of future projections suggested almost stationary conditions for annual data. Regarding quarterly data, a slight decrease in summer drainage was found in three out of five models in both emission scenarios. The RCM ensemble exhibits a large spread in the representation of the future drainage trends. The large interannual variability of precipitation was also quantified and identified as a relevant risk factor for water management, expected to play a major role also in future decades

MODIS time series contribution for the estimation of nutritional properties of alpine grassland

This is an Accepted Manuscript of an article published by Taylor & Francis in European Journal of Remote Sensing on 17th February 2017, available online: https://doi.org/10.5721/EuJRS20164936Despite the Normalised Difference Vegetation Index (NDVI) has been used to make predictions on forage quality, its relationship with bromatological field data has not been widely tested. This relationship was investigated in alpine grasslands of the Gran Paradiso National Park (Italian Alps). Predictive models were built using remotely sensed derived variables (NDVI and phenological information computed from MODIS) in combination with geo-morphometric data as predictors of measured biomass, crude protein, fibre and fibre digestibility, obtained from 142 grass samples collected within 19 experimental plots every two weeks during the whole 2012 growing season. The models were both cross-validated and validated on an independent dataset (112 samples collected during 2013). A good predictability ability was found for the estimation of most of the bromatological measures, with a considerable relative importance of remotely sensed derived predictors; instead, a direct use of NDVI values as a proxy of bromatological variables appeared not to be supported

Preeclampsia-Associated Alteration of DNA Methylation in Fetal Endothelial Progenitor Cells

ObjectiveThe pregnancy complication preeclampsia represents an independent risk factor for cardiovascular disease. Our previous research shows a diminished function of fetal endothelial colony-forming cells (ECFC), a proliferative subgroup of endothelial progenitor cells (EPC) in preeclampsia. The aim of this study was to further investigate whether DNA methylation of fetal EPC is affected in preeclampsia.MethodsThe genomic methylation pattern of fetal ECFC from uncomplicated and preeclamptic pregnancies was compared for 865918 CpG sites, and genes were classified into gene networks. Low and advanced cell culture passages were compared to explore whether expansion of fetal ECFC in cell culture leads to changes in global methylation status and if methylation characteristics in preeclampsia are maintained with increasing passage.ResultsA differential methylation pattern of fetal ECFC from preeclampsia compared to uncomplicated pregnancy was detected for a total of 1266 CpG sites in passage 3, and for 2362 sites in passage 5. Key features of primary networks implicated by methylation differences included cell metabolism, cell cycle and transcription and, more specifically, genes involved in cell-cell interaction and Wnt signaling. We identified an overlap between differentially regulated pathways in preeclampsia and cardiovascular system development and function. Cell culture passages 3 and 5 showed similar gene network profiles, and 1260 out of 1266 preeclampsia-associated methylation changes detected in passage 3 were confirmed in passage 5.ConclusionMethylation modification caused by preeclampsia is stable and detectable even in higher cell culture passages. An epigenetically modified endothelial precursor may influence both normal morphogenesis and postnatal vascular repair capacity. Further studies on epigenetic modifications in complicated pregnancies are needed to facilitate development of EPC based therapies for cardiovascular alterations