Aerosol deposition and origin in French mountains estimated with soil inventories of 210Pb and artificial radionuclides

Radionuclide inventories were measured in soils from different French mountainous areas: Chaîne des Puys (Massif Central), Eastern Corsica, Jura, Montagne Noire, Savoie, Vosges and Rhine Valley. 210Pb soil inventories were used to estimate long-term (>75 yr) deposition of submicron aerosols. Whereas 210Pb total deposition is explained partly by wet deposition, as demonstrated by increase of 210Pb inventory with annual rainfall; a part of 210Pb in the soils of higher altitude is caused by orographic depositions. Using measurements of radionuclides coming from nuclear aerial weapon tests (137Cs and Pu isotopes), we were able to estimate the origin of aerosols deposited in high-altitude sites and to confirm the importance of occult deposition and feeder–seeder mechanism. Using a simple mass balance model, we estimate that occult deposition and feeder–seeder mechanisms account to more than 50% of total deposition of 210Pb and associated submicron aerosols in French altitude sites

Thermal response of Sanabria lake to global change (NW Spain)

Are large water bodies able to act as sensors of global change? As accumulators of water and heat, some of their thermal characteristics might be altered by long term (decadal) hydrometeorological changes and thus may be used as indicators of the effects of global change on fluvial ecosystems. This work focuses on the effect of global change (climate change plus water quantity and land use changes) in the internal organization of Sanabria Lake, specifically in its thermal annual cycle. The existence of temporal trends in the thermal behaviour of the lake was investigated based on the water temperature profiles are available since 1986. Data analyses include the non-parametric Mann-Kendall trend test and the Sen slope estimate to evaluate long term and seasonal patterns of hydrometeorological and in-lake thermal variables. The main results surprisingly point to a net lake cooling that could be explained by a stronger thermocline and a weaker vertical transfer of heat to the hypolimnion during the stratification period. These results contribute to understand and quantify the effects of global change on Iberian freshwater bodies.Peer ReviewedPostprint (published version

Monitoring of acid deposition in central Yakutia

The results of monitoring acid precipitations showed that subacid-alkalescent precipitations, acidity of which varies in close limits (pH 5.89-7.36) prevail in Yakutsk region. Acidity of solid precipitation is very similar to acidity of rain precipitations and comprises 6.70-7.22 for operating pH of rain precipitations (6.85 in average) and 5.89-7.36 for solid precipitations (6.71 in average). The most considerable deviations of acidity-alkalinity of solid precipitation from the average value are observed at the beginning and in the middle of winter period. According to the monitoring results we made an evaluation of the value of chemical components fall-out in atmospheric precipitations. Annual inflow of H^+ ions from atmosphere to the earth surface is much less then critical load for the forest and water ecosystems. Maximal values of sulfur compounds (0.51g/m^2) and nitrogen (2.07g/m^2) fall-out at the monitoring station fall on June and exceed ecostandard and parameters of ecological emergency situation in a volume of nitrogen precipitations

Post-failure evolution analysis of a rainfall-triggered landslide by multi-temporal interferometry SAR approaches integrated with geotechnical analysis

Persistent Scatterers Interferometry (PSI) represents one of the most powerful techniques for Earth's surface deformation processes' monitoring, especially for long-term evolution phenomena. In this work, a dataset of 34 TerraSAR-X StripMap images (October 2013–October 2014) has been processed by two PSI techniques - Coherent Pixel Technique-Temporal Sublook Coherence (CPT-TSC) and Small Baseline Subset (SBAS) - in order to study the evolution of a slow-moving landslide which occurred on February 23, 2012 in the Papanice hamlet (Crotone municipality, southern Italy) and induced by a significant rainfall event (185 mm in three days). The mass movement caused structural damage (buildings' collapse), and destruction of utility lines (gas, water and electricity) and roads. The results showed analogous displacement rates (30–40 mm/yr along the Line of Sight – LOS-of the satellite) with respect to the pre-failure phase (2008–2010) analyzed in previous works. Both approaches allowed detect the landslide-affected area, however the higher density of targets identified by means of CPT-TSC enabled to analyze in detail the slope behavior in order to design possible mitigation interventions. For this aim, a slope stability analysis has been carried out, considering the comparison between groundwater oscillations and time-series of displacement. Hence, the crucial role of the interaction between rainfall and groundwater level has been inferred for the landslide triggering. In conclusion, we showed that the integration of geotechnical and remote sensing approaches can be seen as the best practice to support stakeholders to design remedial works.Peer ReviewedPostprint (author's final draft

Novel stacking models for improved extreme rainfall predictions under climate change scenarios.

Future projections under global warming scenarios of local extreme precipitations by downscaling models is still open challenge. A number of downscaling statistical models have been proposed to link large scale atmospheric circulation features, as simulated by Global Circulation Models (GCMs) and/or Regional Circulation Models (RCMs), to the temporal and spatial distribution of local rainfalls. Despite the efforts, comparisons between simulations and observations show that statistical downscaling methods, although able to realistically reproduce most of the mean rainfall attributes as seasonal or monthly rainfall amount, fail to simulate extreme precipitation with acceptable accuracy. This is due to the difficulties to: (i) select the optimal set of atmospheric variables used as predictors; (ii) solve the non-linear dependencies that link the rains to the atmospheric variables; (iii) assess the temporal dependencies between wet and dry states. To overcome such criticalities, in order to improve extreme precipitation forecasting, in this study we introduce in rainfall downscaling a paradigm already known in other disciplines of data science: the "stacking models". Stacking models combine different simulations from multiple predictive models. According to this approach we used Random Forest, extreme gradient boosting and Non-homogeneous Hidden Markov Model (NHMM). The validation was performed first on the individual models, calibrating the parameters individually and evaluating them globally with a cross validation approach. The performance of the proposed stacking model is assessed by comparing the daily rainfall amount simulations with those obtained by a state-of-the-art NHMM model, in which the probability of the rainfall occurrence is just modeled using a logistic regression with parameters depending upon climatology variables. We show that the stacking model outperforms the latter model, especially in simulating the extreme precipitations. Furthermore, such performance improvement is obtained by using a minor number of atmospheric predictors. Once the downscaling model has been calibrated and validated, we evaluated changes of precipitation extremes under climate change scenarios. The simulations were performed using the variables obtained from a GCM, Community Climate System Model v4 - NCAR, whose scenario is defined by CMIP5 - RCP 8.5. To evaluate the confidence bands of the simulated rainfall it was used an ensemble of simulations obtained by running the latter GCM with different initial conditions. The Lazio region was chosen as a study case. The Lazio Region is located in Central Italy, whose hydrogeological features make it particularly vulnerable to eventual future changes of hydrological cycle such as those induced by climate change. The Mediterranean is made up of many of these vulnerable areas, which makes the application of the method to this case study of general interest

Formulations of moist thermodynamics for atmospheric modelling

Internal energy, enthalpy and entropy are the key quantities to study thermodynamic properties of the moist atmosphere, because they correspond to the First (internal energy and enthalpy) and Second (entropy) Laws of thermodynamics. The aim of this chapter is to search for analytical formulas for the specific values of enthalpy and entropy and for the moist-air mixture composing the atmosphere. The Third Law of thermodynamics leads to the definition of absolute reference values for thermal enthalpies and entropies of all atmospheric species. It is shown in this Chapter 22 that it is possible to define and compute a general moist-air entropy potential temperature, which is really an equivalent of the moist-air specific entropy in all circumstances (saturated, or not saturated). Similarly, it is shown that it is possible to define and compute the moist-air specific enthalpy, which is different from the thermal part of what is called Moist-Static-Energy in atmospheric studies.Comment: 44 pages, 8 figures, URL:http://www.worldscientific.com/doi/abs/10.1142/9781783266913_002

Does the Danube exist? Versions of reality given by various regional climate models and climatological datasets

We present an intercomparison and verification analysis of several regional climate models (RCMs) nested into the same run of the same Atmospheric Global Circulation Model (AGCM) regarding their representation of the statistical properties of the hydrological balance of the Danube river basin for 1961-1990. We also consider the datasets produced by the driving AGCM, from the ECMWF and NCEP-NCAR reanalyses. The hydrological balance is computed by integrating the precipitation and evaporation fields over the area of interest. Large discrepancies exist among RCMs for the monthly climatology as well as for the mean and variability of the annual balances, and only few datasets are consistent with the observed discharge values of the Danube at its Delta, even if the driving AGCM provides itself an excellent estimate. Since the considered approach relies on the mass conservation principle and bypasses the details of the air-land interface modeling, we propose that the atmospheric components of RCMs still face difficulties in representing the water balance even on a relatively large scale. Their reliability on smaller river basins may be even more problematic. Moreover, since for some models the hydrological balance estimates obtained with the runoff fields do not agree with those obtained via precipitation and evaporation, some deficiencies of the land models are also apparent. NCEP-NCAR and ERA-40 reanalyses result to be largely inadequate for representing the hydrology of the Danube river basin, both for the reconstruction of the long-term averages and of the seasonal cycle, and cannot in any sense be used as verification. We suggest that these results should be carefully considered in the perspective of auditing climate models and assessing their ability to simulate future climate changes.Comment: 25 pages 8 figures, 5 table