Mapping the mean monthly precipitation of a small island using kriging with external drifts

This study focuses on the spatial distribution of mean annual and monthly precipitation in a small island (1128 km²) named Martinique, located in the Lesser Antilles. Only 35 meteorological stations are available on the territory, which has a complex topography. With a digital elevation model (DEM), 17 covariates that are likely to explain precipitation were built. Several interpolation methods, such as regression-kriging (????????, ????????, and ????????) and external drift kriging (??????) were tested using a cross-validation procedure. For the regression methods, predictors were chosen by established techniques whereas a new approach is proposed to select external drifts in a kriging which is based on a stepwise model selection by the Akaike Information Criterion (AIC). The prediction accuracy was assessed at validation sites with three different skill scores. Results show that using methods with no predictors such as inverse distance weighting (??????) or universal kriging (????) is inappropriate in such a territory. ?????? appears to outperform regression methods for any criteria, and selecting predictors by our approach improves the prediction of mean annual precipitation compared to kriging with only elevation as drift. Finally, the predicting performance was also studied by varying the size of the training set leading to less conclusive results for ?????? and its performance. Nevertheless, the proposed method seems to be a good way to improve the mapping of climatic variables in a small island.     

Spatial and temporal variabilities of rainfall data using functional data analysis

The paper analyzes equivalent data for a low density meteorological station network (spatially discontinuous data) and poor temporal homogeneity of thunderstorm observational data. Due to that, a Regional Climate Model (RegCM) dataset was tested. The Most Unstable Convective Available Potential Energy index value (MUCAPE) above the 200 J kg^?1 threshold was selected as a predictor describing favorable conditions for the occurrence of thunderstorms. The quality of the dataset was examined through a comparison between model results and soundings from several aerological stations in Central Europe. Good, statistically significant (0.05 significance level) results were obtained through correlation analysis; the value of Pearson’s correlation coefficient was above 0.8 in every single case. Then, using methods associated with gridded climatology, data series for 44 weather stations were derived and an analysis of correlation between RegCM modeled data and in situ thunderstorm observations was conducted with coefficients in the range of 0.75–0.90. The possibility of employing the dataset in thunderstorm climatology analysis was checked via a few examples by mapping monthly, seasonal, and annual means. Moreover, long-term variability and trend analysis along with modeled MUCAPE data were tested. As a result, the RegCM modeled MUCAPE gridded dataset was proposed as an easily available, suitable, and valuable predictor for thunderstorm climatology analysis and mapping. Finally, some limitations are discussed and recommendations for further improvements are given.     

Depositional ice nucleation on NX illite and mixtures of NX illite with organic acids

Mineral dust particles are known to be efficient ice nuclei in the atmosphere. Previous work has probed heterogeneous ice nucleation on various laboratory dust samples including Arizona Test Dust, kaolinite, montmorillonite, and illite as atmospheric dust surrogates. However, it has recently been suggested that NX illite may be a better representation of atmospheric dust. Hiranuma et al. (2015) performed a laboratory comparison for immersion ice nucleation on NX illite, but here we focus on depositional ice nucleation because of its importance in low temperature cirrus cloud formation. A Raman microscope setup was used to examine the ice-nucleating efficiency of NX illite. Organic coatings on the NX illite particles were also investigated using a mixture of 5 dicarboxylic acids (M5). The ratio of NX illite to M5 was varied from 1:10 to 100:1. It was found that NX illite efficiently nucleates ice with S_ice = 1.07 ± 0.01 at ?47 °C, with S_ice slightly increasing at lower temperatures. In contrast, pure M5 is a poorer ice nucleus with S_ice = 1.30 ± 0.02 at ?40 °C, relatively independent of temperature. Further, it was found that M5 coatings on the order of several monolayers thick hindered the ice nucleating ability of NX illite. Optical images suggest that at colder temperatures (< ?50 °C) 1:1 NX illite:M5 particles and pure M5 particles nucleate ice depositionally, while at warmer temperatures (> ?50 °C) subsaturated immersion ice nucleation dominates. These experiments suggest that mineral dust particles may become less active towards ice nucleation as they age in the atmosphere.     

Evaluation of NCEP TIGGE short-range forecast for Indian summer monsoon intraseasonal oscillation

Potential evapotranspiration (PET) is one of the most critical parameters in the research on agro-ecological systems. The computational methods for the estimation of PET vary in data demands from very simple (empirically based), requiring only information based on air temperatures, to complex ones (more physically based) that require data on radiation, relative humidity, wind speed, etc. The current research is focused on three study areas in Greece that face different climatic conditions due to their location. Twelve PET formulae were used, analyzed and inter-compared in terms of their sensitivity regarding their input coefficients for the Ardas River basin in north-eastern Greece, Sperchios River basin in Central Greece and Geropotamos River basin in South Greece. The aim was to compare all the methods and conclude to which empirical PET method(s) better represent the PET results in each area and thus should be adopted and used each time and which factors influence the results in each case. The results indicated that for the areas that face Mediterranean climatic conditions, the most appropriate method for the estimation of PET was the temperature-based, Hamon’s second version (PET_Ham2). Furthermore, the PET_Ham2 was able to estimate PET almost similarly to the average results of the 12 equations. For the Ardas River basin, the results indicated that both PET_Ham2 and PET_Ham1 can be used to estimate PET satisfactorily. Moreover, the temperature-based equations have proven to produce better results, followed by the radiation-based equations. Finally, PET_ASCE, which is the most commonly used PET equation, can also be applied occasionally in order to provide satisfactory results.     

Warm spells in Northern Europe in relation to atmospheric circulation

This study describes warm spells in Northern Europe and determines the synoptic situations that cause their occurrence. In this article, a relatively warm day was defined as a day when the maximum temperature exceeded the 95th annual percentile, and a warm spell (WS) was considered to be a sequence of at least five relatively warm days. In the analysed multiannual period and within the investigated area, 24 (Kallax) to 53 (Oslo) WSs were observed. The occurrence of WSs was mainly connected with positive anomalies of sea level pressure and a 500-hPa isobaric surface, displaying the presence of high-pressure systems. This occurrence was also accompanied by positive T850 anomalies.     

Long-term monitoring of wall paintings affected by soluble salts

Long-term monitoring of wall paintings in historical monuments aims at clarifying involved decay processes and at the same time controlling effects of interventions for conservation. Monitored decay processes relate to the crystallisation of various salts – particularly of nitronatrite and gypsum – from hygroscopic solutions accumulated in the zone of ground moisture. The salts crystallise in response to climatic variations and other environmental changes. Measures for conservation such as protection from water infiltration, reduction of heating temperature and reduction of surface salt accumulation cause a significant slow-down but not a stop of decay. The particular dynamics and causes of remaining slow decay processes are described on three sites in Switzerland: the convent church of Müstair, the crypt in the cathedral of Basel and the crypt in the Grossmünster church of Zürich.     

Analytical solutions of the diffraction problem of a group of truncated vertical cylinders

An exact analytical method is described to solve the diffraction problem of a group of truncated vertical cylinders. In order to account for the interaction between the cylinders, Kagemoto and Yue's exact algebraic method is utilised. The isolated cylinder diffraction potential due to incident waves is obtained using Garret's solution and evanescent mode solutions are derived in a similar manner.Numerical results are presented for arrays of two and four cylinders. Comparisons between the results obtained from the method presented here and those obtained from numerical methods show excellent agreement.     

Modelling of local velocity anomalies: a cookbook

The determination of small-scale velocity anomalies (from tens to a few hundreds of metres) is a major problem in seismic exploration. The impact of such anomalies on a structural interpretation can be dramatic and conventional techniques such as tomographic inversion or migration velocity analysis are powerless to resolve the ambiguity between structural and velocity origins of anomalies. We propose an alternative approach based on stochastic modelling of numerous anomalies until a set of models is found which can explain the real data. This technique attempts to include as much a priori geological information as possible. It aims at providing the interpreter with a set of velocity anomalies which could possibly be responsible for the structural response. The interpreter can then choose one or several preferred models and pursue a more sophisticated analysis. The class of retained models are all equivalent in terms of data and therefore represent the uncertainty in the model space. The procedure emulates the real processing sequence using a simplified scheme. Essentially, the technique consists of five steps: 1 Interpretation of a structural anomaly in terms of a velocity anomaly with its possible variations in terms of position, size and amplitude. 2 Drawing a model by choosing the parameters of the anomaly within the acceptable range. 3 Modelling the traveltimes in this model and producing the imaging of the reflected interface. 4 Comparing the synthetic data with the real data and keeping the model if it lies within the data uncertainty range. 5 Iterate from step 2. In order to avoid the high computational cost inherent in using statistical determinations, simplistic assumptions have been made: ? The anomaly is embedded in a homogeneous medium: we assume that the refraction and the time shift due to the anomaly have a first-order effect compared with ray bending in the intermediate layers. ? We model only the zero-offset rays and therefore we restrict ourselves to structural problems. ? We simulate time migration and so address only models of limited structural complexity. These approximations are justified in a synthetic model which includes strong lateral velocity variations, by comparing the result of a full processing sequence (prestack modelling, stack and depth migration) with the simplified processing. This model is then used in a blind test on the inversion scheme.     

Conditional heavy-tail behavior with applications to precipitation and river flow extremes

This article deals with the right-tail behavior of a response distribution \(F_Y\) conditional on a regressor vector \({\mathbf {X}}={\mathbf {x}}\) restricted to the heavy-tailed case of Pareto-type conditional distributions \(F_Y(y|\ {\mathbf {x}})=P(Y\le y|\ {\mathbf {X}}={\mathbf {x}})\), with heaviness of the right tail characterized by the conditional extreme value index \(\gamma ({\mathbf {x}})>0\). We particularly focus on testing the hypothesis \({\mathscr {H}}_{0,tail}:\ \gamma ({\mathbf {x}})=\gamma _0\) of constant tail behavior for some \(\gamma _0>0\) and all possible \({\mathbf {x}}\). When considering \({\mathbf {x}}\) as a time index, the term trend analysis is commonly used. In the recent past several such trend analyses in extreme value data have been published, mostly focusing on time-varying modeling of location or scale parameters of the response distribution. In many such environmental studies a simple test against trend based on Kendall’s tau statistic is applied. This test is powerful when the center of the conditional distribution \(F_Y(y|{\mathbf {x}})\) changes monotonically in \({\mathbf {x}}\), for instance, in a simple location model \(\mu ({\mathbf {x}})=\mu _0+x\cdot \mu _1\), \({\mathbf {x}}=(1,x)'\), but the test is rather insensitive against monotonic tail behavior, say, \(\gamma ({\mathbf {x}})=\eta _0+x\cdot \eta _1\). This has to be considered, since for many environmental applications the main interest is on the tail rather than the center of a distribution. Our work is motivated by this problem and it is our goal to demonstrate the opportunities and the limits of detecting and estimating non-constant conditional heavy-tail behavior with regard to applications from hydrology. We present and compare four different procedures by simulations and illustrate our findings on real data from hydrology: weekly maxima of hourly precipitation from France and monthly maximal river flows from Germany.     

Identification and assessment of water safety risk for groundwater recharge with reclaimed water in China

Groundwater recharge using reclaimed water has developed rapidly around the world to relieve the groundwater resource shortage and declining of the water table. Traditional water treatment systems are inefficient to remove all the types of contaminants, so it is urgent to identify the priority chemical substances (CSs) that deserve our first concern. In this study, we developed a method (EER method) to identify priority CSs in groundwater recharge by surface spreading and direct aquifer injection. Three stages were processed which were exposure assessment, effect assessment and ranking for identification of priority CSs. Fourteen cities in China were selected for data collected and 90 pollutants in reclaimed water samples were analyzed as the target pollutants for a case study. According to three stages, the 90 CSs studied were divided into five groups (primary control CSs and high, moderate and low and no risk control CSs). In the primary control CSs and high, moderate and low and no risk control CSs group there were 14, 18, 21, 21 and 16 CSs, respectively when groundwater recharged by surface spreading, while there were 15, 18, 21, 21 and 15 CSs when recharged by direct injection. This method provided an indicator of prioritizing the risk of 90 compounds in the reclaimed water for groundwater recharge.