Pseudo-proxy tests of the analogue method to reconstruct spatially resolved global temperature during the Common Era

This study addresses the possibility of carrying out spatially resolved global reconstructions of annual mean temperature using a worldwide network of proxy records and a method based on the search of analogues. Several variants of the method are evaluated, and their performance is analysed. As a test bed for the reconstruction, the PAGES 2k proxy database (version 1.9.0) is employed as a predictor, the HadCRUT4 dataset is the set of observations used as the predictand and target, and a set of simulations from the PMIP3 simulations are used as a pool to draw analogues and carry out pseudo-proxy experiments (PPEs). The performance of the variants of the analogue method (AM) is evaluated through a series of PPEs in growing complexity, from a perfect-proxy scenario to a realistic one where the pseudo-proxy records are contaminated with noise (white and red) and missing values, mimicking the limitations of actual proxies. Additionally, the method is tested by reconstructing the real observed HadCRUT4 temperature based on the calibration of real proxies. The reconstructed fields reproduce the observed decadal temperature variability. From all the tests, we can conclude that the analogue pool provided by the PMIP3 ensemble is large enough to reconstruct global annual temperatures during the Common Era. Furthermore, the search of analogues based on a metric that minimises the RMSE in real space outperforms other evaluated metrics, including the search of analogues in the range-reduced space expanded by the leading empirical orthogonal functions (EOFs). These results show how the AM is able to spatially extrapolate the information of a network of local proxy records to produce a homogeneous gap-free climate field reconstruction with valuable information in areas barely covered by proxies and make the AM a suitable tool to produce valuable climate field reconstructions for the Common Era

Comparando downscaling dinámico y estadístico en aplicaciones paleoclimáticas

Ponencia presentada en: XI Congreso de la Asociación Española de Climatología celebrado en Cartagena entre el 17 y el 19 de octubre de 2018.[ES]La basta resolución espacial de los Modelos de Circulación General (GCM) supone un cuello de botella que limita su aplicabilidad en estudios centrados en escalas regionales o locales, lo que requiere el uso de técnicas de downscaling. En este trabajo utilizamos una simulación de 500 años con un Modelo Climático Regional (RCM) anidado a un GCM para comparar las técnicas de downscaling dinámico y estadístico, evaluando así la capacidad de este último de reproducir las principales características de las variables que se intentan simular. Para llevar a cabo el downscaling estadístico, usamos 40 años de datos para calibrar un modelo basado en redes neuronales artificiales con el fin de reproducir dos variables diarias de interés: temperatura máxima y precipitación. Posteriormente usamos esa calibración para extender esas series hasta cubrir el periodo completo de 500 años. Los resultados muestran una alta correlación temporal entre las variables obtenidas por ambos métodos, así como similar covariabilidad espacial entre localizaciones. Concretamente, para la temperatura máxima, la correlación es de 0.89, apreciándose además un ciclo anual, con valores más altos en verano que en invierno. Para la precipitación el dato desciende a 0.6, lo cual se debe fundamentalmente a limitaciones en la red neuronal para reproducir los eventos más extremos. Estos resultados indican que, si bien el downscaling dinámico no puede ser completamente sustituido por un enfoque estadístico, éste permite obtener una primera aproximación al comportamiento de ciertas variables evitando o minimizando gran parte del coste computacional.[EN]The coarse spatial resolution of General Circulation Models (GCMs) is a bottleneck that limits its applicability in studies focused on regional to local scales, demanding the implementation of downscaling techniques. In this work, we use a 500-year simulation with a Regional Climate Model (RCM) nested to a GCM to compare dynamical and statistical downscaling, thus evaluating the ability of the latter to mimic the main characteristics of the variables that are being simulated, but at a lower computational cost. To carry out the statistical downscaling, we use 40 years of data to calibrate a model based on Artificial Neural Networks in order to reproduce two daily variables of interest: maximum temperature and precipitation. We then use this calibration to extend the series to span the entire 500-year period. The results show a high temporal correlation between the variables obtained by both methods, as well as a similar spatial covariabilities across locations. Specifically, for the máximum temperature, the correlation is 0.89, albeit with a marked annual cycle and higher values in summer than in winter. For precipitation, correlation diminishes to 0.62, mainly due to limitations in the neural network to reproduce the most extreme events. These results indicate that, although dynamic downscaling can not be completely substituted by a statistical approach, the latter is still useful to obtain a first approximation to the behavior of certain variables, avoiding or minimizing the computational cost that the former entails

The Role of Aerosol Concentration on Precipitation in a Winter Extreme Mixed-Phase System: The Case of Storm Filomena

Aerosol concentration, size and composition are fundamental in hydrometeor formation processes. Meteorological models often use prescribed aerosol concentrations and a single substance. In this study, we analyze the role of aerosol concentration, acting both as CCN and IN, in the development of precipitation in a mixed phase system in numerical weather simulations. To this end, Storm Filomena was selected as the case study. In such a mixed-phase system, the coexistence of supercooled water with ice crystals, as well as the particular existence of a thermal inversion, led to the formation of precipitation in the form of rain, snow and graupel. Several high resolution experiments varying the fixed background aerosol concentration as well as a simulation with an interactive aerosol calculation were performed by means of the WRF-Chem model, using the same physics suite, domain and driving conditions. Results show that the total precipitation remains basically unaltered, with maximum changes of 5%; however, the production of snow is heavily modified. The simulation with maximum prescribed aerosol concentration produced 27% more snow than the interactive aerosol simulation, and diminished the graupel (74%) and rain production (28%). This redistribution of precipitation is mainly linked to the fact that under fixed ice crystal population the variation of aerosol concentration translates into changes in the liquid water content and droplet size and number concentration, thus altering the efficiency of precipitation production. In addition, while modifying the prescribed aerosol concentration produces the same precipitation pattern with the concentration modulating the precipitation amount, interactive aerosol calculation leads to a different precipitation pattern due to the spatial and temporal variability induced in the dynamical aerosol distribution

Event selection for dynamical downscaling: a neural network approach for physically-constrained precipitation events

This study presents a new dynamical downscaling strategy for extreme events. It is based on a combination of statistical downscaling of coarsely resolved global model simulations and dynamical downscaling of specific extreme events constrained by the statistical downscaling part. The method is applied to precipitation extremes over the upper Aare catchment, an area in Switzerland which is characterized by complex terrain. The statistical downscaling part consists of an Artificial Neural Network (ANN) framework trained in a reference period. Thereby, dynamically downscaled precipitation over the target area serve as predictands and large-scale variables, received from the global model simulation, as predictors. Applying the ANN to long term global simulations produces a precipitation series that acts as a surrogate of the dynamically downscaled precipitation for a longer climate period, and therefore are used in the selection of events. These events are then dynamically downscaled with a regional climate model to 2 km. The results show that this strategy is suitable to constraint extreme precipitation events, although some limitations remain, e.g., the method has lower efficiency in identifying extreme events in summer and the sensitivity of extreme events to climate change is underestimated

Covariability of seasonal temperature and precipitation over the Iberian Peninsula in high-resolution regional climate simulations (1001–2099)

Precipitation and surface temperature are interdependent variables, both as a response to atmospheric dynamics and due to intrinsic thermodynamic relationships and feedbacks between them. This study analyzes the covariability of seasonal temperature (T) and precipitation (P) across the Iberian Peninsula (IP) using regional climate paleosimulations for the period 1001–1990, driven by reconstructions of external forcings. Future climate (1990–2099) was simulated according to SRES scenarios A2 and B2. These simulations enable exploring, at high spatial resolution, robust and physically consistent relationships.This study was supported by the Spanish government and the Fondo Europeo de Desarrollo Regional (FEDER) through the project SPEQ-TRES (CGL2011-29672-C02-02). J.P. Montávez also acknowledges the financial support from Fundacion Seneca (Ref 19640/EE/14)

The weather behind words – new methodologies for integrated hydrometeorological reconstruction through documentary sources

Historical climatology has remarkable potentialities to produce climatic reconstructions with high temporal resolution. However, some methodological limitations hinder the spatial development of this discipline. This study presents a new approach to historical climatology that overcomes some of the limitations of classical approaches, such as the rogation method or content analysis: the Cost Opportunity for Small Towns (COST). It analyses historic documents and takes advantage of all sorts of meteorological information available in written documents, and not only the severest events, to therefore overcome the most prominent bottlenecks of former approaches. COST relies on the fact that using paper is very costly, so its use to describe meteorological conditions is hypothesised as being proportional to the impact they had on society. To prove the validity of this approach to reconstruct climate conditions, this article exemplarily uses the Municipal Chapter Acts of a small town in southern Spain (Caravaca de la Cruz), which span the 1600–1900 period, and allows reconstructions to be obtained on a monthly basis. Using the same documentary source, the three approaches were used to derive respective climate reconstructions, which were then compared to assess climate signal consistency and to identify possible caveats in the methods. The three approaches led to a generally coherent series of secular variability in the hydrological conditions, which agrees well with previous study results. The COST approach is arguably more objective and less affected by changes in societal behaviour, which allows it to perform comparative studies in regions with different languages and traditions.This research was supported by the Umulink project funded by the Seneca Foundation (ref. 20640/JLI/18) and the Spanish Ministry of Science, Innovation and Universities (“Juan de la Cierva-Incorporación”, grant nos. IJCI-2016-29016, IJCI-2015-26914)

Hydrogen Photo-Production from Glycerol Using Nickel-Doped TiO2 Catalysts: Effect of Catalyst Pre-Treatment

In the present piece of research, hydrogen production via the photo-reforming of glycerol (a byproduct from biodiesel generation) is studied. Catalysts consisted of titania modified by Ni (0.5% by weight) obtained through deposition–precipitation or impregnation synthetic methods (labelled as Ni-0.5-DP and Ni-0.5-IMP, respectively). Reactions were performed both under UV and solar irradiation. Activity significantly improved in the presence of Ni, especially under solar irradiation. Moreover, pre-reduced solids exhibited higher catalytic activities than untreated solids, despite the “in-situ” reduction of nickel species and the elimination of surface chlorides under reaction conditions (as evidenced by XPS). It is possible that the catalyst pretreatment at 400 °C under hydrogen resulted in some strong metal–support interactions. In summary, the highest hydrogen production value (ca. 2600 micromole H2·g−1) was achieved with pre-reduced Ni-0.5-DP solid using UV light for an irradiation time of 6 h. This value represents a 15.7-fold increase as compared to Evonik P25

Etiological and Resistance Profile of Bacteria Involved in Urinary Tract Infections in Young Children

The objective of this study was to identify the bacteria most frequently responsible for urinary tract infection (UTI) in the population of under-2-year-olds in our geographic area and to evaluate the activity of antibiotics widely used for UTI treatment during a 4-year study period. Materials and Methods. A retrospective analysis was conducted of data on the identification and susceptibility of microorganisms isolated in urine samples from children under 2 years of age. A total of 1,045 uropathogens were isolated. Escherichia coli accounted for the majority (60.3%) of these, followed by Enterococcus faecalis (22.4%) and Klebsiella spp. (6.5%). The highest E. coli susceptibility rates (>90%) were to piperacillin-tazobactam, cefuroxime, cefotaxime, ceftazidime, imipenem, gentamicin, nitrofurantoin, and fosfomycin, and the lowest were to amoxicillin-clavulanic acid and cotrimoxazole. Among all bacteria isolated, we highlight the overall high activity of piperacillin-tazobactam, imipenem, nitrofurantoin, and fosfomycin against both community and hospital isolates and the reduced activity of amoxicillin-clavulanic acid, cephalosporins, gentamicin, and cotrimoxazole. There was no significant change in the total activity of any of the studied antibiotics over the 4-year study period. Empiric treatment with amoxicillin-clavulanic acid, cotrimoxazole, cephalosporins, and gentamicin may be inadequate due to their limited activity against uropathogens in our settingParts of this work were supported by the CTS-521 research grou

Sinorhizobium fredii HH103 RirA is required for oxidative stress resistance and efficient symbiosis with Soybean

Members of Rhizobiaceae contain a homologue of the iron-responsive regulatory protein RirA. In different bacteria, RirA acts as a repressor of iron uptake systems under iron-replete conditions and contributes to ameliorate cell damage during oxidative stress. In Rhizobium leguminosarum and Sinorhizobium meliloti, mutations in rirA do not impair symbiotic nitrogen fixation. In this study, a rirA mutant of broad host range S. fredii HH103 has been constructed (SVQ780) and its free-living and symbiotic phenotypes evaluated. No production of siderophores could be detected in either the wild-type or SVQ780. The rirA mutant exhibited a growth advantage under iron-deficient conditions and hypersensitivity to hydrogen peroxide in iron-rich medium. Transcription of rirA in HH103 is subject to autoregulation and inactivation of the gene upregulates fbpA, a gene putatively involved in iron transport. The S. fredii rirA mutant was able to nodulate soybean plants, but symbiotic nitrogen fixation was impaired. Nodules induced by the mutant were poorly infected compared to those induced by the wild-type. Genetic complementation reversed the mutant’s hypersensitivity to H2O2, expression of fbpA, and symbiotic deficiency in soybean plants. This is the first report that demonstrates a role for RirA in the Rhizobium-legume symbiosis.Andalucian Government Grant No. P11-CVI-7500Spanish Government Grant Nos. BIO2013-42801-P and BIO2016-78409-REuropean Regional Development Funds (ERDF)VPPI (V Plan Propio de Investigación) of University of Seville