Assessing the transferability of the regional climate model REMO to different COordinated Regional Climate Downscaling EXperiment (CORDEX) Regions

The transferability of the regional climate model REMO with a standard setup over different regions of the world has been evaluated. The study is based on the idea that the modeling parameters and parameterizations in a regional climate model should be robust to adequately simulate the major climatic characteristic of different regions around the globe. If a model is not able to do that, there might be a chance of an “overtuning” to the “home-region”, which means that the model physics are tuned in a way that it might cover some more fundamental errors, e.g., in the dynamics. All simulations carried out in this study contribute to the joint effort by the international regional downscaling community called COordinated Regional climate Downscaling EXperiment (CORDEX). REMO has been integrated over six CORDEX domains forced with the so-called perfect boundary conditions obtained from the global reanalysis dataset ERA-Interim for the period 1989 to 2008. These six domains include Africa, Europe, North America, South America, West Asia and the Mediterranean region. Each of the six simulations was conducted with the identical model setup which allows investigating the transferability of a single model to regions with substantially different climate characteristics. For the consistent evaluation over the different domains, a new evaluation framework is presented by combining the Köppen-Trewartha climate classification with temperature-precipitation relationship plots and a probability density function (PDF) skill score method. The evaluation of the spatial and temporal characteristics of simulated precipitation and temperature, in comparison to observational datasets, shows that REMO is able to simulate the mean annual climatic features over all the domains quite reasonably, but still some biases remain. The regions over the Amazon and near the coast of major upwelling regions have a significant warm bias. Wet and dry biases appear over the mountainous regions and East Africa, respectively. The temperature over South America and precipitation over the tundra and highland climate of West Asia are misrepresented. The probable causes leading to these biases are discussed and ideas for improvements are suggested. The annual cycle of precipitation and temperature of major catchments in each domain are also well represented by REMO. The model has performed well in simulating the inter- and intra-seasonal characteristics of different climate types in different regions. Moreover, the model has a high ability in representing the general characteristics of different climate types as measured by the probability density function (PDF) skill score method. Although REMO seems to perform best over its home domain in Europe (domain of development and testing), the model has simulated quite well the climate characteristics of other regions with the same set of parameterization options. Therefore, these results lead us to the conclusion that REMO is well suited for long-term climate change simulations to examine projected future changes in all these regions

The first multi-model ensemble of regional climate simulations at kilometer-scale resolution, part I: evaluation of precipitation

Here we present the first multi-model ensemble of regional climate simulations at kilometer-scale horizontal grid spacing over a decade long period. A total of 23 simulations run with a horizontal grid spacing of ∼3 km, driven by ERA-Interim reanalysis, and performed by 22 European research groups are analysed. Six different regional climate models (RCMs) are represented in the ensemble. The simulations are compared against available high-resolution precipitation observations and coarse resolution (∼ 12 km) RCMs with parameterized convection. The model simulations and observations are compared with respect to mean precipitation, precipitation intensity and frequency, and heavy precipitation on daily and hourly timescales in different seasons. The results show that kilometer-scale models produce a more realistic representation of precipitation than the coarse resolution RCMs. The most significant improvements are found for heavy precipitation and precipitation frequency on both daily and hourly time scales in the summer season. In general, kilometer-scale models tend to produce more intense precipitation and reduced wet-hour frequency compared to coarse resolution models. On average, the multi-model mean shows a reduction of bias from ∼ −40% at 12 km to ∼ −3% at 3 km for heavy hourly precipitation in summer. Furthermore, the uncertainty ranges i.e. the variability between the models for wet hour frequency is reduced by half with the use of kilometer-scale models. Although differences between the model simulations at the kilometer-scale and observations still exist, it is evident that these simulations are superior to the coarse-resolution RCM simulations in the representing precipitation in the present-day climate, and thus offer a promising way forward for investigations of climate and climate change at local to regional scales

The first multi-model ensemble of regional climate simulations at kilometer-scale resolution. Part I: Evaluation of precipitation

Here we present the first multi-model ensemble of regional climate simulations at kilometer-scale horizontal grid spacing over a decade long period. A total of 23 simulations run with a horizontal grid spacing of ∼ 3 km, driven by ERA-Interim reanalysis, and performed by 22 European research groups are analysed. Six different regional climate models (RCMs) are represented in the ensemble. The simulations are compared against available high-resolution precipitation observations and coarse resolution (∼ 12 km) RCMs with parameterized convection. The model simulations and observations are compared with respect to mean precipitation, precipitation intensity and frequency, and heavy precipitation on daily and hourly timescales in different seasons. The results show that kilometer-scale models produce a more realistic representation of precipitation than the coarse resolution RCMs. The most significant improvements are found for heavy precipitation and precipitation frequency on both daily and hourly time scales in the summer season. In general, kilometer-scale models tend to produce more intense precipitation and reduced wet-hour frequency compared to coarse resolution models. On average, the multi-model mean shows a reduction of bias from ∼ −40 at 12 km to ∼ −3 at 3 km for heavy hourly precipitation in summer. Furthermore, the uncertainty ranges i.e. the variability between the models for wet hour frequency is reduced by half with the use of kilometer-scale models. Although differences between the model simulations at the kilometer-scale and observations still exist, it is evident that these simulations are superior to the coarse-resolution RCM simulations in the representing precipitation in the present-day climate, and thus offer a promising way forward for investigations of climate and climate change at local to regional scales. © 2021, The Author(s)

Analysis of Compound Climate Extremes and Exposed Population in Africa Under Two Different Emission Scenarios

It is well established that Africa is particularly exposed to climate extremes including heat waves, droughts, and intense rainfall events. How exposed Africa is to the co-occurrence of these events is however virtually unknown. This study provides the first analysis of projected changes in the co-occurrence of five such compound climate extremes in Africa, under a low (RCP2.6) and high (RCP8.5) emissions scenario. These changes are combined with population projections for a low (SSP1) and high (SSP3) population growth scenario, in order to provide estimates of the number of people that may be exposed to such events at the end of the 21st century. We make use of an ensemble of regional climate projections from the Coordinated Output for Regional Evaluations (CORE) project embedded in the Coordinated Regional Climate Downscaling Experiment (CORDEX) framework. This ensemble comprises five different Earth System Model/Regional Climate Model (ESM/RCM) combinations with three different ESMs and two RCMs. We show that all five compound climate extremes will increase in frequency, with changes being greater under RCP8.5 than RCP2.6. Moreover, populations exposed to these changes are greater under RCP8.5/SSP3, than RCP2.6/SSP1, increasing by 47- and 12-fold, respectively, compared to the present-day. Regions of Africa that are particularly exposed are West Africa, Central-East Africa, and Northeast and Southeast Africa. Increased exposure is mainly driven by the interaction between climate and population growth, and the effect of population alone. This has important policy implications in relation to climate mitigation and adaptation

Morphology of the midgut of Rhipicephalus sanguineus (Latreille, 1806) (Acari: Ixodidae) adult ticks in different feeding stages

The intestinal epithelial cells of ticks are fundamental for their full feeding and reproductive success, besides being considered important sites for the development of pathogens. Rhipicephalus sanguineus ticks are known for their great medical and veterinary importance, and for this reason, the knowledge of their intestinal morphology may provide relevant subsidies for the control of these animals, either by direct acaricidal action over these cells or by the production of vaccines. Therefore, this study aimed to describe the midgut morphology of male and female R. sanguineus ticks in different feeding stages, by means of histological analysis. Significant differences were observed between the genders, and such alterations may refer mainly to the distinct demands for nutrients, much higher in females, which need to develop and carry out the egg-laying process. In general, the midgut is coated by a thin muscle layer and presents a pseudostratified epithelium, in which two basic types of cells can be observed, connected to a basal membrane - generative or stem and digestive cells. The latter was classified as follows: residual, deriving from the phase anterior to ecdysis; pinocytic, with vesicles containing liquid or pre-digested components of blood; phagocytic, with entire cells or remnants of nuclear material inside cytoplasmic vesicles; and mature, free in the lumen. Digestion is presumably intracellular and asynchronous and corresponds to a process which starts with the differentiation of generative cells into pinocytic digestive cells, which subsequently start to phagocytize intact blood cells and finally detach from the epithelium, being eliminated with feces. © 2012 Springer-Verlag Berlin Heidelberg

Regional climate modelling in CLARIS‐LPB: a concerted approach towards twentyfirst century projections of regional temperature and precipitation over South America

The results of an ensemble of regional cli- mate model (RCM) simulations over South America are presented. This is the first coordinated exercise of regional climate modelling studies over the continent, as part of the CLARIS-LPB EU FP7 project. The results of different future periods, with the main focus on (2071? 2100) is shown, when forced by several global climate models, all using the A1B greenhouse gases emissions scenario. The analysis is focused on the mean climate conditions for both temperature and precipitation. The common climate change signals show an overall increase of temperature for all the seasons and regions, gener- ally larger for the austral winter season. Future climate shows a precipitation decrease over the tropical region, and an increase over the subtropical areas. These cli- mate change signals arise independently of the driving global model and the RCM. The internal variability of the driving global models introduces a very small level of uncertainty, compared with that due to the choice of the driving model and the RCM. Moreover, the level of uncertainty is larger for longer horizon projections for both temperature and precipitation. The uncertainty in the temperature changes is larger for the subtropical than for the tropical ones. The current analysis allows identi- fication of the common climate change signals and their associated uncertainties for several subregions within the South American continent.Fil: Sanchez, E.. Universidad de Castilla La Mancha. Facultad de Ciencias Ambientales y Bioquímica; EspañaFil: Solman, Silvina Alicia. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinacion Administrativa Ciudad Universitaria. Centro de Investigaciones del Mar y la Atmósfera; ArgentinaFil: Remedio, A. R. C.. Climate Service Center 2.0; AlemaniaFil: Berbery, Ernesto Hugo. University of Maryland. Earth System Science Interdisciplinary Center; Estados UnidosFil: Samuelsson, P.. Rossby Centre, Meteorological And Hydrological Institute Of Sweden; SueciaFil: Da Rocha, R.. Universidade de São Paulo. Departamento de Ciencias Atmosféricas. Instituto de Astronomía, Geofísica e Ciencias Atmosféricas; BrasilFil: Mourão, C.. Instituto Nacional Pesquisas Espaciais. Centro Ciencia Sistema Terrestre; BrasilFil: Li, L.. Laboratoire de Météorologie Dynamique; FranciaFil: Marengo, J.. Instituto Nacional Pesquisas Espaciais. Centro Ciencia Sistema Terrestre; BrasilFil: de Castro, M.. Universidad de Castilla La Mancha. Facultad de Ciencias Ambientales y Bioquímica; EspañaFil: Jacob, D.. Climate Service Center 2.0; Alemani

Familial aggregation of primary glomerulonephritis in an Italian population isolate: Valtrompia study

Hereditary factors are suspected to contribute to the pathogenesis of sporadic primary glomerulonephritis, but their contribution is difficult to delineate in the general population. We studied the prevalence of primary glomerulonephritis in an isolated population from the extreme northern Valtrompia valley, Northern Italy. Investigation of medical records, community urinary screening program and molecular characterization of the population's ancestry were performed; genealogies of affected individuals were researched. Forty-three patients with primary glomerulonephritis were identified: 25 had biopsy-proven disease (11 immunoglobulin A (IgA) nephropathy; eight mesangial proliferative glomerulonephritis without IgA deposits; four focal segmental glomerular sclerosis; two membranous nephropathy), and 18 had clinical glomerulonephritis. All 43 patients originated from three mountain villages (Collio, San Colombano, and Bovegno). In contrast, we found only four cases of primary glomerulonephritis in two nearby villages (Pezzaze and Tavernole) that shared similar population histories and lifestyles, demonstrating heterogeneity of risk factors for glomerulonephritis (P=3 × 10−5). All 43 affected individuals could be traced back to common ancestors (XVI–XVII centuries), enabling the construction of three large pedigree including three parent–child affected pairs and five affected siblings pairs. Molecular data showed lower genetic diversity and increased inbreeding in the Valtrompia population compared to the control population. Molecular and genealogical evidence of limited set of founders and the absence of shared nephritogenic environmental factors suggest that our patients share a common genetic susceptibility to the development of primary glomerulonephritis. Further molecular study of our families will offer the possibility to shed light on the genetic background underlying these glomerular disorders

Performance of a multi-RCM ensemble for South Eastern South America

International audienceThe ability of four regional climate models to reproduce the present-day South American climate is examined with emphasis on La Plata Basin. Models were integrated for the period 1991-2000 with initial and lateral boundary conditions from ERA-40 Reanalysis. The ensemble sea level pressure, maximum and minimum temperatures and precipitation are evaluated in terms of seasonal means and extreme indices based on a percentile approach. Dispersion among the individual models and uncertainties when comparing the ensemble mean with different climatologies are also discussed. The ensemble mean is warmer than the observations in South Eastern South America (SESA), especially for minimum winter temperatures with errors increasing in magnitude towards the tails of the distributions. The ensemble mean reproduces the broad spatial pattern of precipitation, but overestimates the convective precipitation in the tropics and the orographic precipitation along the Andes and over the Brazilian Highlands, and underestimates the precipitation near the monsoon core region. The models overestimate the number of wet days and underestimate the daily intensity of rainfall for both seasons suggesting a premature triggering of convection. The skill of models to simulate the intensity of convective precipitation in summer in SESA and the variability associated with heavy precipitation events (the upper quartile daily precipitation) is far from satisfactory. Owing to the sparseness of the observing network, ensemble and observations uncertainties in seasonal means are comparable for some regions and seasons