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Precipitation downscaling improves the coarse resolution and poor representation of precipitation in global climate models and helps end users to assess the likely hydrological impacts of climate change. This paper integrates perspectives from meteorologists, climatologists, statisticians, and hydrologists to identify generic end user (in particular, impact modeler) needs and to discuss downscaling capabilities and gaps. End users need a reliable representation of precipitation intensities and temporal and spatial variability, as well as physical consistency, independent of region and season. In addition to presenting dynamical downscaling, we review perfect prognosis statistical downscaling, model output statistics, and weather generators, focusing on recent developments to improve the representation of space‐time variability. Furthermore, evaluation techniques to assess downscaling skill are presented. Downscaling adds considerable value to projections from global climate models. Remaining gaps are uncertainties arising from sparse data; representation of extreme summer precipitation, subdaily precipitation, and full precipitation fields on fine scales; capturing changes in small‐scale processes and their feedback on large scales; and errors inherited from the driving global climate model.

We present a 1-km2 gridded German dataset of hourly surface climate variables covering the period 1995 to 2012. The dataset comprises 12 variables including temperature, dew point, cloud cover, wind speed and direction, global and direct shortwave radiation, down- and up-welling longwave radiation, sea level pressure, relative humidity and vapour pressure. This dataset was constructed statistically from station data, satellite observations and model data. It is outstanding in terms of spatial and temporal resolution and in the number of climate variables. For each variable, we employed the most suitable gridding method and combined the best of several information sources, including station records, satellite-derived data and data from a regional climate model. A module to estimate urban heat island intensity was integrated for air and dew point temperature. Owing to the low density of available synop stations, the gridded dataset does not capture all variations that may occur at a resolution of 1 km2. This applies to areas of complex terrain (all the variables), and in particular to wind speed and the radiation parameters. To achieve maximum precision, we used all observational information when it was available. This, however, leads to inhomogeneities in station network density and affects the long-term consistency of the dataset. A first climate analysis for Germany was conducted. The Rhine River Valley, for example, exhibited more than 100 summer days in 2003, whereas in 1996, the number was low everywhere in Germany. The dataset is useful for applications in various climate-related studies, hazard management and for solar or wind energy applications and it is available via doi:10.5676/DWD_CDC/TRY_Basis_v001.

Climate parameters, especially temperature, sunlight, and precipitation, play a decisive role in growing and maturing processes. The aim of this study is to investigate the relationship between climate variability and variations in phenological events in viticulture. Long time series of daily meteorological observations are used to quantify these relations. The primary aim is to predict the date of phenological events by relationships between plant morphology and environmental conditions. Causal relationships between environment and internal activities of the vine (phytochemistry, cellular interactions, molecular and cell biology) are not our focus. The dates of the phenological events are important for planning treatments in the vineyards like pest management, for predicting the duration of the ripening phase and estimating the quality of the grapes and the vintage. The focus is layed on the region of the Upper Moselle, especially the Luxembourgian viticulture. First the regional climate and the phenological states of different vine varieties during the time period 1951–2005 are analysed. Significant trends are detected in annual, spring and summer temperatures. Vine phenology is also found to have changed significantly; budburst date and flowering events occur earlier by about two weeks. In a second step, relationships between phenological events and climate parameters are used to develop a prediction model. The parameterisation used in this study is based on a linear multiple regression method with forward and backward steps. The predictors tested are mainly temperature means for different time periods or temperature derived indices. In addition precipitation and sunshine duration for different time periods are evaluated, but only the temperature based predictors showed sufficient skill. For the budburst event, the significant predictors are the accumulated degree days in March, the mean daily maximum temperature in April and the accumulated frost days from January to March. The flowering event is best predicted by the accumulated degree days in May and April, the mean daily maximum temperature in June, and the date of the budburst event. Depending on the vine variety and the phenological event, the model explains 80–89% of the variance and has a correlation coefficient above 0.90 with the observations.

In order to facilitate offshore wind farm tenders, Deutscher Wetterdienst (DWD, Germany's national meteorological service) provides reanalysis data and quality assessments to Bundesamt für Seeschifffahrt und Hydrographie (BSH, Federal Maritime and Hydrographic Agency). The regional reanalysis COSMO-REA6 is used besides the global reanalysis ERA5. New reanalyses and derived products getting available are (i) the regional reanalysis CERRA (C3S), (ii) COSMO-R6G2, a successor of COSMO-REA6 which is currently produced by DWD and (iii) HoKliSim-De, a convection-permitting climate simulation for Germany with COSMO-CLM as a regional downscaling of ERA5. In the present study, the quality of the different data sets for offshore wind energy application is compared using in-situ measurements of the wind speed and wind direction from the top anemometer and vane of the FINO1 research platform and satellite-based data of the near-surface wind speed from the Copernicus Marine Environment Monitoring Service (CMEMS) and the EUMETSAT Satellite Application Facility on Climate Monitoring (CM SAF). Evaluation at FINO1 focuses on the time period prior to the installation of nearby wind farms to avoid wake effects. COSMO-REA6, CERRA and HoKliSim-De show only small biases and resemble the observed distribution of the wind speed at FINO1 whereas ERA5 shows slightly lower values of the wind speed at 100 m. All model-based products tend to slightly underestimate the occurrence of south-westerly wind directions and overestimate wind directions from West to Northwest. Smallest directional biases are analysed for COSMO-REA6. Analysis of the windstorm CHRISTIAN suggests that ensemble information is required for the representation of individual extreme events. Evaluation of the near-surface wind speed using satellite-based data is performed for an area around the German Exclusive Economic Zone (EEZ) of the North Sea. The median bias of ERA5 and COSMO-REA6 is close to zero. CERRA shows a systematic overestimation of the near-surface wind speed compared to the satellite-based reference datasets. By contrast, a slight underestimation is analysed for HoKliSim-De. The bias distribution analysed for a first simulation stream of COSMO-R6G2 is similar to COSMO-REA6 which provides initial indication for the applicability of the new product.

Land vegetation is currently taking up large amounts of atmospheric CO 2 , possibly due to tree growth stimulation. Extant models predict that this growth stimulation will continue to cause a net carbon uptake this century. However, there are indications that increased growth rates may shorten trees′ lifespan and thus recent increases in forest carbon stocks may be transient due to lagged increases in mortality. Here we show that growth-lifespan trade-offs are indeed near universal, occurring across almost all species and climates. This trade-off is directly linked to faster growth reducing tree lifespan, and not due to covariance with climate or environment. Thus, current tree growth stimulation will, inevitably, result in a lagged increase in canopy tree mortality, as is indeed widely observed, and eventually neutralise carbon gains due to growth stimulation. Results from a strongly data-based forest simulator confirm these expectations. Extant Earth system model projections of global forest carbon sink persistence are likely too optimistic, increasing the need to curb greenhouse gas emissions. The universality of the trade-off between early growth and lifespan in trees and its implications are disputed. Analysing a global tree ring dataset and performing data-driven simulations, the authors demonstrate the pervasiveness of the trade-off and challenge current earth system models that predict a continuation of the carbon sink into mature forests under warming and increasing CO 2 .

Visions of Savage Paradise is the first major book-length study of seventeenth-century Dutch artist Albert Eckhout to be published in nearly seventy years. Eckhout, who was court painter to the colonial governor of Dutch Brazil, created life-size paintings of Amerindians, Africans, and Brazilians of mixed race in support of the governor's project to document the people and natural history of the colony. In this study, Rebecca Parker Brienen provides a detailed analysis of Eckhout's works, framing them with discussions of both their colonial context and contemporary artistic practices in the Dutch republic.

Many different intestinal parasite species can co-occur in the same population. However, classic diagnostic tools can only frame a particular group of intestinal parasite species. Hence, one or two tests do not suffice to provide a complete picture of infecting parasite species in a given population. The present study investigated intestinal parasitic infections in Beira, Mozambique, i.e. in the informal settlement of Inhamudima. Diagnostic accuracy of five classical microscopy techniques and real-time PCR for the detection of a broad spectrum of parasites was compared. A cross-sectional population-based survey was performed. One stool sample per participant (n = 303) was examined by direct smear, formal-ether concentration (FEC), Kato smear, Baermann method, coproculture and real-time PCR. We found that virtually all people (96%) harbored at least one helminth, and that almost half (49%) harbored three helminths or more. Remarkably, Strongyloides stercoralis infections were widespread with a prevalence of 48%, and Ancylostoma spp. prevalence was higher than that of Necator americanus (25% versus 15%), the hookworm species that is often assumed to prevail in East-Africa. Among the microscopic techniques, FEC was able to detect the broadest spectrum of parasite species. However, FEC also missed a considerable number of infections, notably S. stercoralis, Schistosoma mansoni and G. intestinalis. PCR outperformed microscopy in terms of sensitivity and range of parasite species detected. We showed intestinal parasites-especially helminths-to be omnipresent in Inhamudima, Beira. However, it is a challenge to achieve high diagnostic sensitivity for all species. Classical techniques such as FEC are useful for the detection of some intestinal helminth species, but they lack sensitivity for other parasite species. PCR can detect intestinal parasites more accurately but is generally not feasible in resource-poor settings, at least not in peripheral labs. Hence, there is a need for a more field-friendly, sensitive approach for on-the-spot diagnosis of parasitic infections.

Many tropical regions show one distinct dry season. Often, this seasonality induces cambial dormancy of trees, particularly if these belong to deciduous species. This will often lead to the formation of annual rings. The aim of this study was to determine whether tree species in the Bolivian Amazon region form annual rings and to study the influence of the total amount and seasonal distribution of rainfall on diameter growth. Ring widths were measured on stem discs of a total of 154 trees belonging to six rain forest species. By correlating ring width and monthly rainfall data we proved the annual character of the tree rings for four of our study species. For two other species the annual character was proved by counting rings on trees of known age and by radiocarbon dating. The results of the climate--growth analysis show a positive relationship between tree growth and rainfall in certain periods of the year, indicating that rainfall plays a major role in tree growth. Three species showed a strong relationship with rainfall at the beginning of the rainy season, while one species is most sensitive to the rainfall at the end of the previous growing season. These results clearly demonstrate that tree ring analysis can be successfully applied in the tropics and that it is a promising method for various research disciplines.

Amazon forests, which store ∼50% of tropical forest carbon and play a vital role in global water, energy, and carbon cycling, are predicted to experience both longer and more intense dry seasons by the end of the 21st century. However, the climate sensitivity of this ecosystem remains uncertain: several studies have predicted large-scale die-back of the Amazon, whereas several more recent studies predict that the biome will remain largely intact. Combining remote-sensing and ground-based observations with a size- and age-structured terrestrial ecosystem model, we explore the sensitivity and ecological resilience of these forests to changes in climate. We demonstrate that water stress operating at the scale of individual plants, combined with spatial variation in soil texture, explains observed patterns of variation in ecosystem biomass, composition, and dynamics across the region, and strongly influences the ecosystem’s resilience to changes in dry season length. Specifically, our analysis suggests that in contrast to existing predictions of either stability or catastrophic biomass loss, the Amazon forest’s response to a drying regional climate is likely to be an immediate, graded, heterogeneous transition from high-biomass moist forests to transitional dry forests and woody savannah-like states. Fire, logging, and other anthropogenic disturbances may, however, exacerbate these climate change-induced ecosystem transitions.

We present a unique proxy for the reconstruction of variation in precipitation over the Amazon: oxygen isotope ratios in annual rings in tropical cedar (Cedrela odorata). A century-long record from northern Bolivia shows that tree rings preserve the signal of oxygen isotopes in precipitation during the wet season, with weaker influences of temperature and vapor pressure. Tree ring δ ¹⁸O correlates strongly with δ ¹⁸O in precipitation from distant stations in the center and west of the basin, and with Andean ice core δ ¹⁸O showing that the signal is coherent over large areas. The signal correlates most strongly with basin-wide precipitation and Amazon river discharge. We attribute the strength of this (negative) correlation mainly to the cumulative rainout processes of oxygen isotopes (Rayleigh distillation) in air parcels during westward transport across the basin. We further find a clear signature of the El Niño-Southern Oscillation (ENSO) in the record, with strong ENSO influences over recent decades, but weaker influence from 1925 to 1975 indicating decadal scale variation in the controls on the hydrological cycle. The record exhibits a significant increase in δ ¹⁸O over the 20th century consistent with increases in Andean δ ¹⁸O ice core and lake records, which we tentatively attribute to increased water vapor transport into the basin. Taking these data together, our record reveals a fresh path to diagnose and improve our understanding of variation and trends of the hydrological cycle of the world’s largest river catchment.