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Medium range hydrological forecasts in mesoscale catchments are only possible with the use of hydrological models driven by meteorological forecasts, which in particular contribute quantitative precipitation forecasts (QPF). QPFs are accompanied by large uncertainties, especially for longer lead times, which are propagated within the hydrometeorological model system. To deal with this limitation of predictability, a probabilistic forecasting system is tested, which is based on a hydrological-meteorological ensemble prediction system. The meteorological component of the system is the operational limited-area ensemble prediction system COSMO-LEPS that downscales the global ECMWF ensemble to a horizontal resolution of 10 km, while the hydrological component is based on the semi-distributed hydrological model PREVAH with a spatial resolution of 500 m.
Earlier studies have mostly addressed the potential benefits of hydrometeorological ensemble systems in short case studies. Here we present an analysis of hydrological ensemble hindcasts for two years (2005 and 2006). It is shown that the ensemble covers the uncertainty during different weather situations with an appropriate spread-skill relationship. The ensemble also shows advantages over a corresponding deterministic forecast, even under consideration of an artificial spread.
Evaluation of radiation components in a global freshwater model with station-based observations
(2016)
In many hydrological models, the amount of evapotranspired water is calculated using the potential evapotranspiration (PET) approach. The main driver of several PET approaches is net radiation, whose downward components are usually obtained from meteorological input data, whereas the upward components are calculated by the model itself. Thus, uncertainties can be large due to both the input data and model assumptions. In this study, we compare the radiation components of the WaterGAP Global Hydrology Model, driven by two meteorological input datasets and two radiation setups from ERA-Interim reanalysis. We assess the performance with respect to monthly observations provided by the Baseline Surface Radiation Network (BSRN) and the Global Energy Balance Archive (GEBA). The assessment is done for the global land area and specifically for energy/water limited regions. The results indicate that there is no optimal radiation input throughout the model variants, but standard meteorological input datasets perform better than those directly obtained by ERA-Interim reanalysis for the key variable net radiation. The low number of observations for some radiation components, as well as the scale mismatch between station observations and 0.5° × 0.5° grid cell size, limits the assessment.
Background: Driven by globalization, urbanization and climate change, the distribution range of invasive vector species has expanded to previously colder ecoregions. To reduce health-threatening impacts on humans, insect vectors are extensively studied. Population genomics can reveal the genomic basis of adaptation and help to identify emerging trends of vector expansion.
Results: By applying whole genome analyses and genotype-environment associations to populations of the main dengue vector Ae. aegypti, sampled along an altitudinal temperature gradient in Nepal (200- 1300m), we identify adaptive traits and describe the species’ genomic footprint of climate adaptation to colder ecoregions. We found two clusters of differentiation with significantly different allele frequencies in genes associated to climate adaptation between the highland population (1300m) and all other lowland populations (≤ 800 m). We revealed non-synonymous mutations in 13 of the candidate genes associated to either altitude, precipitation or cold tolerance and identified an isolation-by-environment differentiation pattern.
Conclusion: Other than the expected gradual differentiation along the altitudinal gradient, our results reveal a distinct genomic differentiation of the highland population. This finding either indicates a differential invasion history to Nepal or local high-altitude adaptation explaining the population’s phenotypic cold tolerance. In any case, this highland population can be assumed to carry pre-adapted alleles relevant for the species’ invasion into colder ecoregions worldwide that way expanding their climate niche.
Driven by globalization, urbanization and climate change, the distribution range of invasive vector species has expanded to previously colder ecoregions. To reduce health-threatening impacts on humans, insect vectors are extensively studied. Population genomics can reveal the genomic basis of adaptation and help to identify emerging trends of vector expansion. By applying whole genome analyses and genotype-environment associations to populations of the main dengue vector Aedes aegypti, sampled along an altitudinal gradient in Nepal (200–1300 m), we identify putatively adaptive traits and describe the species' genomic footprint of climate adaptation to colder ecoregions. We found two differentiated clusters with significantly different allele frequencies in genes associated to climate adaptation between the highland population (1300 m) and all other lowland populations (≤800 m). We revealed nonsynonymous mutations in 13 of the candidate genes associated to either altitude, precipitation or cold tolerance and identified an isolation-by-environment differentiation pattern. Other than the expected gradual differentiation along the altitudinal gradient, our results reveal a distinct genomic differentiation of the highland population. Local high-altitude adaptation could be one explanation of the population's phenotypic cold tolerance. Carrying alleles relevant for survival under colder climate increases the likelihood of this highland population to a worldwide expansion into other colder ecoregions.
Several past summer floods in Central Europe were associated with so-called Vb‑cyclones propagating from the Mediterranean Sea north-eastward to Central Europe. This study illustrates the usefulness of the parametric transfer entropy measure TE‑linear in investigating heavy Vb‑cyclone precipitation events in the Odra catchment (Poland). With the application of the TE‑linear approach, we confirm the impact of the Mediterranean Sea on precipitation intensification. Moreover, we also detect significant information exchange to Vb‑cyclone precipitation from evaporation over the European continent along the typical Vb‑cyclone pathway. Thus, the Mediterranean Sea could enhance the Vb‑cyclone precipitation by pre-moistening continental moisture source regions that contribute to precipitation downstream in the investigated catchments. Overall, the transfer entropy approach with the measure TE‑linear proved to be computationally effective and complementary to traditional methods such as Lagrangian and Eulerian diagnostics.
A satellite-based climate record of monthly mean surface solar irradiance (SIS) is investigated with regard to possible inhomogeneities in time. The data record is provided by the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) Satellite Application Facility on Climate Monitoring (CM SAF) for the period of 1983 to 2005, covering a disk area between ±70° in latitude and longitude. The Standard Normal Homogeneity Test (SNHT) and two other homogeneity tests are applied with and without the use of reference SIS data (from the Baseline Surface Radiation Network (BSRN) and from the ECMWF (European Centre for Medium-Range Weather Forecasts) ERA -Interim reanalysis. The focus is on the detection of break-like inhomogeneities, which may occur due to satellite or SIS retrieval algorithm changes. In comparison with the few suitable BSRN SIS observation series with limited extension in time (no data before 1992), the CM SAF SIS time series do not show significant inhomogeneities, even though slight discrepancies in the surface measurements appear. The investigation of the full CM SAF SIS domain reveal inhomogeneities related to most of the documented satellite and retrieval changes, but only for relatively small domain fractions (especially in mountainous desert-like areas in Africa). In these regions the retrieval algorithm is not capable of adjusting for the changes of the satellite instruments. For other areas, e.g., Europe, no such breaks in the time series are found. We conclude that the CM SAF SIS data record has to be further assessed and regionally homogenized before climate trend investigations can be conducted.
Influence of sea surface roughness length parameterization on Mistral and Tramontane simulations
(2016)
The Mistral and Tramontane are mesoscale winds in southern France and above the Western Mediterranean Sea. They are phenomena well suited for studying channeling effects as well as atmosphere–land/ocean processes. This sensitivity study deals with the influence of the sea surface roughness length parameterizations on simulated Mistral and Tramontane wind speed and wind direction. Several simulations with the regional climate model COSMO-CLM were performed for the year 2005 with varying values for the Charnock parameter α. Above the western Mediterranean area, the simulated wind speed and wind direction pattern on Mistral days changes depending on the parameterization used. Higher values of α lead to lower simulated wind speeds. In areas, where the simulated wind speed does not change much, a counterclockwise rotation of the simulated wind direction is observed.
Convection-permitting models (CPMs) have proven their usefulness in representing precipitation on a sub-daily scale. However, investigations on sub-hourly scales are still lacking, even though these are the scales for which showers exhibit the most variability. A Lagrangian approach is implemented here to evaluate the representation of showers in a CPM, using the limited-area climate model COSMO-CLM. This approach consists of tracking 5‑min precipitation fields to retrieve different features of showers (e.g., temporal pattern, horizontal speed, lifetime). In total, 312 cases are simulated at a resolution of 0.01 ° over Central Germany, and among these cases, 78 are evaluated against a radar dataset. The model is able to represent most observed features for different types of convective cells. In addition, the CPM reproduced well the observed relationship between the precipitation characteristics and temperature indicating that the COSMO-CLM model is sophisticated enough to represent the climatological features of showers.
Background: Malaria is still a priority public health problem of Nepal where about 84% of the population are at risk. The aim of this paper is to highlight the past and present malaria situation in this country and its challenges for long-term malaria elimination strategies.
Methods: Malariometric indicator data of Nepal recorded through routine surveillance of health facilities for the years between 1963 and 2012 were compiled. Trends and differences in malaria indicator data were analysed.
Results: The trend of confirmed malaria cases in Nepal between 1963 and 2012 shows fluctuation, with a peak in 1985 when the number exceeded 42,321, representing the highest malaria case-load ever recorded in Nepal. This was followed by a steep declining trend of malaria with some major outbreaks. Nepal has made significant progress in controlling malaria transmission over the past decade: total confirmed malaria cases declined by 84% (12,750 in 2002 vs 2,092 in 2012), and there was only one reported death in 2012. Based on the evaluation of the National Malaria Control Programme in 2010, Nepal recently adopted a long-term malaria elimination strategy for the years 2011–2026 with the ambitious vision of a malaria-free Nepal by 2026. However, there has been an increasing trend of Plasmodium falciparum and imported malaria proportions in the last decade. Furthermore, the analysis of malariometric indicators of 31 malaria-risk districts between 2004 and 2012 shows a statistically significant reduction in the incidence of confirmed malaria and of Plasmodium vivax, but not in the incidence of P. falciparum and clinically suspected malaria.
Conclusions: Based on the achievements the country has made over the last decade, Nepal is preparing to move towards malaria elimination by 2026. However, considerable challenges lie ahead. These include especially, the need to improve access to diagnostic facilities to confirm clinically suspected cases and their treatment, the development of resistance in parasites and vectors, climate change, and increasing numbers of imported cases from a porous border with India. Therefore, caution is needed before the country embarks towards malaria elimination.
So-called medicanes (Mediterranean hurricanes) are meso-scale, marine, and warm-core Mediterranean cyclones that exhibit some similarities to tropical cyclones. The strong cyclonic winds associated with medicanes threaten the highly populated coastal areas around the Mediterranean basin. To reduce the risk of casualties and overall negative impacts, it is important to improve the understanding of medicanes with the use of numerical models. In this study, we employ an atmospheric limited-area model (COSMO-CLM) coupled with a one-dimensional ocean model (1-D NEMO-MED12) to simulate medicanes. The aim of this study is to assess the robustness of the coupled model in simulating these extreme events. For this purpose, 11 historical medicane events are simulated using the atmosphere-only model, COSMO-CLM, and coupled model, with different setups (horizontal atmospheric grid-spacings of 0.44°, 0.22°, and 0.08°; with/without spectral nudging, and an ocean grid-spacing of 1/12°). The results show that at high-resolution, the coupled model is able to not only simulate most of medicane events but also improve the track length, core temperature, and wind speed of simulated medicanes compared to the atmosphere-only simulations. The results suggest that the coupled model is more proficient for systemic and detailed studies of historical medicane events, and that this model can be an effective tool for future projections.