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Recently, new soil data maps were developed, which include vertical soil properties like soil type. Implementing those into a multilayer Soil-Vegetation-Atmosphere-Transfer (SVAT) scheme, discontinuities in the water content occur at the interface between dissimilar soils. Therefore, care must be taken in solving the Richards equation for calculating vertical soil water fluxes. We solve a modified form of the mixed (soil water and soil matric potential based) Richards equation by subtracting the equilibrium state of soil matrix potential ψE from the hydraulic potential ψh. The sensitivity of the modified equation is tested under idealized conditions. The paper will show that the modified equation can handle with discontinuities in soil water content at the interface of layered soils.
Appropriate precautions in the case of flood occurrence often require long lead times (several days) in hydrological forecasting. This in turn implies large uncertainties that are mainly inherited from the meteorological precipitation forecast. Here we present a case study of the extreme flood event of August 2005 in the Swiss part of the Rhine catchment (total area 34 550 km2). This event caused tremendous damage and was associated with precipitation amounts and flood peaks with return periods beyond 10 to 100 years. To deal with the underlying intrinsic predictability limitations, 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 COSMO-LEPS that downscales the ECMWF ensemble prediction system 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. We document the setup of the coupled system and assess its performance for the flood event under consideration. We show that the probabilistic meteorological-hydrological ensemble prediction chain is quite effective and provides additional guidance for extreme event forecasting, in comparison to a purely deterministic forecasting system. For the case studied, it is also shown that most of the benefits of the probabilistic approach may be realized with a comparatively small ensemble size of 10 members.
The frequency of extreme events has changed, having a direct impact on human lives. Regional climate models help us to predict these regional climate changes. This work presents an atmosphere–ocean coupled regional climate system model (RCSM; with the atmospheric component COSMO-CLM and the ocean component NEMO) over the European domain, including three marginal seas: the Mediterranean, North, and Baltic Sea. To test the model, we evaluate a simulation of more than 100 years (1900–2009) with a spatial grid resolution of about 25 km. The simulation was nested into a coupled global simulation with the model MPI-ESM in a low-resolution configuration, whose ocean temperature and salinity were nudged to the ocean–ice component of the MPI-ESM forced with the NOAA 20th Century Reanalysis (20CR). The evaluation shows the robustness of the RCSM and discusses the added value by the coupled marginal seas over an atmosphere-only simulation. The coupled system is stable for the complete 20th century and provides a better representation of extreme temperatures compared to the atmosphere-only model. The produced long-term dataset will help us to better understand the processes leading to meteorological and climate extremes.
This study presents a method for adjusting long-term climate data records (CDRs) for the integrated use with near-real-time data using the example of surface incoming solar irradiance (SIS). Recently, a 23-year long (1983–2005) continuous SIS CDR has been generated based on the visible channel (0.45–1 μm) of the MVIRI radiometers onboard the geostationary Meteosat First Generation Platform. The CDR is available from the EUMETSAT Satellite Application Facility on Climate Monitoring (CM SAF). Here, it is assessed whether a homogeneous extension of the SIS CDR to the present is possible with operationally generated surface radiation data provided by CM SAF using the SEVIRI and GERB instruments onboard the Meteosat Second Generation satellites. Three extended CM SAF SIS CDR versions consisting of MVIRI-derived SIS (1983–2005) and three different SIS products derived from the SEVIRI and GERB instruments onboard the MSG satellites (2006 onwards) were tested. A procedure to detect shift inhomogeneities in the extended data record (1983–present) was applied that combines the Standard Normal Homogeneity Test (SNHT) and a penalized maximal T-test with visual inspection. Shift detection was done by comparing the SIS time series with the ground stations mean, in accordance with statistical significance. Several stations of the Baseline Surface Radiation Network (BSRN) and about 50 stations of the Global Energy Balance Archive (GEBA) over Europe were used as the ground-based reference. The analysis indicates several breaks in the data record between 1987 and 1994 probably due to artefacts in the raw data and instrument failures. After 2005 the MVIRI radiometer was replaced by the narrow-band SEVIRI and the broadband GERB radiometers and a new retrieval algorithm was applied. This induces significant challenges for the homogenisation across the satellite generations. Homogenisation is performed by applying a mean-shift correction depending on the shift size of any segment between two break points to the last segment (2006–present). Corrections are applied to the most significant breaks that can be related to satellite changes. This study focuses on the European region, but the methods can be generalized to other regions. To account for seasonal dependence of the mean-shifts the correction was performed independently for each calendar month. In comparison to the ground-based reference the homogenised data record shows an improvement over the original data record in terms of anomaly correlation and bias. In general the method can also be applied for the adjustment of satellite datasets addressing other variables to bridge the gap between CDRs and near-real-time data.
A twentieth century-long coupled atmosphere-ocean regional climate simulation with COSMO-CLM (Consortium for Small-Scale Modeling, Climate Limited-area Model) and NEMO (Nucleus for European Modelling of the Ocean) is studied here to evaluate the added value of coupled marginal seas over continental regions. The interactive coupling of the marginal seas, namely the Mediterranean, the North and the Baltic Seas, to the atmosphere in the European region gives a comprehensive modelling system. It is expected to be able to describe the climatological features of this geographically complex area even more precisely than an atmosphere-only climate model. The investigated variables are precipitation and 2 m temperature. Sensitivity studies are used to assess the impact of SST (sea surface temperature) changes over land areas. The different SST values affect the continental precipitation more than the 2 m temperature. The simulated variables are compared to the CRU (Climatic Research Unit) observational data, and also to the HOAPS/GPCC (Hamburg Ocean Atmosphere Parameters and Fluxes from Satellite Data, Global Precipitation Climatology Centre) data. In the coupled simulation, added skill is found primarily during winter over the eastern part of Europe. Our analysis shows that, over this region, the coupled system is dryer than the uncoupled system, both in terms of precipitation and soil moisture, which means a decrease in the bias of the system. Thus, the coupling improves the simulation of precipitation over the eastern part of Europe, due to cooler SST values and in consequence, drier soil.
has been demonstrated in climate models that both the Indian and East Asian summer monsoons (ISM and EASM) are strengthened by the uplift of the entire Asian orography or Tibetan Plateau (TP) (i.e. bulk mountain uplift). Such an effect is widely perceived as the major mechanism contributing to the evolution of Asian summer monsoons in the Neogene. However, geological evidence suggests more diachronous growth of the Asian orography (i.e. regional mountain uplift) than bulk mountain uplift. This demands a re-evaluation of the relation between mountain uplift and the Asian monsoon in the geological periods. In this study, sensitivity experiments considering the diachronous growth of different parts of the Asian orography are performed using the regional climate model COSMO-CLM to investigate their effects on the Asian summer monsoons. The results show that, different from the bulk mountain uplift, the regional mountain uplift can lead to an asynchronous development of the ISM and EASM. While the ISM is primarily intensified by the thermal insulation (mechanical blocking) effect of the southern TP (Zagros Mountains), the EASM is mainly enhanced by the surface sensible heating of the central, northern and eastern TP. Such elevated surface heating can induce a low-level cyclonic anomaly around the TP that reduces the ISM by suppressing the lower tropospheric monsoon vorticity, but promotes the EASM by strengthening the warm advection from the south of the TP that sustains the monsoon convection. Our findings provide new insights to the evolution of the Asian summer monsoons and their interaction with the tectonic changes in the Neogene.
Im Rahmen einer Zusammenarbeit zwischen der Thüringer Landesanstalt für Umwelt und Geologie und der Goethe-Universität Frankfurt fand in Kooperation mit dem Deutschen Wetterdienst (DWD) eine umfassende Studie zum konvektiven Unwetterpotential über Thüringen statt. Unwetterereignisse, die durch konvektive Prozesse in der Atmosphäre verursacht werden, besitzen ein nicht unerhebliches Schadenspotential, obwohl sie oftmals eine räumlich eng begrenzte Ausdehnung aufweisen. Aufgrund ihrer Charakteristik ist sowohl die Vorhersage solcher Ereignisse, als auch eine vollständige, systematische Erfassung für eine detaillierte Auswertung längerer Zeitreihen noch immer eine Herausforderung. Zusätzliches Interesse besteht in der Abschätzung der durch den Klimawandel abhängigen Entwicklung des zukünftigen Gefährdungspotentials konvektiver Unwetter. Für eine gezielte Untersuchung des Themenkomplexes ist eine Vielzahl unterschiedlicher Daten und Methoden verwendet worden. Mit Hilfe von Fernerkundungsdatensätzen wird ein räumlich differenziertes Gefährdungspotential über Thüringen nachgewiesen. Bedingt durch das Relief ist das Auftreten von Konvektion am häufigsten und intensivsten über dem südlichen Thüringer Wald und dessen Ostrand zu beobachten, während Nordthüringen eine deutlich geringere Aktivität solcher Unwetterereignisse aufweist. Eine Abschätzung mittels globaler Klimamodelle und daraus abgeleiteten Wetterlagen zeigt unter Berücksichtigung des RCP8.5 Klimaszenarios für die nahe Zukunft (2016-2045) eine Zunahme des Gefährdungspotentials durch konvektive Unwetter. Aufgrund des Anstiegs feuchter Wetterlagen (49 % auf 82 %) erhöht sich die Zunahme der Gefährdung für den Zeitraum 2071-2100 noch deutlicher. Im Vergleich zu diesem statistischen Ansatz nimmt die projizierte Gefährdung durch extreme Ereignisse erheblich zu (Faktor 6), wenn die Ergebnisse expliziter Simulationen konvektiver Ereignisse mit einem regionalen Klimamodell (mit horizontaler Gitterdistanz von 1 km) und eine Zunahme der Tage mit konvektiven Extremereignissen berücksichtigt werden. Ein Anstieg der Gefährdung durch konvektive Unwetter in der Zukunft ist wahrscheinlich. Eine Quantifizierung bleibt jedoch unsicher.
Observed weather and projected climate change suggest an increase in the transmission of vector-borne diseases (VBDs) in the Hindu Kush Himalayan (HKH) region. In this study, we systematically explore the literature for empiric associations between the climate variables and specific VBDs and their vectors in the HKH region. We conducted a systematic synthesis of the published literature on climate variables, VBDs and vectors in the HKH region until the 8th of December 2020. The majority of studies show significant positive associations of VBDs with climatic factors, such as temperature, precipitation, relative humidity, etc. This systematic review allowed us to identify the most significant variables to be considered for evidence-based trend estimates of the effects of climate change on VBDs and their vectors in the HKH region. This evidence-based trend was set into the context of climate change as well as the observed expansion of VBDs and disease vectors in the HKH region. The geographic range of VBDs expanded into previously considered non-endemic areas of highlands (mountains) in the HKH region. Based on scarce, but clear evidence of a positive relationship of most climate variables and VBDs and the observed climatic changes, we strongly recommend an expansion of vector control and surveillance programmes in areas of the HKH region that were previously considered to be non-endemic.
Background: Despite its largely mountainous terrain for which this Himalayan country is a popular tourist destination, Nepal is now endemic for five major vector-borne diseases (VBDs), namely malaria, lymphatic filariasis, Japanese encephalitis, visceral leishmaniasis and dengue fever. There is increasing evidence about the impacts of climate change on VBDs especially in tropical highlands and temperate regions. Our aim is to explore whether the observed spatiotemporal distributions of VBDs in Nepal can be related to climate change.
Methodology: A systematic literature search was performed and summarized information on climate change and the spatiotemporal distribution of VBDs in Nepal from the published literature until December 2014 following providing items for systematic review and meta-analysis (PRISMA) guidelines.
Principal findings: We found 12 studies that analysed the trend of climatic data and are relevant for the study of VBDs, 38 studies that dealt with the spatial and temporal distribution of disease vectors and disease transmission. Among 38 studies, only eight studies assessed the association of VBDs with climatic variables. Our review highlights a pronounced warming in the mountains and an expansion of autochthonous cases of VBDs to non-endemic areas including mountain regions (i.e., at least 2,000 m above sea level). Furthermore, significant relationships between climatic variables and VBDs and their vectors are found in short-term studies.
Conclusion: Taking into account the weak health care systems and difficult geographic terrain of Nepal, increasing trade and movements of people, a lack of vector control interventions, observed relationships between climatic variables and VBDs and their vectors and the establishment of relevant disease vectors already at least 2,000 m above sea level, we conclude that climate change can intensify the risk of VBD epidemics in the mountain regions of Nepal if other non-climatic drivers of VBDs remain constant.
Lightning climate change projections show large uncertainties caused by limited empirical knowledge and strong assumptions inherent to coarse-grid climate modeling. This study addresses the latter issue by implementing and applying the lightning potential index parameterization (LPI) into a fine-grid convection-permitting regional climate model (CPM). This setup takes advantage of the explicit representation of deep convection in CPMs and allows for process-oriented LPI inputs such as vertical velocity within convective cells and coexistence of microphysical hydrometeor types, which are known to contribute to charge separation mechanisms. The LPI output is compared to output from a simpler flash rate parameterization, namely the CAPE × PREC parameterization, applied in a non-CPM on a coarser grid. The LPI’s implementation into the regional climate model COSMO-CLM successfully reproduces the observed lightning climatology, including its latitudinal gradient, its daily and hourly probability distributions, and its diurnal and annual cycles. Besides, the simulated temperature dependence of lightning reflects the observed dependency. The LPI outperforms the CAPE × PREC parameterization in all applied diagnostics. Based on this satisfactory evaluation, we used the LPI to a climate change projection under the RCP8.5 scenario. For the domain under investigation centered over Germany, the LPI projects a decrease of 4.8% in flash rate by the end of the century, in opposition to a projected increase of 17.4% as projected using the CAPE × PREC parameterization. The future decrease of LPI occurs mostly during the summer afternoons and is related to (i) a change in convection occurrence and (ii) changes in the microphysical mixing. The two parameterizations differ because of different convection occurrences in the CPM and non-CPM and because of changes in the microphysical mixing, which is only represented in the LPI lightning parameterization.