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Convective rain cell properties and the resulting precipitation scaling in a warm-temperate climate
(2022)
Convective precipitation events have been shown to intensify at rates exceeding the Clausius–Clapeyron rate (CC rate) of ca. 7% K−1 under current climate conditions. In this study, we relate atmospheric variables (low-level dew point temperature, convective available potential energy, and vertical wind shear), which are regarded as ingredients for severe deep convection, to properties of convective rain cells (cell area, maximum precipitation intensity, lifetime, precipitation sum, and cell speed). The rain cell properties are obtained from a rain gauge-adjusted radar dataset in a mid-latitude region, which is characterized by a temperate climate with warm summers (Germany). Different Lagrangian cell properties scale with dew point temperature at varying rates. While the maximum precipitation intensity of cells scales consistently at the CC rate, the area and precipitation sum per cell scale at varying rates above the CC rate. We show that this super-CC scaling is caused by a covarying increase of convective available potential energy with dew point temperature. Wind shear increases the precipitation sum per cell mainly by increasing the spatial cell extent. From a Eulerian point of view, this increase is partly compensated by a higher cell velocity, which leads to Eulerian precipitation scaling rates close to and slightly above the CC rate. Thus, Eulerian scaling rates of convective precipitation are modulated by convective available potential energy and vertical wind shear, making it unlikely that present scaling rates can be applied to future climate conditions. Furthermore, we show that cells that cause heavy precipitation at fixed locations occur at low vertical wind shear and, thus, move relatively slowly compared to typical cells.
Convective shower characteristics simulated with the convection-permitting climate model COSMO-CLM
(2019)
This paper evaluates convective precipitation as simulated by the convection-permitting climate model (CPM) Consortium for Small-Scale Modeling in climate mode (COSMO-CLM) (with 2.8 km grid-spacing) over Germany in the period 2001–2015. Characteristics of simulated convective precipitation objects like lifetime, area, mean intensity, and total precipitation are compared to characteristics observed by weather radar. For this purpose, a tracking algorithm was applied to simulated and observed precipitation with 5-min temporal resolution. The total amount of convective precipitation is well simulated, with a small overestimation of 2%. However, the simulation underestimates convective activity, represented by the number of convective objects, by 33%. This underestimation is especially pronounced in the lowlands of Northern Germany, whereas the simulation matches observations well in the mountainous areas of Southern Germany. The underestimation of activity is compensated by an overestimation of the simulated lifetime of convective objects. The observed mean intensity, maximum intensity, and area of precipitation objects increase with their lifetime showing the spectrum of convective storms ranging from short-living single-cell storms to long-living organized convection like supercells or squall lines. The CPM is capable of reproducing the lifetime dependence of these characteristics but shows a weaker increase in mean intensity with lifetime resulting in an especially pronounced underestimation (up to 25%) of mean precipitation intensity of long-living, extreme events. This limitation of the CPM is not identifiable by classical evaluation techniques using rain gauges. The simulation can reproduce the general increase of the highest percentiles of cell area, total precipitation, and mean intensity with temperature but fails to reproduce the increase of lifetime. The scaling rates of mean intensity and total precipitation resemble observed rates only in parts of the temperature range. The results suggest that the evaluation of coarse-grained (e.g., hourly) precipitation fields is insufficient for revealing challenges in convection-permitting simulations.
Extreme convective precipitation is expected to increase with global warming. However, the rate of increase and the understanding of contributing processes remain highly uncertain. We investigated characteristics of convective rain cells like area, intensity, and lifetime as simulated by a convection-permitting climate model in the area of Germany under historical (1976–2005) and future (end-of-century, RCP8.5 scenario) conditions. To this end, a tracking algorithm was applied to 5-min precipitation output. While the number of convective cells is virtually similar under historical and future conditions, there are more intense and larger cells in the future. This yields an increase in hourly precipitation extremes, although mean precipitation decreases. The relative change in the frequency distributions of area, intensity, and precipitation sum per cell is highest for the most extreme percentiles, suggesting that extreme events intensify the most. Furthermore, we investigated the temperature and moisture scaling of cell characteristics. The temperature scaling drops off at high temperatures, with a shift in drop-off towards higher temperatures in the future, allowing for higher peak values. In contrast, dew point temperature scaling shows consistent rates across the whole dew point range. Cell characteristics scale at varying rates, either below (mean intensity), at about (maximum intensity and area), or above (precipitation sum) the Clausius–Clapeyron rate. Thus, the widely investigated extreme precipitation scaling at fixed locations is a complex product of the scaling of different cell characteristics. The dew point scaling rates and absolute values of the scaling curves in historical and future conditions are closest for the highest percentiles. Therefore, near-surface humidity provides a good predictor for the upper limit of for example, maximum intensity and total precipitation of individual convective cells. However, the frequency distribution of the number of cells depending on dew point temperature changes in the future, preventing statistical inference of extreme precipitation from near-surface humidity.
Extreme convective precipitation events are among the most severe hazards in central Europe and are expected to intensify under global warming. However, the degree of intensification and the underlying processes are still uncertain. In this thesis, recent advances in continuous, radar-based precipitation monitoring and convection-permitting climate modeling are used to investigate Lagrangian properties of convective rain cells such as precipitation intensity, cell area, and precipitation sum and their relationship to large-scale, environmental conditions.
Firstly, convective precipitation objects are tracked in a gauge-adjusted radar-data set and the properties of these cells are related to large-scale environmental variables to investigate the observed super-Clausius-Clapeyron (CC) scaling of convective extreme precipitation. The Lagrangian precipitation sum of convective cells increases with dew point temperature at rates well above the CC-rate with increasing rates for higher dew point temperatures. These varying, high rates are caused by a covarying increase of CAPE with dew point temperature as well as the effect of high vertical wind shear causing an increase in cell area and thus precipitation sum. At the same time, cells move faster at high vertical wind shear so that Eulerian scaling rates are lower than Lagrangian but still above the CC-rate. The results show that wind shear and static instability need to be taken into account when transferring precipitation scaling under current climate conditions to future conditions. Secondly, the representation of convective cell properties in the convection-permitting climate model COSMO-CLM is evaluated. The model can simulate the observed frequency distributions of cell properties such as lifetime, area, mean and maximum intensity, and precipitation sum. The increase of area and intensity with lifetime is also well captured despite an underestimation of the intensity of the most severe cells. Furthermore, the model can represent the temperature scaling of intensity, area, and precipitation sum but fails to simulate the observed increase of lifetime. Thus, the model is suitable to study climatologies of convective storms in Germany. Thirdly, two COSMO-CLM projections at the end of the century under emission scenario RCP8.5 were investigated. While the number of convective cells and their lifetime remain approximately constant compared to present conditions, intensity and area increase strongly. The relative increase of intensity and area is largest for the highest percentiles meaning that extreme events intensify the most. The characteristic afternoon maximum of convective precipitation is damped, and shifted to later times of day which leads to an increase of nighttime precipitation in the future. Scaling rates of cell properties with dew point temperature are nearly identical in present and future in the simulation driven by the EC-Earth model which means that the upper limit of cell properties like intensity, area, and precipitation sum could be predicted from near-surface dew point temperature. However, this result could not be reproduced by the simulation driven by MIROC5 and needs further investigation.
Mechanistic modeling of in vitro data generated from metabolic enzyme systems (viz., liver microsomes, hepatocytes, rCYP enzymes, etc.) facilitates in vitro–in vivo extrapolation (IVIV_E) of metabolic clearance which plays a key role in the successful prediction of clearance in vivo within physiologically-based pharmacokinetic (PBPK) modeling. A similar concept can be applied to solubility and dissolution experiments whereby mechanistic modeling can be used to estimate intrinsic parameters required for mechanistic oral absorption simulation in vivo. However, this approach has not widely been applied within an integrated workflow. We present a stepwise modeling approach where relevant biopharmaceutics parameters for ketoconazole (KTZ) are determined and/or confirmed from the modeling of in vitro experiments before being directly used within a PBPK model. Modeling was applied to various in vitro experiments, namely: (a) aqueous solubility profiles to determine intrinsic solubility, salt limiting solubility factors and to verify pKa; (b) biorelevant solubility measurements to estimate bile-micelle partition coefficients; (c) fasted state simulated gastric fluid (FaSSGF) dissolution for formulation disintegration profiling; and (d) transfer experiments to estimate supersaturation and precipitation parameters. These parameters were then used within a PBPK model to predict the dissolved and total (i.e., including the precipitated fraction) concentrations of KTZ in the duodenum of a virtual population and compared against observed clinical data. The developed model well characterized the intraluminal dissolution, supersaturation, and precipitation behavior of KTZ. The mean simulated AUC0–t of the total and dissolved concentrations of KTZ were comparable to (within 2-fold of) the corresponding observed profile. Moreover, the developed PBPK model of KTZ successfully described the impact of supersaturation and precipitation on the systemic plasma concentration profiles of KTZ for 200, 300, and 400 mg doses. These results demonstrate that IVIV_E applied to biopharmaceutical experiments can be used to understand and build confidence in the quality of the input parameters and mechanistic models used for mechanistic oral absorption simulations in vivo, thereby improving the prediction performance of PBPK models. Moreover, this approach can inform the selection and design of in vitro experiments, potentially eliminating redundant experiments and thus helping to reduce the cost and time of drug product development.
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.
Questions: Both species turnover and intraspecific trait variation can affect plant assemblage dynamics along environmental gradients. Here, we asked how community assemblage patterns in relation to species turnover and intraspecific variation differ between endemic and non-endemic species. We hypothesized that endemic species show lower intraspecific variation than non-endemic species because they tend to have high rates of in situ speciation, whereas non-endemic species are expected to have a larger gene pool and higher phenotypic plasticity.
Location: La Palma, Canary Islands.
Methods: We established 44 sampling sites along a directional gradient of precipitation, heat load, soil nitrogen, phosphorus and pH. Along this gradient, we estimated species abundances and measured three traits (plant height, leaf area and leaf thickness) on perennial endemic and non-endemic plant species. In total, we recorded traits for 1,223 plant individuals of 43 species. Subsequently, we calculated community-weighted mean traits to measure the relative contribution of species turnover, intraspecific variation and their covariation along the analysed gradient.
Results: The contribution of intraspecific variation to total variation was similar in endemic and non-endemic assemblages. For plant height, intraspecific variation explained roughly as much variation as species turnover. For leaf area and leaf thickness, intraspecific variation explained almost no variation. Species turnover effects mainly drove trait responses along the environmental gradient, but intraspecific variation was important for responses in leaf area to precipitation.
Conclusions: Despite their distinct evolutionary history, endemic and non-endemic plant assemblages show similar patterns in species turnover and intraspecific variation. Our results indicate that species turnover is the main component of trait variation in the underlying study system. However, intraspecific variation can increase individual species’ fitness in response to precipitation. Overall, our study challenges the theory that intraspecific trait variation is more important for the establishment of non-endemic species compared with endemic species.
Climatic niches describe the climatic conditions in which species can persist. Shifts in climatic niches have been observed to coincide with major climatic change, suggesting that species adapt to new conditions. We test the relationship between rates of climatic niche evolution and paleoclimatic conditions through time for 65 Old-World flycatcher species (Aves: Muscicapidae). We combine niche quantification for all species with dated phylogenies to infer past changes in the rates of niche evolution for temperature and precipitation niches. Paleoclimatic conditions were inferred independently using two datasets: a paleoelevation reconstruction and the mammal fossil record. We find changes in climatic niches through time, but no or weak support for a relationship between niche evolution rates and rates of paleoclimatic change for both temperature and precipitation niche and for both reconstruction methods. In contrast, the inferred relationship between climatic conditions and niche evolution rates depends on paleoclimatic reconstruction method: rates of temperature niche evolution are significantly negatively related to absolute temperatures inferred using the paleoelevation model but not those reconstructed from the fossil record. We suggest that paleoclimatic change might be a weak driver of climatic niche evolution in birds and highlight the need for greater integration of different paleoclimate reconstructions.