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Stability of halocarbons in whole air samples from the upper
troposphere and lowermost stratosphere
(2019)
Measurements of halogenated hydrocarbons of ambient air frequently rely on canister sampling followed by offline laboratory analysis. This allows for a large number of compounds to be analysed under stable conditions, maximising measurement precision. However, individual compounds might be affected during storage of canister samples. In order to assess halocarbon stability in whole air samples from the upper troposphere and lowermost stratosphere, we performed stability tests using the air sampling unit High REsolution Sampler (HIRES) which is part of the CARIBIC (Civil Aircraft for the Regular Investigation of the Atmosphere Based on an Instrument Container) instrument package. HIRES holds 88 light-weight stainless steel cylinders that are pressurized in flight to 4.5 bar using metal bellows pumps. The HIRES sampling unit was first deployed in 2010, but has up to now not been used for regular halocarbon analysis with exception of chloromethane. The sample collection unit was tested for sampling and storage effects of 28 halogenated compounds. The focus was on compound stability in the stainless steel canisters during storage of up to five weeks and on the influence of ozone, since flights take place in the upper troposphere and lowermost stratosphere with ozone mixing ratios of up to several hundred ppbV. Most of the investigated (hydro)chlorofluorocarbons and long-lived hydrofluorocarbons were found to be stable over a storage time of up to five weeks and were unaltered by ozone being present during pressurization. Some compounds such as for example dichloromethane, trichloromethane and tetrachloroethene started to decrease in the canisters after a storage time of more than two weeks or exhibited lowered mixing ratios in samples pressurized with ozone present. Few compounds such as for example tetrachloromethane and tribromomethane were found to be not stable in the HIRES stainless-steel canisters independent of ozone levels. Also growth was observed during storage, namely for HFC-152a and HFC-23.
Here we present a comprehensive attempt to correlate aragonitic Na∕Ca ratios from Desmophyllum pertusum (formerly known as Lophelia pertusa), Madrepora oculata and a caryophylliid cold-water coral (CWC) species with different seawater parameters such as temperature, salinity and pH. Living CWC specimens were collected from 16 different locations and analyzed for their Na∕Ca ratios using solution-based inductively coupled plasma-optical emission spectrometry (ICP-OES) measurements.
The results reveal no apparent correlation with salinity (30.1–40.57 g kg−1) but a significant inverse correlation with temperature (−0.31±0.04 mmolmol−1∘C−1). Other marine aragonitic organisms such as Mytilus edulis (inner aragonitic shell portion) and Porites sp. exhibit similar results highlighting the consistency of the calculated CWC regressions. Corresponding Na∕Mg ratios show a similar temperature sensitivity to Na∕Ca ratios, but the combination of two ratios appears to reduce the impact of vital effects and domain-dependent geochemical variation. The high degree of scatter and elemental heterogeneities between the different skeletal features in both Na∕Ca and Na∕Mg, however, limit the use of these ratios as a proxy and/or make a high number of samples necessary. Additionally, we explore two models to explain the observed temperature sensitivity of Na∕Ca ratios for an open and semi-enclosed calcifying space based on temperature-sensitive Na- and Ca-pumping enzymes and transport proteins that change the composition of the calcifying fluid and consequently the skeletal Na∕Ca ratio.
Here we present a comprehensive attempt to correlate aragonitic Na / Ca ratios from Lophelia pertusa, Madrepora oculata and a caryophylliid cold-water coral (CWC) species with different seawater parameters such as temperature, salinity and pH. Living CWC specimens were collected from 16 different locations and analyzed for their Na / Ca content using solution-based inductively coupled plasma-optical emission spectrometry (ICP-OES) measurements. The results reveal no apparent correlation with salinity (30.1–40.57 g/kg) but a significant inverse correlation with temperature (−0.31 mmol/mol/°C). Other marine aragonitic organisms such as Mytilus edulis (inner aragonitic shell portion) and Porites sp. exhibit similar results highlighting the consistency of the calculated CWC regressions. Corresponding Na / Mg ratios show a similar temperature sensitivity to Na / Ca ratios, but the combination of two ratios appear to reduce the impact of vital effects and domain-dependent geochemical variation. The high degree of scatter and elemental heterogeneities between the different skeletal features in both Na / Ca and Na / Mg however limit the use of these ratios as a proxy and/or make a high number of samples necessary. Additionally, we explore two models to explain the observed temperature sensitivity of Na / Ca ratios for an open and semi-enclosed calcifying space based on temperature sensitive Na and Ca pumping enzymes and transport proteins that change the composition of the calcifying fluid and consequently the skeletal Na / Ca ratio.
Global impact models represent process-level understanding of how natural and human systems may be affected by climate change. Their projections are used in integrated assessments of climate change. Here we test, for the first time, systematically across many important systems, how well such impact models capture the impacts of extreme climate conditions. Using the 2003 European heat wave and drought as a historical analogue for comparable events in the future, we find that a majority of models underestimate the extremeness of impacts in important sectors such as agriculture, terrestrial ecosystems, and heat-related human mortality, while impacts on water resources and hydropower are overestimated in some river basins; and the spread across models is often large. This has important implications for economic assessments of climate change impacts that rely on these models. It also means that societal risks from future extreme events may be greater than previously thought.
Latitudinal and bathymetrical species richness patterns in the NW Pacific and adjacent Arctic Ocean
(2019)
Global scale analyses have recently revealed that the latitudinal gradient in marine species richness is bimodal, peaking at low-mid latitudes but with a dip at the equator; and that marine species richness decreases with depth in many taxa. However, these overall and independently studied patterns may conceal regional differences that help support or qualify the causes in these gradients. Here, we analysed both latitudinal and depth gradients of species richness in the NW Pacific and its adjacent Arctic Ocean. We analysed 324,916 distribution records of 17,414 species from 0 to 10,900 m depth, latitude 0 to 90°N, and longitude 100 to 180°N. Species richness per c. 50 000 km2 hexagonal cells was calculated as alpha (local average), gamma (regional total) and ES50 (estimated species for 50 records) per latitudinal band and depth interval. We found that average ES50 and gamma species richness decreased per 5° latitudinal bands and 100 m depth intervals. However, average ES50 per hexagon showed that the highest species richness peaked around depth 2,000 m where the highest total number of species recorded. Most (83%) species occurred in shallow depths (0 to 500 m). The area around Bohol Island in the Philippines had the highest alpha species richness (more than 8,000 species per 50,000 km2). Both alpha and gamma diversity trends increased from the equator to latitude 10°N, then further decreased, but reached another peak at higher latitudes. The latitudes 60–70°N had the lowest gamma and alpha diversity where there is almost no ocean in our study area. Model selection on Generalized Additive Models (GAMs) showed that the combined effects of all environmental predictors produced the best model driving species richness in both shallow and deep sea. The results thus support recent hypotheses that biodiversity, while highest in the tropics and coastal depths, is decreasing at the equator and decreases with depth below ~2000 m. While we do find the declines of species richness with latitude and depth that reflect temperature gradients, local scale richness proved poorly correlated with many environmental variables. This demonstrates that while regional scale patterns in species richness may be related to temperature, that local scale richness depends on a greater variety of variables.
In global hydrological models, groundwater (GW) is typically represented by a bucket-like linear groundwater reservoir. Reservoir models, however, (1) can only simulate GW discharge to surface water (SW) bodies but not recharge from SW to GW, (2) provide no information on the location of the GW table, and (3) assume that there is no GW flow among grid cells. This may lead, for example, to an underestimation of groundwater resources in semiarid areas where GW is often replenished by SW or to an underestimation of evapotranspiration where the GW table is close to the land surface. To overcome these limitations, it is necessary to replace the reservoir model in global hydrological models with a hydraulic head gradient-based GW flow model.
We present G3M, a new global gradient-based GW model with a spatial resolution of 5′ (arcminutes), which is to be integrated into the 0.5∘ WaterGAP Global Hydrology Model (WGHM). The newly developed model framework enables in-memory coupling to WGHM while keeping overall runtime relatively low, which allows sensitivity analyses, calibration, and data assimilation. This paper presents the G3M concept and model design decisions that are specific to the large grid size required for a global-scale model. Model results under steady-state naturalized conditions, i.e., neglecting GW abstractions, are shown. Simulated hydraulic heads show better agreement to observations around the world compared to the model output of de Graaf et al. (2015). Locations of simulated SW recharge to GW are found, as is expected, in dry and mountainous regions but areal extent of SW recharge may be underestimated. Globally, GW discharge to rivers is by far the dominant flow component such that lateral GW flows only become a large fraction of total diffuse and focused recharge in the case of losing rivers, some mountainous areas, and some areas with very low GW recharge. A strong sensitivity of simulated hydraulic heads to the spatial resolution of the model and the related choice of the water table elevation of surface water bodies was found. We suggest to investigate how global-scale groundwater modeling at 5′ spatial resolution can benefit from more highly resolved land surface elevation data.
In global hydrological models, groundwater storages and flows are generally simulated by linear reservoir models. Recently, the first global gradient-based groundwater models were developed in order to improve the representation of groundwater-surface water interactions, capillary rise, lateral flows and human water use impacts. However, the reliability of model outputs is limited by a lack of data as well as model assumptions required due to the necessarily coarse spatial resolution. The impact of data quality is presented by showing the sensitivity of a groundwater model to changes in the only available global hydraulic conductivity data-set. To better understand the sensitivity of model output to uncertain spatially distributed parameter inputs, we present the first application of a global sensitivity method for a global-scale groundwater model using nearly 2000 steady-state model runs of the global gradient-based groundwater model G3M. By applying the Morris method in a novel domain decomposition approach that identifies global hydrological response units, spatially distributed parameter sensitivities are determined for a computationally expensive model. Results indicate that globally simulated hydraulic heads are equally sensitive to hydraulic conductivity, groundwater recharge and surface water body elevation, though parameter sensitivities vary regionally. For large areas of the globe, rivers are simulated to be either losing or gaining, depending on the parameter combination, indicating a high uncertainty of simulating the direction of flow between the two compartments. Mountainous and dry regions show a high variance in simulated head due to numerical difficulties of the model, limiting the reliability of computed sensitivities in these regions. This instability is likely caused by the uncertainty in surface water body elevation. We conclude that maps of spatially distributed sensitivities can help to understand complex behaviour of models that incorporate data with varying spatial uncertainties. The findings support the selection of possible calibration parameters and help to anticipate challenges for a transient coupling of the model.
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.
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.