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Floodplains play an important role in the terrestrial water cycle and are very important for biodiversity. Therefore, an improved representation of the dynamics of floodplain water flows and storage in global hydrological and land surface models is required. To support model validation, we combined monthly time series of satellite-derived inundation areas (Papa et al., 2010) with data on irrigated rice areas (Portmann et al., 2010). In this way, we obtained global-scale time series of naturally inundated areas (NIA), with monthly values of inundation extent during 1993–2004 and a spatial resolution of 0.5°. For most grid cells (0.5°×0.5°), the mean annual maximum of NIA agrees well with the static open water extent of the Global Lakes and Wetlands database (GLWD) (Lehner and Döll, 2004), but in 16% of the cells NIA is larger than GLWD. In some regions, like Northwestern Europe, NIA clearly overestimates inundated areas, probably because of confounding very wet soils with inundated areas. In other areas, such as South Asia, it is likely that NIA can help to enhance GLWD. NIA data will be very useful for developing and validating a floodplain modeling algorithm for the global hydrological model WGHM. For example, we found that monthly NIAs correlate with observed river discharges.
Spatial interpolation of rain gauge data is important in forcing of hydrological simulations or evaluation of weather predictions, for example. The spatial density of available data sites is often changing with time. This paper investigates the application of statistical distance, like one minus common variance of time series, between data sites instead of geographical distance in interpolation. Here, as a typical representative of interpolation methods the inverse distance weighting interpolation is applied and the test data is daily precipitation observed in Austria. Choosing statistical distance instead of geographical distance in interpolation of an actually available coarse observation network yields more robust interpolation results at sites of a denser network with actually lacking observations. The performance enhancement is in or close to mountainous terrain. This has the potential to parsimoniously densify the currently available observation network. Additionally, the success further motivates search for conceptual rain-orography interaction models as components of spatial rain interpolation algorithms in mountainous terrain.
Spatial interpolation of rain gauge data is important in forcing of hydrological simulations or evaluation of weather predictions, for example. This paper investigates the application of statistical distance, like one minus common variance of observation time series, between data sites instead of geographical distance in interpolation. Here, as a typical representative of interpolation methods the inverse distance weighting interpolation is applied and the test data is daily precipitation observed in Austria. Choosing statistical distance instead of geographical distance in interpolation of available coarse network observations to sites of a denser network, which is not reporting for the interpolation date, yields more robust interpolation results. The most distinct performance enhancement is in or close to mountainous terrain. Therefore, application of statistical distance in the inverse distance weighting interpolation or in similar methods can parsimoniously densify the currently available observation network. Additionally, the success further motivates search for conceptual rain-orography interaction models as components of spatial rain interpolation algorithms in mountainous terrain.
Spatial interpolation of precipitation data is uncertain. How important is this uncertainty and how can it be considered in evaluation of high-resolution probabilistic precipitation forecasts? These questions are discussed by experimental evaluation of the COSMO consortium's limited-area ensemble prediction system COSMO-LEPS. The applied performance measure is the often used Brier skill score (BSS). The observational references in the evaluation are (a) analyzed rain gauge data by ordinary Kriging and (b) ensembles of interpolated rain gauge data by stochastic simulation. This permits the consideration of either a deterministic reference (the event is observed or not with 100% certainty) or a probabilistic reference that makes allowance for uncertainties in spatial averaging. The evaluation experiments show that the evaluation uncertainties are substantial even for the large area (41 300 km2) of Switzerland with a mean rain gauge distance as good as 7 km: the one- to three-day precipitation forecasts have skill decreasing with forecast lead time but the one- and two-day forecast performances differ not significantly.
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.
Nucleation of aerosol particles from trace atmospheric vapours is thought to provide up to half of global cloud condensation nuclei. Aerosols can cause a net cooling of climate by scattering sunlight and by leading to smaller but more numerous cloud droplets, which makes clouds brighter and extends their lifetimes. Atmospheric aerosols derived from human activities are thought to have compensated for a large fraction of the warming caused by greenhouse gases. However, despite its importance for climate, atmospheric nucleation is poorly understood. Recently, it has been shown that sulphuric acid and ammonia cannot explain particle formation rates observed in the lower atmosphere. It is thought that amines may enhance nucleation, but until now there has been no direct evidence for amine ternary nucleation under atmospheric conditions. Here we use the CLOUD (Cosmics Leaving Outdoor Droplets) chamber at CERN and find that dimethylamine above three parts per trillion by volume can enhance particle formation rates more than 1,000-fold compared with ammonia, sufficient to account for the particle formation rates observed in the atmosphere. Molecular analysis of the clusters reveals that the faster nucleation is explained by a base-stabilization mechanism involving acid–amine pairs, which strongly decrease evaporation. The ion-induced contribution is generally small, reflecting the high stability of sulphuric acid–dimethylamine clusters and indicating that galactic cosmic rays exert only a small influence on their formation, except at low overall formation rates. Our experimental measurements are well reproduced by a dynamical model based on quantum chemical calculations of binding energies of molecular clusters, without any fitted parameters. These results show that, in regions of the atmosphere near amine sources, both amines and sulphur dioxide should be considered when assessing the impact of anthropogenic activities on particle formation.
Teleconnections of the Quasi-Biennial Oscillation in a multi-model ensemble of QBO-resolving models
(2021)
The Quasi-biennial Oscillation (QBO) dominates the interannual variability of the tropical stratosphere and influences other regions of the atmosphere. The high predictability of the QBO implies that its teleconnections could lead to increased skill of seasonal and decadal forecasts provided the relevant mechanisms are accurately represented in models. Here modelling and sampling uncertainties of QBO teleconnections are examined using a multi-model ensemble of QBO-resolving atmospheric general circulation models that have carried out a set of coordinated experiments as part of the Stratosphere-troposphere Processes And their Role in Climate (SPARC) QBO initiative (QBOi). During Northern Hemisphere winter, the stratospheric polar vortex in most of these models strengthens when the QBO near 50 hPa is westerly and weakens when it is easterly, consistent with, but weaker than, the observed response. These weak responses are likely due to model errors, such as systematically weak QBO amplitudes near 50 hPa, affecting the teleconnection. The teleconnection to the North Atlantic Oscillation is less well captured overall, but of similar strength to the observed signal in the few models that do show it. The models do not show clear evidence of a QBO teleconnection to the Northern Hemisphere Pacific-sector subtropical jet.
Towards the goal to understand the role of land-surface processes over the Indian sub-continent, a series of soil-moisture sensitivity simulations have been performed using a non-hydrostatic regional climate model COSMO-CLM. The experiments were driven by the lateral boundary conditions provided by the ERA-Interim (ECMWF) reanalysis. The simulation results show that the pre-monsoonal soil moisture has a significant influence on the monsoonal precipitation. Both, positive and negative soil-moisture precipitation (S-P) feedback processes are of importance. The negative S-P feedback process is especially influential in the western and the northern parts of India.
Abstract
The mineralogy, chemical composition, and physical properties of cratonic mantle eclogites with oceanic crustal protoliths can be modified by secondary processes involving interaction with fluids and melts, generated in various slab lithologies upon subduction (auto‐metasomatism) or mantle metasomatism after emplacement into the cratonic lithosphere. Here we combine new and published data to isolate these signatures and evaluate their effects on the chemical and physical properties of eclogite. Mantle metasomatism involving kimberlite‐like, ultramafic carbonated melts (UM carbonated melts) is ubiquitous though not pervasive, and affected between ~20% and 40% of the eclogite population at the various localities investigated here, predominantly at ~60–150 km depth, overlapping cratonic midlithospheric seismic discontinuities. Its hallmarks include lower jadeite component in clinopyroxene and grossular component in garnet, an increase in bulk‐rock MgO ± SiO2, and decrease in FeO and Al2O3 contents, and LREE‐enrichment accompanied by higher Sr, Pb, Th, U, and in part Zr and Nb, as well as lower Li, Cu ± Zn. This is mediated by addition of a high‐temperature pyroxene from a UM carbonated melt, followed by redistribution of this component into garnet and clinopyroxene. As clinopyroxene‐garnet trace‐element distribution coefficients increase with decreasing garnet grossular component, clinopyroxene is the main carrier of the metasomatic signatures. UM carbonated melt‐metasomatism at >130–150 km has destroyed the diamond inventory at some localities. These mineralogical and chemical changes contribute to low densities, with implications for eclogite gravitational stability, but negligible changes in shear‐wave velocities, and, if accompanied by H2O‐enrichment, will enhance electrical conductivities compared to unenriched eclogites.
Plain Language Summary
Oceanic crust formed at spreading ridges is recycled in subduction zones and undergoes metamorphism to eclogite. Some of this material is captured in the overlying lithospheric mantle, where it is exhumed by passing magmas. Having formed in spreading ridges, these eclogites have proven invaluable archives for the onset of plate tectonics, for the construction of cratons during subduction/collision, as probes of the convecting mantle from which their precursors formed, and as generators of heterogeneity upon recycling into Earth's convecting mantle. During subduction and until exhumation, interaction with fluids and melts (called metasomatism) can change the mineralogy, chemical composition, and physical properties of mantle eclogites, complicating their interpretation, but a comprehensive study of these effects is lacking so far. We investigated mantle eclogites from ancient continents (cratons) around the globe in order to define hallmarks of metasomatism by subduction‐related fluids and small‐volume ultramafic carbonated mantle melts. We find that the latter is pervasive and occurs predominantly at midlithospheric depths where seismic discontinuities are detected, typically causing diamond destruction and a reduction in density. This has consequences for their gravitational stability and for the interpretation of shearwave velocities in cratons.