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Chemical ozone loss in winter 1991–1992 is recalculated based on observations of the HALOE satellite instrument, ER-2 aircraft measurements and balloon data. HALOE satellite observations are shown to be reliable in the lower stratosphere below 400 K, at altitudes where profiles are most likely disturbed by the enhanced sulfate aerosols, as a result of the Mt. Pinatubo eruption in June 1991. Very large chemical ozone loss was observed below 400 K from Kiruna balloon observations between December and March 1992. Additionally, for the two winters after the Mt. Pinatubo eruption, HALOE satellite observations show a stronger extent of chemical ozone loss at lower altitudes compared to other Arctic winter between 1991 and 2003. In stipe of already occurring deactivation of chlorine in March 1992, Mipas-B and LPMA balloon observations indicate still chlorine activation at lower altitudes, consistent with observed chemical ozone loss occurring between February and March and April. Enhanced chemical ozone loss in the Arctic winter 1991–1992 as calculated in earlier studies is corroborated here.
The Match method for quantification of polar chemical ozone loss is investigated mainly with respect to the impact of mixing across the vortex edge onto this estimate. We show for the winter 2002/03 that significant mixing across the vortex edge occurred and was accurately modeled by the Chemical Lagrangian Model of the Stratosphere. Observations of inert tracers and ozone in-situ from HAGAR on the Geophysica aircraft and sondes and also remote from MIPAS on ENVISAT were reproduced well. The model even reproduced a small vortex remnant that was isolated until June 2003 and was observed in-situ by a balloon-borne whole air sampler. We use this CLaMS simulation to quantify the impact of cross vortex edge mixing on the results of the Match method. It is shown that a time integration of the determined vortex average ozone loss rates as performed in Match results in larger ozone loss than the polar vortex average ozone loss in CLaMS. Also, the determination of the Match ozone loss rates can be influenced by mixing. This is especially important below 430 K, where ozone outside the vortex is lower than inside and the vortex boundary is not a strong transport barrier. This effect and further sampling effects cause an offset between vortex average ozone loss rates derived from Match and deduced from CLaMS with an even sampling for the entire vortex. Both, the time-integration of ozone loss and the determination of ozone loss rates for Match are evaluated using the winter 2002/03 CLaMS simulation. These impacts can explain the differences between CLaMS and Match column ozone loss. While the investigated effects somewhat reduce the apparent discrepancy in January ozone loss rates, a discrepancy between simulations and Match remains. However, its contribution to the accumulated ozone loss over the winter is not large.
Strong perturbations of the Arctic stratosphere during the winter 2002/2003 by planetary waves led to enhanced stretching and folding of the vortex. On two occasions the vortex in the lower stratosphere split into two secondary vortices that re-merged after some days. As a result of these strong disturbances the role of transport in and out of the vortex was stronger than usual. An advection and mixing simulation with the Chemical Lagrangian Model of the Stratosphere (CLaMS) utilising a suite of inert tracers tagging the original position of the air masses has been carried out. The results show a variety of synoptic and small scale features in the vicinity of the vortex boundary, especially long filaments peeling off the vortex edge and being slowly mixed into the mid latitude environment. The vortex folding events, followed by re-merging of different parts of the vortex led to strong filamentation of the vortex interior. During January, February, and March 2003 flights of the Russian high-altitude aircraft Geophysica were performed in order to probe the vortex, filaments and in one case the merging zone between the secondary vortices. Comparisons between CLaMS results and observations obtained from the Geophysica flights show in general good agreement.
During the APE-THESEO mission in the Indian Ocean the Myasishchev Design Bureau stratospheric research aircraft M55 Geophysica performed a flight over and within the inner core region of tropical cyclone Davina. Measurements of total water, water vapour, temperature, aerosol backscattering, ozone and tracers were made and are discussed here in comparison with the averages of those quantities acquired during the campaign time frame.
Temperature anomalies in the tropical tropopause layer (TTL), warmer than average in the lower part and colder than average in the upper TTL were observed. Ozone was strongly reduced compared to its average value, and thick cirrus decks were present up to the cold point, sometimes topped by a layer of very dry air. Evidence for meridional transport of trace gases in the stratosphere above the cyclone and the perturbed water distribution in the TTL is illustrated and discussed.
The ENVISAT validation programme for the atmospheric instruments MIPAS, SCIAMACHY and GOMOS is based on a number of balloon-borne, aircraft, satellite and ground-based correlative measurements. In particular the activities of validation scientists were coordinated by ESA within the ENVISAT Stratospheric Aircraft and Balloon Campaign or ESABC. As part of a series of similar papers on other species [this issue] and in parallel to the contribution of the individual validation teams, the present paper provides a synthesis of comparisons performed between MIPAS CH4 and N2O profiles produced by the current ESA operational software (Instrument Processing Facility version 4.61 or IPF v4.61, full resolution MIPAS data covering the period 9 July 2002 to 26 March 2004) and correlative measurements obtained from balloon and aircraft experiments as well as from satellite sensors or from ground-based instruments. In the middle stratosphere, no significant bias is observed between MIPAS and correlative measurements, and MIPAS is providing a very consistent and global picture of the distribution of CH4 and N2O in this region. In average, the MIPAS CH4 values show a small positive bias in the lower stratosphere of about 5%. A similar situation is observed for N2O with a positive bias of 4%. In the lower stratosphere/upper troposphere (UT/LS) the individual used MIPAS data version 4.61 still exhibits some unphysical oscillations in individual CH4 and N2O profiles caused by the processing algorithm (with almost no regularization). Taking these problems into account, the MIPAS CH4 and N2O profiles are behaving as expected from the internal error estimation of IPF v4.61 and the estimated errors of the correlative measurements.
During the second part of the TROCCINOX campaign that took place in Brazil in early 2005, chemical species were measured on-board the high-altitude research aircraft Geophysica (ozone, water vapor, NO, NOy, CH4 and CO) in the altitude range up to 20 km (or up to 450 K potential temperature), i.e. spanning the entire TTL region roughly extending between 350 and 420 K. Here, analysis of transport across the TTL is performed using a new version of the Chemical Lagrangian Model of the Stratosphere (CLaMS). In this new version, the stratospheric model has been extended to the earth surface. Above the tropopause, the isentropic and cross-isentropic advection in CLaMS is driven by meteorological analysis winds and heating/cooling rates derived from a radiation calculation. Below the tropopause, the model smoothly transforms from the isentropic to the hybrid-pressure coordinate and, in this way, takes into account the effect of large-scale convective transport as implemented in the vertical wind of the meteorological analysis. As in previous CLaMS simulations, the irreversible transport, i.e. mixing, is controlled by the local horizontal strain and vertical shear rates. Stratospheric and tropospheric signatures in the TTL can be seen both in the observations and in the model. The composition of air above ≈350 K is mainly controlled by mixing on a time scale of weeks or even months. Based on CLaMS transport studies where mixing can be completely switched off, we deduce that vertical mixing, mainly driven by the vertical shear in the tropical flanks of the subtropical jets and, to some extent, in the the outflow regions of the large-scale convection, offers an explanation for the upward transport of trace species from the main convective outflow at around 350 K up to the tropical tropopause around 380 K.
Long-term average groundwater recharge, which is equivalent to renewable groundwater resources, is the major limiting factor for the sustainable use of groundwater. Compared to surface water resources, groundwater resources are more protected from pollution, and their use is less restricted by seasonal and inter-annual flow variations. To support water management in a globalized world, it is necessary to estimate groundwater recharge at the global scale. Here, we present a best estimate of global-scale long-term average diffuse groundwater recharge (i.e. renewable groundwater resources) that has been calculated by the most recent version of the WaterGAP Global Hydrology Model WGHM (spatial resolution of 0.5° by 0.5°, daily time steps). The estimate was obtained using two state-of-the art global data sets of gridded observed precipitation that we corrected for measurement errors, which also allowed to quantify the uncertainty due to these equally uncertain data sets. The standard WGHM groundwater recharge algorithm was modified for semi-arid and arid regions, based on 15 independent estimates of diffuse groundwater recharge, which lead to an unbiased estimation of groundwater recharge in these regions. WGHM was tuned against observed long-term average river discharge at 1235 gauging stations by adjusting, individually for each basin, the partitioning of precipitation into evapotranspiration and total runoff. We estimate that global groundwater recharge was 12 666 km3/yr for the climate nor20 mal 1961–1990, i.e. 32% of total renewable water resources. In semi-arid and arid regions, mountainous regions, permafrost regions and in the Asian Monsoon region, groundwater recharge accounts for a lower fraction of total runoff, which makes these regions particularly vulnerable to seasonal and inter-annual precipitation variability and water pollution. Average per-capita renewable groundwater resources of countries vary 25 between 8m3/(capita yr) for Egypt to more than 1 million m3/(capita yr) for the Falkland Islands, the global average in the year 2000 being 2091m3/(capita yr). Regarding the uncertainty of estimated groundwater resources due to the two precipitation data sets, deviation from the mean is less than 1% for 50 out of the 165 countries considered, between 1 and 5% for 62, between 5 and 20% for 43 and between 20 and 80% for 10 countries. Deviations at the grid scale can be much larger, ranging between 0 and 186 mm/yr.
his paper investigates the value of observed river discharge data for global-scale hydrological modeling of a number of flow characteristics that are required for assessing water resources, flood risk and habitat alteration of aqueous ecosystems. An improved version of WGHM (WaterGAP Global Hydrology Model) was tuned in a way that simulated and observed long-term average river discharges at each station become equal, using either the 724-station dataset (V1) against which former model versions were tuned or a new dataset (V2) of 1235 stations and often longer time series. WGHM is tuned by adjusting one model parameter (γ) that affects runoff generation from land areas, and, where necessary, by applying one or two correction factors, which correct the total runoff in a sub-basin (areal correction factor) or the discharge at the station (station correction factor). The study results are as follows. (1) Comparing V2 to V1, the global land area covered by tuning basins increases by 5%, while the area where the model can be tuned by only adjusting γ increases by 8% (546 vs. 384 stations). However, the area where a station correction factor (and not only an areal correction factor) has to be applied more than doubles (389 vs. 93 basins), which is a strong drawback as use of a station correction factor makes discharge discontinuous at the gauge and inconsistent with runoff in the basin. (2) The value of additional discharge information for representing the spatial distribution of long-term average discharge (and thus renewable water resources) with WGHM is high, particularly for river basins outside of the V1 tuning area and for basins where the average sub-basin area has decreased by at least 50% in V2 as compared to V1. For these basins, simulated long-term average discharge would differ from the observed one by a factor of, on average, 1.8 and 1.3, respectively, if the additional discharge information were not used for tuning. The value tends to be higher in semi-arid and snow-dominated regions where hydrological models are less reliable than in humid areas. The deviation of the other simulated flow characteristics (e.g. low flow, inter-annual variability and seasonality) from the observed values also decreases significantly, but this is mainly due to the better representation of average discharge but not of variability. (3) The optimal sub-basin size for tuning depends on the modeling purpose. On the one hand, small basins between 9000 and 20 000 km2 show a much stronger improvement in model performance due to tuning than the larger basins, which is related to the lower model performance (with and without tuning), with basins over 60 000 km2 performing best. On the other hand, tuning of small basins decreases model consistency, as almost half of them require a station correction factor.
An evaluation scheme is presented in this paper which can be used to assess groundwater vulnerability according to the requirements of the European Water Framework Directive (WFD). The evaluation scheme results in a groundwater vulnerability map identifying areas of high, medium and low vulnerability, as necessary for the measurement planning of the WFD. The evaluation scheme is based on the definition of the vulnerability of the Intergovernmental Panel on Climate Change (IPCC). It considers exposure, sensitivity and the adaptive capacity of the region. The adaptive capacity is evaluated in an actors' platform, which was constituted for the region in the PartizipA ("Participative modelling, Actor and Ecosystem Analysis in Regions with Intensive Agriculture") project. As a result of the vulnerability assessment, 21% of the catchment area was classified as being highly vulnerable, whereas 73% has medium vulnerability and 6% has low vulnerability. Thus, a groundwater vulnerability assessment approach is presented, which can be used in practice on a catchment scale for the WFD measurement planning.
Global modelling of continental water storage changes : sensitivity to different climate data sets
(2007)
Since 2002, the GRACE satellite mission provides estimates of the Earth's dynamic gravity field with unprecedented accuracy. Differences between monthly gravity fields contain a clear hydrological signal due to continental water storage changes. In order to evaluate GRACE results, the state-of-the-art WaterGAP Global Hydrological Model (WGHM) is applied to calculate terrestrial water storage changes on a global scale. WGHM is driven by different climate data sets to analyse especially the influence of different precipitation data on calculated water storage. The data sets used are the CRU TS 2.1 climate data set, the GPCC Full Data Product for precipitation and data from the ECMWF integrated forecast system. A simple approach for precipitation correction is introduced. WGHM results are then compared with GRACE data. The use of different precipitation data sets leads to considerable differences in computed water storage change for a large number of river basins. Comparing model results with GRACE observations shows a good spatial correlation and also a good agreement in phase. However, seasonal variations of water storage as derived from GRACE tend to be significantly larger than those computed by WGHM, regardless of which climate data set is used.