An intercomparison of remotely sensed soil moisture products at various spatial scales over the Iberian Peninsula

Soil moisture (SM) can be retrieved from active microwave (AM), passive microwave (PM) and thermal infrared (TIR) observations, each having unique spatial and temporal coverages. A limitation of TIR‐based retrievals is a dependence on cloud‐free conditions, whereas microwave retrievals are almost all weather proof. A downside of SM retrievals from PM is the coarse spatial resolution. Although SM retrievals at coarse spatial resolution proved to be valuable for global‐scale and continental‐scale studies, their value for regional‐scale studies remains limited. To increase the use of SM retrievals from PM observations, an existing method to enhance their spatial resolution was applied. We present an intercomparison study over the Iberian Peninsula for three SM products on two different spatial sampling grids. The remotely sensed SM products were also compared with in situ observations from the Remedhus network. Variations between ground data and satellite‐based SM are observed; all three remotely sensed SM products show good agreement to the ground observations. The comparison shows that these ground observations and satellite data are consistent, based on the correlation coefficient (R) and root mean square error (RMSE). The remotely sensed products were intercompared after sampling at 25 × 25 km² and after applying the smoothing filter‐based intensity modulation (SFIM) downscaling technique at 10 × 10 km² grids. After the application of the SFIM technique, the SM retrievals from PM observations show better agreement with the other remotely sensed SM products for approximately 40% of the study area. For another 40% of the study area, we found a similar agreement between these product combinations, whereas in extreme environments, both arid and densely vegetated regions, the agreement decreases after the application of the SFIM technique. Agreement between retrievals of absolute SM content from PM and TIR observations is generally high (R = 0.77 for semi‐arid areas). This study enhances our understanding of the remotely sensed SM products for improvements of SM retrieval and merging strategies. Copyright © 2013 John Wiley & Sons, Ltd.     

Variability of aerosol properties during the 2007–2010 spring seasons over central Europe

Aerosol optical properties have been studied for spring seasons when increased values of PM10 are registered. Measurements of aerosol optical properties were taken by collocated lidar and sun-photometers at Belsk, Poland, and Minsk, Belarus. A significant increase of registered aerosol optical thickness (AOT) was found during episodes with elevated PM10 concentrations. An increase of AOT at 1020 nm amounted to 50% in the case of Minsk and 18% in the case of Belsk, while an increase of AOT at 400 nm was 66% and 33%, respectively. We noted an increase of Ångström exponent by 6% at both stations and no significant increase of single scattering albedo. The LIDAR measurements together with NAAPS model results and backtrajectory analysis suggest that both the biomass burning products and the Saharan dust are responsible for increased PM10 concentrations and large AOT values during spring time. The smoke aerosol is transported over Central Europe mainly in the boundary layer, increasing both PM10 concentration and AOT. The dust aerosol transported in the free troposphere slightly affects the AOT values only. Statistically significant correlation between PM10 concentration and AOT was found during reporting period.     

东亚地区春季黑碳气溶胶源排放及其浓度分布

本研究收集整理了东亚地区一个黑碳气溶胶的排放源,并利用一个三维化学输送模式系统模拟研究了东亚地区春季黑碳气溶胶的输送和演变过程.黑碳气溶胶浓度的模拟值与地面观测站和观测船获取的监测值相比,模拟值与监测值具有良好的一致性,这表明本研究收集整理的黑碳气溶胶的排放量及其分布是基本合理的,模式系统较好地反映了黑碳气溶浓度的时空分布和变化趋势,再现了许多观测到的重要特征.模拟结果表明,东亚地区春季间隙性的长距离输送对于西北太平洋海域的黑碳气溶胶浓度分布具有非常重要的影响.     

Long-range transport of aerosols from agriculture crop residue burning in Indo-Gangetic Plains—A study using LIDAR,ground measurements and satellite data

Agriculture crop residue burning in tropics is an important source of atmospheric aerosols and monitoring their long-range transport is an important element in climate change studies. Synchronous measurements using micro-pulsed lidar, MICROTOPS-II sun photometer, multi-filter rotating shadow band radiometer (MFRSR) on aerosol optical depth and ground reaching solar irradiance were carried at an urban location in central region of India. Aerosol backscatter profiles obtained from micro-pulse lidar showed elevated aerosol layers up to ～3 km on certain days during October 2007. Satellite data observations on aerosol properties suggested transport of particles from agriculture crop residue burning in Indo-Gangetic Plains over large regions. Radiative forcing of aerosols estimated from SBDART model with input information on aerosol chemical properties, aerosol optical depth and single scattering albedo and broadband solar irradiance measurements using MFRSR showed good correlation (R=0.98).     

Simulating spatiotemporal variations of atmospheric CO2 using a nested hemispheric model

A three-dimensional Eulerian nested model for transport, diffusion, and surface fluxes of CO₂ has been developed. The model is used to study the spatial and temporal variations of atmospheric CO₂ concentrations as a step towards a better understanding of the regional source pattern over Europe. The influence from the national surface characteristics, as e.g. fossil CO₂ emissions or ecosystem fluxes, can be treated on a continental or national level in the model. In the future the model can be used as a mean to corroborate national and EU-wide controls or reductions of carbon emissions. One of the major questions in the estimation of e.g. national CO₂ budgets is the quantification of surface ecosystem fluxes. In order to test the sensitivity of atmospheric CO₂ concentrations to ecosystem fluxes, two different parameterizations [J. Geophys. Res. 92 (1987) 2999] and [Global Biogeochem. Cycles 10 (1996) 269] have been implemented in the model. The model both with and without nest is validated by comparison with measurements and the different model results will be discussed. The results show that including a nested domain with higher spatial resolution significantly improves the model performance in some areas. In spite of regional deviations in the two sets of ecosystems fluxes no major differences are seen over Europe as a whole when either of the two parameterizations are included in the model and the results compared.     

Space- and ground-based CO2 measurements: A review

The climate warming is mainly due to the increase in concentrations of anthropogenic greenhouse gases, of which CO₂ is the most important one responsible for radiative forcing of the climate. In order to reduce the great estimation uncertainty of atmospheric CO₂ concentrations, several CO₂-related satellites have been successfully launched and many future greenhouse gas monitoring missions are planned. In this paper, we review the development of CO₂ retrieval algorithms, spatial interpolation methods and ground observations. The main findings include: 1) current CO₂ retrieval algorithms only partially account for atmospheric scattering effects; 2) the accurate estimation of the vertical profile of greenhouse gas concentrations is a long-term challenge for remote sensing techniques; 3) ground-based observations are too sparse to accurately infer CO₂ concentrations on regional scales; and 4) accuracy is the primary challenge of satellite estimation of CO₂ concentrations. These findings, taken as a whole, point to the need to develop a high accuracy method for simulation of carbon sources and sinks on the basis of the fundamental theorem of Earth’s surface modelling, which is able to efficiently fuse space- and ground-based measurements on the one hand and work with atmospheric transport models on the other hand.     

A multi‐source precipitation estimation approach to fill gaps over a radar precipitation field: a case study in the Colorado River Basin

The present work develops an approach to seamlessly blend satellite, available radar, climatological and gauge precipitation products to fill gaps in ground‐based radar precipitation field. To mix different precipitation products, the error of any of the products relative to each other should be removed. For bias correction, the study uses an ensemble‐based method that aims to estimate spatially varying multiplicative biases in SPEs using a radar precipitation product. A weighted successive correction method (SCM) is used to make the merging between error corrected satellite and radar precipitation estimates. In addition to SCM, we use a combination of SCM and Bayesian spatial model for merging the rain gauges (RGs) and climatological precipitation sources with radar and SPEs. We demonstrated the method using a satellite‐based hydro‐estimator; a radar‐based, stage‐II; a climatological product, Parameter‐elevation Regressions on Independent Slopes Model and a RG dataset for several rain events from 2006 to 2008 over an artificial gap in Oklahoma and a real radar gap in the Colorado River basin. Results show that: the SCM method in combination with the Bayesian spatial model produced a precipitation product in good agreement with independent measurements. The study implies that using the available radar pixels surrounding the gap area, RG, Parameter‐elevation Regressions on Independent Slopes Model and satellite products, a radar‐like product is achievable over radar gap areas that benefit the operational meteorology and hydrology community. Copyright © 2013 John Wiley & Sons, Ltd.     

Interannual variability of tropospheric NO2 column over central Europe — observations from SCIAMACHY and GEM-AQ model simulations

Spatial and temporal variability of NO₂ tropospheric column over Europe was analyzed for a 3 year period (2008–2010) based on monthly average observations from SCIAMACHY and the GEM-AQ model results. The GEM-AQ model was run in a global variable configuration with a resolution of ～15 km over Central Europe. Spatial averaged time series were calculated for two selected regions in Western and Central Europe in order to assess the seasonal and interannual variability of the tropospheric NO₂. The spatial pattern is similar near large emission sources for consecutive years. However, in remote regions there are differences due to interannual variability of meteorological conditions. Highest tropospheric NO₂ column values (over 150 × 10¹⁵ molecules/cm²) were persistent over the Benelux and over most of the European agglomerations. The general agreement between modelled and observed NO₂ column is good. In the remote areas, the modelled NO₂ column shows weaker gradients than the observed field.     

Tidal loading along a profile Europe-East Africa-South Asia-Australia and the Pacific Ocean

A knowledge of the vertical component of the oceanic tidal load to a precision of at least one microgal is essential for the geophysical exploitation of the high-precision absolute and differential gravity measurements which are being made at ground level and in deep boreholes. On the other hand the ocean load and attraction signal contained in Earth tide gravity measurements can be extracted with a precision which is sufficient to characterize the behaviour of the oceanic tides in different basins and this provides a check of the validity of the presently proposed cotidal maps. The tidal gravity profiles made since 1971 from Europe to Polynesia, through East Africa, Asia and Australia, with correctly intercalibrated gravimeters, comprise information from 91 tidal gravity stations which is used in this paper with this goal in mind.A discussion of all possible sources of error is presented which shows that at the level of 0.5 μgal the observed effects cannot be ascribed to computational or instrumental errors. Cotidal maps which generate computed loads in agreement with the Earth tide gravity measurements over a sufficiently broad area can be used with confidence as a working standard to apply tidal corrections to high-precision measurements made by using new techniques in geodesy, geophysics and geodynamics, satellite altimetry, very long baseline interferometry, Moon and satellite laser ranging and absolute gravity. The recent cotidal maps calculated by Schwiderski for satellite altimetry reductions agree very well with land-based gravimeter observations of the diurnal components of the tides (O₁, K₁ and P₁ waves) but his semi-diurnal component maps (M₂, S₂ and N₂ waves) strangely appear less satisfactory in some large areas. The maps of Hendershott and Parke give good results in several large areas but not everywhere. More detailed investigations are needed not only for several coastal stations but mainly in the Himalayas.     

3-D Global Induction in the Oceans and Solid Earth: Recent Progress in Modeling Magnetic and Electric Fields from Sources of Magnetospheric,Ionospheric and Oceanic Origin

Electromagnetic induction in the Earth’s interior is an important contributor to the near-Earth magnetic and electric fields. The oceans play a special role in this induction due to their relatively high conductivity which leads to large lateral variability in surface conductance. Electric currents that generate secondary fields are induced in the oceans by two different processes: (a) by time varying external magnetic fields, and (b) by the motion of the conducting ocean water through the Earth’s main magnetic field. Significant progress in accurate and detailed predictions of the electric and magnetic fields induced by these sources has been achieved during the last few years, via realistic three-dimensional (3-D) conductivity models of the oceans, crust and mantle along with realistic source models. In this review a summary is given of the results of recent 3-D modeling studies in which estimates are obtained for the magnetic and electric signals at both the ground and satellite altitudes induced by a variety of natural current sources. 3-D induction effects due to magnetospheric currents (magnetic storms), ionospheric currents (Sq, polar and equatorial electrojets), ocean tides, global ocean circulation and tsunami are considered. These modeling studies demonstrate that the 3-D induction (ocean) effect and motionally-induced signals from the oceans contribute significantly (in the range from a few to tens nanotesla) to the near-Earth magnetic field. A 3-D numerical solution based on an integral equation approach is shown to predict these induction effects with the accuracy and spatial detail required to explain observations both on the ground and at satellite altitudes. On leave from Institute of Terrestrial Magnetism, Ionosphere and Radiowave Propagation, Russian Academy of Sciences, 142190 Troitsk, Moscow region, Russia.     

Hydrodynamics and sediment dynamics in the German Bight. A focus on observations and numerical modelling in the East Frisian Wadden Sea

This work deals with analysis of hydrographic observations and results of numerical simulations. The data base includes acoustic Doppler current profilers (ADCP) observations, continuous measurements on data stations and satellite data originating from the medium resolution imaging spectrometer (MERIS) onboard the European Space Agency (ESA) satellite ENVISAT with a spatial resolution of 300 m. Numerical simulations use nested models with horizontal resolutions ranging from 1 km in the German Bight to 200 m in the East Frisian Wadden Sea coupled with a suspended matter transport model. Modern satellite observations have now a comparable horizontal resolution with high-resolution numerical model of the entire area of the East Frisian Wadden Sea allowing to describe and validate new and so far unknown patterns of sediment distribution. The two data sets are consistent and reveal an oscillatory behaviour of sediment pools to the north of the back-barrier basins and clear propagation patterns of tidally driven suspended particulate matter outflow into the North Sea. The good agreement between observations and simulations is convincing evidence that the model simulates the basic dynamics and sediment transport processes, which motivates its further use in hindcasting, as well as in the initial steps towards forecasting circulation and sediment dynamics in the coastal zone.     

Comparison of heat and bromide as ground water tracers near streams

Heat and bromide were compared as tracers for examining stream/ground water exchanges along the middle reaches of the Santa Clara River, California, during a 10-hour surface water sodium bromide injection test. Three cross sections that comprise six shallow (<1 m) piezometers were installed at the upper, middle, and lower sections of a 17 km long study reach, to monitor temperatures and bromide concentrations in the shallow ground water beneath the stream. A heat and ground water transport simulation model and a closely related solute and ground water transport simulation model were matched up for comparison of simulated and observed temperatures and bromide concentrations in the streambed. Vertical, one-dimensional simulations of sediment temperature were fitted to observed temperature results, to yield apparent streambed hydraulic conductivities in each cross section. The temperature-based hydraulic conductivities were assigned to a solute and ground water transport model to predict sediment bromide concentrations, during the sodium bromide injection test. Vertical, one-dimensional simulations of bromide concentrations in the sediments yielded a good match to the observed bromide concentrations, without adjustment of any model parameters except solute dispersivities. This indicates that, for the spatial and temporal scales examined on the Santa Clara River, the use of heat and bromide as tracers provide comparable information with respect to apparent hydraulic conductivities and fluxes for sediments near streams. In other settings, caution should be used due to differences in the nature of conservative (bromide) versus nonconservative (heat) tracers, particularly when preferential flowpaths are present.     

Variational assimilation of meteorological observations in the lower atmosphere: A tutorial on how it works

Data assimilation combines atmospheric measurements with knowledge of atmospheric behavior as codified in computer models, thus producing a “best” estimate of current conditions that is consistent with both information sources. The four major challenges in data assimilation are: (1) to generate an initial state for a computer forecast that has the same mass-wind balance as the assimilating model, (2) to deal with the common problem of highly non-uniform distribution of observations, (3) to exploit the value of proxy observations (of parameters that are not carried explicitly in the model), and (4) to determine the statistical error properties of observing systems and numerical model alike so as to give each information source the proper weight. Variational data assimilation is practiced at major meteorological centers around the world. It is based upon multivariate linear regression, dating back to Gauss, and variational calculus. At the heart of the method is the minimization of a cost function, which guarantees that the analyzed fields will closely resemble both the background field (a short forecast containing a priori information about the atmospheric state) and current observations. The size of the errors in the background and the observations (the latter, arising from measurement and non-representativeness) determine how close the analysis is to each basic source of information. Three-dimensional variational (3DVAR) assimilation provides a logical framework for incorporating the error information (in the form of variances and spatial covariances) and deals directly with the problem of proxy observations. 4DVAR assimilation is an extension of 3DVAR assimilation that includes the time dimension; it attempts to find an evolution of model states that most closely matches observations taken over a time interval measured in hours. Both 3DVAR and, especially, 4DVAR assimilation require very large computing resources. Researchers are trying to find more efficient numerical solutions to these problems. Variational assimilation is applicable in the upper atmosphere, but practical implementation demands accurate modeling of the physical processes that occur at high altitudes and multiple sources of observations.     

Tackling mass redistribution phenomena by time-dependent GRACE- and terrestrial gravity observations

Time variable gravity field models derived from the satellite mission GRACE have been demonstrated to be consistent with water mass variations in the global hydrological cycle. Independent observations are provided by terrestrial measurements. In order to achieve a maximum of reliability and information gain, ground-based gravity observations may be deployed for comparison with the gravity field variations derived from the GRACE satellite mission. In this context, the data of the network of superconducting gravimeters (SG) of the ‘Global Geodynamics Project’ (GGP) are of particular interest. This study is focused on the dense SG network in Central Europe with its long-term gravity observations. It is shown that after the separation and reduction of local hydrological effects in the SG observations especially for subsurface stations, the time-variable gravity signals from GRACE agree well with the terrestrial observations from the SG station cluster.Station stability of the SG sites with respect to vertical deformations was checked by GNSS based observations. Most of the variability can be explained by loading effects due to changes in continental water storage, and, in general, the stability of all stations has been confirmed.From comparisons based on correlation and coherence analyses in combination with the root mean square (RMS) variability of the time series emerges, that the maximum correspondence between the SG and GRACE time series is achieved when filtering the GRACE data with Gaussian filters of about 1000 km filter length, which is in accordance with previous publications.Empirical Orthogonal Functions (EOF) analysis was applied to the gravity time series in order to identify common characteristic spatial and temporal patterns. The high correspondence of the first modes for GRACE and SG data implies that the first EOF mode represents a large-scale (Central European) time-variable gravity signal seen by both the GRACE satellites and the SG cluster.     

Assimilating remotely sensed snow observations into a macroscale hydrology model

Accurate forecasting of snow properties is important for effective water resources management, especially in mountainous areas like the western United States. Current model-based forecasting approaches are limited by model biases and input data uncertainties. Remote sensing offers an opportunity for observation of snow properties, like areal extent and water equivalent, over larger areas. Data assimilation provides a framework for optimally merging information from remotely sensed observations and hydrologic model predictions. An ensemble Kalman filter (EnKF) was used to assimilate remotely sensed snow observations into the variable infiltration capacity (VIC) macroscale hydrologic model over the Snake River basin. The snow cover extent (SCE) product from the moderate resolution imaging spectroradiometer (MODIS) flown on the NASA Terra satellite was used to update VIC snow water equivalent (SWE), for a period of four consecutive winters (1999–2003). A simple snow depletion curve model was used for the necessary SWE–SCE inversion. The results showed that the EnKF is an effective and operationally feasible solution; the filter successfully updated model SCE predictions to better agree with the MODIS observations and ground surface measurements. Comparisons of the VIC SWE estimates following updating with surface SWE observations (from the NRCS SNOTEL network) indicated that the filter performance was a modest improvement over the open-loop (un-updated) simulations. This improvement was more evident for lower to middle elevations, and during snowmelt, while during accumulation the filter and open-loop estimates were very close on average. Subsequently, a preliminary assessment of the potential for assimilating the SWE product from the advanced microwave scanning radiometer (AMSR-E, flown on board the NASA Aqua satellite) was conducted. The results were not encouraging, and appeared to reflect large errors in the AMSR-E SWE product, which were also apparent in comparisons with SNOTEL data.     

Spatial character of the gaseous and particulate state compound correlation of urban atmospheric pollution in winter and summer

The spatial/temporal variation information of atmospheric dynamic-chemical processes at observation site points of the "canopy" boundary of Beijing urban building ensemble and over urban area "surface", as well as the seasonal correlation structure of the gaseous and particulate states of urban atmospheric pollution (UAP) and its seasonal conversion feature at observation points are investigated, using the comprehensive observation data of the Beijing City Air Pollution Observation Experiment (BECAPEX) in winter and summer 2003 with a "point-surface" combined research approach. By using "one dimension spatial empirical orthogonal function (EOF)" principal component analysis (PCA) mode, the seasonal change of gaseous and particulate states of atmospheric aerosols and the association feature of pollutant species under the background of the complicated structure of urban boundary layer (UBL) are analyzed. The comprehensive analyses of the principal components of particle concentrations,gaseous pollutant species, and meteorological conditions reveal the seasonal changes of the complex constituent and structure features of the gaseous and particulate states of UAP to further trace the impact feature of urban aerosol pollution surface sources and the seasonal difference of the component structure of UAP. Research results suggest that in the temporal evolution of the gaseous and particulate states of winter/summer UAP, NOx, CO, and SO2 showed an "in-phase" evolution feature, however, O3 showed an "inverse-phase" relation with other species,all possessing distinctive dependent feature. On the whole, summer concentrations of gaseous pollutants CO, SO2, and NOx were obviously lower than winter ones, especially, the reduction in CO concentration was most distinctive, and ones in SO2 and NOx were next. However, the summer O3 concentration was more than twice winter one. Winter/summer differences in PM10and PM2.5 particle concentrations were relatively not obvious, which indicates that responses of PM10 and PM2.5 particle concentrations to the difference of winter/summer heating period emission sources are far less distinctive than those of NOx, SO2, and CO. The correlation feature of winter/summer gaseous and particulate states depicts that both PM10 and PM2.5 particles were significantly correlated with NOx, and their correlations with NOx are more significant than those with other pollutants. Through PCA, it is found that there was a distinctive difference in the principal component combination structure of winter/summer PM10 and PM2.5 particles: SO2 and NOx dominated in the principal component of winter PM10 and PM2.5 particles; while CO and NOx played the major role in the principal component of summer PM10 and PM2.5 particles. For winter/summer PM10 and PM2.5 particles, there might exist the gaseous and particulate states correlation structures of different "combinations" of such dependent pollutant species. Research results also uncover that the interaction processes of gaseous and particulate states were also related with the vertical structure of UBL, that is to say, the low value layer of UBL O3 concentration was associated with the collocation of atmospheric vertical structures of the low level inversion,inverse humidity, and small wind, which depicts summer boundary layer atmospheric character, i.e.the compound impact of the dependent factor "combination" of wind, temperature, and humidity elements and their collocation structure on the variations of different gaseous pollutant concentrations. Such a depth structure of the extremely low value of O3 concentration in the UBL accords with its "inverse-phase" relation with other gaseous pollutant species. The PCA of meteorological factors associated with PM10 and PM2.5 concentrations also reveals the sensitivity of PM10 and PM2.5 concentration to the combinatory feature of local meteorological conditions.     

Evaluation of snow models in terrestrial biosphere models using ground observation and satellite data: impact on terrestrial ecosystem processes

Snow is important for water management, and an important component of the terrestrial biosphere and climate system. In this study, the snow models included in the Biome‐BGC and Terrestrial Observation and Prediction System (TOPS) terrestrial biosphere models are compared against ground and satellite observations over the Columbia River Basin in the US and Canada and the impacts of differences in snow models on simulated terrestrial ecosystem processes are analysed. First, a point‐based comparison of ground observations against model and satellite estimates of snow dynamics are conducted. Next, model and satellite snow estimates for the entire Columbia River Basin are compared. Then, using two different TOPS simulations, the default TOPS model (TOPS with TOPS snow model) and the TOPS model with the Biome‐BGC snow model, the impacts of snow model selection on runoff and gross primary production (GPP) are investigated. TOPS snow model predictions were consistent with ground and satellite estimates of seasonal and interannual variations in snow cover, snow water equivalent, and snow season length; however, in the Biome‐BGC snow model, the snow pack melted too early, leading to extensive underpredictions of snow season length and snow covered area. These biases led to earlier simulated peak runoff and reductions in summer GPP, underscoring the need for accurate snow models within terrestrial ecosystem models. Copyright © 2007 John Wiley & Sons, Ltd.     

A multiyear analysis of aerosol optical thickness over Europe and Central Poland using NAAPS model simulation

This study contains a comparative analysis of aerosol optical thickness (AOT) between numerical calculations obtained from the Navy Aerosol Analysis and Prediction System (NAAPS) model and direct observations from the AERONET robotic network and the Saharan Aerosol over WArsaw (SAWA) field campaign. AOT was calculated for 500 nm wavelength. The comparison shows underestimation of the total aerosol optical thickness simulated by NAAPS. The correlation coefficients between model and observation oscillates between 0.57 and 0.72. Results of seven-year (1998–2004) NAAPS simulation of aerosol components (sea salt, mineral dust, sulphate, and smoke) show large temporal and spatial variability of the aerosol optical thickness over Europe. The least polluted region is the Iberian Peninsula, while the highest aerosol burdens occurred in Central Europe, mostly due to anthropogenic sulphate particles. Finally, the analysis of mineral dust transport shows frequent episodes of Saharan dust inflow over Central Europe. There are about 20 days a year (4 days in May) when instantaneous AOT associated with mineral dust aerosol increases over 0.1.     

Application of VLEACH to Vadose Zone Transport of VOCs at an Arizona Superfund Site

Cleanup standards for volatile organic compounds in thick vadose zones can be based on indirect risk (transport to ground water) when contamination is below depths of significant direct risk. At one Arizona Superfund site, a one-dimensional vadose zone transport model (VLE-ACH) was used to estimate the continued transport of VOCs from the vadose zone to ground water. VLEACH is a relatively simple and readily available model that proved useful for estimating indirect risk from VOCs in the vadose zone at this site. The estimates of total soil concentrations used as initial conditions for VLF.ACH incorporated a variety of data from the site. Soil gas concentrations were found to be more useful than soil matrix data for estimating total soil concentrations at this arid-zone site. A simple mixing cell model was used with the VLEACH-derived mass loading estimates from the vadose zone over time to estimate the resulting changes in ground water concentrations. For this site, the results of the linked VLEACH/mixing cell simulations indicate it is likely that the federal MCI. for TCE will be exceeded in underlying ground water if remedial action on I he vadose zone is not pursued.     

Aerosol optical thickness retrieval over the Atlantic Ocean using GOES imager data

An algorithm based on simulated satellite signal calculated by the 6S radiative transfer model has been developed in order to retrieve the aerosol optical thickness of dust over the Atlantic ocean. The algorithm is applied to the visible channel of Geostationary Operational Environmental Satellite (GOES 8) images. The inversion uses a look-up table giving the satellite signal intensity as a function of surface albedo, viewing geometry, solar illumination and the optical properties of the aerosols. The study consists of assessing the feasibility of monitoring and mapping the transport of suspended particles across the Atlantic from the Sahara to the Caribbean. The study area is between 10 and 25 N and 30 and 65 W. The optical thickness of aerosols has been calculated over a period of 11 days between 10th and 20th of June 1997 for the 14:15 UT GOES image acquisition. The calculated aerosol optical thickness ranges from 0.0 to 0.81 with an important event of dust presence occurring between 13th and 16th of June. The retrieved aerosol optical thickness is in good agreement with the values obtained between 14h UT and 15h UT from ground based sun photometer measurements on the island of Guadeloupe, and a coefficient correlation (R²) of 0.88 has been found between the data sets.