scholarly journals In situ measurements of near-surface hydraulic conductivity in engineered clay slopes

2018 ◽  
Vol 52 (1) ◽  
pp. 123-135 ◽  
Author(s):  
N. Dixon ◽  
C. J. Crosby ◽  
R. Stirling ◽  
P. N. Hughes ◽  
J. Smethurst ◽  
...  
Keyword(s):  
Hydraulic Conductivity ◽  
In Situ Measurements ◽  
Near Surface ◽  
Clay Slopes

scholarly journals Numerical simulation of extreme snow melt observed at the SIGMA-A site, northwest Greenland, during summer 2012

2015 ◽  
Vol 9 (1) ◽  
pp. 495-539
Author(s):  
M. Niwano ◽  
T. Aoki ◽  
S. Matoba ◽  
S. Yamaguchi ◽  
T. Tanikawa ◽  
...  
Keyword(s):  
Heat Flux ◽  
Grain Size ◽  
Latent Heat ◽  
Latent Heat Flux ◽  
In Situ Measurements ◽  
The Arctic ◽  
Snow Surface ◽  
Near Surface ◽  
Surface Snow

Abstract. The surface energy balance (SEB) from 30 June to 14 July 2012 at site SIGMA (Snow Impurity and Glacial Microbe effects on abrupt warming in the Arctic)-A, (78°03' N, 67°38' W; 1490 m a.s.l.) on the northwest Greenland Ice Sheet (GrIS) was investigated by using in situ atmospheric and snow measurements, as well as numerical modeling with a one-dimensional, multi-layered, physical snowpack model called SMAP (Snow Metamorphism and Albedo Process). At SIGMA-A, remarkable near-surface snowmelt and continuous heavy rainfall (accumulated precipitation between 10 and 14 July was estimated to be 100 mm) were observed after 10 July 2012. Application of the SMAP model to the GrIS snowpack was evaluated based on the snow temperature profile, snow surface temperature, surface snow grain size, and shortwave albedo, all of which the model simulated reasonably well. However, comparison of the SMAP-calculated surface snow grain size with in situ measurements during the period when surface hoar with small grain size was observed on-site revealed that it was necessary to input air temperature, relative humidity, and wind speed data from two heights to simulate the latent heat flux into the snow surface and subsequent surface hoar formation. The calculated latent heat flux was always directed away from the surface if data from only one height were input to the SMAP model, even if the value for roughness length of momentum was perturbed between the possible maximum and minimum values in numerical sensitivity tests. This result highlights the need to use two-level atmospheric profiles to obtain realistic latent heat flux. Using such profiles, we calculated the SEB at SIGMA-A from 30 June to 14 July 2012. Radiation-related fluxes were obtained from in situ measurements, whereas other fluxes were calculated with the SMAP model. By examining the components of the SEB, we determined that low-level clouds accompanied by a significant temperature increase played an important role in the melt event observed at SIGMA-A. These conditions induced a remarkable surface heating via cloud radiative forcing in the polar region.

scholarly journals Comparison of lidar-derived PM<sub>10</sub> with regional modeling and ground-based observations in the frame of MEGAPOLI experiment

2011 ◽  
Vol 11 (20) ◽  
pp. 10705-10726 ◽  
Author(s):  
P. Royer ◽  
P. Chazette ◽  
K. Sartelet ◽  
Q. J. Zhang ◽  
M. Beekmann ◽  
...  
Keyword(s):  
Mixed Boundary ◽  
Ground Level ◽  
In Situ Measurements ◽  
Percentage Error ◽  
Atmospheric Conditions ◽  
Transport Models ◽  
Near Surface ◽  
Lidar Measurements ◽  
Surface Measurements

Abstract. An innovative approach using mobile lidar measurements was implemented to test the performances of chemistry-transport models in simulating mass concentrations (PM10) predicted by chemistry-transport models. A ground-based mobile lidar (GBML) was deployed around Paris onboard a van during the MEGAPOLI (Megacities: Emissions, urban, regional and Global Atmospheric POLlution and climate effects, and Integrated tools for assessment and mitigation) summer experiment in July 2009. The measurements performed with this Rayleigh-Mie lidar are converted into PM10 profiles using optical-to-mass relationships previously established from in situ measurements performed around Paris for urban and peri-urban aerosols. The method is described here and applied to the 10 measurements days (MD). MD of 1, 15, 16 and 26 July 2009, corresponding to different levels of pollution and atmospheric conditions, are analyzed here in more details. Lidar-derived PM10 are compared with results of simulations from POLYPHEMUS and CHIMERE chemistry-transport models (CTM) and with ground-based observations from the AIRPARIF network. GBML-derived and AIRPARIF in situ measurements have been found to be in good agreement with a mean Root Mean Square Error RMSE (and a Mean Absolute Percentage Error MAPE) of 7.2 μg m−3 (26.0%) and 8.8 μg m−3 (25.2%) with relationships assuming peri-urban and urban-type particles, respectively. The comparisons between CTMs and lidar at ~200 m height have shown that CTMs tend to underestimate wet PM10 concentrations as revealed by the mean wet PM10 observed during the 10 MD of 22.4, 20.0 and 17.5 μg m−3 for lidar with peri-urban relationship, and POLYPHEMUS and CHIMERE models, respectively. This leads to a RMSE (and a MAPE) of 6.4 μg m−3 (29.6%) and 6.4 μg m−3 (27.6%) when considering POLYPHEMUS and CHIMERE CTMs, respectively. Wet integrated PM10 computed (between the ground and 1 km above the ground level) from lidar, POLYPHEMUS and CHIMERE results have been compared and have shown similar results with a RMSE (and MAPE) of 6.3 mg m−2 (30.1%) and 5.2 mg m−2 (22.3%) with POLYPHEMUS and CHIMERE when comparing with lidar-derived PM10 with periurban relationship. The values are of the same order of magnitude than other comparisons realized in previous studies. The discrepancies observed between models and measured PM10 can be explained by difficulties to accurately model the background conditions, the positions and strengths of the plume, the vertical turbulent diffusion (as well as the limited vertical model resolutions) and chemical processes as the formation of secondary aerosols. The major advantage of using vertically resolved lidar observations in addition to surface concentrations is to overcome the problem of limited spatial representativity of surface measurements. Even for the case of a well-mixed boundary layer, vertical mixing is not complete, especially in the surface layer and near source regions. Also a bad estimation of the mixing layer height would introduce errors in simulated surface concentrations, which can be detected using lidar measurements. In addition, horizontal spatial representativity is larger for altitude integrated measurements than for surface measurements, because horizontal inhomogeneities occurring near surface sources are dampened.

scholarly journals Ozone pollution during the COVID-19 lockdown in the spring 2020 over Europe analysed from satellite observations, in situ measurements and models

2021 ◽  
Author(s):  
Juan Cuesta ◽  
Lorenzo Costantino ◽  
Matthias Beekmann ◽  
Guillaume Siour ◽  
Laurent Menut ◽  
...  
Keyword(s):  
Large Scale ◽  
Transport Model ◽  
Surface Ozone ◽  
In Situ Measurements ◽  
Satellite Observations ◽  
Emission Inventories ◽  
Ozone Pollution ◽  
Chemistry Transport Model ◽  
Near Surface

Abstract. We present a comprehensive study integrating satellite observations of ozone pollution, in situ measurements and chemistry transport model simulations for quantifying the role of anthropogenic emission reductions during the COVID-19 lockdown in spring 2020 over Europe. Satellite observations are derived from the IASI+GOME2 multispectral synergism, which provides particularly enhanced sensitivity to near-surface ozone pollution. These observations are first analysed in terms of differences between the average on 1–15 April 2020, when the strictest lockdown restrictions took place, and the same period in 2019. They show clear enhancements of near-surface ozone in Central Europe and Northern Italy, and some other hotspots, which are typically characterized by VOC-limited chemical regimes. An overall reduction of ozone is observed elsewhere, where ozone chemistry is limited by the abundance of NOx. The spatial distribution of positive and negative ozone concentration anomalies observed from space is in relatively good quantitative agreement with surface in situ measurements over the continent (a correlation coefficient of 0.55, a root-mean-squared difference of 11 ppb and the same standard deviation and range of variability). An average bias of ∼8 ppb between the two observational datasets is remarked, which can partly be explained by the fact the satellite approach retrieves partial columns of ozone with a peak sensitivity above the surface (near 2 km of altitude). For assessing the impact of the reduction of anthropogenic emissions during the lockdown, we adjust the satellite and in situ surface observations for withdrawing the influence of meteorological conditions in 2020 and 2019. This adjustment is derived from the chemistry transport model simulations using the meteorological fields of each year and identical emission inventories. This observational estimate of the influence of lockdown emission reduction is consistent for both datasets. They both show lockdown-associated ozone enhancements in hotspots over Central Europe and Northern Italy, with a reduced amplitude with respect to the total changes observed between the two years, and an overall reduction elsewhere over Europe and the ocean. Satellite observations additionally highlight the ozone anomalies in the regions remote from in situ sensors, an enhancement over the Mediterranean likely associated with maritime traffic emissions and a marked large-scale reduction of ozone elsewhere over ocean (particularly over the North Sea), in consistency with previous assessments done with ozonesondes measurements in the free troposphere. These observational assessments are compared with model-only estimations, using the CHIMERE chemistry transport model. For analysing the uncertainty of the model estimates, we perform two sets of simulations with different setups, differing in the emission inventories, their modifications to account for changes in anthropogenic activities during the lockdown and the meteorological fields. Whereas a general qualitative consistency of positive and negative ozone anomalies is remarked between all model and observational estimates, significant changes are seen in their amplitudes. Models underestimate the range of variability of the ozone changes by at least a factor 2 with respect to the two observational data sets, both for enhancements and decreases of ozone, while the large-scale ozone decrease is not simulated. With one of the setups, the model simulates ozone enhancements a factor 3 to 6 smaller than with the other configuration. This is partly linked to the emission inventories of ozone precursors (at least a 30 % difference), but mainly to differences in vertical mixing of atmospheric constituents depending on the choice of the meteorological model.

scholarly journals Assessment of Soil Moisture Anomaly Sensitivity to Detect Drought Spatio-Temporal Variability in Romania

Sensors ◽  
2021 ◽  
Vol 21 (24) ◽  
pp. 8371
Author(s):  
Irina Ontel ◽  
Anisoara Irimescu ◽  
George Boldeanu ◽  
Denis Mihailescu ◽  
Claudiu-Valeriu Angearu ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Root Zone ◽  
Standardized Precipitation Index ◽  
In Situ Measurements ◽  
Near Surface ◽  
Soil Moisture Anomaly

This paper will assess the sensitivity of soil moisture anomaly (SMA) obtained from the Soil water index (SWI) product Metop ASCAT, to identify drought in Romania. The SWI data were converted from relative values (%) to absolute values (m3 m−3) using the soil porosity method. The conversion results (SM) were validated using soil moisture in situ measurements from ISMN at 5 cm depths (2015–2020). The SMA was computed based on a 10 day SWI product, between 2007 and 2020. The analysis was performed for the depths of 5 cm (near surface), 40 cm (sub surface), and 100 cm (root zone). The standardized precipitation index (SPI), land surface temperature anomaly (LST anomaly), and normalized difference vegetation index anomaly (NDVI anomaly) were computed in order to compare the extent and intensity of drought events. The best correlations between SM and in situ measurements are for the stations located in the Getic Plateau (Bacles (r = 0.797) and Slatina (r = 0.672)), in the Western Plain (Oradea (r = 0.693)), and in the Moldavian Plateau (Iasi (r = 0.608)). The RMSE were between 0.05 and 0.184. Furthermore, the correlations between the SMA and SPI, the LST anomaly, and the NDVI anomaly were significantly registered in the second half of the warm season (July–September). Due to the predominantly agricultural use of the land, the results can be useful for the management of water resources and irrigation in regions frequently affected by drought.

scholarly journals Comparison of the aerosol optical properties and size distribution retrieved by Sun photometer with in-situ measurements at mid-latitude

2016 ◽  
Author(s):  
Aurélien Chauvigné ◽  
Karine Sellegri ◽  
Maxime Hervo ◽  
Nadège Montoux ◽  
Patrick Freville ◽  
...  
Keyword(s):  
Remote Sensing ◽  
In Situ Measurements ◽  
The Sun ◽  
Size Distributions ◽  
Particle Size Distributions ◽  
Near Surface ◽  
Atmospheric Column ◽  
Fine Mode ◽  
Sun Photometer

Abstract. Aerosols influence the Earth radiative budget through scattering and absorption of solar radiation. Several methods are used to investigate aerosol properties and thus quantify their direct and indirect impacts on climate. At the Puy de Dôme station, continuous high altitude near surface in-situ measurements and low altitude ground-based remote sensing atmospheric column measurements give the opportunity to compare the aerosol extinction measured with both methods over a one year period. To our knowledge, it is the first time that such a comparison is realized with continuous measurements of a high altitude site during a long term period. This comparison addresses to which extend near surface in-situ measurements are representative of the whole atmospheric column, the aerosol Mixing Layer (ML), or the Free Troposphere (FT). In particular, the impact of multi aerosol layers events detected using LIDAR backscatter profiles is analysed. A good correlation between in-situ aerosol extinction coefficient and Aerosol Optical Depth (AOD) measured by the Aerosol Robotic Network (AERONET) Sun photometer is observed with a correlation coefficient around 0.80, indicating that the in-situ measurements station is representative of the overall atmospheric column. After filtering for multilayer cases and correcting for each layer optical contribution (ML and FT), the atmospheric structure seems to be the main factor influencing the comparison between the two measurement techniques. When the site lies in the ML, the in-situ extinction represents 45 % of the Sun photometer ML extinction while when the site lies within the FT, the in-situ extinction is more than two times higher than the FT Sun photometer extinction. Remote sensing retrievals of the aerosol particle size distributions (PSD) from the Sun photometer observations are then compared to the near surface in-situ measurements, at dry and at ambient relative humidities. When in-situ measurements are considered at dry state, the in-situ fine mode diameters are 44 % higher than the Sun photometer-retrieved diameters and in-situ volume concentrations are 20 % lower than of the Sun photometer-retrieved fine mode concentration. Using a parametrised hygroscopic growth factor applied to aerosol diameters, the difference between in-situ and retrieved diameters grows larger. Coarse mode in-situ diameter and concentrations show a good correlation with retrieved particle size distributions from remote sensing.

scholarly journals Comparison of the aerosol optical properties and size distribution retrieved by sun photometer with in situ measurements at midlatitude

2016 ◽  
Vol 9 (9) ◽  
pp. 4569-4585 ◽  
Author(s):  
Aurélien Chauvigné ◽  
Karine Sellegri ◽  
Maxime Hervo ◽  
Nadège Montoux ◽  
Patrick Freville ◽  
...  
Keyword(s):  
Remote Sensing ◽  
High Altitude ◽  
In Situ Measurements ◽  
Aerosol Extinction ◽  
The Sun ◽  
Near Surface ◽  
Atmospheric Column ◽  
Fine Mode ◽  
Sun Photometer

Abstract. Aerosols influence the Earth radiative budget through scattering and absorption of solar radiation. Several methods are used to investigate aerosol properties and thus quantify their direct and indirect impacts on climate. At the Puy de Dôme station, continuous high-altitude near-surface in situ measurements and low-altitude ground-based remote sensing atmospheric column measurements give the opportunity to compare the aerosol extinction measured with both methods over a 1-year period. To our knowledge, it is the first time that such a comparison is realised with continuous measurements of a high-altitude site during a long-term period. This comparison addresses to which extent near-surface in situ measurements are representative of the whole atmospheric column, the aerosol mixing layer (ML) or the free troposphere (FT). In particular, the impact of multi-aerosol layers events detected using lidar backscatter profiles is analysed. A good correlation between in situ aerosol extinction coefficient and aerosol optical depth (AOD) measured by the Aerosol Robotic Network (AERONET) sun photometer is observed with a correlation coefficient around 0.80, indicating that the in situ measurements station is representative of the overall atmospheric column. After filtering for multilayer cases and correcting for each layer optical contribution (ML and FT), the atmospheric structure seems to be the main factor influencing the comparison between the two measurement techniques. When the site lies in the ML, the in situ extinction represents 45 % of the sun photometer ML extinction while when the site lies within the FT, the in situ extinction is more than 2 times higher than the FT sun photometer extinction. Moreover, the assumption of a decreasing linear vertical aerosol profile in the whole atmosphere has been tested, significantly improving the instrumental agreement. Remote sensing retrievals of the aerosol particle size distributions (PSDs) from the sun photometer observations are then compared to the near-surface in situ measurements, at dry and at ambient relative humidities. When in situ measurements are considered at dry state, the in situ fine mode diameters are 44 % higher than the sun-photometer-retrieved diameters and in situ volume concentrations are 20 % lower than those of the sun-photometer-retrieved fine mode concentration. Using a parameterised hygroscopic growth factor applied to aerosol diameters, the difference between in situ and retrieved diameters grows larger. Coarse mode in situ diameters and concentrations show a good correlation with retrieved PSDs from remote sensing.

scholarly journals Salinity variability in satellite subpixels: impact on satellite in-situ comparisons.

2021 ◽  
Author(s):  
Clovis Thouvenin-Masson ◽  
Jacqueline Boutin ◽  
Jean-Luc Vergely ◽  
Dimitry Khvorostyanov ◽  
Xavier Perrot ◽  
...  
Keyword(s):  
Sampling Error ◽  
In Situ Measurements ◽  
Global Ocean ◽  
Small Scale ◽  
Two Dimensional ◽  
Surface Salinity ◽  
Near Surface ◽  
One Dimensional ◽  
Ship Tracks

&lt;p&gt;Sea Surface Salinity (SSS) are retrieved from SMOS and SMAP L-band radiometers at a spatial resolution of about 50km.&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;&lt;p&gt;Traditionally, satellite SSS products validation is based on comparisons with in-situ near surface salinity measurements.&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;&lt;p&gt;In-situ measurements are performed on moorings, argo floats and along ship tracks[JB1]&amp;#160;, which provide punctual or one-dimensional (along ship tracks) estimations of the SSS.&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;&lt;p&gt;The sampling difference between one-dimensional or punctual in-situ measurements and two-dimensional satellite products results in a sampling error that must be separated from measurement errors for the validation of satellite products.&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;&lt;p&gt;We use a small-scale resolution field (1/12&amp;#176; Mercator Global Ocean Physics Analysis and Forecast) to estimate the expected sampling error of each kind of in-situ measurements, by comparing punctual, [JB2]&amp;#160;one-dimensional and two-dimensional SSS variability.&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;&lt;p&gt;The better understanding of sampling errors allows a more accurate validation of satellite SSS and of the errors estimated by satellite retrieval algorithms. The improvement is quantified by considering the standard deviation of satellite minus in-situ salinities differences normalized by the sampling and retrieval errors. This quantity should be equal to one if all the error contributions are correctly considered. This methodology will be applied to SMOS SSS and to merged SMOS and SMAP SSS products.&lt;/p&gt;

Ground-based in situ measurements of near-surface aerosol mass concentration over Anantapur: Heterogeneity in source impacts

2012 ◽  
Vol 30 (1) ◽  
pp. 235-246 ◽  
Author(s):  
B. S. K. Reddy ◽  
K. R. Kumar ◽  
G. Balakrishnaiah ◽  
K. R. Gopal ◽  
R. R. Reddy ◽  
...  
Keyword(s):  
Mass Concentration ◽  
In Situ Measurements ◽  
Near Surface ◽  
Aerosol Mass ◽  
Aerosol Mass Concentration
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