scholarly journals Spatial distribution of melt‐season cloud radiative effects over Greenland: Evaluating satellite observations, reanalyses, and model simulations against in situ measurements

Author(s):  
Wenshan Wang ◽  
Charles S. Zender ◽  
Dirk van As ◽  
Nathaniel B. Miller
2018 ◽  
Author(s):  
Anne Wiese ◽  
Joanna Staneva ◽  
Johannes Schultz-Stellenfleth ◽  
Arno Behrens ◽  
Luciana Fenoglio-Marc ◽  
...  

Abstract. In this study, the quality of wind and wave data provided by the new Sentinel-3A satellite is evaluated. We focus on coastal areas, where altimeter data are of lower quality than those for the open ocean. The satellite data of Sentinel-3A, Jason-2 and CryoSat-2 are assessed in a comparison with in situ measurements and spectral wave model (WAM) simulations. The sensitivity of the wave model to wind forcing is evaluated using data with different temporal and spatial resolution, such as ERA-Interim and ERA5 reanalyses, ECMWF operational analysis and short-range forecasts, German Weather Service (DWD) forecasts and regional atmospheric model simulations -coastDat. Numerical simulations show that both the wave model forced using the ERA5 reanalyses and that forced using the ECMWF operational analysis/forecast demonstrate the best capability over the whole study period, as well as during extreme events. To further estimate the variance of the significant wave height of ensemble members for different wind forcings, especially during extreme events, an empirical orthogonal function (EOF) analysis is performed. Intercomparisons between remote sensing and in situ observations demonstrate that the overall quality of the former is good over the North Sea and Baltic Sea throughout the study period, although the significant wave heights estimated based on satellite data tend to be greater than the in situ measurements by 7 cm to 26 cm. The quality of all satellite data near the coastal area decreases; however, within 10 km off the coast, Sentinel-3A performs better than the other two satellites. Analyses in which data from satellite tracks are separated in terms of onshore and offshore flights have been carried out. No substantial differences are found when comparing the statistics for onshore and offshore flights. Moreover, no substantial differences are found between satellite tracks under various metocean conditions. Furthermore, the satellite data quality does not depend on the wind direction relative to the flight direction. Thus, the quality of the data obtained by the new Sentinel-3A satellite over coastal areas is improved compared to that of older satellites.


Geoderma ◽  
2020 ◽  
Vol 378 ◽  
pp. 114617
Author(s):  
Chenyang Xu ◽  
John J. Qu ◽  
Xianjun Hao ◽  
Zhiliang Zhu ◽  
Laurel Gutenberg

2010 ◽  
Vol 10 (2) ◽  
pp. 3173-3187
Author(s):  
T. Warneke ◽  
A. K. Petersen ◽  
C. Gerbig ◽  
A. Jordan ◽  
C. Rödenbeck ◽  
...  

Abstract. The first ground-based remote sensing measurements of the column averaged volume mixing ratio of CO2 (XCO2) for the inner tropics have been obtained at Paramaribo, Suriname (5.8° N, 55.2° W). The remote sensing observations are complemented by surface air-samples collected at the site, analyzed for CO2 and 13CO2. The surface in-situ measurements are strongly influenced by local sources. From the isotopic composition of the air samples the local source component is suggested to be dominated by the terrestrial biosphere. Using δ13C from the NOAA/ESRL stations Ascension Is. (ASC), 7.9° S, 14.4° W, and Ragged Point (RPB), 7.9° S, 14.4° W, the data has been corrected for the local source component. Due to the migration of the ITCZ over the measurement site the probed air masses belong to the Northern or Southern Hemisphere depending on the time of the year. Comparison to analyzed CO2 fields based on TM3 model simulations using optimized fluxes indicate agreement for XCO2 as well as for the corrected CO2 mixing ratios at the surface for the long dry season, when Paramaribo belongs to the Southern Hemisphere. A slightly worse agreement during the short dry season is attributed to a larger representation error during this time of the year. Overall the comparison demonstrates that the TM3 model is capable to simulate surface concentrations as well as column densities of CO2 correctly at the same location.


2021 ◽  
Author(s):  
Juan Cuesta ◽  
Lorenzo Costantino ◽  
Matthias Beekmann ◽  
Guillaume Siour ◽  
Laurent Menut ◽  
...  

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.


2019 ◽  
Author(s):  
Khalil Yala ◽  
Ndeye Niang ◽  
Julien Brajard ◽  
Carlos Mejia ◽  
Mory Ouattara ◽  
...  

Abstract. We processed daily ocean-color satellite observations to construct a monthly climatology of phytoplankton pigment concentrations in the Senegalo-Mauritanian region. Thanks to the difficulty of the problem, we proposed a new method. It primarily consists in associating, in well-identified clusters, similar pixels in terms of ocean-color parameters and in situ pigment concentrations taken from a global ocean database. The association is carried using a new Self Organized Map (2S-SOM). Its major advantage is to allow taking into account the specificity of the optical properties of the water by adding specific weights to the different ocean color parameters and the in situ measurements. In the retrieval phase, the pigment concentration of a pixel is estimated by taking the pigment concentration values associated with the 2S-SOM cluster presenting the ocean-color satellite spectral measurements, which are the closest to those of the pixel under study according to some distance. The method was validated by using a cross-validation procedure. We focused our study on the fucoxanthin concentration, which is related to the abundance of diatoms. We showed that the fucoxanthin starts to develop in December, presents its maximum intensity in March when the upwelling intensity is maximum, extends up to the coast of Guinea in April and begins to decrease in May. The results are in agreement with previous observations and recent in situ measurements. The method is very general and can be applied in every oceanic region.


2021 ◽  
Author(s):  
Anna Derkacheva ◽  
Fabien Gillet-Chaulet ◽  
Jeremie Mouginot

<p>Greenland’s future response to climate change will be determined partly by various phenomena controlling ice flow. For the land-terminating sectors, the water lubricating the glacier's base is considered as a major control on the ice motion. For instance, the seasonal modulations of water input induced by summer melt can cause glacier speed-up up to +200-300% compared to the winter mean. Thus, a comprehensive understanding of variations in the basal conditions, which are at the origin of the glacier flow fluctuations, plays a key role for the climate projections.</p><p>While the in-situ measurements stay a local and hard approach to investigate the basal conditions, ice flow modeling offers the possibility to invert for them over the large area based on observations of surface glacier speed and topography. During the last decade, the number of available satellite observations has increased significantly, allowing for far more frequent measurements of the glacier speed and precise reconstruction of the seasonal fluctuations. Here, we investigate the possibility of applying this satellite-derived time-series of surface ice velocity to reconstruct the annual behavior of the basal conditions with 2 weeks temporal resolution using an ice flow model.</p><p>The area of this study is Russell glacier located on the southwest coast of Greenland. A time series of surface velocity dataset was created by merging measurements from Sentinel-1&2 and Landsat-8, covering an area up to 100 km inland with 150 m/pix spatial resolution and 2-weeks temporal resolution (Derkacheva et al. 2020). The 3D Full-Stokes ice flow model Elmer/Ice is used to invert for the effective basal friction coefficient for each time step.  Usage of a friction law that has been derived for hard beds (Gagliardini et al., 2007) allows to constrain the variation of the basal effective pressure. Overall, the results from the model inversions give access to the evolution of the basal ice speed, friction, effective and water pressure, floatation fraction throughout a complete year. The results are compared with in-situ measurements in terms of absolute values and show a good agreement. The impact of the flow model setup, regularization, assumptions for the ice rheology, and the impact of noise in the speed data are also examined and compared with in-situ measurements.</p>


2020 ◽  
Author(s):  
Jana Handschuh ◽  
Frank Baier ◽  
Thilo Erbertseder ◽  
Martijn Schaap

<p>Particulate matter and other air pollutants have become an increasing burden on the environment and human health. Especially in metropolitan and high-traffic areas, air quality is often remarkably reduced. For a better understanding of the air quality in specific areas, which is of great environment-political interest, data with high resolution in space and time is required. The combination of satellite observations and chemistry-transport-modelling has proven to give a good database for assessments and analyses of air pollution. In contrast to sample in-situ measurements, satellite observations provide area-wide coverage ​​of measurements and thus the possibility for an almost gapless mapping of actual air pollutants. For a high temporal resolution, chemistry-transport-models are needed, which calculate concentrations of specific pollutants in continuous time steps. Satellite observations can thus be used to improve model performances.</p><p>There are no direct satellite-measurements of fine particulate matter (PM2.5) but ground-level concentrations of PM2.5 can be derived from optical parameters such as aerosol optical depth (AOD). A wide range of methods for the determination of PM2.5 concentrations from AOD measurements has been developed so far, but it is still a big challenge. In this study a semi-empirical approach based on the physical relationships between meteorological and optical parameters was applied to determine a first-guess of ground-level PM2.5 concentrations for the year 2018 and the larger Germany region. Therefor AOD observations of MODIS (Moderate Resolution Imaging Spectroradiometer) aboard the NASA Aqua satellite were used in a spatial resolution of 3km. First results showed an overestimation of ground-level aerosols and quiet low correlations with in-situ station measurements from the European Environmental Agency (EEA). To improve the results, correction factors were calculated using the coefficients of linear regression between satellite-based and in-situ measured particulate matter concentrations. Spatial and seasonal dependencies were taken into account with it. Correlations between satellite and in-situ measurements could be improved applying this method.</p><p>The MODIS 3km AOD product was found to be a good base for area-wide calculations of ground-level PM2.5 concentrations. First comparisons to the calculated PM2.5 concentrations from chemistry-transport-model POLYPHEMUS/DLR showed significant differences though. Satellite observations will now be used to improve the general model performance, first by helping to find and understand regional and temporal dependencies in the differences. As part of the German project S-VELD funded by the Federal Ministry of Transport and Digital Infrastructure BMVI, it will help for example to adjust the derivation of particle emissions within the model.</p>


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