scholarly journals Quantification and mitigation of the impact of scene inhomogeneity on Sentinel-4 UVN UV-VIS retrievals

2012 ◽  
Vol 5 (2) ◽  
pp. 2043-2075
Author(s):  
S. Noël ◽  
K. Bramstedt ◽  
H. Bovensmann ◽  
J. P. Burrows ◽  
C. Standfuss ◽  
...  
Keyword(s):  
Optimal Estimation ◽  
Maximum Error ◽  
The Other ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Imaging Spectrometer ◽  
Wavelength Calibration ◽  
Data Products ◽  
Tropospheric O3 ◽  
The Impact

Abstract. The quality of trace gas products derived from measurements of a space-borne imaging spectrometer is affected by the inhomogeneity of the illumination of the instrument slit and thus by the heterogeneity of the observed scene. This paper aims to quantify this effect and summarise findings on how to mitigate the impact of inhomogeneous slit illumination on tropospheric O3, NO2, SO2 and HCHO columns derived from measurements of the Sentinel-4 UVN imaging spectrometer. For this purpose, spectra for inhomogeneous ground scenes have been simulated based on a combination of a radiative transfer model and spatially high resolved MODIS (Moderate Resolution Imaging Spectroradiometer) data. The resulting errors on tropospheric O3, NO2, SO2 and HCHO columns derived from these spectra have been determined via an optimal estimation approach. It could be concluded that inhomogeneous illumination results in significant errors in the data products if the natural inhomogeneity of the observed scenes is not accounted for. O3 columns are less affected than the other data products; largest errors occur for NO2 (mean absolute errors about 5%, maximum error exceeding 50%). These errors may be significantly reduced (by factors up to >10) by an appropriate wavelength calibration applied individually to each Earthshine radiance spectrum. With wavelength calibration the estimated mean absolute errors due to inhomogeneity are for all gases well below 1%; maximum errors are about 10% for NO2 and around 5% for the other gases.

scholarly journals Quantification and mitigation of the impact of scene inhomogeneity on Sentinel-4 UVN UV-VIS retrievals

2012 ◽  
Vol 5 (6) ◽  
pp. 1319-1331 ◽  
Author(s):  
S. Noël ◽  
K. Bramstedt ◽  
H. Bovensmann ◽  
K. Gerilowski ◽  
J. P. Burrows ◽  
...  
Keyword(s):  
Optimal Estimation ◽  
Maximum Error ◽  
The Other ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Imaging Spectrometer ◽  
Wavelength Calibration ◽  
Data Products ◽  
Tropospheric O3 ◽  
The Impact

Abstract. The quality of trace gas products derived from measurements of a space-borne imaging spectrometer is affected by the inhomogeneity of the illumination of the instrument slit and thus by the heterogeneity of the observed scene. This paper aims to quantify this effect and summarise findings on how to mitigate the impact of inhomogeneous slit illumination on tropospheric O3, NO2, SO2 and HCHO columns derived from measurements of the Sentinel-4 UVN imaging spectrometer. For this purpose, spectra for inhomogeneous ground scenes have been simulated based on a combination of a radiative transfer model and spatially high resolved MODIS (Moderate Resolution Imaging Spectroradiometer) data. The resulting errors on tropospheric O3, NO2, SO2 and HCHO columns derived from these spectra have been determined via an optimal estimation approach. We conclude that inhomogeneous illumination results in significant errors in the data products if the natural inhomogeneity of the observed scenes are not accounted for. O3 columns are less affected than the other data products; largest errors occur for NO2 (mean absolute errors about 5%, maximum error exceeding 50%, standard deviation of the errors about 8%). These errors may be significantly reduced (by factors up to about 10) by an appropriate wavelength calibration applied individually to each Earthshine radiance spectrum. With wavelength calibration the estimated mean absolute errors due to inhomogeneity are for all gases well below 1%; standard deviations of the errors are 1.5% or lower; maximum errors are about 10% for NO2 and around 5% for the other gases.

scholarly journals Global stratospheric aerosol extinction profile retrievals from SCIAMACHY limb-scatter observations

2012 ◽  
Vol 5 (4) ◽  
pp. 5993-6035 ◽  
Author(s):  
F. Ernst ◽  
C. von Savigny ◽  
A. Rozanov ◽  
V. Rozanov ◽  
K.-U. Eichmann ◽  
...  
Keyword(s):  
Surface Albedo ◽  
Optimal Estimation ◽  
Stratospheric Aerosol ◽  
Visible Spectral Range ◽  
Radiative Transfer Model ◽  
Retrieval Algorithm ◽  
Transfer Model ◽  
Aerosol Extinction ◽  
Index Approach ◽  
The Impact

Abstract. Stratospheric aerosol extinction profiles are retrieved from SCIAMACHY/Envisat limb-scatter observations in the visible spectral range. The retrieval algorithm is based on a colour-index approach using the normalized limb-radiance profiles at 470 nm and 750 nm wavelength. The optimal estimation approach in combination with the radiative transfer model SCIATRAN is employed for the retrievals. This study presents a detailed description of the retrieval algorithm, and a sensitivity analysis investigating the impact of the most important parameters that affect the aerosol extinction profile retrieval accuracy. It is found that the parameter with the largest impact is surface albedo, particularly for SCIAMACHY observations in the Southern Hemisphere where the error in stratospheric aerosol extinction can be up to 50% if the surface albedo is not well known. The effect of errors in the assumed ozone and neutral density profiles on the aerosol profile retrievals is with generally less than 6% relatively small. The aerosol extinction profiles retrieved from SCIAMACHY are compared with co-located SAGE II solar occultation measurements of stratospheric aerosol extinction during the period 2003–2005. The mean aerosol extinction profiles averaged over all co-locations agree to within 20% between 15 and 35 km altitude. However, larger differences are observed at specific latitudes.

scholarly journals Quantifying the impact of aerosol scattering on the retrieval of methane from airborne remote sensing measurements

2020 ◽  
Author(s):  
Yunxia Huang ◽  
Vijay Natraj ◽  
Zhaocheng Zeng ◽  
Yuk L. Yung
Keyword(s):  
Remote Sensing ◽  
Infrared Imaging ◽  
Matched Filter ◽  
Optimal Estimation ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Atmospheric Methane ◽  
Ch4 Emissions ◽  
Aerosol Scattering ◽  
The Impact

Abstract. As a greenhouse gas with strong global warming potential, atmospheric methane (CH4) emissions have attracted a great deal of attention. Remote sensing measurements can provide information about CH4 sources and emissions. However, accurate assessment of CH4 emissions is challenging due to the influence of aerosol scattering in the atmosphere. In this study, imaging spectroscopic measurements from the Airborne Visible/Infrared Imaging Spectrometer–Next Generation (AVIRIS-NG) in the short-wave infrared are used to analyze the impact of aerosol scattering on CH4 retrievals. Using a numerically efficient two-stream-exact-single-scattering radiative transfer model, we also simulate AVIRIS-NG measurements for different scenarios and quantify the impact of aerosol scattering using two retrieval techniques – the traditional Matched Filter (MF) method and the Optimal Estimation (OE) method, which is a popular approach for trace gas retrievals. The results show that the MF method exhibits up to 50 % lower fractional retrieval bias compared to the OE method at high CH4 concentrations (> 100 % enhancement over typical background values) and is suitable for detecting strong CH4 emissions, while the OE method is an optimal technique for diffuse sources (

scholarly journals The impact of residential combustion emissions on atmospheric aerosol, human health, and climate

2016 ◽  
Vol 16 (2) ◽  
pp. 873-905 ◽  
Author(s):  
E. W. Butt ◽  
A. Rap ◽  
A. Schmidt ◽  
C. E. Scott ◽  
K. J. Pringle ◽  
...  
Keyword(s):  
Eastern Europe ◽  
Human Health ◽  
Atmospheric Aerosol ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
So2 Emissions ◽  
Residential Sector ◽  
Residential Combustion ◽  
Combustion Emissions ◽  
The Impact

Abstract. Combustion of fuels in the residential sector for cooking and heating results in the emission of aerosol and aerosol precursors impacting air quality, human health, and climate. Residential emissions are dominated by the combustion of solid fuels. We use a global aerosol microphysics model to simulate the impact of residential fuel combustion on atmospheric aerosol for the year 2000. The model underestimates black carbon (BC) and organic carbon (OC) mass concentrations observed over Asia, Eastern Europe, and Africa, with better prediction when carbonaceous emissions from the residential sector are doubled. Observed seasonal variability of BC and OC concentrations are better simulated when residential emissions include a seasonal cycle. The largest contributions of residential emissions to annual surface mean particulate matter (PM2.5) concentrations are simulated for East Asia, South Asia, and Eastern Europe. We use a concentration response function to estimate the human health impact due to long-term exposure to ambient PM2.5 from residential emissions. We estimate global annual excess adult (>  30 years of age) premature mortality (due to both cardiopulmonary disease and lung cancer) to be 308 000 (113 300–497 000, 5th to 95th percentile uncertainty range) for monthly varying residential emissions and 517 000 (192 000–827 000) when residential carbonaceous emissions are doubled. Mortality due to residential emissions is greatest in Asia, with China and India accounting for 50 % of simulated global excess mortality. Using an offline radiative transfer model we estimate that residential emissions exert a global annual mean direct radiative effect between −66 and +21 mW m−2, with sensitivity to the residential emission flux and the assumed ratio of BC, OC, and SO2 emissions. Residential emissions exert a global annual mean first aerosol indirect effect of between −52 and −16 mW m−2, which is sensitive to the assumed size distribution of carbonaceous emissions. Overall, our results demonstrate that reducing residential combustion emissions would have substantial benefits for human health through reductions in ambient PM2.5 concentrations.

scholarly journals Analysis of actinic flux profiles measured from an ozonesonde balloon

2015 ◽  
Vol 15 (8) ◽  
pp. 4131-4144 ◽  
Author(s):  
P. Wang ◽  
M. Allaart ◽  
W. H. Knap ◽  
P. Stammes
Keyword(s):  
Atmospheric Chemistry ◽  
Low Cost ◽  
Green Light ◽  
Single Layer ◽  
Radiative Transfer Model ◽  
Cloud Base ◽  
Transfer Model ◽  
Actinic Flux ◽  
Clear Sky ◽  
The Impact

Abstract. A green light sensor has been developed at KNMI to measure actinic flux profiles using an ozonesonde balloon. In total, 63 launches with ascending and descending profiles were performed between 2006 and 2010. The measured uncalibrated actinic flux profiles are analysed using the Doubling–Adding KNMI (DAK) radiative transfer model. Values of the cloud optical thickness (COT) along the flight track were taken from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) Cloud Physical Properties (CPP) product. The impact of clouds on the actinic flux profile is evaluated on the basis of the cloud modification factor (CMF) at the cloud top and cloud base, which is the ratio between the actinic fluxes for cloudy and clear-sky scenes. The impact of clouds on the actinic flux is clearly detected: the largest enhancement occurs at the cloud top due to multiple scattering. The actinic flux decreases almost linearly from cloud top to cloud base. Above the cloud top the actinic flux also increases compared to clear-sky scenes. We find that clouds can increase the actinic flux to 2.3 times the clear-sky value at cloud top and decrease it to about 0.05 at cloud base. The relationship between CMF and COT agrees well with DAK simulations, except for a few outliers. Good agreement is found between the DAK-simulated actinic flux profiles and the observations for single-layer clouds in fully overcast scenes. The instrument is suitable for operational balloon measurements because of its simplicity and low cost. It is worth further developing the instrument and launching it together with atmospheric chemistry composition sensors.

scholarly journals Data-Driven Localization Mappings in Filtering the Monsoon–Hadley Multicloud Convective Flows

2018 ◽  
Vol 146 (4) ◽  
pp. 1197-1218
Author(s):  
Michèle De La Chevrotière ◽  
John Harlim
Keyword(s):  
Learning Algorithm ◽  
Data Driven ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Model Errors ◽  
Accurate Analysis ◽  
Perfect Model ◽  
Nonlinear Stochastic Model ◽  
Correlation Statistics ◽  
The Impact

This paper demonstrates the efficacy of data-driven localization mappings for assimilating satellite-like observations in a dynamical system of intermediate complexity. In particular, a sparse network of synthetic brightness temperature measurements is simulated using an idealized radiative transfer model and assimilated to the monsoon–Hadley multicloud model, a nonlinear stochastic model containing several thousands of model coordinates. A serial ensemble Kalman filter is implemented in which the empirical correlation statistics are improved using localization maps obtained from a supervised learning algorithm. The impact of the localization mappings is assessed in perfect-model observing system simulation experiments (OSSEs) as well as in the presence of model errors resulting from the misspecification of key convective closure parameters. In perfect-model OSSEs, the localization mappings that use adjacent correlations to improve the correlation estimated from small ensemble sizes produce robust accurate analysis estimates. In the presence of model error, the filter skills of the localization maps trained on perfect- and imperfect-model data are comparable.

The impact of time-dependent stellar activity on the atmospheric chemistry and observability of exoplanets

2021 ◽  
Author(s):  
Amy Louca ◽  
Yamila Miguel ◽  
Shang-Min Tsai
Keyword(s):  
Atmospheric Chemistry ◽  
Emission Spectra ◽  
Time Dependent ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Stellar Spectrum ◽  
Stellar Spectra ◽  
Chemical Tracers ◽  
Atmospheric Escape ◽  
The Impact

<p class="p1">Observations of exoplanets used to characterize the chemistry and dynamics of atmospheres have developed considerably throughout the years. Nonetheless, it remains a difficult task to give a full and detailed description using solely observations. With future space missions such as JWST and ARIEL, both expected to be launched within this decade, it becomes even more crucial to be able to fully explain and predict the underlying chemistry and physics involved. In this research, we focus on modeling star-planet interactions by using synthetic flare spectra to predict chemical tracers for future missions. We make use of a chemical kinetics code that includes synthetic time-dependent stellar spectra and thermal atmospheric escape to simulate the atmospheres of known exoplanets. Using a radiative transfer model we then retrieve emission spectra. This ongoing study is focused on various known planetary systems of which the stellar spectrum has been obtained by the (mega-)MUSCLES collaboration. Preliminary results on these systems show that stellar flares and thermal escape can have a significant effect on the chemistry in atmospheres. </p>

scholarly journals Characterization of aerosol hygroscopicity using Raman lidar measurements at the EARLINET station of Payerne

2019 ◽  
Vol 19 (18) ◽  
pp. 11651-11668 ◽  
Author(s):  
Francisco Navas-Guzmán ◽  
Giovanni Martucci ◽  
Martine Collaud Coen ◽  
María José Granados-Muñoz ◽  
Maxime Hervo ◽  
...  
Keyword(s):  
Lower Troposphere ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Raman Lidar ◽  
Hygroscopic Growth ◽  
Backscatter Coefficient ◽  
Radiative Balance ◽  
First Case ◽  
The Impact ◽  
Aerosol Hygroscopicity

Abstract. This study focuses on the analysis of aerosol hygroscopicity using remote sensing techniques. Continuous observations of aerosol backscatter coefficient (βaer), temperature (T) and water vapor mixing ratio (r) have been performed by means of a Raman lidar system at the aerological station of MeteoSwiss at Payerne (Switzerland) since 2008. These measurements allow us to monitor in a continuous way any change in aerosol properties as a function of the relative humidity (RH). These changes can be observed either in time at a constant altitude or in altitude at a constant time. The accuracy and precision of RH measurements from the lidar have been evaluated using the radiosonde (RS) technique as a reference. A total of 172 RS profiles were used in this intercomparison, which revealed a bias smaller than 4 % RH and a standard deviation smaller than 10 % RH between both techniques in the whole (in lower) troposphere at nighttime (at daytime), indicating the good performance of the lidar for characterizing RH. A methodology to identify situations favorable to studying aerosol hygroscopicity has been established, and the aerosol hygroscopicity has been characterized by means of the backscatter enhancement factor (fβ). Two case studies, corresponding to different types of aerosol, are used to illustrate the potential of this methodology. The first case corresponds to a mixture of rural aerosol and smoke particles (smoke mixture), which showed a higher hygroscopicity (fβ355=2.8 and fβ1064=1.8 in the RH range 73 %–97 %) than the second case, in which mineral dust was present (fβ355=1.2 and fβ1064=1.1 in the RH range 68 %–84 %). The higher sensitivity of the shortest wavelength to hygroscopic growth was qualitatively reproduced using Mie simulations. In addition, a good agreement was found between the hygroscopic analysis done in the vertical and in time for Case I, where the latter also allowed us to observe the hydration and dehydration of the smoke mixture. Finally, the impact of aerosol hygroscopicity on the Earth's radiative balance has been evaluated using the GAME (Global Atmospheric Model) radiative transfer model. The model showed an impact with an increase in absolute value of 2.4 W m−2 at the surface with respect to the dry conditions for the hygroscopic layer of Case I (smoke mixture).

scholarly journals Cloud sensitivity studies for stratospheric and lower mesospheric ozone profile retrievals from measurements of limb-scattered solar radiation

2009 ◽  
Vol 2 (2) ◽  
pp. 653-678 ◽  
Author(s):  
T. Sonkaew ◽  
V. V. Rozanov ◽  
C. von Savigny ◽  
A. Rozanov ◽  
H. Bovensmann ◽  
...  
Keyword(s):  
Solar Radiation ◽  
Relative Error ◽  
Optical Thickness ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Absorption Bands ◽  
Ozone Profile ◽  
Mesospheric Ozone ◽  
Cloud Optical Thickness ◽  
The Impact

Abstract. Clouds in the atmosphere play an important role in reflection, absorption and transmission of solar radiation and thus affect trace gas retrievals. The main goal of this paper is to examine the sensitivity of stratospheric and lower mesospheric ozone retrievals from limb-scattered radiance measurements to clouds using the SCIATRAN radiative transfer model and retrieval package. The retrieval approach employed is optimal estimation, and the considered clouds are vertically and horizontally homogeneous. Assuming an aerosol-free atmosphere and Mie phase functions for cloud particles, we compute the relative error of ozone profile retrievals in a cloudy atmosphere if clouds are neglected in the retrieval. To access altitudes from the lower stratosphere up to the lower mesosphere, we combine the retrievals in the Chappuis and Hartley ozone absorption bands. We find significant cloud sensitivity of the limb ozone retrievals in the Chappuis bands at lower stratospheric altitudes. The relative error in the retrieved ozone concentrations gradually decreases with increasing altitude and becomes negligible above approximately 40 km. The parameters with the largest impact on the ozone retrievals are cloud optical thickness, ground albedo and solar zenith angle. Clouds with different geometrical thicknesses or different cloud altitudes have a similar impact on the ozone retrievals for a given cloud optical thickness value, if the clouds are outside the field of view of the instrument. The effective radius of water droplets has a small influence on the error, i.e., less than 0.5% at altitudes above the cloud top height. Furthermore, the impact of clouds on the ozone profile retrievals was found to have a rather small dependence on the solar azimuth angle (less than 1% for all possible azimuth angles). For the most frequent cloud types, the total error is below 6% above 15 km altitude, if clouds are completely neglected in the retrieval. Neglecting clouds in the ozone profile retrievals generally leads to a low bias for a low ground albedo and to a high bias for a high ground albedo, assuming that the ground albedo is well known.

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