scholarly journals Bias assessment of lower and middle tropospheric CO<sub>2</sub> concentrations of GOSAT/TANSO-FTS TIR Version 1 product

2017 ◽  
Author(s):  
Naoko Saitoh ◽  
Shuhei Kimoto ◽  
Ryo Sugimura ◽  
Ryoichi Imasu ◽  
Kei Shiomi ◽  
...  
Keyword(s):  
Bias Correction ◽  
Lower Troposphere ◽  
Point Sources ◽  
Upper Atmosphere ◽  
Retrieval Algorithm ◽  
Co2 Absorption ◽  
Free Troposphere ◽  
Absorption Bands ◽  
Co2 Concentrations ◽  
Local Point

Abstract. CO2 observations in the free troposphere can be useful for constraining CO2 source and sink estimates at the surface due to their representativeness being away from local point sources of CO2. The thermal infrared (TIR) band of the Thermal and Near Infrared Sensor for Carbon Observation (TANSO)−Fourier Transform Spectrometer (FTS) on board the Greenhouse Gases Observing Satellite (GOSAT) has been observing global CO2 concentrations in the free troposphere for about 8 years, and thus could provide a dataset with which to evaluate the vertical transport of CO2 from the surface to the upper atmosphere. This study evaluated biases in the TIR version 1 (V1) CO2 product in the lower troposphere (LT) and the middle troposphere (MT) (736–287 hPa), on the basis of comparisons with CO2 profiles obtained over airports using Continuous CO2 Measuring Equipment (CME) in the Comprehensive Observation Network for Trace gases by AIrLiner (CONTRAIL) project. Bias-correction values are presented for TIR CO2 data for each pressure layer in the LT and MT regions during each season and in each latitude band: 40°S–20°S, 20° S–20° N, 20° N–40° N, and 40° N–60° N. TIR V1 CO2 data had consistent negative biases of 1–1.5 % compared with CME CO2 data in the LT and MT regions, with the largest negative biases at 541–398 hPa, partly due to the use of 10-μm CO2 absorption band in conjunction with 15-μm and 9-μm absorption bands in the V1 retrieval algorithm. Global comparisons between TIR CO2 data to which the bias-correction values were applied and CO2 data simulated by Nonhydrostatic ICosahedral Atmospheric Model (NICAM)-based transport model (TM) confirmed the validity of the bias-correction values evaluated over airports in limited areas. In low latitudes in the upper MT region (398–287 hPa), however, TIR CO2 data in northern summer were overcorrected by these bias-correction values; this is because the bias-correction values were determined using comparisons mainly over airports in East Asia where CO2 concentrations in the upper atmosphere display relatively large variations due to strong updrafts.

scholarly journals Bias assessment of lower and middle tropospheric CO<sub>2</sub> concentrations of GOSAT/TANSO-FTS TIR version 1 product

2017 ◽  
Vol 10 (10) ◽  
pp. 3877-3892 ◽  
Author(s):  
Naoko Saitoh ◽  
Shuhei Kimoto ◽  
Ryo Sugimura ◽  
Ryoichi Imasu ◽  
Kei Shiomi ◽  
...  
Keyword(s):  
Bias Correction ◽  
Near Infrared ◽  
Transport Model ◽  
Lower Troposphere ◽  
Upper Atmosphere ◽  
Retrieval Algorithm ◽  
Co2 Absorption ◽  
Free Troposphere ◽  
Absorption Bands ◽  
Co2 Concentrations

Abstract. CO2 observations in the free troposphere can be useful for constraining CO2 source and sink estimates at the surface since they represent CO2 concentrations away from point source emissions. The thermal infrared (TIR) band of the Thermal and Near Infrared Sensor for Carbon Observation (TANSO) Fourier transform spectrometer (FTS) on board the Greenhouse Gases Observing Satellite (GOSAT) has been observing global CO2 concentrations in the free troposphere for about 8 years and thus could provide a dataset with which to evaluate the vertical transport of CO2 from the surface to the upper atmosphere. This study evaluated biases in the TIR version 1 (V1) CO2 product in the lower troposphere (LT) and the middle troposphere (MT) (736–287 hPa), on the basis of comparisons with CO2 profiles obtained over airports using Continuous CO2 Measuring Equipment (CME) in the Comprehensive Observation Network for Trace gases by AIrLiner (CONTRAIL) project. Bias-correction values are presented for TIR CO2 data for each pressure layer in the LT and MT regions during each season and in each latitude band: 40–20° S, 20° S–20° N, 20–40° N, and 40–60° N. TIR V1 CO2 data had consistent negative biases of 1–1.5 % compared with CME CO2 data in the LT and MT regions, with the largest negative biases at 541–398 hPa, partly due to the use of 10 µm CO2 absorption band in conjunction with 15 and 9 µm absorption bands in the V1 retrieval algorithm. Global comparisons between TIR CO2 data to which the bias-correction values were applied and CO2 data simulated by a transport model based on the Nonhydrostatic ICosahedral Atmospheric Model (NICAM-TM) confirmed the validity of the bias-correction values evaluated over airports in limited areas. In low latitudes in the upper MT region (398–287 hPa), however, TIR CO2 data in northern summer were overcorrected by these bias-correction values; this is because the bias-correction values were determined using comparisons mainly over airports in Southeast Asia, where CO2 concentrations in the upper atmosphere display relatively large variations due to strong updrafts.

scholarly journals Global carbon monoxide as retrieved from SCIAMACHY by WFM-DOAS

2004 ◽  
Vol 4 (3) ◽  
pp. 2805-2837 ◽  
Author(s):  
M. Buchwitz ◽  
R. de Beek ◽  
K. Bramstedt ◽  
S. Noël ◽  
H. Bovensmann ◽  
...  
Keyword(s):  
Carbon Monoxide ◽  
Near Infrared ◽  
Weighting Function ◽  
Lower Troposphere ◽  
Quantitative Information ◽  
Scaling Factor ◽  
Retrieval Algorithm ◽  
Absorption Bands ◽  
Spectral Fitting ◽  
Data Product

Abstract. Vertical columns of CO have been retrieved from SCIAMACHY/ENVISAT short wave/near infrared (~2.3µm) nadir spectra using the Weighting Function Modified (WFM) DOAS retrieval algorithm. WFM-DOAS has been applied to a small spectral fitting window located in SCIAMACHY's channel 8 (~2365 nm) covering four CO absorption lines. The focus of this paper is to demonstrate that quantitative information on carbon monoxide (CO) on a global scale can be retrieved from SCIAMACHY. It is shown that plumes of CO resulting from, e.g. biomass burning in Africa, are clearly detectable with SCIAMACHY. The SCIAMACHY CO columns are in good agreement with the CO column data product of MOPITT (V3). For example, the correlation between SCIAMACHY and MOPITT CO columns for cloud free pixels over land is typically in the range r=0.4–0.7, where r is the correlation coefficient. In order to retrieve good CO columns it was necessary to improve the calibration of the SCIAMACHY nadir spectra. Nevertheless, there is still room for significant improvement. The fit residuals, for example, are dominated by stable and systematic spectral artifacts on the order of the weak CO lines. These artifacts are most pronounced in spectral regions of strong overlapping methane and water vapour absorption bands. They might result from spectrometer slit function uncertainties. The CO columns of the WFM-DOAS Version 0.4 CO column data product presented in this paper have been multiplied by a constant and ground scene independent scaling factor of 0.5 to quantitatively adjust the WFM-DOAS retrieved CO columns to the MOPITT CO data. If and how this scaling factor is influenced by SCIAMACHYs much higher sensitivity to the lower troposphere and boundary layer CO and/or by the currently not perfect spectral fitting needs further investigation.

scholarly journals Spectral calibration of the MethaneAIR instrument

2021 ◽  
Vol 14 (5) ◽  
pp. 3737-3753
Author(s):  
Carly Staebell ◽  
Kang Sun ◽  
Jenna Samra ◽  
Jonathan Franklin ◽  
Christopher Chan Miller ◽  
...  
Keyword(s):  
Oil And Gas ◽  
Spectral Response ◽  
Point Sources ◽  
Stray Light ◽  
Lookup Table ◽  
High Spectral Resolution ◽  
Retrieval Algorithm ◽  
Co2 Absorption ◽  
Central Wavelength ◽  
Spectral Calibration

Abstract. MethaneAIR is the airborne simulator of MethaneSAT, an area-mapping satellite currently under development with the goal of locating and quantifying large anthropogenic CH4 point sources as well as diffuse emissions at the spatial scale of an oil and gas basin. Built to closely replicate the forthcoming satellite, MethaneAIR consists of two imaging spectrometers. One detects CH4 and CO2 absorption around 1.65 and 1.61 µm, respectively, while the other constrains the optical path in the atmosphere by detecting O2 absorption near 1.27 µm. The high spectral resolution and stringent retrieval accuracy requirements of greenhouse gas remote sensing in this spectral range necessitate a reliable spectral calibration. To this end, on-ground laboratory measurements were used to derive the spectral calibration of MethaneAIR, serving as a pathfinder for the future calibration of MethaneSAT. Stray light was characterized and corrected for through fast-Fourier-transform-based Van Cittert deconvolution. Wavelength registration was examined and found to be best described by a linear relationship for both bands with a precision of ∼ 0.02 spectral pixel. The instrument spectral spread function (ISSF), measured with fine wavelength steps of 0.005 nm near a series of central wavelengths across each band, was oversampled to construct the instrument spectral response function (ISRF) at each central wavelength and spatial pixel. The ISRFs were smoothed with a Savitzky–Golay filter for use in a lookup table in the retrieval algorithm. The MethaneAIR spectral calibration was evaluated through application to radiance spectra from an instrument flight over the Colorado Front Range.

scholarly journals On variability of total ozone derived from TOVS data over peninsular Indian sub-continent and adjoining oceanic area

MAUSAM ◽  
2022 ◽  
Vol 53 (4) ◽  
pp. 503-514
Author(s):  
R. SURESH
Keyword(s):  
Total Ozone ◽  
Monsoon Season ◽  
Lower Troposphere ◽  
Southwest Monsoon ◽  
Retrieval Algorithm ◽  
Tropospheric Temperature ◽  
Minimum Concentration ◽  
Upper Troposphere ◽  
Positive Correlation Coefficient ◽  
Longitudinal Variability

The total ozone derived from TOVS data from NOAA 12 satellite through one step physical retrieval algorithm of  International TOVS Processing Package (ITPP) version 5.0 has been used to identify  its diurnal, monthly, latitudinal and longitudinal variability during 1998 over the domain Equator to 26° N / 60-100° E. The linkage of  maximum total ozone with warmer tropopause and lower stratosphere has been re-established. The colder upper tropospheric temperature which is normally associated with maximum ozone concentration throughout the year elsewhere in the world  has also been identified in this study but the relationship gets reversed during southwest  monsoon months(June-September) over the domain considered. The moisture  available in abundance in the lower troposphere gets precipitated due to the convective instability prevailing in the atmosphere during monsoon season and very little moisture is only available for vertical transport into the upper troposphere atop 500 hPa. The latent heat released by the  precipitation processes warms up the middle and upper atmosphere. The warm and dry upper troposphere could be the reason for less depletion of ozone in the upper troposphere during monsoonal  months and this is supported by the positive correlation coefficient prevailing in monsoon season between  total ozone and upper tropospheric (aloft 300 hPa) temperature. The warmness in middle and upper troposphere which is associated with less depletion and/or production of more  ozone in the upper troposphere may  perhaps contribute  for the  higher total ozone during monsoon months than in other seasons over peninsular Indian region.  The minimum concentration is observed during January (226 DU) over 6° N and the maximum (283DU) over 18° N during August. Longitudinal variability is less pronounced than the latitudinal variability.

scholarly journals Improving GOES Advanced Baseline Imager (ABI) aerosol optical depth (AOD) retrievals using an empirical bias correction algorithm

2020 ◽  
Vol 13 (11) ◽  
pp. 5955-5975
Author(s):  
Hai Zhang ◽  
Shobha Kondragunta ◽  
Istvan Laszlo ◽  
Mi Zhou
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Bias Correction ◽  
Land Surface ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Infrared Imaging ◽  
Retrieval Algorithm ◽  
Correction Algorithm ◽  
Time Step

Abstract. The Advanced Baseline Imager (ABI) on board the Geostationary Operational Environmental Satellite-R (GOES-R) series enables retrieval of aerosol optical depth (AOD) from geostationary satellites using a multiband algorithm similar to those of polar-orbiting satellites' sensors, such as the Moderate Resolution Imaging Spectroradiometer (MODIS) and Visible Infrared Imaging Radiometer Suite (VIIRS). However, this work demonstrates that the current version of GOES-16 (GOES-East) ABI AOD has diurnally varying biases due to limitations in the land surface reflectance relationships between the 0.47 µm band and the 2.2 µm band and between the 0.64 µm band and 2.2 µm band used in the ABI AOD retrieval algorithm, which vary with the Sun–satellite geometry and NDVI (normalized difference vegetation index). To reduce these biases, an empirical bias correction algorithm has been developed based on the lowest observed ABI AOD of an adjacent 30 d period and the background AOD at each time step and at each pixel. The bias correction algorithm improves the performance of ABI AOD compared to AErosol RObotic NETwork (AERONET) AOD, especially for the high and medium (top 2) quality ABI AOD. AOD data for the period 6 August to 31 December 2018 are used to evaluate the bias correction algorithm. After bias correction, the correlation between the top 2 quality ABI AOD and AERONET AOD improves from 0.87 to 0.91, the mean bias improves from 0.04 to 0.00, and root-mean-square error (RMSE) improves from 0.09 to 0.05. These results for the bias-corrected top 2 qualities ABI AOD are comparable to those of the corrected high-quality ABI AOD. By using the top 2 qualities of ABI AOD in conjunction with the bias correction algorithm, the areal coverage of ABI AOD is increased by about 100 % without loss of data accuracy.

scholarly journals Wintertime Arctic Air Pollution over central Alaska: pre-ALPACA campaign

2021 ◽  
Author(s):  
Eleftherios Ioannidis ◽  
Kathy S. Law ◽  
Jean-Christophe Raut ◽  
Tatsuo Onishi ◽  
Louis Marelle ◽  
...  
Keyword(s):  
Air Pollution ◽  
The United States ◽  
Point Sources ◽  
The Arctic ◽  
Formation Mechanisms ◽  
Winter Conditions ◽  
Local Point ◽  
Temperature Inversions ◽  
Local Emissions ◽  
Pollution Episodes

&lt;p&gt;The wintertime Arctic is influenced by air pollution transported from mid-latitudes, leading to formation of Arctic Haze, as well as local emissions such as combustion for heating and power production in very cold winter conditions. This contributes to severe air pollution episodes, with enhanced aerosol concentrations, inter-dispersed with cleaner periods. However, the formation of secondary aerosol particles (sulphate, organics, nitrate) in cold/dark wintertime Arctic conditions, which could contribute to these pollution episodes, is poorly understood.&lt;/p&gt;&lt;p&gt;In this study, which contributes to the Air Pollution in the Arctic: Climate, Environment and Societies - Alaskan Layered Pollution and Arctic Chemical Analysis (PACES-ALPACA) initiative, the Weather Research Forecasting Model with chemistry (WRF-Chem) is used to investigate wintertime pollution over central Alaska focusing on the Fairbanks region, during the pre-ALPACA campaign in winter 2019-2020. Fairbanks is the most polluted city in the United States during wintertime, due to high local emissions and the occurrence of strong surface temperature inversions trapping pollutants near the surface.&lt;/p&gt;&lt;p&gt;Firstly, different WRF meteorological and surface schemes were tested over Alaska with a particular focus on improving simulations of the wintertime boundary layer structure including temperature inversions. An optimal WRF set-up, with increased vertical resolution below 2km, was selected based on evaluation against available data.&lt;/p&gt;&lt;p&gt;Secondly, a quasi-hemispheric WRF-Chem simulation, using the improved WRF setup, was used to assess large-scale synoptic conditions and to evaluate background aerosols originating from remote anthropogenic and natural sources affecting central Alaska during the campaign. The model was run with Evaluating the Climate and Air Quality Impacts of Short-Lived Pollutants (ECLIPSE) v6b anthropogenic emissions and improved sea-spray aerosol emissions. Discrepancies in modelled aerosols compared available data are being investigated (e.g. missing dark formation mechanisms, treatment of removal processes).&lt;/p&gt;&lt;p&gt;Thirdly, fine resolution simulations, using high resolution emissions (e.g. 2019 CAMS inventory), including local point sources, over the Fairbanks region, were used to investigate chemical and dynamical processes influencing aerosols under different meteorological conditions observed during the field campaign including a cold stable episode and a period with possible mixing of air masses from aloft. The model was evaluated against available aerosol, oxidant (ozone) and aerosol precursor data from surface monitoring sites and collected during the pre-campaign, including vertical profile data collected in the lowest 20m. The sensitivity of modelled aerosols to meteorological factors, such as relative humidity, temperature gradients and vertical mixing under winter conditions are investigated.&lt;/p&gt;

scholarly journals How bias correction goes wrong: measurement of X<sub>CO<sub>2</sub></sub> affected by erroneous surface pressure estimates

2019 ◽  
Vol 12 (4) ◽  
pp. 2241-2259 ◽  
Author(s):  
Matthäus Kiel ◽  
Christopher W. O'Dell ◽  
Brendan Fisher ◽  
Annmarie Eldering ◽  
Ray Nassar ◽  
...  
Keyword(s):  
Surface Pressure ◽  
Bias Correction ◽  
Pressure Difference ◽  
Large Fraction ◽  
Systematic Errors ◽  
Retrieval Algorithm ◽  
Relative Errors

Abstract. All measurements of XCO2 from space have systematic errors. To reduce a large fraction of these errors, a bias correction is applied to XCO2 retrieved from GOSAT and OCO-2 spectra using the ACOS retrieval algorithm. The bias correction uses, among other parameters, the surface pressure difference between the retrieval and the meteorological reanalysis. Relative errors in the surface pressure estimates, however, propagate nearly 1:1 into relative errors in bias-corrected XCO2. For OCO-2, small errors in the knowledge of the pointing of the observatory (up to ∼130 arcsec) introduce a bias in XCO2 in regions with rough topography. Erroneous surface pressure estimates are also caused by a coding error in ACOS version 8, sampling meteorological analyses at wrong times (up to 3 h after the overpass time). Here, we derive new geolocations for OCO-2's eight footprints and show how using improved knowledge of surface pressure estimates in the bias correction reduces errors in OCO-2's v9 XCO2 data.

scholarly journals Full-physics carbon dioxide retrievals from the Orbiting Carbon Observatory-2 (OCO-2) satellite by only using the 2.06 µm band

2019 ◽  
Vol 12 (11) ◽  
pp. 6049-6058 ◽  
Author(s):  
Lianghai Wu ◽  
Otto Hasekamp ◽  
Haili Hu ◽  
Joost aan de Brugh ◽  
Jochen Landgraf ◽  
...  
Keyword(s):  
Carbon Dioxide ◽  
Atmospheric Carbon Dioxide ◽  
Total Carbon ◽  
Co2 Absorption ◽  
Absorption Bands ◽  
Passive Remote Sensing ◽  
Spectral Bands ◽  
Retrieval Technique ◽  
Current State ◽  
Data Yield

Abstract. Passive remote sensing of atmospheric carbon dioxide uses spectroscopic measurements of sunlight backscattered by the Earth's surface and atmosphere. The current state-of-the-art retrieval methods use three different spectral bands, the oxygen A band at 0.76 µm and the weak and strong CO2 absorption bands at 1.61 and 2.06 µm, respectively, to infer information on light scattering and the carbon dioxide column-averaged dry-air mole fraction XCO2. In this study, we propose a one-band XCO2 retrieval technique which uses only the 2.06 µm band measurements from the Orbiting Carbon Observatory-2 (OCO-2) satellite. We examine the data quality by comparing the OCO-2 XCO2 with collocated ground-based measurements from the Total Carbon Column Observing Network (TCCON). Over land and ocean the OCO-2 one-band retrieval shows differences from TCCON observations with a standard deviation of ∼1.30 ppm and a station-to-station variability of ∼0.50 ppm. Moreover, we compare one-band and three-band retrievals over Europe, the Middle East, and Africa and see high correlation between the two retrievals with a SD of 0.93 ppm. Compared to the three-band retrievals, XCO2 retrievals using only the 2.06 µm band have similar retrieval accuracy, precision, and data yield.

scholarly journals A Sensitivity Study of the 4.8 µm Carbon Dioxide Absorption Band in the MWIR Spectral Range

2020 ◽  
Vol 12 (1) ◽  
pp. 172 ◽  
Author(s):  
Vito Romaniello ◽  
Claudia Spinetti ◽  
Malvina Silvestri ◽  
Maria Fabrizia Buongiorno
Keyword(s):  
Carbon Dioxide ◽  
Absorption Band ◽  
Strong Dependence ◽  
Point Sources ◽  
Channel Width ◽  
Anthropogenic Sources ◽  
Co2 Absorption ◽  
Industrial Emissions ◽  
Surface Temperatures ◽  
Concentration Changes

The measurements of gas concentrations in the atmosphere are recently developed thanks to the availability of gases absorbing spectral channels in space sensors and strictly depending on the instrument performances. In particular, measuring the sources of carbon dioxide is of high interest to know the distribution, both spatial and vertical, of this greenhouse gas and quantify the natural/anthropogenic sources. The present study aims to understand the sensitivity of the CO2 absorption band at 4.8 µm to possibly detect and measure the spatial distribution of emissions from point sources (i.e., degassing volcanic plumes, fires, and industrial emissions). With the aim to define the characteristics of future multispectral imaging space radiometers, the performance of the CO2 4.8 µm absorption band was investigated. Simulations of the “Top of Atmosphere” (TOA) radiance have been performed by using real input data to reproduce realistic scenarios on a volcanic high elevation point source (>2 km): actual atmospheric background of CO2 (~400 ppm) and vertical atmospheric profiles of pressure, temperature, and humidity obtained from probe balloons. The sensitivity of the channel to the CO2 concentration has been analyzed also varying surface temperatures as environmental conditions from standard to high temperature. Furthermore, response functions of operational imaging sensors in the middle wave infrared spectral region were used. The channel width values of 0.15 µm and 0.30 µm were tested in order to find changes in the gas concentration. Simulations provide results about the sensitivity necessary to appreciate carbon dioxide concentration changes considering a target variation of 10 ppm in gas column concentration. Moreover, the results show the strong dependence of at-sensor radiance on the surface temperature: radiances sharply increase, from 1 Wm−2sr−1µm−1 (in the “standard condition”) to >1200 Wm−2sr−1µm−1 (in the warmest case) when temperatures increase from 300 to 1000 K. The highest sensitivity has been obtained considering the channel width equal to 0.15 µm with noise equivalent delta temperature (NEDT) values in the range from 0.045 to 0.56 K at surface temperatures ranging from 300 to 1000 K.

scholarly journals Evidence of the complexity of aerosol transport in the lower troposphere on the Namibian coast during AEROCLO-sA

2019 ◽  
Author(s):  
Patrick Chazette ◽  
Cyrille Flamant ◽  
Julien Totems ◽  
Marco Gaetani ◽  
Gwendoline Smith ◽  
...  
Keyword(s):  
South America ◽  
Sea Level ◽  
Complex Mixture ◽  
Lower Troposphere ◽  
Back Trajectory ◽  
Aerosol Layer ◽  
Free Troposphere ◽  
Aerosol Composition ◽  
Mean Sea Level ◽  
Field Campaign

Abstract. The evolution of the vertical distribution and optical properties of aerosols in the free troposphere, above stratocumulus, is analysed for the first time over the Namibian coast, a region where uncertainties on aerosol-cloud coupling in climate simulations are significant. We show the high variability of atmospheric aerosol composition in the lower and middle troposphere during the AEROCLO-sA field campaign (22 August–12 September 2017) around the Henties Bay supersite, using a combination of ground-based, airborne and space-borne lidar measurements. Three distinct periods of 4 to 7 days are observed, associated with increasing aerosol loads (aerosol optical thickness at 550 nm ranging from ~ 0.2 to ~ 0.7), as well as increasing aerosol layer depth and top altitude. Aerosols are observed up to 6 km above mean sea level during the later period. Aerosols transported within the free troposphere are mainly polluted dust (dust mixed with smoke from fires in Angola) for the first 2 periods (22 August–1 September 2017) and smoke (from Angola and South America) for the last part (3–9 September) of the field campaign. Lagrangian back trajectory analyses highlight that the highest aerosol layers (between 5 and 6 km above mean sea level) come from South America (Brazil, Argentina and Paraguay) and reach Henties Bay after 4 to 5 days. They are transported eastward by the mid latitude westerlies and towards Southern Africa by the equatorward moving cut-off low originating within the westerlies. This results in a very complex mixture of aerosols over the coastal regions of Namibia that must be taken into account when investigating aerosols radiative effects above stratocumulus clouds in the south east Atlantic Ocean.

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