scholarly journals The retrieval of snow properties from SLSTR/Sentinel-3 – part 1: method description and sensitivity study

2020 ◽  
Author(s):  
Linlu Mei ◽  
Vladimir Rozanov ◽  
Christine Pohl ◽  
Marco Vountas ◽  
John P. Burrows
Keyword(s):  
Surface Roughness ◽  
Optical Properties ◽  
Particle Shape ◽  
Crystal Surface ◽  
Atmospheric Correction ◽  
Sensitivity Study ◽  
Ice Crystal ◽  
Aerosol Cloud ◽  
Snow Properties ◽  
The Impact

Abstract. The eXtensible Bremen Aerosol/cloud and surfacE parameters Retrieval (XBAER) algorithm has been applied on the Top-Of-Atmosphere reflectance measured by the Sea and Land Surface Temperature Radiometer (SLSTR) instrument onboard Sentinel-3 to derive snow properties: Snow Grain Size (SGS), Snow Particle Shape (SPS) and Specific Surface Area (SSA) under cloud-free conditions. This is the first part of the paper, to describe the retrieval method and the sensitivity study. Nine pre-defined ice crystal particle shapes (aggregate of 8 columns, Drontal, hollow bullet rosettes, hollow column, plate, aggregate of 5 plates, aggregate of 10 plates, solid bullet rosettes, column) are used to describe the snow optical properties. The optimal SGS and SPS are estimated iteratively utilizing a Look-Up-Table (LUT) approach. The SSA is then calculated using another pre-calculated LUT for the retrieved SGS and SPS. The optical properties (e.g., phase function) of the ice crystals can reproduce the wavelength-dependent/angular-dependent snow reflectance features, compared to laboratory measurements. A comprehensive study to understand the impact of aerosol, ice crystal shape, ice crystal surface roughness, and cloud contamination on the retrieval accuracy of snow properties has been performed based on SCIATRAN radiative transfer simulations. The main findings are (1) Snow angular and spectral reflectance feature can be described by the predefined ice crystal properties only when both SGS and SPS can be optimally and iteratively obtained; (2) The impact of ice crystal surface roughness plays minor effects on the retrieval results; (3) SGS and SSA show an inverse linear relationship; (4) The retrieval of SSA assuming non-convex particle shape, compared to convex particle (e.g. sphere) shows larger results; (5) Aerosol/cloud contamination due to unperfected atmospheric correction and cloud screening introduces underestimation of SGS, inaccurate SPS and overestimation of SSA.

scholarly journals The retrieval of snow properties from SLSTR Sentinel-3 – Part 1: Method description and sensitivity study

2021 ◽  
Vol 15 (6) ◽  
pp. 2757-2780
Author(s):  
Linlu Mei ◽  
Vladimir Rozanov ◽  
Christine Pohl ◽  
Marco Vountas ◽  
John P. Burrows
Keyword(s):  
Surface Roughness ◽  
Particle Size ◽  
Optical Properties ◽  
Particle Shape ◽  
Crystal Surface ◽  
Spectral Response ◽  
Sensitivity Study ◽  
Ice Crystal ◽  
Snow Properties ◽  
The Impact

Abstract. The eXtensible Bremen Aerosol/cloud and surfacE parameters Retrieval (XBAER) algorithm has been designed for the top-of-atmosphere reflectance measured by the Sea and Land Surface Temperature Radiometer (SLSTR) instrument on board Sentinel-3 to derive snow properties: snow grain size (SGS), snow particle shape (SPS) and specific surface area (SSA) under cloud-free conditions. This is the first part of the paper, to describe the retrieval method and the sensitivity study. Nine pre-defined SPSs (aggregate of 8 columns, droxtal, hollow bullet rosette, hollow column, plate, aggregate of 5 plates, aggregate of 10 plates, solid bullet rosette, column) are used to describe the snow optical properties. The optimal SGS and SPS are estimated iteratively utilizing a look-up-table (LUT) approach. The SSA is then calculated using another pre-calculated LUT for the retrieved SGS and SPS. The optical properties (e.g., phase function) of the ice crystals can reproduce the wavelength-dependent and angular-dependent snow reflectance features, compared to laboratory measurements. A comprehensive study to understand the impact of aerosols, SPS, ice crystal surface roughness, cloud contamination, instrument spectral response function, the snow habit mixture model and snow vertical inhomogeneity in the retrieval accuracy of snow properties has been performed based on SCIATRAN radiative transfer simulations. The main findings are (1) snow angular and spectral reflectance features can be described by the predefined ice crystal properties only when both SGS and SPS can be optimally and iteratively obtained; (2) the impact of ice crystal surface roughness on the retrieval results is minor; (3) SGS and SSA show an inverse linear relationship; (4) the retrieval of SSA assuming a non-convex particle shape, compared to a convex particle shape (e.g., sphere), shows larger retrieval results; (5) aerosol/cloud contamination due to unperfected atmospheric correction and cloud screening introduces underestimation of SGS, “inaccurate” SPS and overestimation of SSA; (6) the impact of the instrument spectral response function introduces an overestimation into retrieved SGS, introduces an underestimation into retrieved SSA and has no impact on retrieved SPS; and (7) the investigation, by taking an ice crystal particle size distribution and habit mixture into account, reveals that XBAER-retrieved SGS agrees better with the mean size, rather than with the mode size, for a given particle size distribution.

scholarly journals Analysis of simultaneous aerosol and ocean glint retrieval using multi-angle observations

2020 ◽  
Author(s):  
Kirk Knobelspiesse ◽  
Amir Ibrahim ◽  
Bryan Franz ◽  
Sean Bailey ◽  
Robert Levy ◽  
...  
Keyword(s):  
Optical Properties ◽  
Wind Speed ◽  
Radiative Transfer ◽  
Size Distribution ◽  
Atmospheric Correction ◽  
Surface Wind ◽  
Ocean Surface ◽  
True Value ◽  
Aerosol State ◽  
The Impact

Abstract. Since early 2000, NASA's Multi-angle Imaging SpectroRadiometer (MISR) instrument has been performing remote sensing retrievals of aerosol optical properties from the polar orbiting Terra spacecraft. A noteworthy aspect of MISR observations over the ocean is that, for much of the Earth, some of the multi-angle views have contributions from solar reflection by the ocean surface (glint, or glitter), while others do not. Aerosol retrieval algorithms often discard these glint influenced observations because they can overwhelm the signal and are difficult to predict without knowledge of the (wind speed driven) ocean surface roughness. However, theoretical studies have shown that multi-angle observations of a location at geometries with and without reflected sun glint can be a rich source of information, sufficient to support simultaneous retrieval of both the aerosol state and the wind speed at the ocean surface. We are in the early stages of creating such an algorithm. In this manuscript, we describe our assessment of the appropriate level of parameterization for simultaneous aerosol and ocean surface property retrievals using sun glint. For this purpose, we use Generalized Nonlinear Retrieval Analysis (GENRA), an information content assessment (ICA) technique employing Bayesian inference, and simulations from the Ahmad-Fraser iterative radiative transfer code. We find that four parameters are suitable: aerosol optical depth (τ), particle size distribution (expressed as the fine mode fraction f of small particles in a bimodal size distribution), surface wind speed (w), and relative humidity (r, to define the aerosol water content and complex refractive index). None of these parameters define ocean optical properties, as we found that the aerosol state could be retrieved with the nine MISR near-infrared views alone, where the ocean body is black in the open ocean. We also found that retrieval capability varies with observation geometry, and that as τ increases so does the ability to determine aerosol intensive optical properties (r and f, while it decreases for w). Increases in wind speed decrease the ability to determine the true value of that parameter, but have minimal impact on retrieval of aerosol properties. We explored the benefit of excluding the two most extreme MISR view angles for which radiative transfer with the plane parallel approximation is less certain, but found no advantage in doing so. Finally, the impact of treating wind speed as a scalar parameter, rather than as a two parameter directional wind, was tested. While the simpler scalar model does contribute to overall aerosol uncertainty, it is not sufficiently large to justify the addition of another dimension to parameter space. An algorithm designed upon these principles is in development. It will be used to perform an atmospheric correction with MISR for coincident ocean color (OC) observations by the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument, also on the NASA Terra spacecraft. Unlike MISR, MODIS is a single view angle instrument, but it has a more complete set of spectral channels ideal for determination of ocean optical properties. The atmospheric correction of MODIS OC data can therefore benefit from MISR aerosol retrievals. Furthermore, higher spatial resolution data from coincident MISR observations may also improve glint screening.

scholarly journals Implementation of Aerosol-Cloud Interaction within WRF-CHIMERE Online Coupled Model: Evaluation and Investigation of the Indirect Radiative Effect from Anthropogenic Emission Reduction on the Benelux Union

Atmosphere ◽  
2019 ◽  
Vol 10 (1) ◽  
pp. 20 ◽  
Author(s):  
Paolo Tuccella ◽  
Laurent Menut ◽  
Régis Briant ◽  
Adrien Deroubaix ◽  
Dmitry Khvorostyanov ◽  
...  
Keyword(s):  
Indirect Effects ◽  
Coupled Model ◽  
Sensitivity Study ◽  
Cloud Formation ◽  
Radiative Effect ◽  
Satellite Measurements ◽  
Aerosol Cloud ◽  
Order Of Magnitude ◽  
Surface Measurements ◽  
The Impact

The indirect effects of aerosol are particularly important over regions where meteorological conditions and aerosol content are favourable to cloud formation. This was observed during the Intensive Cloud Aerosol Measurement Campaign (IMPACT) (European Integrated project on Aerosol Cloud Climate and Air quality Interaction (EUCAARI) project) in the Benelux Union during May 2008. To better understand this cloud formation variability, the indirect effects of aerosol have been included within the WRF-CHIMERE online model. By comparing model results to the aircraft measurements of IMPACT, to surface measurements from EMEP and AIRBASE and to MODIS satellite measurements, we showed that the model is able to simulate the variability and order of magnitude of the observed number of condensation nuclei (CN), even if some differences are identified for specific aerosol size and location. To quantify the impact of the local anthropogenic emissions on cloud formation, a sensitivity study is performed by halving the surface emissions fluxes. It is shown that the indirect radiative effect (IRE) at the surface is positive for both shortwave and longwave with a net warming of +0.99 W/m2. In addition, important instantaneous changes are modelled at local scale with up to ±6 °C for temperatures and ±50 mm/day for precipitation.

scholarly journals Aerosol–Cloud Closure Study on Cloud Optical Properties using Remotely Piloted Aircraft Measurements during a BACCHUS Field Campaign in Cyprus

2019 ◽  
Author(s):  
Radiance Calmer ◽  
Gregory C. Roberts ◽  
Kevin J. Sanchez ◽  
Jean Sciare ◽  
Karine Sellegri ◽  
...  
Keyword(s):  
Optical Properties ◽  
Solar Radiation ◽  
Shortwave Radiation ◽  
Cloud Base ◽  
Field Campaign ◽  
Aerosol Cloud ◽  
Remotely Piloted Aircraft ◽  
Aerosol Cloud Interactions ◽  
The Impact ◽  
Adiabatic Case

Abstract. In the framework of the EU-FP7 BACCHUS project, an intensive field campaign was performed in Cyprus (2015/03). Remotely Piloted Aircraft System (RPAS), ground-based instruments, and remote-sensing observations were operating in parallel to provide an integrated characterization of aerosol-cloud interactions. Remotely Piloted Aircraft (RPA) were equipped with a 5-hole probe, pyranometers, pressure, temperature and humidity sensors, and measured updraft velocity at cloud base and cloud optical properties of a stratocumulus layer. Ground-based measurements of dry aerosol size distributions and cloud condensation nuclei spectra, and RPA observations of vertical wind velocity and meteorological state parameters are used here to initialize an Aerosol–Cloud Parcel Model (ACPM) and compare the in situ observations of cloud optical properties measured by the RPA to those simulated in the ACPM. Two different cases are studied with the ACPM, including an adiabatic case and an entrainment case, in which the in-cloud temperature profile from RPA is taken into account. Adiabatic ACPM simulation yields cloud droplet number concentrations at cloud base (ca. 400 cm−3) that are similar to those derived from a Hoppel minimum analysis. Cloud optical properties have been inferred using the transmitted fraction of shortwave radiation profile measured by downwelling and upwelling pyranometers mounted on a RPA, and the observed transmitted fraction of solar radiation is then compared to simulations from the ACPM. ACPM simulations and RPA observations show better agreement when associated with entrainment compared to that of an adiabatic case. The mean difference between observed and adiabatic profiles of transmitted fraction of solar radiation is 0.12, while this difference is only 0.03 between observed and entrainment profiles. A sensitivity calculation is then conducted to quantify the relative impacts of two-fold changes in aerosol concentration, and updraft velocity to highlight the importance of accounting for the impact of entrainment in deriving cloud optical properties, as well as the ability of RPAs to leverage ground-based observations for studying aerosol–cloud interactions.

scholarly journals Snow albedo sensitivity to macroscopic surface roughness using a new ray tracing model

2019 ◽  
Author(s):  
Fanny Larue ◽  
Ghislain Picard ◽  
Laurent Arnaud ◽  
Inès Ollivier ◽  
Clément Delcourt ◽  
...  
Keyword(s):  
Surface Roughness ◽  
Smooth Surface ◽  
Incident Angle ◽  
The Sun ◽  
Multiple Reflections ◽  
Snow Albedo ◽  
Snow Properties ◽  
Angle Effect ◽  
Effective Angle ◽  
The Impact

Abstract. Most models simulating snow albedo assume a flat and smooth surface, neglecting surface roughness. However, the presence of macroscopic roughness leads to a systematic decrease in albedo due to two effects: 1) photons are trapped in concavities (multiple reflection effect) and, 2) when the sun is low, the roughness sides facing the sun experience an overall decrease in the local incident angle relative to a smooth surface, promoting higher absorption, whilst the other sides has weak contributions because of the increased incident angle or because they are shadowed (called the effective angle effect here). This paper aims to quantify the impact of surface roughness on albedo and to assess the respective role of these two effects, with 1) observations over varying amounts of surface roughness, and 2) simulations using the new Rough Surface Ray Tracer (RSRT) model, based on a Monte Carlo method for photon transport calculation. The observations include spectral albedo (400–1050 nm) over manually-created roughness surfaces with multiple geometrical characteristics. Measurements highlight that even a low fraction of surface roughness features (7 % of the surface) causes an albedo decrease of 0.02 at 1000 nm when the solar zenith angle (Өs) is larger than 50°. For higher fractions (13 %, 27 % and 63 %), and when the roughness orientation is perpendicular to the sun, the decrease is of 0.03–0.04 at 700 nm and of 0.06–0.10 at 1000 nm. The impact is 20 % lower when roughness orientation is parallel to the sun. The observations are subsequently compared to RSRT simulations. Accounting for surface roughness improves the model observation agreement by a factor two at 700 nm and 1000 nm (errors of 0.03 and 0.04, respectively), compared to simulations considering a flat smooth surface. The model is used to explore the albedo sensitivity to surface roughness with varying snow properties and illumination conditions. Both multiple reflections and the effective angle effect have more impact with low SSA (

scholarly journals On the Improvement of COAMPS Weather Forecasts Using an Advanced Radiative Transfer Model

2009 ◽  
Vol 24 (1) ◽  
pp. 286-306 ◽  
Author(s):  
Ming Liu ◽  
Jason E. Nachamkin ◽  
Douglas L. Westphal
Keyword(s):  
Optical Properties ◽  
Radiative Transfer ◽  
Liquid Water ◽  
Atmospheric Stability ◽  
Sensitivity Study ◽  
Radiative Heating ◽  
Radiative Transfer Model ◽  
Surface Model ◽  
Transfer Model ◽  
The Impact

Abstract Fu–Liou’s delta-four-stream (with a two-stream option) radiative transfer model has been implemented in the U.S. Navy’s Coupled Ocean–Atmosphere Mesoscale Prediction System (COAMPS)1 to calculate solar and thermal infrared fluxes in 6 shortwave and 12 longwave bands. The model performance is evaluated at high resolution for clear-sky and overcast conditions against the observations from the Southern Great Plains of the Atmospheric Radiation Measurement Program. In both cases, use of the Fu–Liou model provides significant improvement over the operational implementation of the standard Harshvardhan radiation parameterization in both shortwave and longwave fluxes. A sensitivity study of radiative flux on clouds reveals that the choices of cloud effective radius schemes for ice and liquid water are critical to the flux calculation due to the effects on cloud optical properties. The sensitivity study guides the selection of optimal cloud optical properties for use in the Fu–Liou parameterization as implemented in COAMPS. The new model is then used to produce 3-day forecasts over the continental United States for a winter and a summer month. The verifications of parallel runs using the standard and new parameterizations show that Fu–Liou dramatically reduces the model’s systematic warm bias in the upper troposphere in both winter and summer. The resultant cooling modifies the atmospheric stability and moisture transport, resulting in a significant reduction in the upper-tropospheric wet bias. Overall ice and liquid water paths are also reduced. At the surface, Fu–Liou reduces the negative temperature and sea level pressure biases by providing more accurate radiative heating rates to the land surface model. The error reductions increase with forecast length as the impact of improved radiative fluxes accumulates over time. A combination of the two- and four-stream options results in major computational efficiency gains with minimal loss in accuracy.

scholarly journals CAAS: an atmospheric correction algorithm for the remote sensing of complex waters

2012 ◽  
Vol 30 (1) ◽  
pp. 203-220 ◽  
Author(s):  
P. Shanmugam
Keyword(s):  
Remote Sensing ◽  
Optical Properties ◽  
Near Infrared ◽  
Atmospheric Correction ◽  
Atmospheric Effects ◽  
Correction Algorithm ◽  
Ocean Colour ◽  
In Situ Data ◽  
Correction Scheme ◽  
The Impact

Abstract. The current SeaDAS atmospheric correction algorithm relies on the computation of optical properties of aerosols based on radiative transfer combined with a near-infrared (NIR) correction scheme (originally with assumptions of zero water-leaving radiance for the NIR bands) and several ancillary parameters to remove atmospheric effects in remote sensing of ocean colour. The failure of this algorithm over complex waters has been reported by many recent investigations, and can be attributed to the inadequate NIR correction and constraints for deriving aerosol optical properties whose characteristics are the most difficult to evaluate because they vary rapidly with time and space. The possibility that the aerosol and sun glint contributions can be derived in the whole spectrum of ocean colour solely from a knowledge of the total and Rayleigh-corrected radiances is developed in detail within the framework of a Complex water Atmospheric correction Algorithm Scheme (CAAS) that makes no use of ancillary parameters. The performance of the CAAS algorithm is demonstrated for MODIS/Aqua imageries of optically complex waters and yields physically realistic water-leaving radiance spectra that are not possible with the SeaDAS algorithm. A preliminary comparison with in-situ data for several regional waters (moderately complex to clear waters) shows encouraging results, with absolute errors of the CAAS algorithm closer to those of the SeaDAS algorithm. The impact of the atmospheric correction was also examined on chlorophyll retrievals with a Case 2 water bio-optical algorithm, and it was found that the CAAS algorithm outperformed the SeaDAS algorithm in terms of producing accurate pigment estimates and recovering areas previously flagged out by the later algorithm. These findings suggest that the CAAS algorithm can be used for applications focussing in quantitative assessments of the biological and biogeochemical properties in complex waters, and can easily be extended to other sensors such as OCM-2, MERIS and GOCI.

scholarly journals Aerosol–cloud closure study on cloud optical properties using remotely piloted aircraft measurements during a BACCHUS field campaign in Cyprus

2019 ◽  
Vol 19 (22) ◽  
pp. 13989-14007 ◽  
Author(s):  
Radiance Calmer ◽  
Gregory C. Roberts ◽  
Kevin J. Sanchez ◽  
Jean Sciare ◽  
Karine Sellegri ◽  
...  
Keyword(s):  
Optical Properties ◽  
Solar Radiation ◽  
Cloud Base ◽  
Field Campaign ◽  
Aerosol Cloud ◽  
Holistic Understanding ◽  
Remotely Piloted Aircraft ◽  
Aerosol Cloud Interactions ◽  
The Impact ◽  
Adiabatic Case

Abstract. In the framework of the EU-FP7 BACCHUS (impact of Biogenic versus Anthropogenic emissions on Clouds and Climate: towards a Holistic UnderStanding) project, an intensive field campaign was performed in Cyprus (March 2015). Remotely piloted aircraft system (RPAS), ground-based instruments, and remote-sensing observations were operating in parallel to provide an integrated characterization of aerosol–cloud interactions. Remotely piloted aircraft (RPA) were equipped with a five-hole probe, pyranometers, pressure, temperature and humidity sensors, and measured vertical wind at cloud base and cloud optical properties of a stratocumulus layer. Ground-based measurements of dry aerosol size distributions and cloud condensation nuclei spectra, and RPA observations of updraft and meteorological state parameters are used here to initialize an aerosol–cloud parcel model (ACPM) and compare the in situ observations of cloud optical properties measured by the RPA to those simulated in the ACPM. Two different cases are studied with the ACPM, including an adiabatic case and an entrainment case, in which the in-cloud temperature profile from RPA is taken into account. Adiabatic ACPM simulation yields cloud droplet number concentrations at cloud base (approximately 400 cm−3) that are similar to those derived from a Hoppel minimum analysis. Cloud optical properties have been inferred using the transmitted fraction of shortwave radiation profile measured by downwelling and upwelling pyranometers mounted on a RPA, and the observed transmitted fraction of solar radiation is then compared to simulations from the ACPM. ACPM simulations and RPA observations shows better agreement when associated with entrainment compared to that of an adiabatic case. The mean difference between observed and adiabatic profiles of transmitted fraction of solar radiation is 0.12, while this difference is only 0.03 between observed and entrainment profiles. A sensitivity calculation is then conducted to quantify the relative impacts of 2-fold changes in aerosol concentration, and updraft to highlight the importance of accounting for the impact of entrainment in deriving cloud optical properties, as well as the ability of RPAs to leverage ground-based observations for studying aerosol–cloud interactions.

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