scholarly journals A Theoretical Analysis for Improving Aerosol-Induced CO2 Retrieval Uncertainties Over Land Based on TanSat Nadir Observations Under Clear Sky Conditions

2019 ◽  
Vol 11 (9) ◽  
pp. 1061 ◽  
Author(s):  
Xi Chen ◽  
Yi Liu ◽  
Dongxu Yang ◽  
Zhaonan Cai ◽  
Hongbin Chen ◽  
...  
Keyword(s):  
Carbon Dioxide ◽  
Refractive Index ◽  
Estimation Method ◽  
Radiative Transfer Model ◽  
Retrieval Algorithm ◽  
Transfer Model ◽  
Aerosol Model ◽  
Coarse Mode ◽  
Fine Mode ◽  
Aerosol Parameters

Aerosols significantly affect carbon dioxide (CO2) retrieval accuracy and precision by modifying the light path. Hyperspectral measurements in the near infrared and shortwave infrared (NIR/SWIR) bands from the generation of new greenhouse gas satellites (e.g., the Chinese Global Carbon Dioxide Monitoring Scientific Experimental Satellite, TanSat) contain aerosol information for correction of scattering effects in the retrieval. Herein, a new approach is proposed for optimizing the aerosol model used in the TanSat CO2 retrieval algorithm to reduce CO2 uncertainties associated with aerosols. The weighting functions of hyperspectral observations with respect to elements in the state vector are simulated by a forward radiative transfer model. Using the optimal estimation method (OEM), the information content and each component of the CO2 column-averaged dry-air mole fraction (XCO2) retrieval errors from the TanSat simulations are calculated for typical aerosols which are described by Aerosol Robotic Network (AERONET) inversion products at selected sites based on the a priori and measurement assumptions. The results indicate that the size distribution parameters (reff, veff), real refractive index coefficient of fine mode (arf) and fine mode fraction (fmf) dominate the interference errors, with each causing 0.2–0.8 ppm of XCO2 errors. Given that only 4–7 degrees of freedom for signal (DFS) of aerosols can be obtained simultaneously and CO2 information decreases as more aerosol parameters are retrieved, four to seven aerosol parameters are suggested as the most appropriate for inclusion in CO2 retrieval. Focusing on only aerosol-induced XCO2 errors, forward model parameter errors, rather than interference errors, are dominant. A comparison of these errors across different aerosol parameter combination groups reveals that fewer aerosol-induced XCO2 errors are found when retrieving seven aerosol parameters. Therefore, the model selected as the optimal aerosol model includes aerosol optical depth (AOD), peak height of aerosol profile (Hp), width of aerosol profile (Hw), effective variance of fine mode aerosol (vefff), effective radius of coarse mode aerosol (reffc), coefficient a of the real part of the refractive index for the fine mode and coarse mode (arf and arc), with the lowest error of less than 1.7 ppm for all aerosol and surface types. For marine aerosols, only five parameters (AOD, Hp, Hw, reffc and arc) are recommended for the low aerosol information. This optimal aerosol model therefore offers a theoretical foundation for improving CO2 retrieval precision from real TanSat observations in the future.

scholarly journals Indirect estimation of absorption properties for fine aerosol particles using AATSR observations: a case study of wildfires in Russia in 2010

2015 ◽  
Vol 8 (8) ◽  
pp. 3075-3085 ◽  
Author(s):  
E. Rodríguez ◽  
P. Kolmonen ◽  
T. H. Virtanen ◽  
L. Sogacheva ◽  
A.-M. Sundström ◽  
...  
Keyword(s):  
Optical Depth ◽  
Continuous Variation ◽  
Radiative Transfer Model ◽  
Retrieval Algorithm ◽  
Transfer Model ◽  
Retrieval Process ◽  
Aerosol Model ◽  
Coarse Mode ◽  
Fine Mode ◽  
Aerosol Properties

Abstract. The Advanced Along-Track Scanning Radiometer (AATSR) on board the ENVISAT satellite is used to study aerosol properties. The retrieval of aerosol properties from satellite data is based on the optimized fit of simulated and measured reflectances at the top of the atmosphere (TOA). The simulations are made using a radiative transfer model with a variety of representative aerosol properties. The retrieval process utilizes a combination of four aerosol components, each of which is defined by their (lognormal) size distribution and a complex refractive index: a weakly and a strongly absorbing fine-mode component, coarse mode sea salt aerosol and coarse mode desert dust aerosol). These components are externally mixed to provide the aerosol model which in turn is used to calculate the aerosol optical depth (AOD). In the AATSR aerosol retrieval algorithm, the mixing of these components is decided by minimizing the error function given by the sum of the differences between measured and calculated path radiances at 3–4 wavelengths, where the path radiances are varied by varying the aerosol component mixing ratios. The continuous variation of the fine-mode components allows for the continuous variation of the fine-mode aerosol absorption. Assuming that the correct aerosol model (i.e. the correct mixing fractions of the four components) is selected during the retrieval process, also other aerosol properties could be computed such as the single scattering albedo (SSA). Implications of this assumption regarding the ratio of the weakly/strongly absorbing fine-mode fraction are investigated in this paper by evaluating the validity of the SSA thus obtained. The SSA is indirectly estimated for aerosol plumes with moderate-to-high AOD resulting from wildfires in Russia in the summer of 2010. Together with the AOD, the SSA provides the aerosol absorbing optical depth (AAOD). The results are compared with AERONET data, i.e. AOD level 2.0 and SSA and AAOD inversion products. The RMSE (root mean square error) is 0.03 for SSA and 0.02 for AAOD lower than 0.05. The SSA is further evaluated by comparison with the SSA retrieved from the Ozone Monitoring Instrument (OMI). The SSA retrieved from both instruments show similar features, with generally lower AATSR-estimated SSA values over areas affected by wildfires.

scholarly journals Aerosol radiative impact during the summer 2019 heatwave produced partly by an inter-continental Saharan dust outbreak – Part 2: Long-wave and net dust direct radiative effect

2021 ◽  
Author(s):  
Michaël Sicard ◽  
Carmen Córdoba-Jabonero ◽  
María-Ángeles López-Cayuela ◽  
Albert Ansmann ◽  
Adolfo Comerón ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Saharan Dust ◽  
Dust Particles ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Radiative Effect ◽  
Radiative Efficiency ◽  
Total Dust ◽  
Coarse Mode ◽  
Fine Mode

Abstract. This paper is the companion paper of Córdoba-Jabonero et al. (2021). It deals with the estimation of the longwave (LW) and net dust direct radiative effect (DRE) during the dust episode that occurred between 23 and 30 June, 2019, and coincided with a mega-heatwave. The analysis is performed at two European sites where polarized-Micro-Pulse Lidars ran continuously to retrieve the vertical distribution of the dust optical properties: Barcelona, Spain, 23–30 June, and Leipzig, Germany, 29–30 June. The radiative effect is computed with the GAME radiative transfer model separately for the fine- and coarse-mode dust. The instantaneous and daily radiative effect and radiative efficiency (DREff) are provided for the fine-mode, coarse-mode and total dust at the surface, top of the atmosphere (TOA) and in the atmosphere. The fine-mode daily LW DRE is small (< 6 % of the shortwave (SW) component) which makes the coarse-mode LW DRE the main modulator of the total dust net DRE. The coarse-mode LW DRE starts exceeding (in absolute values) the SW component in the middle of the episode which produces positive coarse-mode net DRE at both the surface and TOA. Such an unusual tendency is attributed to increasing coarse-mode size and surface temperature along the episode. This has the effect of reducing the SW cooling in Barcelona up to the point of reaching total dust net DRE positive (+0.9 W m−2) on one occasion at the surface and quasi-neutral (−0.6 W m−2) at TOA. When adding the LW component, the total dust SW radiative efficiency is reduced by a factor 1.6 at both surface (on average over the episode, the total dust net DREff is −54.1 W m−2 τ−1) and TOA (−37.3 W m−2 τ−1). A sensitivity study performed on the surface temperature and the air temperature in the dust layer, both linked to the heatwave and upon which the LW DRE strongly depends, shows that the heatwave contributed to reduce the dust net cooling effect at the surface and that it had nearly no effect at TOA. Its subsequent effect was thus to reduce the heating of the atmosphere produced by the dust particles.

scholarly journals Role of Coarse and Fine Mode Aerosols in MODIS AOD Retrieval: a case study over southern India

2014 ◽  
Vol 7 (4) ◽  
pp. 907-917 ◽  
Author(s):  
M. N. Sai Suman ◽  
H. Gadhavi ◽  
V. Ravi Kiran ◽  
A. Jayaraman ◽  
S. V. B. Rao
Keyword(s):  
Regression Line ◽  
Single Scattering ◽  
Southern India ◽  
Retrieval Algorithm ◽  
Aerosol Model ◽  
Coarse Mode ◽  
Modis Aod ◽  
Fine Mode ◽  
R Value ◽  
Moderate Resolution Imaging Spectroradiometer

Abstract. In the present study we compare the MODIS (Moderate Resolution Imaging Spectroradiometer) derived aerosol optical depth (AOD) data with that obtained from operating sky-radiometer at a remote rural location in southern India (Gadanki, 13.45° N, 79.18° E) from April 2008 to March 2011. While the comparison between total (coarse mode + fine mode) AODs shows correlation coefficient (R) value of about 0.71 for Terra and 0.77 for Aqua, if one separates the AOD into fine and coarse mode, the comparison becomes very poor, particularly for fine mode with an R value of 0.44 for both Terra and Aqua. The coarse mode AOD derived from MODIS and sky-radiometer compare better with an R value of 0.74 for Terra and 0.66 for Aqua. The seasonal variation is also well captured by both ground-based and satellite measurements. It is shown that both the total AOD and fine mode AOD are significantly underestimated with slope of regression line 0.75 and 0.35 respectively, whereas the coarse mode AOD is overestimated with a slope value of 1.28 for Terra. Similar results are found for Aqua where the slope of the regression line for total AOD and fine mode AOD are 0.72 and 0.27 whereas 0.95 for coarse mode. The fine mode fraction derived from MODIS data is less than one-half of that derived from the sky-radiometer data. Based on these observations and comparison of single scattering albedo observed using sky-radiometer with that of MODIS aerosol models, we argue that the selection of aerosol types used in the MODIS retrieval algorithm may not be appropriate particularly in the case of southern India. Instead of selecting a moderately absorbing aerosol model (as being done currently in the MODIS retrieval) a more absorbing aerosol model could be a better fit for the fine mode aerosols, while reverse is true for the coarse mode aerosols, where instead of using "dust aerosols" which is relatively absorbing type, usage of coarse sea-salt particles which is less absorbing is more appropriate. However, not all the differences could be accounted based on aerosol model, other factors like errors in retrieval of surface reflectance may also be significant in causing underestimation of AOD by MODIS.

scholarly journals BOREAS – a new MAX-DOAS profile retrieval algorithm for aerosols and trace gases

2018 ◽  
Vol 11 (12) ◽  
pp. 6833-6859 ◽  
Author(s):  
Tim Bösch ◽  
Vladimir Rozanov ◽  
Andreas Richter ◽  
Enno Peters ◽  
Alexei Rozanov ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Trace Gases ◽  
A Priori ◽  
Estimation Method ◽  
Optimal Estimation ◽  
Radiative Transfer Model ◽  
Retrieval Algorithm ◽  
Transfer Model ◽  
Night Time ◽  
Near Surface

Abstract. We present a new MAX-DOAS profiling algorithm for aerosols and trace gases, BOREAS, which utilizes an iterative solution method including Tikhonov regularization and the optimal estimation technique. The aerosol profile retrieval is based on a novel approach in which the absorption depth of O4 is directly used in order to retrieve extinction coefficient profiles instead of the commonly used perturbation theory method. The retrieval of trace gases is done with the frequently used optimal estimation method but significant improvements are presented on how to deal with wrongly weighted a priori constraints and for scenarios in which the a priori profile is inaccurate. Performance tests are separated into two parts. First, we address the general sensitivity of the retrieval to the example of synthetic data calculated with the radiative transfer model SCIATRAN. In the second part of the study, we demonstrate BOREAS profiling accuracy by validating the results with the help of ancillary measurements carried out during the CINDI-2 campaign in Cabauw, the Netherlands, in 2016. The synthetic sensitivity tests indicate that the regularization between measurement and a priori constraints is insufficient when knowledge of the true state of the atmosphere is poor. We demonstrate a priori pre-scaling and extensive regularization tests as a tool for the optimization of retrieved profiles. The comparison of retrieval results with in situ, ceilometer, NO2 lidar, sonde and long-path DOAS measurements during the CINDI-2 campaign always shows high correlations with coefficients greater than 0.75. The largest differences can be found in the morning hours, when the planetary boundary layer is not yet fully developed and the concentration of trace gases and aerosol, as a result of a low night-time boundary layer having formed, is focused in a shallow, near-surface layer.

scholarly journals Retrieval of aerosol absorption properties using the AATSR satellite instrument: a case study of wildfires over Russia 2010

2014 ◽  
Vol 7 (9) ◽  
pp. 9839-9868 ◽  
Author(s):  
E. Rodríguez ◽  
P. Kolmonen ◽  
T. H. Virtanen ◽  
L. Sogacheva ◽  
A.-M. Sundström ◽  
...  
Keyword(s):  
Optical Depth ◽  
Complex Refractive Index ◽  
Single Scattering ◽  
Radiative Transfer Model ◽  
Retrieval Algorithm ◽  
Transfer Model ◽  
Ozone Monitoring Instrument ◽  
Aerosol Model ◽  
Definition Of ◽  
Aerosol Properties

Abstract. The retrieval of aerosol properties from satellite data is based on the optimized fit of simulated and measured radiances at the top of the atmosphere (TOA). The simulations are made using a radiative transfer model with a variety of representative aerosol properties.The optimum fit is obtained for a certain combination of aerosol components, which are externally mixed to provide the aerosol model which in turn is used to calculate the aerosol optical depth (AOD). However, other aerosol properties could be provided. In the aerosol retrieval algorithm (ADV) applied to data from the Advanced Along Track Scanning Radiometer (AATSR), four aerosol components are used, each of which is defined by their (lognormal) size distribution and a complex refractive index. The fine mode fraction is a continuous mixture of weakly and strongly absorbing components which allows for the definition of any absorbing aerosol model within the specified limits. Hence, assuming that the correct aerosol model is selected during the retrieval process, also the single scattering albedo (SSA) should correctly be retrieved. In this paper we present the SSA retrieval using the ADV algorithm by application to wildfires over Russia in the summer of 2010. Together with the AOD, the SSA provides the aerosol absorbing optical depth (AAOD). The results are compared with AERONET data, i.e. AOD level 2.0 and SSA and AAOD inversion products. The RMSE is 0.03 for SSA and 0.02 for AAOD. The SSA is further evaluated by comparison with the SSA retrieved from the Ozone Monitoring Instrument (OMI). The SSA retrieved from both instruments show similar features, but the AATSR-retrieved SSA values over areas affected by wildfires are lower.

scholarly journals Sub-Mode Aerosol Volume Size Distribution and Complex Refractive Index from the Three-Year Ground-Based Measurements in Chengdu China

Atmosphere ◽  
2019 ◽  
Vol 10 (2) ◽  
pp. 46 ◽  
Author(s):  
Chi Zhang ◽  
Ying Zhang ◽  
Zhengqiang Li ◽  
Yongqian Wang ◽  
Hua Xu ◽  
...  
Keyword(s):  
Refractive Index ◽  
Size Distribution ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Complex Refractive Index ◽  
Observation Data ◽  
Aerosol Model ◽  
Coarse Mode ◽  
Fine Mode ◽  
Volume Size

Chengdu is a typical basin city of Southwest China with rare observations of remote sensing measurements. To assess the climate change and establish a region aerosol model, a deeper understanding of the separated volume size distribution (VSD) and complex refractive index (CRI) is required. In this study, we employed the sub-mode VSD and CRI in Chengdu based on the three years observation data to investigate the sub-mode characteristics and climate effects. The annual average fraction of the fine-mode aerosol optical depth (AODf) is 92%, which has the same monthly tendency as the total AOD. But the coarse-mode aerosol optical depth (AODc) has little variation in different months. There are four distinguishing modes of VSD in Chengdu; the median radii are 0.17 μm ± 0.05, 0.31 μm ± 0.12, 1.62 μm ± 0.45, 3.25 μm ± 0.99, respectively. The multi-year average and seasonal variations of fine- and coarse-mode VSD and CRI are also analyzed to characterize aerosols over this region. The fine-mode single scattering albedos (SSAs) are higher than the coarse-mode ones, which suggests that the coarse-mode aerosols have a stronger absorbing effect on solar light than the small-size aerosol particles in Chengdu.

scholarly journals Potential of Hyperspectral Thermal Infrared Spaceborne Measurements to Retrieve Ice Cloud Physical Properties: Case Study of IASI and IASI-NG

2020 ◽  
Vol 13 (1) ◽  
pp. 116
Author(s):  
Lucie Leonarski ◽  
Laurent C.-Labonnote ◽  
Mathieu Compiègne ◽  
Jérôme Vidot ◽  
Anthony J. Baran ◽  
...  
Keyword(s):  
Radiative Transfer ◽  
Signal To Noise Ratio ◽  
Thermal Infrared ◽  
Radiative Transfer Model ◽  
Retrieval Algorithm ◽  
Transfer Model ◽  
Water Path ◽  
Ice Cloud ◽  
Ice Water Path ◽  
Ice Water

The present study aims to quantify the potential of hyperspectral thermal infrared sounders such as the Infrared Atmospheric Sounding Interferometer (IASI) and the future IASI next generation (IASI-NG) for retrieving the ice cloud layer altitude and thickness together with the ice water path. We employed the radiative transfer model Radiative Transfer for TOVS (RTTOV) to simulate cloudy radiances using parameterized ice cloud optical properties. The radiances have been computed from an ice cloud profile database coming from global operational short-range forecasts at the European Center for Medium-range Weather Forecasts (ECMWF) which encloses the normal conditions, typical variability, and extremes of the atmospheric properties over one year (Eresmaa and McNally (2014)). We performed an information content analysis based on Shannon’s formalism to determine the amount and spectral distribution of the information about ice cloud properties. Based on this analysis, a retrieval algorithm has been developed and tested on the profile database. We considered the signal-to-noise ratio of each specific instrument and the non-retrieved atmospheric and surface parameter errors. This study brings evidence that the observing system provides information on the ice water path (IWP) as well as on the layer altitude and thickness with a convergence rate up to 95% and expected errors that decrease with cloud opacity until the signal saturation is reached (satisfying retrievals are achieved for clouds whose IWP is between about 1 and 300 g/m2).

scholarly journals Differences in ozone retrieval in MIPAS channels A and AB: a spectroscopic issue

2018 ◽  
Vol 11 (8) ◽  
pp. 4707-4723 ◽  
Author(s):  
Norbert Glatthor ◽  
Thomas von Clarmann ◽  
Gabriele P. Stiller ◽  
Michael Kiefer ◽  
Alexandra Laeng ◽  
...  
Keyword(s):  
Spectroscopic Data ◽  
Radiative Transfer Model ◽  
Retrieval Algorithm ◽  
Transfer Model ◽  
Forward Modelling ◽  
Hitran Database ◽  
Processing Scheme ◽  
Mixing Ratios ◽  
Level 1 ◽  
Standing Problem

Abstract. Discrepancies in ozone retrievals in MIPAS channels A (685–970 cm−1) and AB (1020–1170 cm−1) have been a long-standing problem in MIPAS data analysis, amounting to an interchannel bias (AB–A) of up to 8 % between ozone volume mixing ratios in the altitude range 30–40 km. We discuss various candidate explanations, among them forward model and retrieval algorithm errors, interchannel calibration inconsistencies and spectroscopic data inconsistencies. We show that forward-modelling errors as well as errors in the retrieval algorithm can be ruled out as an explanation because the bias can be reproduced with an entirely independent retrieval algorithm (GEOFIT), relying on a different forward radiative transfer model. Instrumental and calibration issues can also be refuted as an explanation because ozone retrievals based on balloon-borne measurements with a different instrument (MIPAS-B) and an independent level-1 data processing scheme produce a rather similar interchannel bias. Thus, spectroscopic inconsistencies in the MIPAS database used for ozone retrieval are practically the only reason left. To further investigate this issue, we performed retrievals using additional spectroscopic databases. Various versions of the HITRAN database generally produced rather similar channel AB–A differences. Use of a different database, namely GEISA-2015, led to similar results in channel AB, but to even higher ozone volume mixing ratios for channel A retrievals, i.e. to a reversal of the bias. We show that the differences in MIPAS channel A retrievals result from about 13 % lower air-broadening coefficients of the strongest lines in the GEISA-2015 database. Since the errors in line intensity of the major lines used in MIPAS channels A and AB are reported to be considerably lower than the observed bias, we posit that a major part of the channel AB–A differences can be attributed to inconsistent air-broadening coefficients as well. To corroborate this assumption we show some clearly inconsistent air-broadening coefficients in the HITRAN-2008 database. The interchannel bias in retrieved ozone amounts can be reduced by increasing the air-broadening coefficients of the lines in MIPAS channel AB in the HITRAN-2008 database by 6 %–8 %.

scholarly journals Comparison of measured brightness temperatures from SMOS with modelled ones from ORCHIDEE and H-TESSEL over the Iberian Peninsula

2015 ◽  
Vol 12 (12) ◽  
pp. 13019-13067
Author(s):  
A. Barella-Ortiz ◽  
J. Polcher ◽  
P. de Rosnay ◽  
M. Piles ◽  
E. Gelati
Keyword(s):  
Soil Moisture ◽  
Radiative Transfer ◽  
Iberian Peninsula ◽  
Land Surface ◽  
Function Analysis ◽  
Microwave Emission ◽  
Radiative Transfer Model ◽  
Retrieval Algorithm ◽  
Transfer Model ◽  
Brightness Temperatures

Abstract. L-Band radiometry is considered to be one of the most suitable techniques to estimate surface soil moisture by means of remote sensing. Brightness temperatures are key in this process, as they are the main input in the retrieval algorithm. The work exposed compares brightness temperatures measured by the Soil Moisture and Ocean Salinity (SMOS) mission to two different sets of modelled ones, over the Iberian Peninsula from 2010 to 2012. The latter were estimated using a radiative transfer model and state variables from two land surface models: (i) ORganising Carbon and Hydrology In Dynamic EcosystEms (ORCHIDEE) and (ii) Hydrology – Tiled ECMWF Scheme for Surface Exchanges over Land (H-TESSEL). The radiative transfer model used is the Community Microwave Emission Model (CMEM). A good agreement in the temporal evolution of measured and modelled brightness temperatures is observed. However, their spatial structures are not consistent between them. An Empirical Orthogonal Function analysis of the brightness temperature's error identifies a dominant structure over the South-West of the Iberian Peninsula which evolves during the year and is maximum in Fall and Winter. Hypotheses concerning forcing induced biases and assumptions made in the radiative transfer model are analysed to explain this inconsistency, but no candidate is found to be responsible for it at the moment. Further hypotheses are proposed at the end of the paper.

scholarly journals Refinement of the ice absorption spectrum in the visible using radiance profile measurements in Antarctic snow

2016 ◽  
Author(s):  
Ghislain Picard ◽  
Quentin Libois ◽  
Laurent Arnaud
Keyword(s):  
Absorption Coefficient ◽  
Fiber Optics ◽  
Estimation Method ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Snow Layer ◽  
Antarctic Snow ◽  
Order Of Magnitude ◽  
The Difference ◽  
The Antarctic

Abstract. Ice is a highly transparent material in the visible. According to the most widely used database (Warren and Brandt, 2008; IA2008), the ice absorption coefficient reaches values lower than 10−3 m−1 around 400 nm. These values were obtained from a radiance profile measured in a single snow layer at Dome C in Antarctica. We reproduced this experiment using a fiber optics inserted in the snow to record 56 profiles from which 70 homogeneous layers were identified. Applying the same estimation method on every layer yields 70 ice absorption spectra with a significant variability and overall larger than IA2008 by one order of magnitude. We devise another estimation method based on Bayesian inference. It reduces the statistical variability and confirms the higher absorption, around 2 × 10−2 m−1 near the minimum at 440 nm. We explore potential instrumental artifacts by developing a 3D radiative transfer model able to explicitly account for the presence of the fiber in the snow. The simulation results show that the radiance profile is indeed perturbed by the fiber intrusion but the error on the ice absorption estimate is not larger than a factor 2. This is insufficient to explain the difference between our new estimate and IA2008. Nevertheless, considering the number of profiles acquired for this study and other estimates from the Antarctic Muon and Neutrino Detector Array (AMANDA), we estimate that ice absorption values around 10−2 m−1 at the minimum are more likely than under 10−3 m−1. We provide a new estimate in the range 400–600 nm for future modeling of snow, cloud, and sea-ice optical properties. Most importantly we recommend that modeling studies take into account the large uncertainty of the ice absorption coefficient in the visible.

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