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At least 307 records · Page 17

Bridging New Observational Capabilities and Process-Level Simulation: Insights into Aerosol Roles in the Earth System

The spatial distribution of ambient aerosol particles significantly impacts aerosol–radiation–cloud interactions, which contribute to the largest uncertainty in global anthropogenic radiative forcing estimations. However, the atmospheric boundary layer and lower free troposphere have not been adequately sampled in terms of spatiotemporal resolution, hindering a comprehensive characterization of various atmospheric processes and impeding our understanding of the Earth system. To address this research data gap, we have leveraged the development of uncrewed aerial systems (UAS) and advanced measurement techniques to obtain mesoscale spatial data on aerosol microphysical and optical properties around the U.S. Southern Great Plains (SGP) atmospheric observatory. Our study also benefits from state-of-the-art laboratory facilities that include three-dimensional molecular imaging techniques enabled by secondary ion mass spectrometry and nanogram-level chemical composition analysis via micronebulization aerosol mass spectrometry. Through our study, we have developed a framework for observation–modeling integration, enabling an examination of how various assumptions about the organic–inorganic components mixing state, inferred from chemical analysis, affect clouds and radiation in observation-constrained model simulations. By integrating observational constraints (derived from offline chemical analysis of the aerosol surface using collected samples) with in situ UAS observations, we have identified a prominent role of organic-enriched nanometer layers located at the surface of aerosol particles in determining profiles of aerosol optical and hygroscopic properties over the SGP observatory. Furthermore, we have improved the agreement between predicted clouds and ground-based cloud lidar measurements. This UAS–model–laboratory integration exemplifies how these new advanced capabilities can significantly enhance our understanding of aerosol–radiation–cloud interactions.

54 ENVIRONMENTAL SCIENCES↗

Evaluating Models' Response of Tropical Low Clouds to SST Forcings Using CALIPSO Observations

Recent studies have shown that, in response to a surface warming, the marine tropical low-cloud cover (LCC) as observed by passive-sensor satellites substantially decreases, therefore generating a smaller negative value of the top-of-the-atmosphere (TOA) cloud radiative effect (CRE). Here we study the LCC and CRE interannual changes in response to sea surface temperature (SST) forcings in the GISS model E2 climate model, a developmental version of the GISS model E3 climate model, and in 12 other climate models, as a function of their ability to represent the vertical structure of the cloud response to SST change against 10 years of CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations) observations. The more realistic models (those that satisfy the observational constraint) capture the observed interannual LCC change quite well ([delta]LCC]/[delta]SST= -3.49±1.01%K [negative 1 superscript] vs. [delta]LCC/[delta]SST[subscript obs]= -3.59±0.28%K[negative 1 superscript]) while the others largely underestimate it ([delta]LCC/[delta]SST= -1.32±1.28%K[negative 1 superscript]). Consequently, the more realistic models simulate more positive shortwave (SW) feedback ([delta]CRE/[delta]SST=2.60±1.13Wm[negative 2 superscript] K[negative 1 superscript]) than the less realistic models (CRE/SST=0.87±2.63Wm2K1), in better agreement with the observations ([delta]CRE/[delta]SST[subscript obs]=3±0.26Wm[negative 2 superscript] K[negative 1 superscript] ), although slightly underestimated. The ability of the models to represent moist processes within the planetary boundary layer (PBL) and produce persistent stratocumulus (Sc) decks appears crucial to replicating the observed relationship between clouds, radiation and surface temperature. This relationship is different depending on the type of low clouds in the observations. Over stratocumulus regions, cloud-top height increases slightly with SST, accompanied by a large decrease in cloud fraction, whereas over trade cumulus (Cu) regions, cloud fraction decreases everywhere, to a smaller extent.

low clouds↗

Small-Scale Drop Size Variability: Impact on Estimation of Cloud Optical Properties

Most cloud radiation models and conventional data processing techniques assume that the mean number of drops of a given radius is proportional to volume. The analysis of microphysical data on liquid water drop sizes shows that, for sufficiently small volumes, this proportionality breaks down; the number of cloud drops of a given radius is instead proportional to the volume raised to a drop size-dependent nonunit power. The coefficient of proportionality, a generalized drop concentration, is a function of the drop size. For abundant small drops the power is unity as assumed in the conventional approach. However, for rarer large drops, it falls increasingly below unity. This empirical fact leads to drop clustering, with the larger drops exhibiting a greater degree of clustering. The generalized drop concentration shows the mean number of drops per cluster, while the power characterizes the occurrence frequency of clusters. With a fixed total number of drops in a cloud, a decrease in frequency of clusters is accompanied by a corresponding increase in the generalized concentration. This initiates a competing process missed in the conventional models: an increase in the number of drops per cluster enhances the impact of rarer large drops on cloud radiation while a decrease in the frequency suppresses it. Because of the nonlinear relationship between the number of clustered drops and the volume, these two opposite tendencies do not necessarily compensate each other. The data analysis suggests that clustered drops likely have a stronger radiative impact compared to their unclustered counterpart; ignoring it results in underestimation of the contribution from large drops to cloud horizontal optical path.

Knyazikhin, Y.↗

Surface Radiation Budget (SRB) Release 2.5 QC Longwave 3 hourly Data in Native Format (SRB_REL2.5_QCLW_3HRLY)

This data set contains average surface downward longwave flux, surface net longwave flux, and surface longwave cloud radiative forcing at three hourly intervals for each day for the entire glob between 07/01/1983 and 06/30/2005. These LW surface radiative parameters were derived with the Quality-Check LW (QCLW) algorithm of the NASA World Climate Research Programme/Global Energy and Water-Cycle Experiment (WCRP/GEWEX) Surface Radiation Budget (SRB) Project. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2005-06-30] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=1 degree; Longitude_Resolution=Ranges from 1 degree (tropics and subtropics) to 120 degrees (the poles).; Temporal_Resolution=3-hourly; Temporal_Resolution_Range=3-hourly].

SURFACE DOWNWARD LONGWAVE FLUX↗

ENSO Tropical Cloud and TOA radiative signatures from the CERES observation

The Clouds and the Earth's Radiant Energy System (CERES) project now has over 15 years accurately observed top-of-the-atmosphere (TOA) flux record for climate monitoring and diagnostic studies. The CERES flux-by-cloud-type dataset, which contains cloud properties and radiative fluxes for 42 cloud types sorted by cloud top pressure and cloud optical depth, is used to investigate the clouds and their associated TOA (top-of-the-atmosphere) fluxes changes over the tropical area during ENSO events during the observed period. Unlike past studies, this study shows the impact of ENSO on cloud properties like optical depth, cloud top effective pressure and temperature and TOA LW and SW fluxes for each sub cloud type. The study reveals the detailed contributions from different cloud types for radiative characteristics during different phases of ENSO. This is especially important for very small net TOA radiative balance due to the cancellation of the fluxes from different cloud types. To further demonstrate the usefulness of this dataset, NCAR Community Atmosphere Model (CAM) is used to simulate the cloud and radiative changes during the period. The model cloud properties are converted to MODIS like cloud properties using modified MODIS simulator. The dataset serves as a more stringent validation of the model for cloud properties and radiative fluxes.

Moguo Sun↗

Quantifying and attributing time step sensitivities in present-day climate simulations conducted with EAMv1

Abstract. This study assesses the relative importance of time integration error in present-day climate simulations conducted with the atmosphere component of the Energy Exascale Earth System Model version 1 (EAMv1) at 1∘ horizontal resolution. We show that a factor-of-6 reduction of time step size in all major parts of the model leads to significant changes in the long-term mean climate. Examples of changes in 10-year mean zonal averages include the following: up to 0.5 K of warming in the lower troposphere and cooling in the tropical and subtropical upper troposphere, 1 %–10 % decreases in relative humidity throughout the troposphere, and 10 %–20 % decreases in cloud fraction in the upper troposphere and decreases exceeding 20 % in the subtropical lower troposphere. In terms of the 10-year mean geographical distribution, systematic decreases of 20 %–50 % are seen in total cloud cover and cloud radiative effects in the subtropics. These changes imply that the reduction of temporal truncation errors leads to a notable although unsurprising degradation of agreement between the simulated and observed present-day climate; to regain optimal climate fidelity in the absence of those truncation errors, the model would require retuning. A coarse-grained attribution of the time step sensitivities is carried out by shortening time steps used in various components of EAM or by revising the numerical coupling between some processes. Our analysis leads to the finding that the marked decreases in the subtropical low-cloud fraction and total cloud radiative effect are caused not by the step size used for the collectively subcycled turbulence, shallow convection, and stratiform cloud macrophysics and microphysics parameterizations but rather by the step sizes used outside those subcycles. Further analysis suggests that the coupling frequency between the subcycles and the rest of EAM significantly affects the subtropical marine stratocumulus decks, while deep convection has significant impacts on trade cumulus. The step size of the cloud macrophysics and microphysics subcycle itself appears to have a primary impact on cloud fraction in the upper troposphere and also in the midlatitude near-surface layers. Impacts of step sizes used by the dynamical core and the radiation parameterization appear to be relatively small. These results provide useful clues for future studies aiming at understanding and addressing the root causes of sensitivities to time step sizes and process coupling frequencies in EAM. While this study focuses on EAMv1 and the conclusions are likely model-specific, the presented experimentation strategy has general value for weather and climate model development, as the methodology can help researchers identify and understand sources of time integration error in sophisticated multi-component models.

54 ENVIRONMENTAL SCIENCES↗

Aerosol Absorption and Radiative Forcing

We present a comprehensive examination of aerosol absorption with a focus on evaluating the sensitivity of the global distribution of aerosol absorption to key uncertainties in the process representation. For this purpose we extended the comprehensive aerosol-climate model ECHAM5-HAM by effective medium approximations for the calculation of aerosol effective refractive indices, updated black carbon refractive indices, new cloud radiative properties considering the effect of aerosol inclusions, as well as by modules for the calculation of long-wave aerosol radiative properties and instantaneous aerosol forcing. The evaluation of the simulated aerosol absorption optical depth with the AERONET sun-photometer network shows a good agreement in the large scale global patterns. On a regional basis it becomes evident that the update of the BC refractive indices to Bond and Bergstrom (2006) significantly improves the previous underestimation of the aerosol absorption optical depth. In the global annual-mean, absorption acts to reduce the shortwave anthropogenic aerosol top-of-atmosphere (TOA) radiative forcing clear-sky from -0.79 to -0.53 W m(sup -2) (33%) and all-sky from -0.47 to -0.13W m(sup -2 (72%). Our results confirm that basic assumptions about the BC refractive index play a key role for aerosol absorption and radiative forcing. The effect of the usage of more accurate effective medium approximations is comparably small. We demonstrate that the diversity in the AeroCom land-surface albedo fields contributes to the uncertainty in the simulated anthropogenic aerosol radiative forcings: the usage of an upper versus lower bound of the AeroCom land albedos introduces a global annual-mean TOA forcing range of 0.19W m(sup -2) (36%) clear-sky and of 0.12W m(sup -2) (92%) all-sky. The consideration of black carbon inclusions on cloud radiative properties results in a small global annual-mean all-sky absorption of 0.05W m(sup -2) and a positive TOA forcing perturbation of 0.02W m(sup -2). The long-wave aerosol radiative effects are small for anthropogenic aerosols but become of relevance for the larger natural dust and sea-salt aerosols.

Stier, Philip↗

Cloud and Radiation Studies during SAFARI 2000

Though the emphasis of the Southern Africa Regional Science Initiative 2000 (SAFARI-2000) dry season campaign was largely on emission sources and transport, the assemblage of aircraft (including the high altitude NASA ER-2 remote sensing platform and the University of Washington CV-580, UK MRF C130, and South African Weather Bureau JRA in situ aircrafts) provided a unique opportunity for cloud studies. Therefore, as part of the SAFARI initiative, investigations were undertaken to assess regional aerosol-cloud interactions and cloud remote sensing algorithms. In particular, the latter part of the experiment concentrated on marine boundary layer stratocumulus clouds off the southwest coast of Africa. Associated with cold water upwelling along the Benguela current, the Namibian stratocumulus regime has received limited attention but appears to be unique for several reasons. During the dry season, outflow of continental fires and industrial pollution over this area can be extreme. From below, upwelling provides a rich nutrient source for phytoplankton (a source of atmospheric sulphur through DMS production as well as from decay processes). The impact of these natural and anthropogenic sources on the microphysical and optical properties of the stratocumulus is unknown. Continental and Indian Ocean cloud systems of opportunity were also studied during the campaign. Aircraft flights were coordinated with NASA Terra Satellite overpasses for synergy with the Moderate Resolution Imaging Spectroradiometer (MODIS) and other Terra instruments. An operational MODIS algorithm for the retrieval of cloud optical and physical properties (including optical thickness, effective particle radius, and water path) has been developed. Pixel-level MODIS retrievals (11 km spatial resolution at nadir) and gridded statistics of clouds in th SAFARI region will be presented. In addition, the MODIS Airborne Simulator flown on the ER-2 provided high spatial resolution retrievals (50 m at nadir). These retrievals will be discussed and compared with in situ observations.

Platnick, Steven↗

Surface Radiation Budget (SRB) Release 2.5 QC Longwave 3 Hourly Monthly Data in Native Format(SRB_REL2.5_QCLW_3HRLY_MONTHLY)

These surface radiation budget data sets include downward fluxes and cloud radiative properties for the entire globe between 07/01/1983 and 06/30/2005. These parameters were parameters derived with the Quality-Check LW (QCLW) algorithm of the NASA World Climate Research Programme /Global Energy and Water-Cycle Experiment (WCRP/GEWEX) Surface Radiation Budget (SRB) Project. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2004-12-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=1 degree; Longitude_Resolution=Ranges from 1 degree in the tropics to 120 degrees at the poles; Temporal_Resolution=3 hourly averaged monthly].

CLOUD FORCING↗

A GCM parameterization for the shortwave radiative properties of water clouds

A new parameterization was developed for predicting the shortwave radiative properties of water clouds, suitable for inclusion in general circulation models (GCMs). The parameterization makes use of the simple relationships found by Slingo and Schrecker, giving the three input parameters required to calculate the cloud radiative properties (the optical depth, single scatter albedo and asymmetry parameter) in terms of the liquid water path and equivalent radius of the drop size distribution. The input parameters are then used to derive the cloud radiative properties, using standard two-stream equations for a single layer. The relationships were originally derived for fairly narrow spectral bands but it was found that it is possible to average the coefficients so as to use a much smaller number of bands, without sacrificing accuracy in calculating the cloud radiative properties. This makes the parameterization fast enough to be included in GCMs. The parameterization was programmed into the radiation scheme used in the U.K. Meteorological Office GCM. This scheme and the 24 band Slingo/Schrecker scheme were compared with each other and with observations, using a variety of published datasets. There is good agreement between the two schemes for both cloud albedo and absorption, even when only four spectral bands are employed in the GCM.

Slingo, A.↗

Use of Physics to Improve Solar Forecast: Part II, Machine Learning and Model Interpretability

Machine learning (ML) models have been applied to forecast solar energy; however, they often lack clarity of interpretability and underlying physics. This work addresses such challenges by developing a hierarchy of ML models that gradually introduce predictors to improve the forecast accuracy based on a physics-based framework. Three ML models (ARIMA, LSTM, and XGBoost) are examined and compared with four physics-informed persistence models reported in Part I and the simple persistence model to assess the improvement of different models. The 7-year measurements at the U.S. Department of Energy's Atmospheric Radiation Measurement's Southern Great Plains Central Facility site are used for forecasts and evaluations. The results reveal that the step-by-step introduction of predictors leads to different improvements for models at different hierarchical levels. Comparison of the ML models with persistence models shows that LSTM and XGBoost outperform all the persistence models, with LSTM having the overall best performance; however, ARIMA underperforms the four physics-informed persistence models. This study demonstrates the importance and utility of incorporating physics into ML models in improving forecast accuracy by introducing a hierarchy of physics-based predictors, distinguishing predictor contributions, and enhancing the ML interpretability. The combined use of Global Horizontal Irradiance (GHI) and Direct Normal Irradiance (DNI) significantly improves the forecast accuracy compared to using individual irradiances alone because the pair contains more information on cloud-radiation interactions.

interpretability↗

Examining Cloud Feedback Components in the Simple Cloud-Resolving E3SM Atmosphere Model (SCREAM)

Cloud feedback remains the main source of uncertainty in climate sensitivity estimated by global climate models (GCMs), largely because subgrid cloud responses are parameterized in GCMs due to their coarse resolution. Here, this study examines cloud feedback in the global 3.25-km Simple Cloud-Resolving Energy Exascale Earth System Model (E3SM) Atmosphere Model (SCREAM 3 km) through a pair of 1-yr atmosphere-only simulations with control and +4-K sea surface temperature perturbations. SCREAM 3 km produces a positive cloud feedback that falls within but at the upper end of the range of Coupled Model Intercomparison Project phase 5 (CMIP5) and CMIP phase 6 (CMIP6) models and expert judgment. The positive cloud feedback arises from positive contributions from both high- and low-level clouds, with increases in high-cloud altitude and decreases in low-cloud amount and optical depth playing key roles. The stronger-than-CMIP-average feedback is mainly attributable to the high-cloud altitude feedback, owing to cloud tops rising nearly isothermally in SCREAM 3 km. The positive low-cloud amount feedback is weaker in SCREAM than in GCMs because estimated inversion strength (EIS) increases more dramatically with warming. A coarser 12-km resolution version of SCREAM exhibits a weaker positive cloud feedback than SCREAM 3 km, mainly because its low-cloud-radiative flux is more sensitive to EIS, leading to a stronger negative low-cloud amount feedback. With this process-level assessment of cloud feedback, this study reveals where SCREAM aligns with and diverges from conventional GCMs and expert assessment, providing insights to inform further model improvement and future expert assessment.

Cloud radiative effects↗

3D Radiative Transfer in Cloudy Atmospheres

3D cloud radiative community has matured enough to prepare a volume on 3D radiative transfer in cloudy atmosphere that will be published by Springer-Verlag this year. Many leading 3D radiative transfer scientists are amongst the co-authors of the book. The book starts with the basic 3D radiative transfer problem, describes its solutions and models, discusses the effects of cloud inhomogeneity for remote sensing, addresses climate problems in realistic atmosphere and studies cloud-vegetation interactions.

Marshak, Alexander↗

On the net radiative effectiveness of clouds

The net effect of clouds on the top-of-the-atmosphere energy fluxes was investigated by measuring the relative magnitudes of the effects of clouds on outgoing longwave radiation and on reflected solar radiation. The ratio between these two effects, expressed in terms of the cloud factor angle which measures the departure of the net radiative effect of clouds from a neutral effect, was estimated in two independent ways, using data from the Earth Radiation Budget Experiment. Both estimates of the cloud radiative effectiveness indicate that the global average net radiative effect of today's clouds is cooling, with the decrease in the absorbed solar radiation being greater than the decrease in the outgoing longwave radiation.

Hartmann, Dennis L.↗

Current and Future Perspectives of Aerosol Research at NASA Goddard Space Flight Center

Aerosols are tiny atmospheric particles that are emitted from various natural and anthropogenic sources. They affect climate through direct and indirect interactions with solar and thermal radiation, clouds, and atmospheric circulation (Solomon et al. 2007). The launch of a variety of sophisticated satellite-based observing systems aboard the Terra, Aqua, Aura, SeaWiFS (see appendix for all acronym expansions), CALIPSO, and other satellites in the late 1990s to mid-2000s through the NASA EOS and other U.S. and non-U.S. programs ushered in a golden era in aerosol research. NASA has been a leader in providing global aerosol characterizations through observations from satellites, ground networks, and field campaigns, as well as from global and regional modeling. AeroCenter (http://aerocenter.gsfc.nasa.gov/), which was formed in 2002 to address the many facets of aerosol research in a collaborative manner, is an interdisciplinary union of researchers (~200 members) at NASA GSFC and other nearby institutions, including NOAA, several universities, and research laboratories. AeroCenter hosts a web-accessible regular seminar series and an annual meeting to present up-to-date aerosol research, including measurement techniques; remote sensing algorithms; modeling development; field campaigns; and aerosol interactions with radiation, clouds, precipitation, climate, biosphere, atmospheric chemistry, air quality, and human health. The 2013 annual meeting was held at the NASA GSFC Visitor Center on 31 May 2013, which coincided with the seventh anniversary of the passing of Yoram Kaufman, a modern pioneer in satellite-based aerosol science and the founder of AeroCenter. The central theme of this year's meeting was "current and future perspectives" of NASA's aerosol science and satellite missions.

aerocenter↗

How Difficult is it to Reduce Low-Level Cloud Biases With the Higher-Order Turbulence Closure Approach in Climate Models?

Low-level clouds cover nearly half of the Earth and play a critical role in regulating the energy and hydrological cycle. Despite the fact that a great effort has been put to advance the modeling and observational capability in recent years, low-level clouds remains one of the largest uncertainties in the projection of future climate change. Low-level cloud feedbacks dominate the uncertainty in the total cloud feedback in climate sensitivity and projection studies. These clouds are notoriously difficult to simulate in climate models due to its complicated interactions with aerosols, cloud microphysics, boundary-layer turbulence and cloud dynamics. The biases in both low cloud coverage/water content and cloud radiative effects (CREs) remain large. A simultaneous reduction in both cloud and CRE biases remains elusive. This presentation first reviews the effort of implementing the higher-order turbulence closure (HOC) approach to representing subgrid-scale turbulence and low-level cloud processes in climate models. There are two HOCs that have been implemented in climate models. They differ in how many three-order moments are used. The CLUBB are implemented in both CAM5 and GDFL models, which are compared with IPHOC that is implemented in CAM5 by our group. IPHOC uses three third-order moments while CLUBB only uses one third-order moment while both use a joint double-Gaussian distribution to represent the subgrid-scale variability. Despite that HOC is more physically consistent and produces more realistic low-cloud geographic distributions and transitions between cumulus and stratocumulus regimes, GCMs with traditional cloud parameterizations outperform in CREs because tuning of this type of models is more extensively performed than those with HOCs. We perform several tuning experiments with CAM5 implemented with IPHOC in an attempt to produce the nearly balanced global radiative budgets without deteriorating the low-cloud simulation. One of the issues in CAM5-IPHOC is that cloud water content is much higher than in CAM5, which is combined with higher low-cloud coverage to produce larger shortwave CREs in some low-cloud prevailing regions. Thus, the cloud-radiative feedbacks are exaggerated there. The turning exercise is focused on microphysical parameters, which are also commonly used for tuning in climate models. The results will be discussed in this presentation.

Xu, Kuan-Man↗

The Effects of an Absorbing Smoke Layer on MODIS Marine Boundary Layer Cloud Optical Property Retrievals and Radiative Forcing

Clouds, aerosols, and their interactions are widely considered to be key uncertainty components in our current understanding of the Earth's atmosphere and radiation budget. The work presented here is focused on the quasi-permanent marine boundary layer . (MBL) clouds off the southern Atlantic coast of Africa and the effects on MODIS cloud optical property retrievals (MOD06) of an overlying absorbing smoke layer. During much of August and September, a persistent smoke layer resides over this region, produced from extensive biomass burning throughout the southern African savanna. The resulting absorption, which increases with decreasing wavelength, potentially introduces biases into the MODIS cloud optical property retrievals of the underlying MBL clouds. This effect is more pronounced in the cloud optical thickness retrievals, which over ocean are derived from the wavelength channel centered near 0.86 micron (effective particle size retrievals are derived from the longer-wavelength near-IR channels at 1.6, 2.1, and 3.7 microns). Here, the spatial distributions of the scalar statistics of both the cloud and aerosol layers are first determined from the CALIOP 5 km layer products. Next, the MOD06 look-up tables (LUTs) are adjusted by inserting an absorbing smoke layer of varying optical thickness over the cloud. Retrievals are subsequently performed for a subset of MODIS pixels collocated with the CALIOP ground track, using smoke optical thickness from the CALIOP 5km aerosol layer product to select the appropriate LUT. The resulting differences in cloud optical property retrievals due to the inclusion of the smoke layer in the LUTs will be examined. In addition, the direct radiative forcing of this smoke layer will be investigated from the perspective of the cloud optical property retrieval differences.

Meyer, Kerry↗