Guoyong Wen

THE I3RC: Bringing Together the Most Advanced Radiative Transfer Tools for Cloudy Atmospheres

The interaction of clouds with solar and terrestrial radiation is one of the most important topics of climate research. In recent years it has been recognized that only a full three-dimensional (3D) treatment of this interaction can provide answers to many climate and remote sensing problems, leading to the worldwide development of numerous 3D radiative transfer (RT) codes. The international Intercomparison of 3D Radiation Codes (I3RC), described in this paper, sprung from the natural need to compare the performance of these 3D RT codes used in a variety of current scientific work in the atmospheric sciences. I3RC supports intercomparison and development of both exact and approximate 3D methods in its effort to 1) understand and document the errors/limits of 3D algorithms and their sources; 2) provide “baseline” cases for future code development for 3D radiation; 3) promote sharing and production of 3D radiative tools; 4) derive guidelines for 3D radiative tool selection; and 5) improve atmospheric science education in 3D RT. Results from the two completed phases of I3RC have been presented in two workshops and are expected to guide improvements in both remote sensing and radiative energy budget calculations in cloudy atmospheres.

3-D aerosol-cloud radiative interaction observed in collocated MODIS and ASTER images of cumulus cloud fields

[1] Three-dimensional (3-D) aerosol-cloud interaction is examined by analyzing two images containing cumulus clouds in biomass-burning regions in Brazil. The research consists of two parts. The first part focuses on identifying 3-D cloud impacts on reflectances for the pixels selected for the MODIS aerosol retrieval based purely on observations. The second part of the research combines the observations with radiative transfer computations to identify key parameters in the 3-D aerosol-cloud interaction. We find that 3-D cloud-induced enhancement depends on the optical properties of nearby clouds as well as on wavelength. The enhancement is too large to be ignored. Associated bias error in one-dimensional (1-D) aerosol optical thickness retrieval ranges from 50 to 140% depending on wavelength and the optical depth of nearby clouds, as well as aerosol optical thickness. We caution the community to be prudent when applying 1-D approximations in computing solar radiation in clear regions adjacent to clouds or when using traditional retrieved aerosol optical thickness in aerosol indirect effect research.

Cloud three‐dimensional effects evidenced in Landsat spatial power spectra and autocorrelation functions

An analysis of nadir reflectivity spatial Fourier power spectra and autocorrelation functions for solar wavelengths and cloudy conditions is presented. The data come from Landsat thematic mapper (TM) observations, while Monte Carlo (MC) simulations are used to aid the interpretation of the observations and to examine sensitivity to various factors. We show that shortwave radiative processes produce consistent signatures in power spectra and autocorrelation functions. Power spectra take a variety of shapes not shown or explained in previous observational studies. We demonstrate that TM spectra can potentially be affected by radiative “roughening” at intermediate scales (∼1–5 km) and radiative “smoothing” at small scales (<1 km). These processes are wavelength-dependent, with systematic differences between conservative (for cloud droplets) TM band 4 (∼0.8 μm) and absorbing band 7 (∼2.2 μm). Band 7 exhibits more roughening and less smoothing than band 4 and faster decrease in autocorrelation. Roughening is more prevalent at large solar zenith angles due to optical and/or geometrical side illumination and shadowing. MC spectra illustrate that scale invariant optical depth fields can produce complex power spectra that take a variety of shapes under different conditions. Radiative roughening increases with decreasing single scattering albedo and increasing solar zenith angle (as in the observations). For low solar zenith angles, there is a clear shift in the radiative smoothing scale to smaller values as droplet absorption increases. Power spectra also show stronger decorrelations between optical depth and reflectivity when cloud top variations are more pronounced. Finally, it is shown that power spectral analysis is a useful tool for evaluating the skill of novel optical depth retrieval techniques in removing three-dimensional radiative effects. New techniques using inverse nonlocal independent pixel approximation and normalized difference of nadir reflectivity yield optical depth fields which better match the scale-by-scale variability of the true optical depth field.

Impact of Cumulus Cloud Spacing on Landsat Atmospheric Correction and Aerosol Retrieval

A Landsat 7 Enhanced Thematic Mapper Plus (ETM+) image acquired over the Southern Great Plains site of Department of Energys Atmospheric Radiation Measurement Program during the Atmospheric Radiation Measurement Enhanced Shortwave Experiment II is used to study the effect of clouds on reflected radiation in clear gaps in a cumulus cloud field. A technique using the spectral information of background and clouds is applied to identify clouds. The path radiance technique is used to extract the apparent path radiance in a clear region of the cumulus cloud field. The result shows that the apparent path radiance is enhanced by nearby clouds in both band 1 (blue) and band 3 (red) of ETM+. More importantly, the magnitude of the enhancement depends on the mean cloud-free distance in the clear patches. For cloud-free distances <0.5 km the enhancement of apparent path radiance is more than 0.025 and 0.015 (reflectance units) in band 1 and band 3, respectively, which corresponds to an enhancement of apparent aerosol optical thickness of ∼0.25 and ∼0.15. Neglecting of the three-dimensional cloud effect would lead to underestimates of surface reflectance of ∼0.025 and ∼0.015 in the blue and red band, respectively, if the true aerosol optical thickness is 0.2 and the surface reflectance is 0.05. The enhancement decreases exponentially with mean cloud-free distance, reaching asymptotic values of 0.09 for band 1 and 0.027 for band 3 at a mean cloud-free distance about 2 km. The asymptotic values are slightly larger than the mean path radiances retrieved from a completely clear region: 0.086 and 0.024 for the blue and red bands, respectively.

Correction of MODIS aerosol retrieval for 3D radiative effects in broken cloud fields

Retrieval of aerosol properties near clouds from reflected sunlight is rather challenging. Sunlight reflected from clouds can effectively enhance the reflectance from clear regions nearby. Ignoring cloud 3D radiative adjacency effects can lead to large biases in aerosol retrievals, resulting incorrect interpretation of satellite observations for aerosolcloud interaction. We have developed a simple model to compute cloud-induced radiance enhancement due to radiative interaction between boundary layer clouds and the molecular layer above it. Here we apply this method to broken cloud fields acquired from MODIS. We use CERES observations combined with radiative transfer models to derive visible narrowband radiative fluxes for estimating the radiance enhancement. With the corrected spectral radiances as input to the MODIS aerosol retrieval algorithm, we compute the corrected aerosol optical thicknesses (AOT). We compare the corrected AOT with the original ones to assess the performance of our approach. We furt...

Implications of Whole-Disc DSCOVR EPIC Spectral Observations for Estimating Earth’s Spectral Reflectivity Based on Low-Earth-Orbiting and Geostationary Observations

Earth’s reflectivity is among the key parameters of climate research. National Aeronautics and Space Administration (NASA)’s Earth Polychromatic Imaging Camera (EPIC) onboard National Oceanic and Atmospheric Administration (NOAA)’s Deep Space Climate Observatory (DSCOVR) spacecraft provides spectral reflectance of the entire sunlit Earth in the near backscattering direction every 65 to 110 min. Unlike EPIC, sensors onboard the Earth Orbiting Satellites (EOS) sample reflectance over swaths at a specific local solar time (LST) or over a fixed area. Such intrinsic sampling limits result in an apparent Earth’s reflectivity. We generated spectral reflectance over sampling areas using EPIC data. The difference between the EPIC and EOS estimates is an uncertainty in Earth’s reflectivity. We developed an Earth Reflector Type Index (ERTI) to discriminate between major Earth atmosphere components: clouds, cloud-free ocean, bare and vegetated land. Temporal variations in Earth’s reflectivity are mostly determined by clouds. The sampling area of EOS sensors may not be sufficient to represent cloud variability, resulting in biased estimates. Taking EPIC reflectivity as a reference, low-earth-orbiting-measurements at the sensor-specific LST tend to overestimate EPIC values by 0.8% to 8%. Biases in geostationary orbiting approximations due to a limited sampling area are between − 0.7 % and 12%. Analyses of ERTI-based Earth component reflectivity indicate that the disagreement between EPIC and EOS estimates depends on the sampling area, observation time and vary between − 10 % and 23%.

Spectral solar UV radiation and its variability and climate responses

UV radiation is an important component in the spectral solar irradiance for Earth’s climate system. UV radiation interacts with the atmosphere to form ozone layer that prevents the harmful radiation penetrating to the surface. The absorption of UV radiation depends on the wavelength. While UV-C is completely absorbed in the upper atmosphere, only a small fraction of UV-B penetrates to the surface, UV-A suffers almost no atmospheric absorption. Observations from Spectral Irradiance Monitor (SIM) onboard the Solar Radiation and Climate Experiment (SORCE) satellite show a rather large change in the UV radiation during the descending phase of solar cycle 23 as anticipated by the reconstructed spectral solar irradiance (SSI). Here we examine implications of SIM observations on Sun climate research. To understand the climate impact of variations in UV radiation requires a 3D global climate model. We use Goddard Institute for Space Studies (GISS) Global/Middle Atmosphere Model (GCMAM) to examine the climate resp...

3D radiative processes in satellite measurements of aerosol properties

Improving near-cloud aerosol measurements is important for better understanding two critical aspects of climate, aerosol-cloud interactions and the direct radiative effect of aerosols. This study aims at better understanding the uncertainties that arise in satellite measurement of aerosols because current data interpretation methods don’t consider 3D radiative processes. For this, the paper presents a statistical analysis of a yearlong global dataset of co-located MODIS and CALIOP observations and theoretical simulations. The results reveal that CALIOP-observed particle size and optical thickness, and MODIS-observed solar reflectance increase systematically in a wide zone around clouds. It is estimated that near-cloud changes in particle populations (including aerosols and undetected cloud particles) are responsible for roughly two thirds of the observed increase in 0.55 μm MODIS reflectance. The results also indicate that 3D radiative processes play an important role in near-cloud reflectance enhancement...