ALBERT

Description: Retrieval of semitransparent ice cloud properties from the Visible Infrared Imaging Radiometer Suite (VIIRS) satellite sensor on the Suomi National Polar-orbiting Partnership (S-NPP) and NOAA-20 platforms is challenging due to the absence of infrared (IR) water vapor and CO2 absorption channels. However, on these platforms, there is a companion sensor called the Crosstrack Infrared Sounder (CrIS) that provides these spectral measurements but at a lower spatial resolution (∼15 km at nadir). To mitigate the lack of VIIRS spectral measurements in these IR absorption channels, recent studies suggest an approach to supplement VIIRS measurements by fusion of the imager and sounder data. In particular, Weisz et al. (2017) demonstrate a method to construct IR water vapor and CO2 absorption channel radiances for VIIRS at 750 m spatial resolution. Based on these constructed channels for both S-NPP and NOAA-20, this study evaluates three cloud properties – cloud mask, cloud thermodynamic phase, and cloud top height – through comparison to the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation/Cloud-Aerosol Lidar with Orthogonal Polarization (CALIPSO/CALIOP) V4-20 cloud layer products and Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 6.1 cloud top products. Each of these cloud properties shows improvement with the use of these constructed channel radiances. The major improvement for the cloud mask is found over polar regions, where the correct cloud detection percentage increases due to a decrease in missed clouds and/or false detection. For cloud thermodynamic phase, the ice cloud fraction increases over non-polar regions and the combined liquid water and ice cloud discrimination improves in comparison with CALIPSO. The retrieved cloud top height for semitransparent ice clouds increases over non-polar regions and tends to be closer to the true CALIPSO/CALIOP cloud top height. Moreover, the uncertainty of cloud top height retrievals decreases globally for these clouds.

Description: For nearly 2 decades we have been quantitatively observing the Earth's aerosol system from space at one or two times of the day by applying the Dark Target family of algorithms to polar-orbiting satellite sensors, particularly MODIS and VIIRS. With the launch of the Advanced Himawari Imager (AHI) and the Advanced Baseline Imagers (ABIs) into geosynchronous orbits, we have the new ability to expand temporal coverage of the traditional aerosol optical depth (AOD) to resolve the diurnal signature of aerosol loading during daylight hours. The Korean–United States Air Quality (KORUS-AQ) campaign taking place in and around the Korean peninsula during May–June 2016 initiated a special processing of full-disk AHI observations that allowed us to make a preliminary adoption of Dark Target aerosol algorithms to the wavelengths and resolutions of AHI. Here, we describe the adaptation and show retrieval results from AHI for this 2-month period. The AHI-retrieved AOD is collocated in time and space with existing AErosol RObotic NETwork stations across Asia and with collocated Terra and Aqua MODIS retrievals. The new AHI AOD product matches AERONET, and the standard MODIS product does as well, and the agreement between AHI and MODIS retrieved AOD is excellent, as can be expected by maintaining consistency in algorithm architecture and most algorithm assumptions. Furthermore, we show that the new product approximates the AERONET-observed diurnal signature. Examining the diurnal patterns of the new AHI AOD product we find specific areas over land where the diurnal signal is spatially cohesive. For example, in Bangladesh the AOD increases by 0.50 from morning to evening, and in northeast China the AOD decreases by 0.25. However, over open ocean the observed diurnal cycle is driven by two artifacts, one associated with solar zenith angles greater than 70∘ that may be caused by a radiative transfer model that does not properly represent the spherical Earth and the other artifact associated with the fringes of the 40∘ glint angle mask. This opportunity during KORUS-AQ provides encouragement to move towards an operational Dark Target algorithm for AHI. Future work will need to re-examine masking including snow mask, re-evaluate assumed aerosol models for geosynchronous geometry, address the artifacts over the ocean, and investigate size parameter retrieval from the over-ocean algorithm.

Description: We found that cloud spatial structure manifests itself as spectral signature in shortwave irradiance fields – specifically in transmittance and net horizontal photon transport in the visible and near-ultraviolet wavelength range. In this paper, we demonstrate this through radiative transfer calculations with cloud imagery from a field experiment, and show that such three-dimensional effects may occur on scales up to 60 km. Neglecting net horizontal photon transport leads to a transmittance bias on the order of ±12–19 % even at the relatively coarse spatial resolution of 20 km, and of more than ±50 % for 1 km. This poses a problem for radiative energy budget estimates from space because the bias for any pixel depends on its spatial context in a non-trivial way. The key for solving this problem may lie in the spectral dimension, since we found a robust correlation between the magnitude of net horizontal photon transport (H) and its spectral dependence (slope). It is scale-invariant and holds for the entire pixel population of a domain. This was at first surprising given the large degree of spatial inhomogeneity, but seems to be valid for any cloud field. We prove that the underlying physical mechanism for this phenomenon is molecular scattering in conjunction with cloud inhomogeneity. On this basis, we developed a simple parameterization through a single parameter ε, which quantifies the characteristic spectral signature of spatial heterogeneities. In a companion paper, we will show that it is accompanied by spectral radiance perturbations, which can be detected from multi-spectral imagers and may be translated into bias reductions for cloud radiative effect estimates in the future.

Description: For nearly two decades we have been quantitatively observing the Earth’s aerosol system from space at one or two times of the day by applying the Dark Target family of algorithms to polar-orbiting satellite sensors, particularly MODIS and VIIRS. With the launch of the Advanced Himawari Imager (AHI) and the Advanced Baseline Imagers (ABIs) into geosynchronous orbits, we have the new ability to expand temporal coverage of the traditional aerosol optical depth (AOD) to resolve the diurnal signature of aerosol loading during daylight hours. Here, we describe how the Dark Target aerosol algorithms are adopted for the wavelengths and resolutions of AHI, and show retrieval results from AHI for a two-month period of May–June 2016. The AHI-retrieved AOD is collocated in time and space with existing AErosol RObotic NETwork stations across Asia and with collocated Terra- and Aqua-MODIS retrievals. The new AHI AOD product matches AERONET, as well as does the standard MODIS product, and the agreement between AHI and MODIS retrieved AOD is excellent, as can be expected by maintaining consistency in algorithm architecture and most algorithm assumptions. Furthermore, we show that the new product approximates the AERONET-observed diurnal signature. Examining the diurnal patterns of the new AHI AOD product we find specific areas over land where the diurnal signal is spatially cohesive. For example, in Bangladesh, the AOD increases by 0.50 from morning to evening, and in northeast China, the AOD decreases by 0.25. However, over the open ocean the observed diurnal cycle is driven by two artifacts, one associated with solar zenith angles greater than 70° that may be caused by a radiative transfer model that does not properly represent spherical Earth, and the other artifact associated with the fringes of the 40° glint angle mask. Future work to make the Dark Target AHI algorithm operational will need to re-examine masking including snow mask, re-evaluate assumed aerosol models for geosynchronous geometry, address the artifacts over the ocean and investigate size parameter retrieval from the over-ocean algorithm.

Description: Despite its importance as one of the key radiative properties that determines the impact of upper tropospheric clouds on the radiation balance, ice cloud optical thickness (IOT) has proven to be one of the more challenging properties to retrieve from space-based remote sensing measurements. In particular, optically thin upper tropospheric ice clouds (cirrus) have been especially challenging due to their tenuous nature, extensive spatial scales, and complex particle shapes and light-scattering characteristics. The lack of independent validation motivates the investigation presented in this paper, wherein systematic biases between MODIS Collection 5 (C5) and CALIOP Version 3 (V3) unconstrained retrievals of tenuous IOT (

Description: In this paper, we used cloud imagery from a NASA field experiment in conjunction with three-dimensional radiative transfer calculations to show that cloud spatial structure manifests itself as a spectral signature in shortwave irradiance fields – specifically in transmittance and net horizontal photon transport in the visible and near-ultraviolet wavelength range. We found a robust correlation between the magnitude of net horizontal photon transport (H) and its spectral dependence (slope), which is scale-invariant and holds for the entire pixel population of a domain. This was surprising at first given the large degree of spatial inhomogeneity. We prove that the underlying physical mechanism for this phenomenon is molecular scattering in conjunction with cloud spatial structure. On this basis, we developed a simple parameterization through a single parameter ε, which quantifies the characteristic spectral signature of spatial inhomogeneities. In the case we studied, neglecting net horizontal photon transport leads to a local transmittance bias of ±12–19 %, even at the relatively coarse spatial resolution of 20 km. Since three-dimensional effects depend on the spatial context of a given pixel in a nontrivial way, the spectral dimension of this problem may emerge as the starting point for future bias corrections.