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Passive satellite observations play an important role in monitoring global aerosol properties and helping quantify aerosol radiative forcing in the climate system. The quality of aerosol retrievals from the satellite platform relies on well-calibrated radiance measurements from multiple spectral bands, and the availability of appropriate particle optical models. Inaccurate scattering phase function assumptions can introduce large retrieval errors. The high-spatial resolution, dual-view observations from the advanced baseline imagers onboard the two most recent geostationary operational environmental satellites (GOES), East and West, provide a unique opportunity to better constrain the aerosol phase function. Using dual GOES reflectance measurements for a dust event in the Gulf of Mexico in 2019, we demonstrate how a first-guess phase function can be reconstructed by considering the variations in observed scattering angles throughout the day. Using the reconstructed phase function, aerosol optical depth retrievals from the two satellites are self-consistent and agree well with surface-based optical depth estimates. We evaluate our methodology and reconstructed phase function against independent retrievals made from low-Earth-orbit multi-angle observations for a different dust event in 2020. Our new aerosol optical depth retrievals have a root-mean-square-difference of 0.019–0.047. Furthermore, the retrievals between the two geostationary satellites for this case agree within about 0.059 ± 0.072, as compared to larger discrepancies between the operational GOES products at times, which do not employ the dual-view technique.

Inaccurate mixed‐phase cloud parameterizations over the Southern Ocean remain one of the largest sources of disagreement among global models in determining shortwave cloud radiative feedbacks. Suitable global observations supporting model improvements are currently unavailable. The conventional satellite cloud phase retrieval from passive radiometers is strongly biased toward cloud top without further information on the subcloud phase. Mixed‐phase clouds with the liquid‐top mixed‐phase (LTMP) structures are often classified simply as supercooled liquid. This paper presents a daytime multispectral detection algorithm for LTMP clouds, based on differential absorption between liquid and ice in shortwave infrared bands (1.61 and 2.25 μm). The LTMP algorithm, previously developed for polar‐orbiting sensors, is applied to Himawari‐8 Advanced Himawari Imager (the first of the next‐generation geostationary satellites) to probe subcloud phase for mixed‐phase clouds over the Southern Ocean. The results are compared with spaceborne active sensor data from CloudSat and CALIPSO. Ship‐based field experiment measurements are examined for selected cases to provide a more direct assessment of algorithm performance. The results show that applying the LTMP algorithm to geostationary satellites has potential to provide advanced time‐resolved observations for mixed‐phase clouds globally with improved sublayer cloud phase information that can support enhancement and validation of global models.

Sea breeze fronts propagate inland from the coastline, driving convective initiation and aerosol redistribution. Forecasting sea breezes is challenging due to uncertainties in the initial conditions, as well as the covariance and interaction of various meteorological and surface parameters. Using the Regional Atmospheric Modeling System coupled to an interactive land-surface model, we conduct an ensemble of 130 idealized cloud-resolving simulations by simultaneously perturbing six atmospheric and four surface parameters describing the initial conditions. To identify the key parameters impacting the inland characteristics and the intensity of the sea breeze convection in a tropical rainforest, we apply statistical emulation and variance-based sensitivity analysis techniques. This study extends a previous study which explored the impacts of various parameters on sea breeze characteristics in arid environments devoid of moist convection. Wind speed is identified as the main contributor to the inland extent, similar to the arid environment study. However, the relative impacts of surface properties on the inland extent are less significant in the moist environment where land-surface heating can be suppressed via moist convective processes and vegetation-atmosphere interactions. Two sea breeze-initiated convection regimes are also identified: shallow and deep. Over the shallow regime, where convective available potential energy is limited, the inversion layer strength is the primary control of the convective intensity. Over the deep regime, boundary layer temperature exerts a robust control over the convective available potential energy and hence the convective intensity. The potential vertical redistribution of aerosols is closely related to the convective intensity.

This paper describes a Dynamic Enhancement Background Reduction Algorithm (DEBRA) applicable to multi-spectral satellite imaging radiometers. DEBRA uses ancillary information about the clear-sky background to reduce false detections of atmospheric parameters in complex scenes. Applied here to the detection of lofted dust, DEBRA enlists a surface emissivity database coupled with a climatological database of surface temperature to approximate the clear-sky equivalent signal for selected infrared-based multispectral dust detection tests. This background allows for suppression of false alarms caused by land surface features while retaining some ability to detect dust above those problematic surfaces. The algorithm is applicable to both day and nighttime observations and enables weighted combinations of dust detection tests. The results are provided quantitatively, as a detection confidence factor [0,1], but are also readily visualized as enhanced imagery. Utilizing the DEBRA confidence factor as a scaling factor in false color Red/Green/Blue (R/G/B) imagery enables depiction of the targeted parameter in the context of the local meteorology and topography. In this way, the method holds utility to both automated clients and human analysts alike. Examples of DEBRA performance from notable dust storms and comparisons against other detection methods and independent observations are presented.

Meteorological clouds often exist in the liquid phase at temperatures below 0°C. Traditionally, satellite-derived information on cloud phase comes from narrow bands in the shortwave and thermal infrared, with sensitivity biased strongly toward cloud top. In situ observations suggest an abundance of clouds having supercooled liquid water at their tops but a predominantly ice phase residing below. Satellites may report these clouds simply as supercooled liquid, with no further information regarding the presence of a subcloud top ice phase. Here we describe a physical basis for the detection of liquid-top mixed-phase clouds from passive satellite radiometer observations. The algorithm makes use of reflected sunlight in narrow bands at 1.6 and 2.25 µm to optically probe below liquid-topped clouds and determine phase. Detection is predicated on differential absorption properties between liquid and ice particles, accounting for varying Sun/sensor geometry and cloud optical properties. When tested on numerical weather prediction model simulated cloud fields, the algorithm provided threat scores in the 0.6–0.8 range and false alarm rates in the 0.1–0.2 range. A case study based on surface and satellite observations of liquid-top mixed-phase clouds in northern Alaska was also examined. Preliminary results indicate promising potential for distinction between supercooled liquid-top phase clouds with and without an underlying mixed-phase component.

The Visible Infrared Imaging Radiometer Suite (VIIRS) combines the best aspects of both civilian and military heritage instrumentation. VIIRS has improved capabilities over its predecessors: a wider swath width and much higher spatial resolution at swath edge. The VIIRS day-night band (DNB) is sensitive to very low levels of visible light and is capable of detecting low clouds, land surface features, and sea ice at night, in addition to light emissions from both man-made and natural sources. Imagery from the Suomi National Polar-orbiting Partnership (Suomi NPP) satellite has been in the checkout process since its launch on 28 October 2011. The ongoing evaluation of VIIRS Imagery helped resolve several imagery-related issues, including missing radiance measurements. In particular, near-constant contrast imagery, derived from the DNB, had a large number of issues to overcome, including numerous missing or blank-fill images and a stray light leakage problem that was only recently resolved via software fixes. In spite of various sensor issues, the VIIRS DNB has added tremendous operational and research value to Suomi NPP. Remarkably, it has been discovered to be sensitive enough to identify clouds even in very low light new moon conditions, using reflected light from the Earth's airglow layer. Impressive examples of the multispectral imaging capabilities are shown to demonstrate its applications for a wide range of operational users. Future members of the Joint Polar Satellite System constellation will also carry and extend the use of VIIRS. Imagery evaluation will continue with these satellites to ensure the quality of imagery for end users.

An optimal estimation approach is applied to the physical retrieval of single-layer cloud optical properties (optical depth and effective radius) using multispectral imager channels on the western Geostationary Operational Environmental Satellite (GOES 10). The retrieval includes diagnostic information pertaining to uncertainty and dependence on a priori assumptions required by the forward model. Satellite retrievals of 0.65-μm cloud optical depth and effective radius (micrometers) for marine stratocumulus (in both drizzle and drizzle-free conditions) during the CloudSat Antecedent Validation Experiment and tropical cirrus during the Atmospheric Radiation Measurement (ARM)-Unmanned Aerospace Vehicle spring flight series are examined together with data from the NASA/Jet Propulsion Laboratory Airborne Cloud Radar (ACR), the ARM Cloud Detection Lidar, and the Colorado State University Scanning Spectral Polarimeter (SSP) instruments. Optical depths are found to be consistent between GOES and SSP after taking into account the degradation of responsivity in GOES channel 1. Colocated ACR/GOES observations support past evidence that passive satellite detection of drizzle size droplets (in terms of a significant positive bias in the retrieved effective radius) may be possible under certain conditions. The ability of a dual lidar/radar active observing system to provide independent information over different cloud particle size regimes is illustrated and speaks to the vertical variability of cloud microphysics. The GOES estimate of effective radius was found to be more representative of the upper 0.5 km of the cirrus clouds examined.

Active sensor data, in the form of lidar and radar cloud vertical boundaries, are used as a priori information to passive sensor satellite retrievals of cloud optical depth and effective particle radius. Correct placement of cloud in the vertical eliminates the need to approximate cloud height from multispectral passive techniques and is shown to improve uncertainties in nighttime retrievals of thin cirrus in excess of 30%. The new method is exemplified by two casen studies using imager data from GOES but remains valid for any passive/active remote sensing application. A strength of this method is its ability to diagnose components of the retrieval uncertainty and thereby quantify retrieval performance. Errors associated with the forward model and measurement uncertainties, and an independent validation of the retrieval, are discussed.

The first no-gap OH airglow all-sky imager network was established in northern China in February 2012. The network is composed of six all-sky airglow imagers that make observations of OH airglow gravity waves and cover an area of about 2000 km east and west and about 1400 km south and north. An unusual outbreak of Concentric Gravity Wave (CGW) events were observed by the network nearly every night during the first half of August 2013. These events were coincidentally observed by satellite sensors from Fengyun-2 (FY-2), Atmospheric Infrared Sounder (AIRS)/Aqua, and Visible Infrared Imaging Radiometer Suite (VIIRS)/Suomi National Polar-orbiting Partnership (NPP). Combination of the ground imager network with satellites provides multilevel observations of the CGWs from the stratosphere to the mesopause region. In this paper, two representative CGW events in August 2013 are studied in detail: first is the CGW on the night of 13 August 2013, likely launched by a single thunderstorm. The temporal and spatial analyses indicate that the CGW horizontal wavelengths follow freely propagating waves based on a GW dispersion relation within 300 km from the storm center. In contrast, the more distant observed gravity wave field exhibits a smaller horizontal wavelength of ~20 km, and our analysis strongly suggest this wave field represents a ducted wave. A second event, exhibiting multiple CGWs, was induced by two very strong thunderstorms on 9 August 2013. Multiscale waves with horizontal wavelengths ranging from less than 10 km to 200 km were observed.

[1] Remote sensing observations of aerosol from surface and satellite instruments are extensively used for atmospheric and climate research. From passive sensors, the apparent cloud-free atmosphere in the vicinity of clouds often appears to be brighter than further away from the clouds, leading to an increase in the retrieved aerosol optical depth (τ). Mechanisms contributing to this enhancement or increase, including contamination by undetected clouds, hygroscopic growth of aerosol particles, and meteorological conditions, have been debated in recent literature, but the extent to which each of these factors influence the observed enhancement (Δτ) is poorly known. Here we used 11 years of daily global observations at 10 × 10 km2 resolution from the MODIS on the NASA Terra satellite to quantify τ as a function of cloud fraction (CF). Our analysis reveals that, averaged over the globe, the clear sky τ is enhanced by Δτ = 0.05 in cloudy conditions (CF = 0.8–0.9). This enhancement in Δτ corresponds to relative enhancement of 25% in cloudy conditions (CF = 0.8–0.9) compared with relatively clear conditions (CF = 0.1–0.2). Unlike the absolute enhancement Δτ, the relative increase in τis rather consistent in all seasons and is 25–35% in the subtropics and 15–25% at mid and higher latitudes. Using a simple Gaussian probability density function model to connect cloud cover and the distribution of relative humidity, we argue that much of the enhancement is consistent with aerosol hygroscopic growth in the humid environment surrounding clouds. Consideration of these cloud-dependentτeffects will facilitate understanding aerosol-cloud interactions and reduce the uncertainty in estimates of aerosol radiative forcing by global climate models.

[1] The day/night band channel of the Visible Infrared Imaging Radiometer Suite (VIIRS) instrument on board Suomi-National Polar Partnership (S-NPP) is a visible/near-infrared sensor (500–900 nm band pass) capable of measuring extremely low magnitudes of light, down to the levels of reflected moonlight and beyond. Whereas similar measurement capabilities have existed on predecessor sensors (principally, the Defense Meteorological Satellite Program), the day/night band offers the first calibrated radiance measurements, and as a result, it is the first opportunity to apply moonlight measurements to the problem of retrieving nocturnal cloud optical properties. Daytime retrievals of cloud properties such as top height, optical thickness, cloud top particle size, and water content, have been conducted routinely from an assortment of operational and research grade optical sensors for decades. These observations are providing a satellite-based global data record of increasing relevance to climate change monitoring (where clouds are thought to play an integral feedback role). The lack of a complete diurnal record of such key parameters presents an important shortfall of these records. Here we present the adaption of the daytime cloud optical and microphysical properties algorithm, which derives cloud optical thickness and effective radius from reflected sunlight to lunar reflectance. The new algorithm is referred to nighttime lunar cloud optical and microphysical properties. Day/night consistency of optical depth is shown through global analysis for one complete day of VIIRS data. Limitations of the retrieval of effective radius are discussed.