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During recent decades, there has been dramatic Arctic sea ice retreat. This has reduced the top-of-atmosphere albedo, adding more solar energy to the climate system. There is substantial uncertainty regarding how much ice retreat and associated solar heating will occur in the future. This is relevant to future climate projections, including the timescale for reaching global warming stabilization targets. Here we use satellite observations to estimate the amount of solar energy that would be added in the worst-case scenario of a complete disappearance of Arctic sea ice throughout the sunlit part of the year. Assuming constant cloudiness, we calculate a global radiative heating of 0.71 W/m2 relative to the 1979 baseline state. This is equivalent to the effect of one trillion tons of CO2 emissions. These results suggest that the additional heating due to complete Arctic sea ice loss would hasten global warming by an estimated 25 years.

The springtime atmosphere over the southeast Atlantic Ocean (SEA) is subjected to a consistent layer of biomass burning (BB) smoke from widespread fires on the African continent. An elevated humidity signal is coincident with this layer, consistently proportional to the amount of smoke present. The combined humidity and BB aerosol has potentially significant radiative and dynamic impacts. Here, we use aircraft-based observations from the NASA ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) deployments in conjunction with reanalyses to characterize covariations in humidity and BB smoke across the SEA. The observed plume–vapor relationship, and its agreement with the European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis version 5 (ERA5) and Copernicus Atmosphere Monitoring Service (CAMS) reanalysis, persists across all observations, although the magnitude of the relationship varies as the season progresses. Water vapor is well represented by the reanalyses, while CAMS tends to underestimate carbon monoxide especially under high BB. While CAMS aerosol optical depth (AOD) is generally overestimated relative to ORACLES AOD, the observations show a consistent relationship between carbon monoxide (CO) and aerosol extinction, demonstrating the utility of the CO tracer to understanding vertical aerosol distribution. We next use k -means clustering of the reanalyses to examine multi-year seasonal patterns and distributions. We identify canonical profile types of humidity and of CO, allowing us to characterize changes in vapor and BB atmospheric structures, and their impacts as they covary. While the humidity profiles show a range in both total water vapor concentration and in vertical structure, the CO profiles primarily vary in terms of maximum concentration, with similar vertical structures in each. The distribution of profile types varies spatiotemporally across the SEA region and through the season, ranging from largely one type in the northeast and southwest to more evenly distributed between multiple types where air masses meet in the middle of the SEA. These distributions follow patterns of transport from the humid, smoky source region (greatest influence in the northeast of the SEA) and the seasonal changes in both humidity and smoke (increasing and decreasing through the season, respectively). With this work, we establish a framework for a more complete analysis of the broader radiative and dynamical effects of humid aerosols over the SEA. [ABSTRACT FROM AUTHOR]

The introduction of cloud condensation nuclei and radiative heating by sunlight-absorbing aerosols can modify the thickness and coverage of low clouds, yielding significant radiative forcing of climate. The magnitude and sign of changes in cloud coverage and depth in response to changing aerosols are impacted by turbulent dynamics of the cloudy atmosphere, but integrated measurements of aerosol solar absorption and turbulent fluxes have not been reported thus far. Here we report such integrated measurements made from unmanned aerial vehicles (UAVs) during the CARDEX (Cloud Aerosol Radiative Forcing and Dynamics Experiment) investigation conducted over the northern Indian Ocean. The UAV and surface data reveal a reduction in turbulent kinetic energy in the surface mixed layer at the base of the atmosphere concurrent with an increase in absorbing black carbon aerosols. Polluted conditions coincide with a warmer and shallower surface mixed layer because of aerosol radiative heating and reduced turbulence. The polluted surface mixed layer was also observed to be more humid with higher relative humidity. Greater humidity enhances cloud development, as evidenced by polluted clouds that penetrate higher above the top of the surface mixed layer. Reduced entrainment of dry air into the surface layer from above the inversion capping the surface mixed layer, due to weaker turbulence, may contribute to higher relative humidity in the surface layer during polluted conditions. Measurements of turbulence are important for studies of aerosol effects on clouds. Moreover, reduced turbulence can exacerbate both the human health impacts of high concentrations of fine particles and conditions favorable for low-visibility fog events.

There are many contributing factors which determine the micro- and macrophysical properties of clouds, including atmospheric vertical structure, dominant meteorological conditions, and aerosol concentration, all of which may be coupled to one another. In the quest to determine aerosol effects on clouds, these potential relationships must be understood. Here we describe several observed correlations between aerosol conditions and cloud and atmospheric properties in the Indian Ocean winter monsoon season. In the CARDEX (Cloud, Aerosol, Radiative forcing, Dynamics EXperiment) field campaign conducted in February and March 2012 in the northern Indian Ocean, continuous measurements were made of atmospheric precipitable water vapor (PWV) and the liquid water path (LWP) of trade cumulus clouds, concurrent with measurements of water vapor flux, cloud and aerosol vertical profiles, meteorological data, and surface and total-column aerosol from instrumentation at a ground observatory and on small unmanned aircraft. We present observations which indicate a positive correlation between aerosol and cloud LWP only when considering cases with low atmospheric water vapor (PWV < 40 kg m-2), a criterion which acts to filter the data to control for the natural meteorological variability in the region. We then use the aircraft and ground-based measurements to explore possible mechanisms behind this observed aerosol-LWP correlation. The increase in cloud liquid water is found to coincide with a lowering of the cloud base, which is itself attributable to increased boundary layer humidity in polluted conditions. High pollution is found to correlate with both higher temperatures and higher humidity measured throughout the boundary layer. A large-scale analysis, using satellite observations and meteorological reanalysis, corroborates these covariations: high-pollution cases are shown to originate as a highly polluted boundary layer air mass approaching the observatory from a northwesterly direction. The source air mass exhibits both higher temperatures and higher humidity in the polluted cases. While the warmer temperatures may be attributable to aerosol absorption of solar radiation over the subcontinent, the factors responsible for the coincident high humidity are less evident: the high-aerosol conditions are observed to disperse with air mass evolution, along with a weakening of the high-temperature anomaly, while the high-humidity condition is observed to strengthen in magnitude as the polluted air mass moves over the ocean toward the site of the CARDEX observations. Potential causal mechanisms of the observed correlations, including meteorological or aerosol-induced factors, are explored, though future research will be needed for a more complete and quantitative understanding of the aerosol-humidity relationship.

The decline of Arctic sea ice has been documented in over 30 y of satellite passive microwave observations. The resulting darkening of the Arctic and its amplification of global warming was hypothesized almost 50 y ago but has yet to be verified with direct observations. This study uses satellite radiation budget measurements along with satellite microwave sea ice data to document the Arctic-wide decrease in planetary albedo and its amplifying effect on the warming. The analysis reveals a striking relationship between planetary albedo and sea ice cover, quantities inferred from two independent satellite instruments. We find that the Arctic planetary albedo has decreased from 0.52 to 0.48 between 1979 and 2011, corresponding to an additional 6.4 ± 0.9 W/m(2) of solar energy input into the Arctic Ocean region since 1979. Averaged over the globe, this albedo decrease corresponds to a forcing that is 25% as large as that due to the change in CO2 during this period, considerably larger than expectations from models and other less direct recent estimates. Changes in cloudiness appear to play a negligible role in observed Arctic darkening, thus reducing the possibility of Arctic cloud albedo feedbacks mitigating future Arctic warming.

Inadequate knowledge about the complex microphysical and optical processes of the aerosol–cloud system severely restricts our ability to quantify the resultant impact on climate. Contrary to the negative radiative forcing (cooling) exerted by aerosols in cloud-free skies over dark surfaces, the absorbing aerosols, when lofted over the clouds, can potentially lead to significant warming of the atmosphere. The sign and magnitude of the aerosol radiative forcing over clouds are determined mainly by the amount of aerosol loading, the absorption capacity of aerosols or single-scattering albedo (SSA), and the brightness of the underlying cloud cover. In satellite-based algorithms that use measurements from passive sensors, the assumption of aerosol SSA is known to be the largest source of uncertainty in quantifying above-cloud aerosol optical depth (ACAOD). In this paper, we introduce a novel synergy algorithm that combines direct airborne measurements of ACAOD and the top-of-atmosphere (TOA) spectral reflectance from Ozone Monitoring Instrument (OMI) and Moderate Resolution Imaging Spectroradiometer (MODIS) sensors of NASA's A-train satellites to retrieve (1) SSA of light-absorbing aerosols lofted over the clouds and (2) aerosol-corrected cloud optical depth (COD). Radiative transfer calculations show a marked sensitivity of the TOA measurements to ACAOD, SSA, and COD, further suggesting that the availability of accurate ACAOD allows retrieval of SSA for above-cloud aerosol scenes using the "color ratio" algorithm developed for satellite sensors carrying ultraviolet (UV) and visible-near-IR (VNIR) wavelength bands. The proposed algorithm takes advantage of airborne measurements of ACAOD acquired from the High Spectral Resolution Lidar-2 (HSRL-2) and Spectrometer for Sky-Scanning, Sun-Tracking Atmospheric Research (4STAR) sun photometer operated during the ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) field campaign (September 2016, August 2017, and October 2018) over the southeastern Atlantic Ocean and synergizes them with TOA reflectance from OMI and MODIS to derive spectral SSA in the near-UV (354–388 nm) and VNIR (470–860 nm), respectively. When compared against the ORACLES airborne remote sensing and in situ measurements and the inversion dataset of the ground-based Aerosol Robotic Network (AERONET) over land, the retrieved spectral SSAs from the satellites, on average, were found to be within agreement of ∼ 0.01 – the difference well within the uncertainties involved in all these inversion datasets. The retrieved SSA above the clouds at UV–Vis-NIR wavelengths shows a distinct increasing trend from August to October, which is consistent with the ORACLES in situ measurements, AERONET inversions, and previous findings. The sensitivity analysis quantifying theoretical uncertainties in the retrieved SSA shows that errors in the measured ACAOD, aerosol layer height, and the ratio of the imaginary part of the refractive index (spectral dependence) of aerosols by 20 %, 1 km, and 10 %, respectively, produce an error in the retrieved SSA at 388 nm (470 nm) by 0.017 (0.015), 0.008 (0.002), and 0.03 (0.005). The development of the proposed aerosol–cloud algorithm implies a possible synergy of Cloud–Aerosol Lidar with Orthogonal Polarization (CALIOP) and OMI–MODIS passive sensors to deduce a global product of ACAOD and SSA. Furthermore, the presented synergy algorithm assumes implications for future missions, such as the Atmosphere Observing System (AOS) and the Earth Cloud Aerosol and Radiation Explorer (EarthCARE). The availability of the intended global dataset can help constrain climate models with the much-needed observational estimates of the radiative effects of aerosols in cloudy regions and expand our ability to study aerosol effects on clouds. [ABSTRACT FROM AUTHOR]

The springtime atmosphere over the southeast Atlantic Ocean (SEA) is subjected to a consistent layer of biomass burning (BB) smoke from widespread fires on the African continent. An elevated humidity signal is co-incident with this layer, consistently proportional to the amount of smoke present. The combined humidity and BB aerosol has potentially significant radiative and dynamic impacts. Here we use aircraft-based observations from the NASA ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) deployments in conjunction with reanalyses to characterize co-variations in humidity and BB smoke. The observed plume-vapor relationship, and its agreement with the ERA5 and CAMS reanalyses, persists across all observations, although the magnitude of the relationship varies as the season progresses. Water vapor is well-represented by the reanalyses, while CAMS tends to underestimate carbon monoxide especially under high BB. While CAMS aerosol optical depth (AOD) is generally overestimated relative to ORACLES AOD, the observations show a consistent relationship between CO and aerosol extinction, demonstrating the utility of the CO tracer to understanding vertical aerosol distribution. We next use k-means clustering of the reanalyses to examine multi-year seasonal patterns and distributions. We identify canonical profile types of humidity and of CO, allowing us to characterize changes in vapor and BB atmospheric structures, and their impacts, as they covary. Predominant profile types vary spatiotemporally across the SEA region and through the season. With this work, we establish a framework for a more complete analysis of the broader radiative and dynamical effects of humid aerosols over the SEA. [ABSTRACT FROM AUTHOR]

Inadequate knowledge about the complex microphysical and optical processes of the aerosol-cloud system severely restricts our ability to quantify the resultant impact on climate. Contrary to the negative radiative forcing (cooling) exerted by aerosols in cloud-free skies over dark surfaces, the absorbing aerosols, when lofted over the clouds, can potentially lead to significant warming of the atmosphere. The sign and magnitude of the aerosol radiative forcing over clouds are determined mainly by the amount of aerosol loading, the absorption capacity of aerosols or single-scattering albedo (SSA), and the brightness of the underlying cloud cover. In the satellite-based algorithms that use measurements from passive sensors, the assumption of aerosol SSA is known to be the largest source of uncertainty in quantifying above-cloud aerosol optical depth (ACAOD). In this paper, we introduce a novel synergy algorithm that combines direct airborne measurements of ACAOD and the top-of-atmosphere (TOA) spectral reflectance from OMI and MODIS sensors of NASA's A-train satellites to retrieve 1) SSA of light-absorbing aerosols lofted over the clouds, and 2) aerosol-corrected cloud optical depth (COD). Radiative transfer calculations show a marked sensitivity of the TOA measurements to ACAOD, SSA, and COD, further suggesting that the availability of accurate ACAOD allows retrieval of SSA for above-cloud aerosols scenes using the 'color ratio' algorithm developed for satellite sensors carrying ultraviolet (UV) and visible-near-IR (VNIR) wavelength bands. The proposed algorithm takes advantage of airborne measurements of ACAOD acquired from the High-spectral Resolution Lidar-2 (HSRL-2) and Spectrometer for Sky-Scanning, Sun-Tracking Atmospheric Research (4STAR) Sunphotometer operated during the ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) field campaign (September 2016, August 2017, and October 2018) over the southeastern Atlantic Ocean, and synergize them with TOA reflectance from OMI and MODIS to derive spectral SSA in the near-UV (354-388 nm) and VIS-near-IR (470-860 nm), respectively. When compared against the ORACLES airborne remote sensing and in situ measurements and the inversion dataset of ground-based AERONET over land, the retrieved spectral SSAs from the satellites, on average, were found to be higher overall by ~0.01-0.02--a positive bias still within the uncertainties involved in all these inversion datasets. The sensitivity analysis quantifying theoretical uncertainties in the retrieved SSA shows that errors in the measured ACAOD, aerosol layer height, and the ratio of the imaginary part of the refractive index (spectral dependence) of aerosols by 20%, 1 km, and 10%, respectively, produce an error in the retrieved SSA by 0.017 (0.01), 0.008 (0.001), and 0.03 (0.005) at 388 (470) nm. The development of the proposed aerosol-cloud algorithm implies a possible synergy of CALIOP lidar and OMI-MODIS passive sensors to deduce a global product of ACAOD and SSA. The availability of such global dataset can help constrain the climate models with the much-needed observational estimates of the radiative effects of aerosols in cloudy regions and expand our ability to study aerosol effects on clouds. [ABSTRACT FROM AUTHOR]

Inadequate knowledge about the complex microphysical and optical processes of the aerosol-cloud system severely restricts our ability to quantify the resultant impact on climate. Contrary to the negative radiative forcing (cooling) exerted by aerosols in cloud-free skies over dark surfaces, the absorbing aerosols, when lofted over the clouds, can potentially lead to significant warming of the atmosphere. The sign and magnitude of the aerosol radiative forcing over clouds are determined mainly by the amount of aerosol loading, the absorption capacity of aerosols or single-scattering albedo (SSA), and the brightness of the underlying cloud cover. In the satellite-based algorithms that use measurements from passive sensors, the assumption of aerosol SSA is known to be the largest source of uncertainty in quantifying above-cloud aerosol optical depth (ACAOD). In this paper, we introduce a novel synergy algorithm that combines direct airborne measurements of ACAOD and the top-of-atmosphere (TOA) spectral reflectance from OMI and MODIS sensors of NASA's A-train satellites to retrieve 1) SSA of light-absorbing aerosols lofted over the clouds, and 2) aerosol-corrected cloud optical depth (COD). Radiative transfer calculations show a marked sensitivity of the TOA measurements to ACAOD, SSA, and COD, further suggesting that the availability of accurate ACAOD allows retrieval of SSA for above-cloud aerosols scenes using the 'color ratio' algorithm developed for satellite sensors carrying ultraviolet (UV) and visible-near-IR (VNIR) wavelength bands. The proposed algorithm takes advantage of airborne measurements of ACAOD acquired from the High-spectral Resolution Lidar-2 (HSRL-2) and Spectrometer for Sky-Scanning, Sun-Tracking Atmospheric Research (4STAR) Sunphotometer operated during the ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) field campaign (September 2016, August 2017, and October 2018) over the southeastern Atlantic Ocean, and synergize them with TOA reflectance from OMI and MODIS to derive spectral SSA in the near-UV (354–388 nm) and VIS-near-IR (470–860 nm), respectively. When compared against the ORACLES airborne remote sensing and in situ measurements and the inversion dataset of ground-based AERONET over land, the retrieved spectral SSAs from the satellites, on average, were found to be higher overall by ~0.01–0.02—a positive bias still within the uncertainties involved in all these inversion datasets. The sensitivity analysis quantifying theoretical uncertainties in the retrieved SSA shows that errors in the measured ACAOD, aerosol layer height, and the ratio of the imaginary part of the refractive index (spectral dependence) of aerosols by 20 %, 1 km, and 10 %, respectively, produce an error in the retrieved SSA by 0.017 (0.01), 0.008 (0.001), and 0.03 (0.005) at 388 (470) nm. The development of the proposed aerosol-cloud algorithm implies a possible synergy of CALIOP lidar and OMI-MODIS passive sensors to deduce a global product of ACAOD and SSA. The availability of such global dataset can help constrain the climate models with the much-needed observational estimates of the radiative effects of aerosols in cloudy regions and expand our ability to study aerosol effects on clouds. [ABSTRACT FROM AUTHOR]