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- Author or Editor: Zhanqing Li x
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Abstract
This paper is concerned with uncertainties in the Advanced Very High Resolution Radiometer (AVHRR)-based retrieval of optical depth for heavy smoke aerosol plumes generated from forest fires that occurred in Canada due to a lack of knowledge on their optical properties (single-scattering albedo and asymmetry parameter). Typical values of the optical properties for smoke aerosols derived from such field experiments as Smoke, Clouds, and Radiation-Brazil (SCAR-B); Transport and Atmospheric Chemistry near the Equator-Atlantic (TRACE-A); Biomass Burning Airborne and Spaceborne Experiment in the Amazonas (BASE-A); and Boreal Ecosystem–Atmosphere Study (BOREAS) were first assumed for retrieving smoke optical depths. It is found that the maximum top-of-atmosphere (TOA) reflectance values calculated by models with these aerosol parameters are less than observations whose values are considerably higher. A successful retrieval would require an aerosol model that either has a substantially smaller asymmetry parameter (g < 0.4 versus g > 0.5), or higher single-scattering albedo (ω ≫ 0.9 versus ω < 0.9), or both (e.g., g = 0.39 and ω = 0.91 versus g = 0.57 and ω = 0.87) than the existing models. Several potential causes were examined including small smoke particle size, low black carbon content, humidity effect, calibration errors, inaccurate surface albedo, mixture of cloud and aerosol layers, etc. A more sound smoke aerosol model is proposed that has a lower content of black carbon (mass ratio = 0.015) and smaller size (mean radius = 0.02 μm for dry smoke particles), together with consideration of the effect of relative humidity. Ground-based observations of smoke suggest that for τ < 2.5 there is an increasing trend in ω and a decreasing trend in g with increases in τ, which is consistent with the results of satellite retrievals. Using these relationships as constraints, more plausible values of τ can be obtained for heavy smoke aerosol. The possibility of smoke–cloud mixtures is also considered, which can also lead to high TOA reflectances. However, without measurements, the hypothesis can be neither accepted nor negated. The study demonstrates that without independent assessments of the optical properties, large uncertainties would be incurred in the retrieved values of optical depth for heavy smoke aerosol plumes.
Abstract
This paper is concerned with uncertainties in the Advanced Very High Resolution Radiometer (AVHRR)-based retrieval of optical depth for heavy smoke aerosol plumes generated from forest fires that occurred in Canada due to a lack of knowledge on their optical properties (single-scattering albedo and asymmetry parameter). Typical values of the optical properties for smoke aerosols derived from such field experiments as Smoke, Clouds, and Radiation-Brazil (SCAR-B); Transport and Atmospheric Chemistry near the Equator-Atlantic (TRACE-A); Biomass Burning Airborne and Spaceborne Experiment in the Amazonas (BASE-A); and Boreal Ecosystem–Atmosphere Study (BOREAS) were first assumed for retrieving smoke optical depths. It is found that the maximum top-of-atmosphere (TOA) reflectance values calculated by models with these aerosol parameters are less than observations whose values are considerably higher. A successful retrieval would require an aerosol model that either has a substantially smaller asymmetry parameter (g < 0.4 versus g > 0.5), or higher single-scattering albedo (ω ≫ 0.9 versus ω < 0.9), or both (e.g., g = 0.39 and ω = 0.91 versus g = 0.57 and ω = 0.87) than the existing models. Several potential causes were examined including small smoke particle size, low black carbon content, humidity effect, calibration errors, inaccurate surface albedo, mixture of cloud and aerosol layers, etc. A more sound smoke aerosol model is proposed that has a lower content of black carbon (mass ratio = 0.015) and smaller size (mean radius = 0.02 μm for dry smoke particles), together with consideration of the effect of relative humidity. Ground-based observations of smoke suggest that for τ < 2.5 there is an increasing trend in ω and a decreasing trend in g with increases in τ, which is consistent with the results of satellite retrievals. Using these relationships as constraints, more plausible values of τ can be obtained for heavy smoke aerosol. The possibility of smoke–cloud mixtures is also considered, which can also lead to high TOA reflectances. However, without measurements, the hypothesis can be neither accepted nor negated. The study demonstrates that without independent assessments of the optical properties, large uncertainties would be incurred in the retrieved values of optical depth for heavy smoke aerosol plumes.
Abstract
The concept of cloud radiative forcing (CRF) has been widely employed in studying the effects of clouds on the earth’s radiation budget and climate. CRF denotes, in principle, the net influence of cloud alone on the radiation budget of a system. In practice, however, observational determination of CRF is fraught with uncertainties due to factors other than cloud that induce changes in atmospheric background conditions. The most notable variables include aerosol, water vapor, and the data sampling scheme. The impact of these factors on the derivation of CRF and cloud absorption is investigated here by means of modeling and analysis of multiple datasets. Improved estimation of CRF is attempted at the top of the atmosphere (TOA) and at the surface from spatially and temporally collocated ground and satellite measurements for broadband shortwave fluxes. Satellite data employed include pixel measurements from ERBE (1988–90), ScaRaB (1994–95), and CERES (1998), as well as surface data acquired across the Canadian radiation network, the ARM Central Facility site in Oklahoma, the US/NOAA SURFRAD networks, and the world BSRN (WMO) networks. It is found that surface CRF is much more susceptible to the variability in background conditions than TOA CRF. Selection of overly clear sky conditions often leads to significant overestimation of surface CRF, but TOA CRF remains intact or only slightly affected. As a result, the ratio of CRF at the surface and TOA is prone to overestimation. With careful treatments of these effects, the CRF ratio turns out to vary mostly between 0.9 and 1.1, implying approximately the same magnitude of atmospheric absorption under clear-sky and cloudy-sky conditions.
Abstract
The concept of cloud radiative forcing (CRF) has been widely employed in studying the effects of clouds on the earth’s radiation budget and climate. CRF denotes, in principle, the net influence of cloud alone on the radiation budget of a system. In practice, however, observational determination of CRF is fraught with uncertainties due to factors other than cloud that induce changes in atmospheric background conditions. The most notable variables include aerosol, water vapor, and the data sampling scheme. The impact of these factors on the derivation of CRF and cloud absorption is investigated here by means of modeling and analysis of multiple datasets. Improved estimation of CRF is attempted at the top of the atmosphere (TOA) and at the surface from spatially and temporally collocated ground and satellite measurements for broadband shortwave fluxes. Satellite data employed include pixel measurements from ERBE (1988–90), ScaRaB (1994–95), and CERES (1998), as well as surface data acquired across the Canadian radiation network, the ARM Central Facility site in Oklahoma, the US/NOAA SURFRAD networks, and the world BSRN (WMO) networks. It is found that surface CRF is much more susceptible to the variability in background conditions than TOA CRF. Selection of overly clear sky conditions often leads to significant overestimation of surface CRF, but TOA CRF remains intact or only slightly affected. As a result, the ratio of CRF at the surface and TOA is prone to overestimation. With careful treatments of these effects, the CRF ratio turns out to vary mostly between 0.9 and 1.1, implying approximately the same magnitude of atmospheric absorption under clear-sky and cloudy-sky conditions.
Abstract
The frequent occurrence of high cirrus overlapping low water cloud poses a major challenge in retrieving their optical properties from spaceborne sensors. This paper presents a novel retrieval method that takes full advantage of the satellite data from the Moderate Resolution Imaging Spectroradiometer (MODIS). The main objectives are identification of overlapped high cirrus and low water clouds and determination of their individual optical depths, top heights, and emissivities. The overlapped high cloud top is determined from the MODIS CO2-slicing retrieval and the underlying low cloud top is determined from the neighboring MODIS pixels that are identified as single-layer low clouds. The algorithm applies a dual-layer cloud radiative transfer model using initial cloud properties derived from the MODIS CO2-slicing channels and the visible (0.65 μm) and infrared (11 μm) window channels. An automated iterative procedure follows by adjusting the high cirrus and low water cloud optical depths until computed radiances from the dual-layer model match with observed radiances from both the visible and infrared channels. The algorithm is valid for both single-layer and dual-layer clouds with the cirrus optical depth <∼4 (emissivity <∼0.85). For more than two-layer clouds, its validity depends on the thickness of the upper-layer cloud. A preliminary validation is conducted by comparing against ground-based active remote sensing data. Pixel-by-pixel retrievals and error analyses are presented. It is demonstrated that retrievals based on a single-layer assumption can result in systematic biases in the retrieved cloud top and optical properties for overlapped clouds. Such biases can be removed or lessened considerably by applying the new algorithm.
Abstract
The frequent occurrence of high cirrus overlapping low water cloud poses a major challenge in retrieving their optical properties from spaceborne sensors. This paper presents a novel retrieval method that takes full advantage of the satellite data from the Moderate Resolution Imaging Spectroradiometer (MODIS). The main objectives are identification of overlapped high cirrus and low water clouds and determination of their individual optical depths, top heights, and emissivities. The overlapped high cloud top is determined from the MODIS CO2-slicing retrieval and the underlying low cloud top is determined from the neighboring MODIS pixels that are identified as single-layer low clouds. The algorithm applies a dual-layer cloud radiative transfer model using initial cloud properties derived from the MODIS CO2-slicing channels and the visible (0.65 μm) and infrared (11 μm) window channels. An automated iterative procedure follows by adjusting the high cirrus and low water cloud optical depths until computed radiances from the dual-layer model match with observed radiances from both the visible and infrared channels. The algorithm is valid for both single-layer and dual-layer clouds with the cirrus optical depth <∼4 (emissivity <∼0.85). For more than two-layer clouds, its validity depends on the thickness of the upper-layer cloud. A preliminary validation is conducted by comparing against ground-based active remote sensing data. Pixel-by-pixel retrievals and error analyses are presented. It is demonstrated that retrievals based on a single-layer assumption can result in systematic biases in the retrieved cloud top and optical properties for overlapped clouds. Such biases can be removed or lessened considerably by applying the new algorithm.
Abstract
This study investigates and accounts for the influence of various ice cloud parameters on the retrieval of the surface solar radiation budget (SSRB) from reflected flux at the top of the atmosphere (TOA). The optical properties of ice clouds depend on ice crystal shape, size distribution, water content, and the vertical profiles of geometric and microphysical structure. As a result, the relationship between the SSRB and TOA-reflected flux for an ice cloud atmosphere is more complex and differs from that for water cloud and cloudless atmospheres. The sensitivities of the relationship between the SSRB and TOA-reflected flux are examined with respect to various ice cloud parameters. Uncertainties in the retrieval of the SSRB due to inadequate knowledge of various ice cloud parameters are evaluated thoroughly. The uncertainty study is concerned with both pure ice clouds and multiphase clouds (ice cloud above water cloud). According to the magnitudes of errors in the SSRB retrieval caused by different input variables, parameterized correction terms were introduced. If the input variables are known accurately, errors in the retrieval of the SSRB under a wide range of ice cloud conditions are expected to diminish substantially, to less than 10 W m−2 for 91% of the simulated ice cloud cases. In comparison, the same accuracy may be attained for only 19% of the retrievals for the same ice cloud cases using the retrieval algorithm designed for non-ice-cloud conditions.
Abstract
This study investigates and accounts for the influence of various ice cloud parameters on the retrieval of the surface solar radiation budget (SSRB) from reflected flux at the top of the atmosphere (TOA). The optical properties of ice clouds depend on ice crystal shape, size distribution, water content, and the vertical profiles of geometric and microphysical structure. As a result, the relationship between the SSRB and TOA-reflected flux for an ice cloud atmosphere is more complex and differs from that for water cloud and cloudless atmospheres. The sensitivities of the relationship between the SSRB and TOA-reflected flux are examined with respect to various ice cloud parameters. Uncertainties in the retrieval of the SSRB due to inadequate knowledge of various ice cloud parameters are evaluated thoroughly. The uncertainty study is concerned with both pure ice clouds and multiphase clouds (ice cloud above water cloud). According to the magnitudes of errors in the SSRB retrieval caused by different input variables, parameterized correction terms were introduced. If the input variables are known accurately, errors in the retrieval of the SSRB under a wide range of ice cloud conditions are expected to diminish substantially, to less than 10 W m−2 for 91% of the simulated ice cloud cases. In comparison, the same accuracy may be attained for only 19% of the retrievals for the same ice cloud cases using the retrieval algorithm designed for non-ice-cloud conditions.
Abstract
Updraft speeds of thermals have always been difficult to measure, despite the significant role they play in transporting pollutants and in cloud formation and precipitation. In this study, updraft speeds in buoyancy-driven planetary boundary layers (PBLs) measured by Doppler lidar are found to be correlated with properties of the PBL and surface over the Southern Great Plains (SGP) site operated by the U.S. Department of Energy’s Atmospheric Radiation Measurement Program (ARM). Based on the relationships found here, two approaches are proposed to estimate both maximum (W max) and cloud-base (W cb) updraft speeds using satellite data together with some ancillary meteorological data of PBL depth, wind speed at 10-m height, and air temperature at 2-m height. The required satellite input data are cloud-base and surface skin temperatures. PBL depth can be determined by using cloud-base temperature in combination with European Centre for Medium-Range Weather Forecasts (ECMWF) interim reanalysis data. Validation against lidar-measured updraft speeds demonstrated the feasibility of retrieving W max and W cb using high-resolution Suomi–National Polar-Orbiting Partnership Visible Infrared Imaging Radiometer Suite (Suomi-NPP VIIRS) measurements over land for PBLs with thermally driven convective clouds during the satellite overpass time. The root-mean-square errors (RMSE) of W max and W cb are 0.32 and 0.42 m s−1, respectively. This method does not work for a stable or a mechanically driven PBL.
Abstract
Updraft speeds of thermals have always been difficult to measure, despite the significant role they play in transporting pollutants and in cloud formation and precipitation. In this study, updraft speeds in buoyancy-driven planetary boundary layers (PBLs) measured by Doppler lidar are found to be correlated with properties of the PBL and surface over the Southern Great Plains (SGP) site operated by the U.S. Department of Energy’s Atmospheric Radiation Measurement Program (ARM). Based on the relationships found here, two approaches are proposed to estimate both maximum (W max) and cloud-base (W cb) updraft speeds using satellite data together with some ancillary meteorological data of PBL depth, wind speed at 10-m height, and air temperature at 2-m height. The required satellite input data are cloud-base and surface skin temperatures. PBL depth can be determined by using cloud-base temperature in combination with European Centre for Medium-Range Weather Forecasts (ECMWF) interim reanalysis data. Validation against lidar-measured updraft speeds demonstrated the feasibility of retrieving W max and W cb using high-resolution Suomi–National Polar-Orbiting Partnership Visible Infrared Imaging Radiometer Suite (Suomi-NPP VIIRS) measurements over land for PBLs with thermally driven convective clouds during the satellite overpass time. The root-mean-square errors (RMSE) of W max and W cb are 0.32 and 0.42 m s−1, respectively. This method does not work for a stable or a mechanically driven PBL.
Abstract
Surface latent heat flux (LHF) has been considered as the determinant driver of the stratocumulus-to-cumulus transition (SCT). The distinct signature of the LHF in driving the SCT, however, has not been found in observations. This motivates us to ask, How determinant is the LHF to SCT? To answer this question, we conduct large-eddy simulations in a Lagrangian setup in which the sea surface temperature increases over time to mimic a low-level cold-air advection. To isolate the role of LHF, we conduct a mechanism-denial experiment in which the LHF adjustment is turned off. The simulations confirm the indispensable roles of LHF in sustaining (although not initiating) the boundary layer decoupling (first stage of SCT) and driving the cloud regime transition (second stage of SCT). However, using theoretical arguments and LES results, we show that decoupling can happen without the need for LHF to increase as long as the capping inversion is weak enough to ensure high entrainment efficiency. The high entrainment efficiency alone cannot sustain the decoupled state without the help of LHF adjustment, leading to the recoupling of the boundary layer that eventually becomes cloud-free. Interestingly, the stratocumulus sheet is sustained longer without LHF adjustment. The mechanisms underlying the findings are explained from the perspectives of cloud-layer budgets of energy (first stage) and liquid water path (second stage).
Abstract
Surface latent heat flux (LHF) has been considered as the determinant driver of the stratocumulus-to-cumulus transition (SCT). The distinct signature of the LHF in driving the SCT, however, has not been found in observations. This motivates us to ask, How determinant is the LHF to SCT? To answer this question, we conduct large-eddy simulations in a Lagrangian setup in which the sea surface temperature increases over time to mimic a low-level cold-air advection. To isolate the role of LHF, we conduct a mechanism-denial experiment in which the LHF adjustment is turned off. The simulations confirm the indispensable roles of LHF in sustaining (although not initiating) the boundary layer decoupling (first stage of SCT) and driving the cloud regime transition (second stage of SCT). However, using theoretical arguments and LES results, we show that decoupling can happen without the need for LHF to increase as long as the capping inversion is weak enough to ensure high entrainment efficiency. The high entrainment efficiency alone cannot sustain the decoupled state without the help of LHF adjustment, leading to the recoupling of the boundary layer that eventually becomes cloud-free. Interestingly, the stratocumulus sheet is sustained longer without LHF adjustment. The mechanisms underlying the findings are explained from the perspectives of cloud-layer budgets of energy (first stage) and liquid water path (second stage).
Response of Marine Boundary Layer Cloud Properties to Aerosol Perturbations Associated with Meteorological Conditions from the 19-Month AMF-Azores CampaignAbstract
This study investigates the response of marine boundary layer (MBL) cloud properties to aerosol loading by accounting for the contributions of large-scale dynamic and thermodynamic conditions and quantifies the first indirect effect (FIE). It makes use of 19-month measurements of aerosols, clouds, and meteorology acquired during the Atmospheric Radiation Measurement Mobile Facility field campaign over the Azores. Cloud droplet number concentrations 
Abstract
This study investigates the response of marine boundary layer (MBL) cloud properties to aerosol loading by accounting for the contributions of large-scale dynamic and thermodynamic conditions and quantifies the first indirect effect (FIE). It makes use of 19-month measurements of aerosols, clouds, and meteorology acquired during the Atmospheric Radiation Measurement Mobile Facility field campaign over the Azores. Cloud droplet number concentrations
Abstracts
This is the Part II of a two-part study that seeks a theoretical understanding of an empirical relationship for shallow cumulus clouds: subcloud updraft velocity covaries linearly with the cloud-base height. This work focuses on continental cumulus clouds that are more strongly forced by surface fluxes and more deviated from equilibrium than those over oceans (Part I). We use a simple analytical model for shallow cumulus that is well tested against a high-resolution (25 m in the horizontal) large-eddy simulation model. Consistent with a conventional idea, we find that surface Bowen ratio is the key variable that regulates the covariability of both parameters: under the same solar insolation, a drier surface allows for stronger buoyancy flux, triggering stronger convection that deepens the subcloud layer. We find that the slope of the Bowen-ratio-regulated relationship between the two parameters (defined as λ) is dependent on both the local time and the stability of the lower free atmosphere. The value of λ decreases with time exponentially from sunrise to early afternoon and linearly from early afternoon to sunset. The value of λ is larger in a more stable atmosphere. In addition, continental λ in the early afternoon more than doubles the oceanic λ. Validation of the theoretical results against ground observations over the Southern Great Plains shows a reasonable agreement. Physical mechanisms underlying the findings are explained from the perspective of different time scales at which updrafts and cloud-base height respond to a surface flux forcing.
Abstracts
This is the Part II of a two-part study that seeks a theoretical understanding of an empirical relationship for shallow cumulus clouds: subcloud updraft velocity covaries linearly with the cloud-base height. This work focuses on continental cumulus clouds that are more strongly forced by surface fluxes and more deviated from equilibrium than those over oceans (Part I). We use a simple analytical model for shallow cumulus that is well tested against a high-resolution (25 m in the horizontal) large-eddy simulation model. Consistent with a conventional idea, we find that surface Bowen ratio is the key variable that regulates the covariability of both parameters: under the same solar insolation, a drier surface allows for stronger buoyancy flux, triggering stronger convection that deepens the subcloud layer. We find that the slope of the Bowen-ratio-regulated relationship between the two parameters (defined as λ) is dependent on both the local time and the stability of the lower free atmosphere. The value of λ decreases with time exponentially from sunrise to early afternoon and linearly from early afternoon to sunset. The value of λ is larger in a more stable atmosphere. In addition, continental λ in the early afternoon more than doubles the oceanic λ. Validation of the theoretical results against ground observations over the Southern Great Plains shows a reasonable agreement. Physical mechanisms underlying the findings are explained from the perspective of different time scales at which updrafts and cloud-base height respond to a surface flux forcing.
Abstract
Aerosols contribute to Earth’s radiative budget both directly and indirectly, and large uncertainties remain in quantifying aerosol effects on climate. Variability in aerosol distribution and properties, as might result from changing emissions and transport processes, must be characterized. In this study, variations in aerosol loading across the eastern seaboard of the United States and the North Atlantic Ocean during 2002 to 2012 are analyzed to examine the impacts of anthropogenic emission control measures using monthly mean data from MODIS, AERONET, and IMPROVE observations and Goddard Chemistry Aerosol Radiation and Transport (GOCART) model simulation. MODIS observes a statistically significant negative trend in aerosol optical depth (AOD) over the midlatitudes (−0.030 decade−1). Correlation analyses with surface AOD from AERONET sites in the upwind region combined with trend analysis from GOCART component AOD confirm that the observed decrease in the midlatitudes is chiefly associated with anthropogenic aerosols that exhibit significant negative trends from the eastern U.S. coast extending over the western North Atlantic. Additional analysis of IMPROVE surface PM2.5 observations demonstrates statistically significant negative trends in the anthropogenic components with decreasing mass concentrations over the eastern United States. Finally, a seasonal analysis of observational datasets is performed. The negative trend seen by MODIS is strongest during spring (MAM) and summer (JJA) months. This is supported by AERONET seasonal trends and is identified from IMPROVE seasonal trends as resulting from ammonium sulfate decreases during these seasons.
Abstract
Aerosols contribute to Earth’s radiative budget both directly and indirectly, and large uncertainties remain in quantifying aerosol effects on climate. Variability in aerosol distribution and properties, as might result from changing emissions and transport processes, must be characterized. In this study, variations in aerosol loading across the eastern seaboard of the United States and the North Atlantic Ocean during 2002 to 2012 are analyzed to examine the impacts of anthropogenic emission control measures using monthly mean data from MODIS, AERONET, and IMPROVE observations and Goddard Chemistry Aerosol Radiation and Transport (GOCART) model simulation. MODIS observes a statistically significant negative trend in aerosol optical depth (AOD) over the midlatitudes (−0.030 decade−1). Correlation analyses with surface AOD from AERONET sites in the upwind region combined with trend analysis from GOCART component AOD confirm that the observed decrease in the midlatitudes is chiefly associated with anthropogenic aerosols that exhibit significant negative trends from the eastern U.S. coast extending over the western North Atlantic. Additional analysis of IMPROVE surface PM2.5 observations demonstrates statistically significant negative trends in the anthropogenic components with decreasing mass concentrations over the eastern United States. Finally, a seasonal analysis of observational datasets is performed. The negative trend seen by MODIS is strongest during spring (MAM) and summer (JJA) months. This is supported by AERONET seasonal trends and is identified from IMPROVE seasonal trends as resulting from ammonium sulfate decreases during these seasons.
Abstract
It has been widely recognized that aerosols can modify cloud properties, but it remains uncertain how much the changes and associated variations in cloud radiative forcing are related to aerosol loading. Using 4 yr of A-Train satellite products generated from CloudSat, the Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations satellite, and the Aqua satellite, the authors investigated the systematic changes of deep cloud properties and cloud radiative forcing (CRF) with respect to changes in aerosol loading over the entire tropics. Distinct correlations between CRF and aerosol loading were found. Systematic variations in both shortwave and longwave CRF with increasing aerosol index over oceans and aerosol optical depth over land for mixed-phase clouds were identified, but little change was seen in liquid clouds. The systematic changes are consistent with the microphysical effect and the aerosol invigoration effect. Although this study cannot fully exclude the influence of other factors, attempts were made to explore various possibilities to the extent that observation data available can offer. Assuming that the systematic dependence originates from aerosol effects, changes in CRF with respect to aerosol loading were examined using satellite retrievals. Mean changes in shortwave and longwave CRF from very clean to polluted conditions ranged from −192.84 to −296.63 W m−2 and from 18.95 to 46.12 W m−2 over land, respectively, and from −156.12 to −170.30 W m−2 and from 6.76 to 11.67 W m−2 over oceans, respectively.
Abstract
It has been widely recognized that aerosols can modify cloud properties, but it remains uncertain how much the changes and associated variations in cloud radiative forcing are related to aerosol loading. Using 4 yr of A-Train satellite products generated from CloudSat, the Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations satellite, and the Aqua satellite, the authors investigated the systematic changes of deep cloud properties and cloud radiative forcing (CRF) with respect to changes in aerosol loading over the entire tropics. Distinct correlations between CRF and aerosol loading were found. Systematic variations in both shortwave and longwave CRF with increasing aerosol index over oceans and aerosol optical depth over land for mixed-phase clouds were identified, but little change was seen in liquid clouds. The systematic changes are consistent with the microphysical effect and the aerosol invigoration effect. Although this study cannot fully exclude the influence of other factors, attempts were made to explore various possibilities to the extent that observation data available can offer. Assuming that the systematic dependence originates from aerosol effects, changes in CRF with respect to aerosol loading were examined using satellite retrievals. Mean changes in shortwave and longwave CRF from very clean to polluted conditions ranged from −192.84 to −296.63 W m−2 and from 18.95 to 46.12 W m−2 over land, respectively, and from −156.12 to −170.30 W m−2 and from 6.76 to 11.67 W m−2 over oceans, respectively.
