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- Author or Editor: Qilong Min x
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Abstract
Parameterizations of absorptance depth for ammonium sulfate [(NH4)2SO4], ammonium bisulfate (NH4HSO4), and sulfuric acid (H2SO4) in the infrared are provided for an eight-band model (covering 340–2500 cm−1) and for 32 individual wavenumbers in order to generate other band schemes. The parameterization is simple in form and in its dependence on relative humidity.
It is found that the aerosol surface infrared forcing can cancel about 12%–24% aerosol surface solar forcing in a clear sky condition. Also the existence of clouds could enhance the ratio of aerosol surface infrared forcing to the aerosol surface solar forcing. In contrast to the solar case, a small mode size distribution does not always produce a larger aerosol surface forcing. Also it is found that the aerosol surface forcing is dependent on the aerosol location. Very simple analysis is presented to help understand the related physics on sulfate aerosol infrared radiative forcing.
Abstract
Parameterizations of absorptance depth for ammonium sulfate [(NH4)2SO4], ammonium bisulfate (NH4HSO4), and sulfuric acid (H2SO4) in the infrared are provided for an eight-band model (covering 340–2500 cm−1) and for 32 individual wavenumbers in order to generate other band schemes. The parameterization is simple in form and in its dependence on relative humidity.
It is found that the aerosol surface infrared forcing can cancel about 12%–24% aerosol surface solar forcing in a clear sky condition. Also the existence of clouds could enhance the ratio of aerosol surface infrared forcing to the aerosol surface solar forcing. In contrast to the solar case, a small mode size distribution does not always produce a larger aerosol surface forcing. Also it is found that the aerosol surface forcing is dependent on the aerosol location. Very simple analysis is presented to help understand the related physics on sulfate aerosol infrared radiative forcing.
Abstract
A quasi-linear retrieval was developed to profile moderately thin atmospheres using a high-resolution O2 A-band spectrometer. The retrieval is explicitly linear with respect to single scattering; the multiple-scattering contribution is treated as a perturbation. The properties of the linear inversion, examined using singular value decomposition of the kernel function, demonstrate the impacts of instrument specifications, such as resolution, out-of-band rejection, and signal-to-noise ratio, on information content. A system with 0.5 cm−1 resolution, signal-to-noise ratio of 100:1, and out-of-band floor of 10−3 has four independent pieces of information.
A fast radiative transfer model was developed to compute the multiple-scattering perturbation, in which multiple scattering is calculated at 16 different O2 absorption depths to synthesize the O2 A band. The linear system is then solved using Tikhonov's regularization with inequality constraints. Tests with synthetic data, including noise, of O2 A-band retrievals illustrate that this algorithm is accurate and fast for retrieving aerosol profiles. The errors are less than 10% for the integrated total optical depth for the cases tested. It is shown that instruments with the needed performance are practical.
Abstract
A quasi-linear retrieval was developed to profile moderately thin atmospheres using a high-resolution O2 A-band spectrometer. The retrieval is explicitly linear with respect to single scattering; the multiple-scattering contribution is treated as a perturbation. The properties of the linear inversion, examined using singular value decomposition of the kernel function, demonstrate the impacts of instrument specifications, such as resolution, out-of-band rejection, and signal-to-noise ratio, on information content. A system with 0.5 cm−1 resolution, signal-to-noise ratio of 100:1, and out-of-band floor of 10−3 has four independent pieces of information.
A fast radiative transfer model was developed to compute the multiple-scattering perturbation, in which multiple scattering is calculated at 16 different O2 absorption depths to synthesize the O2 A band. The linear system is then solved using Tikhonov's regularization with inequality constraints. Tests with synthetic data, including noise, of O2 A-band retrievals illustrate that this algorithm is accurate and fast for retrieving aerosol profiles. The errors are less than 10% for the integrated total optical depth for the cases tested. It is shown that instruments with the needed performance are practical.
Abstract
Weather forecasting over complex terrain with diverse land cover is challenging. Utilizing the high-resolution observations from New York State Mesonet (NYSM), we are able to evaluate the surface processes of the Weather Research Forecast (WRF) Model in a detailed, scale-dependent manner. In the study, possible impacts of land–atmosphere interaction on surface meteorology and boundary layer cloud development are investigated with different model resolutions, land surface models (LSMs), and planetary boundary layer (PBL) physical parameterizations. The High-Resolution Rapid Refresh, version 3 (HRRR), forecasting model is used as a reference for the sensitivity evaluation. Results show that over complex terrain, the high-resolution simulations (1 km × 60 vertical levels) generally perform better compared to low-resolution (3 km × 50 levels) in both surface meteorology and cloud fields. LSMs play a more important role in surface meteorology compared to PBL schemes. The NoahMP land surface model exhibits daytime warmer and drier biases compared to the Rapid Update Cycle (RUC) due to better prediction of the Bowen ratio in RUC. The PBL schemes would affect the convective strength in the boundary layer. The Shin–Hong (SH) scale-aware scheme tends to produce the strongest convective strength in the PBL, while the ACM2 PBL scheme rarely resolved convection even at 1-km resolution. By considering the radiation effect of subgrid-scale (SGS) clouds, the Mellor–Yamada–Nakanishi–Niino eddy diffusivity mass flux (MYNN-EDMF) predicted the highest cloud coverage and lowest surface solar radiation bias. The configuration of SGS clouds in MYNN-EDMF would not only significantly reduce shortwave radiation bias, but also affect the convection behaviors through land surface–cloud–radiation interaction.
Abstract
Weather forecasting over complex terrain with diverse land cover is challenging. Utilizing the high-resolution observations from New York State Mesonet (NYSM), we are able to evaluate the surface processes of the Weather Research Forecast (WRF) Model in a detailed, scale-dependent manner. In the study, possible impacts of land–atmosphere interaction on surface meteorology and boundary layer cloud development are investigated with different model resolutions, land surface models (LSMs), and planetary boundary layer (PBL) physical parameterizations. The High-Resolution Rapid Refresh, version 3 (HRRR), forecasting model is used as a reference for the sensitivity evaluation. Results show that over complex terrain, the high-resolution simulations (1 km × 60 vertical levels) generally perform better compared to low-resolution (3 km × 50 levels) in both surface meteorology and cloud fields. LSMs play a more important role in surface meteorology compared to PBL schemes. The NoahMP land surface model exhibits daytime warmer and drier biases compared to the Rapid Update Cycle (RUC) due to better prediction of the Bowen ratio in RUC. The PBL schemes would affect the convective strength in the boundary layer. The Shin–Hong (SH) scale-aware scheme tends to produce the strongest convective strength in the PBL, while the ACM2 PBL scheme rarely resolved convection even at 1-km resolution. By considering the radiation effect of subgrid-scale (SGS) clouds, the Mellor–Yamada–Nakanishi–Niino eddy diffusivity mass flux (MYNN-EDMF) predicted the highest cloud coverage and lowest surface solar radiation bias. The configuration of SGS clouds in MYNN-EDMF would not only significantly reduce shortwave radiation bias, but also affect the convection behaviors through land surface–cloud–radiation interaction.
Abstract
Increased observational analyses provide a unique opportunity to perform years-long cloud-resolving model (CRM) simulations and generate long-term cloud properties that are very much in demand for improving the representation of clouds in general circulation models (GCMs). A year 2000 CRM simulation is presented here using the variationally constrained mesoscale analysis and surface measurements. The year-long (3 January–31 December 2000) CRM surface precipitation is highly correlated with the Atmospheric Radiation Measurement (ARM) observations with a correlation coefficient of 0.97. The large-scale forcing is the dominant factor responsible for producing the precipitation in summer, spring, and fall, but the surface heat fluxes play a more important role during winter when the forcing is weak. The CRM-simulated year-long cloud liquid water path and cloud (liquid and ice) optical depth are also in good agreement (correlation coefficients of 0.73 and 0.64, respectively) with the ARM retrievals over the Southern Great Plains (SGP). The simulated cloud systems have 50% more ice water than liquid water in the annual mean. The vertical distributions of ice and liquid water have a single peak during spring (March–May) and summer (June–August), but a second peak occurs near the surface during winter (December–February) and fall (September–November). The impacts of seasonally varied cloud water are very much reflected in the cloud radiative forcing at the top-of-atmosphere (TOA) and the surface, as well as in the vertical profiles of radiative heating rates. The cloudy-sky total (shortwave and longwave) radiative heating profile shows a dipole pattern (cooling above and warming below) during spring and summer, while a second peak of cloud radiative cooling appears near the surface during winter and fall.
Abstract
Increased observational analyses provide a unique opportunity to perform years-long cloud-resolving model (CRM) simulations and generate long-term cloud properties that are very much in demand for improving the representation of clouds in general circulation models (GCMs). A year 2000 CRM simulation is presented here using the variationally constrained mesoscale analysis and surface measurements. The year-long (3 January–31 December 2000) CRM surface precipitation is highly correlated with the Atmospheric Radiation Measurement (ARM) observations with a correlation coefficient of 0.97. The large-scale forcing is the dominant factor responsible for producing the precipitation in summer, spring, and fall, but the surface heat fluxes play a more important role during winter when the forcing is weak. The CRM-simulated year-long cloud liquid water path and cloud (liquid and ice) optical depth are also in good agreement (correlation coefficients of 0.73 and 0.64, respectively) with the ARM retrievals over the Southern Great Plains (SGP). The simulated cloud systems have 50% more ice water than liquid water in the annual mean. The vertical distributions of ice and liquid water have a single peak during spring (March–May) and summer (June–August), but a second peak occurs near the surface during winter (December–February) and fall (September–November). The impacts of seasonally varied cloud water are very much reflected in the cloud radiative forcing at the top-of-atmosphere (TOA) and the surface, as well as in the vertical profiles of radiative heating rates. The cloudy-sky total (shortwave and longwave) radiative heating profile shows a dipole pattern (cooling above and warming below) during spring and summer, while a second peak of cloud radiative cooling appears near the surface during winter and fall.
Abstract
The 1997/98 El Niño–induced changes in rainfall vertical structure in the east Pacific (EP) are investigated by using collocated Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) and associated daily SST and 6-hourly reanalysis data during January, February, March, and April of 1998, 1999, and 2000. This study shows that there are five key parameters, that is, surface rain rate, precipitation-top height (or temperature), and precipitation growth rates at upper, middle, and low layers to define a rainfall profile, and those five key parameters are strongly influenced by both SST and large-scale dynamics. Under the influence of 1997/98 El Niño, the precipitation-top heights in the EP were systematically higher by about 1 km than those under non–El Niño conditions, while the freezing level was about 0.5 km higher. Under the constraints of rain type, surface rain rate, and the precipitation top, the shape of rainfall profile still showed significant differences: the rain growth was relatively faster in the mid-layer (−5° to +2°C isotherm) but slower in the lower layer (below +2°C isotherm) under the influence of El Niño. It is also evident that the dependence of precipitation top height on SST was stronger under large-scale decent (non–El Niño) circulations but much weaker under large-scale ascent (El Niño) circulations. The combined effect of larger vertical extent and greater growth rate in the middle layer further shifted latent heating upward as compared with the impact of horizontal changes in the rain type fractions (convective versus stratiform). Such additional latent heating shift would certainly further elevate circulation centers and strengthen the upper-layer circulation.
Abstract
The 1997/98 El Niño–induced changes in rainfall vertical structure in the east Pacific (EP) are investigated by using collocated Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) and associated daily SST and 6-hourly reanalysis data during January, February, March, and April of 1998, 1999, and 2000. This study shows that there are five key parameters, that is, surface rain rate, precipitation-top height (or temperature), and precipitation growth rates at upper, middle, and low layers to define a rainfall profile, and those five key parameters are strongly influenced by both SST and large-scale dynamics. Under the influence of 1997/98 El Niño, the precipitation-top heights in the EP were systematically higher by about 1 km than those under non–El Niño conditions, while the freezing level was about 0.5 km higher. Under the constraints of rain type, surface rain rate, and the precipitation top, the shape of rainfall profile still showed significant differences: the rain growth was relatively faster in the mid-layer (−5° to +2°C isotherm) but slower in the lower layer (below +2°C isotherm) under the influence of El Niño. It is also evident that the dependence of precipitation top height on SST was stronger under large-scale decent (non–El Niño) circulations but much weaker under large-scale ascent (El Niño) circulations. The combined effect of larger vertical extent and greater growth rate in the middle layer further shifted latent heating upward as compared with the impact of horizontal changes in the rain type fractions (convective versus stratiform). Such additional latent heating shift would certainly further elevate circulation centers and strengthen the upper-layer circulation.
Abstract
Given the known shortcomings in representing clouds in global climate models (GCMs), comparisons with observations are critical. The International Satellite Cloud Climatology Project (ISCCP) diagnostic products provide global descriptions of cloud-top pressure and column optical depth that extend over multiple decades. Given the characteristics of the ISCCP product, the model output must be converted into what the ISCCP algorithm would diagnose from an atmospheric column with similar physical characteristics. This study evaluates one component of this so-called ISCCP simulator by comparing ISCCP results with simulated ISCCP diagnostics that are derived from data collected at the Atmospheric Radiation Measurement Program (ARM) Southern Great Plains (SGP) Climate Research Facility. It is shown that if a model were to simulate the cloud radiative profile with the same accuracy as can be derived from the ARM data, the likelihood of that occurrence being classified with similar cloud-top pressure and optical depth as ISCCP would range from 30% to 70% depending on optical depth. The ISCCP simulator improved the agreement of cloud-top pressure between ground-based remote sensors and satellite observations, and we find only minor discrepancies because of the parameterization of cloud-top pressure in the ISCCP simulator. The differences seem to be primarily due to discrepancies between satellite and ground-based sensors in the visible optical depth. The source of the optical depth bias appears to be due to subpixel cloud field variability in the retrieval of optical depths from satellite sensors. These comparisons suggest that caution should be applied to comparisons between models and ISCCP observations until the differences in visible optical depths are fully understood. The simultaneous use of ground-based and satellite retrievals in the evaluation of model clouds is encouraged.
Abstract
Given the known shortcomings in representing clouds in global climate models (GCMs), comparisons with observations are critical. The International Satellite Cloud Climatology Project (ISCCP) diagnostic products provide global descriptions of cloud-top pressure and column optical depth that extend over multiple decades. Given the characteristics of the ISCCP product, the model output must be converted into what the ISCCP algorithm would diagnose from an atmospheric column with similar physical characteristics. This study evaluates one component of this so-called ISCCP simulator by comparing ISCCP results with simulated ISCCP diagnostics that are derived from data collected at the Atmospheric Radiation Measurement Program (ARM) Southern Great Plains (SGP) Climate Research Facility. It is shown that if a model were to simulate the cloud radiative profile with the same accuracy as can be derived from the ARM data, the likelihood of that occurrence being classified with similar cloud-top pressure and optical depth as ISCCP would range from 30% to 70% depending on optical depth. The ISCCP simulator improved the agreement of cloud-top pressure between ground-based remote sensors and satellite observations, and we find only minor discrepancies because of the parameterization of cloud-top pressure in the ISCCP simulator. The differences seem to be primarily due to discrepancies between satellite and ground-based sensors in the visible optical depth. The source of the optical depth bias appears to be due to subpixel cloud field variability in the retrieval of optical depths from satellite sensors. These comparisons suggest that caution should be applied to comparisons between models and ISCCP observations until the differences in visible optical depths are fully understood. The simultaneous use of ground-based and satellite retrievals in the evaluation of model clouds is encouraged.
Abstract
A 1-yr observational study of overcast boundary layer stratus at the U.S. Department of Energy Atmospheric Radiation Measurement Program Southern Great Plains site illustrates that surface radiation has a higher sensitivity to cloud liquid water path variations when compared to cloud drop effective radius variations. The mean, median, and standard deviation of observed cloud liquid water path and cloud drop effective radius are 0.120, 0.101, 0.108 mm and 7.38, 7.13, 2.39 μm, respectively. Liquid water path variations can therefore cause 3 times the variation in optical depth as effective radius—a direct consequence of the comparative variability displayed by the statistics of the two parameters. Radiative transfer calculations demonstrate that, over and above the impact of higher liquid water path variability on optical depth, normalized cloud forcing is 2 times as sensitive to liquid water path variations as it is to effective radius variations. Consequently, radiative transfer calculations of surface flux using observed liquid water paths and a fixed effective radius of 7.5 μm have a 79% correlation with observed values. This higher sensitivity of solar flux to liquid water path is a result of the regimes of natural occurrence of cloud liquid water paths and cloud drop effective radii.
Abstract
A 1-yr observational study of overcast boundary layer stratus at the U.S. Department of Energy Atmospheric Radiation Measurement Program Southern Great Plains site illustrates that surface radiation has a higher sensitivity to cloud liquid water path variations when compared to cloud drop effective radius variations. The mean, median, and standard deviation of observed cloud liquid water path and cloud drop effective radius are 0.120, 0.101, 0.108 mm and 7.38, 7.13, 2.39 μm, respectively. Liquid water path variations can therefore cause 3 times the variation in optical depth as effective radius—a direct consequence of the comparative variability displayed by the statistics of the two parameters. Radiative transfer calculations demonstrate that, over and above the impact of higher liquid water path variability on optical depth, normalized cloud forcing is 2 times as sensitive to liquid water path variations as it is to effective radius variations. Consequently, radiative transfer calculations of surface flux using observed liquid water paths and a fixed effective radius of 7.5 μm have a 79% correlation with observed values. This higher sensitivity of solar flux to liquid water path is a result of the regimes of natural occurrence of cloud liquid water paths and cloud drop effective radii.
Abstract
The Clouds, Aerosol, and Precipitation in the Marine Boundary Layer (CAP-MBL) deployment at Graciosa Island in the Azores generated a 21-month (April 2009–December 2010) comprehensive dataset documenting clouds, aerosols, and precipitation using the Atmospheric Radiation Measurement Program (ARM) Mobile Facility (AMF). The scientific aim of the deployment is to gain improved understanding of the interactions of clouds, aerosols, and precipitation in the marine boundary layer.
Graciosa Island straddles the boundary between the subtropics and midlatitudes in the northeast Atlantic Ocean and consequently experiences a great diversity of meteorological and cloudiness conditions. Low clouds are the dominant cloud type, with stratocumulus and cumulus occurring regularly. Approximately half of all clouds contained precipitation detectable as radar echoes below the cloud base. Radar and satellite observations show that clouds with tops from 1 to 11 km contribute more or less equally to surface-measured precipitation at Graciosa. A wide range of aerosol conditions was sampled during the deployment consistent with the diversity of sources as indicated by back-trajectory analysis. Preliminary findings suggest important two-way interactions between aerosols and clouds at Graciosa, with aerosols affecting light precipitation and cloud radiative properties while being controlled in part by precipitation scavenging.
The data from Graciosa are being compared with short-range forecasts made with a variety of models. A pilot analysis with two climate and two weather forecast models shows that they reproduce the observed time-varying vertical structure of lower-tropospheric cloud fairly well but the cloud-nucleating aerosol concentrations less well. The Graciosa site has been chosen to be a permanent fixed ARM site that became operational in October 2013.
Abstract
The Clouds, Aerosol, and Precipitation in the Marine Boundary Layer (CAP-MBL) deployment at Graciosa Island in the Azores generated a 21-month (April 2009–December 2010) comprehensive dataset documenting clouds, aerosols, and precipitation using the Atmospheric Radiation Measurement Program (ARM) Mobile Facility (AMF). The scientific aim of the deployment is to gain improved understanding of the interactions of clouds, aerosols, and precipitation in the marine boundary layer.
Graciosa Island straddles the boundary between the subtropics and midlatitudes in the northeast Atlantic Ocean and consequently experiences a great diversity of meteorological and cloudiness conditions. Low clouds are the dominant cloud type, with stratocumulus and cumulus occurring regularly. Approximately half of all clouds contained precipitation detectable as radar echoes below the cloud base. Radar and satellite observations show that clouds with tops from 1 to 11 km contribute more or less equally to surface-measured precipitation at Graciosa. A wide range of aerosol conditions was sampled during the deployment consistent with the diversity of sources as indicated by back-trajectory analysis. Preliminary findings suggest important two-way interactions between aerosols and clouds at Graciosa, with aerosols affecting light precipitation and cloud radiative properties while being controlled in part by precipitation scavenging.
The data from Graciosa are being compared with short-range forecasts made with a variety of models. A pilot analysis with two climate and two weather forecast models shows that they reproduce the observed time-varying vertical structure of lower-tropospheric cloud fairly well but the cloud-nucleating aerosol concentrations less well. The Graciosa site has been chosen to be a permanent fixed ARM site that became operational in October 2013.
Abstract
Aqueous chemical processing within cloud and fog water is thought to be a key process in the production and transformation of secondary organic aerosol mass, found abundantly and ubiquitously throughout the troposphere. Yet, significant uncertainty remains regarding the organic chemical reactions taking place within clouds and the conditions under which those reactions occur, owing to the wide variety of organic compounds and their evolution under highly variable conditions when cycled through clouds. Continuous observations from a fixed remote site like Whiteface Mountain (WFM) in New York State and other mountaintop sites have been used to unravel complex multiphase interactions in the past, particularly the conversion of gas-phase emissions of SO2 to sulfuric acid within cloud droplets in the presence of sunlight. These scientific insights led to successful control strategies that reduced aerosol sulfate and cloud water acidity substantially over the following decades. This paper provides an overview of observations obtained during a pilot study that took place at WFM in August 2017 aimed at obtaining a better understanding of Chemical Processing of Organic Compounds within Clouds (CPOC). During the CPOC pilot study, aerosol cloud activation efficiency, particle size distribution, and chemical composition measurements were obtained below-cloud for comparison to routine observations at WFM, including cloud water composition and reactive trace gases. Additional instruments deployed for the CPOC pilot study included a Doppler lidar, sun photometer, and radiosondes to assist in evaluating the meteorological context for the below-cloud and summit observations.
Abstract
Aqueous chemical processing within cloud and fog water is thought to be a key process in the production and transformation of secondary organic aerosol mass, found abundantly and ubiquitously throughout the troposphere. Yet, significant uncertainty remains regarding the organic chemical reactions taking place within clouds and the conditions under which those reactions occur, owing to the wide variety of organic compounds and their evolution under highly variable conditions when cycled through clouds. Continuous observations from a fixed remote site like Whiteface Mountain (WFM) in New York State and other mountaintop sites have been used to unravel complex multiphase interactions in the past, particularly the conversion of gas-phase emissions of SO2 to sulfuric acid within cloud droplets in the presence of sunlight. These scientific insights led to successful control strategies that reduced aerosol sulfate and cloud water acidity substantially over the following decades. This paper provides an overview of observations obtained during a pilot study that took place at WFM in August 2017 aimed at obtaining a better understanding of Chemical Processing of Organic Compounds within Clouds (CPOC). During the CPOC pilot study, aerosol cloud activation efficiency, particle size distribution, and chemical composition measurements were obtained below-cloud for comparison to routine observations at WFM, including cloud water composition and reactive trace gases. Additional instruments deployed for the CPOC pilot study included a Doppler lidar, sun photometer, and radiosondes to assist in evaluating the meteorological context for the below-cloud and summit observations.
