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Cloud Thickness from Offbeam Returns (THOR) Validation Campaign on NASA's P3B Over the ARM/SGP

Physical thickness of a cloud layer, sometimes multiple cloud layers, is a crucial controller of solar heating of the Earth- atmosphere system, which drives the convective processes that produce storm systems. Yet clouds of average optical thickness are opaque to conventional lidar, so their thickness is well estimated only by combining a lidar above and another below cloud, or a radar and lidar on the same side, dual facilities not widely available. Here we report initial observations of a new airborne multiple field of view lidar, capable of determining physical thickness of cloud layers from time signatures of off-beam returns from a I kHz micropulse lidar at 540 rim. For a single layer, the time delay of light returning from the outer diffuse halo of light surrounding the beam entry point, relative to the time delay at beam center, determines the cloud physical thickness. The delay combined with the pulse stretch gives the optical thickness. This halo method requires cloud optical thickness exceeding 2, and improves with cloud thickness, thus complimenting conventional lidar, which cannot penetrate thick clouds. Results are presented from March 25, 2002, when THOR flew a butterfly pattern over the ARM site at 8.3 km, above a thin ice cloud at 5 km, and a thick boundary-layer stratus deck with top at 1.3 km, as shown by THOR channel 1, and a base at about 0.3 km as shown by the ground-based MPL. Additional information is included in the original extended abstract.

Cahalan, R. F.↗

Analysis of the Planetary Boundary Layer Height During DISCOVER-AQ Baltimore–Washington, D.C., with Lidar and High-Resolution WRF Modeling

The daytime planetary boundary layer (PBL) was examined for the Deriving Information on Surface Conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) Baltimore (Maryland)–Washington, D.C., campaign of July 2011 using PBL height (PBLH) retrievals from aerosol backscatter measurements from ground-based micropulse lidar (MPL), the NASA Langley Research Center airborne High Spectral Resolution Lidar-1 (HSRL-1), and the Cloud–Aerosol Lidar with Orthogonal Polarization (CALIOP) on the Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite. High-resolution Weather Research and Forecasting (WRF) Model simulations with horizontal grid spacing of 1 km and different combinations of PBL schemes, urban parameterization, and sea surface temperature inputs were evaluated against PBLHs derived from lidars, ozonesondes, and radiosondes. MPL and WRF PBLHs depicted a growing PBL in the morning that reached a peak height by midafternoon. WRF PBLHs calculated from gridded output profiles generally showed more rapid growth and higher peak heights than did the MPLs, and all WRF–lidar differences were dependent on model configuration, PBLH calculation method, and synoptic conditions. At inland locations, WRF simulated an earlier descent of the PBL top in the afternoon relative to the MPL retrievals and radiosonde PBLHs. At Edgewood, Maryland, the influence of the Chesapeake Bay breeze on the PBLH was captured by both the ozonesonde and WRF data but generally not by the MPL PBLH retrievals because of generally weaker gradients in the aerosol backscatter profile and limited normalized relative backscatter data near the top height of the marine layer.

Hegarty, Jennifer D.↗

A New Method to Retrieve the Diurnal Variability of Planetary Boundary Layer Height from Lidar Under Different Thermodynamic Stability Conditions

The planetary boundary layer height (PBLH) is an important parameter for understanding the accumulation of pollutants and the dynamics of the lower atmosphere. Lidar has been used for tracking the evolution of PBLH by using aerosol backscatter as a tracer, assuming aerosol is generally well-mixed in the PBL; however, the validity of this assumption actually varies with atmospheric stability. This is demonstrated here for stable boundary layers (SBL), neutral boundary layers (NBL), and convective boundary layers (CBL) using an 8-year dataset of micropulse lidar (MPL) and radiosonde (RS) measurements at the ARM Southern Great Plains, and MPL at the GSFC site. Due to weak thermal convection and complex aerosol stratification, traditional gradient and wavelet methods can have difficulty capturing the diurnal PBLH variations in the morning and forenoon, as well as under stable conditions generally. A new method is developed that combines lidar-measured aerosol backscatter with a stability dependent model of PBLH temporal variation (DTDS). The latter helps “recalibrate” the PBLH in the presence of a residual aerosol layer that does not change in harmony with PBL diurnal variation. The hybrid method offers significantly improved PBLH detection, with better correlation and smaller biases, under most thermodynamic conditions, especially for SBL and CBL. Relying on the physical process of PBL diurnal development, different schemes are developed for growing, maintenance, and decaying periods. Comprehensive evaluation of this new method shows much better tracking of diurnal PBLH variation and significantly smaller biases under various pollution levels.

Tianning Su↗

Cloud Physics Lidar Measurements During the SAFARI-2000 Field Campaign

A new remote sensing instrument, the Cloud Physics Lidar (CPL) has been built for use on the ER-2 aircraft. The first deployment for CPL was the SAFARI-2000 field campaign during August-September 2000. The CPL is a three-wavelength lidar designed for studies of cirrus, subvisual cirrus, and boundary layer aerosols. The CPL utilizes a high repetition rate, low pulse energy laser with photon counting detectors. A brief description of the CPL instrument will be given, followed by examples of CPL data products. In particular, examples of aerosol backscatter, including boundary layer smoke and cirrus clouds will be shown. Resulting optical depth estimates derived from the aerosol measurements will be shown. Comparisons of the CPL optical depth and optical depth derived from microPulse Lidar and the AATS-14 sunphotomer will be shown.

McGill, Matthew↗

Physical and Optical Characteristics of the October 2010 Haze Event Over Singapore: A Photometric and Lidar Analysis

Trans-boundary biomass burning smoke episodes have increased dramatically during the past 20-30 years and have become an annual phenomenon in the South‐East‐Asia region. On 15th October 2010, elevated levels of fire activity were detected by remote sensing satellites (e.g. MODIS). On the same date, measurements of fine particulate matter (PM2.5) at Singapore and Malaysia found high levels of fine mode particles in the local environment. All these observations were indicative of the initial onset of a smoke episode that lasted for several days. In this work, we investigate the temporal evolution of this smoke episode by analyzing the physical and optical properties of smoke particles with the aid of an AERONET Sun photometer, an MPLNet micropulse lidar, and surface PM2.5 measurements. Elevated levels of fire activity coupled with high aerosol optical depth and PM2.5 were observed over a period of nine days. Increased variability of parameters such as aerosol optical depth, Angstrom exponent number and its fine mode equivalents all indicated high levels of fine particulate presence in the atmosphere. Smoke particle growth due to aging, coagulation and condensation mechanisms was detected during the afternoons and over several days. Retrieved lidar ratios were compatible with the presence of fine particulate within the boundary/aerosol layer. Moreover, retrieved particle size distribution as well as single scattering albedo indicated the prevalence of the fine mode particulate regime as well as particles showing enhanced levels of absorption respectively.

Air quality↗

I’ve Looked at Clouds from Both Sides, Now: Viewpoints from Surface and Spaceborne Lidar Systems

Clouds play a critical role in the Earth’s climate system because they are inextricably linked to the hydrological cycle and radiation budget. Information about cloud height, thickness, occurrence, and amount are critical inputs for a host of numerical applications involving climate research. Therefore, it is important to have highly accurate and quantitative data records of cloud properties that span several years and geographic regions. Verification of even the most basic modeling processes demands long term and continuous observations of global cloud occurrence, if there is to be any confidence in their fidelity. For a number of reasons, however, it is impossible to gauge the complexities of clouds from a single source. Fundamentally, an array of remote sensing methods is needed in order to provide a complete picture. Within the Micropulse Lidar Network (MPLNET), we have developed a new algorithm to improve the quality of our cloud products. The largest impact of the changes to the cloud detection algorithm is evident with high clouds (those with cloud base > 5 km). Furthermore, polarized measurements enable us to determine the cloud thermodynamic phase. Naturally, the next step is to investigate how these improvements compare with observations from spaceborne lidars (e.g. CALIOP) which have a better (unobstructed) view of high clouds. Recent advances in remote sensing have revealed that cirrus clouds are the most common cloud genus observed in the atmosphere. Furthermore, cirrus skew highly towards relatively low cloud optical depths, as observed from both surface and spaceborne viewpoints. The radiative impacts of these findings are quite significant, considering the cumulative effect cirrus exhibit when compared to low clouds.

Jasper R Lewis↗

Airborne Lidar Measurements of Aerosol Optical Properties During SAFARI-2000

The Cloud Physics Lidar (CPL) operated onboard the NASA ER-2 high altitude aircraft during the SAFARI-2000 field campaign. The CPL provided high spatial resolution measurements of aerosol optical properties at both 1064 nm and 532 nm. We present here results of planetary boundary layer (PBL) aerosol optical depth analysis and profiles of aerosol extinction. Variation of optical depth and extinction are examined as a function of regional location. The wide-scale aerosol mapping obtained by the CPL is a unique data set that will aid in future studies of aerosol transport. Comparisons between the airborne CPL and ground-based MicroPulse Lidar Network (MPL-Net) sites are shown to have good agreement.

McGill, M. J.↗

Cloud Spatial Structure and 3D Radiative Transfer

Cloud radiative properties are sensitive to drop size and other parameters of cloud micro-structure, but also to cloud shape, spacing, and other parameters of cloud macro-structure, including internal fractal structure. New information on cloud structure is being derived from a variety of cloud radars and lidars. Ongoing field programs such as DoE/ARM are improving the measurement and modelling of physical and radiative properties of clouds. A parallel effort is underway to improve cloud remote sensing, especially from the new suite of EOS (Earth Observing System) instruments which are beginning to provide higher spectral, spatial resolution, and/or angular resolution. Key parameters for improving pixel-scale retrievals are cloud thickness and photon mean-free-path, which together determine the scale of "radiative smoothing" of cloud fluxes and radiances. This scale has been observed as a change in the spatial spectrum of Landsat cloud radiances, and was also recently found with the Goddard micropulse lidar, by searching for returns from directions nonparallel to the incident beam. "Offbeam" Lidar returns are now being used to estimate the cloud "radiative Green's function", (G). G depends on cloud thickness and may be used to retrieve that important quantity. G is also being applied to improving simple estimates of cloud radiative properties that are based on the "Independent Pixel Approximation" or IPA. This and other measurements of 3D transfer in clouds, coupled with Monte Carlo and other 3D transfer methods, are beginning to provide a better understanding of the dependence of radiation on cloud inhomogeneity, and to suggest new retrieval and parameterization algorithms which take account of cloud inhomogeneity. An international "Intercomparison of 3D Radiation Codes" or I3RC, program is underway to coordinate and evaluate the variety of 3D radiative transfer methods now available, and to make them more widely available. Information is on the Web at: http://climate.gsfc.nasa.gov/I3RC. Input consists of selected cloud fields derived from data sources such as radar, microwave and satellite, and from models involved in the GEWEX Cloud Systems Studies. Output is selected radiative quantities that characterize the large-scale properties of the fields of radiative fluxes and heating. Several example cloud fields will be used to illustrate the effects of cloud inhomogeneity and 3D radiation.

Cahalan, Robert F.↗

Cloud Spatial Structure and 3D Radiative Transfer

Cloud radiative properties are sensitive to drop size and other parameters of cloud micro-structure, but also to cloud shape, spacing, and other parameters of cloud macro-structure, including internal fractal structure. New information on cloud structure is being derived from a variety of cloud radars and lidars. Ongoing field programs such as DoE/ARM (atmospheric radiation measurement) are improving the measurement and modelling of physical and radiative properties of clouds. A parallel effort is underway to improve cloud remote sensing, especially from the new suite of EOS (Earth observing system) instruments which are beginning to provide higher spectral, spatial resolution, and/or angular resolution. Key parameters for improving pixel-scale retrievals are cloud thickness and photon mean-free-path, which together determine the scale of 'radiative smoothing' of cloud fluxes and radiances. This scale has been observed as a change in the spatial spectrum of Landsat cloud radiances, and was also recently found with the Goddard micropulse lidar, by searching for returns from directions nonparallel to the incident beam. 'Offbeam' Lidar returns are now being used to estimate the cloud 'radiative Green's function' (G). G depends on cloud thickness and may be used to retrieve that important quantity. G is also being applied to improving simple estimates of cloud radiative properties that are based on the 'Independent Pixel Approximation' or IPA. This and other measurements of 3D (three dimensional) transfer in clouds, coupled with Monte Carlo and other 3D transfer methods, are beginning to provide a better understanding of the dependence of radiation on cloud inhomogeneity, and to suggest new retrieval and parameterization algorithms which take account of cloud inhomogeneity. An international 'Intercomparison of 3D Radiation Codes' (I3RC) program is underway to coordinate and evaluate the variety of 3D radiative transfer methods now available, and to make them more widely available. Information is on the Web at: http://climate.gsfc.nasa.gov/I3RC. Input consists of selected cloud fields derived from data sources such as radar, microwave and satellite, and from models involved in the GEWEX Cloud Systems Studies. Output is selected radiative quantities that characterize the large-scale properties of the fields of radiative fluxes and heating. Several example cloud fields will be used to illustrate the effects of cloud inhomogeneity and 3D radiation.

Cahalan, Robert F.↗

Airborne Sunphotometry of African Dust and Marine Boundary Layer Aerosols in PRIDE

The Puerto Rico Dust Experiment (PRIDE) was conducted during summer 2000 to study the radiative, microphysical and transport properties of Saharan dust in the Caribbean region. During PRIDE, NASA Ames Research Center's six-channel airborne autotracking sunphotometer (AATS-6) was operated aboard a Piper Navajo airplane based at Roosevelt Roads Naval Station on the northeast coast of Puerto Rico. AATS-6 measurements were taken during 21 science flights off the coast of Puerto Rico in the western Caribbean. Data were acquired within and above the Marine Boundary Layer (MBL) and the Saharan Aerosol Layer (SAL) up to 5.5 km altitude tinder a wide range of dust loadings. Aerosol optical depth (AOD) spectra and columnar water vapor (CWV) values have been calculated from the AATS-6 measurements by using sunphotometer calibration data obtained at Mauna Loa Observatory (3A kin ASL) before (May) and after (October) PRIDE. Mid-visible AOD values measured near the surface during PRIDE ranged from 0.07 on the cleanest day to 0.55 on the most turbid day. Values measured above the MBL were as high as 0.35; values above the SAL were as low as 0.01. The fraction of total column AOD due to Saharan dust cannot be determined precisely from AATS-6 AOD data alone due to the uncertainty in the extent of vertical mixing of the dust down through the MBL. However, analyses of ground-based and airborne in-situ aerosol sampling measurements and ground-based aerosol lidar backscatter data should yield accurate characterization of the vertical mixing that will enable calculation of the Saharan dust AOD component from the sunphotometer data. Examples will be presented showing measured AATS-6 AOD spectra, calculated aerosol extinction and water vapor density vertical profiles, and aerosol size distributions retrieved by inversion of the AOD spectra. Near sea-surface AOD spectra acquired by AATS-6 during horizontal flight legs at 30 m ASL are available for validation of AOD derived from coincident satellite sensor (TOMS, MODIS, MISR) measurements. AATS-6 AOD data acquired during numerous aircraft ascents and descents through the MBL and the SAL should permit atmospheric column closure analyses with respect to aerosol optical depth, extinction, and size distribution by comparison with coincident aircraft-based in-situ particle size distribution measurements and ground-based (Cabras Island, Puerto Rico) micropulse lidar aerosol backscatter measurements. The aerosol information derived from the column closure analyses can be used subsequently to calculate radiative flux changes, which can then be compared with coincident spectral flux measurements taken from aboard the aircraft with a solar spectral flux radiometer.

Livingston, John M.↗

Cloud Spatial Structure and 3D Radiative Transfer

Cloud radiative properties are sensitive to drop size and other parameters of cloud micro-structure, but also to cloud shape,spacing, and other parameters of cloud macro-structure, including internal fractal structure. New information on cloud structure is being derived from a variety of cloud radars, and ongoing field programs such as DoE/ARM. These programs are improving the measurement and modelling of physical and radiative properties of clouds. A parallel effort is underway to improve cloud remote sensing, especially from the new suite of EOS-AM1 instruments which will provide higher spectral, spatial resolution, and/or angular resolution. Key parameters for improving pixel-scale retrievals are cloud thickness and photon mean-free-path, which together determine the scale of "radiative smoothing" of cloud fluxes and radiances. This scale has been observed as a change in the spatial spectrum of Landsat cloud radiances, and was also recently found with the Goddard micropulse lidar, by searching for returns from directions nonparallel to the incident beam. "Offbeam" Lidar returns are now being used to estimate the cloud "radiative Green's function", G,which depends on cloud thickness and may be used to retrieve that important quantity. G is also being applied to improving simple IPA estimates of cloud radiative properties. This and other measurements of 3D transfer in clouds, coupled with Monte Carlo and other 3D transfer methods, are beginning to provide a better understanding of the dependence of radiation on cloud inhomogeneity, and to suggest new retrieval and parameterization algorithms which take account of cloud inhomogeneity.

Cahalan, Robert F.↗

Cloud Spatial Structure and 3D Radiative Transfer

Cloud radiative properties are sensitive to drop size and other parameters of cloud micro-structure, but also to cloud shape,spacing, and other parameters of cloud macro-structure, including internal fractal structure. New information on cloud structure is being derived from a variety of cloud radars. Ongoing field programs such as Department of Energy's Atmospheric Radiation Measurement (DoE/ARM) are improving the measurement and modelling of physical and radiative properties of clouds. A parallel effort is underway to improve cloud remote sensing, especially from the new suite of EOS-AM1 instruments which will provide higher spectral, spatial resolution, and/or angular resolution. Key parameters for improving pixel-scale retrievals are cloud thickness and photon mean-free-path, which together determine the scale of "radiative smoothing" of cloud fluxes and radiances. This scale has been observed as a change in the spatial spectrum of Landsat cloud radiances, and was also recently found with the Goddard micropulse lidar, by searching for returns from directions nonparallel to the incident beam. "Offbeam" Lidar returns are now being used to estimate the cloud "radiative Green's function", G,which depends on cloud thickness and may be used to retrieve that important quantity. G is also being applied to improving simple IPA estimates of cloud radiative properties. This and other measurements of 3D transfer in clouds, coupled with Monte Carlo and other 3D transfer methods, are beginning to provide a better understanding of the dependence of adiation on cloud inhomogeneity, and to suggest new retrieval and parameterization algorithms which take account of cloud inhomogeneity. An international "Intercomparison of 3D Radiation Codes" or I3RC, program is beginning to coordinate and evaluate the variety of 3D radiative transfer methods now available, and to make them more widely available. Information is on the Web at: http://climate.qsfc.nasa.crov/I3RC. Input consists of selected cloud fields derived from data sources such as radar, microwave and satellite, and from models involved in the GEWEX Cloud Systems Studies. Output is selected radiative quantities that characterize the large- scale properties of the fields of radiative fluxes and heating. Several example cloud fields will be used to illustrate.

Cahalan, Robert F.↗

A 3-Year Climatology of Cloud and Radiative Properties Derived from GOES-8 Data Over the Southern Great Plains

While the various instruments maintained at the Atmospheric Radiation Measurement (ARM) Program Southern Great Plains (SGP) Central Facility (CF) provide detailed cloud and radiation measurements for a small area, satellite cloud property retrievals provide a means of examining the large-scale properties of the surrounding region over an extended period of time. Seasonal and inter-annual climatological trends can be analyzed with such a dataset. For this purpose, monthly datasets of cloud and radiative properties from December 1996 through November 1999 over the SGP region have been derived using the layered bispectral threshold method (LBTM). The properties derived include cloud optical depths (ODs), temperatures and albedos, and are produced on two grids of lower (0.5 deg) and higher resolution (0.3 deg) centered on the ARM SGP CF. The extensive time period and high-resolution of the inner grid of this dataset allows for comparison with the suite of instruments located at the ARM CF. In particular, Whole-Sky Imager (WSI) and the Active Remote Sensing of Clouds (ARSCL) cloud products can be compared to the cloud amounts and heights of the LBTM 0.3 deg grid box encompassing the CF site. The WSI provides cloud fraction and the ARSCL computes cloud fraction, base, and top heights using the algorithms by Clothiaux et al. (2001) with a combination of Belfort Laser Ceilometer (BLC), Millimeter Wave Cloud Radar (MMCR), and Micropulse Lidar (MPL) data. This paper summarizes the results of the LBTM analysis for 3 years of GOES-8 data over the SGP and examines the differences between surface and satellite-based estimates of cloud fraction.

Khaiyer, M. M.↗

An Assessment of the Surface Longwave Direct Radiative Effect of Airborne Saharan Dust During the NAMMA Field Campaign

In September 2006, NASA Goddard s mobile ground-based laboratories were deployed to Sal Island in Cape Verde (16.73degN, 22.93degW) to support the NASA African Monsoon Multidisciplinary Analysis (NAMMA) field study. The Atmospheric Emitted Radiance Interferometer (AERI), a key instrument for spectrally characterizing the thermal IR, was used to retrieve the dust IR aerosol optical depths (AOTs) in order to examine the diurnal variability of airborne dust with emphasis on three separate dust events. AERI retrievals of dust AOT are compared with those from the coincident/collocated multifilter rotating shadow-band radiometer (MFRSR), micropulse lidar (MPL), and NASA Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) sensors. The retrieved AOTs are then inputted into the Fu-Liou 1D radiative transfer model to evaluate local instantaneous direct longwave radiative effects (DRE(sub LW)) of dust at the surface in cloud-free atmospheres and its sensitivity to dust microphysical parameters. The top-of-atmosphere DRE(sub LW) and longwave heating rate profiles are also evaluated. Instantaneous surface DRE(sub LW) ranges from 2 to 10 W/sq m and exhibits a strong linear dependence with dust AOT yielding a DRE(sub LW) of 16 W/sq m per unit dust AOT. The DRE(sub LW) is estimated to be approx.42% of the diurnally averaged direct shortwave radiative effect at the surface but of opposite sign, partly compensating for the shortwave losses. Certainly nonnegligible, the authors conclude that DRE(sub LW) can significantly impact the atmospheric energetics, representing an important component in the study of regional climate variation.

Hansell, R. A.↗

Study of MPLNET-Derived Aerosol Climatology over Kanpur, India, and Validation of CALIPSO Level 2 Version 3 Backscatter and Extinction Products

The level 2 aerosol backscatter and extinction profiles from the NASA Micropulse Lidar Network (MPLNET) at Kanpur, India, have been studied from May 2009 to September 2010. Monthly averaged extinction profiles from MPLNET shows high extinction values near the surface during October March. Higher extinction values at altitudes of 24 km are observed from April to June, a period marked by frequent dust episodes. Version 3 level 2 Cloud Aerosol Lidar with Orthogonal Polarization (CALIOP) aerosol profile products have been compared with corresponding data from MPLNET over Kanpur for the above-mentioned period. Out of the available backscatter profiles, the16 profiles used in this study have time differences less than 3 h and distances less than 130 km. Among these profiles, four cases show good comparison above 400 m with R2 greater than 0.7. Comparison with AERONET data shows that the aerosol type is properly identified by the CALIOP algorithm. Cloud contamination is a possible source of error in the remaining cases of poor comparison. Another source of error is the improper backscatter-to-extinction ratio, which further affects the accuracy of extinction coefficient retrieval.

extinction profiles↗

MPLNET V3 Cloud and Planetary Boundary Layer Detection

The NASA Micropulse Lidar Network Version 3 algorithms for planetary boundary layer and cloud detection are described and differences relative to the previous Version 2 algorithms are highlighted. A year of data from the Goddard Space Flight Center site in Greenbelt, MD consisting of diurnal and seasonal trends is used to demonstrate the results. Both the planetary boundary layer and cloud algorithms show significant improvement of the previous version.

cloud detection↗

(GO)2-SIM: a GCM-Oriented Ground-Observation Forward-Simulator Framework for Objective Evaluation of Cloud and Precipitation Phase

General circulation model (GCM) evaluation using ground-based observations is complicated by inconsistencies in hydrometeor and phase definitions. Here we describe (GO)2-SIM, a forward simulator designed for objective hydrometeor-phase evaluation, and assess its performance over the North Slope of Alaska using a 1-year GCM simulation. For uncertainty assessment, 18 empirical relationships are used to convert model grid-average hydrometeor (liquid and ice, cloud, and precipitation) water contents to zenith polarimetric micropulse lidar and Ka-band Doppler radar measurements, producing an ensemble of 576 forward-simulation realizations. Sensor limitations are represented in forward space to objectively remove from consideration model grid cells with undetectable hydrometeor mixing ratios, some of which may correspond to numerical noise.Phase classification in forward space is complicated by the inability of sensors to measure ice and liquid signals distinctly. However, signatures exist in lidar–radar space such that thresholds on observables can be objectively estimated and related to hydrometeor phase. The proposed phase-classification technique leads to misclassification in fewer than 8% of hydrometeor-containing grid cells. Such misclassifications arise because, while the radar is capable of detecting mixed-phase conditions, it can mistake water- for ice-dominated layers. However, applying the same classification algorithm to forward-simulated and observed fields should generate hydrometeor-phase statistics with similar uncertainty. Alternatively, choosing to disregard how sensors define hydrometeor phase leads to frequency of occurrence discrepancies of up to 40%. So, while hydrometeor-phase maps determined in forward space are very different from model "reality" they capture the information sensors can provide and thereby enable objective model evaluation.

Lamer, K.↗

Aerosol Radiative Effects over Ascension Island Using LASIC Observations and MERRA-2

Marine boundary layer clouds, including the transition from stratocumulus to cumulus, are poorly represented in numerical weather prediction and general circulation models. In many cases, the complex physical relationships between marine boundary cloud morphology and the environmental conditions in which the clouds exist are not well understood. Such uncertainties arise in the presence of biomass burning carbonaceous aerosol, as is the case over the southeast Atlantic Ocean. It is likely that the absorbing and heating properties of these aerosols influence the microphysical composition and macrophysical arrangement of marine stratocumulus and trade cumulus in this region; however, this has yet to be quantified. The deployment of the Atmospheric Radiation Measurement Mobile Facility #1 (AMF1) in support of LASIC (Layered Atlantic Smoke Interactions with Clouds) provided a unique opportunity to collect observations of cloud and aerosol properties during two consecutive biomass burning seasons during July through October of 2016 and 2017 over Ascension Island (7.96 S, 14.35 W). Thermodynamic profiles will be analyzed through the unique combination of sounding data from radiosonde launches and microwave profiling radiometers, giving observations of additional quantities important for cloud development such as CAPE and CIN at a fine temporal resolution. The thermodynamic profiles will be presented in conjunction with detailed observations of the cloud structure over the site from a K-band cloud radar, micropulse lidar, and laser ceilometer. Finally, the observed thermodynamic and cloud profiles will be used as input forcing, alongside aerosols from the Modern Era Retrospective analysis for Research and Applications, version 2 (MERRA-2), for the Rapid Radiative Transfer Model (RRTM) to gain information regarding the radiative heating profiles. Idealized experiments using RRTM with and without aerosols will be used to quantify the impact of biomass burning carbonaceous aerosol plumes as they pass over the site.

Collow, Allie↗