We develop a new climatology of the macrophysical properties of single-layer shallow cumuli (ShCu), such as cloud amount and cloud base/top heights, observed during 19 summers (2000-2018) at the Atmospheric Radiation Measurement (ARM) Program’s Southern Great Plains (SGP) Central Facility in northern Oklahoma, USA. Similar to the established datasets, the climatology incorporates the well-known advantages of the narrow field-of-view (FOV) lidar-radar measurements to resolve the vertical structure of clouds along the wind direction. In contrast to these datasets, the climatology combines the well-known advantages of the wide-FOV sky images to describe the horizontal changes of cloud amount across the wind direction. The recent update includes (1) a new tool for visualization of these across-wind changes with user-selected spatial and temporal resolutions, (2) an additional macrophysical property, the so-called cloud equivalent diameter (CED), estimated over a wide range of cloud sizes (about 0.01–3.5 km) with high temporal resolution (30s) and (3) environmental parameters. Our development of the extended climatology is aimed to enhance understanding of the environmental impact on the diurnal evolution of the cloud macrophysical properties and thus to improve performance of ShCu parameterizations.
Substantial difference between cloud amounts obtained from active and passive remote sensing has been documented by previous studies. The difference is typically attributed to two main factors: the different field-of-view (FOV) (first factor) and different sensitivity to cloud properties (second factor) of the active and passive ground-based instruments. The relative impact of these two main factors on shallow cumuli cloud amount is demonstrated in this study. The demonstration involves a new multi-year (2000-2017) product, which integrates both the active and passive remote sensing data collected at the mid-continental Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) Central Facility. Cloud fraction (CF) obtained from the narrow-FOV lidar-radar observations and wide-FOV fractional sky cover (FSC) acquired from sky images are key components of the integrated product. Results of this study indicate that (1) CF tends to overestimate FSC and this overestimation can be large (~40% on average) even at extended temporal scales (several years) and (2) the observed overestimate is primarily due to different sensitivity of the active and passive remote sensing instruments to shallow cumuli, while the limited FOV of active remote sensing instruments plays a minor role in such overestimation.
Cloud amount is an essential and extensively used macrophysical parameter of cumulus clouds. It is commonly defined as a cloud fraction (CF) from zenith-pointing ground-based active and passive remote sensing. However, conventional retrievals of CF from the remote sensing data with very narrow field-of-view (FOV) may not be representative of the surrounding area. Here we assess its representativeness using an integrated dataset collected at the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) program's Southern Great Plains (SGP) site in Oklahoma, USA. For our assessment with focus on selected days with single-layer cumulus clouds (2005-2016), we include the narrow-FOV ARM Active Remotely Sensed Clouds Locations (ARSCL) and large-FOV Total Sky Imager (TSI) cloud products, the 915-MHz Radar Wind Profiler (RWP) measurements of wind speed and direction, and also high-resolution satellite images from Landsat and the Moderate Resolution Imaging Spectroradiometer (MODIS). We demonstrate that the root-mean-square difference (RMSD) between the 15-min averaged ARSCL cloud fraction (CF) and the 15-min averaged TSI fractional sky cover (FSC) is large (up to 0.3). We also discuss how the horizontal distribution of clouds can modify the obtained large RMSD using a new uniformity metric. The latter utilizes the spatial distribution of the FSC over the 100° FOV TSI images obtained with high temporal resolution (30 sec sampling). We demonstrate that cases with more uniform spatial distribution of FSC show better agreement between the narrow-FOV CF and large-FOV FSC, reducing the RMSD by up to a factor of 2.
Aerosol optical depth (AOD) derived from hyperspectral measurements can serve as an invaluable input for simultaneous retrievals of particle size distributions and major trace gases. The required hyperspectral measurements are provided by a new ground-based radiometer, the so-called Shortwave Array Spectroradiometer-Hemispheric (SAS-He), recently developed with support from the Department of Energy (DOE) Office Atmospheric Radiation Measurement (ARM) Program. The SAS-He has wide spectral coverage (350-1700nm) and high spectral resolution: about 2.4 nm and 6 nm within 350-1000 nm and 970-1700 nm spectral ranges, respectively. To illustrate an initial performance of the SAS-He, we take advantage of integrated dataset collected during the ARM-supported Two-Column Aerosol Project (TCAP) over the US coastal region (Cape Cod, Massachusetts). This dataset includes AODs derived using data from Aerosol Robotic Network (AERONET) sunphotometer and Multi-Filter Rotating Shadowband Radiometer (MFRSR). We demonstrate that, on average, the SAS-He AODs closely match the MFRSR and AERONET AODs in the ultraviolet and visible spectral ranges for this area with highly variable AOD. Also, we discuss corrections of SAS-He total optical depth for gas absorption in the near-infrared spectral range and their operational implementation
Ground-based remote sensing and in situ observations of aerosol microphysical and optical properties have been
collected during summertime (June-August, 2012) as part of the Two-Column Aerosol Project (TCAP;
http://campaign.arm.gov/tcap/), which was supported by the U.S. Department of Energy’s (DOE’s) Atmospheric
Radiation Measurement (ARM) Program (http://www.arm.gov/). The overall goal of the TCAP field campaign is to
study the evolution of optical and microphysical properties of atmospheric aerosol transported from North America to
the Atlantic and their impact on the radiation energy budget. During TCAP, the ground-based ARM Mobile Facility
(AMF) was deployed on Cape Cod, an arm-shaped peninsula situated on the easternmost portion of Massachusetts
(along the east coast of the United States) and that is generally downwind of large metropolitan areas. The AMF site was
equipped with numerous instruments for sampling aerosol, cloud and radiative properties, including a Multi-Filter
Rotating Shadowband Radiometer (MFRSR), a Scanning Mobility Particle Sizer (SMPS), an Aerodynamic Particle Sizer
(APS), and a three-wavelength nephelometer. In this study we present an analysis of diurnal and day-to-day variability
of the column and near-surface aerosol properties obtained from remote sensing (MFRSR data) and ground-based in situ
measurements (SMPS, APS, and nephelometer data). In particular, we show that the observed diurnal variability of the
MFRSR aerosol optical depth is strong and comparable with that obtained previously from the AERONET climatology
in Mexico City, which has a larger aerosol loading. Moreover, we illustrate how the variability of aerosol properties
impacts the direct aerosol radiative forcing at different time scales.
We use combined multi-year measurements from the surface and space for assessing the spatial and temporal distribution of aerosol properties within a large (~400x400 km) region centered on Cape Cod, Massachusetts, along the East Coast of the United States. The ground-based Aerosol Robotic Network (AERONET) measurements at Martha’s Vineyard Coastal Observatory (MVCO) site and Moderate Resolution Imaging Spectrometer (MODIS) sensors on board the Terra and Aqua satellites provide horizontal and temporal variations of aerosol optical depth, while the Cloud- Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) offers the altitudes of aerosol-layers. The combined ground-based and satellite measurements indicated several interesting features among which were the large differences in the aerosol properties observed in July and February. We applied the climatology of aerosol properties for designing the Two-Column Aerosol Project (TCAP), which is supported by the U.S. Department of Energy’s (DOE’s) Atmospheric Radiation Measurement (ARM) Program. The TCAP field campaign involves 12-month deployment (started July 1, 2012) of the ground-based ARM Mobile Facility (AMF) and Mobile Aerosol Observing System (MAOS) on Cape Cod and complimentary aerosol observations from two research aircraft: the DOE Gulfstream-1 (G-1) and the National Aeronautics and Space Administration (NASA) B200 King Air. Using results from the coordinated G-1 and B200 flights during the recent (July, 2012) Intensive Observation Period, we demonstrated that the G-1 in situ measurements and B200 active remote sensing can provide complementary information on the temporal and spatial changes of the aerosol properties off the coast of North America.
We perform a case study for estimating the impact of the vertical distribution of cloud fraction on the normalized cloud
radiative forcing (CRF) using a decade-long (2000-2009) high resolution dataset of cloud macrophysical and radiative
properties. This dataset is developed for fair-weather cumuli (FWC) observed at the U.S. Department of Energy's
Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site. The design of the case study reduces
effects associated with non-cloud factors, such as the diurnal changes of aerosol loading and solar zenith angle. The
results of the case study suggest that the impact of the vertical cloud structure can be substantial. Therefore, taking into
account the vertical distribution of clouds would be beneficial for more comprehensive parameterizations aimed to
portray the complex interactions between clouds and radiation more accurately.
An approach for the obtaining column intensive aerosol properties, namely the single scattering albedo (SSA) and
asymmetry parameter (ASP), from the Multi-Filter Rotating Shadowband Radiometer (MFRSR) spectral observations
under partly cloudy conditions is described. The approach involves the MFRSR-based aerosol retrieval for clear-sky
periods and an interpolation of the retrieved column aerosol properties for cloudy periods. The observed weak diurnal
variability of SSA and ASP at the surface and the close association of the surface intensive aerosol properties with their
column counterparts form the basis of such interpolation. The approach is evaluated by calculating the corresponding
clear-sky total, direct and diffuse fluxes at five wavelengths (415, 500, 615, 673 and 870 nm) and compare them with the
observed fluxes. The aerosol properties provided by this approach are applied for (i) an examination of the statistical
relationship between spectral (visible range) and broadband values of the total normalized cloud radiative forcing and
(ii) an estimation of the fractional sky cover. Data collected during 13 days with single-layer cumulus clouds observed
at U.S. Department of Energy Atmospheric Radiation Measurement (ARM) Climate Research Facility (ACRF) Southern
Great Plains (SGP) site during summer 2007 are applied to illustrate the performance and application of this approach.
We outline a new method, called the ratio method, developed to retrieve aerosol optical depth (AOD) under broken
cloud conditions and present validation results from sensitivity and case studies. Results of the sensitivity study
demonstrate that the ratio method, which exploits ratios of reflectances in the visible spectral range, has the potential for
accurate AOD retrievals under different observational conditions and random errors in input data. Also, we examine the
performance of the ratio method using aircraft data collected during the Cloud and Land Surface Interaction Campaign
(CLASIC) and the Cumulus Humilis Aerosol Processing Study (CHAPS). Results of the case study suggest that the ratio
method has the ability to retrieve AOD from multi-spectral aircraft observations of the reflected solar radiation.
Shallow cumuli are ubiquitous over large areas of the globe, including both the interior of continents and the trade wind
regions over the oceans. Measurements made at the Atmospheric Radiation Measurement (ARM) Climate Research
Facility, located in central North America, provide a unique long-term data set that can be used to investigate the
influence that these clouds have on the shortwave surface energy budget at a continental location. Using data collected
for the summers of 2000 through 2007, inclusive, over 900 hours with fair-weather cumuli were identified using data
from a Total Sky Imager, cloud-radar and lidar. Data from a suite of surface radiometers was used to determine the
shortwave forcing. This analysis estimates the three-dimensional effects of shallow cumuli by examining the occurrences
of both positive and negative shortwave forcing. We show that the average surface shortwave forcing is approximately
-45.5 W m-2. When the data are adjusted to account for periods without shallow clouds, the shortwave forcing over the
entire summer (defined as May through August) are reduced in magnitude, with forcings of -2.1 W m-2.
A novel method for the retrieval of aerosol optical depth (AOD) under partly cloudy conditions has been suggested. The
method exploits reflectance ratios, which are not sensitive to the three-dimensional (3D) effects of clouds. As a result,
the new method provides an effective way to avoid the 3D cloud effects, which otherwise would have a large (up to
140%) contaminating impact on the aerosol retrievals. The 1D version of the radiative transfer model has been used to
develop look-up tables (LUTs) of reflectance ratios as functions of two parameters describing the spectral dependence of
AOD (a power law). The new method implements an innovative 2D inversion for simultaneous retrieval of these two
parameters and, thus, the spectral behavior of AOD. The performance of the new method has been illustrated with a
model-output inverse problem. We demonstrated that the new retrieval has the potential for (i) detection of clear pixels
outside of cloud shadows, (ii) increased "harvest" of such pixels, and (iii) accurate (~15%) estimation of AOD for the
majority of them.
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