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Industry advances have greatly reduced the cost and size of ground-based shortwave (SW) sensors for the ultraviolet, visible, and near-infrared spectral ranges that make up the solar spectrum, while simultaneously increasing their ruggedness, reliability, and calibration accuracy needed for outdoor operation. These sensors and collocated meteorological equipment are an important part of the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) User Facility, which has supported parallel integrated measurements of atmospheric and surface properties for more than two decades at fixed and mobile sites around the world. The versatile capability of these ground-based measurements includes 1) rich spectral information required for retrieving cloud and aerosol microphysical properties, such as cloud phase, cloud particle size, and aerosol size distributions, and 2) high temporal resolution needed for capturing fast evolution of cloud microphysical properties in response to rapid changes in meteorological conditions. Here we describe examples of how ARM’s spectral radiation measurements are being used to improve understanding of the complex processes governing microphysical, optical, and radiative properties of clouds and aerosol.

Cloud cover estimates of single-layer shallow cumuli obtained from narrow field-of-view (FOV) lidar–radar and wide-FOV total sky imager (TSI) data are compared over an extended period (2000–2017 summers) at the established United States Atmospheric Radiation Measurement mid-continental Southern Great Plains site. We quantify the impacts of two factors on hourly and sub-hourly cloud cover estimates: (1) instrument-dependent cloud detection and data merging criteria and (2) FOV configuration. Enhanced observations at this site combine the advantages of the ceilometer, micropulse lidar (MPL) and cloud radar in merged data products. Data collected by these three instruments are used to calculate narrow-FOV cloud fraction (CF) as a temporal fraction of cloudy returns within a given period. Sky images provided by TSI are used to calculate the wide-FOV fractional sky cover (FSC) as a fraction of cloudy pixels within a given image. To assess the impact of the first factor on CF obtained from the merged data products, we consider two additional subperiods (2000–2010 and 2011–2017 summers) that mark significant instrumentation and algorithmic advances in the cloud detection and data merging. We demonstrate that CF obtained from ceilometer data alone and FSC obtained from sky images provide the most similar and consistent cloud cover estimates; hourly bias and root-mean-square difference (RMSD) are within 0.04 and 0.12, respectively. However, CF from merged MPL–ceilometer data provides the largest estimates of the multiyear mean cloud cover, about 0.12 (35 %) and 0.08 (24 %) greater than FSC for the first and second subperiods, respectively. CF from merged ceilometer–MPL–radar data has the strongest subperiod dependence with a bias of 0.08 (24 %) compared to FSC for the first subperiod and shows no bias for the second subperiod. The strong period dependence of CF obtained from the combined ceilometer–MPL–radar data is likely results from a change in what sensors are relied on to detect clouds below 3 km. After 2011, the MPL stopped being used for cloud top height detection below 3 km, leaving the radar as the only sensor used in cloud top height retrievals. To quantify the FOV impact, a narrow-FOV FSC is derived from the TSI images. We demonstrate that FOV configuration does not modify the bias but impacts the RMSD (0.1 hourly, 0.15 sub-hourly). In particular, the FOV impact is significant for sub-hourly observations, where 41 % of narrow- and wide-FOV FSC differ by more than 0.1. A new “quick-look” tool is introduced to visualize impacts of these two factors through integration of CF and FSC data with novel TSI-based images of the spatial variability in cloud cover. The influence of cloud field organization, such cloud streets parallel to the wind direction, on narrow- and wide-FOV cloud cover estimates can be visually assessed.

Long-term records of aerosol optical depth (AOD) with high quality, suitable temporal continuity and spatial coverage are of immense interest to climate-related research activities. Both satellite- and ground-based measurements of AOD are typically provided by instruments with different designs, and distinct data acquisition and processing schemes. Thus, the corresponding AOD records likely have different accuracy, spatial coverage, and temporal resolution. Several studies have been focused on the synergy of multi-sensor satellite AOD products. Here we combine multi-year (1997-2018) AOD records available from four collocated ground-based instruments deployed at the mid-continental Southern Great Plains (SGP) Central Facility supported by the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) Program. We demonstrate how to minimize drawbacks (patchy spots) and to maintain benefits (high quality) of these records. Our demonstration finds a combined AOD obtained at two wavelengths (500 and 870 nm), with high temporal resolution (1-min), and provides the user with an estimate of the AOD uncertainty. Finally, we highlight expected applications of the merged dataset and its future extensions.

Aerosol optical depth (AOD) characterizes the aerosol burden in the atmosphere, while its wavelength dependence is a sign of particle size. Long-term records of wavelength-resolved AOD with high quality and suitable continuity are required for climate change assessment. Typically, climate-related studies use AOD products provided by several, and perhaps different, ground-based instruments. The measurements from these instruments often have different accuracy and temporal resolution. To preserve the advantages of these products (high quality) and to reduce their disadvantages (patchy records), we generate a merged dataset obtained from four instruments deployed at a US continental site in which a nearly-continuous AOD record is found at two wavelengths (500 and 870 nm) with high quality and high temporal resolution (1-min) for a 21-yr period (1997–2018). The combined dataset addresses: (1) varying data quality and resolution mismatch of the individual AOD records, and (2) the uncertainty of the merged AOD and its relevance for user-specified needs. The generated dataset will be beneficial for a wide range of applications including aerosol-radiation interactions., Measurement(s) aerosol optical depth Technology Type(s) atmospheric observatory system Factor Type(s) year of data collection Sample Characteristic - Environment atmosphere Sample Characteristic - Location State of Oklahoma Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.13256699

Opening remarks by conference chairs for conference Remote Sensing of Clouds and Atmosphere XXV

While the importance of supermicron particles on human health and climate is well recognized, knowledge of their size‐related properties remains elusive. Many routine near‐surface in situ measurements of aerosol properties include size spectra of submicron particles and aerosol total scattering coefficient at three visible wavelengths and two size cutoffs. These properties are collected, for example, at the U.S. Department of Energy's Atmospheric Radiation Measurement (ARM) user facility. Our study illustrates how these conventional measurements can be used to predict total particle volume (particle size

Aerosol columnar size distributions (SDs) are commonly provided by aerosol inversions based on measurements of both spectral extinction and sky radiance. These inversions developed for a fully clear sky offer few SDs for areas with abundant clouds. Here, we estimate SDs from spectral extinction data alone for cloudy coastal and maritime regions using aerosol refractive index (RI) obtained from chemical composition data. Our estimation involves finding volume and mean radius of lognormally distributed modes of an assumed bimodal size distribution through fitting of the spectral extinction data. We demonstrate that vertically integrated SDs obtained from aircraft measurements over a coastal site have distinct seasonal changes, and these changes are captured reasonably well by the estimated columnar SDs. We also demonstrate that similar seasonal changes occur at a maritime site, and columnar SDs retrieved from the combined extinction and sky radiance measurements are approximated quite well by their extinction only counterparts (correlation exceeds 0.9) during a 7-year period (2013–2019). The level of agreement between the estimated and retrieved SDs depends weakly on wavelength selection within a given spectral interval (roughly 0.4–1 µm). Since the extinction-based estimations can be performed frequently for partly cloudy skies, the number of periods where SDs can be found is greatly increased.

This work is motivated by previous studies of transatlantic transport of Saharan dust and the observed quasi-static nature of coarse mode aerosol with a volume median diameter (VMD) of approximately 3.5 μm. The authors examine coarse mode contributions from transpacific transport of dust to North American aerosol properties using a dataset collected at the high-elevation Storm Peak Laboratory (SPL) and the nearby Atmospheric Radiation Measurement (ARM) Mobile Facility. Collected ground-based data are complemented by quasi-global model simulations and satellite and ground-based observations. The authors identify a major dust event associated mostly with a transpacific plume (about 65% of near-surface aerosol mass) in which the coarse mode with moderate (~3 μm) VMD is distinct and contributes substantially to total aerosol volume (up to 70%) and scattering (up to 40%). The results demonstrate that the identified plume at the SPL site has a considerable fraction of supermicron particles (VMD ~3 μm) and, thus, suggest that these particles have a fairly invariant behavior despite transpacific transport. If confirmed in additional studies, this invariant behavior may simplify considerably parameterizations for size-dependent processes associated with dust transport and removal.

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.

The Two-Column Aerosol Project (TCAP), conducted from June 2012 through June 2013, was a unique study designed to provide a comprehensive data set that can be used to investigate a number of important climate science questions, including those related to aerosol mixing state and aerosol radiative forcing. The study was designed to sample the atmosphere between and within two atmospheric columns; one fixed near the coast of North America (over Cape Cod, MA) and a second moveable column over the Atlantic Ocean several hundred kilometers from the coast. The U.S. Department of Energy's (DOE) Atmospheric Radiation Measurement (ARM) Mobile Facility (AMF) was deployed at the base of the Cape Cod column, and the ARM Aerial Facility was utilized for the summer and winter intensive observation periods. One important finding from TCAP is that four of six nearly cloud-free flight days had aerosol layers aloft in both the Cape Cod and maritime columns that were detected using the nadir pointing second-generation NASA high-spectral resolution lidar (HSRL-2). These layers contributed up to 60% of the total observed aerosol optical depth (AOD). Many of these layers were also intercepted by the aircraft configured for in situ sampling, and the aerosol in the layers was found to have increased amounts of biomass burning material and nitrate compared to aerosol found near the surface. In addition, while there was a great deal of spatial and day-to-day variability in the aerosol chemical composition and optical properties, no systematic differences between the two columns were observed.

The total aerosol burden in the atmosphere is typically represented by aerosol optical depth (AOD). To capture important and climate-relevant signatures of the aerosol burden, such as year-to-year and seasonal variability, continuous multi-year AOD observations are required. For more than two decades, these observations have been performed at the mid-continental Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) Central Facility (CF) using ground-based passive remote sensing. The partially overlapping and fragmentary AOD records at the ARM SGP CF have been provided by four individual instruments, namely two co-located (C1 and E13) Multifilter Rotating Shadowband Radiometers (MFRSRs), a Normal Incidence Multifilter Radiometer (NIMFR), and a Cimel Sunphotometer (CSPHOT). Since these individual records are sporadic with instrument- and time-dependent data quality, development of a continuous multi-year high-quality AOD dataset is a challenging task. In this work, an initial development of a continuous 20-year (1997-2017) high-quality AOD product is introduced. The development involves (1) incorporation of the available data quality information and delivery of the historical time series of AOD with high quality from four individual instruments, (2) comparison of multiple AOD retrievals to identify potential instrument-related issues and/or retrieval problems, and (3) merging these individual time series, generation of a two-decade continuous climatology of high-quality AOD and reporting of the uncertainty estimations of the merged product.

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.

The diffuse all-sky surface irradiances measured at two nearby wavelengths in the visible spectral range and their modeled clear-sky counterparts are the main components of a new method for estimating the fractional sky cover of different cloud types, including cumuli. The performance of this method is illustrated using 1-min resolution data from a ground-based Multi-Filter Rotating Shadowband Radiometer (MFRSR). The MFRSR data are collected at the US Department of Energy Atmospheric Radiation Measurement (ARM) Climate Research Facility (ACRF) Southern Great Plains (SGP) site during the summer of 2007 and represent 13 days with cumuli. Good agreement is obtained between estimated values of the fractional sky cover and those provided by a well-established independent method based on broadband observations.

We present a framework for calculating the total scattering of both non-absorbing and absorbing aerosol at ambient conditions from aircraft data. Our framework is developed emphasizing the explicit use of chemical composition data for estimating the complex refractive index (RI) of particles, and thus obtaining improved ambient size spectra derived from Optical Particle Counter (OPC) measurements. The feasibility of our framework for improved calculations of total scattering is demonstrated using three types of data collected by the U.S. Department of Energy’s (DOE) aircraft during the Two-Column Aerosol Project (TCAP). Namely, these data types are: (1) size distributions measured by a suite of OPC’s, (2) chemical composition data measured by an Aerosol Mass Spectrometer and a Single Particle Soot Photometer, and (3) the dry total scattering coefficient measured by a integrating nephelometer and scattering enhancement factor measured with a humidification system. We demonstrate that good agreement (~10%) between the observed and calculated scattering can be obtained under ambient conditions (RH &lt, 80%) by applying chemical composition data for the RI-based correction of the OPC-derived size spectra. We also demonstrate that ignoring the RI-based correction or using non-representative RI values can cause a substantial underestimation (~40%) or overestimation (~35%) of the calculated scattering, respectively.

Fast and accurate radiative transfer model is the key for satellite data analysis, numerical weather prediction, and observation system simulation experiments for climate study applications. We have developed a Principal Component-based radiative transfer model (PCRTM) which can simulate radiative transfer in the cloudy atmosphere from far IR to visible and UV spectral regions quickly and accurately. Multi-scattering of multiple layers of clouds/aerosols is included in the model. A hybrid stream discrete multiple scattering scheme is used to minimizing the number calculation need. The computation speed is 3 to 4 orders of magnitude faster than the medium speed correlated-k option MODTRAN5 and LBLRTM. The PCRTM calculated radiance spectra agree with the Modtran and LBLRTM within 0.02%. Application of this model to various hyperspectral instrument will be shown and discuss.

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.

Tower-based data combined with high-resolution satellite products have been used to produce surface albedo at various spatial scales over land. Because tower-based albedo data are available at only a few sites, surface albedos using these combined data are spatially limited. Moreover, tower-based albedo data are not representative of highly heterogeneous regions. To produce areal-averaged and spectrally-resolved surface albedo for regions with various degrees of surface heterogeneity, we have developed a transmission-based retrieval and demonstrated its feasibility for relatively homogeneous land surfaces. Here, we demonstrate its feasibility for a highly heterogeneous coastal region. We use the atmospheric transmission measured during a 19-month period (June 2009–December 2010) by a ground-based Multi-Filter Rotating Shadowband Radiometer (MFRSR) at five wavelengths (0.415, 0.5, 0.615, 0.673 and 0.87 µm) at the Department of Energy’s Atmospheric Radiation Measurement (ARM) Mobile Facility (AMF) site located on Graciosa Island. We compare the MFRSR-retrieved areal-averaged surface albedo with albedo derived from Moderate Resolution Imaging Spectroradiometer (MODIS) observations, and also a composite-based albedo. We demonstrate that these three methods produce similar spectral signatures of surface albedo; however, the MFRSR-retrieved albedo, is higher on average (≤0.04) than the MODIS-based areal-averaged surface albedo and the largest difference occurs in winter.

We propose here a novel approach for retrieving in parallel the effective density and real refractive index of weakly absorbing aerosol from optical and size distribution measurements. Here we define "weakly absorbing" as aerosol single-scattering albedos that exceed 0.95 at 0.5 μm. The required optical measurements are the scattering coefficient and the hemispheric backscatter fraction, obtained in this work from an integrating nephelometer. The required size spectra come from mobility and aerodynamic particle size spectrometers commonly referred to as a scanning mobility particle sizer and an aerodynamic particle sizer. The performance of this approach is first evaluated using a sensitivity study with synthetically generated but measurement-related inputs. The sensitivity study reveals that the proposed approach is robust to random noise; additionally the uncertainties of the retrieval are almost linearly proportional to the measurement errors, and these uncertainties are smaller for the real refractive index than for the effective density. Next, actual measurements are used to evaluate our approach. These measurements include the optical, microphysical, and chemical properties of weakly absorbing aerosol which are representative of a variety of coastal summertime conditions observed during the Two-Column Aerosol Project (TCAP; http://campaign.arm.gov/tcap/). The evaluation includes calculating the root mean square error (RMSE) between the aerosol characteristics retrieved by our approach, and the same quantities calculated using the conventional volume mixing rule for chemical constituents. For dry conditions (defined in this work as relative humidity less than 55%) and sub-micron particles, a very good (RMSE ~ 3%) and reasonable (RMSE ~ 28%) agreement is obtained for the retrieved real refractive index (1.49 ± 0.02) and effective density (1.68 ± 0.21), respectively. Our approach permits discrimination between the retrieved aerosol characteristics of sub-micron and sub-10-micron particles. The evaluation results also reveal that the retrieved density and refractive index tend to decrease with an increase of the relative humidity.

We present here a simple retrieval of the areal-averaged spectral surface albedo using only ground-based measurements of atmospheric transmission under fully overcast conditions. Our retrieval is based on a one-line equation. The feasibility of our retrieval for routine determinations of albedo is demonstrated for different landscapes with various degrees of heterogeneity using three sets of measurements: (1) spectral atmospheric transmission from the Multi-Filter Rotating Shadowband Radiometer (MFRSR) at five wavelengths (415, 500, 615, 673, and 870 nm); (2) tower-based measurements of local surface albedo at the same wavelengths; and (3) areal-averaged surface albedo at four wavelengths (470, 560, 670 and 860 nm) from collocated and coincident Moderate Resolution Imaging Spectroradiometer (MODIS) observations. These integrated datasets cover both temporally long (2008–2013) and short (April–May 2010) periods at the Atmospheric Radiation Measurement (ARM) Southern Great Plains site and the National Oceanic and Atmospheric Administration (NOAA) Table Mountain site, respectively. The calculated root mean square error (RMSE), defined here as the root mean squared difference between the MODIS-derived surface albedo and the retrieved areal-averaged albedo, is quite small (RMSE ≤ 0.015) and comparable with that obtained previously by other investigators for the shortwave broadband albedo. Good agreement between tower-based measurements of daily-averaged surface albedo for completely overcast and non-overcast conditions is also demonstrated.

Strong diurnal variability of aerosol has been observed frequently for many urban/industrial regions. How this variability may alter the direct aerosol radiative forcing (DARF), however, is largely unknown. To quantify changes in the time-averaged DARF, we perform an assessment of 29 days of high temporal resolution ground-based data collected during the Two-Column Aerosol Project (TCAP) on Cape Cod, which is downwind of metropolitan areas. We demonstrate that strong diurnal changes of aerosol loading (about 20% on average) have a negligible impact on the 24-h average DARF, when daily averaged optical properties are used to find this quantity. However, when there is a sparse temporal sampling of aerosol properties, which may preclude the calculation of daily averaged optical properties, large errors (up to 100%) in the computed DARF may occur. We describe a simple way of reducing these errors, which suggests the minimal temporal sampling needed to accurately find the forcing.

A new treatment for shallow clouds has been introduced into the Weather Research and Forecasting Model (WRF). The new scheme, called the cumulus potential (CuP) scheme, replaces the ad hoc trigger function used in the Kain–Fritsch cumulus parameterization with a trigger function related to the distribution of temperature and humidity in the convective boundary layer via probability density functions (PDFs). An additional modification to the default version of WRF is the computation of a cumulus cloud fraction based on the time scales relevant for shallow cumuli. Results from three case studies over the U.S. Department of Energy’s Atmospheric Radiation Measurement (ARM) site in north-central Oklahoma are presented. These cases were selected because of the presence of shallow cumuli over the ARM site. The modified version of WRF does a much better job predicting the cloud fraction and the downwelling shortwave irradiance than control simulations utilizing the default Kain–Fritsch scheme. The modified scheme includes a number of additional free parameters, including the number and size of bins used to define the PDF, the minimum frequency of a bin within the PDF before that bin is considered for shallow clouds to form, and the critical cumulative frequency of bins required to trigger deep convection. A series of tests were undertaken to evaluate the sensitivity of the simulations to these parameters. Overall, the scheme was found to be relatively insensitive to each of the parameters.

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

Substantial uncertainties still exist in the scientific understanding of the possible interactions between urban and natural (biogenic) emissions in the production and transformation of atmospheric aerosol and the resulting impact on climate change. The US Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) program's Carbonaceous Aerosol and Radiative Effects Study (CARES) carried out in June 2010 in Central Valley, California, was a comprehensive effort designed to improve this understanding. The primary objective of the field study was to investigate the evolution of secondary organic and black carbon aerosols and their climate-related properties in the Sacramento urban plume as it was routinely transported into the forested Sierra Nevada foothills area. Urban aerosols and trace gases experienced significant physical and chemical transformations as they mixed with the reactive biogenic hydrocarbons emitted from the forest. Two heavily-instrumented ground sites – one within the Sacramento urban area and another about 40 km to the northeast in the foothills area – were set up to characterize the evolution of meteorological variables, trace gases, aerosol precursors, aerosol size, composition, and climate-related properties in freshly polluted and "aged" urban air. On selected days, the DOE G-1 aircraft was deployed to make similar measurements upwind and across the evolving Sacramento plume in the morning and again in the afternoon. The NASA B-200 aircraft, carrying remote sensing instruments, was also deployed to characterize the vertical and horizontal distribution of aerosols and aerosol optical properties within and around the plume. This overview provides: (a) the scientific background and motivation for the study, (b) the operational and logistical information pertinent to the execution of the study, (c) an overview of key observations and initial findings from the aircraft and ground-based sampling platforms, and (d) a roadmap of planned data analyses and focused modeling efforts that will facilitate the integration of new knowledge into improved representations of key aerosol processes and properties in climate models., United States. Dept. of Energy. Atmospheric System Research Program (Contract DE-AC06-76RLO 1830), United States. National Oceanic and Atmospheric Administration, United States. National Aeronautics and Space Administration. HQ Science Mission Directorate Radiation Sciences Program, United States. National Aeronautics and Space Administration. CALIPSO Program, United States. Dept. of Energy. Atmospheric Radiation Measurement Program (Interagency Agreement No. DE-AI02-05ER63985)

Much of the large uncertainty in estimates of anthropogenic aerosol effects on climate arises from the multi-scale nature of the interactions between aerosols, clouds and dynamics, which are difficult to represent in conventional general circulation models (GCMs). In this study, we use a multi-scale aerosol-climate model that treats aerosols and clouds across multiple scales to study aerosol indirect effects. This multi-scale aerosol-climate model is an extension of a multi-scale modeling framework (MMF) model that embeds a cloud-resolving model (CRM) within each vertical column of a GCM grid. The extension allows a more physically-based treatment of aerosol-cloud interactions in both stratiform and convective clouds on the global scale in a computationally feasible way. Simulated model fields, including liquid water path (LWP), ice water path, cloud fraction, shortwave and longwave cloud forcing, precipitation, water vapor, and cloud droplet number concentration are in reasonable agreement with observations. The new model performs quantitatively similar to the previous version of the MMF model in terms of simulated cloud fraction and precipitation. The simulated change in shortwave cloud forcing from anthropogenic aerosols is −0.77 W m−2, which is less than half of that (−1.79 W m−2) calculated by the host GCM (NCAR CAM5) with traditional cloud parameterizations and is also at the low end of the estimates of other conventional global aerosol-climate models. The smaller forcing in the MMF model is attributed to a smaller (3.9 %) increase in LWP from preindustrial conditions (PI) to present day (PD) compared with 15.6 % increase in LWP in stratiform clouds in CAM5. The difference is caused by a much smaller response in LWP to a given perturbation in cloud condensation nuclei (CCN) concentrations from PI to PD in the MMF (about one-third of that in CAM5), and, to a lesser extent, by a smaller relative increase in CCN concentrations from PI to PD in the MMF (about 26 % smaller than that in CAM5). The smaller relative increase in CCN concentrations in the MMF is caused in part by a smaller increase in aerosol lifetime from PI to PD in the MMF, a positive feedback in aerosol indirect effects induced by cloud lifetime effects from aerosols. The smaller response in LWP to anthropogenic aerosols in the MMF model is consistent with observations and with high resolution model studies, which may indicate that aerosol indirect effects simulated in conventional global climate models are overestimated and point to the need to use global high resolution models, such as MMF models or global CRMs, to study aerosol indirect effects. The simulated total anthropogenic aerosol effect in the MMF is −1.05 W m−2, which is close to the Murphy et al. (2009) inverse estimate of −1.1±0.4 W m−2 (1σ) based on the examination of the Earth's energy balance. Further improvements in the representation of ice nucleation and low clouds in MMF are needed to refine the aerosol indirect effect estimate.

The Markovian approach, originally suggested in the early 1900s, has widespread practical use in many of our present-day studies and allows one to build bridges between diverse research areas such as statistical physics, astronomy, and computational science. This overview takes a broad sweep of several important examples with the emphasis on the stochastic radiative transfer in a cloudy atmosphere. In particular, the overview (i) highlights important contributions made by Pomraning and Titov to the neutron and radiation transport theory in a stochastic medium with homogeneous statistics and (ii) illustrates that ideas and tools introduced by these two distinguished scientists are gaining increasing impact and recognition in the atmospheric science.

Anthropogenic aerosol effects on climate produce one of the largest uncertainties in estimates of radiative forcing of past and future climate change. Much of this uncertainty arises from the multi-scale nature of the interactions between aerosols, clouds and large-scale dynamics, which are difficult to represent in conventional general circulation models (GCMs). In this study, we develop a multi-scale aerosol-climate model that treats aerosols and clouds across different scales, and evaluate the model performance, with a focus on aerosol treatment. This new model is an extension of a multi-scale modeling framework (MMF) model that embeds a cloud-resolving model (CRM) within each grid column of a GCM. In this extension, the effects of clouds on aerosols are treated by using an explicit-cloud parameterized-pollutant (ECPP) approach that links aerosol and chemical processes on the large-scale grid with statistics of cloud properties and processes resolved by the CRM. A two-moment cloud microphysics scheme replaces the simple bulk microphysics scheme in the CRM, and a modal aerosol treatment is included in the GCM. With these extensions, this multi-scale aerosol-climate model allows the explicit simulation of aerosol and chemical processes in both stratiform and convective clouds on a global scale. Simulated aerosol budgets in this new model are in the ranges of other model studies. Simulated gas and aerosol concentrations are in reasonable agreement with observations (within a factor of 2 in most cases), although the model underestimates black carbon concentrations at the surface by a factor of 2–4. Simulated aerosol size distributions are in reasonable agreement with observations in the marine boundary layer and in the free troposphere, while the model underestimates the accumulation mode number concentrations near the surface, and overestimates the accumulation mode number concentrations in the middle and upper free troposphere by a factor of about 2. The overestimation of accumulation model number concentrations in the middle and upper free troposphere is consistent with large aerosol mass fraction above 5 km in the MMF model compared with other models. Simulated cloud condensation nuclei (CCN) concentrations are within the observational variations. Simulated aerosol optical depths (AOD) are in reasonable agreement with observations (within a factor of 2), and the spatial distribution of AOD is consistent with observations, while the model underestimates AOD over regions with strong fossil fuel and biomass burning emissions. Overall, this multi-scale aerosol-climate model simulates aerosol fields as well as conventional aerosol models.

We examine the performance of our approach for calculating the total scattering coefficient of both non-absorbing and absorbing aerosol at ambient conditions from aircraft data. Our extended examination involves airborne in situ data collected by the U.S. Department of Energy&rsquo, s (DOE) Gulf Stream 1 aircraft during winter over Cape Cod and the western North Atlantic Ocean as part of the Two-Column Aerosol Project (TCAP). The particle population represented by the winter dataset, in contrast with its summer counterpart, contains more hygroscopic particles and particles with an enhanced ability to absorb sunlight due to the larger fraction of black carbon. Moreover, the winter observations are characterized by more frequent clouds and a larger fraction of super-micron particles. We calculate model total scattering coefficient at ambient conditions using size spectra measured by optical particle counters (OPCs) and ambient complex refractive index (RI) estimated from measured chemical composition and relative humidity (RH). We demonstrate that reasonable agreement (~20% on average) between the observed and calculated scattering can be obtained under subsaturated ambient conditions (RH &lt, 80%) by applying both screening for clouds and chemical composition data for the RI-based correction of the OPC-derived size spectra.

We conducted a sensitivity study to better understand the potential of a new method for retrieving aerosol optical depth (AOD) under partly cloudy conditions. This method exploits ratios of reflectances in the visible spectral range and provides an effective way to avoid three-dimensional (3D) cloud effects. The sensitivity study is performed for different observational conditions and random errors in input data. The results of the sensitivity study suggest that this ratio method has the ability to detect clear pixels even in close proximity to clouds. Such detection does not require a statistical analysis of the two-dimensional (2D) horizontal distribution of reflected solar radiation, which makes it suitable for operational retrievals. In comparison with previously suggested approaches, the ratio method has the capability to increase the “harvest” of clear pixels. Similar to the traditional independent pixel approximation (IPA), the ratio method has a low computational cost for retrieving AOD. In contrast to the IPA method, the ratio method provides much more accurate estimations of the AOD values under broken cloud conditions: pixel-based and domain-averaged estimations of errors in AOD are about 25% and 10%, respectively. Finally, both the ratio-based cloud screening and the accuracy of domain-averaged ratio-based AOD values do not suffer greatly when 5% random errors are introduced in the reflectances.

Data taken from the MCMA-2003 and the 2006 MILAGRO field campaigns are used to examine the absorption of solar radiation by the organic component of aerosols. Using irradiance data from a Multi-Filter Rotating Shadowband Radiometer (MFRSR) and an actinic flux spectroradiometer (SR), we derive aerosol single scattering albedo, ϖ0, λ, as a function of wavelength, λ. We find that in the near-UV spectral range (250 to 400 nm) ϖ0, λ is much lower compared to ϖ0, λ at 500 nm indicating enhanced absorption in the near-UV range. Absorption by elemental carbon, dust, or gas cannot account for this enhanced absorption leaving the organic carbon component of the aerosol (OA) as the most likely absorber. We use data from a surface deployed Aerodyne Aerosol Mass Spectrometer (AMS) along with the inferred ϖ0, λ to estimate the Mass Absorption Cross section (MAC) for the organic aerosol. We find that the MAC is about 10.5 m2/g at 300 nm and falls close to zero at about 500 nm; values that are roughly consistent with other estimates of organic aerosol MAC. These MAC values can be considered as "radiatively correct", because when used in radiative transfer calculations, the calculated irradiances/actinic fluxes match those measured at the wavelengths considered here. For an illustrative case study described here, we estimate that the light absorption by the "brown" (organic) carbonaceous aerosol can add about 40% to the light absorption of black carbon in Mexico City. This contribution will vary depending on the relative abundance of organic aerosol relative to black carbon. Furthermore, our analysis indicates that organic aerosol would slow down photochemistry by selectively scavenging the light reaching the ground at those wavelengths that drive photochemical reactions. Finally, satellite retrievals of trace gases that are used to infer emissions currently assume that the MAC of organic carbon is zero. For trace gases that are retrieved using wavelengths shorter then 420 nm (i.e. SO2, HCHO, halogenoxides, NO2), the assumption of non-zero MAC values will induce an upward correction to the inferred emissions. This assumption will be particularly relevant in polluted urban atmospheres and areas of biomass burning where organic aerosols are particularly abundant.

Continental fair-weather cumuli exhibit significant diurnal, day-to-day, and year-to-year variability. This study describes the climatology of cloud macroscale properties, over the U.S. Department of Energy’s Atmospheric Radiation Measurement (ARM) Climate Research Facility (ACRF) Southern Great Plains (SGP) site. The diurnal cycle of cloud fraction, cloud-base height, cloud-top height, and cloud thickness were well defined. The cloud fraction reached its maximum value near 1400 central standard time. The average cloud-base height increased throughout the day, while the average cloud thickness decreased with time. In contrast to the other cloud properties, the average cloud-chord length remained nearly constant throughout the day. The sensitivity of the cloud properties to the year-to-year variability of precipitation and day-to-day changes in the height of the lifting condensation level (zLCL) and surface fluxes were compared. The cloud-base height was found to be sensitive to both the year, zLCL, and the surface fluxes of heat and moisture; the cloud thickness was found to be more sensitive to the year than to zLCL; the cloud fraction was sensitive to both the low-level moisture and the surface sensible heat flux; and cloud-chord length was sensitive to zLCL. Distributions of the cloud-chord length over the ACRF SGP site were computed and were well fit by an exponential distribution. The contribution to the total cloud fraction by clouds of each cloud-chord length was computed, and it was found that the clouds with a chord length of about 1 km contributed most to the observed cloud fraction. This result is similar to observations made with other remote sensing instruments or in modeling studies, but it is different from aircraft observations of the contribution to the total cloud fraction by clouds of different sizes.

An algorithm is presented here for determining cloud optical depth, � , using data from shortwave broadband ir- radiances, focusing on the case of optically thin clouds. This method is empirical and consists of a one-line equation. This method is applied to cirrus clouds observed at the Atmospheric Radiation Measurement Program Climate Research Facil- ity (ACRF) at Darwin, Australia, during the Tropical Warm Pool International Cloud Experiment (TWP-ICE) campaign and cirrus clouds observed at the ACRF Southern Great Plains (SGP) site. These cases were chosen because independent verification of cloud optical depth retrievals was possible. For the TWP-ICE case, the calculated optical depths agree to within 1 unit withcalculated from a vertical profile of ice particle size distributions obtained from an aircraft sounding. For the SGP case, the results from the algorithm correspond reasonably well withvalues obtained from an average over other retrieval methods, some of which have been subject to independent verification. The medians of the two time series are 0.79 and 0.81, for the empirical and averaged values, respectively. Because such close agreement is likely to be fortui- tous and therefore not truly represent the performance of our method, � values derived from our method were compared to values obtained from lidar data. Over a three year period, the difference in median values between the two methods is about 0.6, with the lidar optical depths being larger. This tool may be applied wherever measurements of the direct, dif- fuse, and total components of the shortwave broadband flux are available at 1- to 5-minute resolution. Because these measurements are made across the world, it then becomes possible to estimate optical depth for both liquid water and ice clouds at many locations.

Multi-filter Rotating Shadowband Radiometers (MFRSRs) provide routine measurements of the aerosol optical depth (τ) at six wavelengths (0.415, 0.5, 0.615, 0.673, 0.870 and 0.94 μm). The single-scattering albedo (π0) is typically estimated from the MFRSR measurements by assuming the asymmetry parameter (g). In most instances, however, it is not easy to set an appropriate value of g due to its strong temporal and spatial variability. Here, we introduce and validate an updated version of our retrieval technique that allows one to estimate simultaneously π0 and g for different types of aerosol. We use the aerosol and radiative properties obtained during the Atmospheric Radiation Measurement (ARM) Program's Aerosol Intensive Operational Period (IOP) to validate our retrieval in two ways. First, the MFRSR-retrieved optical properties are compared with those obtained from independent surface, Aerosol Robotic Network (AERONET), and aircraft measurements. The MFRSR-retrieved optical properties are in reasonable agreement with these independent measurements. Second, we perform radiative closure experiments using the MFRSR-retrieved optical properties. The calculated broadband values of the direct and diffuse fluxes are comparable (~5 W/m2) to those obtained from measurements.

During the Mexico City Metropolitan Area (MCMA) field campaign of 2003, measurements of the shortwave radiation field allowed the inference of the black carbon (BC) specific absorption, αλ, defined as the monochromatic absorption cross section per unit mass (with units of m2/g). The averaged values of αλ derived from the method here are either 8.9 m2/g or 8.2 m2/g at 500 nm, depending upon the physical and optical parameters assumed for BC. These results are reasonably consistent with those of Schuster et al. (2005), 9.5 m2/g, and Baumgartner et al. (2002), 7.0 m2/g, both measured at 550 nm. The αλ values reported in this paper should only be considered effective, "radiatively correct" values because when used in radiative transfer calculations the calculated irradiances match the measured irradiances at 500 nm. The specific absorption so defined can assume a wide range of values, depending upon: (1) the assumptions made prior to the retrieval (e.g., shell/core aerosol configuration), and (2) values chosen for BC density and refractive index. The range of possible values is large, corresponding to a "worst case" uncertainty of about ±70%, assuming that all errors are additive and of the same sign so that no error cancellation occurs.

As part of a major atmospheric chemistry and aerosol field program carried out in March 2006, a study was conducted in the area to the north and northeast of Mexico City to investigate the evolution of aerosols and their associated optical properties in the first few hours after their emission. The focus of the T1-T2 aerosol study was to investigate changes in the specific absorption αABS (absorption per unit mass, with unit of m2 g−1) of black carbon as it aged and became coated with compounds such as sulfate and organic carbon, evolving from an external to an internal mixture. Such evolution has been reported in previous studies. The T1 site was located just to the north of the Mexico City metropolitan area; the T2 site was situated approximately 35 km farther to the northeast. Nephelometers, particle soot absorption photometers, photoacoustic absorption spectrometers, and organic and elemental carbon analyzers were used to measure the optical properties of the aerosols and the carbon concentrations at each of the sites. Radar wind profilers and radiosonde systems helped to characterize the meteorology and to identify periods when transport from Mexico City over T1 and T2 occurred. Organic and elemental carbon concentrations at T1 showed diurnal cycles reflecting the nocturnal and early morning buildup from nearby sources, while concentrations at T2 appeared to be more affected by transport from Mexico City. Specific absorption during transport periods was lower than during other times, consistent with the likelihood of fresher emissions being found when the winds blew from Mexico City over T1 and T2. The specific absorption at T2 was larger than at T1, which is also consistent with the expectation of more aged particles with encapsulated black carbon being found at the more distant location. In situ measurements of single scattering albedo with an aircraft and a ground station showed general agreement with column-averaged values derived from rotating shadowband radiometer data, although some differences were found that may be related to boundary-layer evolution.

Areal-averaged albedos are particularly difficult to measure in coastal regions, because the surface is not homogenous, consisting of a sharp demarcation between land and water. With this difficulty in mind, we evaluate a simple retrieval of areal-averaged surface albedo using ground-based measurements of atmospheric transmission alone under fully overcast conditions. To illustrate the performance of our retrieval, we find the areal-averaged albedo using measurements from the Multi-Filter Rotating Shadowband Radiometer (MFRSR) at five wavelengths (415, 500, 615, 673, and 870 nm). These MFRSR data are collected at a coastal site in Graciosa Island, Azores supported by the U.S. Department of Energy’s (DOE’s) Atmospheric Radiation Measurement (ARM) Program. The areal-averaged albedos obtained from the MFRSR are compared with collocated and coincident Moderate Resolution Imaging Spectroradiometer (MODIS) whitesky albedo at four nominal wavelengths (470, 560, 670 and 860 nm). These comparisons are made during a 19-month period (June 2009 - December 2010). We also calculate composite-based spectral values of surface albedo by a weighted-average approach using estimated fractions of major surface types observed in an area surrounding this coastal site. Taken as a whole, these three methods of finding albedo show spectral and temporal similarities, and suggest that our simple, transmission-based technique holds promise, but with estimated errors of about ±0.03. Additional work is needed to reduce this uncertainty in areas with inhomogeneous surfaces.

Total-sky imager (TSI) and hemispheric-sky imager (HSI) each have a hemispherical field of view, and many TSIs are now deployed. These instruments have been used routinely to provide a time series of the fractional sky cover only. In this study, the possible retrieval of cloud-base height (CBH) from TSI surface observations is examined. This paper presents a validation analysis of a new retrieval using both a model-output inverse problem and independent, ground-based micropulse lidar data. The obtained results suggest that, at least for single-layer cloud fields, moderately accurate (within ∼0.35 km) CBH retrieval is possible.

Both individual and combined effects of the horizontal and vertical variability of cumulus clouds on solar radiative transfer are investigated using a two-dimensional ( x - and z -directions) cloud radar dataset. This high-resolution dataset of typical fair-weather marine cumulus is derived from ground-based 94 GHz cloud radar observations. The domain-averaged (along x -direction) radiative properties are computed by a Monte Carlo method. It is shown that (i) different cloud-scale resolutions can be used for accurate calculations of the mean absorption, upward and downward fluxes; (ii) the resolution effects can depend strongly on the solar zenith angle; and (iii) a few cloud statistics can be successfully applied for calculating the averaged radiative properties.

The relationship between hemispherical sky cover and nadir-view cloud fraction is examined by using both model simulations and surface observations. Monte Carlo simulations of ground-based hemispherical measurements are based on four-dimensional cloud fields produced by a large-eddy simulation model. Surface hemispherical observations are performed during the Atmospheric Radiation Measurement Program’s Cloudiness Intercomparison Intensive Operational Period. It is shown that (i) 15-min averages of frequently sampled (30 s) sky cover provide a reasonable estimation of the cloud fraction for limited fields of view and that (ii) this estimation can be substantially improved (for cumulus clouds) if additional information about the cloud aspect ratio is incorporated into the retrieval process.

In the second part of our two-part paper, we estimated the accuracy and robustness of the approximated equations for the mean radiance that were derived in Part I. In our analysis we used the three-dimensional (3D) cloud fields provided by (i) the stochastic Boolean model, (ii) large-eddy simulation model and (iii) satellite cloud retrieval. The accuracy of the obtained equations was evaluated by comparing the ensemble-averaged radiative properties that were obtained by the numerical averaging method (reference) and the analytical averaging method (approximation). The robustness of these equations was estimated by comparing the domain-averaged radiative properties obtained by using (i) the full 3D cloud structure (reference) and (ii) the bulk cloud statistics (approximation). It was shown that the approximated equations could provide reasonable accuracy (∼15%) for both the ensemble- and domain-averaged radiative properties.

A two-part paper describes the statistical treatment of solar radiative transfer in multilayer broken clouds. The proposed approach is a logical development of the statistical ones originally suggested for a single-layer broken clouds. This first part introduces a new statistically inhomogeneous Markovian model that allows one to properly account for different combinations of the random and maximum overlap of broken clouds at distinct vertical layers. The statistically inhomogeneous Markovian model and the stochastic radiative transfer equation have been used to derive equations for the mean radiance of solar radiation. It was demonstrated that in extreme cases the obtained equations agree with corresponding equations previously derived for (i) the statistically homogeneous broken clouds and (ii) the vertically inhomogeneous overcast clouds.

We introduce and evaluate a simple retrieval of areal-averaged surface albedo using ground-based measurements of atmospheric transmission alone at five wavelengths (415, 500, 615, 673 and 870nm), under fully overcast conditions. Our retrieval is based on a one-line semi-analytical equation and widely accepted assumptions regarding the weak spectral dependence of cloud optical properties, such as cloud optical depth and asymmetry parameter, in the visible and near-infrared spectral range. To illustrate the performance of our retrieval, we use as input measurements of spectral atmospheric transmission from the Multi-Filter Rotating Shadowband Radiometer (MFRSR). These MFRSR data are collected at two well-established continental sites in the United States supported by the U.S. Department of Energy’s (DOE’s) Atmospheric Radiation Measurement (ARM) Program and National Oceanic and Atmospheric Administration (NOAA). The areal-averaged albedos obtained from the MFRSR are compared with collocated and coincident Moderate Resolution Imaging Spectroradiometer (MODIS) white-sky albedo. In particular, these comparisons are made at four MFRSR wavelengths (500, 615, 673 and 870nm) and for four seasons (winter, spring, summer and fall) at the ARM site using multi-year (2008-2013) MFRSR and MODIS data. Good agreement, on average, for these wavelengths results in small values (≤0.015) of the corresponding root mean square errors (RMSEs) for these two sites. The obtained RMSEs are comparable with those obtained previously for the shortwave albedos (MODIS-derived versus tower-measured) for these sites during growing seasons. We also demonstrate good agreement between tower-based daily-averaged surface albedos measured for “nearby” overcast and non-overcast days. Thus, our retrieval originally developed for overcast conditions likely can be extended for non-overcast days by interpolating between overcast retrievals.