Annette Koontz

Climatology of aerosol optical depth in north‐central Oklahoma: 1992–2008

[1] Aerosol optical depth (AOD) has been measured at the Atmospheric Radiation Measurement Program central facility near Lamont, Oklahoma, since the fall of 1992. Most of the data presented are from the multifilter rotating shadowband radiometer, a narrow‐band, interference‐filter Sun radiometer with five aerosol bands in the visible and near infrared; however, AOD measurements have been made simultaneously and routinely at the site by as many as three different types of instruments, including two pointing Sun radiometers. Scatterplots indicate high correlations and small biases consistent with earlier comparisons. The early part of this 16 year record had a disturbed stratosphere with residual Mt. Pinatubo aerosols, followed by the cleanest stratosphere in decades. As such, the last 13 years of the record reflect changes that have occurred predominantly in the troposphere. The field calibration technique is briefly described and compared to Langley calibrations from Mauna Loa Observatory. A modified cloud‐ screening technique is introduced that increases the number of daily averaged AODs retrieved annually to about 250 days compared with 175 days when a more conservative method was employed in earlier studies. AODs are calculated when the air mass is less than six; that is, when the Sun’s elevation is greater than 9.25°. The more inclusive cloud screen and the use of most of the daylight hours yield a data set that can be used to more faithfully represent the true aerosol climate for this site. The diurnal aerosol cycle is examined month‐by‐month to assess the effects of an aerosol climatology on the basis of infrequent sampling such as that from satellites.

Efficient data IO for a Parallel Global Cloud Resolving Model

Execution of a Global Cloud Resolving Model (GCRM) at target resolutions of 2-4 km will generate, at a minimum, 10s of Gigabytes of data per variable per snapshot. Writing this data to disk, without creating a serious bottleneck in the execution of the GCRM code, while also supporting efficient post-execution data analysis is a significant challenge. This paper discusses an Input/Output (IO) application programmer interface (API) for the GCRM that efficiently moves data from the model to disk while maintaining support for community standard formats, avoiding the creation of very large numbers of files, and supporting efficient analysis. Several aspects of the API will be discussed in detail. First, we discuss the output data layout which linearizes the data in a consistent way that is independent of the number of processors used to run the simulation and provides a convenient format for subsequent analyses of the data. Second, we discuss the flexible API interface that enables modelers to easily add variables to the output stream by specifying where in the GCRM code these variables are located and to flexibly configure the choice of outputs and distribution of data across files. The flexibility of the API is designed to allow model developers to add new data fields to the output as the model develops and new physics is added. It also provides a mechanism for allowing users of the GCRM code to adjust the output frequency and the number of fields written depending on the needs of individual calculations. Third, we describe the mapping to the NetCDF data model with an emphasis on the grid description. Fourth, we describe our messaging algorithms and IO aggregation strategies that are used to achieve high bandwidth while simultaneously writing concurrently from many processors to shared files. We conclude with initial performance results.

IO strategies and data services for petascale data sets from a global cloud resolving model

Global cloud resolving models at resolutions of 4km or less create significant challenges for simulation output, data storage, data management, and post-simulation analysis and visualization. To support efficient model output as well as data analysis, new methods for IO and data organization must be evaluated. The model we are supporting, the Global Cloud Resolving Model being developed at Colorado State University, uses a geodesic grid. The non-monotonic nature of the grids coordinate variables requires enhancements to existing data processing tools and community standards for describing and manipulating grids. The resolution, size and extent of the data suggest the need for parallel analysis tools and allow for the possibility of new techniques in data mining, filtering and comparison to observations. We describe the challenges posed by various aspects of data generation, management, and analysis, our work exploring IO strategies for the model, and a preliminary architecture, web portal, and tool enhancements which, when complete, will enable broad community access to the data sets in familiar ways to the community.

The Ascension Island Boundary Layer in the Remote Southeast Atlantic is Often Smoky

Observations from June to October 2016, from a surface-based ARM Mobile Facility deployment on Ascension Island (8∘S, 14.5∘W) indicate that refractory black carbon (rBC) is almost always present within the boundary layer. The rBC mass concentrations, light absorption coefficients, and cloud condensation nuclei concentrations vary in concert and synoptically, peaking in August. Light absorption coefficients at three visible wavelengths as a function of rBC mass are approximately double that calculated from black carbon in lab studies. A spectrally-flat absorption angstrom exponent suggests most of the light absorption is from lens-coated black carbon. The single-scattering-albedo increases systematically from August to October in both 2016 and 2017, with monthly means of 0.78 ± 0.02 (August), 0.81 ± 0.03 (September), and 0.83 ± 0.03 (October) at the green wavelength. Boundary layer aerosol loadings are only loosely correlated with total aerosol optical depth, with smoke more likely to be present in the boundary layer earlier in the biomass burning season, evolving to smoke predominantly present above the cloud layers in September–October, typically resting upon the cloud top inversion. The time period with the campaign-maximum near-surface light absorption and column aerosol optical depth, on 13–16 August 2016, is investigated further. Backtrajectories that indicate more direct boundary layer transport westward from the African continent is central to explaining the elevated surface aerosol loadings. Plain Language Summary First findings from the remote Ascension Island midway between Africa and South America in the Atlantic Ocean indicate that smoke is present much more often near the surface than has been previously thought. The new measurements from a 17-month-long campaign suggest that August is the smokiest month near the surface. The smoke includes other aerosols besides black carbon, and is most absorptive of sunlight in June and least in October. The smoke is more present near the surface earlier in the biomass burning season, or June, while later on toward September and October, more of the smoke resides above the cloud layer. This has implications for which aerosol-cloud microphysical and radiative interactions are dominant when. The campaign-maximum aerosol loading event is investigated further and attributed to an unusual direct westward flow from the continental African fire sources at low altitudes.

ARM: Derived: Hourly Averages of Aerosol intensive properties from AOS, Delene and Ogren et al, 2001

Derived: Hourly Averages of Aerosol intensive properties from AOS, Delene and Ogren et al, 2001