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Shippert, Timothy R.

Publications and source records attributed to Shippert, Timothy R..

Observationally derived rise in methane surface forcing mediated by water vapour trend

Atmospheric methane (CH4) mixing ratios exhibited a plateau between 1995 and 2006 and have subsequently been increasing. While there are a number of competing explanations for the temporal evolution of this greenhouse gas, these prominent features in the temporal trajectory of atmospheric CH4 are expected to perturb the surface energy balance through radiative forcing, largely due to the infrared radiative absorption features of CH4. However, to date this has been determined strictly through radiative transfer calculations. Here, we present a quantified observation of the time series of clear-sky radiative forcing by CH4 at the surface from 2002 to 2012 at a single site derived from spectroscopic measurements along with line-by-line calculations using ancillary data. There was no significant trend in CH4 forcing between 2002 and 2006, but since then, the trend in forcing was 0.026?±?0.006 (99.7%?CI)?W?m2?yr-1. The seasonal-cycle amplitude and secular trends in observed forcing are influenced by a corresponding seasonal cycle and trend in atmospheric CH4. However, we find that we must account for the overlapping absorption effects of atmospheric water vapour (H2O) and CH4 to explain the observations fully. Thus, the determination of CH4 radiative forcing requires accurate observations of both the spatiotemporal distribution of CH4 and the vertically resolved trends in H2O.

Feldman, Daniel R.↗

Long-term measurements of submicrometer aerosol chemistry at the Southern Great Plains (SGP) using an Aerosol Chemical Speciation Monitor (ACSM)

In this study the long-term trends of non-refractory submicrometer aerosol (NR-PM1) composition and mass concentration measured by an Aerosol Chemical Speciation Monitor (ACSM) at the Atmospheric Radiation Measurement (ARM) program's Southern Great Plains (SGP) site are discussed. NR-PM1 data was recorded at ~30 min intervals over a period of 19 months between November 2010 and June 2012. Positive Matrix Factorization (PMF) was performed on the measured organic mass spectral matrix using a rolling window technique to derive factors associated with distinct sources, evolution processes, and physiochemical properties. The rolling window approach also allows us to capture the dynamic variations of the chemical properties in the organic aerosol (OA) factors over time. Three OA factors were obtained including two oxygenated OA (OOA) factors, differing in degrees of oxidation, and a biomass burning OA (BBOA) factor. Back trajectory analyses were performed to investigate possible sources of major NR-PM1 species at the SGP site. Organics dominated NR-PM1 mass concentration for the majority of the study with the exception of winter, when ammonium nitrate increases due to transport of precursor species from surrounding urban and agricultural areas and also due to cooler temperatures. Sulfate mass concentrations have little seasonal variation with mixed regional and local sources. In the spring BBOA emissions increase and are mainly associated with local fires. Isoprene and carbon monoxide emission rates were obtained by the Model of Emissions of Gases and Aerosols from Nature (MEGAN) and the 2011 U.S. National Emissions Inventory to represent the spatial distribution of biogenic and anthropogenic sources, respectively. The combined spatial distribution of isoprene emissions and air mass trajectories suggest that biogenic emissions from the southeast contribute to SOA formation at the SGP site during the summer.

54 ENVIRONMENTAL SCIENCES↗

Observational determination of surface radiative forcing by CO 2 from 2000 to 2010

The climatic impact of CO 2 and other greenhouse gases is usually quantified in terms of radiative forcing, calculated as the difference between estimates of the Earth's radiation field from pre-industrial and present-day concentrations of these gases. Radiative transfer models calculate that the increase in CO 2 since 1750 corresponds to a global annual-mean radiative forcing at the tropopause of 1.82 ± 0.19 W m -2 . However, despite widespread scientific discussion and modelling of the climate impacts of well-mixed greenhouse gases, there is little direct observational evidence of the radiative impact of increasing atmospheric CO 2 . Here in this paper, we present observationally based evidence of clear-sky CO 2 surface radiative forcing that is directly attributable to the increase, between 2000 and 2010, of 22 parts per million atmospheric CO 2 . The time series of this forcing at the two locations-the Southern Great Plains and the North Slope of Alaska-are derived from Atmospheric Emitted Radiance Interferometer spectra together with ancillary measurements and thoroughly corroborated radiative transfer calculations. The time series both show statistically significant trends of 0.2 W m -2 per decade (with respective uncertainties of ± 0.06 W m -2 per decade and ± 0.07 W m -2 per decade) and have seasonal ranges of 0.1-0.2 W m -2 . This is approximately ten per cent of the trend in downwelling longwave radiation. These results confirm theoretical predictions of the atmospheric greenhouse effect due to anthropogenic emissions, and provide empirical evidence of how rising CO 2 levels, mediated by temporal variations due to photosynthesis and respiration, are affecting the surface energy balance.

54 ENVIRONMENTAL SCIENCES↗

A Scientific Data Processing Framework for Time Series NetCDF Data

ARM Data Integrator (ADI) is a framework to streamline the development of scientific algorithms that analyze time-series NetCDF data, and to improve the content and consistency of the output data products produced by these algorithms. ADI achieves these goals by automating the process of retrieving and preparing data for analysis, supporting the definition of output data products through a graphical interface, and providing a modular, flexible software development architecture. The input data, preprocessing, and output data specifications are defined through a graphical interface and stored in a database. ADI also includes a workflow for data integration, a library of software modules to support the workflow, and a source code generator that produces C, IDL and Python templates. Data preparation support includes automated retrieval of data from input files, merging the retrieved data into appropriately sized chunks, and transformation of the data onto a common coordinate system grid. Through the graphical interface, users can view the details of both their data products and those in the ARM catalog. The variable and attribute definitions of the existing data products can be used to build new output data products. In addition, the rules that make up the ARM archive’s data standards are laid on top of the view of the new data product providing the user with a visual cue indicating where their output violates an archive standard. The necessary configurations are stored in a database that is accessed by the ADI libraries. This paper discusses the ADI framework, its supporting components, and how ADI can significantly decrease the time and cost of implementing scientific algorithms while improving the ability of scientists to disseminate their results.

Atmospheric Science↗