Evaluating the added value of multi-input atmospheric transport ensemble modeling for applications of the Comprehensive Nuclear Test-Ban Treaty organization (CTBTO).

The Comprehensive Nuclear Test-Ban Treaty Organization (CTBTO) runs to date operationally an atmospheric transport modeling chain in backward mode based on operational deterministic European Centre for Medium-Range Weather Forecasts-Integrated Forecasting System (ECMWF-IFS) and on National Centers for Environmental Prediction-Global Forecast System (NCEP-GFS) input data. Meanwhile, ensemble dispersion modeling is becoming more and more widespread due to the ever increasing computational power and storage capacities. The potential benefit of this approach for current and possible future CTBTO applications was investigated using data from the ECMWF-Ensemble Prediction System (EPS). Five different test cases - among which are the ETEX-I experiment and the Fukushima accident - were run in backward or forward mode and - in the light of a future operational application - special emphasis was put on the performance of an arbitrarily selected 10- versus the full 51-member ensemble. For those test cases run in backward mode and based on a puff release it became evident that Possible Source Regions (PSRs) can be meaningfully reduced in size compared to results based solely on the deterministic run by applying minimum and probability of exceedance ensemble metrics. It was further demonstrated that a given puff release of 4E10 Bq of Se-75 can be reproduced within the meteorological uncertainty range [1.9E9 Bq,1.7E13 Bq] including a probability for not exceeding an assumed upper limit source term using simple scaling of a measurement with the corresponding ensemble metrics of backward fields. For the test cases run in forward mode it was found that the control run as well as 10- and 51-member medians all exhibit similar performance in time series evaluation. Maximum rank difference adds up to less than 10% with reference to possible rank values [0,4]. The maximum difference in the Brier score for both ensembles is less than 3%. The main added value of the ensemble lies in producing meteorologically induced concentration uncertainties and thus explaining observed measurements at specific sites. Depending on the specific test case and on the ensemble size between 27 and 74% of samples all lie within concentration ranges derived from the different meteorological fields used. In the future uncertainty information per sample could be used in a full source term inversion to account for the meteorological uncertainty in a proper way. It can be concluded that a 10-member meteorological ensemble is good enough to already benefit from useful ensemble properties. Meteorological uncertainty to a large degree is covered by the 10-member subset because forecast uncertainty is largely suppressed due to concatenating analyses and short term forecasts, as required in the operational CTBTO procedure, on which this study focuses. Besides, members from different analyses times are on average unrelated. It was recommended to Working Group B of CTBTO to implement the ensemble system software in the near future.

Instrumentation and Measurement Strategy for the NOAA SENEX Aircraft Campaign as Part of the Southeast Atmosphere Study 2013.

Natural emissions of ozone-and-aerosol-precursor gases such as isoprene and monoterpenes are high in the southeast of the US. In addition, anthropogenic emissions are significant in the Southeast US and summertime photochemistry is rapid. The NOAA-led SENEX (Southeast Nexus) aircraft campaign was one of the major components of the Southeast Atmosphere Study (SAS) and was focused on studying the interactions between biogenic and anthropogenic emissions to form secondary pollutants. During SENEX, the NOAA WP-3D aircraft conducted 20 research flights between 27 May and 10 July 2013 based out of Smyrna, TN. Here we describe the experimental approach, the science goals and early results of the NOAA SENEX campaign. The aircraft, its capabilities and standard measurements are described. The instrument payload is summarized including detection limits, accuracy, precision and time resolutions for all gas-and-aerosol phase instruments. The inter-comparisons of compounds measured with multiple instruments on the NOAA WP-3D are presented and were all within the stated uncertainties, except two of the three NO2 measurements. The SENEX flights included day- and nighttime flights in the Southeast as well as flights over areas with intense shale gas extraction (Marcellus, Fayetteville and Haynesville shale). We present one example flight on 16 June 2013, which was a daytime flight over the Atlanta region, where several crosswind transects of plumes from the city and nearby point sources, such as power plants, paper mills and landfills, were flown. The area around Atlanta has large biogenic isoprene emissions, which provided an excellent case for studying the interactions between biogenic and anthropogenic emissions. In this example flight, chemistry in and outside the Atlanta plumes was observed for several hours after emission. The analysis of this flight showcases the strategies implemented to answer some of the main SENEX science questions.

Organic aerosol formation downwind from the Deepwater Horizon oil spill.

A large fraction of atmospheric aerosols are derived from organic compounds with various volatilities. A National Oceanic and Atmospheric Administration (NOAA) WP-3D research aircraft made airborne measurements of the gaseous and aerosol composition of air over the Deepwater Horizon (DWH) oil spill in the Gulf of Mexico that occurred from April to August 2010. A narrow plume of hydrocarbons was observed downwind of DWH that is attributed to the evaporation of fresh oil on the sea surface. A much wider plume with high concentrations of organic aerosol (>25 micrograms per cubic meter) was attributed to the formation of secondary organic aerosol (SOA) from unmeasured, less volatile hydrocarbons that were emitted from a wider area around DWH. These observations provide direct and compelling evidence for the importance of formation of SOA from less volatile hydrocarbons.