GMD Publications for 2015
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U.S. national and regional emissions of HFC-134a are derived for 2008–2012 based on atmospheric observations from ground and aircraft sites across the U.S. and a newly developed regional inverse model. Synthetic data experiments were first conducted to optimize the model assimilation design and to assess model-data mismatch errors and prior flux error covariances computed using a maximum likelihood estimation technique. The synthetic data experiments also tested the sensitivity of derived national and regional emissions to a range of assumed prior emissions, with the goal of designing a system that was minimally reliant on the prior. We then explored the influence of additional sources of error in inversions with actual observations, such as those associated with background mole fractions and transport uncertainties. Estimated emissions of HFC-134a range from 52 to 61 Gg yr−1 for the contiguous U.S. during 2008–2012 for inversions using air transport from Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model driven by the 12 km resolution meteorogical data from North American Mesoscale Forecast System (NAM12) and all tested combinations of prior emissions and background mole fractions. Estimated emissions for 2008–2010 were 20% lower when specifying alternative transport from Stochastic Time-Inverted Lagrangian Transport (STILT) model driven by the Weather Research and Forecasting (WRF) meteorology. Our estimates (for HYSPLIT-NAM12) are consistent with annual emissions reported by U.S. Environmental Protection Agency for the full study interval. The results suggest a 10–20% drop in U.S. national HFC-134a emission in 2009 coincident with a reduction in transportation-related fossil fuel CO2 emissions, perhaps related to the economic recession. All inversions show seasonal variation in national HFC-134a emissions in all years, with summer emissions greater than winter emissions by 20–50%.
Continuous measurements of total ozone (by Dobson spectrophotometers) across the contiguous United States began in the early 1960s. Here, we analyze temporal and spatial variability and trends in total ozone from the five US sites with long-term records. While similar long-term ozone changes are detected at all five sites, we find differences in the patterns of ozone variability on shorter timescales. In addition to standard evaluation techniques, STL-decomposition methods (Seasonal Trend decomposition of time series based on LOESS (LOcally wEighted Scatterplot Smoothing)) are used to address temporal variability and "fingerprints" of dynamical features in the Dobson data. Methods from statistical extreme value theory (EVT) are used to characterize days with high and low total ozone (termed EHOs and ELOs, respectively) at each station and to analyze temporal changes in the frequency of ozone extremes and their relationship to dynamical features such as the North Atlantic Oscillation (NAO) and El Niño–Southern Oscillation. A comparison of the fingerprints detected in the frequency distribution of the extremes with those for standard metrics (i.e., the mean) shows that more fingerprints are found for the extremes, particularly for the positive phase of the NAO, at all five US monitoring sites. Results from the STL decomposition support the findings of the EVT analysis. Finally, we analyze the relative influence of low- and high-ozone events on seasonal mean column ozone at each station. The results show that the influence of ELOs and EHOs on seasonal mean column ozone can be as much as ±5 %, about as large as the overall long-term decadal ozone trends.