Susan E. Strahan

A trajectory-based estimate of the tropospheric ozone column using the residual method

We estimate the tropospheric column ozone using a forward trajectory model to increase the horizontal resolution of the Aura Microwave Limb Sounder (MLS) derived stratospheric column ozone. Subtracting the MLS stratospheric column from Ozone Monitoring Instrument total column measurements gives the trajectory enhanced tropospheric ozone residual (TTOR). Because of different tropopause definitions, we validate the basic residual technique by computing the 200-hPa-to-surface column and comparing it to the same product from ozonesondes and Tropospheric Emission Spectrometer measurements. Comparisons show good agreement in the tropics and reasonable agreement at middle latitudes, but there is a persistent low bias in the TTOR that may be due to a slight high bias in MLS stratospheric column. With the improved stratospheric column resolution, we note a strong correlation of extratropical tropospheric ozone column anomalies with probable troposphere-stratosphere exchange events or folds. The folds can be identified by their colocation with strong horizontal tropopause gradients. TTOR anomalies due to folds may be mistaken for pollution events since folds often occur in the Atlantic and Pacific pollution corridors. We also compare the 200-hPa-to-surface column with Global Modeling Initiative chemical model estimates of the same quantity. While the tropical comparisons are good, we note that chemical model variations in 200-hPa-to-surface column at middle latitudes are much smaller than seen in the TTOR.

Comparison of lower stratospheric tropical mean vertical velocities

[1]xa0We have analyzed 13 years (1993–2005) of tropical stratospheric water vapor data from the Halogen Occultation Experiment and over 3 years of data (October 2004 through November 2007) from the Aura Microwave Limb Sounder. By correlating the phase lag of the water vapor “tape recorder” signal between levels we estimate the time mean vertical velocity. Our estimated vertical velocity compares well with calculations from the Goddard Earth Observing System (GEOS) chemistry-climate model (CCM) and from the GEOS data assimilation system. Between 18 and 26 km both the GEOS CCM simulations and water vapor observations agree that the vertical velocity is below 0.04 cm/s, with a minimum near 20 km of 0.03 cm/s. Vertical velocities deduced from water vapor observations are higher than those from the GEOS CCM in the region 16–18 km (0.04 cm/s) and above 26–30 km (up to 0.07 cm/s). These estimates are close to earlier estimates from a shorter water vapor record and radiative transfer models. No evidence is found for velocities as high as 0.15 cm/s as was recently estimated from aircraft CO2 measurements in the upper troposphere/lower stratosphere. Further diagnosis of the aircraft CO2 data and model simulations of CO2 show that while the CO2 data give an apparent upward transport velocity of ∼0.06 cm/s, about half of this is due to vertical and horizontal eddy transport. Accounting for the eddy terms gives a CO2-based estimate of the vertical velocity of ∼0.03 cm/s, in much closer agreement with that estimated from water vapor.

Uncertainties in global aerosol simulations: Assessment using three meteorological data sets

[1]xa0Current global aerosol models use different physical and chemical schemes and parameters, different meteorological fields, and often different emission sources. Since the physical and chemical parameterization schemes are often tuned to obtain results that are consistent with observations, it is difficult to assess the true uncertainty due to meteorology alone. Under the framework of the NASA global modeling initiative (GMI), the differences and uncertainties in aerosol simulations (for sulfate, organic carbon, black carbon, dust, and sea salt) solely due to different meteorological fields are analyzed and quantified. Three meteorological data sets available from the NASA Goddard Data Assimilation Office (DAO) general circulation model (GCM), the Goddard Institute for Space Studies (GISS) GCM, version II and the NASA Goddard Global Modeling and Assimilation Office (GMAO), finite-volume GCM (FVGCM) are used to drive the same aerosol model. The global sulfate and mineral dust burdens with FVGCM fields are 40% and 20% less than those with DAO and GISS fields, respectively, due to its larger precipitation. Meanwhile, the sea salt burden predicted with FVGCM fields is 56% and 43% higher than those with DAO and GISS, respectively, due to its stronger convection especially over the Southern Hemispheric Ocean. Sulfate concentrations at the surface in the Northern Hemisphere extratropics and in the middle to upper troposphere differ by a factor of 3 between the three meteorological data sets. The agreement between model calculated and observed aerosol concentrations in the surface source regions is similar for all three meteorological data sets. Away from the source regions, however, the comparisons with observations differ greatly for DAO, FVGCM, and GISS, and the performance of the model using different meteorological data sets varies depending on the site and the compared species. Sensitivity simulations with the NASA GEOS-4 assimilated fields show that the interannual variability of aerosol concentrations can be higher than a factor of 2 depending on the location and season, which is generally, however, smaller than the differences due to using different meteorological data sets. Global annual average aerosol optical depth at 550 nm is 0.120–0.131 for the three meteorological data sets. However, the contributions from different aerosol components to this total optical depth differ significantly, which reflects differences in the aerosol spatial distributions. The global annual average anthropogenic and all-sky aerosol direct forcing at the top-of-the atmosphere is estimated to be −0.75, −0.35, and −0.40 W m−2 for DAO, FVGCM, and GISS fields, respectively. Regional differences can be much larger (by a factor of 4–5) in the tropics over the ocean and in the polar regions.

Radicals and Reservoirs in the GMI Chemistry and Transport Model: Comparison to Measurements

[1]xa0We have used a three-dimensional chemistry and transport model (CTM), developed under the Global Modeling Initiative (GMI), to carry out two simulations of the composition of the stratosphere under changing halogen loading for 1995 through 2030. The two simulations differ only in that one uses meteorological fields from a general circulation model while the other uses meteorological fields from a data assimilation system. A single years winds and temperatures are repeated for each 36-year simulation. We compare results from these two simulations with an extensive collection of data from satellite and ground-based measurements for 1993–2000. Comparisons of simulated fields with observations of radical and reservoir species for some of the major ozone-destroying compounds are of similar quality for both simulations. Differences in the upper stratosphere, caused by transport of total reactive nitrogen and methane, impact the balance among the ozone loss processes and the sensitivity of the two simulations to the change in composition.

Evaluating the credibility of transport processes in simulations of ozone recovery using the Global Modeling Initiative three‐dimensional model

[1]xa0The Global Modeling Initiative (GMI) has integrated two 36-year simulations of an ozone recovery scenario with an offline chemistry and transport model using two different meteorological inputs. Physically based diagnostics, derived from satellite and aircraft data sets, are described and then used to evaluate the realism of temperature and transport processes in the simulations. Processes evaluated include barrier formation in the subtropics and polar regions, and extratropical wave-driven transport. Some diagnostics are especially relevant to simulation of lower stratospheric ozone, but most are applicable to any stratospheric simulation. The global temperature evaluation, which is relevant to gas phase chemical reactions, showed that both sets of meteorological fields have near climatological values at all latitudes and seasons at 30 hPa and below. Both simulations showed weakness in upper stratospheric wave driving. The simulation using input from a general circulation model (GMIGCM) showed a very good residual circulation in the tropics and Northern Hemisphere. The simulation with input from a data assimilation system (GMIDAS) performed better in the midlatitudes than it did at high latitudes. Neither simulation forms a realistic barrier at the vortex edge, leading to uncertainty in the fate of ozone-depleted vortex air. Overall, tracer transport in the offline GMIGCM has greater fidelity throughout the stratosphere than it does in the GMIDAS.

Sensitivity of Arctic ozone loss to polar stratospheric cloud volume and chlorine and bromine loading in a chemistry and transport model

[1]xa0The sensitivity of Arctic ozone loss to polar stratospheric cloud volume (VPSC) and chlorine and bromine loading is explored using chemistry and transport models (CTMs). One simulation uses multi-decadal winds and temperatures from a general circulation model (GCM). Winter polar ozone loss depends on both equivalent effective stratospheric chlorine (EESC) and polar vortex characteristics (temperatures, descent, isolation, polar stratospheric cloud amount). The simulation reproduces a linear relationship between ozone loss and VPSC in agreement with that derived from observations for 1992–2003. The relationship holds for EESC within ∼85% of its maximum (∼1990–2020). For lower EESC the ozone loss varies linearly with EESC unless VPSC ∼ 0. A second simulation recycles a single years winds and temperatures from the GCM so that polar ozone loss depends only on changes in EESC. This simulation shows that ozone loss varies linearly with EESC for the entire EESC range for constant, high VPSC.

Influence of planetary wave transport on Arctic ozone as observed by Polar Ozone and Aerosol Measurement (POAM) III

[1]xa0Interannual differences in Arctic ozone are investigated using data from the Polar Ozone and Aerosol Measurement (POAM) III instrument obtained between May 1998 and April 2001. These three winters were unusually warm or cold relative to the 1979–2001 mean, resulting in years with either a warm, disturbed vortex or a cold, quiet vortex. Contours of probability distribution functions (PDFs) of the POAM data are used to identify seasonal and interannual variations in the transport processes controlling ozone. A major warming in December, 1998, displaced the middle stratospheric vortex from the pole for nearly a month, dissipating it. The vortex reformed in January, 1999, filled with high O3 air from lower latitudes, which then cooled and descended. By the end of winter 1999, ozone at 500 K in the vortex was 0.5–1.0 ppm higher than in the subsequent cold winter. The winter of 2000–2001 had frequent wave disturbances, beginning with a fairly large event in November. However, at the end of this event, the high potential vorticity (PV) core of the vortex was intact, and by February, O3 in the vortex looked the same as in 2000. Transport in these winters is inferred from the PDFs and supported by potential vorticity analyses. This study demonstrates that variability in the O3-PV relationship can be caused by transport, independent of loss by polar stratospheric clouds (PSCs). Ozone in the vortex in a very disturbed winter can be unusually high due to transport and will not represent O3 levels expected in the absence of PSCs in other years.

Sensitivity of Global Modeling Initiative model predictions of Antarctic ozone recovery to input meteorological fields

[1]xa0We use the Global Modeling Initiative chemistry and transport model to simulate the evolution of stratospheric ozone between 1995 and 2030, using boundary conditions consistent with the recent World Meteorological Organization ozone assessment. We compare the Antarctic ozone recovery predictions of two simulations, one driven by an annually repeated year of meteorological data from a general circulation model (GCM), the other using a year of output from a data assimilation system (DAS), to examine the sensitivity of Antarctic ozone recovery predictions to the characteristic dynamical differences between GCM- and DAS-generated meteorological data. Although the age of air in the Antarctic lower stratosphere differs by a factor of 2 between the simulations, we find little sensitivity of the 1995–2030 Antarctic ozone recovery between 350 and 650 K to the differing meteorological fields, particularly when the recovery is specified in mixing ratio units. Percent changes are smaller in the DAS-driven simulation compared to the GCM-driven simulation because of a surplus of Antarctic ozone in the DAS-driven simulation which is not consistent with observations. The peak ozone change between 1995 and 2030 in both simulations is ∼20% lower than photochemical expectations, indicating that changes in ozone transport due to changing ozone gradients at 450 K between 1995 and 2030 constitute a small negative feedback. Total winter/spring ozone loss during the base year (1995) of both simulations and the rate of ozone loss during August and September is somewhat weaker than observed. This appears to be due to underestimates of Antarctic Cly at the 450-K potential temperature level.