Gretchen Lingenfelser

SPARC Data Initiative: A comparison of ozone climatologies from international satellite limb sounders

A comprehensive quality assessment of the ozone products from 18 limb-viewing satellite instruments is provided by means of a detailed intercomparison. The ozone climatologies in form of monthly zonal mean time series covering the upper troposphere to lower mesosphere are obtained from LIMS, SAGE I/II/III, UARS-MLS, HALOE, POAM II/III, SMR, OSIRIS, MIPAS, GOMOS, SCIAMACHY, ACE-FTS, ACE-MAESTRO, Aura-MLS, HIRDLS, and SMILES within 1978–2010. The intercomparisons focus on mean biases of annual zonal mean fields, interannual variability, and seasonal cycles. Additionally, the physical consistency of the data is tested through diagnostics of the quasi-biennial oscillation and Antarctic ozone hole. The comprehensive evaluations reveal that the uncertainty in our knowledge of the atmospheric ozone mean state is smallest in the tropical and midlatitude middle stratosphere with a 1σ multi-instrument spread of less than ±5%. While the overall agreement among the climatological data sets is very good for large parts of the stratosphere, individual discrepancies have been identified, including unrealistic month-to-month fluctuations, large biases in particular atmospheric regions, or inconsistencies in the seasonal cycle. Notable differences between the data sets exist in the tropical lower stratosphere (with a spread of ±30%) and at high latitudes (±15%). In particular, large relative differences are identified in the Antarctic during the time of the ozone hole, with a spread between the monthly zonal mean fields of ±50%. The evaluations provide guidance on what data sets are the most reliable for applications such as studies of ozone variability, model-measurement comparisons, detection of long-term trends, and data-merging activities.

Lagrangian forecasting during ASHOE/MAESA: Analysis of predictive skill for analyzed and reverse‐domain‐filled potential vorticity

A statistical analysis is conducted to determine to what extent analyzed and 5-day reverse-domain-filled (RDF) potential vorticity (PV) obtained from meteorological analyses can predict ATLAS nitrous oxide (N2O) tracer structure encountered along the ER-2 flight track during the Airborne Southern Hemisphere Ozone Experiment / Measurements for Assessing the Effects of Stratospheric Aircraft (ASHOE/MAESA) campaign. The results indicate that RDF PV shows no statistically significant improvement in forecast skill over analyzed PV in predicting tracer structure along the ER-2 flight track. In fact, RDF generally shows a degradation in predictive skill. RDF does show some success in refining large-scale gradients and small-scale structures, present in the analyzed PV fields. In at least one case, RDF PV captured a filament encountered by the ER-2, but in general, such structure is marked by low confidence in the RDF PV analyses.

Large‐scale stratospheric ozone photochemistry and transport during the POLARIS Campaign

Measurements from the Halogen Occultation Experiment (HALOE) on board the UARS satellite and assimilated winds, temperatures, and diabatic heating rates from the NASA Goddard data assimilation office (DAO) are used with the NASA Langley Research Center (LaRC) Lagrangian photochemical model to compute 3-D air parcel trajectories with photochemistry for all Northern Hemisphere HALOE observations during the period March-September 1997. Results from ensemble means of the photochemical trajectory calculations provide a global perspective for the interpretation of constituent measurements made from the ER-2 and balloon platforms during the POLARIS aircraft campaign. Lagrangian photochemical predictions are shown to compare favorably with ER-2, balloon, Total Ozone Mapping Spectometer (TOMS), and subsequent coincident HALOE observations. Model predictions show large-scale photochemical ozone loss in high latitudes at ER-2 flight altitudes of over 10% per month in June and July, in good agreement with steady state photochemical calculations constrained with ER-2 observations of radical and long-lived species. Largest summertime photochemical ozone losses (over 1.4 ppmv/month) are found to occur poleward of 60°N above 30 mbar, in good agreement with steady state photochemical calculations constrained with observations from the balloon-borne Fourier transform infrared solar absorption spectrometer (MkIV) instrument. Summertime polar photochemical ozone losses are driven largely by NO x chemistry and are largest for air parcels with high NO x /NO y ratios that have experienced continuous sunlight for several days. Differences between predicted net changes in ozone and changes due to photochemistry are used to estimate residual changes due to transport processes. Photochemical and residual transport tendencies tend to be of similar magnitude but opposite sign. Photochemical loss of ozone tends to outweigh positive transport tendencies in high latitudes, while upwelling of low ozone below the tropical ozone maximum moderates photochemical production there. The estimated transport tendencies are generally consistent with expectations based on transformed Eulerian circulation derived from the DAO assimilated data and the mean ozone distribution. A net (photochemical plus transport) ozone decrease of over 0.2 ppmv/ month is predicted throughout the middle and lower stratosphere poleward of 70°N during the summer months.

Photochemical calculations along air mass trajectories during ASHOE/MAESA

The practicality of conducting photochemical calculations along trajectories of air masses is investigated. An isentropic trajectory package is used in conjunction with a detailed photochemical model to compare predictions of the mean chemical content of air masses initialized with the Halogen Occultation Experiment (HALOE) data with coincident in situ observations from instruments onboard the ER-2 aircraft. Comparisons are made for 10 ER-2 flights originating from Christchurch, New Zealand, during the May to June and October 1994 Airborne Southern Hemisphere Ozone Experiment/Measurements for Assessing the Effects of Stratospheric Aircraft (ASHOE/MAESA) deployments. Between 54 and 84 coincidences are found, depending on the species measured. Correlations between the ER-2 and HALOE air mass/box model calculations are high (0.56–0.90) for most species considered except for H2O (0.14) and HCl (0.24). Statistically significant low biases in the prediction of HCl, H2O, and OH are found. Kolmogorov-Smirnov (KS) significance tests are used to quantify the agreement between the distribution of species observed by the ER-2 and predicted by the HALOE trajectory/ photochemical model. The model predictions agree with the observed variance within the distributions at significance levels greater than 0.80 (greater than 80% confidence that the predicted and observed variance are identical) for H2O, ClO, O3, and NOy. The impact of computational errors in the trajectory calculations and measurement uncertainty in the computed confidence levels are investigated using Monte Carlo techniques. Computational trajectory errors are found to play a small role in reducing confidence levels. The error analysis shows that the HALOE trajectory/photochemical model calculations reproduce the large-scale variability found in the in situ ER-2 constituent measurements to within the expected uncertainties in the HALOE observations for all species considered. It is concluded that the combined trajectory/photochemical model is an effective tool for interpreting in situ aircraft observations within the global perspective provided by remote satellite measurements.

The SPARC Data Initiative: A comparison of ozone climatologies from international satellite limb sounders

A comprehensive quality assessment of the ozone products from 18 limb-viewing satellite instruments is provided by means of a detailed intercomparison. The ozone climatologies in form of monthly zonal mean time series covering the upper troposphere to lower mesosphere are obtained from LIMS, SAGE I/II/III, UARS-MLS, HALOE, POAM II/III, SMR, OSIRIS, MIPAS, GOMOS, SCIAMACHY, ACE-FTS, ACE-MAESTRO, Aura-MLS, HIRDLS, and SMILES within 1978–2010. The intercomparisons focus on mean biases of annual zonal mean fields, interannual variability, and seasonal cycles. Additionally, the physical consistency of the data is tested through diagnostics of the quasi-biennial oscillation and Antarctic ozone hole. The comprehensive evaluations reveal that the uncertainty in our knowledge of the atmospheric ozone mean state is smallest in the tropical and midlatitude middle stratosphere with a 1σ multi-instrument spread of less than ±5%. While the overall agreement among the climatological data sets is very good for large parts of the stratosphere, individual discrepancies have been identified, including unrealistic month-to-month fluctuations, large biases in particular atmospheric regions, or inconsistencies in the seasonal cycle. Notable differences between the data sets exist in the tropical lower stratosphere (with a spread of ±30%) and at high latitudes (±15%). In particular, large relative differences are identified in the Antarctic during the time of the ozone hole, with a spread between the monthly zonal mean fields of ±50%. The evaluations provide guidance on what data sets are the most reliable for applications such as studies of ozone variability, model-measurement comparisons, detection of long-term trends, and data-merging activities.

Comparison of satellite and in situ ozone measurements in the lower stratosphere

An air parcel trajectory model with chemistry initialized using data obtained by the Halogen Occultation Experiment (HALOE) has been demonstrated to be an effective tool for studying chemical and transport processes in the lower stratosphere. One of the sources of the differences between the trajectory calculations and the in situ observations from instruments aboard the NASA ER-2 aircraft is the uncertainty in the initial HALOE data. We compared HALOE ozone (O3) with near-coincident O3 obtained by the NOAA dual-beam UV-absorption photometer during the 1994 Airborne Southern Hemisphere Ozone Experiment/Measurements for Assessing the Effects of Stratospheric Aircraft campaign in a previous study. We have extended this study to obtain a more reliable evaluation of the differences in the remote and in situ O3 data by increasing the statistical base and using a revised version of HALOE data. In the present study we have extended the comparisons of O3 data to encompass four separate ER-2 airborne campaigns that have occurred since HALOE became operational in 1991. By extending the previous study to encompass the time span from 1991 through 1996, a broader range of latitude in both hemispheres, and a variety of seasons, we believe the conclusions resulting from the comparisons to be more robust and reliable. Statistical analyses show that the best agreement between HALOE and ER-2 O3 occurs in the 50–70 mbar region, where the difference of the means and RMS differences between the data sets are less than 7% and 28%, respectively, and where the HALOE data have an estimated error greater than 18% but less than 30%. Differences are larger in the 70–100 mbar region, where the maximum mean and RMS differences are 20% and 50%, respectively. These differences are somewhat less than those determined in the previous study.

Intercomparison of ozone measurements in the lower stratosphere from the UARS Halogen Occultation Experiment and the ER-2 UV absorption photometer

Ozone data obtained by the Halogen Occultation Experiment (HALOE) on the NASA Upper Atmosphere Research Satellite (UARS) have been compared with ozone data obtained by the NOAA dual-beam, UV absorption photometer on the NASA ER-2 aircraft during the 1994 Airborne Southern Hemisphere Ozone Experiment/Measurements for Assessing the Effects of Stratospheric Aircraft (ASHOE/MAESA) campaign. This paper describes the measurement characteristics of the two instruments and the precision and accuracy of the two data sets. A total of 26 cases are discussed in which the two different measurements occur within 24 hours, 2.5° latitude, and 10° longitude of each other. Generally, agreement between the two data sets improved the closer in time and space the two measurements occurred. The agreement was better than 10% at ER-2 cruise altitudes (∼50–70 mbar) where the error estimated for HALOE is slightly larger than 18%.

SPARC Data Initiative: A comparison of ozone climatologies from international satellite limb sounders – OZONE CLIMATOLOGIES FROM LIMB SOUNDERS

A comprehensive quality assessment of the ozone products from 18 limb-viewing satellite instruments is provided by means of a detailed intercomparison. The ozone climatologies in form of monthly zonal mean time series covering the upper troposphere to lower mesosphere are obtained from LIMS, SAGE I/II/III, UARS-MLS, HALOE, POAM II/III, SMR, OSIRIS, MIPAS, GOMOS, SCIAMACHY, ACE-FTS, ACE-MAESTRO, Aura-MLS, HIRDLS, and SMILES within 1978–2010. The intercomparisons focus on mean biases of annual zonal mean fields, interannual variability, and seasonal cycles. Additionally, the physical consistency of the data is tested through diagnostics of the quasi-biennial oscillation and Antarctic ozone hole. The comprehensive evaluations reveal that the uncertainty in our knowledge of the atmospheric ozone mean state is smallest in the tropical and midlatitude middle stratosphere with a 1σ multi-instrument spread of less than ±5%. While the overall agreement among the climatological data sets is very good for large parts of the stratosphere, individual discrepancies have been identified, including unrealistic month-to-month fluctuations, large biases in particular atmospheric regions, or inconsistencies in the seasonal cycle. Notable differences between the data sets exist in the tropical lower stratosphere (with a spread of ±30%) and at high latitudes (±15%). In particular, large relative differences are identified in the Antarctic during the time of the ozone hole, with a spread between the monthly zonal mean fields of ±50%. The evaluations provide guidance on what data sets are the most reliable for applications such as studies of ozone variability, model-measurement comparisons, detection of long-term trends, and data-merging activities.