NDACC Theory and Analysis Protocol

Introduction

Network for the Detection of Atmospheric Composition Change, NDACC aims to encourage the widest possible use of its data. The role of the Theory and Analysis PIs is to enhance awareness of this NDACC data and to encourage its exploitation. Subject to the data protocol (see below) interested scientists will have direct access to all data products.

The primary goals of the Network for the Detection of Atmospheric Composition Change, NDACC, are:

• To study the temporal and spatial variability of atmospheric composition and structure in order to provide early detection and subsequent long-term monitoring of changes in the physical and chemical state of the stratosphere and upper troposphere; in particular to provide the means to discern and understand the causes of such changes.
• To establish the links between changes in stratospheric ozone, UV radiation at the ground, tropospheric chemistry, and climate.
• To provide independent calibrations and validations of space-based sensors of the atmosphere and to make complementary measurements.
• To support field campaigns focusing on specific processes occurring at various latitudes and seasons.
• To produce verified data sets for testing and improving multidimensional models of both the stratosphere and the troposphere.

The achievement of such goals requires high precision state-of-the-art measurements together with an analysis and interpretation procedure that both ensure excellent data quality and provide ready data access. The NDACC Data Protocol was thus structured to yield a verifiable product, referred to as "NDACC data" which would form the basis for trend detection and understanding.

The analysis and verification process through which atmospheric observations are transformed into NDACC data necessarily involves collaboration between the experimental measurement teams and theorists and statistical scientists. Such collaboration is valuable in areas such as: (i) data analysis (both the forward model and the retrieval of geophysical parameters), (ii) statistical studies (ascertaining the significance of the results), (iii) application of atmospheric modelling for the validation of the data, and (iv) scientific analysis of the data.

Areas (i) and (ii) are cornerstones of the NDACC; hence, the formal collaboration of relevant experts with instrument PIs is essential. Areas (iii) and (iv) are also important NDACC goals and involve collaboration with scientists, possibly with no previous contact with NDACC, accessing specific data products.

Use of Data

All NDACC data more than two years old (i.e. the vast majority) is public data. Additionally some instrument PIs have authorised their data for early release. This is available as soon as it is cataloged in the database. All NDACC data newer than two years from acquisition and not authorised for early release is proprietary data and available only through direct accounts on the NDACC database. Parties interested in general access to this data should prepare a proposal to the NDACC Steering Committee for consideration as NDACC collaborators. For more information contact the NDACC Steering Committee co-Chairs: Dr. Michael J. Kurylo or Dr. Geir O. Braathen. Otherwise, the use of any individual NDACC data set prior to its being made publicly available (i.e., for use associated with field campaigns, satellite validation, etc.) is possible via collaborative arrangement with the appropriate PI(s).

As with all investigators associated with the NDACC, Theory and Analysis collaborators must comply with the NDACC publication and data access policies set out in the NDACC Data Protocol. Scientists who access NDACC data are also encouraged to make contact with the relevant instrument PI in order to receive any direct comments on the data product which could be useful in their studies. Collaborators are also asked to acknowledge NDACC by name in written articles and presentations.

Further Theory and Analysis Needs of NDACC Instrument Groups

A number of theoreticians may be interested in collaborating closely with instrument PIs in order to improve the quality NDACC data products. The remainder of this document gives examples of where theory and analysis collaborators could work closely with NDACC PIs in order to achieve this (areas (i) and (ii) above). Collaborators interested in these activities should contact the Theory and Analysis Working Group Representatives, or the PIs of the relevant instruments. This list is by no means exhaustive and any scientist with an interest in the data retrieval process is welcome to contact the relevant instrument PIs.

General Needs:

Sampling Plans - Instrument PIs need plans for sampling that will accomplish early detection of trends for each species or parameter while not overburdening resources by collecting more data than is necessary for trend determination of the required sensitivity. These aspects of experimental design, including measurement frequency, need to be constructed from the statistical point of view, with attention given to parameter or species variation levels (e.g., sampling and testing standard deviations), autocorrelation in successive values, measurement locations, missing values, averaging periods, coincidental measures on other species, etc.

An overall plan for sampling must be designed to account for the general needs of the NDACC programs and the specific requirements for detecting changes in a given species measured by an instrument at a chosen site.

Quality Assurance and Control Plan - A general plan and set of guidelines for quality assurance and control is needed by the instrument PIs to maintain accuracy and precision of their instruments to the highest levels possible. This should have a strong statistical quality control basis that includes regular calibration checks and the detection of special cause variation (e.g., instrument drifts, outliers, inadequate viewing conditions, etc.). Experimental design procedures need to be applied to identify controllable operating conditions that keep the instruments on target with minimal measurement (i.e., analytical) variation. Control charts on the instrument performance against a set of standards will be needed.

Intercomparison - NDACC measurements from different instruments need to be compared for consistency and evidence of statistically significant differences. Consistency checks will be made against satellite instruments and with complementary measurements chosen for standard level comparisons. Causes of significant measurement differences between instruments measuring the same parameter will require interpretation from instrumental, theoretical, retrieval, and/or statistical bases.

Error Analysis - Error analysis and retrieval characterization need to be made in a unified and comparable manner, so that the nature of the remote measurements can be properly understood and intercomparisons can be carried out correctly.

Analysis of Long-Term Variability and Trends - Statistical analysis of NDACC data can include time series analysis of observations, along with more sophisticated comparisons to state-of-the-art chemistry-climate model (CCM) simulations. Time series analysis can involve multivariate regression studies to identify trends and other variability linked to the effects of the QBO, ENSO, solar cycle and other factors. More detailed comparisons with CCMs can include quantifying variability of temperatures and numerous trace species across a range of spatial and temporal scales, providing comprehensive fingerprints for validating model behavior and interpreting the long-term NDACC observations.

Specific Instrument Needs:

Collaborators who bring experience and expertise in the following areas could make a very valuable contribution to NDACC activities.

Lidar -

Lidar Retrieval Techniques - In all cases lidar signals have to be processed to obtain range resolved values of the geophysical parameters of interest: ozone, temperature, and aerosol scattering ratios. This processing generally implies spatial filtering, temporal averaging, and range derivative of the raw signals. Various methods have been developed using different filtering techniques (polynomial, derivative filters, windowing, etc.) to adapt the range resolution of the measurements to the expected signal to noise ratio. In particular, the range resolution has to vary with altitude.

Analysis of these various processing techniques can be conducted following the general methodology adopted for data processing evaluation in, for example, WMO/UNEP Ozone Assessments. This will allow the determination of the real altitude resolution and precision of the measurements. In addition, the magnitude of various systematic errors related to the use of ancillary data (ozone cross-section dependence on temperature, influence of pressure boundary conditions on temperature retrievals, calibration of aerosol measurements, etc.) should be studied further.

Microwave -

Microwave Spectroscopy - Microwave retrievals can only be as good as the forward radiative transfer models used in the inversion process. The accuracy of the forward models depends mainly on the line list and the spectral line parameters used in these models. Theory and analysis collaborators could include individuals who are expert in microwave spectroscopy. They could interface with the PIs to ensure that forward model line lists are kept current. In addition, the team could help ensure that the radiative transfer models themselves are up to standard by coordinating forward model comparison studies.

Inversion Techniques - It is important that the microwave retrievals are performed in the 'optimum' way and that such fundamental properties of the retrievals as vertical resolution and errors are properly characterized. Experts in these areas could provide support to the instrument PIs in developing and maintaining their operational retrieval algorithms. In addition, they could provide oversight to ensure the quality of these retrieval algorithms.

UV/Visible Spectroscopy -

UV/Visible observations of chemical species are carried out largely during twilight conditions and, therefore, require a good understanding of twilight chemistry. In addition, understanding the air mass factors characterizing the vertical columns of species measured requires a detailed analysis of scattering processes. Spectroscopy in the 300-700 nm region is a key aspect of the data analysis including consideration of the Ring effect, polarization, and the effects of clouds. Finally, as with other measurement techniques, a thorough understanding of error analysis is needed to aid in the NDACC data analysis and verification process.

FTIR Spectroscopy -

The infrared investigators could collaborate with theorists who specialize in infrared data and can help primarily in the data analysis. Collaborators could help with: (i) the selection of small regions (microwindows) for the retrieval of individual compounds, (ii) the determination of the molecular parameters and their uncertainties for use in the retrievals, design, and evaluation of retrieval algorithms, and (iii) studies of the information content of the line profile for determination of the vertical profiles of constituents. In these last two areas, the infrared work has a lot in common with microwave work.

Revised: September, 2010.