IGACO Framework Architecture
IGACO Report: 5.1 A Global System is Required[edit | edit source]
GR1 Establishment: An Integrated Global Atmospheric Chemistry Observation System (IGACO) should be established for a target list of atmospheric chemistry variables and ancillary meteorological data.
The Integrated Global Atmosphere Chemistry Observation System (IGACO) proposed in this report consists of three measurement components (groundbased, aircraft and satellite), and a modelling component to integrate the observations into a global picture of atmospheric composition and its trends. In addition, there are the crucial additional elements of qualityassurance, data distribution and data archiving/ analysis. The proposed system is summarised in Section 5.2.
The proposed system is similar to that used by the meteorological community, which has a long history: the meteorological system was developed by the national hydrological and meteorological services and space agencies, coordinated by the WMO, to integrate measurements of meteorological variables important to weather prediction and climate. Today a system of non-satellite networks and satellites delivers observations of physical variables such as temperature, pressure, wind speed and humidity in real time through a Global Telecommunications System (GTS) to forecast modelling centres around the World. It also delivers a more comprehensive data set consisting of real-time and non-real-time observations to a data archive, where it is accessible for re-analysis using models at the NCEP, ECMWF and JMA. Using sophisticated mathematical descriptions of atmospheric processes and the most powerful computers available, these models serve to integrate the observations from a variety of sources into a comprehensive picture of current and projected global weather patterns.
Establishment of an integrated observational system for chemical variables lags, by several decades, the observational system for physical variables. Now, early in the 21st century, all the components are either in place or, with careful planning,will be readily available at reasonable cost within the next 10 years. What is missing is a well-focused strategic plan and an internationally coordinated implementation effort, which it is the purpose of this report to provide. The authors and the reviewers of this document agree that the establishment of IGACO to observe the composition of the atmosphere and its changes is necessary, timely, and feasible. It will be necessary to start planning immediately for a necessary minimum of satellites, ground stations and routine aircraft programmes, with the required modelling support, to produce IGACO.
GR2 Continuity: the data products from satellite and non-satellite instruments, which are to be integrated into a global picture by IGACO,must have assured long-term continuity.
In order to quantify the changing atmospheric composition, an overarching and fundamental requirement for IGACO is that continuity of measurement is maintained for all the system components.
GR3 Management of IGACO. The responsibility for the co-ordination and implementation of IGACO should rest with a single international body.
International and national agencies responsible for aspects of IGACO should be committed partners and agree on their appropriate responsibilities.
It is not yet clear where the responsibility for the development of IGACO in its entirety should lie. The current international meteorological, environmental and space agencies all have different mandates with respect to the generation of the data needed, and no one body is responsible for observing the changing atmosphere. This is a critical management issue to be dealt with in the implementation phase of IGACO, which is discussed further in Section 5.3.
5.2 The Proposed Architecture for IGACO[edit | edit source]
Fig. 5.1: IGACO Framework. It should be emphasised that, although various components and elements of the IGACO system are presently available or projected, a complete system does not yet exist for any atmospheric constituent in the target list of variables (Tables 4.2 and 4.3). Essential to the proper functioning of IGACO is a system for data collection from various sources, a system for distribution of the data to users and of archiving these data for establishing long-term records, as well as an end-to-end quality-assurance and qualitycontrol system to quantify the uncertainties in the data.
5.2.1 Measurements[edit | edit source]
GR4 Gaps in observational coverage: for each target species and variable, the present gaps in the current spatial and temporal coverage should be filled by extending the existing measurement systems.
The proposed measurement system comprises an optimised network of ground-based stations, routine aircraft flights and satellites in a configuration suitable for addressing the temporal and spatial variability of a specified chemical variable. Since observations are made with a variety of instruments, which vary in their spatial and temporal resolutions, an efficient mathematical approach to assimilating them into a global picture is necessary to define an optimal mix of each instrument type.Currently, there are major gaps in the global coverage of observations for all the target chemicals.
5.2.2 Quality-assurance and Data-handling protocols[edit | edit source]
GR5 Long-term validation of satellite observations: in order to ensure accuracy and consistency for satellite measurements, sustained qualityassurance measures, over the entire lifetime of the observations, are essential.
There are presently large gaps in the quantitative information for each chemical parameter about the comparability of observations by different instruments, which limits our ability to merge observations into a global data set. Quality assurance is the only effective way to ensure the comparability of data. Three elements of quality assurance are essential in the measurement/analysis/assessment hierarchy:
- Data Quality Objectives (DQO): defined by
trueness, precision, completeness, comparability and representativeness.
- Quality Control (QC): achieved through
calibration/validation and traceability to globally harmonised standards and reference methods, instrument and method intercomparison, good laboratory practice, etc.
- Quality Assessment (QA): achieved through
independent verification (e.g. system and performance audits for ground-based stations).
For most ground-based and routine aircraft observations of the gaseous species, the quality assurance of measurements is already achievable using internationally traceable standard reference materials or reference methods, routine inter-laboratory comparisons, instrument calibration programmes and data analysis aimed at ensuring that the qualityassurance criteria are being met. However, in practice, the effectiveness of delivery of quality assurance in a measurement programme is patchy at best. It is limited by the resources needed for key quality-assurance facilities and functions.
For satellite-borne sensors the quality-assurance commonly referred to as calibration/validation is more complicated. It involves the evaluation of the retrieval algorithms used to extract geophysical quantities from calibrated and well-characterised basic data products. Calibration/validation is being addressed by the Working Group on Calibration and Validation of the CEOS subgroup on atmospheric composition. A policy for validating data for satellite ozone and chemistry missions was suggested in WMO/CEOS Report No. 140. The components in the end-to-end calibration/ validation of satellite data are:
1. Pre-launch calibration. The purpose of calibration is to assign the correct physical quantities to instrument output. This encompasses a precise characterisation of the radiometric instrument response, including conversion of the measured signal to atmospheric radiances, as well as the accurate determination of the spectral domain and resolution, the viewing direction and, in some cases, the polarisation sensitivity. The uncertainties of these parameters and their sensitivity to environmental conditions needs to be established. For a large class of instruments, the need to carry out calibration under vacuum conditions encountered in space constitutes an important requirement. Calibration requires standards and measurements provided by the recognised national standards institutions to be known and traceable.
2. In-flight calibration is needed to quantify changes in the instrument induced by launch vibrations, outgassing upon deployment in space, thermal variations in orbit, ageing and radiation damage to electrical and optical components. It should include radiometric calibration using internal sources, solar radiation or deep-space measurements, spectral calibration with internal sources or solar or terrestrial spectroscopic measurements, pointing calibration, using welldefined terrestrial or celestial references. Usually, special calibration modes are required, which form part of the instrument design and the operational in-orbit scenario. It must be recognised that both in-flight and onground calibration will have inherent limitations. For example, on-ground calibration in vacuum will put limitations on the range and type of measurements that can be carried out, and terrestrial sources available will not always be able to simulate the instrument input prevalent in space. On the other hand, in space independent radiometric and spectral sources are not always available (for example, a source of known polarisation state).Therefore, calibration is often a compromise between what is needed ideally and what is achievable in practice.
3. Retrieval algorithm consistency. Multiple satellite systems will be in orbit measuring the same constituent (e.g. O3 from NPOESS and METOP). Every effort should be made to have a common or well-compared radiative transfer model and the same spectroscopic databases to ensure that these fundamental parameters do not cause biases. The respective algorithms for each system have a different heritage and physical basis. It is highly desirable to have a uniform data set among the systems so as to avoid biases between them. Comparisons of the algorithms using a common radiance data set should be conducted as part of the cal/val programme or even sooner.
4. Geophysical validation. Trace gas or aerosol data retrieved from spaceborne sensors are validated by comparison to the most reliable correlative data. Simultaneity and co-location of the measurements must be optimised, and any remaining sampling differences must be bridged using, for example, CTMs. Ideally, validation sources should be based on a different measurement principle or different spectroscopic features; they include ground-based networks and airborne measurements, sometimes complemented by chemical models to get access to additional species. Profile data covering the stratosphere and upper troposphere can often only be validated by scientific instruments operated on a campaign basis, e.g. on stratospheric balloons and aircraft. Intense geophysical validation campaigns are needed in the early phase of a space mission, followed by periodic short measurement campaigns and continuous use of routine observation networks, to monitor instrument performance throughout its lifetime.
5. Inter-satellite comparison. Observations of old and new satellite instruments require intercomparison in order to establish consistent longterm datasets, despite possible discrepancies between absolute values of data. Apart from their necessary role within IGACO, groundbased networks are essential components in the validation of satellite observations.
GR6 Validation of vertical-profile data from satellite observations: a set of high performance scientific instruments using ground, aircraft and balloon platforms, possibly operated on campaign basis, must be maintained to provide the crucial validation data.
Validation of satellite data also requires a component outside the long-term continuous observation system addressed in this report:
GR7 Comparability: the ability to merge observations of different types must be ensured by insisting that appropriate routine calibration and comparison activities linking diverse measurements together are part of an individual instrument measurement programme.
In order for the full power of diverse observations of any parameter to be fully realised, the quality and comparability of a measurement require that the data quality objectives are routinely met, and that they be available with the data.This is an essential requirement of IGACO.
GR8 Distribution of data: universally recognised distribution protocols for exchange of data on atmospheric chemical constituents should be established.
The data and associated quality-assurance information need to be in such a format that they are easily accessible in real time (for assimilation in forecast models) or on time scales of months to a year for integration into a comprehensive data archive using model integration techniques. Data distribution protocols are needed that allow for effective transmission of observations together with their associated quality-assurance information to an established archive and to forecast modellers. The Global Telecommunications System (GTS) of WMO is an example of such a system for real-time meteorological data.
5.2.3 World Integrated Data Archive Centres (WIDAC)[edit | edit source]
GR9 Multi-stake holder World Integrated Data Archive Centres (WIDAC) should be established for the targeted chemical variables.
GR10 Storage for raw data should be established so that they can be re-interpreted as models and understanding improves.
In the IGACO system, observations should be made available though a World Integrated Data Archive Centre (WIDAC) for future applications and re-analysis (see Fig. 5.1).The need for re-analysis will recur as more sophisticated tools and improved observational data become available. A WIDAC must be sufficiently robust that it can last for many years. The optimal configuration of the WIDAC will have to be decided, but it may be centralised or distributed. The meteorological community has such an archive for a short list of meteorological parameters, but is facing major challenges to extend it to other parameters such as water vapour. Furthermore, despite the maturity of meteorological data coordination, there is still no WIDAC for meteorological data that has free access. There is currently no potential WIDAC for any chemical constituent on the target list. World Data Centres do exist for individual network or satellite observations for particular variables on the target list, but there is no integration at present. For instance, GAW has a World Ozone and UV Data Centre for non-satellite observations and many organisations have surface ozone observations. The satellite agencies have ozone data centres for observations from specific satellite instruments, and there have been releases of qualitycontrolled data with suitable software tools to manipulate them; these include updates as funding allows. To bring all this information together in a synergistic way is the challenge that IGACO intends to meet.
Stakeholders in a WIDAC are:
- providers of measurement data,
- data analysis and model groups,
- users of the integrated data set.
A WIDAC should have periodic updates of observations and reanalysis built into it, so as to cope with the continuous improvement in satellite retrieval algorithms and revisions of nonsatellite observations. Access to data should be free of charge and expedited by software tools that are userfriendly. 5.2.4 Models and model inputs needed for the IGACO system
GR11 The development of comprehensive chemical modules in weather and climate models should be an integral part of IGACO.
As the preceding sections illustrate, atmospheric models that encompass the target constituents are needed for use in forecasting air quality and for reanalysis of the global comprehensive database in the WIDAC to produce a 4-D composition distribution. Data assimilation tools have started to provide consistent distributions of stratospheric ozone and water vapour on a routine basis. They now need to be improved and extended to include other species on the IGACO target list. The assimilation of all of these species into the weather and climate models which include a full chemical scheme will allow for more confident predictions of the distributions of many other compounds not on the target list. GR12 Strong coordination with meteorological services is essential so that the ancillary meteorological data required by IGACO is accessible.
The requirements for numerical weather prediction have been mandated to and are addressed by the national meteorological services represented by the WMO. The essential ancillary data for IGACO listed in Chapter 4 is, in principle, available from them.However, some coordination is needed to ensure that the data is in fact freely available.
IGOS Workshop IGOS Framework on Data[edit | edit source]
B.7 Data Integration - Prof. Toshio Koike (Univ. of Tokyo)
Key issues identified for Theme implementation
Data policies[edit | edit source]
- coordination/harmonization by relevant international organizations
- data accessibility
- data timeliness
- data provider's privilege for R&D
- metadata (documentation on the data)
Standards, practices and calibration[edit | edit source]
- standard format or conversion function based on data description
- quality control
- real time or delayed mode
Transformation of measurements into information[edit | edit source]
- combination with many other data sources: natural science - socio-economic
- too voluminous and heterogeneous
- prediction needs:
- Information sharing worldwide
Key recommendations[edit | edit source]
To IGOS-P or related entities:
- Establish a Data Integration Function, distributed/centerized, in each Theme and encourage collaboration among Themes;
- Promote co-operation between the IGOS Themes and Global Mapping for strengthening the Theme impact on socio-economical aspects;
- Promote collaboration among research communities and operational organizations for establishment of sustained Data Integration systems.
To GEO, sponsoring bodies etc:[edit | edit source]
- Develop a ten year implementation plan for Data Integration by considering perspectives on computing power and data amount;
- Emphasise the combination of in-situ data/satellite data /model output with socio-economic data for contributions to sound decision-making;
- Promote collaboration among research communities and operational organisations for establishment of sustained Data Integration systems.