“Upper Air” as used in the context of GRUAN refers to the combined troposphere and stratosphere. GRUAN places a strong emphasis on the upper troposphere/lower stratosphere region, which has the strongest climate relevance and a large variability. Measurement capabilities for different atmospheric parameters may be strongly altitude dependent and thus the abilities to achieve climate records at different altitude may vary.
Once fully completed GRUAN will be a world-wide network of reference stations. These stations should cover all major climatic regions of our planet. In its initial stage, GRUAN is heavily centered around a number of sites in Europe and the continental United States, with one site in China, several sites in the Western Pacific and only one site in the southern Mid-latitudes. Thus there is an obvious need to establish sites in a number of regions not yet covered by GRUAN.
A reference observations is an observation that gives the best estimate for the measurand as well as the best estimate for the level of confidence in this measurement. The best estimate for the measurand is nothing else than the measurement itself, the estimate for the level of confidence is described by the measurement uncertainty. Therefore, GRUAN will strive to establish uncertainty estimates for every measurement, which implies, that for a profile of an atmospheric parameter, GRUAN will attempt to establish the corresponding profile of the measurement uncertainty. The usefulness of any measurement will be determined by the size of the measurement uncertainty.
The measurement uncertainty will be established by analyzing all sources of measurement uncertainty and by combining them to one single error bar for each measurement point. The investigation of all sources of uncertainty will be a time consuming and iterative process and will require a detailed understanding of the instrumentation that is being used as well as a careful consideration of the operational influences that contribute to the measurement uncertainty. Error bars during the early stages of GRUAN are expected to be somewhat crude. As the understanding of the instrumentation improves and as the instrumentation itself improves, uncertainty estimations are expected to improve as well. Thus, it is expected that there will be different versions of GRUAN data, which differ mostly in their uncertainty estimate.
No. Precision is the recognition that there might be systematic uncertainties in a measurement, which are irrelevant for long term trends as long as the instrumentation does not change. However, for climate records spanning multiple decades, it is expected that the instrumentation will change several times. In particular sounding equipment has gone through a rapid development in the last years and slowing down of this development is not expected. Therefore, the distinction between accuracy and precision has only limited use for long term climate records. A more suitable concept is a best estimate for the level of confidence in a measurement, which may simply be called uncertainty estimation.
Systematic errors have to be corrected. This means that studies are required to identify and quantify systematic biases. The solar radiation correction for the temperature measurement on radiosondes is a classic example for such a systematic bias that requires correction. Since no correction algorithm is perfect, this correction will then introduce a new and hopefully random uncertainty, which is then combined with all other sources of uncertainty.
No. GRUAN stations will have a variety of instrumentation and observational platforms. The GRUAN challenge will be to homogenize the observations of this diverse set of instruments to establish a consistent data set that can be used for climate research, satellite validation and the characterization of the atmospheric column. However, to achieve homogeneity of observations between different stations identical treatment of observations is a must. This means that observational data have to be analyzed to the same detailed level and that uncertainty estimations have to be done consistently across all stations. To verify that observations and uncertainty estimates at different sites using different instrumentation leads to consistent results frequent intercomparisons of these instruments are required. This may be achieved either in dedicated intercomparison campaigns at dedicated sites or routine intercomparisons as part of the observational program.
Currently the only balloon borne sounding instruments capable of measuring water vapor in the tropopause region and the stratosphere are the Cryogenic Frostpoint Hygrometer (CFH, and the closely related NOAA frostpoint hygrometer) and Fluorescent Advanced Stratospheric Hygrometer (FLASH). GRUAN encourages the development of new instruments and will allow the use of other sondes capable of measuring stratospheric water vapor as they come online. For middle and upper tropospheric water vapor a number of radiosonde sensors may be used, however, a careful analysis is required and will be done, to remove any systematic biases and to reduce random errors. Several assessments and comparisons are currently under way and will be available in the future.
GRUAN calls for an uncertainty for every measured parameter. This includes wind measurements as well. Differences in wind and position measurements by different GPS systems have already been noted and this topic is not trivial. Uncertainties as the best estimate for the level of confidence for a given measurement should be established from a detailed understanding of the measurement principle and a detailed understanding of the processing that leads to the final reported measurement. Limitations in the uncertainty estimate imposed by manufacturers should be minimized where possible and verified through independent redundant measurements. In the worst case scenario, uncertainties can only be estimated in the comparison of different systems.
The Accurate Temperature Measuring (ATM) radiosonde is one instrument to quantify the solar radiation error of the temperature measurement. The use of such an instrument is highly encouraged and may be used with additional surface measurements aimed at quantifying the radiation error of different temperature sensors. Uncertainty estimates should be provided for this type of instrument as well and may require additional research. This research will strongly contribute to minimizing radiation related uncertainties of temperature measurements. The lead center may coordinate such efforts.
Guidelines for all instruments will be developed and guidelines for the CFH are in progress. A team composed of different GRUAN participants using the same kind of instrument (such as the CFH or any other type of instrument) could take up this task. This would indeed be highly beneficial. The lead center may motivate the formation of such groups.
Routine radiosondes generally provide better measurements on ascent. This is due to the fact that the rise rate is relatively constant and that in most instruments the sensor is oriented such that ascent measurements are less contaminated from the instrument package itself. Descent measurements may suffer from time lag issues on fast descending parachutes or from self contamination of temperature measurements on radiosondes. Polymer humidity sensors fall from fast a region of no sensitivity (stratosphere) into a region of sensitivity (troposphere) and enter this region at cold temperatures. This leads to a significant lag that needs to be corrected. Slow descents of valved balloons may not always be feasible and may lead to stronger self contamination for ascent oriented sensors (usually temperature). This issue needs to be studied further before a quantitative statement can be given.
Issues related to the non-co-location of different observing systems are currently being studied and depend critically on the horizontal distance as well as the local geography. Another important aspect is whether a non co-located routine sounding site is able to modify or amend current routine observations. Additional ground checks or more extensive meta data collection may be required to satisfy the needs of GRUAN. Thus it is important to understand the level of co-operation or control that a GRUAN site has over a non co-located radiosonde site. The critical question will be, whether it is possible to establish and verify measurement uncertainties for the routine sonde operations and whether it will be possible to compare these results in a quantitative fashion with remote sensing or special sonde operations at the core GRUAN site. If a quantitative connection between two non co-located sites cannot be established, their combined use may be limited.
GRUAN stations can submit their data in their native format. These data should include raw data, complete meta data as well as processed data. The GRUAN archive will add uncertainty estimations in cooperation with the station and bring all data into a standard format. The lead center can coordinate support for each site in data collection and data formatting.
At this point no strong financial support exists to fund observational programs under GRUAN. Strong and coordinated efforts will be required to secure long term secure funding for GRUAN. This issue will need to be addressed.
Real time and near real time delivery of observations is currently not a priority for GRUAN. The requirements for GRUAN are to provide upper reference observations of climate research, for the validation of globally comprehensive observations systems and for the complete characterization of the atmospheric column. These requirements will require additional processing, which is not expected to be delivered in near real time. Stations, which already deliver observations in near real-time are encouraged to continue this delivery schedule in support of numerical weather forecasting. However, stations not connected to real time data streams are not expected to implement near real time data delivery.
Best practices at a GRUAN site aim at obtaining long term climate reference observations and reference observations for validation of other sensors. This requires operational best practices as well as best practices for instruments and data analysis. Establishing measurement uncertainties will be an important element of best practices. This implies that any instrument that is being used needs to be characterized to the best possible extent. For example, ground checks for sounding equipment are highly recommended for each parameter independent from a manufacturers ground check. This will ensure that possible and unexpected instrumental biases may be identified before launch. Instrument preparation needs to be standardized as much as possible to reduce any possible observer influence. Another element will be establishing measurement uncertainties for every measurement point. This may be done in cooperation with the lead center depending on the instrumentation that is being used. This implies that as part of data analysis all know systematic biases (e.g., time-lag corrections or empirical corrections) are being applied and that all remaining uncertainties are characterized and quantified. Comparison with other reference instrument should be done routinely to verify, whether the uncertainty estimation is consistent and to identify weaknesses that need to be improved. The frequency of reference observations depends on the vertical altitude region as well as the natural variability of the measured parameter. This subject remains under investigation. Metadata need to be complete to describe every aspect of the measurement and every source of uncertainty. The lead center will provide a common template for metadata collection.