G4.12 Lack of reference-quality data for temperature in the upper stratosphere and mesosphere

Gap abstract: 

The GCOS Reference Upper Air Network (GRUAN) provides reference in-situ data for temperature and humidity with traceable estimates of uncertainty. This network can be used to validate NWP short-range forecasts for temperature and humidity to reference standards (see gap G4.01). The NWP temperature and humidity forecasts can then be used to perform satellite Cal/Val of new instruments, with improved knowledge of the associated uncertainties. However, there are very few GRUAN data above 40 hPa and none above 5hPa. We therefore identify a gap in reference-quality observations in the upper stratosphere and mesosphere, which particularly affects the calibration/validation of microwave and infrared temperature sounding channels at these heights, particularly AMSU-A channels 12 – 14, ATMS channels 13 – 15, CrIS channels at 667.500 cm-1, 668.125 cm-1, and 668.750 cm-1, IASI channels at 648.500 - 669.750 cm-1 and AIRS channel numbers 54 - 83.

Part I Gap description

Primary gap type: 
  • Vertical domain and/or vertical resolution
Secondary gap type: 
  • Knowledge of uncertainty budget and calibration
ECVs impacted: 
  • Temperature
User category/Application area impacted: 
  • Operational services and service development (meteorological services, environmental services, Copernicus Climate Change Service (C3S) and Atmospheric Monitoring Service (CAMS), operational data assimilation development, etc.)
Non-satellite instrument techniques involved: 
  • Radiosonde
  • G4.01 should be addressed after G4.12.

    Gap 4.01 concerns about the lack of validation of NWP fields to reference standards. Validating NWP fields at 20 0.01hPa cannot be done without reference-quality data at these heights.

    G6.03 should be addressed with G4.12

    The colocation of GNSS-RO with a GRUAN sonde is in principle forecastable at least two weeks into the future. Potential golden overpass times, when the GRUAN site is coincident with a polar orbiter measure and a radio occultation measure, are therefore predictable. 

Detailed description: 

The direct assimilation of microwave and infrared temperature sounders into Numerical Weather Prediction (NWP) and reanalysis systems improves estimates of the atmospheric state, directly improving both the NWP weather forecasts, as well as the long-term monitoring of atmospheric temperature by reanalysis systems, such as Copernicus C3S reanalysis (ERA-5 and later). When data from new temperature sounders (e.g. ATMS, AMSU-A, IASI, AIRS, CrIS) become available, it is important to assess the quality of the observations before they can be assimilated. Short-range temperature forecasts from NWP systems provide a good reference for validating new temperature-sounding satellite instruments due to the high accuracy of these forecasts, particularly in the troposphere. For example, estimates of the uncertainties of tropospheric temperature forecasts for the ECMWF system indicate that they are around 0.1K in radiance space (Bormann et al, 2010). Using NWP forecasts as a reference also facilitates the inter-comparison of satellite data, since differences in time and space of the measurements can be accounted for with the use of a forecast model. This allows to estimate inter-satellite biases (e.g. Bormann et al 2013; Lu et al 2015).

While NWP temperature fields are very useful as a reference for satellite Cal/Val, this method does not currently lead to fully traceable estimates of uncertainty (see gap G4.01), since the uncertainties in the NWP background, the uncertainties in the radiative-transfer model, and the spatial-mismatch uncertainties are not known to fully traceable standards. This first point can be addressed by using reference in-situ data such as from GRUAN for assessing the uncertainties in the ECMWF and Met Office NWP short-range forecasts of temperature and humidity. To do this, a tool known as the GRUAN processor has been developed based on the EUMETSAT NWP Satellite Application Facility (NWP SAF) Radiance Simulator (see https://www.nwpsaf.eu/GProc_test/ins.shtml). This tool can be used to calculate the differences between GRUAN-temperature measurements and NWP forecasts in both geophysical space (temperature and humidity as a function of height) and radiance space (radiances as a function of channel for different satellite instruments) and compare these differences to the GRUAN uncertainties.

GRUAN reference temperature measurements are available from the surface to an atmospheric height of up to 5 hPa. However, less radiosonde data are available in the stratosphere than the troposphere and none above 5 hPa. In the upper reaches balloon-burst propensity leads to potentially biased sampling of solely warmer tail conditions. The lack of reference data in the upper stratosphere and mesosphere affects the assessment of uncertainties in NWP temperature fields to reference standards, leading to a poorer assessment at heights around 40 5 hPa and no assessment being possible above 5 hPa. In turn, this affects the calibration/validation of new temperature sounding data, which are sensitive to this portion of the atmosphere. This is particularly true of AMSU-A channel 14, whose weighting function peaks around 2 3 hPa, but it also affects channels 12 13 (peaking at 10 and 5 hPa respectively). The equivalent channels on ATMS are also affected, and there are also a number of infra-red temperature sounding channels on hyperspectral infrared sounders which are affected, including CrIS channels at 667.500 cm-1, 668.125 cm-1, and 668.750 cm-1, IASI channels at 648.500 - 669.750 cm-1 and AIRS channel numbers 54 - 83. Furthermore, the weighting functions for most satellite sounding channels have a stratospheric tail with some small sensitivity to the stratospheric temperature, so that this will contribute to the uncertainty of the Cal/Val for all channels, although with less of an impact for the channels peaking lower in the atmosphere.

The gap identified here is twofold a lack of reference observations at 40 5 hPa, and no reference observations above 5 hPa. The first part could be solved by supplementing the GRUAN-reference dataset with GNSS Radio Occultation (GNSS-RO) observations and products, including sets of bending angles and temperature retrievals. GNSS-RO bending angles have a high vertical resolution and uncertainties have been calculated both for these observations and for the derived temperature profiles with a high accuracy (Kursinski et al 1997). This makes GNSS-RO observations potentially very valuable as references for the calibration/validation of new satellite temperature-sounding data. We propose, therefore, including both the bending angles and derived temperature profiles, along with their estimated uncertainties, in the GRUAN processor in future work. This requires efforts to co-locate GRUAN profiles and GNSS-Radio Occultations. Such work will benefit where GRUAN sites in future make use of an EUMETSAT simulator that predicts up to two weeks in advance coincidence of polar orbiter overpasses and GNSS-RO occultations.

It should be noted that there are some known drawbacks to using GNSS-RO temperature profiles as a reference, however. Firstly, since the observations are directly sensitive to pressure/temperature rather than temperature, there is a so-called null space, in which the observations are blind to combined mean errors in temperature and pressure, which cancel each other out. Because of this, it is important to keep using reference radiosondes such as the GRUAN observations. Secondly, the temperature profiles at higher altitudes are less accurate since the observations rely on the bending by the atmosphere and in thin atmosphere the signal-to-noise ratio becomes very low. This makes it difficult to use GNSS-RO observations as a reference at altitudes above around 5 hPa (Healy and Eyre, 2000; Collard and Healy, 2003). The use of GNSS-RO measurements would therefore not help the lack of observations about 5hPa, but it would increase global coverage, improving the cal/val of new satellite temperature sounding data at heights of 40 5 hPa.

There is a clear need to develop instrumentation capable of measuring temperature routinely above 40 hPa (and in particular above 5hPa) in a traceable manner with metrologically well characterised uncertainties. The remedy defined here (using GNSS-RO temperature profiles as a reference dataset) only partially closes this gap and does not obviate the need for technological developments in upper atmosphere profiling.

Operational space missions or space instruments impacted: 
  • MetOp
  • MetOp-SG
  • Other, please specify:

All instruments with temperature sounding channels whose weighting functions include a significant contribution from 40 – 0.01 hPa. This includes:

  • All AMSU-A instruments (NOAA, MetOp and Aqua satellites)
  • Special Sensor Microwave Imager/Sounder instruments (F-16 to F-19)
  • ATMS instruments (Suomi-NPP, JPSS-1 and later)
  • MWTS-2 instruments (FY-3 satellite series)
  • MWHS-2 instruments (118 GHz channel 2) on FY-3 satellite series
  • MTVZA-GY instrument on Meteor-N
  • IASI instruments (MetOp series)

  • AIRS instruments (Aqua)
  • CrIS instruments (Suomi-NPP and JPSS satellite series)
  • HIRAS instruments (FY-3D and later satellites)
  • GIRSS (FY-4E and later)
  • MTG (Meteosat Third Generation) IRS
Validation aspects addressed: 
  • Radiance (Level 1 product)
  • Geophysical product (Level 2 product)
  • Gridded product (Level 3)
Gap status after GAIA-CLIM: 
  • After GAIA-CLIM this gap remains unaddressed

Part II Benefits to resolution and risks to non-resolution

Identified benefitUser category/Application area benefittedProbability of benefit being realisedImpacts
Space Agencies
  • International (collaboration) frameworks (SDGs, space agency, EU institutions, WMO programmes/frameworks etc.)
  • High
Better calibration/validation of stratospheric and mesospheric temperature sounding data
Numerical Weather Prediction
  • Operational services and service development (meteorological services, environmental services, Copernicus services C3S & CAMS, operational data assimilation development, etc.)
  • High
Improved assimilation of AMSU-A and ATMS higher peaking channels (particularly channel 14 AMSU-A and channel 15 ATMS)
Improved assimilation of the higher peaking channels on infra-red hyperspectral sounders (AIRS, IASI, CrIS)
Quantitative assessment of the biases in short-range forecasts in the upper stratosphere and mesosphere
Copernicus C3S Reanalysis
  • Operational services and service development (meteorological services, environmental services, Copernicus services C3S & CAMS, operational data assimilation development, etc.)
  • Climate research (research groups working on development, validation and improvement of ECV Climate Data Records)
  • High
Improved assimilation of temperature sounding channels sensitive to the upper stratosphere and mesosphere (see above)
Identified riskUser category/Application area at riskProbability of risk being realisedImpacts
Sub-optimal Cal/Val of atmospheric sounding data at heights of 40 – 5 hPa, due to very little available reference data.
  • All users and application areas will suffer from it.
  • High
Less confidence in the validation of NWP data to reference standard for these atmospheric heights, given the smaller number of available reference data.
No Cal/Val to reference standard possible for atmospheric sounding data strongly sensitive to heights above 5 hPa (e.g. AMSU-A channel 14).
  • All users and application areas will suffer from it.
  • High
The ‘true biases’ of upper stratospheric and mesospheric temperature sounding channels cannot be known due to a lack of reference data.
Consequently there is a larger uncertainty associated with the mean forecast and analysis values in the upper stratosphere and mesosphere
This uncertainty is supported by jumps observed in the long-term time series of stratospheric/mesospheric temperature analyses from reanalysis, associated with the AMSU-A data available at the time.

Part III Gap remedies

Gap remedies: 

Remedy 1: Use of GNSS-RO temperature profiles as a reference dataset for satellite Cal/Val

Primary gap remedy type: 
TRL 5 – technology development / demonstration
Secondary gap remedy type: 
Proposed remedy description: 

As a first step, we propose the inclusion of GNSS-RO bending angles and derived temperature profiles and their uncertainty estimates in the GRUAN processor. It is important to keep the bending angles, as well as the temperature profiles, since the latter have additional sources of uncertainty due to the need for prior information in the retrievals. This first step would involve some technical work. It would also require work by GRUAN sites to improve scheduling to match with GNSS-RO profiles within reasonable colocation criteria. EUMETSAT has developed a tool that has been shown to be able to forecast occultation positions with >98% skill up to two weeks in advance. This can forecast optimal launch times to create a full profile from the surface to 5hPa that coincides with a polar orbiter overpass.

A second step would be to carry out a research study comparing the NWP forecasts with GNSS-RO bending angles and derived temperature profiles and evaluate whether the mean differences fall within the uncertainty estimates. This would lead to an indication of the uncertainties in NWP temperature fields, as indicated by comparison with GNSS-RO observations.

The final step would be to evaluate these uncertainties in radiance space for different satellite instruments. The proposal here follows the procedure that is currently being used for GRUAN data in the GAIA-CLIM project. 


The solution proposed here addresses the lack of reference observations for temperature at atmospheric heights 40 5hPa. This is important for the calibration/validation of stratospheric temperature sounding channels. An additional benefit would be increased global coverage of reference temperature-sensitive observations. 

Measurable outcome of success: 

Firstly, development of the GRUAN processor to include GNSS-RO observations and uncertainties. Secondly, a documented study of the comparison between GNSS-RO temperature profiles and NWP temperature fields in both geophysical space (temperature-height) and radiance space (radiances by channel) for different satellite instruments. 

Expected viability for the outcome of success: 
  • High
Scale of work: 
  • Single institution
  • Consortium
Time bound to remedy: 
  • Less than 1 year
Indicative cost estimate (investment): 
  • Low cost (< 1 million)
Indicative cost estimate (exploitation): 
  • No
Potential actors: 
  • EU H2020 funding
  • National Meteorological Services
  • WMO
  • ESA, EUMETSAT or other space agency
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  •    Bormann, N., A. Fouilloux and W. Bell (2013). Evaluation and assimilation of ATMS data in the ECMWF system. Journal of Geophysical Research: Atmospheres. 118, pp. 12970 12980.

  •    Collard, A. and S. Healy (2003). The combined impact of future space-based atmospheric sounding instruments on numerical weather-prediction analysis fields: A simulation Study. Quarterly Journal of the Royal Meteorological Society, 129, pp. 27412760

  •    Healy, S. and J. Eyre (2000). Retrieving temperature, water vapour and surface pressure information from refractive-index profiles derived by radio occultation: A simulation study. Quarterly Journal of the Royal Meteorological Society, 126, pp.  1661-1683

  •    Kursinski, E. R., G. A. Hajj, J. T. Schofield, and R. P. Linfield (1997). Observing Earths atmosphere with radio occultation measurements using the Global Positioning System. Journal of Geophysical Research, 102.19, pp. 23429 23465.

  •     Lu, Q., H. Lawrence, N. Bormann, S. English, K. Lean, N. Atkinson, W. Bell, and F. Carminati (2015). An evaluation of FY-3C satellite data quality at ECMWF and the Met Office. ECMWF Tech. Memo., 767.