G6.03 Lack of sustained dedicated periodic observations to coincide with satellite overpasses to minimise co-location effects

Gap abstract: 

There are many non-satellite measurement systems that, in principle, could be used for the purposes of satellite characterisation on a sustained basis. Such measurements are metrologically well characterised and understood. They often measure variables, which are measured or measurable from space. However, many of the measurement systems are discontinuous (discrete) in time and their measurement scheduling is typically made with no regard to satellite-overpass times. This considerably diminishes their value for satellite Cal/Val activities. Better scheduling would increase their intrinsic value for satellite programs. 

Part I Gap description

Primary gap type: 
  • Governance (missing documentation, cooperation etc.)
Secondary gap type: 
  • Spatiotemporal coverage
  • Uncertainty in relation to comparator measures
ECVs impacted: 
  • Temperature,Water vapour, Ozone, Aerosols, Carbon Dioxide, Methane
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.)
  • International (collaborative) frameworks and bodies (space agencies, EU institutions, WMO programmes/frameworks etc.)
  • Climate research (research groups working on development, validation and improvement of ECV Climate Data Records)
Non-satellite instrument techniques involved: 
  • Radiosonde
  • Ozonesonde
  • Lidar
  • FPH/CFH
  • G6.01 - To be addressed with G6.03

    Argument: The resolution to the current gap will be simpler if a more unified governance of non-satellite measurement networks is achieved and the data is provided from these networks in a more unified manner.

    G6.06 To be addressed with G6.03

    Argument: Operationalising instruments that can be operated 24/7 removes the current gap for the instruments affected. 

Detailed description: 

For some non-satellite instruments, there are geophysical limitations as to when measurements can be undertaken, e.g. an FTIR requires direct line of sight to the sun or a MAX-DOAS can only measure at sunrise/sunset.

Other instruments can and do operate 24/7 and therefore could always capture a co-location, if the satellite passes overhead. For example, both GNSS-PW and microwave radiometers, in principle, operate on a 24/7 basis. G6.06 discusses issues around their continuous operation where this is not yet assured.

But for many non-satellite measurement techniques, it is for financial or logistical reasons that measurements are solely episodic. For example, operational radiosonde launches tend to be twice-daily or at best four times daily at fixed local times. Similarly, for many instrument configurations, lidar operations may be made only when staff are available. These types of considerations effect very many non-satellite measurements, which could, in principle, be better targeted to support EO-sensor characterization by taking measurements much closer to satellite-overpass time. This would reduce the co-location mismatch and thus the attendant mismatch uncertainties. Because funding for these observations typically is not concerned with satellite characterisation, the current sampling strategy ends up being sub-optimal for satellite characterisation. Better aligning sampling strategies with times of satellite overpass, which are predictable a substantial time in advance, would increase their utility to satellite Cal/Val activities. 

Operational space missions or space instruments impacted: 
  • Independent of specific space mission or space instruments
Validation aspects addressed: 
  • Radiance (Level 1 product)
  • Geophysical product (Level 2 product)
  • Time series and trends
  • Representativity (spatial, temporal)
  • Calibration (relative, absolute)
  • Auxiliary parameters (clouds, lightpath, surface albedo, emissivity)
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
Better intra-satellite and inter-satellite data characterization using the ground (non-satellite) segment through increased pool of co-locations to common non-satellite tie-points
  • 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
Better characterized satellite data will yield improved utilization in derived products, including reanalyses products and resulting services.
More robust funding support for ground-based observations continuity, recognising that ground-based products may have unique value in, e.g., providing vertically resolved profiles to characterise satellites.
  • Operational services and service development (meteorological services, environmental services, Copernicus services C3S & CAMS, operational data assimilation development, etc.)
  • International (collaboration) frameworks (SDGs, space agency, EU institutions, WMO programmes/frameworks etc.)
  • Medium
Increased diversity and quality of tools and data available to support service providers to develop bespoke products.
Identified riskUser category/Application area at riskProbability of risk being realisedImpacts
Insufficient number of high-quality co-locations in the future that meet co-location match-up criteria to meaningfully constrain (at least some) satellite missions.
  • 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
Reduced confidence in satellite measurements and products and services derived therefrom.
Inability to use non-satellite segment to effectively bridge across any unplanned gap in spaceborne EO capabilities
  • 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)
  • Low
Reduced colocations reduces the opportunity to use the non-satellite series to bridge the effects of any gap and yield a homogeneous series. This reduces the value of the satellite record for monitoring long-term environmental changes.
Reduction in perceived utility and value of measurements leading to reduction in funding
  • International (collaboration) frameworks (SDGs, space agency, EU institutions, WMO programmes/frameworks etc.)
  • Low
Diversifying the usage base of the high-quality measurements increases their intrinsic value and helps support widespread adoption.

Part III Gap remedies

Gap remedies: 

Remedy 1: Optimization of scheduling to enhance capability for satellite Cal/Val activities

Primary gap remedy type: 
Deployment
Secondary gap remedy type: 
Governance
Proposed remedy description: 

Sustained funding and governance mechanisms need to be instigated and assured that optimise the observational scheduling of relevant high-quality non-satellite periodic (non-continuous) measurements and their provision in NRT for satellite characterisation, if the full potential value of these measures is to be realised. To be effective, space agencies and non-satellite high-quality observing networks need to work together to design, instigate, and fund a sustained program of targeted measurements that optimise collection and dissemination of non-satellite data in support of the space-based observational segment. The scientific benefits will be maximised if a strategy can be devised, which optimizes the ability of the non-satellite data segment to characterize satellite instrument performance across time, across platforms and across instrument types. This, in turn, points to individual non-satellite observational segments being tasked with helping to characterise across multiple missions from multiple agencies from multiple countries to maximise the scientific value of the cal/val exercise rather than this support being extended and decided on a per mission basis. The strategy should include recourse to other measurements. For example, EUMETSAT have recently introduced a forecasting tool, which can, with high probability, forecast colocations of radio-occultation measurements with a ground-based instrument and any given polar orbiter mission. Finding such occurrences potentially enhances the value of co-locations substantially by making them multi-point comparisons.

Care must be taken for any changes in scheduling not to impact deleteriously upon existing functions and purposes of the non-satellite segment. This implies that, in at least some cases, the remedy will need to involve funding support commensurate with taking new or additional measurements at sites. The most obvious solution would be to instigate an international measurements support program, which would administer and disperse funding support for sustained satellite cal/val with reference-quality data from operators who optimise spending decisions and have as active stakeholders space agencies, non-satellite data providers, and end-users. 

Relevance: 

Better scheduling would increase the number of co-locations available for measurement systems that are discontinuous in time and increase the intrinsic value of the non-satellite observations for satellite Cal/Val. 

 

Expected viability for the outcome of success: 
  • High
Scale of work: 
  • Programmatic multi-year, multi-institution activity
Time bound to remedy: 
  • Less than 5 years
Indicative cost estimate (investment): 
  • Medium cost (< 5 million)
Indicative cost estimate (exploitation): 
  • Yes
Potential actors: 
  • Copernicus funding
  • National funding agencies
  • WMO
  • ESA, EUMETSAT or other space agency
  • Academia, individual research institutes
  • SMEs/industry
  • National measurement institutes

Remedy 2: Operationalise use of double-differencing techniques in co-location matchups to minimise the effects of scheduling mismatch

Primary gap remedy type: 
Deployment
Secondary gap remedy type: 
Research
Proposed remedy description: 

In some circumstances, competing demands make it impossible to better align scheduling of non-satellite measurements to satellite measurements. In other cases, the measurement itself is constrained by the measurement technique. Thus, efforts are required to quantify and reduce the impacts of scheduling mismatches if these cannot be avoided. Within GAIA-CLIM, much effort has been made on quantifying mismatch effects, but there are also potentially tools and techniques to effectively remove the effects, at least to first order. One potential way to do so, which has shown promise for ECVs amenable to data assimilation in NWP models, is double differencing (Tradowsky et al., 2017). This involves the calculation and comparison of the pair of differences to a model estimate between observations that are relatively proximal in space and time under the assumption that the model biases are either negligible or constant. In theory, the technique could be applied to a broad range of ECVs and problems although work would be required to develop such approaches using chemistry models or similar models. Work is additionally required to operationally produce such estimates and tag the co-locations with these estimates, if they are to prove useful in reducing the impact of unavoidable mismatch effects arising from conflicting scheduling requirements.

Relevance: 

Reduces the potential impact if a scheduling mismatch is unavoidable by removing a first order dynamical estimate of the effects of the differences in the sensed air mass. 

Measurable outcome of success: 
Expected viability for the outcome of success: 
  • High
Scale of work: 
  • Single institution
  • Consortium
Time bound to remedy: 
  • Less than 5 years
Indicative cost estimate (investment): 
  • Medium cost (< 5 million)
Indicative cost estimate (exploitation): 
  • Yes
Potential actors: 
  • National Meteorological Services
  • Academia, individual research institutes
  • SMEs/industry
  • National measurement institutes
References: 
  • Tradowsky J S, C P Burrows, S B Healy and J Eyre, 2017: A new method to correct radiosonde temperature biases using radio occultation data. J. Appl. Meteor. Climatol., 56, 1643-1661, https://doi.org/10.1175/JAMC-D-16-0136.1