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