Content - Long-term Records for Climate Understanding

Long-term Records for Climate Understanding

Image Credit: JAXA

SPARC has a well-established history of assessing the quality and utility of long-term climate records of temperature, water vapour, ozone, and aerosols. SPARC promotes the creation, analysis, and interpretation of climate data records (CDRs) of a range of essential climate variables (ECVs), including temperature, water vapour, ozone, and aerosols. In particular, this research provides support to WMO/UNEP scientific assessments of ozone depletion and IPCC assessments of the physical science basis of climate change. Ozone CDRs are not only essential for assessing the effectiveness of the Montreal Protocol but are also needed for prescribing forcings in climate model simulations without stratospheric chemistry.

SPARC promotes activities to guide construction, analysis, and interpretation of CDRs that require international cooperation. For example, merging ground-based, balloon, aircraft, and space-based measurements and accounting for the spatial and temporal sampling characteristics of each measurement type.


Science questions

  • What are the vertically and spatially resolved trends in SPARC-relevant ECVs?
  • What are the requirements on observing programmes, both in terms of measurement uncertainties and measurement sampling regimens, such that these observing programmes can reliably detect and quantify trends?
  • Which species and state variables are needed, and with what resolution, frequency, and uncertainty, to better diagnose those changes in atmospheric composition and dynamics relevant to SPARC research?
  • Is the atmosphere, both in terms of chemistry and dynamics, evolving in a way that is consistent with our understanding?
  • What is the temporal evolution of global and regional forcing of the climate system, considering both natural and anthropogenic forcing?
  • To what extent do current observations test our knowledge of atmospheric composition and dynamics? Which observations would provide more robust tests of our current level of understanding?


Related SPARC activities: