The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XLVIII-4/W1-2022
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-4/W1-2022, 187–194, 2022
https://doi.org/10.5194/isprs-archives-XLVIII-4-W1-2022-187-2022
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-4/W1-2022, 187–194, 2022
https://doi.org/10.5194/isprs-archives-XLVIII-4-W1-2022-187-2022
 
05 Aug 2022
05 Aug 2022

DEPLOYMENT OF AI-ENHANCED SERVICES IN CLIMATE RESILIENCE INFORMATION SYSTEMS

N. Hempelmann1, C. Ehbrecht2, E. Plesiat2, G. Hobona1, J. Simoes1, D. Huard3, T. J. Smith3, U. S. McKnight4, I. G. Pechlivanidis4, and C. Alvarez-Castro5 N. Hempelmann et al.
  • 1OGC - Open Geospatial Consortium, Innovation Program, Leuven, Belgium
  • 2DKRZ - German Climate Computing Center, Hamburg, Germany
  • 3Ouranos, Montreal, Canada
  • 4SMHI - Swedish Meteorological and Hydrological Institute, Norrköping, Sweden
  • 5CMCC - Fondazione Centro Euro-Mediterraneo sui Cambiamenti Climatici, Lecce, Italy

Keywords: Climate Resilience Information Systems, Climate Change, Climate resilience, OGC API Processes, Climate Service, Climate Indices

Abstract. Recent advances in modelling capabilities and data processing combined with vastly improved observation tools and networks have resulted in the expansion of available weather and climate information, from historical observations to seasonal climate forecasts, as well as decadal climate predictions and multi-decadal climate change projections. However, it remains a key challenge to ensure this information reaches the intended climate-sensitive sectors (e.g. water, energy, agriculture, health), and is fit-for-purpose to guarantee the usability of climate information for these downstream users. Climate information can be produced on demand via climate resilience information systems which are existing in various forms. To optimise the efficiency and establish better information exchange between these systems, standardisation is necessary. Here, standards and deployment options are described for how scientific methods can be be deployed in climate resilience information systems, respecting the principles of being findable, accessible, interoperable and reusable. Besides the general description of OGC-API Standards and OGC-API Processes based on existing building blocks, ongoing developments in AI-enhanced services for climate services are described.