The Potential Impact of Upper Stratospheric Measurements on Sub-seasonal Forecasts in the Extra-Tropics

  • Christopher Lee
  • Pieter Smets
  • Andrew Charlton-PerezEmail author
  • Läslo Evers
  • Giles Harrison
  • Graeme Marlton


This chapter examines the potential improvements in tropospheric weather forecasts that might arise from an enhanced representation of the upper stratospheric state. First, the chapter reviews current operational practice regarding observation of the atmosphere and the relative paucity of observations in the altitude range 40–70 km. Then, we describe some idealised model calculations to quantify the potential gain in skill available from improved monitoring in this region. The idealised model experiments use a relaxation technique with the Hadley Centre General Environment Model, to assess the potential gain in skill from observations both of the whole stratosphere and the upper stratosphere. At weather forecasting timescales (up to forecast day 30), better knowledge of the stratosphere, close to the onset of a sudden stratospheric warming, improves forecasts of the tropospheric northern annular mode. Whole-stratosphere information significantly improved average surface temperature anomalies over northern North America, whilst upper stratosphere information improved anomalies over Central Siberia. These results suggest any new observational technique which can contribute to monitoring of the 40–70 km region would likely benefit tropospheric forecast skill during wintertime.



This work made use of the facilities of HECToR, the UK’s former national high-performance computing service. Access was provided by the Natural Environment Research Council’s High Performance Computing Facility. This research is part of the Atmospheric Dynamics Research Infrastructure in Europe (ARISE) project, funded by the European Union’s Seventh Framework Program. We would like to thank Kirsty Hanley, Grenville Lister, Scott Osprey, Paul Telford and Peter Watson, for their help setting up the experiments discussed here.


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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Christopher Lee
    • 1
  • Pieter Smets
    • 2
    • 3
  • Andrew Charlton-Perez
    • 1
    Email author
  • Läslo Evers
    • 2
    • 3
  • Giles Harrison
    • 1
  • Graeme Marlton
    • 1
  1. 1.Department of MeteorologyUniversity of ReadingReadingUK
  2. 2.Seismology DivisionRoyal Netherlands Meteorological InstituteDe BiltThe Netherlands
  3. 3.Faculty of Civil Engineering and Geosciences, Department of Geoscience and EngineeringDelft University of TechnologyDelftThe Netherlands

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