Subseasonal prediction with and without a well-represented stratosphere in cesm1

Jadwiga H. Richter, Kathy Pegion, Lantao Sun, Hyemi Kim, Julie M. Caron, Anne Glanville, Emerson Lajoie, Stephen Yeager, Who M. Kim, Ahmed Tawfik, Dan Collins

Research output: Contribution to journalArticlepeer-review

12 Scopus citations

Abstract

There is a growing demand for understanding sources of predictability on subseasonal to seasonal (S2S) time scales. Predictability at subseasonal time scales is believed to come from processes varying slower than the atmosphere such as soil moisture, snowpack, sea ice, and ocean heat content. The stratosphere as well as tropospheric modes of variability can also provide predictability at subseasonal time scales. However, the contributions of the above sources to S2S predictability are not well quantified. Here we evaluate the subseasonal prediction skill of the Community Earth System Model, version 1 (CESM1), in the default version of the model as well as a version with the improved representation of stratospheric variability to assess the role of an improved stratosphere on prediction skill. We demonstrate that the subseasonal skill of CESM1 for surface temperature and precipitation is comparable to that of operational models. We find that a betterresolved stratosphere improves stratospheric but not surface prediction skill for weeks 3–4. SIGNIFICANCE STATEMENT: There is a growing demand in society for understanding sources of predictability on subseasonal to seasonal time scales. In this work we demonstrate that the CESM1 research Earth system model can be utilized as a subseasonal prediction model and show that its subseasonal prediction skill is comparable to that of operational models. We also show that the inclusion of a well-resolved stratosphere does not improve the subseasonal (week 3–4 averaged) forecast of temperature and precipitation at the surface.

Original languageEnglish
Pages (from-to)2589-2602
Number of pages14
JournalWeather and Forecasting
Volume35
Issue number6
DOIs
StatePublished - Dec 2020

Bibliographical note

Publisher Copyright:
© 2020 American Meteorological Society.

Keywords

  • Ensembles
  • Forecast verification/skill
  • Hindcasts
  • Seasonal forecasting
  • Stratospheric circulation
  • Tropical variability

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