Experimental high-resolution winter seasonal climate reforecasts for Florida

Amit Bhardwaj, Vasubandhu Misra, Ben Kirtman, Tirusew Asefa, Carolina Maran, Kevin Morris, Ed Carter, Christopher Martinez, Daniel Roberts

Research output: Contribution to journalArticlepeer-review

Abstract

We present here the analysis of 20 years of high-resolution experimental winter seasonal climate reforecasts for Florida (CLIFF). These winter seasonal reforecasts were dynamically downscaled by a regional atmospheric model at 10-km grid spacing from a global model run at T62 spectral resolution (~210-km grid spacing at the equator) forced with sea surface temperatures (SST) obtained from one of the global models in the North American Multimodel Ensemble (NMME). CLIFF was designed in consultation with water managers (in utilities and public water supply) in Florida targeting its five water management districts, including two smaller watersheds of two specific stakeholders in central Florida that manage the public water supply. This enterprise was undertaken in an attempt to meet the climate forecast needs of water management in Florida. CLIFF has 30 ensemble members per season generated by changes to the physics and the lateral boundary conditions of the regional atmospheric model. Both deterministic and probabilistic skill measures of the seasonal precipitation at the zero-month lead for November-December-January (NDJ) and one-month lead for December-January-February (DJF) show that CLIFF has higher seasonal prediction skill than persistence. The results of the seasonal prediction skill of land surface temperature are more sobering than precipitation, although, in many instances, it is still better than the persistence skill.

Original languageEnglish (US)
Pages (from-to)1169-1182
Number of pages14
JournalWeather and Forecasting
Volume36
Issue number4
DOIs
StatePublished - Aug 2021

Keywords

  • Climate models
  • Ensembles
  • Probability forecasts/models/distribution
  • Seasonal forecasting
  • Seasonal variability

ASJC Scopus subject areas

  • Atmospheric Science

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