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Predictability of Monthly Mean Temperature and Precipitation: Role of Initial Conditions

Predictability of Monthly Mean Temperature and Precipitation: Role of Initial Conditions. Mingyue Chen, Wanqiu Wang, and Arun Kumar Climate Prediction Center/NCEP/NOAA. Issues to be discussed. What is the predictability (prediction skill) because of initialized observed conditions?

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Predictability of Monthly Mean Temperature and Precipitation: Role of Initial Conditions

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  1. Predictability of Monthly Mean Temperature and Precipitation: Role of Initial Conditions Mingyue Chen, Wanqiu Wang, and Arun Kumar Climate Prediction Center/NCEP/NOAA

  2. Issues to be discussed • What is the predictability (prediction skill) because of initialized observed conditions? • What is the lead-time dependence? • How does the predictability due to atmospheric/land initial conditions compare with that from SSTs? Analysis method • Assess lead-time dependence of prediction skill of monthly means in CFS hindcasts • Compare CFS with the simulation skill from the AMIP integrations to assess predictability due to SSTs, and to assess on what time scale influence of initial conditions decays

  3. Models and data • Retrospective forecast • CFS (5 member ensemble) • AMIP simulations • GFS (5 member ensemble) • Variables to be analyzed • T2m • Precipitation • The analysis is based on forecast and simulations for 1981-2006

  4. Assessment of CFS monthly mean forecast skills with different lead times

  5. Definition of forecast lead time 30-day-lead 20-day-lead 10-day-lead 0-day-lead 1st day 1st day 11th day 21st day Target month

  6. CFS T2m monthly correlation skill • High CFS skill at 0-day lead time • Dramatic skill decrease with lead time from 0-day lead to 10-day lead and more slow decrease afterwards • Large spatial variation

  7. CFS T2m monthly correlation skill (global mean) • High CFS skill at 0-day lead time • Dramatic skill decrease with lead time from 0-day lead to 10-day lead and more slow decrease afterwards

  8. CFS T2m monthly forecast skills with different lead time(zonal mean) 20 10 50 40 30 0 • Little change with lead time over tropics • Quick decrease in high latitudes

  9. CFS Prec monthly forecast skills with different lead time • The monthly prec useful skills are at 0-day-lead forecast • No useful skill at lead time long than 10 day for most regions • Prec skill much lower than T2m skill

  10. Question:What is the source of remaining skill for longer lead-time forecasts? A comparison of CFS hindcasts with GFS AMIP simulations

  11. CFS T2m monthly correlation skill vs. GFS AMIP • The AMIP skill in high-latitudes is low • The GFS AMIP is similar to CFS in the tropics.

  12. CFS T2m monthly correlation skill vs. GFS AMIP(global mean) CFS forecast GFS AMIP • Globally, the AMIP skill is comparable to CFS skill at 20-30-day lead

  13. T2m monthly correlation skill (CFS vs. GFS AMIP)(zonal mean) 0 10 20 40 30 50 GFS AMIP • Similar skills in CFS & GFS AMIP near the equator • In N. lower latitudes (5N-35N), CFS skill higher at lead time shorter than 20 days • Over N. high latitudes (35N-80N), CFS skill higher at lead time shorter than 20-30 days

  14. Conclusions • For monthly forecasts, contribution from the observed land and atmospheric initial conditions does lead to improvements in skill. • The improvement in skill, however, decays quickly, and within 20-30 days, skill of initialized runs asymptotes to that from SSTs.

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