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

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

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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

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Assessment of CFS monthly mean forecast skills
with different lead times
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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
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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

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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

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CFS T2m monthly forecast skills with different
lead time(zonal mean)
20
10
0
30
40
50

• Little change with lead time over tropics
• Quick decrease in high latitudes

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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

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

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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

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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

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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.