Short Term forecasts along the GCSS Pacific Cross-section ...Cécile Hannay, Dave Williamson, Jerry...
Transcript of Short Term forecasts along the GCSS Pacific Cross-section ...Cécile Hannay, Dave Williamson, Jerry...
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Short Term forecasts
along the GCSS Pacific Cross-section:
Evaluating new Parameterizations
in the Community Atmospheric Model
Cécile Hannay, Dave Williamson, Jerry Olson, Rich Neale,
Andrew Gettelman, Hugh Morrison, Sungsu Park* and Chris Bretherton*.
National Center for Atmospheric Research, Boulder
*University of Washington, Seattle
CCSM Meeting, Breckenridge, June 17-19, 2008
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Outline
• The Pacific cross-section
• New candidate parameterizations for CAM4
• Methodology of the forecasts
• Evaluation of the forecasts against observations
• Conclusions
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The Pacific Cross-section
- Pacific Cross-section: several cloud regimes
stratocumulus, shallow cumulus, deep convection…
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Towards CAM4: a suite of new parameterizations
Control: CAM3
(2004)
- Deep convection: Zhang-McFarlane (1995)
- Microphysics: Rasch an Kristjansson (1998)
- Boundary layer: Holtslag-Boville (1993)
- Shallow convection: Hack (1993)
Deep convection (dilute)
Neale and Ritcher- parcels are diluted by environment air
Microphysics (MG)Morrison and Gettelman
- 2-moment scheme: prognostics variable for cloud mass
and number concentration (liquid + ice)
- explicit representation of mixed phase
PBL and shallow
convection (UW)Bretherton and Park
- Turbulence scheme includes explicit entrainment at the
top of the PBL
- Shallow convection: cloud-base mass flux based on
surface TKE and convection inhibition near cloud baseTo
wa
rds C
AM
4 (
Oct 2
00
8)
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Methodology for the forecasts
• StrategyIf the atmosphere is initialized
realistically, the error comes from the
parameterizations deficiencies.
• Advantages - Evaluate the simulation of moist
processes against observations taken
on a particular day and location
- Evaluate the nature of moist processes
parameterization errors before longer-
time scale feedbacks develop.
• LimitationsAccuracy of the atmospheric state ?
Initialize realistically ECWMF analysis
CAM
5-day forecastStarting daily at 00 UT
AIRS, ISCCP, TRMM, SSMI, CloudSat
ECWMF analyzes
Forecast
Evaluation
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Ensemble mean forecast and timeseries forecast
Individual forecasts
Timeseries forecast: concatenate
data at the same “forecast time”
(hours 0-24) from individual forecasts
Ensemble mean forecast:
average data at the same
“forecast time”
Forecast time (days)
Starting date
7/1
7/2
7/3
0 21 3
Day of July21 3
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Accuracy of the initialization: ECMWF versus AIRS
Temperature error, July 2003 Moisture error , July 2003
Accuracy of the daily global profiles
- temperature: 1 K per 1 km layer
- moisture: 20-60% per 2 km layer
ECWMF analysisIFS cycle 26r3
Longitude (moving East along cross-section)
Pre
ssu
re le
ve
ls (
mb
)
ITCZ Transition Stratocumulus
Longitude (moving East along cross-section)
ITCZ Transition Stratocumulus
Pre
ssu
re le
ve
ls (
mb
)
AIRS
ECWMF:
too shallow PBL
ECWMF: good
representation
of ITCZ
region
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Ensemble mean forecast: T error at day 1 and day 5
Control: T error, July 2003
where deep convection is active,
error is set within 1 day
5-day errors are comparable
to the mean climate errors.
Error built slower towards the
stratocumulus region
day 1
day 5
Longitude (moving East along cross-section)
ITCZ Transition Stratocumulus
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Sensitivity to the new schemes: T error at day 5
Change in the error
structure even
where the deep
convection is not
active
3. Microphysics (MG) 4. PBL/ShCu (UW)
2. deep convection (dilute)1. Control
Conclusion:
New schemes:
reduce T error
Cooling is related to shallow convection
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Precipitation along cross-section, July 2003
• Deep convection ~ improvement
• Model always drizzles
ITCZ Transition Stratocumulus
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Timeseries of precipitation at the ITCZ
Good correlation with obs
model misses strong events
Control
Deep convection (dilute)
Model always rains
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Cloud fraction averaged over day 1
3. Microphysics (MG) 4. PBL/ShCu (UW)
2. deep convection (dilute)1. Control
PBL/ShCuLow-level cloud further from the
coast and lower in the
troposphere
deep convectionReduces high level
cloud near ITCZ
CloudSat
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Low-level cloud as seen by ISCCP
Forecast timeseries (0-24h average)
Ensemble mean forecast
Major improvement of the
low-level clouds with the
new PBL/ShCu scheme
Longitude
Low
clo
ud
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High-level cloud as seen by ISCCP
Forecast timeseries (0-24h average)
Ensemble mean forecast
Longitude
Hig
h c
loud
High level cloud is largely
reduced by the new
convective scheme
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Conclusion
• CAM forecasts allows for diagnosing parameterization
errors in the different cloud regimes.
• Climate bias appears very quickly– where deep convection is active, error is set within 1 day
– 5-day errors are comparable to the mean climate errors.
• Sensitivity to candidate parameterizationsDeep convection (dilute):
- reduces temperature bias
- dramatic improvement of the precipitation in the ITCZ region
- high-level cloud fraction too low compared to ISCCP.
Microphysics (MG):
- little change along the cross-section.
PBL/ShCu (UW):
- improvement of the low-level clouds when compared to ISCCP.
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Extra slides
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Liquid water path versus SSMI
Longitude
Ensemble mean forecast (day1) Cloud water budget
• Cloud water is dumped out at the first timestep and slowly rebuilt within 5 days
• New microphysics: cloud water is too low near ITCZ.
• New PBL/ShCu: values too large in the transition and stratocumulus regions
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Moisture and ability to maintain the PBL height
+ new microphysics + new PBL/ShCu
+ new deep convectionControl
Stratocumulus: PBL too shallow but maintained in 5-day forecast
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Moisture and PBL for stratocumulus, JJA 1998
PBL heightSpecific humidity
Control
+ new
PBL/ShCu
Stronger daily cyclePBL collapses
day 0
day 1
day 2
day 5
Earlier results for JJA 1998
collapse of the PBL
compared to ECWMF.
But:
- different dynamical core
- different initialization
- different year
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Outstanding issues and future work
• Quality of the analysis in the stratocumulus region.
• Behavior of the PBL in the stratocumulus region for 1998
versus 2003 (impact of the dynamical core and of the initial
condition)
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Accuracy of the initialization: ECMWF versus AIRS
AIRS: Accuracy of the daily global profiles
- temperature: 1 K per 1 km layer
- moisture: 20-60% per 2 km layer
ECWMF analysisIFS cycle 26r3
Temperature error, July 2003 Moisture relative error , July 2003
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Cloud fraction averaged over day 1
+ new microphysics + new PBL/ShCu
+ new deep convectionControl
PBL/ShCuLow-level cloud in
stratocumulus and
cumulus regions
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LWP
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