Transcript ppt

Interannual Variability of Great Plains
Summer Rainfall in Reanalyses and
NCAR and NASA AMIP-like
Simulations
Alfredo Ruiz-Barradas
Sumant Nigam
Department of
Atmospheric and Oceanic Science
University of Maryland
5th International Scientific Conference on the Global Energy and Water Cycle
Orange County, California, USA
June 20-24, 2005
Motivation
To better know the structure and mechanisms of
precipitation variability in nature and models
At issue:
– Model validation
– Relative contributions of local (evaporation) and
remote (moisture fluxes) water sources
– SST-Circulation-Hydroclimate linkages
Outline
• The data sets.
• Precipitation variability over the Great Plains.
• Structure of hydroclimate fields and their
relative contributions associated with
precipitation anomalies.
• Implications on the surface energy balance.
• Conclusions.
• References.
Data Sets
•
•
•
•
North American Regional Reanalysis (NARR): 1979-1998.
ECMWF Global Reanalysis (ERA-40): 1958-1998.
NCEP Global Reanalysis (NCEP): 1950-1998
AMIP integrations from:
– NCAR’s Community Atmospheric Model, version 3.0 (CAM3.0):
1950-1998
– NASA’s Seasonal-to-Interannual Prediction Project Model (NSIPP):
1950-1998.
• CPC’s US-Mexico retrospective precipitation analysis
(US-Mexico): 1950-1998
• COLA’s Global Offline Land Surface Data set (GOLD):
1979-1998
Standard Deviation of
monthly rainfall during
summer (JJA)
•NARR assimilates very
well precipitation
•Quasi-realistic variability
in global reanalyses
•Models better than global
reanalyses
Blue box is used to define
the Great Plains
Precipitation (GPP) Index:
Area-averaged precipitation
anomalies.
Smoothed GPP Indices during the warm-season months
1993
1950s
1970s
1988
US-Mexico
0.90
Monthly JJA STD (mm/day)
NARR ERA-40 NCEP CAM3.0
0.81
0.66
1.21
0.96
NSIPP
0.99
US-Mexico
Monthly JJA
1
Correlations wrt US-Mexico
NARR ERA-40 NCEP CAM3.0
0.99
0.71
0.53
0.11
NSIPP
-0.09
Smoothed
1
0.99
0.55
0.33
0.25
0.06
Warm-season regressions
of monthly GPP indices on
PRECIPITATION
0.8
0.9
0.6
1.2
1.0
1.0
•Regionally confined
anomalies in NARR &
US-Mexico
•Sub-continental scale
anomalies in ERA-40 and
NCEP
•Simulated anomalies are
closer to observations than
global reanalyses
Warm-season regressions
of monthly GPP indices on
STATIONARY MOISTURE
FLUXES
NARR
•Southerly moisture fluxes
from the Gulf of Mexico and
Caribbean Sea converging
over central US.
•Westerly moisture fluxes
0.6
from southwestern states
Global Reanalyses
•ERA-40,especially, has
both pathways
Models
•CAM3.0 has very weak
transport from the Gulf of
Mexico
0.3
•NSIPP has stronger fluxes
from the Gulf of Mexico
•None of the models has
westerly fluxes
0.8
0.4
0.4
Warm-season regressions
of monthly GPP indices on
TRANSIENT MOISTURE
FLUXES
Transients carry moisture
from the southeast to the
northwest of the region,
especially in NARR and
ERA-40.
0.0
0.0
0.1
-0.0
Warm-season regressions
of monthly GPP indices on
TOTAL MOISTURE
FLUXES
•Total moisture fluxes keep
the circulation features
from the stationary
component.
0.7
0.6
0.5
•Maximum of MFC is now
centered in the region
0.4
Warm-season regressions
of monthly GPP indices on
EVAPORATION
0.2
0.1
•NARR and GOLD have
similar structure and
amplitude of anomalies
•Reanalyses EVAPORATION -0.1
anomalies are ~a third of
MFC anomalies (except in
NCEP).
•Simulated EVAPORATION
anomalies are ~twice the
MFC anomalies!!
0.8
0.2
0.7
CI=1/3 of that in P & MFC
Correlation between July’s
rainfall and preceding and
succeeding monthly rainfall.
US-Mexico
Low dependence on previous
months rainfall.
Reanalyses
Moderate dependence on
previous months rainfall.
CAM3.0
Dependence of previous
months rainfall is comparable
to reanalyses.
NSIPP
Very high dependence on
previous months rainfall
Warm-season regressions
of monthly GPP index on
SURFACE RADIATION
& TEMPERATURE
0.4
-0.8
SW anomalies are very
close in NARR and both
models, however, LH
anomalies are ~ 3x larger
in models:
NARR CAM3.0 NSIPP
SW -5.1
-5.2
-4.9
LH -5.8 -22.1 -19.9
-2.0
-2.0
Large evaporation in models
induces large surface cooling,
decreased upward LW
(increased LW anomalies),
increased SH from the atm
to the sfc and a total negative
surface energy balance:
-1.6
-1.4
NARR CAM3.0 NSIPP
LW 4.5
10.4
10.0
SH 6.8
14.8
13.6
EB 0.4
-2.0
-1.6
T -0.8
-2.0
-1.4
Conclusions
•Reanalyses suggest that remote water sources (moisture
fluxes) dominate over local water sources (evaporation) in
the generation of interannual rainfall variability over the
Great Plains during the warm-season.
•Models put a premium on local water sources
(precipitation recycling).
•Deficient simulation of moisture pathways feeding the
Great Plains.
•In consequence: regional hydroclimate simulations and
predictions remain challenging for global models (at least
in the context of variability over the Great Plains).
References
• Nigam, S., and A. Ruiz-Barradas, 2005: Seasonal
hydroclimate variability over North America in ERA-40,
Regional Reanalysis and AMIP simulations. Submitted to
J. Climate.
• Ruiz-Barradas, A., and S. Nigam, 2005a: Warm-season
Precipitation Variability over the US Great Plains in
Observations, NCEP and ERA-40 Reanalyses, and
NCAR and NASA Atmospheric Simulations. J. Climate.,
18, 1808-1829.
• ______, ______, 2005b: Great Plains Hydroclimate
Variability: The View from the North American Regional
Reanalysis. Submitted, J. Climate.