ppt - University of Maryland

Interannual Variability in Summer Hydroclimate over North America in CAM2.0 and NSIPP AMIP Simulations
By
Alfredo Ruiz–Barradas1, and Sumant Nigam
University of Maryland
--------o--------
8th Annual CCSM Workshop
Breckenridge, CO
June 24–26, 2003
[email protected]
1.Introduction. Interannual variability of stationary moisture fluxes over North
America from the Community Atmosphere Model (CAM2.0) and the NASA
Seasonal-to-Interannual Precipitation Project (NSIPP) Model are compared.
Seasonal moisture fluxes into the United States are dominated by those coming
from the Gulf of Mexico. The present study focuses on their interannual
variability and linkage with extreme hydroclimate events.
3b. Great Plains Precipitation Index.
Model performance over the Great Plains region can also be assessed through a
precipitation index over that region (Ting and Wang, 1997):
3c. Rotated Empirical Orthogonal Function Analysis. The structure of
interannual variability can also be characterized from rotated EOF analysis of
precipitation and contemporaneous surface temperature and pressure.
(The role of local land-surface interactions in generating hydroclimate
variability will likely be revealed by analysis of antecedent seasons’ surface
conditions, and this work is in progress.)
The large scale circulation features associated with these patterns are extracted
from regression of the principal components on geopotential height and moisture
fluxes.
From observed field analysis:
♦ Consistency with the regressed Great Plains
precipitation index:
• deep upper level low,
•southerly moisture flux from the
Gulf of Mexico toward a the
Great Plains,
• couplet of VIMFC anomalies
over the Gulf of Mexico and
Great Plains.
From observed fields:
2. Data. NCEP Reanalysis data set is used as target for AMIP runs from the
CAM and NSIPP models for the 1979-1993 period. The Xie/Arkin precipitation
data is used for additional corroboration. Data sets are on a 5x2.5 grid.
Reanalyses and simulation data sets are on pressure levels at 1000, 925, 850,
700, 600, 500, 400 and 300 mb. Monthly anomalies are calculated with respect
to the 1979-1993 climatology.
3. Results. Simulated summer hydrology is assessed in three ways, 1) through
their climatology, standard deviation, and extreme events, 2) through the
creation of a precipitation index, and 3) through a multivariate analysis.
3a. Climatology, standard deviation, and the 1988 and 1993 events.
♦ Precipitation anomalies centered over
the Great Plains region are the first mode
of variability.
♦ Timing match the dry and wet events of
1988 and 1993 respectively.
♦ Low/High surface pressure promotes
wet/dry conditions that cool/warm the
surface.
♦ Correlation with the Great Plains
precipitation index from Xie/Arkin is 0.8.
♦ Low correlations between the observed and simulated monthly indices during
May to August:
 CAM: mean MJJA correlation = 0.1
 NSIPP: mean MJJA correlation = -0.2
♦ High correlation in other months:
 CAM: September correlation = 0.6
 NSIPP: February correlation = 0.7
Regressed geopotential heights and vertically integrated moisture fluxes
illustrate the large scale circulation associated with the Great Plains
hydroclimate:
From CAM fields analysis
♦ Some similarities with the regressed Great
Plains precipitation index:
• weak upper level low,
• no southerly moisture flux from
the Gulf of Mexico toward the
Great Plains,
• geopotential heights anomalies
at upper levels from the tropics
toward midlatitudes.
From CAM fields:
♦ Precipitation anomalies over central US
are the second mode of variability.
♦ Coupling with precipitation anomalies
of opposite sign over the North American
Monsoon region.
♦ Relationship among fields is still valid.
♦ Correlation with the Great Plains
precipitation index from CAM is 0.7.
From NSIPP fields analysis:
♦ Few similarities with the regressed Great
Plains precipitation index:
♦ CAM precipitation is weaker over Central America, western Caribbean, Gulf
of Mexico, and the central US.
From NSIPP fields:
♦ Standard Deviation of precipitation is smaller in CAM than in both NSIPP
simulation and observations:
 Smaller ITCZ variability in CAM simulation.
 Smaller variability over central US in CAM simulation.
 NSIPP variability is closer to that observed over the central US.
♦ CAM simulation underestimates the dry and wet events over central US.
♦ CAM simulation is deficient over the eastern Pacific ITCZ region.
♦ Neither simulation is consistently better than the other over central US.
♦ CAM and NSIPP differences over the Gulf of Mexico and Central America
are mostly due to the larger NSIPP variability in that region.
♦ Observed conditions:
1) A deep upper level low over central US flanked by weak but identifiable
anticyclones, one off the west coast and another over the south east.
2) A couplet of vertically integrated moisture flux convergence (VIMFC)
anomalies over the Gulf of Mexico and Great Plains.
3) Southerly moisture flux from the Gulf of Mexico toward the Great Plains.
♦ Simulations:
1) Weaker upper level lows over central US that do not extend to 850 mb, and
deficient upper level anticyclones:
•
CAM does not have anticyclones while those from NSIPP are
stronger than the low.
2) Deficient VIMFC anomalies over the Gulf of Mexico and Great Plains:
•
CAM does not have VIMFC anomalies while NSIPP has
oppositely signed ones over the Gulf of Mexico.
3) Deficient southerly moisture flux from the Gulf of Mexico toward the Great
Plains:
•
CAM does not have it but NSIPP does.
•
Weak height anomalies over most of the eastern tropical Pacific
and adjacent American continent:
•
CAM has positive anomalies while NSIPP has negative
anomalies.
♦ Precipitation anomalies over central US
are the main pattern of variability.
♦ Anomalies are less shifted to the west
than those from the CAM fields.
♦ Relationship among fields is not clear.
♦ Correlation with the Great Plains
precipitation index from NSIPP is 0.7.
♦ Analysis for the larger period 1950-1998 (using the Hulme precipitation data
set) does not change the results of the observed fields but it does for the
simulated fields:
 The first CAM mode has now a maximum over northwest Mexico rather
than the Great Plains region; the second mode however has a maximum
over the Great Plains region.
 The first NSIPP mode is possibly spurious, arising from the larger model
variability over the eastern tropical Pacific. The second mode is similar to
the one shown above.
SST Regressions: Different patterns.
Observations: Large anomalies in both the
Atlantic and Pacific basins; PDV-like
structure in the Pacific?
CAM: Notable anomalies are confined to
the Pacific; ENSO-like features?
NSIPP: Anomalies in both the Pacific and
Atlantic
basins;
not
easily
characterized.
4. Conclusions. The undertaken analysis suggests that the notable Great Plains
summer precipitation anomalies are linked to anomalous vertically integrated
moisture flux from the Gulf of Mexico. AMIP simulations with the state-of-theart climate models do produce notable hydroclimate anomalies in the central US,
but are unable to capture the anomalous southerly moisture transport associated
with these events, as seen in observations. Perhaps, the moisture transport by
transient motions is more active in the models, but this needs to be investigated.
5. References.
Ting, M., and H. Wang, 1997: Summertime U.S. precipitation variability and its
relation to Pacific sea surface temperature. J. Climate, 10, 1853-1873.