♦ CAM simulation underestimates the dry and wet events over central US.

1. Interannual Variability in Summer Hydroclimate over North America in CAM2.0 and NSIPP AMIP Simulations ByAlfredo Ruiz–Barradas1, and Sumant NigamUniversity of Maryland--------o--------8th Annual CCSM WorkshopBreckenridge, CO June 24–26, 2003 1alfredo@atmos.umd.edu 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: • 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. 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. 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.) From observed fields: ♦ 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. ♦ 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.                         ♦ 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. From NSIPP fields: SST Regressions: Different patterns. ♦ 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. ♦ Observed conditions: • 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. • A couplet of vertically integrated moisture flux convergence (VIMFC) anomalies over the Gulf of Mexico and Great Plains. • Southerly moisture flux from the Gulf of Mexico toward the Great Plains. ♦ Simulations: • 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. • 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. • 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. 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-the-art 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. ♦ 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. ♦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.