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W05415 WOODHOUSE ET AL.: UPDATED COLORADO RIVER RECONSTRUCTIONS W05415 Table 5a. Interbasin Correlations of Observed and Reconstructed Flows: Correlation Matrices of Observed and Reconstmction Flow for the Period 1906 -1995a GRUT COCI Obsel1'ed cocr 0.85 SJBL 0.55 0.77 Lees 0.92 0.98 Reconstrucfed COCI 0.87 SlBL 0.71 0.84 Lees 0.93 0.95 SJBL 0.83 aGRUT, Green River at Green River; COCl, Colorado River near Cisco: SJBL, San Juan near Bluff; Lees, Colorado at Lees Ferry. structed means are significantly (0. = 0.05) different than the observed mean. [23] Depending on reconstruction model, the long-term standard deviation is greater than (non-PCA models) or less than (PCA models) the standard deviation of observed flows (Table ~). If.climate ~ere equally variable before and during the cahbratlOn penod, compression of the variance in re~ression would tend to yield a long-term reconstruction WIth lower variance than that of the observed flows. The greater st::ndard ~eviation for the non-PCA models implies more varIable chmate before the start of the calibration period than after. All four reconstructions are negatively skewed, but the assumption of zero skew can be rejected (p < 0.05, N = 508) only for the reconstructions from the residual chronologies (Table 4). [24] Differences in first-order autocorrelation among models were noted for the 1906-1995 calibration period (Table 3), ~d those differences also apply to the long-term reconstructIons (Table 4). A comparison of first-order auto correlations of reconstructed data for the full recon- st':-lctio!l and the calibration period suggests the autocorre- latIOn III the calibration period is representative of the long-term record. It is also evident, however, that the autocorrelation of the reconstructed flows from residual chronologies is biased low relative to that of the observed flows (Table 3). The impact of the disparity in first-order autoc?rrelations !or model Lees-A was investigated by restormg the perSIstence to the reconstructed flow with an autor~gressi.ve model, and comparing the original recon- structIOn WIth the persistence-restored reconstruction. The two series were. extremely similar, and although 2-year droughts were shghtly less common and three-year slightly more common in the persistence-restored reconstruction, there were .no distinct differences for longer droughts. The reconstructIOns from standard chronologies more accurately reflect the first-order autocorrelation of the observed record (Table 3). Model Lees-D is perhaps strongest in this regard because the reconstructed flows are slightly more autocorre- lated than the observed flows. This is reasonable because the reconstruction errors are assumed to not be autocorrelated. [25] Extreme n-year running means are quite similar for the alternative Lees Ferry reconstructions, but somewhat more extreme for the reconstructions using the standard chronologies (Table 4). Regardless of model, the lowest I-year, 5-year and 20-year means for the full reconstructions are much below those in the observed flows. The lowest 0.79 reconstructed 20-year means for all models are in the late 1500s (Figure 4; note that this drought is somewhat more severe in the standard chronology PCA model). In the standard chronology models, the highest reconstructed n-year means exceed those in the observed record, with the exception of 5-year means. Smoothed time series of the four reconstructions are in agreement in the exceptional wetness of the early 1900s (Figure 4). The implication is that a period of such sustained wetness had not occurred since the start of the 1600s. [26] In summary, the above comparison shows that key features of the updated flow reconstructions for Lees Ferry are fairly robust to modeling choices. The models using the standard chronologies appear to more closely match the persistence in the gauge record, and the non-PCA version using standard chronologies (Lees-B) has the greatest cal- ibration period accuracy as measured by regression R2. On the other hand, the models based on standard chronologies overestimate the severity of muItidecadal droughts (20-year means) in the calibration period, which is worrisome considering that the regression procedure itself tends to compress reconstructed values toward the calibration period mean. Smoothed time series plots (Figure 4) suggest the PCA reconstruction on standard chronologies (Lees-D) is somewhat of an outlier, and gives a worst-case scenario for the severity of extended droughts and wet periods. In view of the fact that the subbasin gauges were reconstructed using the residual chronologies and a non-PCA approach, for consistency of analysis we used the reconstruction version Lees-A as the baseline record in the subbasin analysis that follows. 3.4. Spatial Fidelity Among Gauges and Reconstructions [27] The relationship between gauges within the Upper Colorado River basin, and how those relationships were preserved in the reconstructions, was evaluated by examin- ing the shared variance between the set of gauge records and the set of reconstructions. Spatial relationships were then examined with regard to the magnitudes of flow from the subbasins and their relationship to the total Colorado River flow at Lees Ferry. [28] In the gauge records, all flows are highly correlated (r > 0.77) except between the San Juan and the Green (r = 0.55), the most widely separated gauges (Table Sa). In the reconstructed flow records for the same time period (1906- 1995), the same relationships are preserved between the Green, Colorado-Cisco, and Lees Ferry reconstructions. Correlations between the San Juan and the other reconstruc- tions are somewhat inflated, particularly between the Green and San Juan (Table Sa). The relationships for the full Table 5b. Interbasin Correlations of Observed and Reconstmcted Flows: COlTelation Matrix of Reconstructed Flows for the Period 1569-1997a COCI SlBL Lees GRUT 0.87 0.69 0.93 COCI SlBL 0.83 0.96 0.82 aGRUT, Green River at Green River; COCI, Colorado River near Cisco; SlBL, San Juan near Bluff: Lees, Colorado at Lees Ferry. 7 of 16