A NEW APPROACH TO PALEOCLIMATIC RESEARCH USING LINEAR-PROGRAMMING

One of the most frequently attempted correlations in Quaternary resear ch is between insolation and paleoclimatic data. Yet there are a large number of insolation time series that could potentially explain a Qua ternary dataset, individually or in combination. We computed 342 insol ation time series (varying by latitude, time of year and time of day) for fitting to four different paleoclimatic records: foraminiferal del ta(18)O from SPECMAP; temperatures inferred from Vostok, Antarctica ic e cores; marine accumulation rates of a freshwater diatom, Melosira, o riginating from tropical Africa lakebeds; and delta(18)O variations in calcite al Devil's Hole, Nevada. We developed two ''inductive'' linea r programming models that solve for the weighted combination of insola tion curves that minimize either the average or maximum residual from the proxy curve. Each of the four proxy records, lagged and unlagged, was solved by both model types. On average, our composite insolation c urves fit the proxy records 48-76% better than does June daily insolat ion at 60 degrees N, the key insolation curve of the Milankovitch para digm. Globally, high latitude insolation (60 degrees-70 degrees N and S) and insolation at specific times of day (noon or non-noon, as oppos ed to daily) dominated the results. Regionally, the model tended to se lect insolation curves from absolute latitudes similar to those of the proxy records. The fact that these results are plausible given known biophysical processes, combined with the fact that a small number of c urves repeatedly accounted for a disproportionate share of the explana tion, suggest strongly that the correlations found are not happenstanc e, despite the inductive method used.