TY - JOUR
T1 - A new approach to paleoclimatic research using linear programming
AU - Kuby, Michael
AU - Cerveny, Randall
AU - Dorn, Ronald
N1 - Funding Information:
We thank Pat Bartlein,B rian Atwatera nd an anonymourse viewerf or helpful commentsa,n d Alan Mix for core V30-40 dataset. The "'SPECMAP" and "'Vostok" datasets were obtainedf rom the National GeophysicaDl ata Center in Boulder, Colorado. We thank B. Trapido-Lurifeo r graphicaslu pporat ndJ . Shaffer for digitizingth eD H-11 recordR. . Danielo f Dash AssociatesL td. providedt echnicals upporta nd consultingR. .C. receivedp artial support from NSF grantS ES 9121398M. .K, and R.D. thank ArizonaS tateU niversityfo r sabbaticaslu pport.
PY - 1997/4
Y1 - 1997/4
N2 - One of the most frequently attempted correlations in Quaternary research is between insolation and paleoclimatic data. Yet there are a large number of insolation time series that could potentially explain a Quaternary dataset, individually or in combination. We computed 342 insolation time series (varying by latitude, time of year and time of day) for fitting to four different paleoclimatic records: foraminiferal δ18O from SPECMAP; temperatures inferred from Vostok, Antarctica ice cores; marine accumulation rates of a freshwater diatom, Melosira, originating from tropical Africa lakebeds: and δ18O variations in calcite at Devil's Hole, Nevada. We developed two 'inductive' linear programming models that solve for the weighted combination of insolation 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 curves fit the proxy records 48-76% better than does June daily insolation at 60°N, the key insolation curve of the Milankovitch paradigm. Globally, high latitude insolation (60°-70°N and S) and insolation at specific times of day (noon or non-noon, as opposed to daily) dominated the results. Regionally, the model tended to select 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 curves repeatedly accounted for a disproportionate share of the explanation, suggest strongly that the correlations found are not happenstance, despite the inductive method used.
AB - One of the most frequently attempted correlations in Quaternary research is between insolation and paleoclimatic data. Yet there are a large number of insolation time series that could potentially explain a Quaternary dataset, individually or in combination. We computed 342 insolation time series (varying by latitude, time of year and time of day) for fitting to four different paleoclimatic records: foraminiferal δ18O from SPECMAP; temperatures inferred from Vostok, Antarctica ice cores; marine accumulation rates of a freshwater diatom, Melosira, originating from tropical Africa lakebeds: and δ18O variations in calcite at Devil's Hole, Nevada. We developed two 'inductive' linear programming models that solve for the weighted combination of insolation 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 curves fit the proxy records 48-76% better than does June daily insolation at 60°N, the key insolation curve of the Milankovitch paradigm. Globally, high latitude insolation (60°-70°N and S) and insolation at specific times of day (noon or non-noon, as opposed to daily) dominated the results. Regionally, the model tended to select 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 curves repeatedly accounted for a disproportionate share of the explanation, suggest strongly that the correlations found are not happenstance, despite the inductive method used.
KW - Climate change
KW - Linear programming
KW - Milankovitch
KW - Orbital parameters
KW - Quaternary
KW - Reconstruction
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U2 - 10.1016/S0031-0182(96)00118-6
DO - 10.1016/S0031-0182(96)00118-6
M3 - Article
AN - SCOPUS:0030620098
SN - 0031-0182
VL - 129
SP - 251
EP - 267
JO - Palaeogeography, Palaeoclimatology, Palaeoecology
JF - Palaeogeography, Palaeoclimatology, Palaeoecology
IS - 3-4
ER -