Nonlinear dynamics and the Great Salt Lake: A predictable indicator of regional climate

被引:18
作者
Abarbanel, HDI
LAll, U
Moon, YI
Mann, ME
Sangoyomi, T
机构
[1] UNIV CALIF SAN DIEGO,SCRIPPS INST OCEANOG,MARINE PHYS LAB,LA JOLLA,CA 92093
[2] UTAH STATE UNIV,UTAH WATER RES LAB,LOGAN,UT 84322
[3] YALE UNIV,DEPT GEOL & GEOPHYS,NEW HAVEN,CT 06520
[4] HYDROSPHERE RESOURCE CONSULTANTS,BOULDER,CO 80302
关键词
D O I
10.1016/0360-5442(96)00018-7
中图分类号
O414.1 [热力学];
学科分类号
摘要
Using methods from nonlinear dynamics, we examine a long climatological record of measurements of the volume of the Great Salt Lake in Utah. These observations, recorded every 15 days since 1847, provide direct insight into the effect of large-scale atmospheric motions in climatological studies. The lake drains nearly 100,000 km(2), and it thus acts as a spatial filter for the finest degrees of freedom for climate. In filtering out a very large number of atmospheric and climatological motions, it reduces its complexity but retains its effectiveness as a climate sensing system. We demonstrate that there are four degrees of freedom active in the Great Salt Lake volume record, that these data reside on a strange attractor of dimension slightly larger than three, and that these data are predictable with a horizon of order a few years. We then show that predictive models based on local properties on the attractor perform remarkably well in reproducing the observations when trained on earlier observations. The ability to predict using earlier observations on the attractor suggests very strongly that over the period of the record, the system has been stationary and that it is a record of the natural variation of the climate. If there is anthropomorphic influence leading to changes in climate, this record suggests it has not made its effect measurable in such large-scale integrating observations. (C) 1996 Elsevier Science Ltd.
引用
收藏
页码:655 / 665
页数:11
相关论文
共 30 条
[1]  
Abarbanel H., 1996, Analysis of Observed Chaotic Data
[2]   THE ANALYSIS OF OBSERVED CHAOTIC DATA IN PHYSICAL SYSTEMS [J].
ABARBANEL, HDI ;
BROWN, R ;
SIDOROWICH, JJ ;
TSIMRING, LS .
REVIEWS OF MODERN PHYSICS, 1993, 65 (04) :1331-1392
[3]   LOCAL FALSE NEAREST NEIGHBORS AND DYNAMIC DIMENSIONS FROM OBSERVED CHAOTIC DATA [J].
ABARBANEL, HDI ;
KENNEL, MB .
PHYSICAL REVIEW E, 1993, 47 (05) :3057-3068
[4]  
ABARBANEL HDI, 1995, IN PRESS CLIMATE DYN
[5]   INVESTIGATING THE ORIGINS AND SIGNIFICANCE OF LOW-FREQUENCY MODES OF CLIMATE VARIABILITY [J].
ALLEN, MR ;
SMITH, LA .
GEOPHYSICAL RESEARCH LETTERS, 1994, 21 (10) :883-886
[6]  
BARNETT TP, 1991, J CLIMATE, V4, P269, DOI 10.1175/1520-0442(1991)004<0269:TIOMTS>2.0.CO
[7]  
2
[8]   SMOOTHING NOISY DATA WITH SPLINE FUNCTIONS [J].
WAHBA, G .
NUMERISCHE MATHEMATIK, 1975, 24 (05) :383-393
[9]  
DESER C, 1993, J CLIMATE, V6, P1743, DOI 10.1175/1520-0442(1993)006<1743:SCVOTN>2.0.CO
[10]  
2