Abstract

The stable isotopic composition of materials such as glacial ice, tree rings, lake sediments, and speleothems from low-to-mid latitudes contains information about past changes in temperature ( T) and precipitation amount ( P). However, the transfer functions which link δ 18O p to changes in T or P, dδ 18O p/d T and dδ 18O p/d P, can exhibit significant temporal and spatial variability in these regions. In areas affected by the Southeast Asian monsoon, past variations in δ 18O and δD of precipitation have been attributed to variations in monsoon intensity, storm tracks, and/or variations in temperature. Proper interpretation of past δ 18O p variations here requires an understanding of these complicated stable isotope systematics. Since temperature and precipitation are positively correlated in China and have opposite effects on δ 18O p, it is necessary to determine which of these effects is dominant for a specific region in order to perform even qualitative paleoclimate reconstructions. Here, we evaluate the value of the transfer functions in modern precipitation to more accurately interpret the paleorecord. The strength of these transfer functions in China is investigated using multiple regression analysis of data from 10 sites within the Global Network for Isotopes in Precipitation (GNIP). δ 18O p is modeled as a function of both temperature and precipitation. The magnitude and signs of the transfer functions at any given site are closely related to the degree of summer monsoon influence. δ 18O p values at sites with intense summer monsoon precipitation are more dependent on the amount of precipitation than on temperature, and therefore exhibit more negative values in the summer. In contrast, δ 18O p values at sites that are unaffected by summer monsoon precipitation exhibit strong relationships between δ 18O p and temperature. The sites that are near the northern limit of the summer monsoon exhibit dependence on both temperature and amount of precipitation. Comparison with simple linear models (δ 18O p as a function of T or P) and a geographic model (δ 18O p as a function of latitude and altitude) shows that the multiple regression model is more successful at reproducing δ 18O p values at sites that are strongly influenced by the summer monsoon. The fact that the transfer function values are highly spatially variable and closely related to the degree of summer monsoon influence suggests that these values may also vary temporally. Since the Southeast Asian monsoon intensity is known to exhibit large variations on a number of timescales (annual to glacial–interglacial), and the magnitude and sign of the transfer functions is related to monsoon intensity, we suggest that as monsoon intensity changes, the magnitude and possibly even the sign of the transfer functions may vary. Therefore, quantitative paleoclimate reconstructions based on δ 18O p variations may not be valid.

Highlights

  • Since 1964, when Dansgaard [1] ¢rst reported that the N18O of precipitation (N18Op) at a given locale re£ects environmental factors such as surface temperature (T), amount of precipitation (P), elevation, and source composition, numerous studies have attempted to infer paleoclimate information from the isotopic composition (N18O and ND) of paleoprecipitation preserved in natural archive materials, such as glacial ice, tree rings, lake sediments, freshwater mollusks, pedogenic carbonates, £uid inclusions in speleothems, and speleothem calcite

  • The goal of this study is to investigate the systematics of stable isotopes in precipitation in the Asian monsoon region of China, to improve interpretations of isotopic paleoclimate records obtained from archives in this region

  • This is analogous to linear regressions, such as those that are commonly performed between N18Op and T at higher latitudes, but through the use of multiple regression, we separate out the confounding e¡ects of precipitation that may obscure the underlying N^T relationship at low latitudes and in the Asian Monsoon region

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Summary

Introduction

Since 1964, when Dansgaard [1] ¢rst reported that the N18O of precipitation (N18Op) at a given locale re£ects environmental factors such as surface temperature (T), amount of precipitation (P), elevation, and source composition, numerous studies have attempted to infer paleoclimate information from the isotopic composition (N18O and ND) of paleoprecipitation preserved in natural archive materials, such as glacial ice, tree rings, lake sediments, freshwater mollusks, pedogenic carbonates, £uid inclusions in speleothems, and speleothem calcite. Continental paleoclimate records from the region include ice core records [6], loess records [14], speleothem records [4], lake records [15], and tree ring records [5] These proxy records suggest that the intensity of the Asian monsoon has undergone dramatic changes throughout the Pleistocene and Holocene, with a much drier climate during glacial times due to a decrease in summer monsoon intensity, and an increase in the intensity of the dry winter monsoon [16]. Multiple regression analysis is a convenient method for viewing stable isotopes in precipitation in three dimensions, treating N18Op, for example, as a function of two variables : surface temperature and precipitation amount This is analogous to linear regressions, such as those that are commonly performed between N18Op and T at higher latitudes, but through the use of multiple regression, we separate out the confounding e¡ects of precipitation that may obscure the underlying N^T relationship at low latitudes and in the Asian Monsoon region. Our hypothesis is that N18Op (or ND) at any given site, in regions where the amount e¡ect is important, can be described as: N18Op 1⁄4 L 0 þ L tT þ L PP þ O ð1Þ

Data and methods
Results
Southern China
Northeastern China
Northcentral China
Western China
Deuterium excess
Multiple regression versus mean N18Op
Multiple regression versus simple linear regression models
Findings
Conclusions
Full Text
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