Spatial and temporal variability in the stable isotope systematics of modern precipitation in China: implications for paleoclimate reconstructions

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.