1395个现代湖泊的季节湖-空温度传递函数:一个用代理湖水温度重建气温的工具

IF 1.9 3区 地球科学 Q1 GEOLOGY
Alexa Terrazas, Nathan Hwangbo, Alexandrea J. Arnold, Robert N. Ulrich, Aradhna Tripati
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引用次数: 0

摘要

湖泊古温度重建对于表征过去的温度和水文气候变化、验证多代理重建和评估全球气候模式具有重要意义。特别是湖泊水温通常由地球化学代用物——包括团块同位素(Δ47)、氧同位素(δ18O)、烯酮脂(Uk’37)和GDGT化合物(TEX86)得出。然而,受分辨率、计算需求和成本的限制,全球气候模式被设计为模拟大尺度过程,往往以解决湖泊和模拟湖泊温度为代价。因此,这一限制使气候模式模拟的变量(如空气温度)与湖水温度或其他代理变量(如花粉产生的空气温度)的比较复杂化,并且需要使用传递函数将湖泊温度与空气温度联系起来。以前的工作开发了传递函数,利用88个湖泊的地面测量数据,将代理获得的季节性湖泊水温转换为年平均气温。通过对1395个现代湖泊的气候再分析数据和地表温度的长期卫星观测数据进行基于回归的逆模型分析,本研究报告了新的湖泊-空气温度传递函数(全年、春季到夏季、春季、夏季和最暖月份),该函数包含湖泊地表水温度以及纬度和海拔等新变量。通过使用多元回归模型和大约10倍大的数据集,与以前的工作相比,年平均气温的预测误差减少了48%。为了证明新的传递函数在整合和比较代理数据与模式输出方面的潜力,我们利用Δ47-derived湖泊温度重建了上新世和更新世的年平均气温,并与末次冰期极大期和中皮亚琴世暖期的模式模拟结果进行了比较。新的传递函数具有更小的误差,应该能够更准确地从代理得出的湖泊水温重建古温度,并允许对气候模式技能进行更全面的评估。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Seasonal lake-to-air temperature transfer functions derived from an analysis of 1395 modern lakes: A tool for reconstructing air temperature from proxy-derived lake water temperature

Seasonal lake-to-air temperature transfer functions derived from an analysis of 1395 modern lakes: A tool for reconstructing air temperature from proxy-derived lake water temperature

Lacustrine palaeotemperature reconstructions are important for characterising past temperature and hydroclimate change, validating multi-proxy reconstructions and evaluating global climate models. In particular, lake water temperature is often derived from geochemical proxies—including clumped isotopes (Δ47), oxygen isotopes (δ18O), alkenone lipids (Uk’37) and GDGT compounds (TEX86). However, global climate models, constrained by resolution, computational demand and cost, are designed to simulate large-scale processes, often at the expense of resolving lakes and simulating lake temperature. Consequently, this limitation complicates the comparison of climate model-simulated variables such as air temperature, with lake water temperature or with other proxy variables (e.g. pollen-derived air temperature), and requires the use of a transfer function to relate lake temperature to air temperature. Previous work developed transfer functions to translate proxy-derived seasonal lake water temperature to mean annual air temperature using ground-based measurements from 88 lakes. This study reports new lake-to-air temperature transfer functions (for annual, spring through summer, spring, summer and warmest month) that incorporate lake surface water temperature, and new variables including latitude and elevation, by analysing climate reanalysis data and long-term satellite observations of surface temperatures for 1395 modern lakes via regression-based inverse modelling. With the use of multiple regression models and a dataset roughly 10 times larger, the error in predictions of mean annual air temperature is reduced by up to 48% compared to previous work. To demonstrate the potential of the new transfer functions for integrating and comparing proxy data with model output, Pliocene and Pleistocene mean annual air temperature was reconstructed from Δ47-derived lake temperatures and compared with model simulations for the Last Glacial Maximum and mid-Piacenzian warm period. The new transfer functions, with reduced error, should enable more accurate palaeotemperature reconstructions from proxy-derived lake water temperature and allow for more comprehensive assessments of climate model skill.

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来源期刊
CiteScore
4.10
自引率
16.70%
发文量
42
审稿时长
16 weeks
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