利用气象观测资料预测未来气候，生成长期全新世气候资料的简单方法

IF 1.6 Q2 MULTIDISCIPLINARY SCIENCES

MethodsX Pub Date : 2025-03-13 DOI:10.1016/j.mex.2025.103265

Jake Tuuli , Andy J. Baird , Dylan M. Young , Andrew Duncan , Roxane Andersen

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引用次数: 0

摘要

泥炭地在全球碳储存中发挥着至关重要的作用，但它们对气候变化的适应能力仍不确定。本研究提出了一种新的方法来生成长期（>；1000年）特定地点的气候数据，以驱动泥炭地生态水文模型。利用气象观测资料，我们利用朗阿什顿研究站天气发生器（LARS-WG）生成降水和温度的随机气候序列。该方法整合了EPOCH-2数据库的全新世气候重建，模拟古气候趋势，并基于CMIP6模型的共享社会经济路径（SSP）插值气候预测。最后，利用修正版的Thornthwaite方程计算潜在蒸散量的时间序列。这种方法确保了泥炭地建模的气候输入的连续性，有助于评估长期气候对碳动态的影响。我们的方法为其他地区提供了一个可复制的框架，支持改进气候驱动的泥炭地模拟。•为特定地点量身定制的气候预测的长期古气候数据很少可用•本研究概述了一种简单的方法，用于生成驱动生态系统模型的气候序列•使用适用于整个欧洲的开源资源和数据库

本文章由计算机程序翻译，如有差异，请以英文原文为准。

A simple method for generating long-term Holocene climate data with future climate projections from meteorological observation data

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A simple method for generating long-term Holocene climate data with future climate projections from meteorological observation data

Peatlands play a crucial role in global carbon storage, yet their resilience to climate change remains uncertain. This study presents a novel method for generating long-term (>1000 years) site-specific climate data to drive peatland ecohydrological models. Using meteorological observations, we employ the Long Ashton Research Station Weather Generator (LARS-WG) to produce stochastic climate series for precipitation and temperature. The method integrates Holocene climate reconstructions from the EPOCH-2 database to simulate paleoclimate trends and interpolates climate projections based on Shared Socioeconomic Pathways (SSP) from CMIP6 models. Finally, a time series of potential evapotranspiration is calculated using a modified version of the Thornthwaite equation. This approach ensures continuity in climate inputs for peatland modelling, aiding in the assessment of long-term climate impacts on carbon dynamics. Our method provides a replicable framework for other regions, supporting improved climate-driven peatland simulations.

•
Long-term paleoclimate data with climate projections tailored to specific sites are scarcely available
•
This research outlines a simple method for generating climate series for driving ecosystem models
•
Uses open-source resources and databases that are applicable across Europe

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