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LegacyClimate 1.0: A dataset of pollen-based climate reconstructions from 2594 Northern Hemisphere sites covering the late Quaternary
| Content Provider | Scilit |
|---|---|
| Author | Herzschuh, Ulrike Böhmer, Thomas Li, Chenzhi Chevalier, Manuel Dallmeyer, Anne Cao, Xianyong Bigelow, Nancy H. Nazarova, Larisa Novenko, Elena Y. Park, Jungjae Peyron, Odile Rudaya, Natalia A. Schlütz, Frank Shumilovskikh, Lyudmila S. Tarasov, Pavel E. Wang, Yongbo Wen, Ruilin Xu, Qinghai Zheng, Zhuo |
| Copyright Year | 2022 |
| Description | Here we describe the LegacyClimate 1.0, a dataset of the reconstruction of mean July temperature $(T_{July}$), mean annual temperature $(T_{ann}$), and annual precipitation $(P_{ann}$) from 2594 fossil pollen records from the Northern Hemisphere spanning the entire Holocene with some records reaching back to the Last Glacial. Two reconstruction methods, the Modern Analogue Technique (MAT) and Weighted-Averaging Partial-Least Squares regression (WA-PLS) reveal similar results regarding spatial and temporal patterns. To reduce the impact of precipitation on temperature reconstruction and vice versa, we also provide reconstructions using tailored modern pollen data limiting the range of the corresponding other climate variables. We assess the reliability of the reconstructions using information from the spatial distributions of the root-mean squared error of prediction and reconstruction significance tests. The dataset is beneficial for climate proxy synthesis studies and to evaluate the output of climate models and thus help to improve the models themselves. We provide our compilation of reconstructed $T_{July}$, $T_{ann}$, and $P_{ann}$ as open-access datasets at PANGAEA (https://doi.pangaea.de/10.1594/PANGAEA.930512; Herzschuh et al., 2021). R code for the reconstructions is provided at Zenodo (https://doi.org/10.5281/zenodo.5910989; Herzschuh et al., 2022), including harmonized open-access modern and fossil datasets used for the reconstructions, so that customized reconstructions can be easily established. |
| e-ISSN | 18663591 |
| DOI | 10.5194/essd-2022-38 |
| Journal | Earth System Science Data Discussions |
| Volume Number | 2022 |
| Language | English |
| Publisher | Copernicus GmbH |
| Publisher Date | 2022-02-10 |
| Access Restriction | Open |
| Subject Keyword | Partial Least Squares Regression Reconstructions Using |
| Content Type | Text |
| Resource Type | Article |
