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Mid-Holocene climate change over China: model-data discrepancy | |
Lin, Yating1,3; Ramstein, Gilles1; Wu, Haibin2,3; Rani, Raj1; Braconnot, Pascale1; Kageyama, Masa1; Li, Qin2; Luo, Yunli4; Zhang, Ran5; Guo, Zhengtang2,3 | |
2019 | |
Source Publication | CLIMATE OF THE PAST |
ISSN | 1814-9324 |
Volume | 15Issue:4Pages:1223-1249 |
Abstract | The mid-Holocene period (MH) has long been an ideal target for the validation of general circulation model (GCM) results against reconstructions gathered in global datasets. These studies aim to test GCM sensitivity, mainly to seasonal changes induced by the orbital parameters (longitude of the perihelion). Despite widespread agreement between model results and data on the MH climate, some important differences still exist. There is no consensus on the continental size (the area of the temperature anomaly) of the MH thermal climate response, which makes regional quantitative reconstruction critical to obtain a comprehensive understanding of the MH climate patterns. Here, we compare the annual and seasonal outputs from the most recent Paleoclimate Modelling Intercomparison Project Phase 3 (PMIP3) models with an updated synthesis of climate reconstruction over China, including, for the first time, a seasonal cycle of temperature and precipitation. Our results indicate that the main discrepancies between model and data for the MH climate are the annual and winter mean temperature. A warmerthan-present climate condition is derived from pollen data for both annual mean temperature (similar to 0.7K on average) and winter mean temperature (similar to 1K on average), while most of the models provide both colder-than-present annual and winter mean temperature and a relatively warmer summer, showing a linear response driven by the seasonal forcing. By conducting simulations in BIOME4 and CESM, we show that surface processes are the key factors creating the uncertainties between models and data. These results pinpoint the crucial importance of including the non-linear responses of the surface water and energy balance to vegetation changes. |
Subject Area | Geosciences, Multidisciplinary ; Meteorology & Atmospheric Sciences |
DOI | 10.5194/cp-15-1223-2019 |
Indexed By | SCI |
Language | 英语 |
WOS Keyword | LAST GLACIAL MAXIMUM ; HOLOCENE VEGETATION HISTORY ; PMIP2 COUPLED SIMULATIONS ; EARTH SYSTEM MODEL ; POLLEN RECORD ; INNER-MONGOLIA ; ASIAN MONSOON ; PALEOCLIMATE RECONSTRUCTION ; ENVIRONMENTAL-CHANGES ; FUTURE PROJECTIONS |
WOS Research Area | Geology ; Meteorology & Atmospheric Sciences |
WOS ID | WOS:000520467400001 |
Publisher | COPERNICUS GESELLSCHAFT MBH |
Subtype | Article |
Publication Place | GOTTINGEN |
EISSN | 1814-9332 |
Funding Organization | National Basic Research Program of ChinaNational Basic Research Program of China [2016YFA0600504] ; National Science Foundation of ChinaNational Natural Science Foundation of China (NSFC) [41572165, 41690114, 41125011] |
Corresponding Author Email | haibin-wu@mail.iggcas.ac.cn |
OA | gold, Green Submitted |
Citation statistics | |
Document Type | 期刊论文 |
Identifier | http://ir.ibcas.ac.cn/handle/2S10CLM1/19712 |
Collection | 植被与环境变化国家重点实验室 |
Affiliation | 1.Chinese Acad Sci, Inst Geol & Geophys, Key Lab Cenozo Geol & Environm, Beijing 100029, Peoples R China 2.Univ Paris Saclay, LSCE, IPSL, CEA,CNRS,UVSQ, F-91191 Gif Sur Yvette, France 3.CAS Ctr Excellence Life & Paleoenvironm, Beijing 100044, Peoples R China 4.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 5.Chinese Acad Sci, Inst Bot, Beijing 100093, Peoples R China 6.Chinese Acad Sci, Inst Atmospher Phys, Beijing 100029, Peoples R China |
Recommended Citation GB/T 7714 | Lin, Yating,Ramstein, Gilles,Wu, Haibin,et al. Mid-Holocene climate change over China: model-data discrepancy[J]. CLIMATE OF THE PAST,2019,15(4):1223-1249. |
APA | Lin, Yating.,Ramstein, Gilles.,Wu, Haibin.,Rani, Raj.,Braconnot, Pascale.,...&Guo, Zhengtang.(2019).Mid-Holocene climate change over China: model-data discrepancy.CLIMATE OF THE PAST,15(4),1223-1249. |
MLA | Lin, Yating,et al."Mid-Holocene climate change over China: model-data discrepancy".CLIMATE OF THE PAST 15.4(2019):1223-1249. |
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