Mid-Holocene ocean and vegetation feedbacks over East Asia

Abstract

Mid-Holocene ocean and vegetation feedbacks over East Asia are investigated by a set of numerical experiments performed with the version 4 of the Community Climate System Model (CCSM4). With reference to the pre-industrial period, most of the mid-Holocene annual and seasonal surface-air temperature and precipitation changes are found to result from a direct response of the atmosphere to insolation forcing, while dynamic ocean and vegetation modulate regional climate of East Asia to some extent. Because of its thermal inertia, the dynamic ocean induced an additional warming of 0.2 K for the annual mean, 0.5 K in winter (December–February), 0.0003 K in summer (June–August), and 1.0 K in autumn (September–November), but a cooling of 0.6 K in spring (March–May) averaged over China, and it counteracted (amplified) the direct effect of insolation forcing for the annual mean and in winter and autumn (spring) for that period. The dynamic vegetation had an area-average impact of no more than 0.4 K on the mid-Holocene annual and seasonal temperatures over China, with an average cooling of 0.2 K for the annual mean. On the other hand, ocean feedback induced a small increase of precipitation in winter (0.04 mm day^−1) and autumn (0.05 mm day^−1), but a reduction for the annual mean (0.14 mm day^−1) and in spring (0.29 mm day^−1) and summer (0.34 mm day^−1) over China, while it also suppressed the East Asian summer monsoon rainfall. The effect of dynamic vegetation on the mid-Holocene annual and seasonal precipitation was comparatively small, ranging from −0.03 mm day⁻¹ to 0.06 mm day⁻¹ averaged over China. In comparison, the CCSM4 simulated annual and winter cooling over China agrees with simulations within the Paleoclimate Modeling Intercomparison Project (PMIP), but the results are contrary to the warming reconstructed from multiple proxy data for the mid-Holocene. Ocean feedback narrows this model–data mismatch, whereas vegetation feedback plays an opposite role but with a level of uncertainty

Evaluation of CMIP5 palaeo-simulations to improve climate projections

“…Although some vegetation-enabled models show amplification of the northern Africa monsoon in the midHolocene 43,44 , the PMIP2 models with dynamic vegetation did not produce greater amplification of any of the Northern Hemisphere monsoons during that time 7 . Furthermore, mid-Holocene simulations with the (CMIP5) CCSM4 model 45 show that vegetation feedback produces only very small changes in seasonal temperature and has no impact on precipitation over the Pacific monsoon region. The contrast between these PMIP2/CMIP5 results and earlier studies that prescribed vegetation changes or used simpler models suggests that significant improvements to the modelling of vegetation and its coupling with the atmosphere are required to address the role of land-surface feedbacks properly 46 .…”

Vegetation and Ocean Feedbacks on the Asian Climate Response to the Uplift of the Tibetan Plateau

“…There are also some biases, particularly, the overestimated needleleaf tree over the TP, the overestimated broadleaf tree in the east of the TP, and the underestimated shrub and grass in these regions (Figure S2). This discrepancy has been reported by several previous studies using CESM, CCSM4, and only CLM4 (e.g., Castillo et al, ; Qiu & Liu, ; Tian & Jiang, ; Yu et al, ) and is partly due to the potential bias in preindustrial observation derived from MODIS data set and the fact that there are large crop distributions in the Indian Peninsula and East China in the MODIS data set but dynamic vegetation only simulates natural vegetation. Given that the large‐scale vegetation pattern in Asian continent is reasonably reproduced, it is feasible to use this dynamic vegetation model to study the vegetation feedback in response to the TP uplift.…”

“…The land and sea-ice components share the same horizontal grids as the atmosphere and ocean components, respectively. In CLM4, multiple land surface types and plant functional types (PFTs) are contained within one grid, and CLM4 can be run in a dynamic vegetation mode to simulate natural vegetation, including trees, grass, and shrub plant functional types (e.g., Castillo et al, 2012;Qiu & Liu, 2016;Tian & Jiang, 2013;Yu et al, 2014). Generally, CESM and its previous versions are capable of broadly reproducing the features of present-day climate (Gent et al, 2011) and have been widely used in climate modeling (e.g., Meehl et al, 2012;Rosenbloom et al, 2013).…”

Simulated warm periods of climate over China during the last two millennia: The Sui‐Tang warm period versus the Song‐Yuan warm period

“…The sea ice component is version 4 of the Community Ice Code, which adopts the same horizontal grid as POP2. CESM is capable of reproducing the major features of the present‐day climate [e.g., Marsh et al ., ; Tian and Jiang , ; Yan et al ., ] and has been widely used to simulate past and future climate [e.g., Hurrell et al ., ; Wei et al ., , ; Tian and Jiang , ; Peng et al ., ].…”

“…The blue star indicates the site where proxy data suggest cold conditions in the Sui-TangWP [Shi et al, 1999;Yang et al, 2000;Xu et al, 2002;Liu et al, 2006;Chu et al, 2012]. Marsh et al, 2013;Tian and Jiang, 2013a;Yan et al, 2014] and has been widely used to simulate past and future climate [e.g., Hurrell et al, 2013;Wei et al, 2012Wei et al, , 2014Tian and Jiang, 2013b;Peng et al, 2014].…”