Search Results

You are looking at 1 - 4 of 4 items for :

  • Author or Editor: Min Chen x
  • Journal of Climate x
  • All content x
Clear All Modify Search
Jee-Hoon Jeong, Hans W. Linderholm, Sung-Ho Woo, Chris Folland, Baek-Min Kim, Seong-Joong Kim, and Deliang Chen

Abstract

The present study examines the impacts of snow initialization on surface air temperature by a number of ensemble seasonal predictability experiments using the NCAR Community Atmosphere Model version 3 (CAM3) AGCM with and without snow initialization. The study attempts to isolate snow signals on surface air temperature. In this preliminary study, any effects of variations in sea ice extent are ignored and do not explicitly identify possible impacts on atmospheric circulation. The Canadian Meteorological Center (CMC) daily snow depth analysis was used in defining initial snow states, where anomaly rescaling was applied in order to account for the systematic bias of the CAM3 snow depth with respect to the CMC analysis. Two suites of seasonal (3 months long) ensemble hindcasts starting at each month in the colder part of the year (September–April) with and without the snow initialization were performed for 12 recent years (1999–2010), and the predictability skill of surface air temperature was estimated. Results show that considerable potential predictability increases up to 2 months ahead can be attained using snow initialization. Relatively large increases are found over East Asia, western Russia, and western Canada in the later part of this period. It is suggested that the predictability increases are sensitive to the strength of snow–albedo feedback determined by given local climate conditions; large gains tend to exist over the regions of strong snow–albedo feedback. Implications of these results for seasonal predictability over the extratropical Northern Hemisphere and future direction for this research are discussed.

Full access
Huimin Chen, Bingliang Zhuang, Jane Liu, Shu Li, Tijian Wang, Xiaodong Xie, Min Xie, Mengmeng Li, and Ming Zhao

Abstract

Black carbon (BC) aerosol is a significant and short-lived climate forcing factor. Here, the direct effects of BC emissions from India (IDBC) and China (CNBC) are investigated in East Asia during summer using the state-of-the-art regional climate model RegCM4. In summer, IDBC and CNBC account for approximately 30% and 46% of the total BC emissions in Asia, respectively. The total BC column burden from the two countries and corresponding TOA effective radiative forcing are 1.58 mg m−2 and +1.87 W m−2 in East Asia, respectively. The regional air temperature increases over 0.3 K at maximum and precipitation decreases 0.028 mm day−1 on average. Individually, IDBC and CNBC each can bring about rather different effects on regional climate. IDBC can result in a cooling perturbation accompanied by a substantially increased cloud amount and scattering aerosol loading, resulting in a complex response in the regional precipitation, while CNBC can lead to regional warming, and further induce a local flood in northern China or drought in southern China depending on the opposite but significant circulation anomalies. CNBC plays a dominant role in modulating the regional climate over East Asia due to its higher magnitude, wider coverage, and stronger climate feedback. The direct effect of the total BC from both countries is not a linear combination of that of IDBC and CNBC individually, suggesting that the regional climate responses are highly nonlinear to the emission intensity or aerosol loading, which may be greatly related to the influences of the perturbed atmospheric circulations and climate feedback.

Open access
Paul A. Levine, James T. Randerson, Yang Chen, Michael S. Pritchard, Min Xu, and Forrest M. Hoffman

Abstract

El Niño–Southern Oscillation (ENSO) is an important driver of climate and carbon cycle variability in the Amazon. Sea surface temperature (SST) anomalies in the equatorial Pacific drive teleconnections with temperature directly through changes in atmospheric circulation. These circulation changes also impact precipitation and, consequently, soil moisture, enabling additional indirect effects on temperature through land–atmosphere coupling. To separate the direct influence of ENSO SST anomalies from the indirect effects of soil moisture, a mechanism-denial experiment was performed to decouple their variability in the Energy Exascale Earth System Model (E3SM) forced with observed SSTs from 1982 to 2016. Soil moisture variability was found to amplify and extend the effects of SST forcing on eastern Amazon temperature and carbon fluxes in E3SM. During the wet season, the direct, circulation-driven effect of ENSO SST anomalies dominated temperature and carbon cycle variability throughout the Amazon. During the following dry season, after ENSO SST anomalies had dissipated, soil moisture variability became the dominant driver in the east, explaining 67%–82% of the temperature difference between El Niño and La Niña years, and 85%–91% of the difference in carbon fluxes. These results highlight the need to consider the interdependence between temperature and hydrology when attributing the relative contributions of these factors to interannual variability in the terrestrial carbon cycle. Specifically, when offline models are forced with observations or reanalysis, the contribution of temperature may be overestimated when its own variability is modulated by hydrology via land–atmosphere coupling.

Open access
Chu-Chun Chen, Min-Hui Lo, Eun-Soon Im, Jin-Yi Yu, Yu-Chiao Liang, Wei-Ting Chen, Iping Tang, Chia-Wei Lan, Ren-Jie Wu, and Rong-You Chien

Abstract

Tropical deforestation can result in substantial changes in local surface energy and water budgets, and thus in atmospheric stability. These effects may in turn yield changes in precipitation. The Maritime Continent (MC) has undergone severe deforestation during the past few decades but it has received less attention than the deforestation in the Amazon and Congo rain forests. In this study, numerical deforestation experiments are conducted with global (i.e., Community Earth System Model) and regional climate models (i.e., Regional Climate Model version 4.6) to investigate precipitation responses to MC deforestation. The results show that the deforestation in the MC region leads to increases in both surface temperature and local precipitation. Atmospheric moisture budget analysis reveals that the enhanced precipitation is associated more with the dynamic component than with the thermodynamic component of the vertical moisture advection term. Further analyses on the vertical profile of moist static energy indicate that the atmospheric instability over the deforested areas is increased as a result of anomalous moistening at approximately 800–850 hPa and anomalous warming extending from the surface to 750 hPa. This instability favors ascending air motions, which enhance low-level moisture convergence. Moreover, the vertical motion increases associated with the MC deforestation are comparable to those generated by La Niña events. These findings offer not only mechanisms to explain the local climatic responses to MC deforestation but also insights into the possible reasons for disagreements among climate models in simulating the precipitation responses.

Open access