Two distinct modes of tropical convection structure and associated climate variability over East Asia/Korea in January

2021 ◽  
Author(s):  
Sae‐Rim Yeo ◽  
WonMoo Kim ◽  
Baek‐Min Kim
Keyword(s):  
Climate Variability ◽  
East Asia ◽  
Tropical Convection

Mineral magnetic record of the Miocene-Pliocene climate transition on the Chinese Loess Plateau, North China

2017 ◽  
Vol 89 (3) ◽  
pp. 619-628 ◽  
Author(s):  
Hong Ao ◽  
Mark J. Dekkers ◽  
Andrew P. Roberts ◽  
Eelco J. Rohling ◽  
Zhisheng An ◽  
...  
Keyword(s):  
Climate Variability ◽  
East Asia ◽  
Loess Plateau ◽  
Single Domain ◽  
Chinese Loess Plateau ◽  
Red Clay ◽  
Chinese Loess ◽  
Mineral Magnetic ◽  
Climate Transition ◽  
The Chinese Loess Plateau

AbstractPre-Quaternary terrestrial climate variability is less well understood than that during the Quaternary. The continuous eolian Red Clay sequence underlying the well-known Quaternary loess-paleosol sequence on the Chinese Loess Plateau (CLP) provides an opportunity to study pre-Quaternary terrestrial climate variability in East Asia. Here, we present new mineral magnetic records for a recently found Red Clay succession from Shilou area on the eastern CLP, and demonstrate a marked East Asian climate shift across the Miocene-Pliocene boundary (MPB). Pedogenic fine-grained magnetite populations, ranging from superparamagnetic (SP)/single domain (SD) up to small pseudo-single domain (PSD) sizes (i.e., from <30 nm up to ~1000 nm), dominate the magnetic properties. Importantly, our mineral magnetic results indicate that both pedogenic formation of SP grains and transformation of SP grains to SD and small PSD grains accelerated across the MPB in the Shilou Red Clay, which are indicative of enhanced pedogenesis. We relate this enhanced pedogenesis to increased soil moisture availability on the CLP, associated with stronger Asian Summer Monsoon precipitation during an overall period of global cooling. Our study thus provides new insights into the Miocene-Pliocene climate transition in East Asia.

scholarly journals Correction to: A newly developed APCC SCoPS and its prediction of East Asia seasonal climate variability

2019 ◽  
Vol 53 (5-6) ◽  
pp. 3703-3704 ◽  
Author(s):  
Suryun Ham ◽  
A-Young Lim ◽  
Suchul Kang ◽  
Hyein Jeong ◽  
Yeomin Jeong ◽  
...  
Keyword(s):  
Climate Variability ◽  
East Asia ◽  
Seasonal Climate

scholarly journals A newly developed APCC SCoPS and its prediction of East Asia seasonal climate variability

2018 ◽  
Vol 52 (11) ◽  
pp. 6391-6410
Author(s):  
Suryun Ham ◽  
A-Young Lim ◽  
Suchul Kang ◽  
Hyein Jeong ◽  
Yeomin Jeong
Keyword(s):  
Climate Variability ◽  
East Asia ◽  
Seasonal Climate

scholarly journals Prediction of Drought on Pentad Scale Using Remote Sensing Data and MJO Index through Random Forest over East Asia

2018 ◽  
Vol 10 (11) ◽  
pp. 1811 ◽  
Author(s):  
Seonyoung Park ◽  
Eunkyo Seo ◽  
Daehyun Kang ◽  
Jungho Im ◽  
Myong-In Lee
Keyword(s):  
Remote Sensing ◽  
Random Forest ◽  
Climate Variability ◽  
East Asia ◽  
Drought Index ◽  
Prediction Models ◽  
Remote Sensing Data ◽  
Drought Prediction ◽  
Drought Conditions ◽  
Index Maps

Rapidly developing droughts, including flash droughts, have frequently occurred throughout East Asia in recent years, causing significant damage to agricultural ecosystems. Although many drought monitoring and warning systems have been developed in recent decades, the short-term prediction of droughts (within 10 days) is still challenging. This study has developed drought prediction models for a short-period of time (one pentad) using remote-sensing data and climate variability indices over East Asia (20°–50°N, 90°–150°E) through random forest machine learning. Satellite-based drought indices were calculated using the European Space Agency (ESA) Climate Change Initiative (CCI) soil moisture, Tropical Rainfall Measuring Mission (TRMM) precipitation, Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST), and normalized difference vegetation index (NDVI). The real-time multivariate (RMM) Madden–Julian oscillation (MJO) indices were used because the MJO is a short timescale climate variability and has important implications for droughts in East Asia. The validation results show that those drought prediction models with the MJO variables (r ~ 0.7 on average) outperformed the original models without the MJO variables (r ~ 0.4 on average). The predicted drought index maps showed similar spatial distribution to actual drought index maps. In particular, the MJO-based models captured sudden changes in drought conditions well, from normal/wet to dry or dry to normal/wet. Since the developed models can produce drought prediction maps at high resolution (5 km) for a very short timescale (one pentad), they are expected to provide decision makers with more accurate information on rapidly changing drought conditions.

Land-atmosphere coupling and summer climate variability over East Asia

2011 ◽  
Vol 116 (D5) ◽  
Author(s):  
Jingyong Zhang ◽  
Lingyun Wu ◽  
Wenjie Dong
Keyword(s):  
Climate Variability ◽  
East Asia ◽  
Summer Climate

Mapping Large-scale Climate Variability to Hydrological Extremes: An Application of the Linear Inverse Model to Subseasonal Prediction

2020 ◽  
pp. 1-58
Author(s):  
Kai-Chih Tseng ◽  
Nathaniel C. Johnson ◽  
Eric D. Maloney ◽  
Elizabeth A. Barnes ◽  
Sarah B. Kapnick
Keyword(s):  
Climate Variability ◽  
Large Scale ◽  
Teleconnection Pattern ◽  
Inverse Model ◽  
Tropical Convection ◽  
Madden Julian Oscillation ◽  
Atmospheric Rivers ◽  
Hydrological Extremes ◽  
The Pacific ◽  
Linear Inverse Model

AbstractThe excitation of the Pacific-North American (PNA) teleconnection pattern by the Madden-Julian Oscillation (MJO) has been considered as one of the most important predictability sources on subseasonal timescales over the extratropical Pacific and North America. However, until recently, the interactions between tropical heating and other extratropical modes and their relationships to subseasonal prediction have received comparatively little attention. In this study, a linear inverse model (LIM) is applied to examine the tropical-extratropical interactions. The LIM provides a means of calculating the response of a dynamical system to a small forcing by constructing a linear operator from the observed covariability statistics of the system. Given the linear assumptions, it is shown that the PNA is one of a few leading modes over the extratropical Pacific that can be strongly driven by tropical convection while other extratropical modes present at most a weak interaction with tropical convection. In the second part of this study, a two-step linear regression is introduced which leverages a LIM and large-scale climate variability to the prediction of hydrological extremes (e.g. atmospheric rivers) on subseasonal timescales. Consistent with the findings of the first part, most of the predictable signals on subseasonal timescales are determined by the dynamics of MJO-PNA teleconnection while other extratropical modes are important only at the shortest forecast leads.

Estimation of winter PM2.5 concentrations in East Asia associated with climate variability

2020 ◽  
Author(s):  
Jaein Jeong ◽  
Rokjin Park ◽  
Sang-Wook Yeh ◽  
Joon-Woo Roh
Keyword(s):  
Climate Variability ◽  
East Asia ◽  
Transport Model ◽  
Climate Index ◽  
Anthropogenic Emissions ◽  
Climate Indices ◽  
Linear Regression Models ◽  
Chemical Transport Model ◽  
High Position ◽  
The Relationship

&lt;p&gt;Interannual variability in large circulations associated with climate connections, such as monsoon and El Ni&amp;#241;o, have a significant impact on winter PM&lt;sub&gt;2.5&lt;/sub&gt; concentrations in East Asia. In this study, we use the global 3D chemical transport model (GEOS-Chem) over the last 35 years to investigate the relationship between major climate variability and winter PM&lt;sub&gt;2.5&lt;/sub&gt; concentrations in East Asia. First, the model is evaluated by comparing the simulated and observed aerosol concentrations with the ground and satellite-based aerosol concentrations. The results indicate that this model well reproduces the variability and magnitude of aerosol concentrations observed in East Asia. Sensitivity simulations are then used with fixed anthropogenic emissions to investigate the effects of meteorological variability on changes in aerosol concentrations in East Asia. The variability of winter PM&lt;sub&gt;2.5&lt;/sub&gt; concentrations in northern East Asia was found to be closely correlated with ENSO and Siberian high position. To predict PM&lt;sub&gt;2.5&lt;/sub&gt; concentrations using key climate indices, we develop multiple linear regression models. As a result, the predicted winter PM&lt;sub&gt;2.5&lt;/sub&gt; concentrations using the key climate index are well reproduced in the simulated PM&lt;sub&gt;2.5&lt;/sub&gt; concentrations, especially in northern East Asia.&lt;/p&gt;

Sign in / Sign up

Export Citation Format

Share Document