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45 results for “Asian Monsoon”
Case Study Scenarios (CSS) 10 for the Asian Summer Monsoon
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AGCM output for "Effects of subseasonal variation in the East Asian monsoon system on the summertime heat wave in western North America in 2021"
<p>The file named "EXP_2021ANO_heat.nc" is the anomalous heating used in "EXP_2021ANO". The file of "EXP_2021ANO_output.nc" is simulated largescale fields including temperature, zonal and meridional winds and geopotential height at 5 sigma levels integrated for 121 days.</p> <p>The files named "EXP_2021ANO_ens*_heat.nc" and "EXP_2021ANO_ens*_output.nc" are the anomalous heating and simulated largescale fields from five ensemble members of "EXP_2021ANO" experiment, respectively. </p> <p>The files named "EXP_2021CL_*.nc", "EXP_2021HT_*.nc", and "EXP_CLIMJET_*.nc" are same with "EXP_2021ANO_*.nc", but for the results for sensitive experiemts of "EXP_2021CL", "EXP_2021HT" and "EXP_CLIMJET".</p>
A benchmark dataset of diurnal- and seasonal-scale radiation, heat and CO2 fluxes in a typical East Asian monsoon region
<p>A benchmark dataset include 30-min meteorology and eddy flux variables at four sites with two typical surface types (i.e., SX-cropland, DT-cropland, XZ-suburb, and DS-suburb) in the Yangtze River Delta of China.<br> SX-cropland: 15 Jul 2015–24 Apr 2019<br> DT-cropland: 1 Dec 2014–30 Nov 2017<br> XZ-suburb: 27 Mar 2014–22 Jan 2017<br> DS-suburb: 16 Apr 2011–1 Jan 2019</p>
Outputs of Numerical experiments verifying the diverse interannual variability of Asian summer monsoon onset process
<p><strong>Introduction</strong></p> <p>We designed two sets of numerical experiments using the Community Earth System Model (CESM 1.2.2) released by NCAR to verify the SSTAs' effect on the interannual modes of ASMOP in April and May. In the atmospheric general circulation model (AGCM) experiments, we solely forced the Community Atmosphere Model version 5.3 (CAM5.3), the atmospheric component of the CESM 1.2.2, by the specific SSTAs in April–May. The AGCM control run included a 40-yr integration forced by the climatological sea surface temperature (SST) with the annual cycle. We attached the specific SSTAs to the climatological SST in each sensitivity experiment and integrated them for 40 years. The ensemble results in the last 30 years were used for analysis. By contrast, in the PACEMAKER experiments, we first integrated the CESM 1.2.2 for 200 years as a control run to exclude the evident climate shift. Afterward, the sensitivity experiments were conducted on the last 100-yr outputs of the control run, in which we nudged the April–May SSTAs in the specific domain but left the rest of the model's coupled climate system free to evolve. The last 30 members were ensembled for analysis in each PACEMAKER experiment. </p> <p><strong>Numerical Experiment Design</strong></p> <p>In the AGCM category, we forced CAM 5.3 by warm SSTAs in the southwestern Indian Ocean (20°S-0°, 40°-80°E) in the ASMOP-PC2 experiment but by cold SSTAs in the western North Pacific (0°-20°N, 120°-160°E) in the ASMOP-PC3 experiment from April to May, respectively. Similar SSTAs were nudged in the two oceanic domains from April to May in the PACEMAKER category.</p> <p><strong>File Description</strong></p> <ol> <li>Output files were saved in the NetCDF format.</li> <li>The "AGCM.tar.gz" and "PACEMAKER.tar.gz" was the compressed files of the atmospheric outputs in May in the AGCM and PACEMAKER experiments, respectively.</li> <li>In each compressed file, the results of the control run (in the subfolder named "Control_Run"), ASMOP-PC2 (in the subfolder named "ASMOP-PC2"), and ASMOP-PC3 (in the subfolder named "ASMOP-PC3") sensitivity experiments were included for comparison.</li> </ol>
Pacific Walker Circulation modulated millennial-scale Asian monsoon rainfall variability over past 40 kyr
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Processed model outputs for "South Asian summer monsoon enhanced by the uplift of Iranian Plateau in Middle Miocene"
<p>This dataset contains processed model outputs from modeling experiments performed in Zuo et al. (2024), including a set of 12 experiment with different CO2 concentrations and topography during the Middle Miocene. Due to space limitations, we provide the summer(JJA) mean climatology data for each experiment and some data that can be used to reproduce the figures in this paper. The raw data can be obtained by contacting the corresponding author.</p> <p><strong><span>Table 1. </span></strong><span>Simulations performed with CESM1.2 in this study.</span></p> <table> <tbody> <tr> <td> <p><span>experiment</span></p> </td> <td> <p><span>Geolography</span></p> </td> <td> <p><span>vegetation</span></p> </td> <td> <p><span>CO2</span></p> <p><span>(ppm)</span></p> </td> <td> <p><span>IP</span></p> </td> <td> <p><span>HM</span></p> </td> </tr> <tr> <td> <p><span>piControl</span></p> </td> <td> <p><span>Modern</span></p> </td> <td> <p><span>Modern</span></p> </td> <td> <p><span>280 </span></p> </td> <td> <p><span>Modern</span></p> </td> <td> <p><span>Modern</span></p> </td> </tr> <tr> <td> <p><span>MMIO</span></p> <p><span>(IP100HM80)</span></p> </td> <td> <p><span>M.Miocene*</span></p> </td> <td> <p><span>M.Miocene</span></p> </td> <td> <p><span>400</span></p> </td> <td> <p><span>M.Miocene</span></p> </td> <td> <p><span>M.Miocene</span></p> </td> </tr> <tr> <td> <p><span>IP0HM0</span></p> </td> <td> <p><span>M.Miocene</span></p> </td> <td> <p><span>M.Miocene</span></p> </td> <td> <p><span>400</span></p> </td> <td> <p><span>0</span></p> </td> <td> <p><span>0</span></p> </td> </tr> <tr> <td> <p><span>IP50HM0</span></p> </td> <td> <p><span>M.Miocene</span></p> </td> <td> <p><span>M.Miocene</span></p> </td> <td> <p><span>400</span></p> </td> <td> <p><span>50%</span></p> </td> <td> <p><span>0</span></p> </td> </tr> <tr> <td> <p><span>IP100HM0</span></p> </td> <td> <p><span>M.Miocene</span></p> </td> <td> <p><span>M. Miocene</span></p> </td> <td> <p><span>400</span></p> </td> <td> <p><span>100%</span></p> </td> <td> <p><span>0</span></p> </td> </tr> <tr> <td> <p><span>IP0HM100</span></p> </td> <td> <p><span>M.Miocene</span></p> </td> <td> <p><span>M.Miocene</span></p> </td> <td> <p><span>400</span></p> </td> <td> <p><span>0</span></p> </td> <td> <p><span>100%**</span></p> </td> </tr> <tr> <td> <p><span>IP50HM100</span></p> </td> <td> <p><span>M.Miocene</span></p> </td> <td> <p><span>M.Miocene</span></p> </td> <td> <p><span>400</span></p> </td> <td> <p><span>50%</span></p> </td> <td> <p><span>100%</span></p> </td> </tr> <tr> <td> <p><span>IP100HM100</span></p> </td> <td> <p><span>M. Miocene</span></p> </td> <td> <p><span>M. Miocene</span></p> </td> <td> <p><span>400</span></p> </td> <td> <p><span>100%</span></p> </td> <td> <p><span>100%</span></p> </td> </tr> <tr> <td> <p><span>MMIO280</span></p> </td> <td> <p><span>M. Miocene</span></p> </td> <td> <p><span>M.Miocene</span></p> </td> <td> <p><span>280</span></p> </td> <td> <p><span>M. Miocene</span></p> </td> <td> <p><span>M.Miocene</span></p> </td> </tr> <tr> <td> <p><span>MMIO560</span></p> </td> <td> <p><span>M. Miocene</span></p> </td> <td> <p><span>M.Miocene</span></p> </td> <td> <p><span>560</span></p> </td> <td> <p><span>M. Miocene</span></p> </td> <td> <p><span>M.Miocene</span></p> </td> </tr> <tr> <td> <p><span>MMIO800</span></p> </td> <td> <p><span>M. Miocene</span></p> </td> <td> <p><span>M.Miocene</span></p> </td> <td> <p><span>800</span></p> </td> <td> <p><span>M. Miocene</span></p> </td> <td> <p><span>M.Miocene</span></p> </td> </tr> <tr> <td> <p><span>MMIO1000</span></p> </td> <td> <p><span>M.Miocene</span></p> </td> <td> <p><span>M.Miocene</span></p> </td> <td> <p><span>1000</span></p> </td> <td> <p><span>M. Miocene</span></p> </td> <td> <p><span>M.Miocene</span></p> </td> </tr> </tbody> </table> <p><span>*M.Miocen</span><span>e</span><span>: Middle Miocene</span></p> <p><span>** 100% of the height of modern HM.</span></p>
Characteristics of Raindrop Size Distribution in Western and Eastern Parts of East Asian Summer Monsoon Rainband
<p>The datasets used in our manuscript are provided here, along with the main code.</p>
Influence of the Southeast Asian mountains on the statistics of monsoon low pressure systems over India
<p>Data used in the letter titled "Influence of the Southeast Asian mountains on the statistics of monsoon low pressure systems over India".</p>
Data for CSJin et al., 2023, PNAS, " Tectonic and orbital forcing of the South Asian monsoon in central Tibet during the late Oligocene"
<p>This zip file contains data presented in the PNAS paper “Tectonic and orbital forcing of the South Asian monsoon in central Tibet during the late Oligocene” by Jin et al., 2023. There are 7 Excel files for Figure 2, 3, 4, S4, S11, S13 and S14 of the paper, respectively.</p>
Precipitation isotope changes over the East Asian monsoon region driven by sea surface temperature during the Last Glacial Maximum
<p>This dataset includes speleothem and ice core proxies used for paper [Lan et al., (2023): Precipitation isotope changes over the East Asian monsoon region driven by sea surface temperature during the Last Glacial Maximum].</p>
Data from: Response of subtropical submarine-cave ecosystem to Holocene cave development and Asian monsoon variability
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Data from: Origins of East Asian Summer Monsoon Seasonality
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Slab Ocean forcing file and model output for "Seasonal Transitions and the Westerly Jet in the Holocene East Asian Summer Monsoon"
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Ice sheet effects to the Asian winter monsoon since the Last Glacial Maximum
<p><strong><em>Modern climate data, surface sediment dataset, <em><strong> Simu</strong></em>lations of TRACE and PMIP3.</em></strong></p>
Dataset for "Impact of Dust Shortwave Absorbability on the East Asian Summer Monsoon"
<p>Dataset for "Impact of Dust Shortwave Absorbability on the East Asian Summer Monsoon"</p>
Data from: Both temperature fluctuations and East Asian monsoons have driven plant diversification in the karst ecosystems from southern China
Karst ecosystems in southern China are species-rich and have high levels of endemism, yet little is known regarding the evolutionary processes responsible for the origin and diversification of karst biodiversity. The genus Primulina (Gesneriaceae) comprises ca. 170 species endemic to southern China with high levels of ecological (edaphic) specialization, providing an exceptional model to study the plant diversification in karsts. We used molecular data from nine chloroplast and 11 nuclear regions and macroevolutionary analyses to assess the origin and cause of species diversification due to paleoenvironmental changes and edaphic specialization in Primulina. We found that speciation was positively associated with changes in past temperatures and East Asian monsoons through the evolutionary history of Primulina. Climatic change around the mid-Miocene triggered an early burst followed by a slowdown of diversification rate towards the present with the climate cooling. We detected different speciation rates among edaphic types, and transitions among soil types were infrequently and did not impact the overall speciation rate. Our findings suggest that both global temperature changes and East Asian monsoons have played crucial roles in floristic diversification within the karst ecosystems in southern China, such that speciation was higher when climate was warmer and wetter. This is the first study to directly demonstrate that past monsoon activity is positively correlated with speciation rate in East Asia. This case study could motivate further investigations to assess the impacts of past environmental changes on the origin and diversification of biodiversity in global karst ecosystems, most of which are under threat.
Dataset for article "Nonlinear Response of Asian Summer Monsoon Precipitation to Emission Reductions in South and East Asia"
<p>Dataset and jupyter notebook relating to the journal article "Nonlinear Response of Asian Summer Monsoon Precipitation to Emission Reductions in South and East Asia".</p> <p>The published paper can be found at <a href="https://doi.org/10.1088/1748-9326/ac3b19">https://doi.org/10.1088/1748-9326/ac3b19</a></p> <p>The dataset includes all model output. The jupyter notebook has all neccessary scripts for plotting the model output and reproducing figures from the article.</p> <p>In order to run the script please update the dataset path name and figure output path at the beginning of the notebook.</p> <p> </p>
Holocene East Asian Summer Monsoon Precipitation Modulated by Zonal Migration of the Asian Westerly Jet Core
<p>Data and associated codes generated in this study are archived here.</p>
SI_Robust Increase in South Asian Monsoon Rainfall Under Global Warming Driven by Southern Ocean Heat Uptake and Eurasia Cloud Changes
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Rapid northwestward extension of the East Asian summer monsoon over the last deglaciation: evidence from mollusk record
<p>The magnitude and rate of spatial expansion of the East Asian summer monsoon (EASM) rain belt as the climate warms remains unclear. Existing assessments still lack the ecological records that are more sensitive to the EASM rainfall to quantify the spatial extension during the past warming scenarios. Here, the spatiotemporal extension of EASM intensity since the last glacial maximum (LGM) is reconstructed using six well-dated mollusk fossil sequences from Chinese loess sections located at the northern part of the EASM. The abundant occurrence of typical dominant mollusk species indicative of EASM intensity gradually delayed from southeast to northwest since the last deglacial warming. The estimated expansion rate of EASM intensity accelerated markedly during the ~12-9 ka (~50 km/ka), which corresponded with the early-Holocene rapid warming period, shifting northwestward ~150 km compared to present. This imply that northern fringe of EASM in northern China will become wetter as the climate warms.</p>
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