Find research datasets worth reusing

opencc-by-4.0May 2022View details →

Insolation and CO2 impacts on the spatial differences of the MIS-9 and MIS-11 climate between monsoonal China and central Asia

The model outputs we use are those performed in Yin & Berger (2012) where the climate of the last nine interglacials were simulated with the LOVECLIM model. The model outputs for MIS-11 and MIS-9 are used here to study the climate conditions in mid and eastern Asia.

opencc-by-4.0May 2022View details →

A benchmark dataset of diurnal- and seasonal-scale radiation, heat and CO2 fluxes in a typical East Asian monsoon region

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. SX-cropland: 15 Jul 2015–24 Apr 2019 DT-cropland: 1 Dec 2014–30 Nov 2017 XZ-suburb: 27 Mar 2014–22 Jan 2017 DS-suburb: 16 Apr 2011–1 Jan 2019

opencc-by-4.0Jul 2022View details →

Aphrodites_daily_mean_temperature_monsoon_Asia

The dataset contains the average temperature over monsoon Asia.

Distribution. Restricted to a small range within the monsoon tropics of N Northern Territory, Australia, with almost all records from Kakadu and Litchfield National Parks. in Muridae

Distribution. Restricted to a small range within the monsoon tropics of N Northern Territory, Australia, with almost all records from Kakadu and Litchfield National Parks.

Distribution. Restricted to the sandstone plateau and escarpment of W Arnhem Land, in monsoonal N Australia. in Muridae

Distribution. Restricted to the sandstone plateau and escarpment of W Arnhem Land, in monsoonal N Australia.

Subspecies and Distribution. P d. delicatulus Gould, 1842 — monsoonal NW & NC Australia, from Pilbara to far NW Queensland, and including the islands of Tent, Augustus, Bigge, Sir Graham Moore, Bathurst, Melville, Marchinbar, Groote Eylandt, and Sir Edward Pellew Group (West, South West, North, and Vanderlin). P. d. pumilus Troughton, 1936 — NE & CE Australia from Cape York S to NE New South Wales, including Fraser I; also reported from Trans Fly plains in S New Guinea. in Muridae

Subspecies and Distribution. P d. delicatulus Gould, 1842 — monsoonal NW & NC Australia, from Pilbara to far NW Queensland, and including the islands of Tent, Augustus, Bigge, Sir Graham Moore, Bathurst, Melville, Marchinbar, Groote Eylandt, and Sir Edward Pellew Group (West, South West, North, and Vanderlin). P. d. pumilus Troughton, 1936 — NE & CE Australia from Cape York S to NE New South Wales, including Fraser I; also reported from Trans Fly plains in S New Guinea.

Distribution. Extensive, but sparse and discontinuous, distribution in monsoonal N Australian mainland, extending S to the Pilbara region; present also on Thevenard I, oft NW Western Australia. Translocated to nearby Serrurier I. in Muridae

Distribution. Extensive, but sparse and discontinuous, distribution in monsoonal N Australian mainland, extending S to the Pilbara region; present also on Thevenard I, oft NW Western Australia. Translocated to nearby Serrurier I.

Distribution. Extends from monsoonal NW Australia through semiarid areas of the mid-Northern Territory to NW Queensland. in Muridae

Distribution. Extends from monsoonal NW Australia through semiarid areas of the mid-Northern Territory to NW Queensland.

opencc-by-4.0Sep 2022View details →

Scientific dataset for the manuscript "Implication of contrasting surface conditions on monsoonal heavy rainfall events over India"

The observational and model simulated data for the Manuscript "Implication of contrasting surface conditions on monsoonal heavy rainfall events over India",  submitted to the Journal of Applied Meteorology and Climatology are shared here. The details of the dataset provided are as follows:  i) IMD daily gridded rainfall (mm) for each heavy rainfall case.  ii) WRF simulated daily average values from Noah and SLAB experiments.  iii) 3-hourly time series of air temperature (K) and specific humidity (kg/kg) at 2m from AWS stations and from model simulations at respective observation locations. These datasets are provided for Case 1 and Case 2 only.  iv) Volumetric soil moisture (m3/m3) daily climatology (2001-2013) averaged over central India from ESA CCI, GLDAS, and LDAS.  v)  The 3-hourly time series of Volumetric soil moisture (m3/m3) average and standard deviations over central India for the period May 15-18, 2013, June 22-25, 2013, and August 15-18, 2013. The average values from GLDAS soil moisture are provided.

dryad32/100

Data from: How do functional traits influence tree demographic properties in a subtropical monsoon forest?

1. Functional traits are good predictors of plant responses and adaptations to ever-changing environments. However, forecasting forest community dynamics is challenging because the relationships among different tree demographic properties (growth, mortality, and recruitment) and how functional traits are associated with tree demography remain largely unknown. 2. Here, in a 20-ha subtropical forest permanent plot, we quantified the rates of tree growth, mortality, and recruitment across 53 dominant tree species (diameter at breast height; DBH ≥ 1 cm) from 2005 to 2020. Functional traits that are closely related to plant photosynthesis, nutrients, hydraulics, and drought tolerance were measured. 3. We found that tree growth rate (GR) varied independently from rates of tree mortality and recruitment. Hydraulic conductivity was positively correlated with GR (explaining 27% variation – the strongest relationship observed) whereas wood density was negatively correlated with GR. Leaf life span was negatively related to tree mortality. Species with high carbon assimilation rate, nutrient concentration and hydraulic conductivity had high recruitment rates. Leaf turgor loss point was unrelated to plant demography. Principal component analysis revealed that species with quick resource-acquisition rates had high rates of growth and recruitment. 4. Our results illustrate that the correlations among tree demographic properties were weak in this subtropical forest with monsoonal climate. Most notably, against expectations there was no observed tradeoff between growth and mortality. Individual functional traits explained up to 27% of each demographic rate. Variation in recruitment rate was aligned with traits indexing the leaf economic spectrum and also plant hydraulic variation. A better understanding of the role of disturbances on trait-demography relationships would help build a deeper and more nuanced understanding of the ecology of subtropical monsoon forests.

opencc-zeroSep 2022View details →

opencc-by-4.0Sep 2022View details →

Outputs of Numerical experiments verifying the diverse interannual variability of Asian summer monsoon onset process

Introduction 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.  Numerical Experiment Design 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. File Description <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>

opencc-by-4.0Sep 2022View details →

Monsoon-regulated marine carbon reservoir effect in the northern South China Sea

ΔR result from east of Hainan Island and Xisha Island, South China Sea

opencc-by-4.0May 2024View details →

Indian summer monsoon variability during the late Quaternary northeastern Arabian Sea

This dataset contains benthic foraminifera abundance and Stable isotope values from northeastern Arabian sea since the 18 cal Kyr BP.

opencc-by-4.0May 2024View details →

Pacific Walker Circulation modulated millennial-scale Asian monsoon rainfall variability over past 40 kyr

Open the record for dataset details and reuse information.

opencc-by-4.0Jun 2024View details →

Processed model outputs for "South Asian summer monsoon enhanced by the uplift of Iranian Plateau in Middle Miocene"

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. Table 1. Simulations performed with CESM1.2 in this study. <table> <tbody> <tr> <td> experiment </td> <td> Geolography </td> <td> vegetation </td> <td> CO2 (ppm) </td> <td> IP </td> <td> HM </td> </tr> <tr> <td> piControl </td> <td> Modern </td> <td> Modern </td> <td> 280 </td> <td> Modern </td> <td> Modern </td> </tr> <tr> <td> MMIO (IP100HM80) </td> <td> M.Miocene* </td> <td> M.Miocene </td> <td> 400 </td> <td> M.Miocene </td> <td> M.Miocene </td> </tr> <tr> <td> IP0HM0 </td> <td> M.Miocene </td> <td> M.Miocene </td> <td> 400 </td> <td> 0 </td> <td> 0 </td> </tr> <tr> <td> IP50HM0 </td> <td> M.Miocene </td> <td> M.Miocene </td> <td> 400 </td> <td> 50% </td> <td> 0 </td> </tr> <tr> <td> IP100HM0 </td> <td> M.Miocene </td> <td> M. Miocene </td> <td> 400 </td> <td> 100% </td> <td> 0 </td> </tr> <tr> <td> IP0HM100 </td> <td> M.Miocene </td> <td> M.Miocene </td> <td> 400 </td> <td> 0 </td> <td> 100%** </td> </tr> <tr> <td> IP50HM100 </td> <td> M.Miocene </td> <td> M.Miocene </td> <td> 400 </td> <td> 50% </td> <td> 100% </td> </tr> <tr> <td> IP100HM100 </td> <td> M. Miocene </td> <td> M. Miocene </td> <td> 400 </td> <td> 100% </td> <td> 100% </td> </tr> <tr> <td> MMIO280 </td> <td> M. Miocene </td> <td> M.Miocene </td> <td> 280 </td> <td> M. Miocene </td> <td> M.Miocene </td> </tr> <tr> <td> MMIO560 </td> <td> M. Miocene </td> <td> M.Miocene </td> <td> 560 </td> <td> M. Miocene </td> <td> M.Miocene </td> </tr> <tr> <td> MMIO800 </td> <td> M. Miocene </td> <td> M.Miocene </td> <td> 800 </td> <td> M. Miocene </td> <td> M.Miocene </td> </tr> <tr> <td> MMIO1000 </td> <td> M.Miocene </td> <td> M.Miocene </td> <td> 1000 </td> <td> M. Miocene </td> <td> M.Miocene </td> </tr> </tbody> </table> *M.Miocene: Middle Miocene ** 100% of the height of modern HM.

FIGURE 14 in Species delimitation in the Gehyra nana (Squamata: Gekkonidae) complex: cryptic and divergent morphological evolution in the Australian Monsoonal Tropics, with the description of four new species

FIGURE 14. Comparison of the subdigital lamellae of G. nana (no additional granules), G. granulum sp. nov. (1 to 3 small granules dividing proximal lamellae, shown in red) and G. spheniscus (small wedge of granules that extends towards tip of digit) (drawing—L. Tedeschi).

FIGURE 1 in Species delimitation in the Gehyra nana (Squamata: Gekkonidae) complex: cryptic and divergent morphological evolution in the Australian Monsoonal Tropics, with the description of four new species

FIGURE 1. Distribution maps of species in the Gehyra nana group. A) Distribution of previously-described species and G. nana as redefined here. The distribution of the G. nana complex is represented in light green and based on over 100 genotyped specimens. For other species, symbols represent genotyped specimens. B) Distribution of the four new species described herein. Dots represent genotyped specimens.

FIGURE 10 in Species delimitation in the Gehyra nana (Squamata: Gekkonidae) complex: cryptic and divergent morphological evolution in the Australian Monsoonal Tropics, with the description of four new species

FIGURE 10. Holotype of Gehyra pseudopunctata sp. nov. (WAM R164776) from Mt Nyulasy, WA, in dorsal, ventral and lateral views (scale bar = 10 mm).

FIGURE 2 in Species delimitation in the Gehyra nana (Squamata: Gekkonidae) complex: cryptic and divergent morphological evolution in the Australian Monsoonal Tropics, with the description of four new species

FIGURE 2. Species tree (from Moritz et al. 2018), obtained using StartBEAST2 of members of the Gehyra nana group. Numbers on the nodes indicate posterior probabilities. Photo credits: P. Doughty, S. Wilson, R.J. Ellis, S. Mahony, H. Cook, B. Maryan, L. Tedeschi.

FIGURE 15 in Species delimitation in the Gehyra nana (Squamata: Gekkonidae) complex: cryptic and divergent morphological evolution in the Australian Monsoonal Tropics, with the description of four new species

FIGURE 15. Holotype of Gehyra pluraporosa sp. nov. (WAM R174024) from King Edward River west, WA, in dorsal, ventral and lateral views (scale bar = 10 mm).