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18 results for “monsoon system”
Monsoon low-pressure-system tracks over South Asia (1979-2019)
<p>Monsoon LPS tracks over South Asia, computed using ERA-Interim reanalysis data.<br> Tracking algorithm described in Hunt and Fletcher (2018) [doi:10.1007/s00382-019-04744-x] and Hunt <em>et al.</em> (2016) [doi:10.1175/MWR-D-15-0138.1].<br> <br> Description of fields:<br> <em>point_id</em>: unique integer identifier for each point<br> <em>time</em>: string with format DD/MM/YY HH:MM, denoting time of detected track point<br> <em>lon</em>: longitude of detected track point<br> <em>lat</em>: latitude of detected track point<br> <em>track_id</em>: unique integer identifier for each track (constituting a group of points)<br> <em>vort</em>: relative vorticity at 850 hPa for the given point (units: s<sup>-1</sup>)<br> <em>circulation</em>: vorticity integrated over the blob of positive vorticity containing the track point (units: arb)<br> <em>eccentricity</em>: eccentricity of the vorticity blob containing the track point<br> <em>category</em>: integer from 0-6 denoting the category of the LPS at the given point, approximately matching IMD criteria. 0: low-pressure area, 1: deep low-pressure area, 2: depression, 3: deep depression, 4: cyclonic storm, 5: severe cyclonic storm, 6: very severe cyclonic storm (and above).</p>
Tracks of Indian Summer monsoon Low-Pressure Systems from ERA5
<p>This repository contains the codes and dataset as explained below:</p> <p>1) This dataset contains downstream and in situ LPS tracks over the Bay of Bengal (BoB) classified using the algorithm developed by Srujan et al. (2021) from 1979-2017 using the ERA5 reanalysis dataset. The LPS are tracked from mean sea level pressure (MSLP) using the algorithm developed by Praveen et al. (2015).</p> <p>2) This also contains Principal components (PCs) of Rossby filtered OLR. </p> <p>3) The code to compute Transfer Entropy between PC1 of Rossby filtered OLR over West Pacific region and MSLP anomaly over BoB. </p> <p><strong>References:</strong></p> <p>Praveen, V., Sandeep, S., & Ajayamohan, R. S. (2015). <strong>On the relationship between mean monsoon precipitation and low pressure systems in climate model simulations</strong>. <em>Journal of Climate</em>, <em>28</em>(13), 5305-5324.</p> <p>Srujan, K. S. S. S., Sandeep, S., & Suhas, E. (2021). <strong>Downstream and In Situ Genesis of Monsoon Low‐Pressure Systems in Climate Models</strong>. <em>Earth and Space Science</em>, <em>8</em>(9), e2021EA001741.</p>
Tracks of Indian Summer monsoon Low-Pressure Systems from ERA5
<p>This repository contains the codes and dataset as explained below:</p> <p>1) This dataset contains downstream and in situ LPS tracks over the Bay of Bengal (BoB) classified using the algorithm developed by Srujan et al. (2021) from 1979-2017 using the ERA5 reanalysis dataset. The LPS are tracked from mean sea level pressure (MSLP) using the algorithm developed by Praveen et al. (2015).</p> <p>2) This also contains Principal components (PCs) of Rossby filtered OLR. </p> <p>3) The code to compute Transfer Entropy between PC1 of Rossby filtered OLR over West Pacific region and MSLP anomaly over BoB. </p> <p>4) Codes and data to perform Kolmogorov Smirnov (KS) test.</p> <p><strong>References:</strong></p> <p>Praveen, V., Sandeep, S., & Ajayamohan, R. S. (2015). <strong>On the relationship between mean monsoon precipitation and low pressure systems in climate model simulations</strong>. <em>Journal of Climate</em>, <em>28</em>(13), 5305-5324.</p> <p>Srujan, K. S. S. S., Sandeep, S., & Suhas, E. (2021). <strong>Downstream and In Situ Genesis of Monsoon Low‐Pressure Systems in Climate Models</strong>. <em>Earth and Space Science</em>, <em>8</em>(9), e2021EA001741.</p>
The North American Monsoon Climate System and its influence on Ponderosa pine water use and water use efficiency
All data in this package are presented as used in Strange et al. (2023). Earlywood (EW) and Latewood (LW) isotope chronologies are presented in the delta (d) notation relative to Vienna Peedee Belemnite (VPDB) standards. Further details regarding data collection, processing, α-cellulose extraction, etc. can be found in the Global Change Biology manuscript associated with these data.
Indian Summer monsoon Low-Pressure Systems Dataset from ERA5
<p>This dataset contains downstream and in situ LPS genesis dates and their location over the Bay of Bengal classified using the algorithm developed by Srujan et al. (2021) from 1979-2017 using the ERA5 reanalysis dataset. The LPS are tracked from mean sea level pressure using the algorithm developed by Praveen et al. (2015).</p> <p><strong>References:</strong></p> <p>Praveen, V., Sandeep, S., & Ajayamohan, R. S. (2015). <strong>On the relationship between mean monsoon precipitation and low pressure systems in climate model simulations</strong>. <em>Journal of Climate</em>, <em>28</em>(13), 5305-5324.</p> <p>Srujan, K. S. S. S., Sandeep, S., & Suhas, E. (2021). <strong>Downstream and In Situ Genesis of Monsoon Low‐Pressure Systems in Climate Models</strong>. <em>Earth and Space Science</em>, <em>8</em>(9), e2021EA001741.</p>
Monsoon low-pressure system (LPS) tracks in ERA5 over India (1979-2019) with added environmental variables
<p>Derived from the LPS v3.0 dataset (https://doi.org/10.5281/zenodo.7568990). Filtered to monsoon LPSs (majority of track lifetime between June and September), with genesis over the Bay of Bengal and making landfall over India. Temporal resolution also reduced from hourly to six-hourly. This dataset accompanies the paper "Using interpretable gradient-boosted decision-tree ensembles to uncover novel dynamical relationships governing monsoon low-pressure systems" (DOI to follow).</p> <p>Aside from the core variables described in the main LPS dataset (linked above), this version includes a large number of environmental variables, listed below. All are computed from ERA5 unless otherwise stated, "<em>mean</em>" means that the variable is computed as an average within 400 km of the LPS centre, "<em>mcz</em>" means that the variable is computed as an average in the box [75-85°E, 18.5-27°N].<br> <em>mean_u200</em>: 200 hPa zonal wind (m s<sup>-1</sup>)<br> <em>mean_u850</em>: 850 hPa zonal wind (m s<sup>-1</sup>)<br> <em>mean_skt</em>: surface temperature (K)<br> <em>mean_land_frac</em>: fraction of area within 400 km that is over land<br> <em>mcz_tcwv</em>: mean total column water vapour over monsoon trough (kg m<sup>-2</sup>)<br> <em>vortex_depth</em>: mean_vort_500 x mean_vort_700/mean_vort_850<sup>2</sup><br> <em>over_land</em>: flag for LPS centre (Boolean)<br> <em>dvo850_dt</em>: rate of change of mean_vort_850 (10<sup>-5</sup> s<sup>-1</sup> day<sup>-1</sup>) <br> <em>acc_land_time</em>: accumulated time where over_land = True (hours)<br> <em>total_land_time</em>: final value of acc_land_time} for a given LPS (hours)<br> <em>qshear_850</em>: meridional shear of 850 hPa specific humidity over India (m<sup>3</sup> m<sup>-3</sup> (°)<sup>-1</sup>)<br> <em>ushear_850</em>: meridional shear of 850 hPa zonal wind over India (m s<sup>-1</sup> (°)<sup>-1</sup>)<br> <em>mean_cape</em>: CAPE (J kg<sup>-1</sup>)<br> <em>mcz_cape</em>: mean CAPE over the monsoon trough (J kg<sup>-1</sup>)<br> <em>mean_dthetae_dp_900_750</em>: d(theta_e)/dp between 900 and 750 hPa, a measurement of atmospheric stability (K hPa<sup>-1</sup>)<br> <em>mean_dthetae_dp_750_500</em>: d(theta_e)/dp between 750 and 500 hPa, a measurement of atmospheric stability (K hPa<sup>-1</sup>)<br> <em>mean_land_skt</em>: land surface temperature (K; NaN over ocean)<br> <em>mean_sst</em>: sea surface temperature (K; NaN over land)<br> <em>mean_swvl1</em>: soil moisture in the top layer (m<sup>3</sup> m<sup>-3</sup>; <7 cm; NaN over ocean)<br> <em>mean_swvl2</em>: soil moisture in the second layer (m<sup>3</sup> m<sup>-3</sup>; 7-28 cm; NaN over ocean)<br> <em>mean_swvl1_grad</em>: mean absolute horizontal gradient of mean_swvl1 (m<sup>3</sup> m<sup>-4</sup>)<br> <em>mean_swvl2_grad</em>: mean absolute horizontal gradient of mean_swvl2 (m<sup>3</sup> m<sup>-4</sup>)<br> <em>olr_90</em>: 90th percentile of negative OLR (i.e. ~90th percentile of cloud top height) (W m<sup>-2</sup>)<br> <em>olr_75</em>: 75th percentile of negative OLR (W m<sup>-2</sup>)<br> <em>olr_50</em>: 50th percentile of negative OLR (W m<sup>-2</sup>)<br> <em>qshear_850_background</em>: qshear\_850 averaged over the previous ten days (m<sup>3</sup> m<sup>-3</sup> (°)<sup>-1</sup>)<br> <em>ushear_850_background</em>: ushear\_850 averaged over the previous ten days (m<sup>3</sup> s<sup>-1</sup> (°)<sup>-1</sup>)<br> <em>mean_q_850</em>: 850 hPa specific humidity (m<sup>3</sup> m<sup>-3</sup>)<br> <em>orography_height</em>: elevation of land surface under LPS centre (m)<br> <em>peak_vorticity</em>: largest value of mean_vort_850} attained by a given LPS (10<sup>-5</sup> s<sup>-1</sup>)<br> <em>reached_peak</em>: False if peak\_vorticity has not been reached yet, else True<br> <em>mean_prcp_400</em>: mean precipitation rate within 400 km of the LPS centre over the next six hours (kg m<sup>-2</sup> s<sup>-1</sup>)<br> <em>mean_prcp_800</em>: mean precipitation rate within 800 km of the LPS centre over the next six hours (kg m<sup>-2</sup> s<sup>-1</sup>)<br> <em>max_prcp_400</em>: maximum precipitation rate within 400 km of the LPS centre over the next six hours (kg m<sup>-2</sup> s<sup>-1</sup>)<br> <em>max_prcp_800</em>: maximum precipitation rate within 800 km of the LPS centre over the next six hours (kg m<sup>-2</sup> s<sup>-1</sup>)<br> <em>mean_vimfd_400</em>: vertically integrated moisture flux convergence (kg m<sup>-2</sup> s<sup>-1</sup>)<br> <em>mean_v200</em>: 200 hPa meridional wind speed (m s<sup>-1</sup>)<br> <em>mean_v500</em>: 500 hPa meridional wind speed (m s<sup>-1</sup>)<br> <em>mean_v850</em>: 850 hPa meridional wind speed (m s<sup>-1</sup>)<br> <em>mean_u500</em>: 500 hPa zonal wind speed (m s<sup>-1</sup>)<br> <em>zonal_speed</em>: zonal (x) component of LPS propagation velocity (m s<sup>-1</sup>)<br> <em>merid_speed</em>: meridional (y) component of LPS propagation velocity (m s<sup>-1</sup>)<br> <em>mean_prcp_imerg</em>: as mean_prcp_400 but computed using IMERG data, rather than ERA5 (kg m<sup>-2</sup> hr<sup>-1</sup>)</p> <p> </p> <p>qshear_850, ushear_850 and their backgrounds are averaged over 5° longitude either side of the LPS centre, with the gradient computed between 10°N and 27°N, reflecting the moisture and zonal wind gradients across the monsoon region.</p>
Monsoon Mission Coupled Forecast System Version 2.0: Model Description and Indian Monsoon Simulations Figures
<p>Monsoon Mission Coupled Forecast System Version 2.0: Model Description and Indian Monsoon Simulations Figures</p>
Data from: Fossil amphibian offers insights into the interplay between monsoons and amphibian evolution in paleoequatorial Late Triassic systems
Open the record for dataset details and reuse information.
Global track dataset of monsoon low pressure systems
<p>This dataset contains the tracks and intensities of low pressure system (LPS) in the global tropics (35ºS-35ºN), as identified in five atmospheric reanalyses (ERA5, ERA-Interim, JRA55, MERRA2, and CFSR) using the algorithm described in the paper titled <strong>Assessing historical variability of South Asian monsoon lows and depressions with an optimized tracking algorithm</strong>. Tracking of LPS was performed using an automated Lagrangian pointwise feature tracker, TempestExtremes (Ullrich & Zarzycki, 2017), with criteria chosen to best match a subjectively analyzed LPS dataset while minimizing disagreement between four atmospheric reanalyses. A full description of the algorithm and dataset is described in the preprint *(<a href="https://doi.org/10.1029/2020JD032977">https://doi.org/10.1029/2020JD032977</a>)</p> <p> </p> <p><strong>Files:</strong></p> <ul> <li><em><strong>Header.txt</strong>: contains the names of columns of the LPS dataset files</em></li> <li><em><strong>LPS_Global_ERA5.dat</strong>: LPS track file for ERA5, 1979-2019, hourly resolution</em></li> <li><em><strong>LPS_Global_ERA-Interim.dat</strong>: LPS track file for ERA-Interim, 1979-2018, six-hourly resolution</em></li> <li><em><strong>LPS_Global_JRA55.dat</strong>: LPS track file for JRA55, 1958-2019, six-hourly resolution</em></li> <li><em><strong>LPS_Global_CFSR.dat</strong>: LPS track file for CFSR, 1979-2010, six-hourly resolution</em></li> <li><em><strong>LPS_Global_MERRA2.dat</strong>: LPS track file for MERRA2, 1980-2019, three-hourly resolution</em></li> </ul> <p><strong><em>Extented Data for ERA5:</em></strong></p> <ul> <li><em>ERA5 tracks for 1940-2022 are available on <strong><a href="https://boos.berkeley.edu">https://boos.berkeley.edu</a> </strong>in the "Data & Tools" section.</em></li> </ul> <p><strong>Script:</strong></p> <ul> <li><em><strong>Run_tempest_lps.sh</strong>: TempestExtremes script to track LPS in reanalysis dataset. </em></li> </ul> <p>Additionally, four python scripts are available to subset the dataset:</p> <ol> <li><em><strong>Python_Moist_LPS_heat_low.py</strong>: Python script to create two separate files for moist LPS and heat lows</em></li> <li><em><strong>Python_Low_Depression.py</strong>: Python script to create two separate files for monsoon lows and monsoon depressions</em></li> <li><em><strong>Python_Region.py</strong>: Python script to create a separate file for a region</em></li> <li><em><strong>Python_Season.py</strong>: Python script to create a separate file for a season</em></li> </ol> <p> </p> <ul> <li> </li> </ul> <p>Note: The TempestExtremes software can be obtained from GitHub at <a href="https://github.com/ClimateGlobalChange/tempestextremes">https://github.com/ClimateGlobalChange/tempestextremes</a>.</p> <p>For further details, contact S. Vishnu (<em>vishnuedv@gmail.com</em>) or William R Boos (<em>billboos@alum.mit.edu</em>).</p>
Observed trends in the South Asian monsoon low-pressure systems and rainfall extremes since the late1970s
<p>LPS tracks for the manuscript "Observed trends in the South Asian monsoon low-pressure systems and rainfall extremes since the late1970s"</p>
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>
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>
Figure 4 from: McDonnell AJ, Wetreich HB, Cantley JT, Jobson P, Martine CT (2019) Solanum plastisexum, an enigmatic new bush tomato from the Australian Monsoon Tropics exhibiting breeding system fluidity. PhytoKeys 124: 39-55. https://doi.org/10.3897/phytokeys.124.33526
Figure 4 Map showing geographic distribution of all taxa compared in this study. red points = S.jobsonii, blue points = S.diversiflorum, black points = S.eburneum, pink points = S.watneyi, yellow points = S.succosum and purple asterisk = S.plastisexum. All points are based on specimens databased in the Australasian Virtual Herbarium (https://avh.chah.org.au/) and specimens held at BUPL.
Figure 1 from: McDonnell AJ, Wetreich HB, Cantley JT, Jobson P, Martine CT (2019) Solanum plastisexum, an enigmatic new bush tomato from the Australian Monsoon Tropics exhibiting breeding system fluidity. PhytoKeys 124: 39-55. https://doi.org/10.3897/phytokeys.124.33526
Figure 1 Morphology and the earliest-known herbarium specimen of Solanumplastisexum. A Flowering stem with a single staminate flower in 2016 B Mature fruit C Erect inflorescences bearing staminate flowers in 2018 and D Specimen collected by P. Latz in 1974, held at DNA and annotated by D. Symon with an annotation indicating his confusion about the reproductive morphology of the specimen (male rachis visible above fruit on far left).
Figure 3 from: McDonnell AJ, Wetreich HB, Cantley JT, Jobson P, Martine CT (2019) Solanum plastisexum, an enigmatic new bush tomato from the Australian Monsoon Tropics exhibiting breeding system fluidity. PhytoKeys 124: 39-55. https://doi.org/10.3897/phytokeys.124.33526
Figure 3 Principal components analysis score plot with eigenvalues and the contribution of each PC displayed (left) and loading plot (right) of characters and species in Table 1. Left, red triangles = S.jobsonii, blue circles = S.diversiflorum, black crosses = S.eburneum, pink triangles = S.watneyi, yellow squares = S.succosum and purple asterisks = S.plastisexum. Right, weighted characters labelled and indicated with red arrows. A Seed length B Fruit width C Number of seeds per fruit D Fruit length E Depth of lobing on apical leaves F Depth of lobing on basal leaves G Fruit wall width H Width of basal leaves I Surface area of basal leaves J Calyx lobe length, hermaphrodite flowers K Internode length L Width of apical leaves, M Surface area of apical leaves N Petiole length O Pedicel length in fruit P Corolla diameter, hermaphrodite flowers Q Length of basal leaves R Corolla diameter, male flowers S Length of apical leaves T Plant height U Stem prickle length V Trichome density, abaxial surface of apical leaves W Trichome density, adaxial surface of apical leaves X Calyx lobe length, male flowers. Colours associated with each taxon also used in Figs 2, 3.
Figure 2 from: McDonnell AJ, Wetreich HB, Cantley JT, Jobson P, Martine CT (2019) Solanum plastisexum, an enigmatic new bush tomato from the Australian Monsoon Tropics exhibiting breeding system fluidity. PhytoKeys 124: 39-55. https://doi.org/10.3897/phytokeys.124.33526
Figure 2 Closely related species of andromonoecious bush tomatoes included in this study. ASolanumjobsoniiBS.watneyiCS.succosumDS.plastisexumES.diversiflorum and FS.eburneum. Colours associated with each taxon also used in Figs 3, 4.
Figure 5 from: McDonnell AJ, Wetreich HB, Cantley JT, Jobson P, Martine CT (2019) Solanum plastisexum, an enigmatic new bush tomato from the Australian Monsoon Tropics exhibiting breeding system fluidity. PhytoKeys 124: 39-55. https://doi.org/10.3897/phytokeys.124.33526
Figure 5 Scan of holotype of Solanumplastisexum, held at DNA.
Figure 6 from: McDonnell AJ, Wetreich HB, Cantley JT, Jobson P, Martine CT (2019) Solanum plastisexum, an enigmatic new bush tomato from the Australian Monsoon Tropics exhibiting breeding system fluidity. PhytoKeys 124: 39-55. https://doi.org/10.3897/phytokeys.124.33526
Figure 6 Typical habitat of Solanumplastisexum, taken from the Buchanan Highway.
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