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Citation
Udy, D., Vance, T., Kiem, A., Holbrook, N. and Curran, M. (2020) Daily synoptic weather types of southern Indian Ocean: January 1979-October 2018, Ver. 1, Australian Antarctic Data Centre - doi:10.4225/15/58eedf00d78fe, Accessed: 2021-01-19
Title
Daily synoptic weather types of southern Indian Ocean: January 1979-October 2018
Data Centre
Australian Antarctic Data Centre, Australia
DOI
doi:10.4225/15/58eedf00d78fe
Created Date
2020-10-15
Revision Date
2020-11-09
Parent record
None

Description

Daily synoptic typing dataset for the southern Indian Ocean (30°-75°S, 40°-180° E) for the period January 1979 to October 2018 developed using self-organising maps (SOMs).  The nine synoptic types represented by the nodes defined in this study included four meridional (SOM1, SOM2, SOM6 and SOM9), three mixed (SOM4, SOM7 and SOM8), a zonal (SOM3) and a transitional pattern (SOM5).  Refer to Udy et al. Links between large scale modes of climate variability and synoptic weather patterns in the southern Indian Ocean. J.Climate in review.

Included datasets:
SOM_daily_z500_anomaly_3_3.nc includes the composite z500 daily anomaly patterns for each of the 9 SOM nodes - lat, lon, z500 anomaly, node. 

SOM_daily_z500_anomaly_3_3.txt includes the daily 'winning' node between 1st January 1979 and 31st October 2018.  Each day is assigned to a 'winning' node between 1-9.  e.g. 19790101 is assigned to SOM3. 

SOM code: "Kohonen" Package in R https://cran.r-project.org/web/packages/kohonen/index.html

Study domain: 30°-75°S, 40°-180° E

Time step / period: daily / January 1979-October 2018

Input data: ERA-Interim (https://apps.ecmwf.int/datasets/) 500hPa geopotential height (z500) daily anomalies.  Climate Data Operators (CDO) was used to calculate the daily anomaly (https://code.mpimet.mpg.de/projects/cdo/)

SOM algorithm parameters: refer to kohonen documentation for more information.
dist.fcts (performance evaluation distance) = euclidean, grid = rect, neighbourhood function = gaussian, Nodes (number of SOM nodes) = 9, rlen (number of iterations) = 1000, alp (learning rate) = 0.05 to 0.01 and rad (radius) = 4 to 0. 

In the Kohonen R-package, a radius value less than or equal to one corresponds to the point where only the 'winning' node is updated by each iteration, making the SOM algorithm similar to clustering techniques (e.g. k-means).  The SOM algorithm used in this study was a hybrid between SOM/clustering (75% SOM, 25% clustering).

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Purpose

Describe the key synoptic scale weather systems (500hPa geopotential height) of the southern Indian Ocean (30°-75°S, 40°-180° E).

Access

These data are publicly available for download from the provided URL.

Temporal Coverages

Spatial Coverages

Data Resolution

Latitude Resolution:
0.75 Degree(s)
Longitude Resolution:
0.75 Degree(s)

Science Keywords

Additional Keywords

  • ECMWF ERA-INTERIM
  • SELF-ORGANISING MAPS ALGORITHM
  • SYNOPTIC WEATHER PATTERNS
  • SYNOPTIC TYPING
  • SELF-ORGANISING MAPS

Locations

  • OCEAN > INDIAN OCEAN
  • OCEAN > SOUTHERN OCEAN
  • CONTINENT > ANTARCTICA
  • GEOGRAPHIC REGION > POLAR

Platforms

  • MAPS
  • MODELS

Instruments

  • Computer

Researchers

  • udy, danielle (INVESTIGATOR,TECHNICAL CONTACT,DIF AUTHOR)
  • vance, tessa (INVESTIGATOR,TECHNICAL CONTACT)
  • kiem, anthony (INVESTIGATOR,TECHNICAL CONTACT)
  • holbrook, neil (INVESTIGATOR,TECHNICAL CONTACT)
  • curran, mark (INVESTIGATOR,TECHNICAL CONTACT)

Use Constraints

This data set conforms to the CCBY Attribution License (http://creativecommons.org/licenses/by/4.0/).

Please follow instructions listed in the citation reference provided at http://data.aad.gov.au/aadc/metadata/citation.cfm?entry_id=AAS_4537_z500_SynopticTyping_SouthernIndianOcean when using these data.

Creative Commons License