Track dataset of Indian monsoon low-pressure systems in Subseasonal-to-Seasonal prediction models, ERA-Interim and MERRA-2 reanalysis datasets

This dataset contains tracks and intensities of Indian monsoon low-pressure systems (LPSs), as identified in all ensemble members of eleven models of the Subseasonal-to-Seasonal (S2S) prediction project during a common reforecast period of May–October 1999–2010. Track details of LPSs identified in the ERA-Interim and MERRA-2 reanalysis datasets during June–September 1999–2010. The temporal resolution of all S2S models is daily (0000 UTC), whereas that of ERA-Interim and MERRA-2 are six-hourly and three-hourly respectively. LPSs were tracked using a feature-tracking algorithm (Hunt et al., 2016; 2018), which is based on identifying and linking track points featuring 850 hPa relative vorticity maximum. Non-LPSs (e.g., heat lows) were eliminated from the dataset using a temperature-pressure filter. A full description of S2S models used in the dataset, and the tracking as well as post-tracking process is described in the paper: https://doi.org/10.1175/WAF-D-20-0081.1

Files: 

       1. S2S models 

• bom_lps: contains track details of LPSs identified in all ensemble members of the Bureau of Meteorology model
• cma_lps: contains track details of LPSs identified in all ensemble members of the China Meteorological Administration model
• cnrm_lps: contains track details of LPSs identified in all ensemble members of the Météo France/Centre National de Recherche Meteorologiques model
• eccc_lps: contains track details of LPSs identified in all ensemble members of the Environment and Climate Change Canada model
• ecmwf_lps: contains track details of LPSs identified in all ensemble members of the European Centre for Medium-Range Weather Forecasts model
• hmcr_lps: contains track details of LPSs identified in all ensemble members of the Hydrometeorological Centre of Russia model
• isac-cnr_lps: contains track details of LPSs identified in all ensemble members of the Institute of Atmospheric Sciences and Climate of the National Research Council model 
• jma_lps: contains track details of LPSs identified in all ensemble members of the Japan Meteorological Agency model
• kma_lps: contains track details of LPSs identified in all ensemble members of the Korea Meteorological Administration model
• ncep_lps: contains track details of LPSs identified in all ensemble members of the National Centers for Environmental Prediction model
• ukmo_lps: contains track details of LPSs identified in all ensemble members of the UK Met Office model

       Columns: 

• candidate_id: a random identity number for each LPS
• hindcast: the reforecast date of a hindcast file from which an LPS was identified
• lat: the latitude of an LPS at a given time step
• lon: the longitude of an LPS at a given time step
• lead: the forecast lead time, calculated as the difference between the LPS date and reforecast date of the hindcast from which it was identified
• time: a time stamp showing when an LPS was present 
• vort: the 850 hPa relative vorticity at the centre of an LPS at a given time step
• member: the ensemble member from which an LPS was identified; the control run is indicated by a zero (0) 

      2. Reanalysis datasets 

• era-interim_lps: contains track details of LPSs identified in the ERA-Interim reanalysis dataset. 
• merra-2_lps: contains track details of LPSs identified in the MERRA-2 reanalysis dataset. 

       Columns: 

• time: a time stamp showing when an LPS was present
• lon: the longitude of an LPS at a given time step
• lat: the latitude of an LPS at a given time step
• candidate_id: a random identity number for each LPS  
• vort: the 850 hPa relative vorticity at the centre of an LPS at a given time step

For further details, contact Akshay Deoras (deorasakshay@gmail.com).