1. Check the Data
  2. Get the Data
  3. Clean the Data
  4. Data Timespan
  5. Names of Tropical Cyclones in 2015
  6. Get Tropical Cyclones by Name

Category 1

Check the Data

During the upload part of the tutorial, you may have checked if all the data were present. The following WarpScript™ basically does the same thing but goes further by testing both wind speed and pressure GTSs.

Try this WarpScript™.

Get the Data

Enough checks, we want to look at the data! Here we select the data of all tropical cyclones during January 2015. There also a visualization module integrated in WarpStudio so we can really look at it.

Try this WarpScript™.

Clean the Data

If you look closely at the data from the previous script, you may see that there are invalid values. Usually these are wind speeds or pressures at 0 but we want to make sure all the data is in a valid range: wind speeds strictly more than 0 kt and pressure between 800 and 1100 mb. All other values should be discarded.

Try this WarpScript™.

Data Timespan

The sample of the IBTrACS data we propose covers 2010 to 2015, included. For the following analysis, we want to make sure of the actual bounds of the data. We go for the brute force method and fetch all the data to compute them. This is OK because we work on a small dataset, but for true data we should go for another method.

Try this WarpScript™.

Names of Tropical Cyclones in 2015

Hurricane names follow a strict procedure but what about tropical cyclones in general? We can get all the names for 2015. You can compare this list to the one on Wikipedia.

Try this WarpScript™

Get Tropical Cyclones by Name

Until now, we fetched data based on the type of measurement and time window. It is also possible to select GTSs according to the labels or the values. Here we fetch tropical cyclones by name, thus on the attributes of the GTSs.

Try this WarpScript™

NEXT: Category 1