Some Comments on the Reliability of NOAA's Storm Events Database

22 Pages Posted: 23 Jun 2016 Last revised: 24 Jun 2016

See all articles by Renato P dos Santos

Renato P dos Santos

PPGECIM/ULBRA - Lutheran University of Brazil; CIAGE - Centre for Generative Artificial Intelligence in Cognition and Education

Date Written: June 22, 2016

Abstract

Storms and other severe weather events can result in fatalities, injuries, and property damage. Therefore, preventing such outcomes to the extent possible is a key concern, and the scientific community faces an increasing demand for regularly updated appraisals of evolving climate conditions and extreme weather. NOAA's Storm Events Database is undoubtedly an invaluable resource to the general public, to the professional, and to the researcher. Due to such importance, the primary objective of this study was to explore this database and get clues about its reliability. A complete investigation of the damage estimates, injuries or fatalities figures is unfeasible due to the extension of the database. However, an exploratory data analysis with the resources of the R statistical data analysis language found that damage reports are missing in more than half of the records, that part of the damage values are incorrect, and that, despite all efforts of standardizations, non-standard event type names are still finding their way into the database. These few results are enough to demonstrate that the database suffers from incompleteness and inconsistencies and should not be used without taking reservations and appropriate precautions before advancing any inferences from the data.

Keywords: NOAA's Storm Events Database, data governance, Meteorology, data cleaning

JEL Classification: C8, C1

Suggested Citation

P dos Santos, Renato, Some Comments on the Reliability of NOAA's Storm Events Database (June 22, 2016). Available at SSRN: https://ssrn.com/abstract=2799273 or http://dx.doi.org/10.2139/ssrn.2799273

Renato P dos Santos (Contact Author)

PPGECIM/ULBRA - Lutheran University of Brazil ( email )

Av. Farroupilha, 8001
São José
Canoas, RS 92425-900
Brazil
+55 51 3477.9278 (Phone)
+55 51 3477.9239 (Fax)

HOME PAGE: http://www.ulbra.br/ppgecim/

CIAGE - Centre for Generative Artificial Intelligence in Cognition and Education ( email )

Av. Farroupilha, 8001
São José
Canoas, RS 92425-900
Brazil
+55 51 3477.9278 (Phone)
+55 51 3477.9239 (Fax)

HOME PAGE: http://www.ulbra.br/ppgecim/

Do you have negative results from your research you’d like to share?

Paper statistics

Downloads
74
Abstract Views
621
Rank
576,524
PlumX Metrics