Bias correction of 20 years of IMERG satellite precipitation data over Canada and Alaska
Lober, Carolyn ; Fayne, Jessica ; Hashemi, Hossein LU
and Smith, Laurence
(2023)
In Journal of Hydrology: Regional Studies
47.
- Abstract
- Study region
We define two northern study areas: one covering all of Canada and Alaska and a second, smaller subregion surrounding the Peace-Athabasca Delta for testing.
Study focus
This study aims to use bias correction to improve satellite precipitation data over a relatively data-sparse high latitude region using a network of in-situ rain gauges. We evaluate the satellite data and derive a linear bias-elevation relationship and apply the correction with a digital elevation model at a monthly scale, and further disaggregate it to produce corrected data at a daily scale.
New hydrological insights for the region
We find that the underestimation in the satellite data increases linearly with increasing... (More) - Study region
We define two northern study areas: one covering all of Canada and Alaska and a second, smaller subregion surrounding the Peace-Athabasca Delta for testing.
Study focus
This study aims to use bias correction to improve satellite precipitation data over a relatively data-sparse high latitude region using a network of in-situ rain gauges. We evaluate the satellite data and derive a linear bias-elevation relationship and apply the correction with a digital elevation model at a monthly scale, and further disaggregate it to produce corrected data at a daily scale.
New hydrological insights for the region
We find that the underestimation in the satellite data increases linearly with increasing elevation, above 500 m a.s.l. at the continental scale and for all elevations at the regional scale. Bias also varies seasonally, with higher bias in summer and lower bias in winter. Compared with uncalibrated data, the monthly continental correction reduces absolute bias by 16% and the root mean squared error by 6%, while the daily continental correction improves absolute bias by 17% but degrades root mean squared error slightly by 2%. We conclude that applying elevation-based bias correction reduces systematic elevational bias in northern high-latitude satellite precipitation data. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/76cde591-bd86-4944-a919-29628f037049
- author
- Lober, Carolyn
; Fayne, Jessica
; Hashemi, Hossein
LU
and Smith, Laurence
- organization
- publishing date
- 2023-04-18
- type
- Contribution to journal
- publication status
- published
- subject
- in
- Journal of Hydrology: Regional Studies
- volume
- 47
- article number
- 101386
- publisher
- Elsevier
- external identifiers
-
- scopus:85152746307
- ISSN
- 2214-5818
- DOI
- 10.1016/j.ejrh.2023.101386
- language
- English
- LU publication?
- yes
- id
- 76cde591-bd86-4944-a919-29628f037049
- date added to LUP
- 2023-05-25 15:40:51
- date last changed
- 2023-10-10 12:13:13
@article{76cde591-bd86-4944-a919-29628f037049,
abstract = {{Study region<br/>We define two northern study areas: one covering all of Canada and Alaska and a second, smaller subregion surrounding the Peace-Athabasca Delta for testing.<br/><br/>Study focus<br/>This study aims to use bias correction to improve satellite precipitation data over a relatively data-sparse high latitude region using a network of in-situ rain gauges. We evaluate the satellite data and derive a linear bias-elevation relationship and apply the correction with a digital elevation model at a monthly scale, and further disaggregate it to produce corrected data at a daily scale.<br/><br/>New hydrological insights for the region<br/>We find that the underestimation in the satellite data increases linearly with increasing elevation, above 500 m a.s.l. at the continental scale and for all elevations at the regional scale. Bias also varies seasonally, with higher bias in summer and lower bias in winter. Compared with uncalibrated data, the monthly continental correction reduces absolute bias by 16% and the root mean squared error by 6%, while the daily continental correction improves absolute bias by 17% but degrades root mean squared error slightly by 2%. We conclude that applying elevation-based bias correction reduces systematic elevational bias in northern high-latitude satellite precipitation data.}},
author = {{Lober, Carolyn and Fayne, Jessica and Hashemi, Hossein and Smith, Laurence}},
issn = {{2214-5818}},
language = {{eng}},
month = {{04}},
publisher = {{Elsevier}},
series = {{Journal of Hydrology: Regional Studies}},
title = {{Bias correction of 20 years of IMERG satellite precipitation data over Canada and Alaska}},
url = {{http://dx.doi.org/10.1016/j.ejrh.2023.101386}},
doi = {{10.1016/j.ejrh.2023.101386}},
volume = {{47}},
year = {{2023}},
}