Hossein Hashemi
Researcher
Bias correction of 20 years of IMERG satellite precipitation data over Canada and Alaska
Author
Summary, in English
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.
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.
Department/s
- Division of Water Resources Engineering
- LTH Profile Area: Water
- MECW: The Middle East in the Contemporary World
- Centre for Advanced Middle Eastern Studies (CMES)
Publishing year
2023-04-18
Language
English
Publication/Series
Journal of Hydrology: Regional Studies
Volume
47
Document type
Journal article
Publisher
Elsevier
Topic
- Meteorology and Atmospheric Sciences
- Climate Research
Status
Published
ISBN/ISSN/Other
- ISSN: 2214-5818