Filling Gaps in Hourly Air Temperature Data Using Debiased ERA5 Data
Missing data in hourly and daily temperature data series is a common problem in long-term data series and many observational networks. Agricultural and environmental models and climate-related tools can be used only if weather data series are complete. To support user communities, a technique for ga...
Main Authors: | Miloš Lompar, Branislava Lalić, Ljiljana Dekić, Mina Petrić |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2019-01-01
|
Series: | Atmosphere |
Subjects: | |
Online Access: | http://www.mdpi.com/2073-4433/10/1/13 |
Similar Items
-
Validation of the Gap-fill as an Overall Measure of English Language Proficiency among Iraqi EFL Learners
by: Ahmed Sattar
Published: (2024-06-01) -
Comparison of Cloud-Filling Algorithms for Marine Satellite Data
by: Andy Stock, et al.
Published: (2020-10-01) -
New Gap-Filling Strategies for Long-Period Flux Data Gaps Using a Data-Driven Approach
by: Minseok Kang, et al.
Published: (2019-09-01) -
Using Window Regression to Gap-Fill Landsat ETM+ Post SLC-Off Data
by: Evan B. Brooks, et al.
Published: (2018-09-01) -
Hyper-active gap filling
by: Akira eOmaki, et al.
Published: (2015-04-01)