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Section 1: Overview
Name of Research Project
Related Project
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Part
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Core Modelling and Forecasting Team
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SMFD
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Program Affiliations
Related Research Project(s)
Dataset Title
SC-Earth: A Station-based Serially Complete Earth Dataset from 1950 to 2019
Additional Information
Creators and Contributors
Guoqiang Tang | Point of Contact, Author | guoqiang.tang@usask.ca | University of Saskatchewan |
Martyn Clark | Point of Contact, Author | martyn.clark@usask.ca | University of Saskatchewan |
Simon Papalexiou | Author | | University of Saskatchewan |
Abstract
Meteorological data from ground stations suffer from temporal discontinuities caused by missing values and short measurement periods. Gap filling and reconstruction techniques have proven to be effective in producing serially complete station datasets that are used for a myriad of meteorological applications (e.g., developing gridded meteorological datasets and validating models). We developed the serially complete Earth (SC-Earth) dataset, which provides global station-based daily precipitation, mean temperature, temperature range, dew-point temperature, and wind speed data from 1950 to 2019. SC-Earth utilizes raw station data from the Global Historical Climatology Network-Daily (GHCN-D) and the Global Surface Summary of the Day (GSOD).
The five variables are precipitation (prcp), mean daily temperature (tmean), daily temperature range (trange), dew-point temperature (tdew), and wind speed (wind). Daily minimum and maximum temperature can be inferred from tmean and trange. Humidity variables can be inferred from tdew.
There are three files for each variable. "observation" contains quality controlled raw station observations. "estimate" contains SC-Earth estimates for all days (including days that "observation" has values) by merging estimates from 15 strategies (quantile mapping, interpolation, machine learning, and multiple-strategy merging). "final" is the final SC-Earth output, which uses "estimate" to fill the gap that "observation" is not available.
Purpose
This dataset was created as part of the spatial meteorological forcing data (SMFD) theme of the GWF Core Modelling and Forecasting Team. It is useful for various purposes of applications that require:
(1) Quality-controlled actual station observations;
(2) Station observations without missing values in the observation period;
(3) Serially complete station observations. Users should be cautious when using this dataset for trend analysis because it is possible that trends are not well reconstructed.
Plain Language Summary
Keywords
serially complete dataset |
precipitation |
temperature |
wind speed |
Citations
Tang, G., Clark, M. P., Papalexiou, S. M. (2021). SC-Earth: A Station-based Serially Complete Earth Dataset from 1950 to 2019 [Dataset]. Zenodo.
http://doi.org/10.5281/zenodo.4762585Tang, G., Clark, M. P., Papalexiou, S. M. (2021). SC-Earth: A Station-Based Serially Complete Earth Dataset from 1950 to 2019. Journal of Climate, 34(16), 6493-6511.
https://doi.org/10.1175/JCLI-D-21-0067.1
Section 3: Status and Provenance
Dataset Version
1
Dataset Creation Date
2021-05-17
Status of data collection/production
Dataset Completion or Abandonment Date
2021-05-17
Data Update Frequency
Creation Software
Primary Source of Data
Other Source of Data (if applicable)
Data Lineage (if applicable). Please include versions (e.g., input and forcing data, models, and coupling modules; instrument measurements; surveys; sample collections; etc.)
SC-Earth utilizes raw station data from the Global Historical Climatology Network-Daily (GHCN-D) and the Global Surface Summary of the Day (GSOD).
There are three types of missing values that are infilled/reconstructed by this dataset:
(1) Missing value during the observation period when the station still works.
(2) Missing value beyond the observation period (reconstruction period) before the station is deployed or after the station ceases working.
(3) Station measurements that fail quality control checks are treated as missing values and imputed.
Section 4: Access and Downloads
Access to the Dataset
Terms of Use
Does the data have access restrictions?
Downloading and Characteristics of the Dataset
Download Links and Instructions
Total Size of all Dataset Files (GB)
23.3
File formats and online databases
Other Data Formats (if applicable)
List of Parameters and Variables