1. Title: 
SC-Earth: A Station-based Serially Complete Earth Dataset from 1950 to 2019

2. Author lists:
Guoqiang Tang, Martyn P. Clark, Simon Michael Papalexiou

3. Contact information:
Guoqiang Tang (guoqiang.tang@usask.ca)
Martyn P. Clark (martyn.clark@usask.ca)

4. Dataset Description:
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 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).

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.

This dataset 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.

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 "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.

Note: tmean and trange stations are not exactly the same because some raw stations only provide mean temperature observations.


5. Citation:
When using this dataset, please cite “Guoqiang Tang, Martyn P. Clark, Simon Michael Papalexiou. (2021). SC-Earth: A Station-based Serially Complete Earth Dataset from 1950 to 2019. Journal of Climate”.
We recommend that dataset users also cite GHCN-D and GSOD which are the input sources of SC-Earth.