Addendum to: Scientific Data https://doi.org/10.1038/s41597-019-0068-8, published online 16 May 2019
The original dataset1 provides spatialised climatological values of the annual and monthly Optimal Integration Times (OPT) for Lagrangian Studies of Atmospheric Moisture Sources and Sinks for the period 1980–2015. The data provide more appropriate times in days to use in Lagrangian approaches for estimating the precipitation in terrestrial target regions from the moisture transported from its sources of humidity; enabling to make a distinction between precipitation originating from global terrestrial and oceanic sources2.
The database provided in the original version (Version 1) can be used for general climatological studies, but has inherent limitations to higher precision analysis for any particular month. To provide a more widespread temporal coverage as required for some studies, the updated second version (Version 2) of the dataset has been calculated month-by-month for the longest period available in ERA-Interim reanalysis, from 1980 to 2018. To achieve the new individual monthly dataset, the method is the same as described in Nieto & Gimeno2 but it is here adjusted to each individual month along the study period (468 months). Here we present a complete dataset with a spatial resolution of 0.25º × 0.25º in latitude and longitude.
References
Nieto, R. & Gimeno, L. P. Optimal Integration Times for Lagrangian Studies of Atmospheric Moisture Sources and Sinks. Zenodo, https://doi.org/10.5281/zenodo.1453842 (2018).
Nieto, R. & Gimeno, L. A database of optimal integration times for Lagrangian studies of atmospheric moisture sources and sinks. Scientific Data 6, 1–10, https://doi.org/10.1038/s41597-019-0068-8 (2019).
Nieto, R. & Gimeno, L. P. Optimal Integration Times for Lagrangian Studies of Atmospheric Moisture Sources and Sinks. Zenodo https://doi.org/10.5281/zenodo.4550857 (2021).
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Nieto, R., Gimeno, L. Addendum: A database of optimal integration times for Lagrangian studies of atmospheric moisture sources and sinks. Sci Data 8, 130 (2021). https://doi.org/10.1038/s41597-021-00902-1
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DOI: https://doi.org/10.1038/s41597-021-00902-1