Version 1
: Received: 5 December 2023 / Approved: 6 December 2023 / Online: 6 December 2023 (08:16:21 CET)
How to cite:
Carrillo, C.M.; Muñoz-Arriola, F.; Chen, L. Multi-scale Sources of Precipitation Predictability in the Northern Great Plains. Preprints2023, 2023120362. https://doi.org/10.20944/preprints202312.0362.v1
Carrillo, C.M.; Muñoz-Arriola, F.; Chen, L. Multi-scale Sources of Precipitation Predictability in the Northern Great Plains. Preprints 2023, 2023120362. https://doi.org/10.20944/preprints202312.0362.v1
Carrillo, C.M.; Muñoz-Arriola, F.; Chen, L. Multi-scale Sources of Precipitation Predictability in the Northern Great Plains. Preprints2023, 2023120362. https://doi.org/10.20944/preprints202312.0362.v1
APA Style
Carrillo, C.M., Muñoz-Arriola, F., & Chen, L. (2023). Multi-scale Sources of Precipitation Predictability in the Northern Great Plains. Preprints. https://doi.org/10.20944/preprints202312.0362.v1
Chicago/Turabian Style
Carrillo, C.M., Francisco Muñoz-Arriola and Liang Chen. 2023 "Multi-scale Sources of Precipitation Predictability in the Northern Great Plains" Preprints. https://doi.org/10.20944/preprints202312.0362.v1
Abstract
This study leverages the relationships between the Great Plains low-level jet (GP-LLJ) and the circumglobal teleconnection (CGT) to enhance the 30-day rainfall forecast skill in the Northern Great Plains (NGP). The assessment of 30-day simulated precipitation using the Climate Forecast System (CFS) is contrasted with the North American Regional Reanalysis, searching for sources of precipitation predictability associated with extended wet and drought events. We analyze the 30-day sources of precipitation predictability using (1) the characterization of dominant statistical modes of variability of 900-mb winds associated with the GP-LLJ, (2) the large-scale atmospheric patterns based on 200-mb geopotential height (HGT), and (3) the use of GP-LLJ and CGT conditional probability distributions using a continuous correlation threshold approach to identify when and where the forecast of NGP precipitation occurs. Two factors contributing to the predictability of precipitation in the NGP are documented. We found that multi-scale geospatial interactions occur at the daily and sub-seasonal time windows. The CFS reforecast suggests that the ability to forecast sub-seasonal precipitation increases in response to the enhanced simulation of the GP-LLJ and CGT. Finally, the multi-dimensional analysis of covariance reveals that high-precipitation forecasting skill is associated with a better prognostic of GP-LLJ and CGT.
Environmental and Earth Sciences, Atmospheric Science and Meteorology
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
