A conceptual prediction model for seasonal drought processes using atmospheric and oceanic standardized anomalies: application to regional drought processes in China

Liu, Zhenchen; Lu, Guihua; He, Hai; Wu, Zhiyong; He, Jian

doi:https://doi.org/10.5194/hess-22-529-2018

Articles | Volume 22, issue 1

https://doi.org/10.5194/hess-22-529-2018

© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 3.0 License.

Special issue:

Sub-seasonal to seasonal hydrological forecasting

https://doi.org/10.5194/hess-22-529-2018

© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 3.0 License.

Articles | Volume 22, issue 1

Research article

|

22 Jan 2018

Research article |

| 22 Jan 2018

A conceptual prediction model for seasonal drought processes using atmospheric and oceanic standardized anomalies: application to regional drought processes in China

Zhenchen Liu, Guihua Lu, Hai He, Zhiyong Wu, and Jian He

Supplement

https://doi.org/10.5194/hess-22-529-2018-supplement

Data sets

Precipitation data Climate Data Centre (CDC) http://data.cma.cn/data/detail/dataCode/SURF_CLI_CHN_PRE_DAY_GRID_0.5.html

The NCEP/NCAR 40-year reanalysis project E. Kalnay et al. https://doi.org/10.1175/1520-0477(1996)077<0437:tnyrp>2.0.co;2

Daily high-resolution-blended analyses for sea surface temperature R. W. Reynolds et al. https://doi.org/10.1175/2007jcli1824.1

The NCEP Climate Forecast System Version 2 S. Saha et al. https://doi.org/10.1175/JCLI-D-12-00823.1

Reforecast and forecast datasets National Oceanic and Atmospheric Administration (NOAA) https://nomads.ncdc.noaa.gov/modeldata/

Short summary

Process prediction of seasonal drought is the goal of our study. We developed a drought prediction model based on atmospheric–oceanic anomalies. It is essentially the synchronous statistical relationship between atmospheric–oceanic anomalies and precipitation anomalies, forced by seasonal climate forecast models. It can predict seasonal drought development very well, despite its weakness in drought severity.