Multidecadal Variation in the Seasonal Predictability of Winter PNA and Its Sources
Authors/Creators
- 1. Key Laboratory of Marine Hazards Forecasting, Ministry of Natural Resources, Hohai University, Nanjing, China; College of Oceanography, Hohai University, Nanjing, China
- 2. College of Oceanography, Hohai University, Nanjing, China; Environmental Science and Engineering, University of North British Columbia, Prince George, Canada
- 3. Key Laboratory of Marine Hazards Forecasting, Ministry of Natural Resources, Hohai University, Nanjing, China; College of Oceanography, Hohai University, Nanjing, China; State Key Laboratory of Satellite Ocean Environment Dynamics, Second Institute of Oceanography, Ministry of Natural Resources, Hangzhou, China
- 4. State Key Laboratory of Satellite Ocean Environment Dynamics, Second Institute of Oceanography, Ministry of Natural Resources, Hangzhou, China; Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, China
Description
This directory contain the climate indices from CESM ensemble hindcasts during period 1900-2014 that are used for a manuscript ("Multidecadal Variation in the Seasonal Predictability of Winter PNA and Its Sources") submitted for Geophysical Research Letters.
Description:
The PNA index is defined by using the pointwise method , i.e., a linear combination of the normalized 500 hPa geopotential height anomalies (Z) at the four active centers: PNA = 1/4[Z(20°N, 160°W) – Z (45°N, 165°W) + Z (55°N, 115°W) – Z (30°N, 85°W)].The predicted seasonal mean PNA index is calculated based on the CESM monthly mean 500 hPa geopotential height prediction in December, January and February (DJF), i.e., with a 2-month lead time. The ensemble mean PNA index is the mean of 20 ensemble seasonal mean PNA indices.
The predicted seasonal mean Niño 3.4 index is calculated as the area average of SSTA in the domain of 170°W-120°W, 5°S-5°N based on the CESM monthly mean SST in December, January and February (DJF), i.e., with a 2-month lead time. The linear signal of global warming is filtered out from the SSTA. The ensemble mean Niño index is the mean of 20 ensemble seasonal mean Niño 3.4 indices.
The predicted seasonal mean PDO index is calculated as the time series associated with the first leading empirical orthogonal function (EOF) pattern of the winter mean (DJF) North Pacific SSTA (north of 20°N) based on the CESM monthly mean SST in December, January and February (DJF), i.e., with a 2-month lead time. The linear signal of global warming is filtered out from the SSTA. The ensemble mean PDO index is the mean of 20 ensemble seasonal mean PDO indices.