EGU24-868, updated on 08 Mar 2024
EGU General Assembly 2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

Relationship of the predictability of North Pacific Mode and ENSO with predictability of PDO

Jivesh Dixit and Krishna M. AchutaRao
Jivesh Dixit and Krishna M. AchutaRao
  • Indian Institute of Technology, Delhi (IIT Delhi), Centre for Atmospheric Sciences (CAS), India

PDO and ENSO are most prominent variability modes in the Pacific Ocean at decadal and interannual timescales respectively. Mutual independence between ENSO and PDO is questionable (Chen & Wallace, 2016). Linear combination of the first two orthogonal modes of SST variability in our Study Region (SR; 70oN - 20oS, 110oE - 90oW) i.e. mode 1 (interannual mode, we call it, IAM; ENSO like variability) and mode 2 (North Pacific Mode (NPM; Deser & Blackmon (1995)); a decadal mode) produces a PDO like variability (Chen & Wallace, 2016). It suggests that PDO is not independently hosted in the Pacific Ocean and can be represented by two linearly independent variability modes.

To produce credible and skillful climate information at multi-year to decadal timescales, Decadal Climate Prediction Project (DCPP), led by the Working Group on Subseasonal to Interdecadal Prediction (WGSIP), focuses on both the scientific and practical elements of forecasting climate by employing predictability research and retrospective analyses within the Coupled Model Intercomparison Project Phase 6 (CMIP6). Component A under DCPP experiments concentrates on hindcast experiments to examine the prediction skill of participating models with respect to actual observations.

As linear combination of  IAM and NPM in SR produces PDO pattern and timescales efficiently, we compared the  ability of DCPP-A hindcasts to predict  IAM, NPM, and  PDO. In this analysis we use output from 9 models (a total of 128 ensemble members), initialised every year from 1960 to 2010. To produce the prediction skill estimates.

At lead year 1 from initialisation, the prediction of NPM,  IAM and PDO is quite skillful as the models are initialised with observations. In subsequent years, skill of either IAM or NPM or both drop significantly and that leads to drop in skill of predicted PDO index. Both the deterministic estimates and probabilistic estimates of prediction skill for DCPP hindcast experiments suggest that the ability of hindcast experiments to predict NPM governs the prediction skill to predict PDO index.

Keywords: PDO, ENSO, NPM, CMIP6, DCPP, hindcast


Chen, X., & Wallace, J. M. (2016). Orthogonal PDO and ENSO indices. Journal of Climate, 29(10), 3883–3892.

Deser, C., & Blackmon, M. L. (1995). On the Relationship between Tropical and North Pacific Sea Surface Temperature Variations. Journal of Climate, 8(6), 1677–1680.<1677:OTRBTA>2.0.CO;2

How to cite: Dixit, J. and AchutaRao, K. M.: Relationship of the predictability of North Pacific Mode and ENSO with predictability of PDO, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-868,, 2024.

Comments on the supplementary material

AC: Author Comment | CC: Community Comment | Report abuse

supplementary materials version 1 – uploaded on 12 Apr 2024, no comments