National Oceanic and Atmospheric Administration, Climate Variability and Predictability (CVP) Program
A Nudging and Ensemble Forecasting Approach to Identify and Correct
Tropical Pacific Bias-Producing Processes in CESM
Arthur J. Miller and Aneesh Subramanian
Award: ~$499,000
Duration: 2014-2017
Project Summary.
Current short-term tropical climate forecasts (e.g, of the Madden Julian Oscillation (MJO) and
of El Niñouthern Oscillation (ENSO) events) experience both a systematic error (climate
drift) that results in sustained biases of the model tropical climatology and an error in
representing the space-time scales of the transients (e.g., phase speed errors, etc.) We propose
to identify the physical mechanisms that lead to the seasonal biases in the tropical Pacific by
isolating the parameters and parameterizations that influence the development of biases in
short-term climate forecasts. Our overarching scientific objective is to identify, explain, and
correct the climate biases in the Pacific ocean that occur in the Community Earth System
Model (CESM). We are currently using the Community Atmospheric Model (CAM3) in MJO
forecast experiments and tests of convective parameterization improvements. We propose to
extend these MJO forecast studies to include (a) the fully coupled CESM system, and (b)
ENSO timescale forecasts.
We plan to study the spatiotemporal structures of bias development in CESM forecasts,
launched from numerous initial states and during which random ENSO and MJO events
occur, to determine the relative importance of poor mean-state representation versus the
integrated impacts of the transient flows. This bias development will be studied as a function
of season to account for significant changes in the background state of the coupled oceanatmosphere
system in the tropical Pacific. We will also seek to ascribe these effects to wellknown
physical processes for the specific climate modes of variability. We will test the
sensitivity of the bias development to changes in coupled model resolution and model
parameter selection. We will also implement nudging experiments (towards observations) to
pinpoint where the worst parts of the biases develop apart from the nudged variables.
We expect this research to result in identification of the physical processes that lead to the
mean biases in the model system and an improvement in parameterizations used in CESM and
CAM for forecasts of the climate-scale processes in the tropical Pacific.
This proposal contributes to the CVP component of the NOAA ESS Program by attempting to
improve our understanding of the processes contributing to tropical Pacific biases in global
climate models (CESM, in this case). Specifically, our work involves (i) short-term forecast
experiments, from weeks to a year, to isolate the time scales of bias development and the
responsible processes, (ii) development of metrics for coupled GCMs that help to elucidate the
main processes contributing to biases, (iii) atmosphere-only and ocean-only models to isolate the
sources and amplifiers of biases, and (iv) intercomparison of model parameterizations within
CESM. Our overall research will thereby contribute significantly to NOAA.s Next Generation
Strategic Plan by improving our scientific understanding of the climate system that will result in
better identifying potential climate impacts.