Robert Jnglin Wills

Climate Scientist, University of Washington
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Low-Frequency Component Analysis (LFCA)

Low-frequency component analysis (LFCA) is a method that transforms the leading empirical orthogonal functions (EOFs) of a data set in order to identify a pattern with the maximum ratio of low-frequency to total variance (based on application of a lowpass filter). The resulting low-frequency patterns (LFPs) and low-frequency components (LFCs) isolate low-frequency climate variability and are useful in diagnosing the corresponding mechanisms. This method is presented in Wills et al. (2018, GRL). Matlab and Python code for LFCA is available on GitHub:


Wills, R.C., T. Schneider, J.M. Wallace, D.S. Battisti, and D.L. Hartmann, 2018: Disentangling global warming, multidecadal variability, and El Niño in Pacific temperatures. Geophysical Research Letters, 45, doi:10.1002/2017GL076327. [PDF] [SI] [Official version]


Forced-Pattern Filtering (FP Filtering)

Forced-pattern filtering is a method to identify spatial patterns (linear combinations of empirical orthogonal functions (EOFs)) with the maximum ratio of signal to noise (with signal defined as variance that is agreed upon across an ensemble). The resulting forced patterns (FPs) isolate the patterns of forced change within climate model ensembles (where each simulation is subject to the same external forcing). This method is presented in Wills et al. (2020, J. Climate, in review). Matlab code for FP filtering is available on GitHub: Python code coming soon.


Wills, R.C.J., D.S. Battisti, K.C. Armour, T. Schneider, and C. Deser, 2020: Pattern recognition methods to separate forced responses from internal variability in climate model ensembles and observations, submitted to Journal of Climate. [PDF] [SI]


Idealized GCM

I have made extensive use of an idealized general circulation model (GCM) based on the dynamical core from NOAA's Geophysical Fluid Dynamics Laboratory (GFDL) Flexible Modeling System (FMS), in particular the moist atmospheric model version coupled to a slab ocean. I have also made (small) contributions to its continued development. A detailed description of the idealized GCM is available here: The code is available on GitHub: