{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Identify Patterns in the Coupled Fields of SLP and SST through Canonical Correlation Analysis" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Canonical correlation analysis (CCA) is a widely used multivariate statistical tool to identify the linear relationship between two variates by maximizing the correlation between linear combinations of the variates (Hotelling, 1936; Barnett and Preisendorfer, 1987; Hardoon et al., 2004). Application of canonical correlation analysis has been found in a variety of scientific fields such as meteorology and neuroscience.\n", "\n", "There are two typical purposes of CCA:\n", "1. Data reduction: explain covariation between two sets of variables using small number of linear combinations\n", "2. Data interpretation: find features (i.e., canonical variates) that are important for explaining covariation between sets of variables.\n", "\n", "This notebook applies CCA to real data—the tropical Pacific sea level pressure (SLP) and sea surface temperature (SST) fields—and identify the coupled patterns from the data, including the famous tropical Pacific climate variability known as the El Nin o–Southern Oscillation (ENSO). ENSO has warm El Nino states and cool La Nina states, with changes found not only in the SST but also in the SLP.\n", "\n", "The SLP and SST data are downloaded from http://www.esrl.noaa.gov/psd/gcos_wgsp/Gridded/data.hadslp2.html and http://www.esrl.noaa.gov/psd/thredds/catalog/Datasets/kaplan_sst/catalog.html, respectively." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## 1. Load all needed libraries" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "matplotlib inline\n" ] } ], "source": [ "%matplotlib inline\n", "\n", "import numpy as np\n", "import xarray as xr\n", "from sklearn.decomposition import PCA\n", "from sklearn.cross_decomposition import CCA\n", "import cartopy.crs as ccrs\n", "import datetime as dt\n", "import matplotlib.pyplot as plt\n", "import matplotlib.dates as mdates\n", "import matplotlib.gridspec as gridspec\n", "\n", "plt.rcParams['figure.figsize'] = (15,9)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## 2. Load Data\n", "\n", "Spatial domain: -180W ~ -70W, and 30N ~ -30S\n", "\n", "Period: 1950~2005\n", "\n", "Raw SLP and SST are converted to monthly anomalies" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 2.1 SLP" ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "collapsed": true }, "outputs": [], "source": [ "ds1 = xr.open_dataset('data\\slp.mnmean.hadslp2.nc')\n", "slp = ds1.slp.sel(lat=slice(30, -30), lon=slice(180, 290), time=slice('1950-01-01','2005-12-31'))\n", "lon_slp = ds1.lon.sel(lon=slice(180, 290))\n", "lat_slp = ds1.lat.sel(lat=slice(30, -30))\n", "dates = ds1.time.sel(time=slice('1950-01-01','2005-12-31')).values\n", "\n", "# climatology\n", "#slp_clm = slp.sel(time=slice('1981-01-01','2010-12-31')).groupby('time.month').mean(dim='time')\n", "slp_clm = slp.groupby('time.month').mean(dim='time')\n", "# anomaly\n", "slp_anom = slp.groupby('time.month') - slp_clm" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 2.2 SST" ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "collapsed": true, "scrolled": true }, "outputs": [], "source": [ "ds2 = xr.open_dataset('data\\sst.mon.anom.kaplan.nc')\n", "#sst_anom = ds2.sst.sel(lat=slice(30, -30), lon=slice(180, 290), time=slice('1950-01-01','2004-12-31'))\n", "sst_anom = ds2.sst.sel(lat=slice(-30, 30), lon=slice(180, 290), time=slice('1950-01-01','2005-12-31'))\n", "lat_sst = ds2.lat.sel(lat=slice(-30, 30))\n", "lon_sst = ds2.lon.sel(lon=slice(180, 290))\n", "#lat_sst = ds2.lat.sel(lat=slice(30, -30))\n", "\n", "# climatology\n", "#sst_clm = sst.sel(time=slice('1981-01-01','2010-12-31')).groupby('time.month').mean(dim='time')\n", "#sst_clm = sst.groupby('time.month').mean(dim='time')\n", "# anomaly\n", "#sst_anom = sst.groupby('time.month') - sst_clm" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## 3. Identify coupled patterns between SLP and SST" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 3.1 Preprocess SLP\n", "\n", "Convert anomalies of SLP to 2D array and use PCA to reduce the amount of noise by eliminating the higher EOF modes, which represent poorly organized, small-scale features of the fields. Here 6 PCs are used, explaining 72.8% of variance." ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "0.7289731174475278\n" ] } ], "source": [ "slp2d = slp_anom.values\n", "ntime, nrow_slp, ncol_slp = slp2d.shape\n", "slp2d = np.reshape(slp2d, (ntime, nrow_slp*ncol_slp), order='F')\n", "\n", "pca_slp = PCA(n_components=6)\n", "pca_slp.fit(slp2d)\n", "\n", "slp2d_pcs = pca_slp.inverse_transform(pca_slp.transform(slp2d))\n", "print(pca_slp.explained_variance_ratio_.sum()) " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 3.2 Preprocess SST\n", "\n", "Convert anomalies of SST to 2D array and construct a new array without NaN values. *Keep in mind that both of PCA and CCA in the sklearn package do not support NaN values in their input arrays*.In addition, use PCA to reduce the amount of noise by eliminating the higher EOF modes, which represent poorly organized, small-scale features of the fields. Here 4 PCs are used, explaining 70.1% of variance." ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "0.7013537355888356\n" ] } ], "source": [ "sst2d = sst_anom.values\n", "ntime, nrow_sst, ncol_sst = sst2d.shape\n", "sst2d = np.reshape(sst2d, (ntime, nrow_sst*ncol_sst), order='F')\n", "\n", "nonMissingIndex = np.where(np.isnan(sst2d[0]) == False)[0]\n", "sst2dNoMissing = sst2d[:, nonMissingIndex]\n", "\n", "pca_sst = PCA(n_components=4)\n", "pca_sst.fit(sst2dNoMissing)\n", "sst2d_pcs = pca_sst.inverse_transform(pca_sst.transform(sst2dNoMissing))\n", "print(pca_sst.explained_variance_ratio_.sum()) " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 3.3 Apply CCA to SLP and SST\n", "\n", "To visualize CCA variates in a same plot, they are standardized along the time axis." ] }, { "cell_type": "code", "execution_count": 6, "metadata": { "collapsed": true }, "outputs": [], "source": [ "cca = CCA(n_components=1)\n", "slp_c, sst_c = cca.fit_transform(slp2d_pcs, sst2d_pcs)\n", "\n", "slp_c /= slp_c.std(axis=0)\n", "sst_c /= sst_c.std(axis=0)\n", "\n", "A = cca.x_weights_ \n", "B = cca.y_weights_\n", "A = np.reshape(A, (nrow_slp,ncol_slp), order='F')\n", "\n", "BB = np.ones([nrow_sst*ncol_sst,1]) * np.NaN\n", "BB = BB.astype(B.dtype)\n", "BB[nonMissingIndex,0] = B[:,0]\n", "BB = BB.reshape([nrow_sst,ncol_sst], order='F')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## 4. Visualize\n", "\n", "For comparison, the CCA mode 1 spatial patterns for the SLP and SST are shown in the following figure." ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAAA2wAAAHlCAYAAACJTH9oAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAABJRU5ErkJggg==\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "fig = plt.figure()\n", "gs = gridspec.GridSpec(2, 2)\n", "gs.update(wspace=0.1, hspace=0.15)\n", "levels = np.arange(-0.17, 0.171, 0.01)\n", "\n", "# plot SLP Monthly Anomaly CCA 1\n", "ax1 = fig.add_subplot(gs[0,0], projection=ccrs.PlateCarree())\n", "x1, y1 = np.meshgrid(lon_slp, lat_slp)\n", "cs = ax1.contourf(x1, y1, A,\n", " levels=levels,\n", " transform=ccrs.PlateCarree(),\n", " cmap='RdBu')\n", " \n", "cb=fig.colorbar(cs, ax=ax1, shrink=0.8, aspect=20) \n", "ax1.coastlines()\n", "ax1.set_global()\n", "ax1.set_extent([-180, -70, -19, 19])\n", "ax1.set_title('SLP Monthly Anomaly CCA 1')\n", "\n", "# plot SST Monthly Anomaly CCA 1\n", "ax2 = fig.add_subplot(gs[0,1], projection=ccrs.PlateCarree())\n", "x2, y2 = np.meshgrid(lon_sst, lat_sst)\n", "cs2 = ax2.contourf(x2, y2, BB,\n", " levels=levels, \n", " transform=ccrs.PlateCarree(),\n", " cmap='RdBu')\n", " \n", "cb2=fig.colorbar(cs2, ax=ax2, shrink=0.8, aspect=20)\n", "ax2.coastlines()\n", "ax2.set_global()\n", "ax2.set_extent([-180, -70, -19, 19])\n", "ax2.set_title('SST Monthly Anomaly CCA 1')\n", "\n", "# plot CCA 1 Variates\n", "ax3 = fig.add_subplot(gs[1,:]) \n", "ax3.plot(dates, slp_c[:,0], label='SLP')\n", "ax3.plot(dates, sst_c[:,0], label='SST')\n", "r = np.corrcoef(slp_c[:,0], sst_c[:,0])[0, 1]\n", "ax3.set_title('CCA 1 Variates: R = ' + str(round(r,3)))\n", "ax3.legend()\n", "ax3.set_ylim([-4,4])\n", "\n", "ax3.format_xdata = mdates.DateFormatter('%Y')\n", "#ax3.grid(True)\n", "fig.autofmt_xdate()" ] }, { "cell_type": "markdown", "metadata": { "collapsed": true }, "source": [ "## 5. Summary\n", "\n", "The above figure shows the first CCA mode calculated between the monthly anomaly fields of Sea Surface Pressure (SLP) and Sea Surface Temperature (SST) for the region of the equatorial Pacific. Mode 1 shows the strong large scale coupling between SLP and SST anomalies (e.g. areas with positive CCA values in SLP appear to coincide with negative SST). This is what we would expect of the El Niño Southern Oscillation (ENSO) - High SLP anomalies in the western Pacific is typical of the warm El Niño phase, which results in warmer SST anomalies throughout the equatorial Pacific. The opposite La Niña phase results from low SLP in the western Pacific.\n", "\n", "However, it is worth noting that the aim in standard CCA is to find the linear relationship between the two variables x and y. Therefore, the method fails if the relationship is non-linear. This also is a similar issue for the linear PCA method used as a preprocessing step for CCA. Another disadvantage of the standard CCA is that it is very sensitive to outliers, as it is based on the correlation coefficient. To overcome these limitations, som Nonlinear canonical correlation analysis (NLCCA) methods have been proposed recently. For example, Hsieh (2000, 2001) introduced an NN approach to improve the standard CCA. In an attempt to increase the flexibility of CCA, Kernel CCA can be used to map the data into a high-dimensional space before performing CCA (known as the kernel trick). If the kernel function is nonlinear, kernel CCA can be used to capture nonlinear relationships in the data (Hardoon et al., 2004). \n", "\n", "Deep Canonical Correlation Analysis (DCCA) was proposed by Andrew et al.(2013), which is a method to learn complex nonlinear transformations of two views of data such that the resulting representations are highly linearly correlated. Parameters of both transformations are jointly learned to maximize the (regularized) total correlation. It can be viewed as a nonlinear extension of the linear method canonical correlation analysis (CCA). " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## References\n", "\n", "Allan, R., and T. Ansell, 2006: A New Globally Complete Monthly Historical Gridded Mean Sea Level Pressure Dataset (HadSLP2): 1850-2004. J. Climate, 19, 5816-5842.\n", "\n", "Kaplan, A., M. Cane, Y. Kushnir, A. Clement, M. Blumenthal, and B. Rajagopalan, Analyses of global sea surface temperature 1856-1991, Journal of Geophysical Research, 103, 18,567-18,589, 1998\n", "\n", "Fabian Pedregosa, Gaël Varoquaux, Alexandre Gramfort, Vincent Michel, Bertrand Thirion, Olivier Grisel, Mathieu Blondel, Peter Prettenhofer, Ron Weiss, Vincent Dubourg, Jake Vanderplas, Alexandre Passos, David Cournapeau, Matthieu Brucher, Matthieu Perrot, Édouard Duchesnay. Scikit-learn: Machine Learning in Python, Journal of Machine Learning Research, 12, 2825-2830 (2011)\n", "\n", "Stéfan van der Walt, S. Chris Colbert and Gaël Varoquaux. The NumPy Array: A Structure for Efficient Numerical Computation, Computing in Science & Engineering, 13, 22-30 (2011), DOI:10.1109/MCSE.2011.37\n", "\n", "Fernando Pérez and Brian E. Granger. IPython: A System for Interactive Scientific Computing, Computing in Science & Engineering, 9, 21-29 (2007), DOI:10.1109/MCSE.2007.53\n", "\n", "John D. Hunter. Matplotlib: A 2D Graphics Environment, Computing in Science & Engineering, 9, 90-95 (2007), DOI:10.1109/MCSE.2007.55\n", "\n", "Hoyer, S. & Hamman, J., (2017). xarray: N-D labeled Arrays and Datasets in Python. Journal of Open Research Software. 5(1), p.10. DOI: http://doi.org/10.5334/jors.148\n", "\n", "Barnett, T. P., and R. Preisendorfer, 1987: Origins and levels of monthly and seasonal forecast skill for United States surface air temperatures determined by canonical correlation analysis. Mon. Wea. Rev., 115, 1825–1850\n", "\n", "Harold Hotelling. Relations between two sets of variates. Biometrika, 28(3/4):321–377, 1936.\n", "\n", "David R Hardoon, Sandor Szedmak, and John Shawe-Taylor. Canonical correlation analysis: an overview with application to learning methods. Neural computation, 16(12):2639–2664, December 2004. ISSN 0899-7667. doi: 10.1162/0899766042321814. URL http://www.ncbi.nlm.nih.gov/pubmed/15516276.\n", "\n", "Hsieh, W. W., 2000: Nonlinear canonical correlation analysis by neural networks. Neural Networks, 13, 1095–1105\n", "\n", "Hsieh, W. W. (2001), Nonlinear canonical correlation analysis of the tropical Pacific climate variability using a neural network approach, J. Clim., 14, 2528–2539.\n", "\n", "G. Andrew, R. Arora, J. Bilmes, and K. Livescu. Deep canonical correlation analysis. In ICML, 2013" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": true }, "outputs": [], "source": [] } ], "metadata": { "anaconda-cloud": {}, "kernelspec": { "display_name": "Python [conda root]", "language": "python", "name": "conda-root-py" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 2 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython2", "version": "2.7.12" } }, "nbformat": 4, "nbformat_minor": 2 }