The Remarkable Ocean Correlations to Temperature and Moisture of New Mexico
Our forecasts are tethered to the remarkable correlations of some ocean indexes to key features of climate and weather. Accordingly we routinely exam shifts and patterns in ocean indexes via correlation analyses.
Pictured here are two correlation coefficient (CC) contour sets (all for data cast as 10 year trailing averages). For each set a CC of 0.6 or higher is of particular interest. Moreover a CC of 0.8 or 0.9 is especially noteworthy, since a CC of 1.0 indicates perfect correlation. The 0.9 CC contour peak shown in the red contour set, compares the Atlantic Multidecadal Oscillation (AMO) to regional raw temperature values over our current study domain. The green 0.8 CC contour peak is the set which matches the Pacific Decadal Oscillation (PDO) to regional streamflow values over the same general study domain.
The image suggests that New Mexico hosts two of the premier ocean index connections (PDO and AMO) for two of the premier climate variables (Moisture and Temperature). This is a pattern which has previously been suggested by the work of our colleague Dr. Petr Chylek. If borne out, New Mexico might soon be recognized as one of the more extraordinary climate connection locations on our planet.
Finally, this leading image is an excerpt from subscriber content. The subscriber content covers more area and more CC sets, including additional ocean drivers (such as ENSO), and captures our accelerating breakthroughs in high fidelity hydrologic forecasting.* Those breakthroughs include the effective use of these correlations and others to produce high accuracy forecasts even in areas where both the PDO and AMO correlations are relatively low, including portions of the West Coast of the US.
*MW&A applies our unique approach, grounded in best stochastic hydrologic practices, in producing these forecasts, and in analyzing past forecasts and forecasts by others. MW&A makes no further representations on forecast performance or accuracy. Buyers are cautioned and advised to treat all hydroclimatologic forecasts as exercises which although based on quantifiable data, are nonetheless subject to extensive uncertainty.
We strive to ensure that our forecasts are quantitative, transparent, and traceable. For example, we don’t simply claim that an area will get wetter or drier. We also produce quantitative estimates.
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