Fetch and process climate and seasonal data

Angus Gray-Weale 2024-10-10

This repository is a work in progress. It has been through limited testing, and requires clearer control of its settings. Email me if you’d like access or information about projects and publications that use this code.

It’s helpful if each batch of data need only be downloaded once, or as few times as possible. It’s also helpful if the same code can download data from multiple sources, and apply the same processing and analysis steps.

This repository contains the open source version of schnauzer. The full schnauzer code downloads, processes, and analyses NCEP, JRA, and ERA5 analyses, as well as GEFS or CFS forecasts. The code will then check the data, regrid as desired, calculate scaled anomalies, and if appropriate obtain a set of principal components for use in further analysis.

This public version demonstrates the download of NCEP analysis data at the surface or on pressure levels, and calculates from these a covariance matrix and principal components (sometimes called EOFs).

Multiweek prediction of the state of the northern hemisphere

Imperfect knowledge of the state of the Earth system, combined with sensitivity to initial state, limits predictions. Useful advanced warning of extreme weather requires multi-week lead times, as do decisions on investments sensitive to energy markets. An original mathematical method, and the design of data structures that describe the Earth System, reduce the computational complexity and make possible multi-week predictions not possible with traditional methods, better even than with supercomputers used by facilities such as NOAA in the USA, the Met. Office in the UK, and the ECMWF in Europe. This new, lightweight method outperforms for variables of critical interest the large scale, computationally expensive, monolithic models that I developed and debugged for the Bureau of Meteorology.

Who is Toby?

Toby is a schnauzer. He will fetch a stick or a ball if you throw it, but if you throw it again he will just look at you. He fetched it for you once! Surely that’s enough? Toby would be good at managing climate and seasonal data. He likes to do a thing once and do it properly.