New Berkeley Earth High Resolution Temperature Data Set

Berkeley Earth is premiering a new high resolution analysis of historical instrumental temperatures.

This builds on our existing work on climate reconstruction by adding a simple machine learning layer to our analysis.  This new approach extracts weather patterns from model, satellite, and reanalysis data, and then layers these weather patterns on top of instrumental observations and our existing interpolation methods to produce new high resolution historical temperature fields.  This has quadrupled our output resolution from the previous 1° x 1° lat-long to a new global 0.25° x 0.25° lat-long resolution.  However, this is not simply a downscaling effort.  Firstly, the use of weather patterns derived from physical models and observations increases the spatial realism of the reconstructed fields.  Secondly, observations from regions with high density measurement networks have been directly incorporated into the high resolution field, allowing dense observations to be more fully utilized.  

This new data product uses significantly more observational weather station data and produces higher resolution historical temperature fields than any comparable product, allowing for unprecedented insights into historical local and regional climate change.  In particular, the effect of geographic features such as mountains, coastlines, and ecosystem variations are resolved with a level of detail that was not previously possible.  At the same time, previously established techniques for bias corrections, noise reduction, and error analysis continued to be utilized.  The resulting global field initially spans 1850 to present and will be updated on an ongoing basis.  This project does not significantly change the global understanding of climate change, but helps to provide local detail that was often unresolved previously.  The initial data product focuses on monthly temperatures, though a proposal exists to also create a high resolution daily temperature data set using similar methods.

This talk will describe the construction of the new data set and its characteristics.  The techniques used in this project are accessible enough that they are likely to be useful for other types of instrumental analyses wishing to improve resolution or leverage basic information about weather patterns derived from models or other sources.