Long-Term Climate Evolution Research Using Rescued Historical Weather Observations and Modern Records

Dear Colleagues,

Understanding climate evolution, through climate variability and change studies, remains a major challenge. It is essential to understand past climate behavior, in particular decadal to centennial variability in order to understand how regional and global climate is evolving, to determine how anthropogenic actions have already modified the climate system and to develop prediction tools for near-future and future climate as proposed by the WCRP. Most research, however, has focused on modern climate records readily available, which usually correspond to the last six or seven decades at best. Undetermined lower frequency interdecadal variability, encompassing twenty to fifty or more year periods, can be confused with trends and thus can obscure the real variability and trends.

Reanalyses products with global coverage started in the late 1940s, using the surface observing network and radiosonde records. With the advent of earth observing satellites in the late 1970s and early 1980s, the various institutions generating reanalyses introduce processing changes in their data assimilation to handle the introduction of satellite observations, changes that can impact the reanalyses outputs in that period. Thus, as discussed in the literature, the use of such reanalyses for long-term climate studies since the late 1940s poses some issues regarding the validity of results. Only NCEP 20CR (1836-2015) currently provides reanalyses products obtained only using surface data with standard assimilation procedures throughout the assimilation period. The regional and temporal quality of these 20th century reanalyses depends on the availability of extended observational records.

Surface weather observations began in Italy during the 17th century thanks to Galileo and Torricelli. A number of locations in Europe started regular daily/sub-daily observations by the mid-1700s. Weather observations were increasingly carried out around the globe during the 19th century by amateurs, scientists, and engineers. With the creation of the International Meteorological Organization (IMO, precursor of WMO) in 1873, well-defined station requirements and observation procedures were established. Regular weather and ocean monitoring from naval units was also promoted by the British Royal Navy and adopted by other navies and shipping/whaling companies. Thus, there are vast amounts of weather and climate records available globally, most of which are currently at risk of being lost. Data Rescue (DR) projects such as ACRE (Atmospheric Circulation Reconstructions over the Earth) have been promoting national and regional DR efforts and data digitization. WMOs Centennial Station Program recognizes observing stations in continuous operations for at least 100 years and fosters both the protection of centennial weather records and the continuity whenever possible of such weather stations.

In recent years, while there are a number of publications considering data quality and homogeneity issues in single and merged records, there have been few studies published using such rescued and homogenized data, appropriately merged with present day surface records, focusing on understanding climate variability and changes on centennial/historic timescales. Their results are nevertheless very relevant to understand local/regional climate variability on interannual to interdecadal timescales, estimate trends, assess mechanisms driving such variability, and thus better determine how climate change is evolving. As climate and weather DR efforts make relevant progress, it is now necessary to advance in the climate study of such historic weather records, independently or in combination with more recent observations, exploring all aspects of climate evolution.

The aim of this Special Issue is to explore climate evolution using reconstructed historic data records spanning at least 100 years on a local and/or regional scale around the Earth for the 19th-early 21st century period. Potential topics include, but are not limited to, the following:

1. Linear and non-linear time-series analysis of reconstructed historic data records, focusing on interannual to interdecadal timescales and trends.
2. Climatology of extremes and extreme events in the reconstructed historic records to present. Discussion of extremes behavior under the light of observed variability and trends is highly relevant.
3. Detection of climate shifts/jumps, similar to the 1976/1977 global climate jump, changes in variability, and in trends in the reconstructed data records, after discriminating for perturbations resulting from data merger or impacts of station displacements. It is important to assess in centennial time-series the behavior of trends, in particular whether and when local/regional trends change, as well as their value after adequate filtering of low frequency variability (decadal to interdecadal), which is known to impact trend estimates, in particular when using shorter time-series.
4. Intercomparison of historic data records with currently available 20th century reanalyses products, in particular of variability and trends.
5. Analysis of mechanisms driving the observed variability and change using historic climate indices.
6. The use and evaluation of machine learning for climate variability prediction to assess their interannual to interdecadal variability prediction skills over the period 1980-2020 based on centennial data records prior to 1980.

Submittals considering the use of advanced time-series, space–time analysis, and relevant new statistical tools are welcome.

Dr. Pablo Canziani
Guest Editor

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• climate variability
• climate variability drivers
• extreme events
• centennial time-series analysis
• linear and non-linear time-series analysis
• atmospheric data rescue and use
• decadal to interdecadal variability
• reanalysis validation
• machine learning using centennial time-series