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Dryad

Western North American Temperature Atlas (WNATA)

Cite this dataset

King, Karen et al. (2024). Western North American Temperature Atlas (WNATA) [Dataset]. Dryad. https://doi.org/10.5061/dryad.70rxwdc4v

Abstract

Across western North America (WNA), 20th-21st century anthropogenic warming has increased the prevalence and severity of concurrent drought and heat events, also termed hot droughts. However, the lack of independent spatial reconstructions of both soil moisture and temperatures limits the potential to identify these events in the past and to place them in a long-term context. Here, we develop the Western North American Temperature Atlas (WNATA), a data-independent 0.5° gridded reconstruction of summer maximum temperatures back to the 16th century. Our evaluation of the WNATA with existing hydroclimate reconstructions reveals an increasing association between maximum temperature and drought severity in recent decades, relative to the past five centuries. The synthesis of these paleo-reconstructions indicates that the amplification of the modern WNA megadrought by increased temperatures, and the frequency and spatial extent of compound hot and dry conditions in the 21st century are likely unprecedented since at least 1553 CE.

README: Western North American Temperature Atlas

https://doi.org/10.5061/dryad.70rxwdc4v

0.5° spatial field reconstruction of summer (June-August) average maximum temperatures for western North America, spanning 1553-2020 CE and based on tree ring density and blue intensity measurements.

Description of the data and file structure

The data consists of 3029 grid point reconstructions of summer average maximum temperatures. In the Excel file, rows 1 and 2 are the Latitude/Longitude coordinates for each reconstruction. Rows 3-470 are the annual reconstruction estimates. Estimates are displayed as z-scores, relative to the period 1553-2020 CE.

Methods

The Western North American Temperature Atlas (WNATA), a 0.5° gridded reconstruction for western North America, was created using a nested, ensemble principal components regression approach, where a network of tree ring density and blue intensity chronologies were used as predictors to reconstruct June–August average maximum surface temperatures. The predicted climate data was CRU TS land 4.06 June–August maximum temperature data.  For the first of three total reconstruction nests, we calibrated and validated each of the 3029 grid point reconstructions over the period 1901-1980 CE (the common period shared between the instrumental temperature data and all tree-ring predictors in the WNATA network). We used a split calibration/verification approach, where we calibrated over the period spanning 1941-1980 CE and verified on the period spanning 1901-1940 CE. We repeated this approach for the remaining two forward nests: 1901-1990 CE and 1901-2000 CE. The verification period remained constant, but the calibration period varied for each nest (1941-1980; 1941-1990; 1941-2000 CE). For each reconstruction nest, we applied eight weights to each of the selected tree-ring predictors based on their correlations with temperature, resulting in a 24-member ensemble. 

Funding

National Science Foundation, Award: BCS-2012482

National Science Foundation, Award: AGS-1803995

National Science Foundation, Award: BCS-1759629

Lamont-Doherty Earth Observatory, Postdoctoral Research Fellowship