Preprints
https://doi.org/10.5194/egusphere-2022-476
https://doi.org/10.5194/egusphere-2022-476
 
02 Aug 2022
02 Aug 2022
Status: this preprint is open for discussion.

Assessing decadal to centennial scale nonstationary variability in meteorological drought trends

Kyungmin Sung1, Max Carl Arne Torbenson2, and James H. Stagge1 Kyungmin Sung et al.
  • 1Civil, Environmental and Geodetics Engineering, The Ohio State University, Columbus, Ohio
  • 2Department of Geography, Johannes Gutenberg Universität, Mainz, Germany

Abstract. There are indications that the reference climatology underlying meteorological drought has shown non-stationarity at seasonal, decadal, and centennial time scales, impacting the interpretation of normalized drought indices and potentially producing serious ecological, economic, and social consequences. Analyzing these trends in the meteorological drought climatology beyond the 100-year observation period contributes to a better understanding of the non-stationary changes, ultimately determining whether they are within the range of natural variability or outside this range. To accomplish this, our study introduces a novel approach to incorporate unevenly scaled tree-ring proxy data (NASPA) with instrumental precipitation datasets by first temporal downscaling the proxy data to produce a regular time series, and then modeling climate non-stationarity while simultaneously correcting model induced bias. This new modeling approach was applied to 14 sites across the continental United States using the 3-month Standardized Precipitation Index (SPI) as a basis. Findings showed locations which have experienced recent rapid shifts towards drier or wetter conditions during the instrumental period compared to the past 1000 years, with drying trends generally in the west and wetting trends in the east. This study also found that seasonal shifts have occurred in some regions recently, with seasonality changes most notable for southern gauges. We expect that our new approach provides a foundation for incorporating various datasets to examine non-stationary variability in long-term precipitation climatology and to confirm the spatial patterns noted here in greater detail.

Kyungmin Sung et al.

Status: open (until 27 Sep 2022)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse

Kyungmin Sung et al.

Kyungmin Sung et al.

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Short summary
This study is aims to analyze seasonal and long-term trend of meteorological drought trends under climate change. We merge tree-ring proxy with instrumental datasets to understand multi-centennial trends. We develop an approach for temporal downscaling from bi-annual time series to monthly scale, and develop a model for bias correction and trend analysis across all datasets. The model was applied to 14 sites in US, and found regions with recent wetting/drying trends and rapid seasonal shifts.