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80-year meteorological record and drought indices for Sequoia National Park and Sequoia National Monument, CA

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NIAID Data Ecosystem2026-04-30 收录
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https://figshare.com/articles/dataset/80-year_meteorological_record_and_drought_indices_for_Sequoia_National_Park_and_Sequoia_National_Monument_CA/27010234
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The data presented contain on-site and modeled PRISM (Parameter-elevation Regressions on Independent Slopes Model) meteorological data, as well as five drought indices parameterized with these two sources of meteorology. Data are provided for three sites, from October 1933 through September 2020, on the western slope of the southern Sierra Nevada, California and identified by the closest geographical name place: Marble Fork Kaweah River (Lodgepole, CA, Sequoia National Park), Stony Creek (Stony Creek Campground, Sequoia National Monument), and Huckleberry Meadow (near Crescent Meadow, Sequoia National Park). The meteorological data include daily precipitation sum and mean air temperature. Monthly PET (potential evapotranspiration) derived from the Thornthwaite equation, and annual hydrological year (October 1 through September 30) SPEI (Standardized Precipitation and Evapotranspiration Index), AI (Aridity Index), PDSI (Palmer Drought Severity Index), PHDI (Palmer Hydrological Drought Index), and scPDSI (self-calibrating PDSI) are also given as parameterized from on-site and modeled meteorological data. Drought indices (DIs) are relied upon for monitoring and evaluating drought severity relevant to ecological systems, and down-stream agricultural, industrial, and domestic users. The application of these data was to evaluate the performance of five commonly used DIs (SPEI, AI, PDSI, scPDSI, PHDI) in a complex, upland landscape in the Sierra Nevada in a separate analysis (Kim et al. 2022). Correlation coefficients between different parameterizations of DIs (on-site vs. modeled meteorology) on the one hand, and streamflow and remotely-sensed stand normalized difference vegetation index (NDVI) on the other hand were used as relative measures of DI performance. A model was developed to predict tree basal area increment (BAI) within each of three stands using on-site or modeled meteorological parameterizations of DIs, along with biological co-factors (tree vigor, tree to tree competition). The significance and proportion of variance explained by on-site or modeled meteorological parameterizations of DI within the context of the co-factors were also used to evaluate DI performance. For more information about this study and these data, see Kim et al. (2022). These data were published on 02/24/2022. On 10/24/2024, minor metadata updates were made.
创建时间:
2022-01-02
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