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Reanalysis datasets outperform other gridded climate products in vegetation change analysis in peripheral conservation areas of Central Asia

DOI zum Zitieren der Version auf EPub Bayreuth: https://doi.org/10.15495/EPub_UBT_00005345
URN to cite this document: urn:nbn:de:bvb:703-epub-5345-3

Title data

Zandler, Harald ; Senftl, Thomas ; Vanselow, Kim André:
Reanalysis datasets outperform other gridded climate products in vegetation change analysis in peripheral conservation areas of Central Asia.
In: Scientific Reports. Vol. 10 (31 December 2020) . - No. 22446.
ISSN 2045-2322
DOI der Verlagsversion: https://doi.org/10.1038/s41598-020-79480-y

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Project's official titleProject's id
Open Access PublizierenNo information

Project financing: UNDP GEF grant AA/Pj/PIMS: 00076820/0088001/5038
Fondation Segré grant "Transboundary Conservation of Mountain Monarchs in Afghanistan and Pakistan”

Abstract

Global environmental research requires long-term climate data. Yet, meteorological infrastructure is missing in the vast majority of the world’s protected areas. Therefore, gridded products are frequently used as the only available climate data source in peripheral regions. However, associated evaluations are commonly biased towards well observed areas and consequently, station-based datasets. As evaluations on vegetation monitoring abilities are lacking for regions with poor data availability, we analyzed the potential of several state-of-the-art climate datasets (CHIRPS, CRU, ERA5-Land, GPCC-Monitoring-Product, IMERG-GPM, MERRA-2, MODIS-MOD10A1) for assessing NDVI anomalies (MODIS-MOD13Q1) in two particularly suitable remote conservation areas. We calculated anomalies of 156 climate variables and seasonal periods during 2001–2018, correlated these with vegetation anomalies while taking the multiple comparison problem into consideration, and computed their spatial performance to derive suitable parameters. Our results showed that four datasets (MERRA-2, ERA5-Land, MOD10A1, CRU) were suitable for vegetation analysis in both regions, by showing significant correlations controlled at a false discovery rate < 5% and in more than half of the analyzed areas. Cross-validated variable selection and importance assessment based on the Boruta algorithm indicated high importance of the reanalysis datasets ERA5-Land and MERRA-2 in both areas but higher differences and variability between the regions with all other products. CHIRPS, GPCC and the bias-corrected version of MERRA-2 were unsuitable and not important in both regions. We provide evidence that reanalysis datasets are most suitable for spatiotemporally consistent environmental analysis whereas gauge- or satellite-based products and their combinations are highly variable and may not be applicable in peripheral areas.

Further data

Item Type: Article in a journal
Keywords: Climate sciences; Ecology; Environmental sciences
DDC Subjects: 500 Science > 500 Natural sciences
500 Science > 550 Earth sciences, geology
500 Science > 570 Life sciences, biology
900 History and geography > 910 Geography, travel
Institutions of the University: Faculties > Faculty of Biology, Chemistry and Earth Sciences > Department of Earth Sciences > Professor Climatology
Faculties > Faculty of Biology, Chemistry and Earth Sciences > Department of Earth Sciences > Professor Climatology > Professor Climatology - Univ.-Prof. Dr. Cyrus Samimi
Research Institutions > Research Centres > Bayreuth Center of Ecology and Environmental Research- BayCEER
Faculties
Faculties > Faculty of Biology, Chemistry and Earth Sciences
Faculties > Faculty of Biology, Chemistry and Earth Sciences > Department of Earth Sciences
Research Institutions
Research Institutions > Research Centres
Language: English
Originates at UBT: Yes
URN: urn:nbn:de:bvb:703-epub-5345-3
Date Deposited: 19 Mar 2021 09:43
Last Modified: 22 Mar 2021 11:18
URI: https://epub.uni-bayreuth.de/id/eprint/5345

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