The confounding effect of snow cover on assessing spring phenology from space: A new look at trends on the Tibetan Plateau
Creators
- 1. Department of Geosciences and Natural Resource Management, University of Copenhagen, Copenhagen 1350 (Denmark)
- 2. Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101 (China)
- 3. CAS Center for Excellence in Tibetan Plateau Earth Sciences, Beijing 100101 (China)
- 4. Department of Physical Geography and Ecosystems Analysis, Lund University, Lund 22100 (Sweden)
Description
Highlights: • Four satellite indicators are tested to estimate spring phenology trends over the Tibetan Plateau. • The confounding effect of snow cover is evaluated. • The Normalized Difference Phenology Index provides best results for snow conditions. • Normalized Difference Vegetation Index SOS trends are biased by snow trends. The Tibetan Plateau is the highest and largest plateau in the world, hosting unique alpine grassland and having a much higher snow cover than any other region at the same latitude, thus representing a "climate change hot-spot". Land surface phenology characterizes the timing of vegetation seasonality at the per-pixel level using remote sensing systems. The impact of seasonal snow cover variations on land surface phenology has drawn much attention; however, there is still no consensus on how the remote sensing estimated start of season (SOS) is biased by the presence of preseason snow cover. Here, we analyzed SOS assessments from time series of satellite derived vegetation indices and solar-induced chlorophyll fluorescence (SIF) during 2003–2016 for the Tibetan Plateau. We evaluated satellite-based SOS with field observations and gross primary production (GPP) from eddy covariance for both snow-free and snow covered sites. SOS derived from SIF was highly correlated with field data (R2 = 0.83) and also the normalized difference phenology index (NDPI) performed well for both snow free (R2 = 0.77) and snow covered sites (R2 = 0.73). On the contrary, normalized difference vegetation index (NDVI) correlates only weakly with field data (R2 = 0.35 for snow free and R2 = 0.15 for snow covered sites). We further found that an earlier end of the snow season caused an earlier estimate of SOS for the Tibetan Plateau from NDVI as compared to NDPI. Our research therefore adds new evidence to the ongoing debate supporting the view that the claimed advance in land surface SOS over the Tibetan Plateau is an artifact from snow cover changes. These findings improve our understanding of the impact of snow on land surface phenology in alpine ecosystems, which can further improve remote sensing based land surface phenology assessments in snow-influenced ecosystems.
Availability note (English)
Available from http://dx.doi.org/10.1016/j.scitotenv.2020.144011Additional details
Identifiers
- DOI
- 10.1016/j.scitotenv.2020.144011;
- PII
- S0048969720375422;
Publishing Information
- Journal Title
- Science of the Total Environment
- Journal Volume
- 756
- Journal Page Range
- vp.
- ISSN
- 0048-9697
- CODEN
- STENDL
INIS
- Country of Publication
- Netherlands
- Country of Input or Organization
- International Atomic Energy Agency (IAEA)
- INIS RN
- 54063855
- Subject category
- S54: ENVIRONMENTAL SCIENCES;
- Descriptors DEI
- CHLOROPHYLL; FLUORESCENCE; GREENHOUSE EFFECT; PHENOLOGY; RANGELANDS; REMOTE SENSING; SEASONS; SNOW; SURFACES
- Descriptors DEC
- ATMOSPHERIC PRECIPITATIONS; CARBOXYLIC ACIDS; CLIMATIC CHANGE; ECOSYSTEMS; EMISSION; HETEROCYCLIC ACIDS; HETEROCYCLIC COMPOUNDS; LUMINESCENCE; ORGANIC ACIDS; ORGANIC COMPOUNDS; ORGANIC NITROGEN COMPOUNDS; PHOTON EMISSION; PHYTOCHROMES; PIGMENTS; PORPHYRINS; PROTEINS; TERRESTRIAL ECOSYSTEMS
Optional Information
- Copyright
- Copyright (c) 2020 Elsevier B.V. All rights reserved.