Climate-driven phenological changes in the Russian Arctic derived from MODIS LAI time series 2000–2019

N V Shabanov,W G Rees,O V Tutubalina,G J Marshall,S A Bartalev,E I Golubeva

doi:10.1088/1748-9326/ac0be2

Abstract

Arctic surface temperature has increased at approximately twice the global rate over the past few decades and is also projected to warm most in the 21st century. However, the mechanism of Arctic vegetation response to this warming remains largely uncertain. Here, we analyse variations in the seasonal profiles of MODerate resolution Imaging Spectroradiometer Leaf Area Index (LAI) and ERA-interim cumulative near-Surface Air Temperature (SATΣ) over the northern Russia, north of 60° N for 2000–2019. We find that commonly used broad temporal interval (seasonal) trends cannot fully represent complex interannual variations of the LAI profile over the growing season. A sequence of narrow temporal interval (weekly) LAI trends form an inverted S-shape over the course of the growing season with enhanced green-up and senescence, but balanced during the growing season’s peak. Spatial patterns of weekly LAI trends match with those of weekly SATΣ trends during the green-up, while the drivers of the browning trends during senescence remain unclear. Geographically the area with the statistically significant temperature-driven enhanced green-up is restricted by a large patch carrying significant positive SATΣ trends, which includes North Siberian Lowland, Taimyr, Yamal and adjacent territories. The strength, duration and timing of the changes depend on vegetation type: enhanced green-up is most pronounced in tundra, while enhanced senescence is pronounced in forests. Continued release of the climatic constraints will likely increase the capacity both of the environment (i.e. permafrost thawing) and vegetation (i.e. appearance of more productive woody species), and transform LAI seasonal shifts to change of LAI seasonal amplitude.

Highlights

The ‘greening trend’, an increase of green biomass in response to the warming at northern high latitudes over the past 40 years, has been analysed in many studies at global and regional scales
We note that the spatial distribution of LAIMAX trends in this study is consistent with those obtained using the NASA MODerate resolution Imaging Spectroradiometer (MODIS) NDVI product for 2000–2016 (Elsakov 2017)
Applying the new methodology to high accuracy data, this research has quantified a major mechanism of vegetation greenness changes over the Russian Arctic during the past 20 years of the 21st century

Summary

Introduction

The ‘greening trend’, an increase of green biomass in response to the warming at northern high latitudes (north of 40◦ N) over the past 40 years, has been analysed in many studies at global and regional scales. Confirmation at the regional to global scale will require estimates based on moderateresolution remote sensing data and these remain largely uncertain These uncertainties arise because the solution of the complex monitoring task (i.e. due to persistent cloudiness, short growing season, sparse vegetation vulnerable to rapidly changing weather) (Stow et al 2004, Wang et al 2018) is attempted in terms of standard data processing and analysis techniques (i.e. the use of radiometric proxies for biophysical parameters, broad temporal interval (seasonal) averages and spatial aggregation), significantly limiting potential of modern remote sensing data sets (Berner et al 2020, Myers-Smith et al 2020)

Objectives

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Conclusion