# Patterns of Arctic Tundra Greenness Based on Spatially Downscaled Solar-Induced Fluorescence
## 1 Introduction  
Since the early 1980s, increased vegetation productivity or greening of Arctic tundra has been deduced from the trend of using the satellite-derived normalized difference vegetation index (NDVI) [1; 2; 3; 4]. For example, [PERSON], et al. [3] found the seasonal amplitude of the NDVI increased by 8% from 1982-1990 at 65\({}^{\circ}\) N and higher latitudes. Arctic tundra greening was also observed or simulated at the circumpolar Arctic region [5; 6; 7; 8], Eurasian Arctic [9; 10; 11], Alaska [2; 12; 13], and Canada [14]. It is speculated that a positive NDVI trend may be in response to climate warming or reduced snow cover, which would lead to the expansion of vegetation in the tundra [15; 16; 17; 18; 19], changing phenological periods [20; 21], increased biomass [22; 23], and surface water variation associated with thermokarst [24]. Since 2011, regional surface browning trends have been observed that have reversed the direction of the Arctic greening trend after nearly 33 years [4; 5; 25; 26]. If such a change in the greenness trend corresponds to the decline in carbon uptake capacity or vegetation productivity via photosynthesis, then most ecosystem models have not considered this shift [26]. Therefore, it is important to understand which parts of the Arctic region are most sensitive and show the greatest browning [4].  
Until now, the circumpolar pattern of greening is derived from satellite-based NDVIs, such as the Advanced Very High Resolution Radiometer (AVHRR), Moderate Resolution Imaging Spectroradiometer (MODIS), Satellite Pour I'Observation de la Terre VEGETATION (SPOT-VGT), Sea-viewing Wide Field-of-view Sensor (SeaWiFS) and Landsat [2; 3; 5; 26; 27]. However, the dataproducts generated by these platforms are limited to a coarser spectral resolution that may affect a better understanding of greening and browning trends. To date, no published studies have examined the spatiotemporal pattern of the circumpolar Arctic tundra greenness trend using satellite data with a finer spectral resolution (such as passive solar-induced chlorophyll fluorescence (SIF)).  
Compared to the NDVI, which is related to the fraction of photosynthetically active radiation (fAPAR), SIF is a more direct proxy for photosynthesis and can be obtained from satellite-based observations [28; 29]. Although the NDVI has been shown to be related to photosynthesis [30], there are intrinsic limitations in the effectiveness of the NDVI due to the difference between potential and actual photosynthesis [31]. SIF is emitted with light absorption from the chlorophyll complex during photosynthesis under natural sunlight [32; 33], shares the same origin with non-photochemical quenching (NPQ) and photochemical quenching (PQ) [34], is intimately related to carbon assimilation, and has been considered as a direct indicator of photosynthesis [35; 36]. The NDVI is related to potential photosynthesis and SIF is related to actual photosynthesis [31]. To improve the spatial resolution of SIF data, [PERSON] and [PERSON] [37] developed a method to spatially disaggregate the information of each coarse SIF pixel, and spatially downscaled SIF data were obtained with a higher spatial resolution (0.05 degree, approximately 5 km). Spatially downscaled SIF data can be considered as a proxy for gross primary production (GPP) [37]. The NDVI has a robust relationship with the vegetation productivity of the circumpolar Arctic tundra [26; 38]. Here, we suppose that greenness can be indicated by the NDVI and SIF data, respectively.  
This research aims to investigate and analyze the spatiotemporal patterns of Arctic tundra greenness (2007-2013) using spatially downscaled SIF data in conjunction with two NDVI products. The eddy-covariance (EC) flux measurements (GPP) were used for the greenness trend comparison.