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Solar-induced chlorophyll fluorescence (SIF) brings major advancements in measuring terrestrial photosynthesis. Several recent studies have evaluated the potential of SIF retrievals from the Orbiting Carbon Observatory-2 (OCO-2) in estimating gross primary productivity (GPP) based on GPP data from eddy covariance (EC) flux towers. However, the spatially and temporally sparse nature of OCO-2 data makes it challenging to use these data for many applications from the ecosystem to the global scale. Here, we developed a new global ‘OCO-2’ SIF data set (GOSIF) with high spatial and temporal resolutions (i.e., 0.05°, 8-day) over the period 2000–2017 based on a data-driven approach. The predictive SIF model was developed based on discrete OCO-2 SIF soundings, remote sensing data from the Moderate Resolution Imaging Spectroradiometer (MODIS), and meteorological reanalysis data. Our model performed well in estimating SIF (R2 = 0.79, root mean squared error (RMSE) = 0.07 W m−2 μm−1 sr−1). The model was then used to estimate SIF for each 0.05° × 0.05° grid cell and each 8-day interval for the study period. The resulting GOSIF product has reasonable seasonal cycles, and captures the similar seasonality as both the coarse-resolution OCO-2 SIF (1°), directly aggregated from the discrete OCO-2 soundings, and tower-based GPP. Our SIF estimates are highly correlated with GPP from 91 EC flux sites (R2 = 0.73, p < 0.001). They capture the expected spatial and temporal patterns and also have remarkable ability to highlight the crop areas with the highest daily productivity across the globe. Our product also allows us to examine the long-term trends in SIF globally. Compared with the coarse-resolution SIF that was directly aggregated from OCO-2 soundings, GOSIF has finer spatial resolution, globally continuous coverage, and a much longer record. Our GOSIF product is valuable for assessing terrestrial photosynthesis and ecosystem function, and benchmarking terrestrial biosphere and Earth system models.

Accurately quantifying gross primary production (GPP) globally is critical for assessing plant productivity, carbon balance, and carbon-climate feedbacks, while current GPP estimates exhibit substantial uncertainty. Solar-induced chlorophyll fluorescence (SIF) observed by the Orbiting Carbon Observatory-2 (OCO-2) has offered unprecedented opportunities for monitoring land photosynthesis, while its sparse coverage remains a bottleneck for mapping finer-resolution GPP globally. Here, we used the global, OCO-2-based SIF product (GOSIF) and linear relationships between SIF and GPP to map GPP globally at a 0.05° spatial resolution and 8-day time step for the period from 2000 to 2017. To account for the uncertainty of GPP estimates resulting from the SIF-GPP relationship, we used a total of eight SIF-GPP relationships with different forms (universal and biome-specific, with and without intercept) at both site and grid cell levels to estimate GPP. Our results showed that all of the eight SIF-GPP relationships performed well in estimating GPP globally. The ensemble mean 8-day GPP was generally highly correlated with flux tower GPP for 91 eddy covariance flux sites across the globe (R2 = 0.74, Root Mean Square Error = 1.92 g C m−2 d−1). Our fine-resolution GPP estimates showed reasonable spatial and seasonal variations across the globe and fully captured both seasonal cycles and spatial patterns present in our coarse-resolution (1°) GPP estimates based on coarse-resolution SIF data directly aggregated from discrete OCO-2 soundings. SIF-GPP relationships with different forms could lead to significant differences in annual GPP particularly in the tropics. Our ensemble global annual GPP estimate (135.5 ± 8.8 Pg C yr−1) is between the median estimate of non-process based methods and the median estimate of process-based models. Our GPP estimates showed interannual variability in many regions and exhibited increasing trends in many parts of the globe particularly in the Northern Hemisphere. With the availability of high-quality, gridded SIF observations from space (e.g., TROPOMI, FLEX), our novel approach does not rely on any other input data (e.g., climate data, soil properties) and therefore can map GPP solely based on satellite SIF observations and potentially lead to more accurate GPP estimates at regional to global scales. The use of a universal SIF-GPP relationship versus biome-specific relationships can also avoid the uncertainty associated with land cover maps. Our novel, independent GPP product (GOSIF GPP), freely available at our data repository, will be valuable for studying photosynthesis, carbon cycle, agricultural production, and ecosystem responses to climate change and disturbances, informing ecosystem management, and benchmarking terrestrial biosphere and Earth system models.

Phenology plays a fundamental role in regulating photosynthesis, evapotranspiration, and surface energy fluxes and is sensitive to climate change. The global mean surface air temperature data indicate a global warming hiatus between 1998 and 2012, while its impacts on global phenology remains unclear. Here we use long-term satellite and FLUXNET records to examine phenology trends in the northern hemisphere before and during the warming hiatus. Our results based on the satellite record show that the phenology change rate slowed down during the warming hiatus. The analysis of the long-term FLUXNET measurements, mainly within the warming hiatus, shows that there were no widespread advancing (or delaying) trends in spring (or autumn) phenology. The lack of widespread phenology trends partly led to the lack of widespread trends in spring and autumn carbon fluxes. Our findings have significant implications for understanding the responses of phenology to climate change and the climate-carbon feedbacks. A global warming hiatus occurred during 1998 and 2012 but its effects on phenology are unclear. Here the authors examine the trends in spring and autumn phenology in the northern hemisphere and the effects of the warming hiatus and show that phenology change rate in the northern hemisphere slowed down during the warming hiatus.

Diurnal cycling of plant carbon uptake and water use, and their responses to water and heat stresses, provide direct insight into assessing ecosystem productivity, agricultural production and management practices, carbon and water cycles, and feedbacks to the climate. Temperature, light, atmospheric water demand, soil moisture and leaf water potential vary over the course of the day, leading to diurnal variations in stomatal conductance, photosynthesis and transpiration. Earth observations from polar-orbiting satellites are incapable of studying these diurnal variations. Here, we review the emerging satellite observations that have the potential for studying how plant functioning and ecosystem processes vary over the course of the diurnal cycle. The recently launched ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) and Orbiting Carbon Observatory-3 (OCO-3) provide land surface temperature, evapotranspiration (ET), gross primary production (GPP) and solar-induced chlorophyll fluorescence data at different times of day. New generation operational geostationary satellites such as Himawari-8 and the GOES-R series can provide continuous, high-frequency data of land surface temperature, solar radiation, GPP and ET. Future satellite missions such as GeoCarb, TEMPO and Sentinel-4 are also planned to have diurnal sampling capability of solar-induced chlorophyll fluorescence. We explore the unprecedented opportunities for characterizing and understanding how GPP, ET and water use efficiency vary over the course of the day in response to temperature and water stresses, and management practices. We also envision that these emerging observations will revolutionize studies of plant functioning and ecosystem processes in the context of climate change and that these observations and findings can inform agricultural and forest management and lead to improvements in Earth system models and climate projections.

Heatwave events are expected to become more frequent and intense in the mid-latitudes of the Northern Hemisphere in the future. However, our knowledge of the impacts of these extreme temperature events on ecosystem functions is still limited. We investigated the responses of ecosystem gross primary productivity (GPP) to heatwaves for nine sites encompassing a wide variety of ecosystem types with long-term (i.e., >7 years) flux and meteorological observations at northern mid-latitudes. Our results showed that GPP was depressed during heatwaves for most ecosystems except the C4 sites. The evaporative stress index (ESI) was the primary variable responsible for the changes in GPP during heatwaves across the nine ecosystems. Furthermore, forest ecosystems were more resistant and resilient to heatwaves than other ecosystems. Additionally, the asymmetric diurnal pattern of GPP in forest ecosystems was attributed to xylem refilling and high water storage capacity, indicating that GPP was more sensitive to heatwaves in the afternoon. Interestingly, C4 herbaceous ecosystems could promote canopy stomatal conductance (Gc) for avoiding leaf burn and tissue damage during heatwaves. The herbaceous ecosystems had weaker stomatal control on water loss during heatwaves and were more vulnerable to heatwaves owing to the water stress afterwards. This research highlighted the importance of ecosystem type and plant functional type in determining the responses of photosynthesis to heatwaves. Understanding the post-effect after heatwaves is also vital for comprehensively assessing the impacts of heatwaves on ecosystem functions.

Satellite-derived vegetation indices (VIs) have been widely used to approximate or estimate gross primary productivity (GPP). However, it remains unclear how the VI-GPP relationship varies with indices, biomes, timescales, and the bidirectional reflectance distribution function (BRDF) effect. We examined the relationship between VIs and GPP for 121 FLUXNET sites across the globe and assessed how the VI-GPP relationship varied among a variety of biomes at both monthly and annual timescales. We used three widely-used VIs: normalized difference vegetation index (NDVI), enhanced vegetation index (EVI), and 2-band EVI (EVI2) as well as a new VI - NIRV and used surface reflectance both with and without BRDF correction from the moderate resolution imaging spectroradiometer (MODIS) to calculate these indices. The resulting traditional (NDVI, EVI, EVI2, and NIRV) and BRDF-corrected (NDVIBRDF, EVIBRDF, EVI2BRDF, and NIRV, BRDF) VIs were used to examine the VI-GPP relationship. At the monthly scale, all VIs were moderate or strong predictors of GPP, and the BRDF correction improved their performance. EVI2BRDF and NIRV, BRDF had similar performance in capturing the variations in tower GPP as did the MODIS GPP product. The VIs explained lower variance in tower GPP at the annual scale than at the monthly scale. The BRDF-correction of surface reflectance did not improve the VI-GPP relationship at the annual scale. The VIs had similar capability in capturing the interannual variability in tower GPP as MODIS GPP. VIs were influenced by temperature and water stresses and were more sensitive to temperature stress than to water stress. VIs in combination with environmental factors could improve the prediction of GPP than VIs alone. Our findings can help us better understand how the VI-GPP relationship varies among indices, biomes, and timescales and how the BRDF effect influences the VI-GPP relationship.

The semi-arid ecosystems dominate the inter-annual variability of the global carbon sink and the driving role of semi-arid ecosystems is becoming increasingly important. However, the impacts of climate change on the dynamics of carbon and water fluxes in global semi-arid ecosystems are still not well understood. We used a data-driven (or machine learning) approach, along with observations from a number of FLUXNET sites and spatially continuous satellite and meteorological data, to generate gridded carbon and water flux estimates for semi-arid regions globally, and then examined the magnitude, spatial patterns, and trends of carbon and water fluxes and their responses to climate change during the period 1982-2015. The average annual gross primary productivity (GPP), net ecosystem productivity (NEP), evapotranspiration (ET), and water use efficiency (WUE) were 628.6 g C m−2 yr−1, 9.6 g C m−2 yr−1, 463.1 mm yr−1, and 1.60 g C Kg−1 H2O, respectively. The climate conditions during the period 1982-2015 enhanced gross and net carbon uptake in global semi-arid regions. The spatially-averaged annual GPP, NEP, ET, and WUE in semi-arid regions showed significant increases both globally and regionally (Asia, Africa, and Australia). As with GPP and ET, WUE significantly increased in North America, Asia, Africa, and Australia. Australia was the most sensitive semi-arid region in terms of changes in carbon and water fluxes and their responses to climate. Semi-arid forests, shrublands, and savannas were net carbon sinks; croplands were minor carbon sources; grasslands were nearly carbon neutral. Overall, precipitation was the most important climate factor influencing the carbon and water fluxes; WUE in 40.9% of the semi-arid region was significantly influenced by precipitation. The global climate change is expected to influence global semi-arid ecosystems in many ways and our findings have implications for semi-arid ecosystem management and policy making.

The surface urban heat island (SUHI), which represents the difference of land surface temperature (LST) in urban relativity to neighboring non-urban surfaces, is usually measured using satellite LST data. Over the last few decades, advancements of remote sensing along with spatial science have considerably increased the number and quality of SUHI studies that form the major body of the urban heat island (UHI) literature. This paper provides a systematic review of satellite-based SUHI studies, from their origin in 1972 to the present. We find an exponentially increasing trend of SUHI research since 2005, with clear preferences for geographic areas, time of day, seasons, research foci, and platforms/sensors. The most frequently studied region and time period of research are China and summer daytime, respectively. Nearly two-thirds of the studies focus on the SUHI/LST variability at a local scale. The Landsat Thematic Mapper (TM)/Enhanced Thematic Mapper (ETM+)/Thermal Infrared Sensor (TIRS) and Terra/Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) are the two most commonly-used satellite sensors and account for about 78% of the total publications. We systematically reviewed the main satellite/sensors, methods, key findings, and challenges of the SUHI research. Previous studies confirm that the large spatial (local to global scales) and temporal (diurnal, seasonal, and inter-annual) variations of SUHI are contributed by a variety of factors such as impervious surface area, vegetation cover, landscape structure, albedo, and climate. However, applications of SUHI research are largely impeded by a series of data and methodological limitations. Lastly, we propose key potential directions and opportunities for future efforts. Besides improving the quality and quantity of LST data, more attention should be focused on understudied regions/cities, methods to examine SUHI intensity, inter-annual variability and long-term trends of SUHI, scaling issues of SUHI, the relationship between surface and subsurface UHIs, and the integration of remote sensing with field observations and numeric modeling.

Increasing urbanization causes an urban heat island (UHI) effect and exacerbates health risks of heat waves due to global warming. The surface UHI (SUHI) in large cities has been extensively studied, yet a systematic evaluation on the impacts of urbanization on local‐to global‐scale land surface warming is lacking. We propose a new procedure to quantify the warming effects of urbanization at local, regional, and global scales using high‐resolution satellite observations. We find strong local warming effects for 88% of the urban‐dominated pixels across the globe and cooling effects for the rest of the urban lands on a diurnal mean timescale, with a global urban mean intensity of 1.1°C in 2015. The SUHI effects differ substantially by time of day, season, and climate zone, and are closely related to surface evapotranspiration. By extending local effects to the entire land surface, we estimate a diurnal mean warming of only 0.008°C globally. However, urbanization can have large warming effects regionally, especially in eastern China, the eastern United States, and Europe. In addition, we show that global urban expansion results in over three‐quarters of SUHI effects in 1985–2015, and its effect will likely increase by 50%–200% by the end of this century. The SUHI‐added warming could be up to 0.12°C in summer in Europe by 2100 under a fossil‐fueled development pathway. Our results reveal that urbanization substantially intensifies local and regional land surface warming and that prioritized attention should be given to the SUHI‐added warming in highly or rapidly urbanized regions. Plain Language Summary Rapid urban expansion can increase temperature by the resultant urban heat island effect, therefore exacerbating negative impacts of global warming on the environment, human health, and energy consumption. However, the magnitude by which global urbanization intensifies land surface warming is not well understood. We proposed a new procedure to quantify the effects of urban land use on local‐, regional‐, and global‐scale land surface warming using high‐resolution satellite observations. It is shown that urban expansion substantially warms local and regional climates, with high spatial‐temporal variability, but contributes little to global‐scale warming, and that the impacts are projected to nearly triple under a fossil‐fueled development pathway by the end of this century. This study offers a new perspective of methods to quantify the surface urban heat island effect and important insights for climate change assessments. Key Points Impacts of urbanization on local‐to global‐scale land surface warming are quantified according to high‐resolution satellite observations Urbanization contributes little to global warming but greatly intensifies local and regional warming with large spatiotemporal variability Urban expansion leads to over 3/4 of the current urban heating effects in 1985–2015 and likely a 50%–200% further increase globally by 2100

Amazon forests play an important role in the global carbon cycle and Earth's climate. The vulnerability of Amazon forests to drought remains highly controversial. Here we examine the impacts of the 2015 drought on the photosynthesis of Amazon forests to understand how solar radiation and precipitation jointly control forest photosynthesis during the severe drought. We use a variety of gridded vegetation and climate datasets, including solar-induced chlorophyll fluorescence (SIF), photosynthetic active radiation (PAR), the fraction of absorbed PAR (APAR), leaf area index (LAI), precipitation, soil moisture, cloud cover, and vapor pressure deficit (VPD) in our analysis. Satellite-derived SIF observations provide a direct diagnosis of plant photosynthesis from space. The decomposition of SIF to SIF yield (SIFyield) and APAR (the product of PAR and fPAR) reveals the relative effects of precipitation and solar radiation on photosynthesis. We found that the drought significantly reduced SIFyield, the emitted SIF per photon absorbed. The higher APAR resulting from lower cloud cover and higher LAI partly offset the negative effects of water stress on the photosynthesis of Amazon forests, leading to a smaller reduction in SIF than in SIFyield and precipitation. We further found that SIFyield anomalies were more sensitive to precipitation and VPD anomalies in the southern regions of the Amazon than in the central and northern regions. Our findings shed light on the relative and combined effects of precipitation and solar radiation on photosynthesis, and can improve our understanding of the responses of Amazon forests to drought.