Variations in the amplitude and timing of the seasonal cycle of atmospheric CO2 have shown an association with surface air temperature consistent with the hypothesis that warmer temperatures have promoted increases in plant growth during summer1 and/or plant respiration during winter2 in the northern high latitudes. Here we present evidence from satellite data that the photosynthetic activity of terrestrial vegetation increased from 1981 to 1991 in a manner that is suggestive of an increase in plant growth associated with a lengthening of the active growing season. The regions exhibiting the greatest increase lie between 45°N and 70°N, where marked warming has occurred in the spring time3 due to an early disappearance of snow4. The satellite data are concordant with an increase in the amplitude of the seasonal cycle of atmospheric carbon dioxide exceeding 20% since the early 1970s, and an advance of up to seven days in the timing of the drawdown of CO2 in spring and early summer1. Thus, both the satellite data and the CO2 record indicate that the global carbon cycle has responded to interannual fluctuations in surface air temperature which, although small at the global scale, are regionally highly significant.
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... However, most studies have focused on community scales or small study areas because of their limitations in field measurements. With the rapid progress of remote sensing, a combination of remote sensing and ground observations datasets at different scales can be used to effectively estimate vegetation biomass (Myneni et al., 1997Piao et al., 2005Piao et al., , 2007Fang et al., 2007). For instance, Piao et al. (2003) estimated the magnitude and changes in grassland biomass in some ecosystems in China. ...
... Our results further showed that T min and T max had an asymmetric effect on the aboveground biomass of the investigated marsh wetland ( Table 1), suggesting that the increased maximum temperature in spring and winter may be associated with the temporal change in marsh AGB, especially during spring. Furthermore, our findings were consistent with previous studies showing that a warmer climate could lead to increase aboveground biomass as a consequence of enhanced photosynthetic rate and longer growth season (Myneni et al., 1997Los et al., 2001;Tucker et al., 2001;Zhou et al., 2001;Hicke et al., 2002;Slayback et al., 2003). First, warming during the day accelerates the reaction FIGURE 5 | Spatial distributions of correlation coefficients between the annual AGB and annual precipitation (A), annual mean temperature (B), annual maximum temperature (C), and annual minimum temperature (D) in the western Songnen Plain marshes. ...
Understanding the spatiotemporal dynamics of aboveground biomass (AGB) is crucial for investigating the wetland ecosystem carbon cycle. In this paper, we explored the spatiotemporal change of aboveground biomass and its response to climate change in a marsh wetland of western Songen Plain by using field measured AGB data and vegetation index derived from MODIS datasets. The results showed that the AGB could be established by the power function between measured AGB density and the annual maximum NDVI (NDVImax) of marsh: Y = 302.06 × NDVImax1.9817. The averaged AGB of marshes showed a significant increase of 2.04 g⋅C/m2/a, with an average AGB value of about 111.01 g⋅C/m2 over the entire western Songnen Plain. For the influence of precipitation and temperature, we found that the annual mean temperature had a smaller effect on the distribution of marsh AGB than that of the total precipitation in the western Songnen Plain. Increased precipitation in summer and autumn would increase AGB by promoting marshes’ vegetation growth. In addition, we found that the minimum temperature (Tmin) and maximum temperatures (Tmax) have an asymmetric effect on marsh AGB on the western Songnen Plain: warming Tmax has a significant impact on AGB of marsh vegetation, while warming at night can non-significantly increase the AGB of marsh wetland. This research is expected to provide theoretical guidance for the restoration, protection, and adaptive management of wetland vegetation in the western Songnen Plain.
... Previous findings have demonstrated that changes in VPD, temperature, and atmospheric CO 2 concentration can significantly influence plant growth by controlling photosynthetic rate, stomatal conductance, CO 2 assimilation, and other physiological pathways (Bonan et al., 2014;Green et al., 2020;Lopez et al., 2021;Piao et al., 2013;Wang et al., 2020). Moreover, the remotely sensed indicators such as Vegetation Indices (VIs) and Leaf Area Index (LAI) were used to investigate the relationships between terrestrial ecosystems and climate change at regional and global scales (Myneni et al., 1997;Nemani et al., 2003;Zhang, Song, et al., 2017;Zhu et al., 2016). Recent studies suggested that satellite-derived measurements of solar-induced chlorophyll fluorescence (SIF) can capture climate change impacts on vegetation productivity better than other indicators (Dechant et al., 2020;Fournier et al., 2012;Migliavacca et al., 2017;Song et al., 2021). ...
... Multiple lines of evidence indicated that global vegetation productivity has increased over the last two decades (Figure 2). Similar to the previous results based on VIs (Myneni et al., 1997;Zhang, Song, et al., 2017;Zhu et al., 2016), our results showed that SIF (or GPP) has increased over more than half (approximately 66.5%-72.2%) of the globally vegetated areas. Most of the upward trends were found in East Asia, South Asia, Central Africa, central North America, and continental Europe. ...
Rising atmospheric dryness [vapor pressure deficit (VPD)] can limit photosynthesis and thus reduce vegetation productivity. Meanwhile, plants can benefit from global warming and the fertilization effect of carbon dioxide (CO2). There are growing interests to study climate change impacts on terrestrial vegetation. However, global vegetation productivity responses to recent climate and CO2 trends remain to be fully understood. Here, we provide a comprehensive evaluation of the relative impacts of VPD, temperature, and atmospheric CO2 concentration on global vegetation productivity over the last two decades using a robust ensemble of solar‐induced chlorophyll fluorescence (SIF) and gross primary productivity (GPP) data. We document a significant increase in global vegetation productivity with rising VPD, temperature, and atmospheric CO2 concentration over this period. For global SIF (or GPP), the decrease due to rising VPD was comparable to the increase due to warming but far less than the increase due to elevated CO2 concentration. We found that rising VPD counteracted only a small proportion (approximately 8.1%–15.0%) of the warming and CO2‐induced increase in global SIF (or GPP). Despite the sharp rise in atmospheric dryness imposing a negative impact on plants, the warming and CO2 fertilization effects contributed to a persistent and widespread increase in vegetation productivity over the majority (approximately 66.5%–72.2%) of the globally vegetated areas. Overall, our findings provide a quantitative and comprehensive attribution of rising atmospheric dryness on global vegetation productivity under concurrent climate warming and CO2 increasing.
... The high positive trend in the maximum annual NDVI index value in the southern part of Iceland is in line with the widespread afforestation of that region (Fries 2017). The other studies about northern latitude's vegetation variations, indicate that there is a great increase in vegetation coverage between 45°N and 70°N (Myneni et al. 1997;Huang et al. 2017). ...
Changes in the vegetation of the Arctic and sub-Arctic regions have been used as indicators of the impact and seriousness of climate change. In this study, 342 MODIS NDVI images were used to monitor and assess the variability and long-term changes in the vegetation in Iceland in the period 2001–2018. An insignificant trend in the changes of the vegetation coverage (R = 0.16, p-value = 0.05) was obtained, however, it also resulted that the area with the low values of the NDVI (< 0.6) is decreasing, whereas the area with higher values of the NDVI (> 0.6, mostly forests) is increasing. The NDVI index during the study period rose for the area of about 3260 km2, while it declined for 1635 km2. The results of this study can be used for organizing the strategies preventing climate change and global warming.
... Remote and near-surface spectral observations provide Vegetation Indices (VIs) sensitive to canopy greenness (Tucker, 1979;Huete et al., 2002;Richardson et al., 2009), which can be used to monitor canopy development, phenology, and vegetation functioning (Wu et al., 2009;Migliavacca et al., 2011;Toomey et al., 2015). This linkage between the variation of greenness and vegetation functioning is strong in canopies with a pronounced seasonal dynamics of leaf area index (LAI) and chlorophyll content (Myneni et al., 1997;Zhang et al., 2003;Migliavacca et al., 2015) like grassland and deciduous forests. By contrast, evergreen forests, especially those with broadleaf trees, exhibit low temporal variability in their canopy greenness Moser et al., 2020), which results in a desynchronization between seasonal changes in canopy-scale greenness and seasonality of vegetation functioning such as carbon and water fluxes . ...
Remote sensing capabilities to monitor evergreen broadleaved vegetation are limited by the low temporal variability in the greenness signal. With canopy greenness computed from digital repeat photography (PhenoCam), we investigated how canopy greenness related to seasonal changes in leaf age and traits as well as variation of trees’ water fluxes (characterized by sap flow and canopy conductance). The results showed that sprouting leaves are mainly responsible for the rapid increase in canopy green chromatic coordinate (GCC) in spring. We found statistically significantly differences in leaf traits and spectral properties among leaves of different leaf ages. Specifically, mean GCC of young leaves was 0.385 ± 0.010 (mean ± SD), while for mature and old leaves was 0.369 ± 0.003, and 0.376 ± 0.004, respectively. Thus, the temporal dynamics of canopy GCC can be explained by changes in leaf spectral properties and leaf age. Sap flow and canopy conductance are both well explained by a combination of environmental drivers and greenness (96% and 87% of the variance explained, respectively). In particular, air temperature and vapor pressure deficit (VPD) explained most of sap flow and canopy conductance variance, respectively. Besides, GCC is an important explanatory variable for variation of canopy conductance may because GCC can represent the leaf ontogeny information. We conclude that PhenoCam GCC can be used to identify the leaf flushing for evergreen broadleaved trees, which carries important information about leaf ontogeny and traits. Thus, it can be helpful for better estimating canopy conductance which constraints water fluxes.
... It is worth noting that both T day and T night had intensive influences on vegetation dynamics according to their proportions of significant pixels ( Fig. 5 and Fig. 7). On the contrary, daytime warming in the same cold Arctic regions has been reported to be more positively influential for vegetation and is probably due to the much shorter duration of nighttime during the growing season (Piao et al., 2015;Shen et al., 2016;Myneni et al., 1997). The ongoing drastic nighttime warming in alpine ecosystems like HMA should receive more attention. ...
Meteorological records over the past five decades have shown that climate warming has been faster during the nighttime than during the daytime. However, the responses of vegetation development to asymmetric warming are not well understood due to the misinterpretation of phenology that have resulted from the snowmelt effect. We applied normalized difference vegetation index (NDVI) sources from Global Inventory Modeling and Mapping Studies (GIMMS:1982-2015) and Moderate Resolution Imaging Spectroradiometer (MODIS: 2000-2020) to reveal maximum greenness in high-mountain Asia (HMA). The snow-free normalized difference phenology index (NDPI), which is a 3-band vegetation index that designed to best contrast vegetation from soil and snow, was applied for estimating the start of the growing season (SOS). We found that alpine pastures in HMA generally became greener and the SOS was delayed. Preseason daytime temperatures (T day) and nighttime temperatures (T night) had opposite effects on maximum greenness, with T day being negative and T night being positive. The responses of SOS to T day and T night were highly related with the frequency of meteorological drought events during 2000-2020. In regions with lower frequency of drought events, both daytime and nighttime warming could advance SOS. In regions with higher frequency of drought events, daytime warming could delay SOS, but nighttime warming could advance SOS. The results of our study are of great significance to understand the responses of alpine ecosystems to asymmetric climate warming. Such an understanding is quite valuable for pasture management and future vegetation climate projections.
... Vegetation index (NDVI) changes. The Normalized Difference Vegetation Index (NDVI) is an important indicator of vegetation growth 24 . The study results reveal that the NDVI of the lower reaches of the Tarim River increased from 0.14 in 2000 to 0.21 in 2020, representing a rise of about 33.3%. ...
Water system management is a worldwide challenge, especially in arid and semi-arid regions. Ecological water conveyance projects aim to raise the groundwater table, thereby saving natural vegetation and curbing ecological deterioration. Since 2000, these projects have been implemented in the arid zone of northwest China, with generally successful outcomes. Taking a portion of the lower reaches of the Tarim River as the study area, this paper analyzes in detail the ecohydrological effects which have occurred since the launching of artificial water conveyance 20 years ago. The results show that the groundwater table in the upper, middle and lower segments of the Tarim River’s lower reaches has been raised on average 4.06, 4.83 and 5.13 m, respectively, while the area of surface water bodies connected to those sections has expanded from 49.00 km² to 498.54 km². At the same time, Taitema Lake, which is the terminal lake of the Tarim River, has been revived and now boasts a water area of 455.27 km². Other findings indicate that the surface ecological response is extremely sensitive and that the area of natural vegetation has expanded to 1423 km². Furthermore, the vegetation coverage, vegetation index (NDVI), and Net Primary Productivity (NPP) have increased by 132 km², 0.07 and 7.6 g C m⁻², respectively, and the Simpson dominance, McIntosh evenness, and Margalef richness indices have risen by 0.33, 0.35 and 0.49, respectively, in the monitored sample sites. As well, the carbon sink area has expanded from 1.54% to 7.8%. Given the increasing intensity of the occurrence of extreme hydrological events and successive dry years, similar ecological water conveyance projects should be considered elsewhere in China and in other parts of the world. The water conveyance scheme has generally proven successful and should be optimized to enhance the benefits of ecological water conveyance under water resource constraints.
... The Arctic (north of 66.5 • N) and boreal region (between 45 and 65 • N) have undergone dramatic temperature and ecological changes over the past century, and the rate of this change has accelerated in recent decades (Cohen et al., 2014). Satellite-based observations of leaf area index (LAI) and normalized difference vegetation index (NDVI) suggest that northern high latitudes have shown a significant trend of greening in the past three decades as a result of vegetation growth (Bhatt et al., 2017;Keeling et al., 1996;Myers-Smith et al., 2011;Myneni et al., 1997;Xu et al., 2013;Zhou et al., 2001;, in part because the temperature is the limiting factor for vegetation growth in this region (Nemani et al., 2003). In the meantime, boreal forest fires have shown an increasing trend over the past few decades, which is likely to continue (Abatzoglou and Williams, 2016). ...
Here we use satellite observations of formaldehyde (HCHO) vertical column densities (VCD) from the TROPOspheric Monitoring Instrument (TROPOMI), aircraft measurements, combined with a nested regional chemical transport model (GEOS-Chem at 0.5×0.625∘ resolution), to better understand the variability and sources of summertime HCHO in Alaska. We first evaluate GEOS-Chem with in-situ airborne measurements during the Atmospheric Tomography Mission 1 (ATom-1) aircraft campaign. We show reasonable agreement between observed and modeled HCHO, isoprene, monoterpenes and the sum of methyl vinyl ketone and methacrolein (MVK+MACR) in the continental boundary layer. In particular, HCHO profiles show spatial homogeneity in Alaska, suggesting a minor contribution of biogenic emissions to HCHO VCD. We further examine the TROPOMI HCHO product in Alaska in summer, reprocessed by GEOS-Chem model output for a priori profiles and shape factors. For years with low wildfire activity (e.g., 2018), we find that HCHO VCDs are largely dominated by background HCHO (58 %–71 %), with minor contributions from wildfires (20 %–32 %) and biogenic VOC emissions (8 %–10 %). For years with intense wildfires (e.g., 2019), summertime HCHO VCD is dominated by wildfire emissions (50 %–72 %), with minor contributions from background (22 %–41 %) and biogenic VOCs (6 %–10 %). In particular, the model indicates a major contribution of wildfires from direct emissions of HCHO, instead of secondary production of HCHO from oxidation of larger VOCs. We find that the column contributed by biogenic VOC is often small and below the TROPOMI detection limit, in part due to the slow HCHO production from isoprene oxidation under low NOx conditions. This work highlights challenges for quantifying HCHO and its precursors in remote pristine regions.
The vegetation green-up date (GUD) of the Tibetan Plateau (TP) is highly sensitive to climate change. Accurate estimation of GUD is essential for understanding the dynamics and stability of terrestrial ecosystems and their interactions with climate. The GUD is usually determined from a time-series of vegetation indices (VIs). The adoption of different VIs and GUD extraction methods can lead to different GUDs. However, our knowledge of the uncertainty in these GUDs on TP is still limited. In this study, we evaluated the performance of different VIs and GUD extraction methods on TP from 2003 to 2020. The GUDs were determined from six Moderate Resolution Imaging Spectroradiometer (MODIS) derived VIs: normalized difference vegetation index (NDVI), enhanced vegetation index (EVI), normalized difference infrared index (NDII), phenology index (PI), normalized difference phenology index (NDPI), and normalized difference greenness index (NDGI). Four extraction methods (βmax, CCRmax, G20, and RCmax) were applied individually to each VI to determine GUD. The GUDs obtained from all VIs showed similar patterns of early green-up in the eastern and late green-up in the western plateau, and similar trend of GUD advancement in the eastern and postponement in the western plateau. The accuracy of the derived GUDs was evaluated by comparison with ground-observed GUDs from 19 agrometeorological stations. Our results show that two snow-free VIs, NDGI and NDPI, had better performance in GUD extraction than the snow-calibrated conventional VIs, NDVI and EVI. Among all the VIs, NDGI gave the highest GUD accuracy when combined with the four extraction methods. Based on NDGI, the GUD extracted by the CCRmax method was found to have the highest consistency (r = 0.62, p < 0.01, RMSE = 11 days, bias = −3.84 days) with ground observations. The NDGI also showed the highest accuracy for preseason snow-covered site-years (r = 0.71, p < 0.01, RMSE = 10.69 days, bias = −4.05 days), indicating its optimal resistance to snow cover influence. In comparison, NDII and PI hardly captured GUD. NDII was seriously affected by preseason snow cover, as indicated by the negative correlation coefficient (r = −0.34, p < 0.1), high RMSE and bias (RMSE = 50.23 days, bias = −24.25 days).
In the context of global warming, vegetation activity in northeastern East Asia (40–45°N, 105–130°E) (NEA) shows a significant growth trend on a multidecadal scale, but how vegetation changes on a decadal scale is unclear. In this study, we find a significant trend of vegetation greening in northeastern East Asia during 1982–1998 and a slowdown in the greening trend during 1998–2014. Trend analysis of the extreme climate indices reveals that the trends of precipitation-related extreme climate indices are similar to those of vegetation change, and further correlation analysis reveals that precipitation-related extreme climate indices have a strong positive correlation with the NDVI. The results indicate that the vegetation in northeastern East Asia is more sensitive to precipitation changes, especially extreme precipitation, compared with the temperature and related extreme indices. Furthermore, the analysis of large-scale atmospheric circulation changes suggests a role of Northwest Pacific subtropical high (NPSH) in the trend changes of precipitation-related extreme indices. The strengthening of NPSH before 1998 enhances the moisture transport to the NEA, providing abundant water vapor favorable for extreme precipitation events, while after 1998, the NPSH trend is much weakened, corresponding to a decrease in the moisture transport trend.
The greening and browning of global vegetation are driven by various processes such as climate change, CO2 fertilization, and land management, etc. From the perspective of the vegetation-water-heat relationship, the above processes can be briefly summarized as two types of eco-hydrological processes: 1. dryness change; 2. usage change. We here present a diagnostic procedure to identify the dominant eco-hydrological processes, thus evaluate the climate change impacts on ecosystems. Utilizing remote-sensing based leaf area index (LAI) and climate data during 1982–2016, we demonstrate that dryness changes showed prior dominance over 1/4 global lands where LAI trends are significant. Concretely, drying/wetting has expanded/reduced its regional dominance from 8%/15.8% (1982–1999) to 18.1%/11.9% (1999–2016), indicating that dryness change has turned to more drying than wetting for global vegetated lands. As increased over twofold, drying is playing an increasingly important role in the climate change impacts on terrestrial ecosystems, bringing fundamental weakening of global greening.
The first global terrestrial gridded data set of the daily average and range of temperature and daily precipitation has been developed, intended for use in terrestrial biospheric modeling. Data for the year 1987 are shown to illustrate our methodology. Daily station data, primarily from the World Meteorological Organization global synoptic surface network of stations, have been extensively quality checked and interpolated to a 1×1 degree grid by using a nearest neighbors interpolation scheme. Annual averages of the daily average temperatures have been compared with 1987 temperatures constructed from data supplied by P. D. Jones (personal communication, 1996). Agreement between these two data sets is good, except in some areas of the southern hemisphere where station coverage is poor. Monthly and annual totals of the daily precipitation data have been compared with the monthly 1987 data set produced by the Global Precipitation Climatology Centre. Agreement between the two data sets is good over much of the northern hemisphere and South America; however, large discrepancies are seen in east-central and south-central Africa and in most of Australia, primarily due to the poor station coverage there. Comparison of the time series from individual stations with those from the gridded data set indicate that the day-to-day variation of temperature and the fraction of wet days are preserved, except in the tropics where wet days are overestimated. Station densities have been tabulated in terms of total annual net primary productivity to identify countries where increases in station data will be most effective for terrestrial biospheric modeling.
A reprocessing of 12 years of global data from the Advanced Very High Resolution Radiometers on board the afternoon-viewing NOAA series satellites (NOAA-7, 9, and 11) is taking place as part of the NASA/NOAA Pathfinder project. A Pathfinder AVHRR land data set is being produced which is composed of global, 8 km NDVI with associated reflectances, brightness temperatures, solar and scan geometry, and cloud estimation. This data set is being processed using the best available methods in order to produce a consistent time series of data of unprecedented quality. Methods used in processing include a cross-satellite calibration, navigation using an orbital model and updated ephemerides, and correction for Rayleigh scattering. The data will be available to the community as both daily and composite data, and analysis of this long time series is expected to provide insight into terrestrial processes, seasonal and annual variability, and methods for handling large volume data sets.
A programme of global arid and semi-arid land monitoring is currently underway at NASA/Goddard Space Flight Center using meteorological satellite data to detect possible climatic change as manifested by changes in arid and semi-arid land extent. This has resulted in the processing and interpretation of a large amount of satellite data from the NOAA-series of polar-orbiting satellites. Techniques are described and preliminary results presented for determination of the boundary between the Sahara Desert and the Sahel Zone of Africa using daily advanced very high resolution radiometer data from 1980–1992. Some of the techniques may be of interest to other researchers who are or will be using large multi-year data sets derived from coarse-resolution satellite data to investigate large-scale land surface questions.
Observations of atmospheric CO2 concentrations at Mauna Loa, Hawaii, and at the South Pole over the past four decades show an approximate proportionality between the rising atmospheric concentrations and industrial CO2 emissions. This proportionality, which is most apparent during the first 20 years of the records, was disturbed in the 1980s by a disproportionately high rate of rise of atmospheric CO2, followed after 1988 by a pronounced slowing down of the growth rate. To probe the causes of these changes, we examine here the changes expected from the variations in the rates of industrial CO2 emissions over this time, and also from influences of climate such as El Niño events. We use the 13C/12C ratio of atmospheric CO2 to distinguish the effects of interannual variations in biospheric and oceanic sources and sinks of carbon. We propose that the recent disproportionate rise and fall in CO2 growth rate were caused mainly by interannual variations in global air temperature (which altered both the terrestrial biospheric and the oceanic carbon sinks), and possibly also by precipitation. We suggest that the anomalous climate-induced rise in CO2 was partially masked by a slowing down in the growth rate of fossil-fuel combustion, and that the latter then exaggerated the subsequent climate-induced fall.
The effect of sensor degradation in the Advanced Very High Resolution Radiometer (AVHRR) channels 1 and 2 on the Normalized Difference Vegetation Index (NDVI) has been established. Three models have been developed that adjust NDVI for sensor degradation without recourse to component channel 1 and 2 data. The models have been verified with data obtained by the AVHRR on board of NOAA-7, -9 and -11. Two models provide accurate results in some cases, but perform less well in others. A third model is applicable to all cases investigated, and estimates the effect of sensor degradation with a maximum RMS error of 0·002NDVI. The remaining error depends on surface characteristics and the magnitude of sensor degradation, and cannot be accounted for without the component channel 1 and 2 data.
Meteorological satellite data from 1982 to 1990 were used to identify
areas of significant association between tropical Pacific sea surface
temperature (SST) and remotely sensed normalized difference vegetation
index (NDVI) anomalies, here taken as a surrogate for rainfall
anomalies. During this period, large areas of arid and semi-arid Africa,
Australia and South America experienced NDVI anomalies directly
correlated to tropical Pacific SST anomalies. The results are limited by
the relatively short time period of analysis. However, they confirm the
disruptive effects of large-scale tropical Pacific SST variations on
arid and semiarid continental rainfall patterns in Africa, Australia,
and South America, as reported previously.
THROUGHOUT the Northern Hemisphere the concentration of atmospheric carbon dioxide rises in winter and declines in summer, mainly in response to the seasonal growth in land vegetation1–4. In the far north the amplitude of the seasonal cycle, peak to trough, is between 15 and 20 parts per million by volume5. The annual amplitude diminishes southwards to about 3 p.p.m. near the Equator, owing to the diminishing seasonally of plant activity towards the tropics. In spite of atmospheric mixing processes, enough spatial variability is retained in the seasonal cycle of CO2 to reveal considerable regional detail in seasonal plant activity6. Here we report that the annual amplitude of the seasonal CO2 cycle has increased by 20%, as measured in Hawaii, and by 40% in the Arctic, since the early 1960s. These increases are accompanied by phase advances of about 7 days during the declining phase of the cycle, suggesting a lengthening of the growing season. In addition, the annual amplitudes show maxima which appear to reflect a sensitivity to global warming episodes that peaked in 1981 and 1990. We propose that the amplitude increases reflect increasing assimilation of CO2 by land plants in response to climate changes accompanying recent rapid increases in temperature.