Siberian Greening Enhances Coastal Spring Chlorophyll in Western North America

doi:10.21203/rs.3.rs-4812859/v1

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Siberian Greening Enhances Coastal Spring Chlorophyll in Western North America

https://doi.org/10.21203/rs.3.rs-4812859/v1

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Climate change is driving unprecedented changes in terrestrial and marine ecosystems, with profound effects on global atmospheric dynamics, carbon cycling, and productivity^1,2. In particular, Siberia has experienced an earlier onset of the growing season^3,4,5 and increased productivity⁴, contributing to regional warming^4,5,6 and altered aerosol emissions^7,8. At the same time, coastal spring chlorophyll in the northwestern US and Canada is undergoing significant changes due to coastal upwelling and resulting nutrient enrichment, affecting ecological dynamics and fisheries sustainability^9–15. However, trends in the spring chlorophyll and its future changes remain uncertain. This study shows a significant increasing trend in coastal spring chlorophyll along the west of North America, associated with enhanced northerly winds induced by Siberian spring greening under greenhouse gas warming. Increased warming in Siberia, associated with spring greening, induces positive atmospheric pressure and northerly winds along the northwest coast of North America during spring. These winds drive enhanced upwelling, leading to elevated nitrate concentrations and significant spring chlorophyll blooms. Model simulations incorporating current and future CO2 forcings consistently confirm the observed increase in chlorophyll levels along the coastal waters of northern California, Oregon, Washington, and southern British Columbia. This study underscores the central role of Siberian spring greening in shaping the Northeastern Pacific Ocean spring ecosystem. The results highlight the complex linkages between terrestrial greening, atmospheric teleconnections, nutrient cycling, and marine ecosystems. A comprehensive understanding of these linkages is critical for predicting and managing the impacts of greenhouse gas-induced warming on fish catches and broader ecosystem dynamics. This research will help refine predictions and develop strategies to mitigate the broad impacts of climate change on marine ecosystems.

Earth and environmental sciences/Ecology/Climate-change ecology

Earth and environmental sciences/Ecology/Ecosystem ecology

Earth and environmental sciences/Climate sciences/Climate change/Climate and Earth system modelling

Earth and environmental sciences/Climate sciences/Atmospheric science/Atmospheric dynamics

In recent decades, Siberia has experienced significant warming^6,16–18, marking a global climatic shift. This temperature increase has resulted in a sustained greening, covering approximately 20% of the world's forested areas^15–24 and acting as a net sink for atmospheric CO2 in recent decades, contributing to global carbon dynamics^17–23. Notably, Siberian warming has played a central role in influencing East Asian climate²¹, atmospheric dynamics²⁵, ecosystems, and carbon cycles^22–23.

Meanwhile, the eastern coastal regions of the northern Pacific, including California, are known globally for their biological richness. Northerly winds in these areas drive robust upwelling processes that transport cold, nutrient-rich subsurface waters to the surface layer²⁶-²⁷. This phenomenon supports primary production, fisheries, and biodiversity, making these coastal regions vital components of marine ecosystems²⁷. However, the factors influencing the dynamics of their increasing trends remain poorly constrained.

This study aims to provide evidence for the effects of Siberian greening on marine productivity along the west coast of North America in spring. In addition, we investigate potential physical mechanisms linking Siberian greening to marine physical and biological dynamics, particularly those related to atmospheric and oceanic circulation. Using an Earth system model, we conducted a series of experiments in which we systematically manipulated greening anomalies in Siberia. Our results show that the observed greening trends in Siberia have contributed to enhanced chlorophyll trends on the west coast of the US through enhanced upwelling and upward transport of nutrients driven by northerly winds induced by atmospheric teleconnections associated with Siberian warming. Furthermore, taking into account the influence of significant anthropogenic factors, our study suggests a plausible scenario in which the future marine primary productivity of the west coast of North America may experience an increase due to the ongoing greening trends in Siberia. This research highlights the intricate connections between terrestrial vegetation changes and marine productivity and underscores the significant impacts of Siberian greening and warming during spring. These factors, which were previously not strongly influential, now play a significant role in shaping increasing spring chlorophyll trends in the Northeast Pacific due to atmospheric teleconnections. The statement also emphasizes the importance of considering these dynamics for a comprehensive understanding of future ecological trends.

Increasing trends of coastal chlorophyll trends in the western US and Canada.

We focus on spring coastal chlorophyll along the west of North America, where a pronounced increasing trend has been observed since the 2000s (Fig. 1a). Due to the uncertainty of satellite-based chlorophyll measurements²⁸, we estimated recent trends using different data sources. All data show significant increasing trends in spring chlorophyll along the western coast of North America, ranging from 0.17 to 0.33 mg m^− 3 per 25 years, which represents 17–35% of its mean value. Combined data of all satellite data (see Method) also show notable increasing trends over 25 years (1998–2002) with an average rise of 40%. This trend is evident in the time series of the chlorophyll averaged over the northwestern coast of North America, corresponding to an annual increment of 0.012 mg m^− 3 year^− 1 (P < 0.01; Fig. 1b). Consistent with the satellite retrievals, field-based observations^29,30 of chlorophyll data (CalCOFI) over northern California (Fig. 1a; see Methods) show robust increasing trends.

Furthermore, the averaged spring chlorophyll from selected data increases from 0.55 (1998–2009) to 0.71 (2010–2022), a statistically significant increase of about 29% above the 95% confidence level, according to a bootstrap test (see Method). If target periods are alternatively defined as 1998–2007 and 2013–2022, we obtain an essentially identical result, indicating that spring chlorophyll along the northwestern coast of North America has increased over the 25 years. This finding is supported by a statistically significant increase in combined data and strong inter-data consensus.

We also examine the spatial pattern of trends in spring chlorophyll. Farther downstream in the North Pacific, the combined data show a significant increasing trend in spring chlorophyll along the west coast of North America, ranging from 0.13 to 0.51 mg m^− 3 per 25 years. Notably, the coastal regions of northern California, Oregon, Washington, and southern British Columbia (125°W-130°W, 35°N-50°N) (Fig. 1d) show an increasing trend in chlorophyll of 0.4–0.5 mg m^− 3 per 25 years.

Possible link between Siberian greening and coastal chlorophyll trends in the western US and Canada.

The increased trends in coastal chlorophyll along the western coast of North America are linked to significant climatic changes in Eastern Siberia, where a pronounced greening trend has been observed during the spring season since the 2000s (Fig. 2a). This greening trend is also evident in the time series of the gross primary productivity (GPP) in Siberia³¹ (Supplementary Fig. S2), which shows a remarkable increase of 56.2% (+ 35.7 g C m^− 2 yr^− 1, P < 0.01). Spatially, 82% of the Siberian GPP over 90°E-140°E, 55°N-70°N (boxed in Fig. 2a) shows significant increasing trends (P < 0.01), with the only opposite trend observed over 80°E-90°E.

A robust increase in Siberian greening from 1998 to 2022 (Fig. 2a) is speculated to be due to global warming, which has accelerated since the 2000s³². The Siberian greening trend is associated with surface warming^6,17. To understand the underlying mechanisms, we examine the recent climatic changes over Siberia. Previous studies have shown that the accelerated greening has been driven by Siberian warming, which in turn may further intensify the warming trend due to reduced surface albedo. The proposed processes are in good agreement with our analyses shown in Figs. 2b (see also Supplementary Fig. S2)^6,17,18. In terms of spring seasonal progression, eastern Siberia experiences the earliest onset of spring warming. The observed warming trend, particularly pronounced in this region, indicates an enhanced spring warming, possibly due to feedback between anthropogenic warming and ecosystem response^6,17,18.

This intensified trend of Siberian GPP could significantly influence regional climate and atmospheric circulations. We investigate trends in atmospheric circulation and find a weakening trend of the Siberian High (Fig. 2c; see negative sea-level pressure (SLP) trends over the Siberian region; see also Supplementary Fig. 3b-3d). Early snowmelt and resulting ground conditions due to anthropogenic warming can lead to a warmer atmosphere and positive geopotential height anomalies by inhibiting evaporative cooling^33–35. In the upper troposphere, the advanced seasonal transition is evident in a positive geopotential height trend (Fig. 2b), illustrating the early shrinkage of the East Asian trough³⁶—a stationary planetary trough that characterizes the winter atmospheric circulation over East Asia (Supplementary Fig. 3e). This accelerated decay of the winter climatological circulation is followed by an early establishment of the summer circulation. A negative height trend over the North Pacific (Fig. 2b) supports the early development of the Mid-Pacific Trough³⁷, a planetary wave that dominates the summer atmospheric circulation (Supplementary Fig. 3f and 3g), while strong positive trends over the Northeast Pacific in both the upper and lower tropospheres act in favor of the early development of the summer North Pacific High (Fig. 2a,b).

The positive SLP trend over the northeast Pacific deserves a closer look, as it induces northerly winds along the coastal regions of the western US and Canada. Northerly wind speeds have increased significantly by 4.0 m s^− 1 between 1998 and 2021, double the climatological value. This intensified northerly wind enhances upwelling from the subsurface to the surface ocean through Ekman pumping. Observational data show that the upwelling trends have increased by 18 cm day^− 1 over two decades (50% above the mean), with a vertical structure showing increasing trends down to 100m depth, peaking at about 30m along the west coast of North America (Supplementary Fig. S4a)^38,39. The upwelling may have been accompanied by enhanced upward transport of nutrients from the subsurface (or mixed layer). Estimates of nitrate concentration at 0–10 m depth, based on sampling data show a significant increasing trend, especially after 2010, although with relatively large uncertainties (Supplementary Fig. S4b). The abundance of nutrients in the surface ocean may partially contribute to the chlorophyll from the previous spring, consistent with previous studies linking northerly winds to chlorophyll activity in the western US^11,26. Note that chlorophyll decreases in southern California (Fig. 1d) due to southerly wind trends (Fig. 2a) and enhanced downwelling, reducing nutrient supply to the near ocean surface layer and causing a decrease in chlorophyll levels.

These serial responses, coupled with an accelerated seasonal transition, suggest that the observed chlorophyll trend off the west coast of the US and Canada may be amplified by Siberian warming with local vegetation system feedback. In the next section, causality will be clearly demonstrated through Earth system model experiments.

Sensitivity of chlorophyll in the western US and Canada to Siberian GPP

To explore the causal relationship between Siberian GPP-enhanced warming and chlorophyll levels on the west coast of North America, we used an Earth System Model (ESM) in our study. An idealized simulation using the ESM allowed us to assess the influence of Siberian GPP on chlorophyll in this region. The simulation included a reference run with pre-industrial forcing ('SIGPP_1.0'). We introduced a nearly uniform 150% increase in the mean GPP from the reference run in the Siberian region ('SIGPP_1.5') and a 50% reduction in the GPP ('SIGPP_0.5'), as described in the Methods section and Fig. 1a (red box). The differences in chlorophyll between 'SIGPP_1.5' and 'SIGPP_0.5' are shown in Figs. 3a and 3b, and effectively replicate the observed increase in chlorophyll over the US west coast attributed to Siberian greening.

To further validate the robustness of the enhanced effect of Siberian greening effect on western US chlorophyll, we conducted two additional sensitivity experiments involving a doubling ('SIGPP_2.0') and 2.5 times ('SIGPP_2.5') of Siberian greening with ensemble simulations (see Methods). The results, with an overall accuracy of more than 95%, showed a significant positive correlation between Siberian GPP and the chlorophyll response (Fig. 3b), consistent with the observations in the comparison between the 'SIGPP_1.5' and 'SIGPP_0.5' experiments. The difference in chlorophyll between 'SIGPP_2.0' and 'SIGPP_1.0' ranged from 0.15 to 0.20 mg m^− 3, approximately 40–55% of the spring mean chlorophyll from the reference run. This increase was particularly pronounced in Oregon, Washington, and southern British Columbia, where there was substantial enhancement of northerly and oceanic upwelling. In summary, Siberian greening leads to an increase in marine productivity and carbon sink by altering climatic conditions on the West Coast of the US region.

To gain a deeper understanding of this mechanism, we leveraged the results from the ESM simulations. Our analysis aimed to quantify the influence of Siberian Gross Primary Productivity (GPP) on marine productivity along the western US through the 'SIGPP_1.5' and 'SIGPP_0.5' simulations. Figure 3c nicely illustrates the differences in climate and ecosystems between these two simulations, successfully reproducing the SLP trend pattern (e.g., Fig. 2a) and the enhancement of northerly winds in the western U.S. due to Siberian greening. The model deviates slightly from observations by simulating the southward shift of the negative SLP and the westward shift of the positive SLP. Nevertheless, it effectively reproduces the zonal dipole pattern of the SLP, which is characterized by anomalous high pressure in the northeastern Pacific accompanied by northerly anomalies (Fig. 3c). In addition, the model skillfully captures the seasonal transition of planetary waves in the upper troposphere, accompanied by Siberian heating, resulting in anomalous high pressure and northeasterly winds over the western US (Supplementary Fig. S5). The model also reproduces the oceanic response to the northerly winds at the surface, simulating significant upwelling anomalies (Supplementary Fig. S6a) and abundant nutrients (Supplementary Fig. S6b), although the magnitudes are relatively weaker than observed. In summary, our results suggest that the increasing trends in chlorophyll over the western U.S. are largely due to the seasonal modulation initiated by Siberian greening and warming and the resulting northerly winds.

Impacts of Siberian Greening on Western US Marine Productivity under Global Warming Conditions

The effects of greenhouse warming on marine productivity, particularly along the west coast of North America, have been investigated by numerous observational and climate model studies^{10–15,26−28,40}. To quantitatively assess the positive effects of Siberian warming enhanced by the greening on marine productivity along the west coast of North America under greenhouse warming, two additional simulations have been conducted using the ESM. In the first simulation, carbon dioxide (CO2) concentrations were abruptly quadrupled ('4XCO2'), allowing the vegetation system to respond freely. In the second simulation, CO2 concentrations were also quadrupled, but pre-industrial climatological conditions for Siberian GPP were maintained ('4XCO2 + GPPclim'). In the '4XCO2' simulation, chlorophyll increases by 1.05 mg m^− 3 over 40 years compared to the reference run (SIGPP_1.0). Conversely, when Siberian greening was suppressed ('4XCO2 + GPPclim'), chlorophyll showed a less significant increase compared to the '4XCO2' simulation, with a lower concentration (by 0.3–0.4 mg m^− 3 in Fig. 4a). An analysis of the differences between these simulations revealed that Siberian greening led to enhanced positive chlorophyll anomalies in the northeast Pacific, associated with increased surface northerly winds and increased upwelling. These processes were similar to those observed in models with pre-industrial CO2 forcing (difference between SIGPP_1.5 and SIGPP_0.5; refer Fig. 3), suggesting that the enhanced effect of Siberian greening on western US marine GPP persists under greenhouse warming conditions, albeit with potential differences in the underlying mechanisms in a warmer background climate.

The results presented in Fig. 4a are further corroborated by an examination of emission-based model simulations in the Coupled Model Intercomparison Project Phase 6 (CMIP6) future scenario runs (Methods). The CMIP6 simulations include data from 8 models for the period 2040 to 2099. The models with greater Siberian greening tend to simulate greater increases in coastal chlorophyll in the western US and Canada, with a correlation coefficient of r = 0.64 (P < 0.01) (Fig. 4b). The increasing trends in Siberian GPP appear to result in an enhanced positive SLP in the northeastern Pacific (Fig. 4b). The enhanced positive SLP can intensify northerly winds in the western US coastal region through an enhanced upwelling and high nutrient concentrations, thus contributing to increased chlorophyll. This is supported by CMIP6 simulations, which indicate that Siberian GPP enhances northerly winds in the coastal region of the western US and Canada and tends to increase nutrients. This change is statistically significant (r = 0.66, P < 0.01) (Fig. 4c). We plot the increased coastal chlorophyll in the western US under greenhouse warming as a function of the corresponding Siberian greening (Fig. 4c). Overall, these CMIP6 model results are in good agreement with our model simulations.

In this study, we find a robust positive relationship between Siberian greening and marine productivity. Both our analyses of observed data and model-generated results strongly support the notion that Siberian greening has the potential to increase coastal chlorophyll over much of the western US and Canada, thereby contributing to an enhanced carbon sink. These results underscore the importance of considering Siberian greening conditions when predicting and improving the predictability of marine productivity. As Siberia has exhibited more pronounced greening trends in recent decades, there is an increased possibility of a substantial increase in chlorophyll resources. Since chlorophyll trends are primarily sensitive to nutrient availability under greenhouse warming, it is crucial to note that uncertainties in future coastal chlorophyll can be partially attributed to projected Siberian greening in model simulations. This study highlights the critical importance of accurately simulating Siberian conditions, not only for understanding regional climate change but also for understanding global ecosystem changes and their interactions between terrestrial and marine ecosystems.

Natural variations in the northern Pacific, such as the Northern Pacific Oscillation (NPO) and the Northern Pacific Gyre Oscillation (NPGO), can influence atmospheric circulation along the eastern boundary of the northern Pacific, leading to positive trends in the SLP and enhanced northerly winds^39–40. In spring, the NPO manifests itself as negative SLP anomalies in the northern Pacific (45°N-70°N) and positive anomalies in the southern Pacific (20°N-45°N) extending to 120°W, accompanied by northerly winds near the west coast of the United States. The NPO index showed a significant upward trend from 1986-2016³⁹. However, after 1994, there was a notable shift from positive to negative SLP anomalies around 130°W-120°W, resulting in a significant weakening of the associated northerly winds. This suggests that the NPO plays a minor role in the increasing trend of positive SLP and northerly winds over the Northeast Pacific after 1994. The NPGO is well known for its effects on both atmospheric circulation and ecosystems along the eastern boundary of the northern Pacific. However, the correlation between upwelling, abundant nutrients, and enhanced chlorophyll is particularly strong with the NPGO in southern California⁴⁰.

Increased upwelling in the western U.S. and Canada has far-reaching effects on marine ecosystems, including fish catch^11,41,44. We examine trends in fish catch using data from the FishStat database. While an increase in chlorophyll is traditionally associated with abundant fish populations, our results reveal a contrasting scenario in the western US, where major fish catchments show a declining trend from 2000 to 2022 (Supplementary Fig. S4). In particular, the Pacific cupped oyster experienced a significant decline of $43 million (82%) between 2003 and 2022, while the albacore fishery declined by 50% and other species declined by 56%. The decline in fish populations may be due to a decrease in near-surface dissolved oxygen^11,44. Along the west coast of North America, where the oxygen minimum zone exists in the subsurface layer, increased upwelling can bring O2-depleted subsurface waters to the surface. The effects of ocean transport on O2 in the upper ocean may have been exacerbated by increased O2 consumption by marine heterotrophs, as inferred from increased ocean productivity, which has contributed to a sharp decline in O2 in recent decades⁴⁴. The upwelling system, designed to deliver nutrients, delivers anomalously low oxygen levels, leading to mass fish and invertebrate mortality.

Diagnosis of the observed data

To derive the monthly mean sea surface temperature (SST), we used the National Oceanic and Atmospheric Administration Extended Reconstructed SST version 5 (ERSST)⁴⁵. Near-surface temperature, wind, sea level pressure, net shortwave radiation, and geopotential height (1998–2021) were obtained from the ERA5 (European Centre for Medium-Range Weather Forecasts Reanalysis)⁴⁶ (https://www.ecmwf.int/en/forecasts/dataset/ecmwf-reanalysis-v5). For gross primary productivity (GPP) over land, we used near-infrared (NIR) reflectance (g C m^− 2 mon^− 1), which is based on the absorption of blue and red light energy by vegetation for photosynthesis (1998–2018)³¹. The Siberian greening index is defined as the averaged gross primary productivity over 90°E-130°W, 55N°-70°N) during May. We used different satellite data sources to examine the significance of chlorophyll trends. First, we used chlorophyll concentration data at 9 km spatial resolution from SeaWiFS⁴⁷ and MODIS-Aqua⁴⁸ ocean color observations (1998 to 2022). In Addition, we use the first 240 months of the standard monthly 9-km MODIS-Aqua three ocean wavebands of remote sensing reflectance (Rrs), centered at 443 nm, 531 nm, and 667 nm (https://modis.gsfc.nasa.gov/about/specifications.php). The 2022 reprocessing of Rrs and Chl was used, which reduces atmospheric correction errors and, crucially, minimizes any instrumental drift through updated sensor calibrations. Furthermore, we used chlorophyll concentration data at 9 km spatial resolution from MODIS-Aqua ocean color observations based on the Garver-Siegel Maritorena (GSM) algorithm⁶⁰ (1998 to 2022), which is a semi-analytical model used for deriving the inherent optical properties (IOPs) of ocean water from Rrs data. We combined all satellite-based chlorophyll data by averaging them to create a comprehensive dataset. The coastal chlorophyll (CHL) index in the western USA is defined as the averaged chlorophyll concentration over 125°W-120°W and 50N°-65°N during May. Chlorophyll, dissolved oxygen (DO), and nitrate (NO3) site sample data were obtained from the California Cooperative Oceanic Fisheries Investigations (CalCOFI, https://calcofi.org/data/oceanographic-data/ctd-cast-files/). These data were collected during quarterly CalCOFI cruises (winter, spring, summer, and fall). At each station, CHL, DO, and NO3 were collected near the surface (10 m) and at the depth of the chlorophyll maximum, which varies in time and space. The chlorophyll maximum is identified on the downcast of the CTD and subsequently sampled on the upcast of the CTD^40,41. If these two depths coincided, only one seawater sample was collected. For complete environmental data collection and analysis methods, see https://calcofi.org/references/methods. Ocean upwelling data used in this study is based on reanalysis output from the National Centers for Environmental Prediction (NCEP) GODAS for the period 1998–2021.

Earth system model

We employed the third version of the Nanjing University of Information Science and Technology Earth System Model (NESM3.0)^49–52, comprising fully coupled atmosphere, ocean, sea ice, and land models connected by an explicit coupler. The atmospheric model had a resolution of T63L47. The ocean model featured a grid resolution of 1°, with a meridional refinement to 1/3° over the equatorial region. The model utilized 46 vertical layers, with the upper 15 layers extending to the top 100 m. NESM3.0 demonstrated a reasonable climatology, capturing key characteristics of climate variabilities. The NESM includes the JSBACH3 model, capable of simulating the interannual variability of Gross Primary Productivity (GPP) and ecosystem dynamics^53–55. The ocean biogeochemical model can simulate the lower trophic levels of marine ecosystems (phytoplankton, microzooplankton, and mesozooplankton). The model also replicates the biogeochemical cycles of carbon and the main nutrients (P, N, Fe, and Si). The model incorporates 24 prognostic variables (tracers), including two phytoplankton compartments (diatoms and nanophytoplankton), two zooplankton size classes (microzooplankton and mesozooplankton), and a description of carbonate chemistry^56–59.

Bootstrap methods

A bootstrap method is used to examine whether the ensemble or multi-model mean changes in the autocorrelation of DJF NINO3.4 SST anomalies, skewness of monthly NINO3.4 SST anomalies, and the number of El Nino following LaNino is statistically significant. The data in the present-day period (blue bars in Fig. 2a) are resampled randomly to construct 10,000 realizations of mean response value over large ensemble or multi-models. In this random resampling process, any value can be selected again. The same is carried out for the future period. We compute the s.d. of the 10,000 inter-realizations of mean response value for the two periods.

Sensitivity of the Siberian greening on coastal marine productivity in the western US.

To investigate the response of coastal chlorophyll in the western USA to changes in Siberian greening, we conducted idealized simulations using current external forcings based on historical simulations (2000s) from the Coupled Model-Intercomparison Project Phase 6 (CMIP6). In the Siberian region, increasing spring GPP trends generally coincide with increasing leaf area index (LAI). The given increasing LAI induces reduced surface albedo and resulting surface warming^4,17. Since GPP is a diagnostic variable, not a prognostic variable that could influence the climate system, including surface warming, we changed LAI instead. Increasing (decreasing) LAI leads to decreasing (increasing) albedo and thus contributes to surface warming (cooling). The NESM3.0 was integrated for 500 years with fixed historical forcings (2000–2014) based on the CMIP6 protocol to obtain an initial state with a stable equilibrium between the atmosphere, ocean, and GPP over Siberia. The last 50 years of data are used for the reference run ('SIGPP_1.0'). In 'SIGPP_1.5', for the Siberian region (90°E-130°W, 55N°-70°N), the model was simulated with the Siberian LAI spring climatology 150% higher than in the control run. Note that the GPPs in other regions were calculated freely. Similarly, the sensitivity simulations 'SIGPP_2.0', 'SIGPP_2.5', and 'SIGPP_0.5' represent Siberian spring greening by 200%, 250%, and 50%, respectively. To estimate the effect of greenhouse warming on Siberian greening-coastal chlorophyll interactions in the western USA, we conducted four additional experiments. In '4×CO2', we abruptly quadrupled the CO2 concentration from 'SI + 100%' (current CO2 concentration). 4×CO2 + GPPclim' is the same as '4×CO2', but Siberia used the 'SI + 100%' climatology. The significance level of the difference between the 'SIGPP_1.5' and 'SIGPP_0.5' conditions was determined using a Kolmogorov-Smirnov two-sample test. All simulations were integrated over 50 years.

CMIP6 model simulation data

We used CMIP6 CO2 emission-driven future scenario simulations (SSP585). The models include an interactive bio-geo-chemistry module in the models. We used nine model simulation data (ACCESS-ESM1-5, CanESM5, GISS-E2-1-G-CC, MPI-ESM1-2-LR, MRI-ESM2-0, NorESM2-LM, CNRM-ESM2-1, MIROC-ES2L, GFDL-ESM4) with 2016–2100 periods. The data was downloaded from https://esgf-node.llnl.gov/search/cmip6.

Data availability

All observed data used in this study are publicly available (https://psl.noaa.gov/data/gridded/ data.20thC_ReanV3.html; https://psl.noaa.gov/data/gridded/data.noaa.ersst.v5.html; https://oceandata.sci.gsfc.nasa.gov/MODIS-Aqua; https://calcofi.org/data/oceanographic-data/ctd-cast-files/).). The data can be downloaded from https://figshare.com/articles/dataset/SiberiaGPP_NPCHL/ 19771102.

Code availability

The codes used in this study can be downloaded here: https://figshare.com/articles/dataset/SiberiaGPP_NPCHL/ 19771102.

Author contributions statement

Y.-M.Y., S.-I.A., and J.-Y.L. conceived the idea. Y.-M.Y. performed the model experiments and analyses. S.-I.A., Y.-M.Y., S.-W.Y., B.W, E.-Y.K., M.-K.S., J.-Y.L., and J.-H.P. wrote the manuscript. All authors provided critical feedback and helped shape the research, analysis, and manuscript.

Competing interests

The authors declare no competing interests.

Acknowledgments

Y.-M.Y. is supported by the National Natural Science Foundation of China (NSFC042088101) and the National Research Foundation of Korea (NRF-2022R1A2C1013296). S.-I.A. is supported by the National Research Foundation of Korea (NRF) grant funded by the Korean government (NRF-2018R1A5A1024958).

Trisos, C.H., Merow, C. & Pigot, A.L. The projected timing of abrupt ecological disruption from climate change. Nature 580, 496–501 (2020).
Gretta T. Pecl et al., Biodiversity redistribution under climate change: Impacts on ecosystems and human well-being.Science355,eaai9214(2017).
Gao, S., Liang, E., Liu, R. et al. An earlier start of the thermal growing season enhances tree growth in cold humid areas but not in dry areas. Nat Ecol Evol 6, 397–404 (2022).
Buermann, W., Forkel, M., O’Sullivan, M. et al. Widespread seasonal compensation effects of spring warming on northern plant productivity. Nature 562, 110–114 (2018).
Chen, X., & Yang, Y. Observed earlier start of the growing season from middle to high latitudes across the Northern Hemisphere snow-covered landmass for the period 2001–2014. Environmental Research Letters, 15(3), 034042 (2020)
Piao, S., Wang, X., Park, T. et al. Characteristics, drivers and feedbacks of global greening. Nat Rev Earth Environ 1, 14–27 (2020)
Bourtsoukidis, E., Pozzer, A., Williams, J. et al. High temperature sensitivity of monoterpene emissions from global vegetation. Commun Earth Environ 5, 23 (2024).
Tang, J., Zhou, P., Miller, P.A. et al. High-latitude vegetation changes will determine future plant volatile impacts on atmospheric organic aerosols. npj Clim Atmos Sci 6, 147 (2023).
Fan, L., Wigneron, JP., Ciais, P. et al. Siberian carbon sink reduced by forest disturbances. Nat. Geosci. 16, 56–62 (2023).
Dai, Y., Yang, S., Zhao, D. et al. Coastal phytoplankton blooms expand and intensify in the 21st century. Nature 615, 280–284 (2023)
Grantham, B., Chan, F., Nielsen, K. et al. Upwelling-driven nearshore hypoxia signals ecosystem and oceanographic changes in the northeast Pacific. Nature 429, 749–754 (2004).
National Research Council. Coastal Waters: Understanding and Reducing the Effects of Nutrient Pollution (National Academy Press, Washington DC, 2000)
Wheeler, P. A., Huyer, A. & Fleischbein, J. Cold halocline, increased nutrients and higher productivity off Oregon in 2002. Geophys. Res. Lett. [online] 30, 8021 (2003)
Freeland, H. J., Gatien, G., Huyer, A. & Smith, R. L. Cold halocline in the northern California current: an invasion of subarctic water. Geophys. Res. Lett. [online] 30, 1141 (2003) (doi:10.1029/2002GL016663)
McCabe, R. M., B. M. Hickey, R. M. Kudela, K. A. Lefebvre, N. G. Adams, B. D. Bill, F. M. D. Gulland, R. E. Thomson, W. P. Cochlan, and V. L. Trainer. An unprecedented coastwide toxic algal bloom linked to anomalous ocean conditions, Geophys. Res. Lett., 43, 10,366–10 (2016).
Buermann, W., Forkel, M., O’Sullivan, M. et al. Widespread seasonal compensation effects of spring warming on northern plant productivity. Nature 562, 110–114 (2018).
Betts, R. Offset of the potential carbon sink from boreal forestation by decreases in surface albedo. Nature 408, 187–190 (2000).
Zeng, Z., Piao, S., Li, L. et al. Climate mitigation from vegetation biophysical feedbacks during the past three decades. Nature Clim Change 7, 432–436 (2017). https://doi.org/10.z1038/nclimate3299
Alkama, R., Forzieri, G., Duveiller, G. et al. Vegetation-based climate mitigation in a warmer and greener World. Nat Commun 13, 606 (2022).
Schuur, E. A. G. et al. Climate change and the permafrost carbon feedback. Nature 520, 171–179 (2015).
Liu, Y., Li, Z. & Chen, Y. Continuous warming shift greening towards browning in the Southeast and Northwest High Mountain Asia. Sci Rep 11, 17920 (2021).
Manlick, P.J., Perryman, N.L., Koltz, A.M. et al. Climate warming restructures food webs and carbon flow in high-latitude ecosystems. Nat. Clim. Chang. (2024).
Froitzheim, N., Majka, J., and Zastrozhnov, D.: Methane release from carbonate rock formations in the Siberian permafrost area during and after the 2020 heat wave, P. Natl. Acad. Sci. USA, 118, e2107632118, https://.org/10.1073/pnas.2107632118, 2021
Josep G. Canadell, Michael R. Raupach,Managing Forests for Climate Change Mitigation.Science320,1456–1457(2008).
Rebecca C. Scholten et al.,Early snowmelt and polar jet dynamics co-influence recent extreme Siberian fire seasons.Science378,1005–1009(2022).
Chavez, F. P., & Messié, M. (2009). A comparison of eastern boundary upwelling ecosystems. Progress in Oceanography, 83(1–4), 80–96.
Cochrane, K., De Young, C., Soto, D., & Bahri, T. (2009). Climate change implications for fisheries and aquaculture. FAO Fisheries and Aquaculture Technical Paper, 530, 21
Kessouri, F., Bianchi, D., Renault, L., McWilliams, J. C., Frenzel, H., & Deutsch, C. A. (2020). Submesoscale currents modulate the seasonal cycle of nutrients and productivity in the California Current System. Global Biogeochemical Cycles, 34, e2020GB006578.
Lampe, R.H., Coale, T.H., Forsch, K.O. et al. Short-term acidification promotes diverse iron acquisition and conservation mechanisms in upwelling-associated phytoplankton. Nat Commun 14, 7215 (2023).
Kahru, M., Kudela, R., Manzano-Sarabia, M. & Mitchell, B. G. Trends in primary production in the California Current detected with satellite data. Geophys. Res. Lett. 114, C02004 (2009)
Wang, S., Zhang, Y. (2020). Long-term (1982–2018) global gross primary production dataset based on NIRv. National Tibetan Plateau/Third Pole Environment Data Center, https://doi.org/10.6084/m9.figshare.12981977.
Xie, S. P., & Kosaka. What caused the global surface warming hiatus of 1998–2013?. Current Climate Change Reports, 3, 128–140 (2017).
Rebecca C. Scholten et al.,Early snowmelt and polar jet dynamics co-influence recent extreme Siberian fire seasons.Science378,1005–1009(2022).
Q. Tang, X. Zhang, J. A. Francis, Extreme summer weather in northern mid-latitudes linked to a vanishing cryosphere. Nat. Clim. Chang. 4, 45–50 (2014).
S. I. Seneviratne, T. Corti, E. L. Davin, M. Hirschi, E. B. Jaeger, I. Lehner, B. Orlowsky, A. J. Teuling, Investigating soil moisture-climate interactions in a changing climate: A review. Earth Sci. Rev. 99, 125–161 (2010).
Wang, L., W. Chen, W. Zhou, and R. Huang: Interannual variations of East Asian trough axis at 500 hPa and its association with the East Asian winter monsoon pathway. J. Climate, 22, 600–614 (2009)
Deng, K., Yang, S., Ting, M., Hu, C., & Lu, M. Variations of the mid-Pacific trough and their relations to the Asian–Pacific–North American climate: Roles of tropical sea surface temperature and Arctic sea ice. Journal of Climate, 31(6), 2233–2252 (2018).
García-Reyes, M., and J. Largier. Observations of increased wind-driven coastal upwelling off central California, J. Geophys. Res., 115, C04011 (2010).
Foreman, M. G. G., B. Pal, and W. J. Merryfield. Trends in upwelling and downwelling winds along the British Columbia shelf, J. Geophys. Res., 116, C10023 (2011).
James, C.C., Barton, A.D., Allen, L.Z. et al. Influence of nutrient supply on plankton microbiome biodiversity and distribution in a coastal upwelling region. Nat Commun 13, 2448 (2022).
Beman, J., Carolan, M. Deoxygenation alters bacterial diversity and community composition in the ocean’s largest oxygen minimum zone. Nat Commun 4, 2705 (2013).
Yeh, S.-W., Yi, D.-W., Sung, M.-K., & Kim, Y. H. An eastward shift of the North Pacific Oscillation after the mid-1990s and its relationship with ENSO. Geophysical Research Letters, 45, 6654–6660 (2018).
Di Lorenzo, E., et al. North Pacific Gyre Oscillation links ocean climate and ecosystem change, Geophys. Res. Lett., 35, L08607 (2008)
Pierce, S. D., J. A. Barth, R. K. Shearman, and A. Y. Erofeev. Declining Oxygen in the Northeast Pacific. J. Phys. Oceanogr., 42, 495–501 (2012).
Huang, B. et al. Extended reconstructed sea surface temperature, version 5 (ERSSTv5): upgrades, validations, and intercomparisons. J. Clim. 30, 8179–8205 (2017).
Dee, D. P. et al. The ERA-Interim reanalysis: configuration and performance of the data assimilation system. Q. J. R. Meteorol. Soc. 137, 553–597 (2011).
NASA Goddard Space Flight Center, Ocean Ecology Laboratory & Ocean Biology Processing Group. Sea-viewing Wide Field-of-view Sensor (SeaWiFS) Chlorophyll Data; Reprocessing. NASA OB.DAAC, Greenbelt, MD, USA. https://doi.org/10.5067/ORBVIEW-2/SEAWIFS/L3M/CHL/2022. (2022).
NASA Goddard Space Flight Center, Ocean Ecology Laboratory & Ocean Biology Processing Group. Moderate-resolution Imaging Spectroradiometer (MODIS) Aqua Chlorophyll Data; Reprocessing. NASA OB.DAAC, Greenbelt, MD, USA. https://doi.org/10.5067/AQUA/MODIS/L3M/CHL/2022. (2022).
Yang, Y.-M., An, S.-I., Wang, B. & Park, J.-H. A global-scale multidecadal variability driven by Atlantic multidecadal oscillation. Natl. Sci. Rev. 7, 1190–1197 (2020).
Yang, Y.-M., Wang, B., Cao, J. et al. Improved historical simulation by enhancing moist physical parameterizations in the climate system model NESM3.0. Clim. Dyn. 54, 3819–3840 (2020).
Yang, Y.-M., Park, J.-H., An, S.-I. et al. Mean sea surface temperature changes influence ENSO-related precipitation changes in the mid-latitudes. Nat. Commun. 12, 1495 (2021).
Yang, YM., Park, JH., An, SI. et al. Increased Indian Ocean-North Atlantic Ocean warming chain under greenhouse warming. Nat Commun 13, 3978 (2022). https://doi.org/10.1038/s41467-022-31676-8
Thum, T., et al. (2011), Soil carbon model alternatives for ECHAM5/JSBACH climate model: Evaluation and impacts on global carbon cycle estimates, J. Geophys. Res., 116, G02028, doi:10.1029/2010JG001612.
Mäkelä, J., Minunno, F., Aalto, T., Mäkelä, A., Markkanen, T., and Peltoniemi, M.: Sensitivity of 21st century simulated ecosystem indicators to model parameters, prescribed climate drivers, RCP scenarios and forest management actions for two Finnish boreal forest sites, Biogeosciences, 17, 2681–2700, https://doi.org/10.5194/bg-17-2681-2020, 2020.
Thum, T., Nabel, J. E. M. S., Tsuruta, A., Aalto, T., Dlugokencky, E. J., Liski, J., Luijkx, I. T., Markkanen, T., Pongratz, J., Yoshida, Y., and Zaehle, S.: Evaluating two soil carbon models within the global land surface model JSBACH using surface and spaceborne observations of atmospheric CO2, Biogeosciences, 17, 5721–5743, https://doi.org/10.5194/bg-17-5721-2020, 2020.
Fogli, P. G., Iovino, D.: CMCC–CESM–NEMO: Toward the new CMCC Earth System Model. CMCC Research Rep. RP0248, 19 pp. (2014). [Available online at http://www.cmcc.it/wp-content/uploads/2015/02/rp0248-ans-12-2014.pdf]. Accessed 11 April 2019
Madec, G.: NEMO ocean engine. Note du Pole de modélisation, Version 3.6 27 ISSN No 1288–1619, Institut Pierre-Simon Laplace (IPSL), France (2016)
Séférian, R., Bopp, L., Gehlen, M., Orr, J.C., Ethé, C., Cadule, P., Aumont, O., Mélia, D.S., Voldoire, A., Madec, G.: Skill assessment of three earth system models with common marine biogeochemistry. Clim. Dyn. 40, 2549–2573 (2013). https://doi.org/10.1007/s00382-012-1362-8
Aumont, O., Ethe, C., Tagliabue, A., Bopp, L., Gehlen, M.: PISCES-v2: an ocean biogeochemical model for carbon and ecosystem studies. Geosci. Model Dev. 8, 2465–2513 (2015). https://doi.org/10.5194/gmd-8-2465-2015
Maritorena, S., d'Andon, O. H. F., Mangin, A., & Siegel, D. A. (2010). Merged satellite ocean color data 1061 1062 products using a bio-optical model: Characteristics, benefits and issues. Remote Sensing of Environment, 114(8), 1791–1804

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Siberian Greening Enhances Coastal Spring Chlorophyll in Western North America

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Abstract

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Introduction

Sensitivity of chlorophyll in the western US and Canada to Siberian GPP

Impacts of Siberian Greening on Western US Marine Productivity under Global Warming Conditions

Discussion

Methods

Diagnosis of the observed data

Earth system model

Bootstrap methods

CMIP6 model simulation data

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Author contributions statement

Competing interests

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