Julia K Green

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Scholarly Contributions

Chapters

• Green, J. (2024). Machine Learning to Predict and Explain Complex Carbon Cycle Interactions. In Land Carbon Cycle Modeling, Second Edition. doi:10.1201/9781032711126-44
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  Machine learning models are often considered as being black boxes. This chapter shows ways to gain in-depth understanding of the interactions between predictor and response variables in these algorithms. Specifically, a recent study (see the first suggested reading) is used to illustrate some examples of the utility of machine learning models in the carbon science field, and outline several methods available for machine learning model interpretability.

Journals/Publications

• Feldman, A., Reed, S., Amaral, C., Babst-Kostecka, A., Babst, F., Biederman, J., Devine, C., Fu, Z., Green, J., Guo, J., Hanan, N., Kokaly, R., Litvak, M., MacBean, N., Moore, D., Ojima, D., Poulter, B., Scott, R., Smith, W., , Swap, R., et al. (2024). Adaptation and Response in Drylands (ARID): Community Insights for Scoping a NASA Terrestrial Ecology Field Campaign in Drylands. Earth's Future, 12(9). doi:10.1029/2024EF004811
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  Dryland ecosystems cover 40% of our planet's land surface, support billions of people, and are responding rapidly to climate and land use change. These expansive systems also dominate core aspects of Earth's climate, storing and exchanging vast amounts of water, carbon, and energy with the atmosphere. Despite their indispensable ecosystem services and high vulnerability to change, drylands are one of the least understood ecosystem types, partly due to challenges studying their heterogeneous landscapes and misconceptions that drylands are unproductive “wastelands.” Consequently, inadequate understanding of dryland processes has resulted in poor model representation and forecasting capacity, hindering decision making for these at-risk ecosystems. NASA satellite resources are increasingly available at the higher resolutions needed to enhance understanding of drylands' heterogeneous spatiotemporal dynamics. NASA's Terrestrial Ecology Program solicited proposals for scoping a multi-year field campaign, of which Adaptation and Response in Drylands (ARID) was one of two scoping studies selected. A primary goal of the scoping study is to gather input from the scientific and data end-user communities on dryland research gaps and data user needs. Here, we provide an overview of the ARID team's community engagement and how it has guided development of our framework. This includes an ARID kickoff meeting with over 300 participants held in October 2023 at the University of Arizona to gather input from data end-users and scientists. We also summarize insights gained from hundreds of follow-up activities, including from a tribal-engagement focused workshop in New Mexico, conference town halls, intensive roundtables, and international engagements.
• Green, J., Zhang, Y., Luo, X., & Keenan, T. (2024). Systematic Underestimation of Canopy Conductance Sensitivity to Drought by Earth System Models. AGU Advances, 5(1). doi:10.1029/2023AV001026
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  The response of vegetation canopy conductance (gc) to changes in moisture availability ((Formula presented.)) is a major source of uncertainty in climate projections. While vegetation typically reduces stomatal conductance during drought, accurately modeling how and to what degree stomata respond to changes in moisture availability at global scales is particularly challenging, because no global scale gc observations exist. Here, we leverage a collection of satellite, reanalysis and station-based near-surface air and surface temperature estimates, which are physically and statistically linked to (Formula presented.) due to the local cooling effect of gc through transpiration, to develop a novel emergent constraint of (Formula presented.) in an ensemble of Earth System Models (ESMs). We find that ESMs systematically underestimate (Formula presented.) by ∼33%, particularly in grasslands, croplands, and savannas in semi-arid and bordering regions of the Central United States, Central Europe, Southeastern South America, Southern Africa, Eastern Australia, and parts of East Asia. We show that this underestimation occurs because ESMs inadequately reduce gc when soil moisture decreases. As gc controls carbon, water and energy fluxes, the misrepresentation of modeled (Formula presented.) contributes to biases in ESM projections of gross primary production, transpiration, and temperature during droughts. Our results suggest that the severity and duration of droughts may be misrepresented in ESMs due to the impact of sustained gc on both soil moisture dynamics and the biosphere-atmosphere feedbacks that affect local temperatures and regional weather patterns.
• Huang, J., Kong, F., Yin, H., Middel, A., Green, J., & Liu, H. (2024). Green roof plant physiological water demand for transpiration under extreme heat. Urban Forestry and Urban Greening, 98. doi:10.1016/j.ufug.2024.128411
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  Green roofs are a sustainable strategy for improving the eco-environment in urban areas. However, plants on green roofs are increasingly threatened by extreme heat and drought due to climate change. There is a lack of comprehensive understanding of the physiological water demand of green roof vegetation under extreme heat. Therefore, this exploratory study investigated two commonly used Sedum species for urban green roofs (Sedum spectabile Boreau and Sedum alfredii Hance) under extreme heat, considering two treatments: irrigation and non-irrigation. The results indicated that under extreme heat, if without irrigation, the two Sedum species’ mean daily water consumption by transpiration was approximately 4.68 g per Sedum plant. However, under irrigation, the diurnal variation of stomatal conductance of the two Sedum species allowed the stomata to remain open throughout the day, resulting in an over-twentyfold increase in mean daily water consumption through transpiration (120.34 g per Sedum plant) and twofold increase in leaf area index. A random forest model showed that multi-environmental factors explained 67.53 % of the variability in stomatal behavior. Photosynthetically active radiation and soil moisture are the primary environmental factors that directly affect stomatal conductance. The irrigation induces stomatal opening throughout the diurnal cycle, ensuring the continuation of vegetation growth and the maintenance of physiological functions under extreme heat, which then contributes to keeping its eco-environmental functions and providing sustainable services, such as cooling and carbon sequestration. The findings of this study can guide planning and managing green roofs in urban areas that face extreme heat events.
• Tian, J., Luo, X., Xu, H., Green, J., Tang, H., Wu, J., & Piao, S. (2024). Slower changes in vegetation phenology than precipitation seasonality in the dry tropics. Global Change Biology, 30(1). doi:10.1111/gcb.17134
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  The dry tropics occupy ~40% of the tropical land surface and play a dominant role in the trend and interannual variability of the global carbon cycle. Previous studies have reported considerable changes in the dry tropical precipitation seasonality due to climate change, however, the accompanied changes in the length of the vegetation growing season (LGS)—the key period of carbon sequestration—have not been examined. Here, we used long-term satellite observations along with in-situ flux measurements to investigate phenological changes in the dry tropics over the past 40 years. We found that only ~18% of the dry tropics show a significant (p ≤.1) increasing trend in LGS, while ~13% show a significant decreasing trend. The direction of the LGS change depended not only on the direction of precipitation seasonality change but also on the vegetation water use strategy (i.e. isohydricity) as an adaptation to the long-term average precipitation seasonality (i.e. whether the most of LGS is in the wet season or dry season). Meanwhile, we found that the rate of LGS change was on average ~23% slower than that of precipitation seasonality, caused by a buffering effect from soil moisture. This study uncovers potential mechanisms driving phenological changes in the dry tropics, offering guidance for regional vegetation and carbon cycle studies.
• Wang, H., Ciais, P., Sitch, S., Green, J., Tao, S., Fu, Z., Albergel, C., Bastos, A., Wang, M., Fawcett, D., Frappart, F., Li, X., Liu, X., Li, S., & Wigneron, J. (2024). Anthropogenic disturbance exacerbates resilience loss in the Amazon rainforests. Global Change Biology, 30(1). doi:10.1111/gcb.17006
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  Uncovering the mechanisms that lead to Amazon forest resilience variations is crucial to predict the impact of future climatic and anthropogenic disturbances. Here, we apply a previously used empirical resilience metrics, lag-1 month temporal autocorrelation (TAC), to vegetation optical depth data in C-band (a good proxy of the whole canopy water content) in order to explore how forest resilience variations are impacted by human disturbances and environmental drivers in the Brazilian Amazon. We found that human disturbances significantly increase the risk of critical transitions, and that the median TAC value is ~2.4 times higher in human-disturbed forests than that in intact forests, suggesting a much lower resilience in disturbed forests. Additionally, human-disturbed forests are less resilient to land surface heat stress and atmospheric water stress than intact forests. Among human-disturbed forests, forests with a more closed and thicker canopy structure, which is linked to a higher forest cover and a lower disturbance fraction, are comparably more resilient. These results further emphasize the urgent need to limit deforestation and degradation through policy intervention to maintain the resilience of the Amazon rainforests.
• H, H., Wigneron, J. P., Ciais, p., Yao, Y., Fan, L., Liu, X., Li, X., Green, J. K., Tian, F., Tao, S., Li, W., Frappart, F., Albergel, C., Wang, M., & Li, S. (2023). Seasonal variations in vegetation water content retrieved from microwave remote sensing over Amazon intact forests. Remote Sensing of Environment, 113409.
• Massoud, E., Hoffman, F., Shi, Z., Tang, J., Alhajjar, E., Barnes, M., Braghiere, R. K., Cardon, Z., Collier, N., Crompton, O., Dennedy-Frank, P. J., Gautam, S., Gonzalez-Meler, M. A., Green, J. K., Koven, C., Levine, P., MacBean, N., Mao, J., Mills, R. T., , Mishra, U., et al. (2023).

  Perspectives on Artificial Intelligence for Predictions in Ecohydrology.

  . Artificial Intelligence for the Earth Systems, 2(4).
• Wang, H., Wigneron, J., Ciais, P., Yao, Y., Fan, L., Liu, X., Li, X., Green, J. K., Tian, F., Tao, S., Li, W., Frappart, F., Albergel, C., Wang, M., & Li, S. (2023). Seasonal variations in vegetation water content retrieved from microwave remote sensing over Amazon intact forests. Remote Sensing of the Environment. doi:10.1016/j.rse.2022.113409
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  Vegetation optical depth (VOD) is seasonally sensitive to plant water content and aboveground biomass. This index has a strong penetrability within the vegetation canopy and is less impacted by atmosphere aerosol contamination effects, clouds and sun illumination than optical vegetation indices. VOD is thus increasingly applied in ecological applications, e.g., carbon stock, phenology and vegetation monitoring. However, VOD retrieval over dense forests is subject to uncertainties caused by the thick canopy and complex multiple scattering effects. Thus, a comprehensive evaluation of VOD products over dense forests is needed for effective and accurate applications. This study evaluated the seasonal variations of eight recently developed/reprocessed VOD products at different frequencies (e.g., Ku-, X-, C- and L-band) over Amazon intact forests, supported by the ORCHIDEE-CAN-NHA model-simulated vegetation water content. Furthermore, we also explored the potential causes of VOD retrieval issues, in terms of retrieval algorithm uncertainties. We first confirmed that soil water availability dominated seasonal dynamics of vegetation water content over Amazon intact forests. This was verified by model-simulated vegetation water content and by C-band radar backscatter observations. Generally, evening or midday vegetation water content shows higher correlations with soil moisture than morning or midnight vegetation water content. In terms of ability of morning or midnight VOD products to follow the seasonality of soil moisture, active microwave ASCAT-IB C-VOD (median seasonal correlation with soil moisture (R) ∼ 0.50) outperforms the passive microwave VOD products, followed by passive microwave AMSR2 X-VOD (R ∼ 0.26) and VODCA X-VOD (R ∼ 0.16). However, SMOS-IC L-VOD (R ∼ −0.15) and AMSR2 C1-VOD (R ∼ −0.20) show obviously negative seasonal correlations with soil moisture across most pixels. This implausible behavior is likely to be caused by the inappropriate setting of time-invariant scattering effects in the passive microwave VOD retrieval algorithms, which could lead to an overestimation of the VOD amplitude during dry seasons. Thus, we recommend that the seasonal scattering effects be considered in the passive microwave VOD retrieval algorithms. These findings can contribute to the improvement of VOD retrieval algorithms and help with the development of their ecological applications over Amazon dense forests.
• Fu, Z., Ciais, P., Prentice, I., Gentine, P., Makowski, D., Bastos, A., Luo, X., Green, J., Stoy, P., Yang, H., & Hajima, T. (2022). Atmospheric dryness reduces photosynthesis along a large range of soil water deficits. Nature Communications, 13(1). doi:10.1038/s41467-022-28652-7
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  Both low soil water content (SWC) and high atmospheric dryness (vapor pressure deficit, VPD) can negatively affect terrestrial gross primary production (GPP). The sensitivity of GPP to soil versus atmospheric dryness is difficult to disentangle, however, because of their covariation. Using global eddy-covariance observations, here we show that a decrease in SWC is not universally associated with GPP reduction. GPP increases in response to decreasing SWC when SWC is high and decreases only when SWC is below a threshold. By contrast, the sensitivity of GPP to an increase of VPD is always negative across the full SWC range. We further find canopy conductance decreases with increasing VPD (irrespective of SWC), and with decreasing SWC on drier soils. Maximum photosynthetic assimilation rate has negative sensitivity to VPD, and a positive sensitivity to decreasing SWC when SWC is high. Earth System Models underestimate the negative effect of VPD and the positive effect of SWC on GPP such that they should underestimate the GPP reduction due to increasing VPD in future climates.
• Green, J. K., Ballantyne, A. P., Abramoff, R., Gentine, P., Makowski, D., & Ciais, P. (2022). Surface temperatures reveal the patterns of vegetation water stress and their environmental drivers across the tropical Americas. Global Change Biology. doi:10.1111/gcb.16139
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  Vegetation is a key component in the global carbon cycle as it stores ~450 GtC as biomass, and removes about a third of anthropogenic CO2 emissions. However, in some regions, the rate of plant carbon uptake is beginning to slow, largely because of water stress. Here, we develop a new observation-based methodology to diagnose vegetation water stress and link it to environmental drivers. We used the ratio of remotely sensed land surface to near surface atmospheric temperatures (LST/Tair ) to represent vegetation water stress, and built regression tree models (random forests) to assess the relationship between LST/Tair and the main environmental drivers of surface energy fluxes in the tropical Americas. We further determined ecosystem traits associated with water stress and surface energy partitioning, pinpointed critical thresholds for water stress, and quantified changes in ecosystem carbon uptake associated with crossing these critical thresholds. We found that the top drivers of LST/Tair , explaining over a quarter of its local variability in the study region, are (1) radiation, in 58% of the study region; (2) water supply from precipitation, in 30% of the study region; and (3) atmospheric water demand from vapor pressure deficits (VPD), in 22% of the study region. Regions in which LST/Tair variation is driven by radiation are located in regions of high aboveground biomass or at high elevations, while regions in which LST/Tair is driven by water supply from precipitation or atmospheric demand tend to have low species richness. Carbon uptake by photosynthesis can be reduced by up to 80% in water-limited regions when critical thresholds for precipitation and air dryness are exceeded simultaneously, that is, as compound events. Our results demonstrate that vegetation structure and diversity can be important for regulating surface energy and carbon fluxes over tropical regions.
• Green, J., & Keenan, T. (2022). The limits of forest carbon sequestration. Science, 376(6594). doi:10.1126/science.abo6547
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  Current models may be overestimating the sequestration potential of forests.
• Yang, H., Ciais, P., Wigneron, J., Chave, J., Cartus, O., Chen, X., Fan, L., Green, J., Huang, Y., Joetzjer, E., Kay, H., Makowski, D., Maignan, F., Santoro, M., Tao, S., Liu, L., & Yao, Y. (2022). Climatic and biotic factors influencing regional declines and recovery of tropical forest biomass from the 2015/16 El Ni~no. Proceedings of the National Academy of Sciences of the United States of America, 119(26). doi:10.1073/pnas.2101388119
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  The 2015/16 El Ni~no brought severe drought and record-breaking temperatures in the tropics. Here, using satellite-based L-band microwave vegetation optical depth, we mapped changes of above-ground biomass (AGB) during the drought and in subsequent years up to 2019. Over more than 60% of drought-affected intact forests, AGB reduced during the drought, except in the wettest part of the central Amazon, where it declined 1 y later. By the end of 2019, only 40% of AGB reduced intact forests had fully recovered to the predrought level. Using random-forest models, we found that the magnitude of AGB losses during the drought was mainly associated with regionally distinct patterns of soil water deficits and soil clay content. For the AGB recovery, we found strong influences of AGB losses during the drought and of γ. γ is a parameter related to canopy structure and is defined as the ratio of two relative height (RH) metrics of Geoscience Laser Altimeter System (GLAS) waveform data - RH25 (25% energy return height) and RH100 (100% energy return height; i.e., top canopy height). A high γ may reflect forests with a tall understory, thick and closed canopy, and/or without degradation. Such forests with a high γ (γ ≥ 0.3) appear to have a stronger capacity to recover than low-γ ones. Our results highlight the importance of forest structure when predicting the consequences of future drought stress in the tropics.
• Chen, X., Ciais, P., Maignan, F., Zhang, Y., Bastos, A., Liu, L., Bacour, C., Fan, L., Gentine, P., Goll, D., Green, J., Kim, H., Li, L., Liu, Y., Peng, S., Tang, H., Viovy, N., Wigneron, J., Wu, J., , Yuan, W., et al. (2021). Vapor Pressure Deficit and Sunlight Explain Seasonality of Leaf Phenology and Photosynthesis Across Amazonian Evergreen Broadleaved Forest. Global Biogeochemical Cycles, 35(6). doi:10.1029/2020GB006893
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  Amazonian evergreen forests show distinct canopy phenology and photosynthetic seasonality but the climatic triggers are not well understood. This imposes a challenge for modeling leaf phenology and photosynthesis seasonality in land surface models (LSMs) across Amazonian evergreen forest biome. On continental scale, we tested two climatic triggers suggested by site observations, vapor pressure deficit (VPD), and short-wave incoming radiation (SW) for defining leaf shedding and incorporated VPD- and SW-triggered new canopy phenology modules in the ORCHIDEE LSM (hereafter VPD-AP and SW-AP versions). Our results show that both VPD and SW are plausible precursors of large scale litterfall seasonality across the basin by comparing against in situ data from 14 sites. Specially, both VPD-AP and SW-AP correctly capture the increases in litterfall during the early dry season, followed by a flush of new leaves with increasing photosynthetic rates during the later dry season. The VPD-AP version performs better than the SW-AP version in capturing a dry-season increase of photosynthesis across the wet Amazonia areas where mean annual precipitation exceeds 2,000 mm yr−1, consistent with previous satellite data analysis. Both VPD-AP and SW-AP model versions perform well in northern, central and southern Amazon regions where the SW seasonality is unimodal, but miss the seasonality of satellite GPP proxies in the eastern region off the coast of Guyana shield where SW seasonality is bimodal. Our findings imply that atmospheric dryness and sunlight availability likely explain the seasonality of leaf shedding and leaf flush processes, respectively, and consequently control canopy photosynthesis in Amazonian evergreen forests.
• Kwon, M., Ballantyne, A., Ciais, P., Bastos, A., Chevallier, F., Liu, Z., Green, J., Qiu, C., & Kimball, J. (2021). Siberian 2020 heatwave increased spring CO2uptake but not annual CO2uptake. Environmental Research Letters, 16(12). doi:10.1088/1748-9326/ac358b
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  Siberia experienced an unprecedented strong and persistent heatwave in winter to spring of 2020. Using bottom-up and top-down approaches, we evaluated seasonal and annual CO2 fluxes of 2020 in the northern hemisphere (north of 30 °N), focusing on Siberia where the pronounced heatwave occurred. We found that, over Siberia, CO2 respiration loss in response to the pronounced positive winter temperature anomaly was greater than in previous years. However, continued warming in the spring enhanced photosynthetic CO2 uptake, resulting in the largest seasonal transition in net ecosystem CO2 exchange; that is, the largest magnitude of the switch from the net CO2 loss in winter to net CO2 uptake in spring until June. However, this exceptional transition was followed by the largest reduction in CO2 uptake in late summer due to multiple environmental constraints, including a soil moisture deficit. Despite a substantial increase of CO2 uptake by 22 ± 9 gC m-2 in the spring in response to the heatwave, the mean annual CO2 uptake over Siberia was slightly lower (3 ± 13 gC m-2yr-1) than the average of the previous five years. These results highlight the highly dynamic response of seasonal carbon fluxes to extreme temperature anomalies at high latitudes, indicating a seasonal compensation between abnormal uptake and release of CO2 in response to extreme warmth that may limit carbon sink capacity in high northern latitudes.
• Fu, Z., Ciais, P., Bastos, A., Stoy, P. C., Yang, H., Green, J. K., Wang, B., Yu, K., Huang, Y., Knohl, A., Šigut, L., Gharun, M., Cuntz, M., Arriga, N., Roland, M., Peichl, M., Migliavacca, M., Cremonese, E., Varlagin, A., , Brümmer, C., et al. (2020). Sensitivity of gross primary productivity to climatic drivers during the summer drought of 2018 in Europe. Philosophical Transactions of the Royal Society B. doi:10.1098/rstb.2019.0747
• Green, J. K., Gentine, P., Zhang, Y., Berry, J. A., & Ciais, P. (2020). Amazon rainforest increases photosynthesis in reponse to atmospheric dryness. Science Advances. doi:10.5194/egusphere-egu2020-5195
• Gentine, P., Green, J. K., Guérin, M., Humphrey, V., Seneviratne, S. I., Zhang, Y., & Zhou, S. (2019). Coupling between the terrestrial carbon and water cycles—a review. Environmental Research Letters. doi:10.1088/1748-9326/ab22d6
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  Abstract The terrestrial carbon and water cycles are strongly coupled. As atmospheric carbon dioxide concentration increases, climate and the coupled hydrologic cycle are modified, thus altering the terrestrial water cycle and the availability of soil moisture necessary for plants’ carbon dioxide uptake. Concomitantly, rising surface carbon dioxide concentrations also modify stomatal (small pores at the leaf surface) regulation as well as biomass, thus altering ecosystem photosynthesis and transpiration rates. Those coupled changes have profound implications for the predictions of the carbon and water cycles. This paper reviews the main mechanisms behind the coupling of the terrestrial water and carbon cycles. We especially focus on the key role of dryness (atmospheric dryness and terrestrial water availability) on carbon uptake, as well as the predicted impact of rising carbon dioxide on the water cycle. Challenges related to this coupling and the necessity to constrain it based on observations are finally discussed.
• Gentine, P., Massmann, A., Lintner, B. R., Alemohammad, H., Fu, R., Green, J. K., Kennedy, D., & Arellano, J. V. (2019). Land–atmosphere interactions in the tropics – a review. Environmental Research Letters. doi:10.5194/hess-23-4171-2019
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  Abstract. The continental tropics play a leading role in the terrestrial energy, water, and carbon cycles. Land–atmosphere interactions are integral in the regulation of these fluxes across multiple spatial and temporal scales over tropical continents. We review here some of the important characteristics of tropical continental climates and how land–atmosphere interactions regulate them. Along with a wide range of climates, the tropics manifest a diverse array of land–atmosphere interactions. Broadly speaking, in tropical rainforest climates, light and energy are typically more limiting than precipitation and water supply for photosynthesis and evapotranspiration (ET), whereas in savanna and semi-arid climates, water is the critical regulator of surface fluxes and land–atmosphere interactions. We discuss the impact of the land surface, how it affects shallow and deep clouds, and how these clouds in turn can feed back to the surface by modulating surface radiation and precipitation. Some results from recent research suggest that shallow clouds may be especially critical to land–atmosphere interactions. On the other hand, the impact of land-surface conditions on deep convection appears to occur over larger, nonlocal scales and may be a more relevant land–atmosphere feedback mechanism in transitional dry-to-wet regions and climate regimes.
• Green, J. K., Seneviratne, S. I., Berg, A., Findell, K. L., Hagemann, S., Lawrence, D. M., & Gentine, P. (2019). Large influence of soil moisture on long-term terrestrial carbon uptake. Nature. doi:10.1038/s41586-018-0848-x
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  Although the terrestrial biosphere absorbs about 25 per cent of anthropogenic carbon dioxide (CO2) emissions, the rate of land carbon uptake remains highly uncertain, leading to uncertainties in climate projections1,2. Understanding the factors that limit or drive land carbon storage is therefore important for improving climate predictions. One potential limiting factor for land carbon uptake is soil moisture, which can reduce gross primary production through ecosystem water stress3,4, cause vegetation mortality5 and further exacerbate climate extremes due to land–atmosphere feedbacks6. Previous work has explored the impact of soil-moisture availability on past carbon-flux variability3,7,8. However, the influence of soil-moisture variability and trends on the long-term carbon sink and the mechanisms responsible for associated carbon losses remain uncertain. Here we use the data output from four Earth system models9 from a series of experiments to analyse the responses of terrestrial net biome productivity to soil-moisture changes, and find that soil-moisture variability and trends induce large CO2 fluxes (about two to three gigatons of carbon per year; comparable with the land carbon sink itself1) throughout the twenty-first century. Subseasonal and interannual soil-moisture variability generate CO2 as a result of the nonlinear response of photosynthesis and net ecosystem exchange to soil-water availability and of the increased temperature and vapour pressure deficit caused by land–atmosphere interactions. Soil-moisture variability reduces the present land carbon sink, and its increase and drying trends in several regions are expected to reduce it further. Our results emphasize that the capacity of continents to act as a future carbon sink critically depends on the nonlinear response of carbon fluxes to soil moisture and on land–atmosphere interactions. This suggests that the increasing trend in carbon uptake rate may not be sustained past the middle of the century and could result in accelerated atmospheric CO2 growth. Earth system models suggest that soil-moisture variability and trends will induce large carbon releases throughout the twenty-first century.
• Alemohammad, H., Fang, B., Konings, A. G., Aires, F., Green, J. K., Kolassa, J., Miralles, D. G., Prigent, C., & Gentine, P. (2017). Water, Energy, and Carbon with Artificial Neural Networks (WECANN): a statistically based estimate of global surface turbulent fluxes and gross primary productivity using solar-induced fluorescence. Biogeosciences. doi:10.5194/bg-14-4101-2017
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  A new global estimate of surface turbulent fluxes, latent heat flux (LE) and sensible heat flux (H), and gross primary production (GPP) is developed using a machine learning approach informed by novel remotely sensed Solar-Induced Fluorescence (SIF) and other radiative and meteorological variables. This is the first study to jointly retrieve LE, H and GPP using SIF observations. The approach uses an artificial neural network (ANN) with a target dataset generated from three independent data sources, weighted based on triple collocation (TC) algorithm. The new retrieval, named Water, Energy, and Carbon with Artificial Neural Networks (WECANN), provides estimates of LE, H and GPP from 2007 to 2015 at 1° × 1° spatial resolution and on monthly time resolution. The quality of ANN training is assessed using the target data, and the WECANN retrievals are evaluated using eddy covariance tower estimates from FLUXNET network across various climates and conditions. When compared to eddy covariance estimates, WECANN typically outperforms other products, particularly for sensible and latent heat fluxes. Analysing WECANN retrievals across three extreme drought and heatwave events demonstrates the capability of the retrievals in capturing the extent of these events. Uncertainty estimates of the retrievals are analysed and the inter-annual variability in average global and regional fluxes show the impact of distinct climatic events - such as the 2015 El Niño - on surface turbulent fluxes and GPP.
• Green, J., Konings, A., Alemohammad, S., Berry, J., Entekhabi, D., Kolassa, J., Lee, J., & Gentine, P. (2017). Regionally strong feedbacks between the atmosphere and terrestrial biosphere. Nature Geoscience, 10(6). doi:10.1038/ngeo2957
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  The terrestrial biosphere and atmosphere interact through a series of feedback loops. Variability in terrestrial vegetation growth and phenology can modulate fluxes of water and energy to the atmosphere, and thus affect the climatic conditions that in turn regulate vegetation dynamics. Here we analyse satellite observations of solar-induced fluorescence, precipitation, and radiation using a multivariate statistical technique. We find that biosphere-atmosphere feedbacks are globally widespread and regionally strong: They explain up to 30% of precipitation and surface radiation variance in regions where feedbacks occur. Substantial biosphere-precipitation feedbacks are often found in regions that are transitional between energy and water limitation, such as semi-arid or monsoonal regions. Substantial biosphere-radiation feedbacks are often present in several moderately wet regions and in the Mediterranean, where precipitation and radiation increase vegetation growth. Enhancement of latent and sensible heat transfer from vegetation accompanies this growth, which increases boundary layer height and convection, affecting cloudiness, and consequently incident surface radiation. Enhanced evapotranspiration can increase moist convection, leading to increased precipitation. Earth system models underestimate these precipitation and radiation feedbacks mainly because they underestimate the biosphere response to radiation and water availability. We conclude that biosphere-atmosphere feedbacks cluster in specific climatic regions that help determine the net CO2 balance of the biosphere.