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Nicholas C. Parazoo
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California, USA

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Preprint content
Published: 09 July 2021
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ACS Style

Yan Yang; A. Anthony Bloom; Shuang Ma; Paul Levine; Alexander Norton; Nicholas C. Parazoo; John T. Reager; John Worden; Gregory R. Quetin; T. Luke Smallman; Mathew Williams; Liang Xu; Sassan Saatchi. Supplementary material to "CARDAMOM-FluxVal Version 1.0: a FLUXNET-based Validation System for CARDAMOM Carbon and Water Flux Estimates". 2021, 1 .

AMA Style

Yan Yang, A. Anthony Bloom, Shuang Ma, Paul Levine, Alexander Norton, Nicholas C. Parazoo, John T. Reager, John Worden, Gregory R. Quetin, T. Luke Smallman, Mathew Williams, Liang Xu, Sassan Saatchi. Supplementary material to "CARDAMOM-FluxVal Version 1.0: a FLUXNET-based Validation System for CARDAMOM Carbon and Water Flux Estimates". . 2021; ():1.

Chicago/Turabian Style

Yan Yang; A. Anthony Bloom; Shuang Ma; Paul Levine; Alexander Norton; Nicholas C. Parazoo; John T. Reager; John Worden; Gregory R. Quetin; T. Luke Smallman; Mathew Williams; Liang Xu; Sassan Saatchi. 2021. "Supplementary material to "CARDAMOM-FluxVal Version 1.0: a FLUXNET-based Validation System for CARDAMOM Carbon and Water Flux Estimates"." , no. : 1.

Preprint content
Published: 09 July 2021
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Land-atmosphere carbon and water exchanges have large uncertainty in land surface and biosphere models. Using observations to reduce land biosphere model structural and parametric errors is a key priority for both understanding and accurately predicting carbon and water fluxes. Recent implementations of the Bayesian CARDAMOM model-data fusion framework have yielded key insights into ecosystem carbon and water cycling. CARDAMOM analyses—informed by co-located C and H2O flux observations—have exhibited considerable skill in both representing the variability of assimilated observations and predicting withheld observations. While CARDAMOM model configurations (namely CARDAMOM-compatible biogeochemical model structures) have been continuously developed to accommodate new scientific challenges and an expanding variety of observational constraints, there has so far been no concerted effort to globally and systematically validate CARDAMOM performance across individual model-data fusion configurations. Here we use the FLUXNET-2015 dataset—an ensemble of 200+ eddy covariance flux tower sites—to formulate a concerted benchmarking framework for CARDAMOM carbon (GPP, NEE) and water (ET) flux estimates (CARDAMOM-FLUXVal version 1.0). We present a concise set of skill metrics to evaluate CARDAMOM performance against both assimilated and withheld FLUXNET-2015 GPP, NEE and ET data. We further demonstrate the potential for tailored CARDAMOM evaluations by categorizing performance in terms of (i) individual land cover types, (ii) monthly, annual and mean fluxes, and (iii) length of assimilation data. The CARDAMOM benchmarking system—along with CARDAMOM driver files provided—can be readily repeated to support both the intercomparison between existing CARDAMOM model configurations and the formulation, development and testing of new CARDAMOM model structures.

ACS Style

Yan Yang; A. Anthony Bloom; Shuang Ma; Paul Levine; Alexander Norton; Nicholas C. Parazoo; John T. Reager; John Worden; Gregory R. Quetin; T. Luke Smallman; Mathew Williams; Liang Xu; Sassan Saatchi. CARDAMOM-FluxVal Version 1.0: a FLUXNET-based Validation System for CARDAMOM Carbon and Water Flux Estimates. 2021, 2021, 1 -25.

AMA Style

Yan Yang, A. Anthony Bloom, Shuang Ma, Paul Levine, Alexander Norton, Nicholas C. Parazoo, John T. Reager, John Worden, Gregory R. Quetin, T. Luke Smallman, Mathew Williams, Liang Xu, Sassan Saatchi. CARDAMOM-FluxVal Version 1.0: a FLUXNET-based Validation System for CARDAMOM Carbon and Water Flux Estimates. . 2021; 2021 ():1-25.

Chicago/Turabian Style

Yan Yang; A. Anthony Bloom; Shuang Ma; Paul Levine; Alexander Norton; Nicholas C. Parazoo; John T. Reager; John Worden; Gregory R. Quetin; T. Luke Smallman; Mathew Williams; Liang Xu; Sassan Saatchi. 2021. "CARDAMOM-FluxVal Version 1.0: a FLUXNET-based Validation System for CARDAMOM Carbon and Water Flux Estimates." 2021, no. : 1-25.

Preprint content
Published: 17 June 2021
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Stephanie G. Stettz; Nicholas C. Parazoo; A. Anthony Bloom; Peter D. Blanken; David R. Bowling; Sean P. Burns; Cédric Bacour; Fabienne Maignan; Brett Raczka; Alexander J. Norton; Ian Baker; Mathew Williams; Mingjie Shi; Yongguang Zhang; Bo Qiu. Supplementary material to "Resolving temperature limitation on spring productivity in an evergreen conifer forest using a model-data fusion framework". 2021, 1 .

AMA Style

Stephanie G. Stettz, Nicholas C. Parazoo, A. Anthony Bloom, Peter D. Blanken, David R. Bowling, Sean P. Burns, Cédric Bacour, Fabienne Maignan, Brett Raczka, Alexander J. Norton, Ian Baker, Mathew Williams, Mingjie Shi, Yongguang Zhang, Bo Qiu. Supplementary material to "Resolving temperature limitation on spring productivity in an evergreen conifer forest using a model-data fusion framework". . 2021; ():1.

Chicago/Turabian Style

Stephanie G. Stettz; Nicholas C. Parazoo; A. Anthony Bloom; Peter D. Blanken; David R. Bowling; Sean P. Burns; Cédric Bacour; Fabienne Maignan; Brett Raczka; Alexander J. Norton; Ian Baker; Mathew Williams; Mingjie Shi; Yongguang Zhang; Bo Qiu. 2021. "Supplementary material to "Resolving temperature limitation on spring productivity in an evergreen conifer forest using a model-data fusion framework"." , no. : 1.

Model description paper
Published: 17 June 2021 in Geoscientific Model Development
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When estimating fossil fuel carbon dioxide (FFCO2) emissions from observed CO2 concentrations, the accuracy can be hampered by biogenic carbon exchanges during the growing season, even for urban areas where strong fossil fuel emissions are found. While biogenic carbon fluxes have been studied extensively across natural vegetation types, biogenic carbon fluxes within an urban area have been challenging to quantify due to limited observations and differences between urban and rural regions. Here we developed a simple model representation, i.e., Solar-Induced Fluorescence (SIF) for Modeling Urban biogenic Fluxes (“SMUrF”), that estimates the gross primary production (GPP) and ecosystem respiration (Reco) over cities around the globe. Specifically, we leveraged space-based SIF, machine learning, eddy-covariance (EC) flux data, and ancillary remote-sensing-based products, and we developed algorithms to gap-fill fluxes for urban areas. Grid-level hourly mean net ecosystem exchange (NEE) fluxes are extracted from SMUrF and evaluated against (1) non-gap-filled measurements at 67 EC sites from FLUXNET during 2010–2014 (r>0.7 for most data-rich biomes), (2) independent observations at two urban vegetation and two crop EC sites over Indianapolis from August 2017 to December 2018 (r=0.75), and (3) an urban biospheric model based on fine-grained land cover classification in Los Angeles (r=0.83). Moreover, we compared SMUrF-based NEE with inventory-based FFCO2 emissions over 40 cities and addressed the urban–rural contrast in both the magnitude and timing of CO2 fluxes. To illustrate the application of SMUrF, we used it to interpret a few summertime satellite tracks over four cities and compared the urban–rural gradient in column CO2 (XCO2) anomalies due to NEE against XCO2 enhancements due to FFCO2 emissions. With rapid advances in space-based measurements and increased sampling of SIF and CO2 measurements over urban areas, SMUrF can be useful to inform the biogenic CO2 fluxes over highly vegetated regions during the growing season.

ACS Style

Dien Wu; John C. Lin; Henrique F. Duarte; Vineet Yadav; Nicholas C. Parazoo; Tomohiro Oda; Eric A. Kort. A model for urban biogenic CO2 fluxes: Solar-Induced Fluorescence for Modeling Urban biogenic Fluxes (SMUrF v1). Geoscientific Model Development 2021, 14, 3633 -3661.

AMA Style

Dien Wu, John C. Lin, Henrique F. Duarte, Vineet Yadav, Nicholas C. Parazoo, Tomohiro Oda, Eric A. Kort. A model for urban biogenic CO2 fluxes: Solar-Induced Fluorescence for Modeling Urban biogenic Fluxes (SMUrF v1). Geoscientific Model Development. 2021; 14 (6):3633-3661.

Chicago/Turabian Style

Dien Wu; John C. Lin; Henrique F. Duarte; Vineet Yadav; Nicholas C. Parazoo; Tomohiro Oda; Eric A. Kort. 2021. "A model for urban biogenic CO2 fluxes: Solar-Induced Fluorescence for Modeling Urban biogenic Fluxes (SMUrF v1)." Geoscientific Model Development 14, no. 6: 3633-3661.

Preprint content
Published: 17 June 2021
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The flow of carbon through terrestrial ecosystems and the response to climate is a critical but highly uncertain process in the global carbon cycle. However, with a rapidly expanding array of in situ and satellite data, there is an opportunity to improve our mechanistic understanding of the carbon (C) cycle’s response to land use and climate change. Uncertainty in temperature limitation on productivity pose a significant challenge to predicting the response of ecosystem carbon fluxes to a changing climate. Here we diagnose and quantitatively resolve environmental limitations on growing season onset of gross primary production (GPP) using nearly two decades of meteorological and C flux data (2000–2018) at a subalpine evergreen forest in Colorado USA. We implement the CARDAMOM model-data fusion network to resolve the temperature sensitivity of spring GPP. To capture a GPP temperature limitation – a critical component of integrated sensitivity of GPP to temperature – we introduced a cold temperature scaling function in CARDAMOM to regulate photosynthetic productivity. We found that GPP was gradually inhibited at temperature below 6.0 °C (±2.6 °C) and completely inhibited below −7.1 °C (±1.1 °C). The addition of this scaling factor improved the model’s ability to replicate spring GPP at interannual and decadal time scales (r = 0.88), relative to the nominal CARDAMOM configuration (r = 0.47), and improved spring GPP model predictability outside of the data assimilation training period (r = 0.88) . While cold temperature limitation has an important influence on spring GPP, it does not have a significant impact on integrated growing season GPP, revealing that other environmental controls, such as precipitation, play a more important role in annual productivity. This study highlights growing season onset temperature as a key limiting factor for spring growth in winter-dormant evergreen forests, which is critical in understanding future responses to climate change.

ACS Style

Stephanie G. Stettz; Nicholas C. Parazoo; A. Anthony Bloom; Peter D. Blanken; David R. Bowling; Sean P. Burns; Cédric Bacour; Fabienne Maignan; Brett Raczka; Alexander J. Norton; Ian Baker; Mathew Williams; Mingjie Shi; Yongguang Zhang; Bo Qiu. Resolving temperature limitation on spring productivity in an evergreen conifer forest using a model-data fusion framework. 2021, 2021, 1 -24.

AMA Style

Stephanie G. Stettz, Nicholas C. Parazoo, A. Anthony Bloom, Peter D. Blanken, David R. Bowling, Sean P. Burns, Cédric Bacour, Fabienne Maignan, Brett Raczka, Alexander J. Norton, Ian Baker, Mathew Williams, Mingjie Shi, Yongguang Zhang, Bo Qiu. Resolving temperature limitation on spring productivity in an evergreen conifer forest using a model-data fusion framework. . 2021; 2021 ():1-24.

Chicago/Turabian Style

Stephanie G. Stettz; Nicholas C. Parazoo; A. Anthony Bloom; Peter D. Blanken; David R. Bowling; Sean P. Burns; Cédric Bacour; Fabienne Maignan; Brett Raczka; Alexander J. Norton; Ian Baker; Mathew Williams; Mingjie Shi; Yongguang Zhang; Bo Qiu. 2021. "Resolving temperature limitation on spring productivity in an evergreen conifer forest using a model-data fusion framework." 2021, no. : 1-24.

Journal article
Published: 08 June 2021 in Journal of Geophysical Research: Biogeosciences
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The increase in wildfire occurrence and severity seen over the past decades in the boreal and Arctic biomes is expected to continue in the future in response to rapid climate change in this region. Recent studies documented positive trends in gross primary productivity (GPP) for Arctic boreal biomes driven by warming, but it is unclear how GPP trends are affected by wildfires. Here, we used satellite vegetation observations and environmental data with a diagnostic GPP model to analyze recovery from large fires in Alaska over the period 2000‐2019. We confirmed earlier findings that warmer‐than‐average years provide favorable climate conditions for vegetation growth, leading to a GPP increase of 1 Tg C yr‐1, contributed mainly from enhanced productivity in the early growing season. However, higher temperatures increase the risk of wildfire occurrence leading to direct carbon loss over a period of 1‐3 years. While mortality related to severe wildfires reduce ecosystem productivity, post‐fire productivity in moderately burned areas shows a significant positive trend. The rapid GPP recovery following fires reported here might be favorable for maintaining the region’s net carbon sink, but wildfires can indirectly promote the release of long‐term stored carbon in the permafrost. With the projected increase in severity and frequency of wildfires in the future, we expect a reduction of GPP and therefore amplification of climate warming in this region.

ACS Style

Nima Madani; Nicholas C. Parazoo; John S. Kimball; Rolf H. Reichle; Abhishek Chatterjee; Jennifer D. Watts; Sassan Saatchi; Zhihua Liu; Arthur Endsley; Torbern Tagesson; Brendan M. Rogers; Liang Xu; Jonathan A. Wang; Troy Magney; Charles E. Miller. The Impacts of Climate and Wildfire on Ecosystem Gross Primary Productivity in Alaska. Journal of Geophysical Research: Biogeosciences 2021, 126, 1 .

AMA Style

Nima Madani, Nicholas C. Parazoo, John S. Kimball, Rolf H. Reichle, Abhishek Chatterjee, Jennifer D. Watts, Sassan Saatchi, Zhihua Liu, Arthur Endsley, Torbern Tagesson, Brendan M. Rogers, Liang Xu, Jonathan A. Wang, Troy Magney, Charles E. Miller. The Impacts of Climate and Wildfire on Ecosystem Gross Primary Productivity in Alaska. Journal of Geophysical Research: Biogeosciences. 2021; 126 (6):1.

Chicago/Turabian Style

Nima Madani; Nicholas C. Parazoo; John S. Kimball; Rolf H. Reichle; Abhishek Chatterjee; Jennifer D. Watts; Sassan Saatchi; Zhihua Liu; Arthur Endsley; Torbern Tagesson; Brendan M. Rogers; Liang Xu; Jonathan A. Wang; Troy Magney; Charles E. Miller. 2021. "The Impacts of Climate and Wildfire on Ecosystem Gross Primary Productivity in Alaska." Journal of Geophysical Research: Biogeosciences 126, no. 6: 1.

Research letter
Published: 07 June 2021 in Geophysical Research Letters
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Responses to COVID-19 have resulted in unintended reductions of city-scale carbon dioxide (CO2) emissions. Here, we detect and estimate decreases in CO2 emissions in Los Angeles and Washington DC/Baltimore during March and April 2020. We present three lines of evidence using methods that have increasing model dependency, including an inverse model to estimate relative emissions changes in 2020 compared to 2018 and 2019. The March decrease (25%) in Washington DC/Baltimore is largely supported by a drop in natural gas consumption associated with a warm spring whereas the decrease in April (33%) correlates with changes in gasoline fuel sales. In contrast, only a fraction of the March (17%) and April (34%) reduction in Los Angeles is explained by traffic declines. Methods and measurements used herein highlight the advantages of atmospheric CO2 observations for providing timely insights into rapidly changing emissions patterns that can empower cities to course-correct CO2 reduction activities efficiently.

ACS Style

Vineet Yadav; Subhomoy Ghosh; Kimberly Mueller; Anna Karion; Geoffrey Roest; Sharon M. Gourdji; Israel Lopez‐Coto; Kevin R. Gurney; Nicholas Parazoo; Kristal R. Verhulst; Jooil Kim; Steve Prinzivalli; Clayton Fain; Thomas Nehrkorn; Marikate Mountain; Ralph F. Keeling; Ray F. Weiss; Riley Duren; Charles E. Miller; James Whetstone. The Impact of COVID‐19 on CO 2 Emissions in the Los Angeles and Washington DC/Baltimore Metropolitan Areas. Geophysical Research Letters 2021, 48, 1 .

AMA Style

Vineet Yadav, Subhomoy Ghosh, Kimberly Mueller, Anna Karion, Geoffrey Roest, Sharon M. Gourdji, Israel Lopez‐Coto, Kevin R. Gurney, Nicholas Parazoo, Kristal R. Verhulst, Jooil Kim, Steve Prinzivalli, Clayton Fain, Thomas Nehrkorn, Marikate Mountain, Ralph F. Keeling, Ray F. Weiss, Riley Duren, Charles E. Miller, James Whetstone. The Impact of COVID‐19 on CO 2 Emissions in the Los Angeles and Washington DC/Baltimore Metropolitan Areas. Geophysical Research Letters. 2021; 48 (11):1.

Chicago/Turabian Style

Vineet Yadav; Subhomoy Ghosh; Kimberly Mueller; Anna Karion; Geoffrey Roest; Sharon M. Gourdji; Israel Lopez‐Coto; Kevin R. Gurney; Nicholas Parazoo; Kristal R. Verhulst; Jooil Kim; Steve Prinzivalli; Clayton Fain; Thomas Nehrkorn; Marikate Mountain; Ralph F. Keeling; Ray F. Weiss; Riley Duren; Charles E. Miller; James Whetstone. 2021. "The Impact of COVID‐19 on CO 2 Emissions in the Los Angeles and Washington DC/Baltimore Metropolitan Areas." Geophysical Research Letters 48, no. 11: 1.

Journal article
Published: 14 May 2021 in Journal of Geophysical Research: Biogeosciences
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The boreal forest is a major contributor to the global climate system, therefore, reducing uncertainties in how the forest will respond to a changing climate is critical. One source of uncertainty is the timing and drivers of the spring transition. Remote sensing can provide important information on this transition, but persistent foliage greenness, seasonal snow cover, and a high prevalence of mixed forest stands (both deciduous and evergreen species) complicate interpretation of these signals. We collected tower‐based remotely sensed data (reflectance‐based vegetation indices and Solar‐Induced Chlorophyll Fluorescence (SIF)), stem radius measurements, gross primary productivity, and environmental conditions in a boreal mixed forest stand. Evaluation of this dataset shows a two‐phased spring transition. The first phase is the reactivation of photosynthesis and transpiration in evergreens, marked by an increase in relative SIF, and is triggered by thawed stems, warm air temperatures and increased available soil moisture. The second phase is a reduction in bulk photoprotective pigments in evergreens, marked by an increase in the Chlorophyll‐Carotenoid Index. Deciduous leaf‐out occurs during this phase, marked by an increase in all remotely sensed metrics. The second phase is controlled by soil thaw. Our results demonstrate that remote sensing metrics can be used to detect specific physiological changes in boreal tree species during the spring transition. The two‐phased transition explains inconsistencies in remote sensing estimates of the timing and drivers of spring recovery. Our results imply that satellite‐based observations will improve by using a combination of vegetation indices and SIF, along with species distribution information.

ACS Style

Zoe Pierrat; Magali F. Nehemy; Alexandre Roy; Troy Magney; Nicholas C. Parazoo; Colin Laroque; Christoforos Pappas; Oliver Sonnentag; Katja Grossmann; David R. Bowling; Ulli Seibt; Alexandra Ramirez; Bruce Johnson; Warren Helgason; Alan Barr; Jochen Stutz. Tower‐Based Remote Sensing Reveals Mechanisms Behind a Two‐phased Spring Transition in a Mixed‐Species Boreal Forest. Journal of Geophysical Research: Biogeosciences 2021, 126, 1 .

AMA Style

Zoe Pierrat, Magali F. Nehemy, Alexandre Roy, Troy Magney, Nicholas C. Parazoo, Colin Laroque, Christoforos Pappas, Oliver Sonnentag, Katja Grossmann, David R. Bowling, Ulli Seibt, Alexandra Ramirez, Bruce Johnson, Warren Helgason, Alan Barr, Jochen Stutz. Tower‐Based Remote Sensing Reveals Mechanisms Behind a Two‐phased Spring Transition in a Mixed‐Species Boreal Forest. Journal of Geophysical Research: Biogeosciences. 2021; 126 (5):1.

Chicago/Turabian Style

Zoe Pierrat; Magali F. Nehemy; Alexandre Roy; Troy Magney; Nicholas C. Parazoo; Colin Laroque; Christoforos Pappas; Oliver Sonnentag; Katja Grossmann; David R. Bowling; Ulli Seibt; Alexandra Ramirez; Bruce Johnson; Warren Helgason; Alan Barr; Jochen Stutz. 2021. "Tower‐Based Remote Sensing Reveals Mechanisms Behind a Two‐phased Spring Transition in a Mixed‐Species Boreal Forest." Journal of Geophysical Research: Biogeosciences 126, no. 5: 1.

Journal article
Published: 30 April 2021 in Biogeosciences
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The terrestrial carbon cycle plays a critical role in modulating the interactions of climate with the Earth system, but different models often make vastly different predictions of its behavior. Efforts to reduce model uncertainty have commonly focused on model structure, namely by introducing additional processes and increasing structural complexity. However, the extent to which increased structural complexity can directly improve predictive skill is unclear. While adding processes may improve realism, the resulting models are often encumbered by a greater number of poorly determined or over-generalized parameters. To guide efficient model development, here we map the theoretical relationship between model complexity and predictive skill. To do so, we developed 16 structurally distinct carbon cycle models spanning an axis of complexity and incorporated them into a model–data fusion system. We calibrated each model at six globally distributed eddy covariance sites with long observation time series and under 42 data scenarios that resulted in different degrees of parameter uncertainty. For each combination of site, data scenario, and model, we then predicted net ecosystem exchange (NEE) and leaf area index (LAI) for validation against independent local site data. Though the maximum model complexity we evaluated is lower than most traditional terrestrial biosphere models, the complexity range we explored provides universal insight into the inter-relationship between structural uncertainty, parametric uncertainty, and model forecast skill. Specifically, increased complexity only improves forecast skill if parameters are adequately informed (e.g., when NEE observations are used for calibration). Otherwise, increased complexity can degrade skill and an intermediate-complexity model is optimal. This finding remains consistent regardless of whether NEE or LAI is predicted. Our COMPLexity EXperiment (COMPLEX) highlights the importance of robust observation-based parameterization for land surface modeling and suggests that data characterizing net carbon fluxes will be key to improving decadal predictions of high-dimensional terrestrial biosphere models.

ACS Style

Caroline A. Famiglietti; T. Luke Smallman; Paul A. Levine; Sophie Flack-Prain; Gregory R. Quetin; Victoria Meyer; Nicholas C. Parazoo; Stephanie G. Stettz; Yan Yang; Damien Bonal; A. Anthony Bloom; Mathew Williams; Alexandra G. Konings. Optimal model complexity for terrestrial carbon cycle prediction. Biogeosciences 2021, 18, 2727 -2754.

AMA Style

Caroline A. Famiglietti, T. Luke Smallman, Paul A. Levine, Sophie Flack-Prain, Gregory R. Quetin, Victoria Meyer, Nicholas C. Parazoo, Stephanie G. Stettz, Yan Yang, Damien Bonal, A. Anthony Bloom, Mathew Williams, Alexandra G. Konings. Optimal model complexity for terrestrial carbon cycle prediction. Biogeosciences. 2021; 18 (8):2727-2754.

Chicago/Turabian Style

Caroline A. Famiglietti; T. Luke Smallman; Paul A. Levine; Sophie Flack-Prain; Gregory R. Quetin; Victoria Meyer; Nicholas C. Parazoo; Stephanie G. Stettz; Yan Yang; Damien Bonal; A. Anthony Bloom; Mathew Williams; Alexandra G. Konings. 2021. "Optimal model complexity for terrestrial carbon cycle prediction." Biogeosciences 18, no. 8: 2727-2754.

Review article
Published: 24 March 2021 in Reviews of Geophysics
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A constellation of satellites are now in orbit providing information about terrestrial carbon and water storage and fluxes. These combined observations show that the tropical biosphere has changed significantly in the last two decades from the combined effects of climate variability and land use. Large areas of forest have been cleared in both wet and dry forests, increasing the source of carbon to the atmosphere. Concomitantly, tropical fire emissions have declined, at least until 2016, from changes in land‐use practices and rainfall, increasing the net carbon sink. Measurements of carbon stocks and fluxes from disturbance and recovery and of vegetation photosynthesis show significant regional variability of net biosphere exchange (NBE) and gross primary productivity (GPP) across the tropics and are tied to seasonal and interannual changes in water fluxes and storage. Comparison of satellite based estimates of evapotranspiration (ET), photosynthesis, and the deuterium content of water vapor with patterns of total water storage and rainfall demonstrate the presence of vegetation‐atmosphere interactions and feedback mechanisms across tropical forests. However, these observations of stocks, fluxes and inferred interactions between them do not point unambiguously to either positive or negative feedbacks in carbon and water exchanges. These ambiguities highlight the need for assimilation of these new measurements with Earth System models for a consistent assessment of process interactions, along with focused field campaigns that integrate ground, aircraft and satellite measurements, to quantify the controlling carbon and water processes and their feedback mechanisms.This article is protected by copyright. All rights reserved.

ACS Style

John Worden; Sassan Saatchi; Michael Keller; A. Anthony Bloom; Junjie Liu; Nicholas Parazoo; Joshua B. Fisher; Kevin Bowman; John T. Reager; Kristen Fahy; David Schimel; Rong Fu; Sarah Worden; Yi Yin; Pierre Gentine; Alexandra G. Konings; Gregory R. Quetin; Mathew Williams; Helen Worden; Mingjie Shi; Armineh Barkhordarian. Satellite Observations of the Tropical Terrestrial Carbon Balance and Interactions With the Water Cycle During the 21st Century. Reviews of Geophysics 2021, 59, 1 .

AMA Style

John Worden, Sassan Saatchi, Michael Keller, A. Anthony Bloom, Junjie Liu, Nicholas Parazoo, Joshua B. Fisher, Kevin Bowman, John T. Reager, Kristen Fahy, David Schimel, Rong Fu, Sarah Worden, Yi Yin, Pierre Gentine, Alexandra G. Konings, Gregory R. Quetin, Mathew Williams, Helen Worden, Mingjie Shi, Armineh Barkhordarian. Satellite Observations of the Tropical Terrestrial Carbon Balance and Interactions With the Water Cycle During the 21st Century. Reviews of Geophysics. 2021; 59 (1):1.

Chicago/Turabian Style

John Worden; Sassan Saatchi; Michael Keller; A. Anthony Bloom; Junjie Liu; Nicholas Parazoo; Joshua B. Fisher; Kevin Bowman; John T. Reager; Kristen Fahy; David Schimel; Rong Fu; Sarah Worden; Yi Yin; Pierre Gentine; Alexandra G. Konings; Gregory R. Quetin; Mathew Williams; Helen Worden; Mingjie Shi; Armineh Barkhordarian. 2021. "Satellite Observations of the Tropical Terrestrial Carbon Balance and Interactions With the Water Cycle During the 21st Century." Reviews of Geophysics 59, no. 1: 1.

Preprint content
Published: 04 March 2021
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Responses to COVID-19 have resulted in unintended reductions of city-scale carbon dioxide (CO2) emissions. Here we detect and estimate decreases in CO2 emissions in Los Angeles and Washington DC/Baltimore during March and April 2020. Our analysis uses three lines of evidence with increasing model dependency. The first detects the timing of emissions declines using the variability in atmospheric CO2 observations, the second assesses the continuation of reduced emissions using CO2 enhancements, and the third employs an inverse model to estimate the relative emissions changes in 2020 compared to 2018 and 2019. Emissions declines began in mid-March in both cities. The March decrease (25%) in Washington DC/Baltimore is largely supported by a drop in natural gas consumption associated with a warm spring whereas the decrease in April (33%) correlates with changes in gasoline fuel sales, a proxy for vehicular emissions. In contrast, only a fraction of the March (17%) and April (34%) reduction in Los Angeles is explained by traffic declines, while the remainder of the emissions reduction remains unexplained. To help diagnose such observed changes in emissions, more reliable, publicly available emission information from all significant sectors needs to be made available. Methods and measurements used herein highlight the advantages of atmospheric CO2 observations for providing timely insights into rapidly changing urban emissions patterns that can empower cities to course-correct mitigation activities more efficiently.

ACS Style

Anna Karion; Vineet Yadav; Subhomoy Ghosh; Kimberly Mueller; Geoffrey Roest; Sharon Gourdji; Israel Lopez-Coto; Kevin Gurney; Nicholas Parazoo; Kristal Verhulst; Jooil Kim; Steve Prinzivalli; Clayton Fain; Thomas Nehrkorn; Marikate Mountain; Ralph Keeling; Ray Weiss; Riley Duren; Charles Miller; James Whetstone. The impact of COVID-19 on CO2 emissions in the Los Angeles and Washington DC/Baltimore metropolitan areas . 2021, 1 .

AMA Style

Anna Karion, Vineet Yadav, Subhomoy Ghosh, Kimberly Mueller, Geoffrey Roest, Sharon Gourdji, Israel Lopez-Coto, Kevin Gurney, Nicholas Parazoo, Kristal Verhulst, Jooil Kim, Steve Prinzivalli, Clayton Fain, Thomas Nehrkorn, Marikate Mountain, Ralph Keeling, Ray Weiss, Riley Duren, Charles Miller, James Whetstone. The impact of COVID-19 on CO2 emissions in the Los Angeles and Washington DC/Baltimore metropolitan areas . . 2021; ():1.

Chicago/Turabian Style

Anna Karion; Vineet Yadav; Subhomoy Ghosh; Kimberly Mueller; Geoffrey Roest; Sharon Gourdji; Israel Lopez-Coto; Kevin Gurney; Nicholas Parazoo; Kristal Verhulst; Jooil Kim; Steve Prinzivalli; Clayton Fain; Thomas Nehrkorn; Marikate Mountain; Ralph Keeling; Ray Weiss; Riley Duren; Charles Miller; James Whetstone. 2021. "The impact of COVID-19 on CO2 emissions in the Los Angeles and Washington DC/Baltimore metropolitan areas ." , no. : 1.

Article
Published: 17 February 2021
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Solar-Induced chlorophyll Fluorescence (SIF) provides a powerful proxy for determining forest gross primary production (GPP), particularly in evergreen ecosystems where traditional measures of greenn

ACS Style

Zoe Pierrat; Alexander Norton; Nicholas Parazoo; Andrew Maguire; Katja Grossmann; Troy Magney; Alan Barr; Bruce Johnson; Jochen Stutz. Radiative transfer and viewing geometry considerations for the SIF/GPP relationship. 2021, 1 .

AMA Style

Zoe Pierrat, Alexander Norton, Nicholas Parazoo, Andrew Maguire, Katja Grossmann, Troy Magney, Alan Barr, Bruce Johnson, Jochen Stutz. Radiative transfer and viewing geometry considerations for the SIF/GPP relationship. . 2021; ():1.

Chicago/Turabian Style

Zoe Pierrat; Alexander Norton; Nicholas Parazoo; Andrew Maguire; Katja Grossmann; Troy Magney; Alan Barr; Bruce Johnson; Jochen Stutz. 2021. "Radiative transfer and viewing geometry considerations for the SIF/GPP relationship." , no. : 1.

Data description paper
Published: 10 February 2021 in Earth System Science Data
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Here we present a global and regionally resolved terrestrial net biosphere exchange (NBE) dataset with corresponding uncertainties between 2010–2018: Carbon Monitoring System Flux Net Biosphere Exchange 2020 (CMS-Flux NBE 2020). It is estimated using the NASA Carbon Monitoring System Flux (CMS-Flux) top-down flux inversion system that assimilates column CO2 observations from the Greenhouse Gases Observing Satellite (GOSAT) and NASA's Observing Carbon Observatory 2 (OCO-2). The regional monthly fluxes are readily accessible as tabular files, and the gridded fluxes are available in NetCDF format. The fluxes and their uncertainties are evaluated by extensively comparing the posterior CO2 mole fractions with CO2 observations from aircraft and the NOAA marine boundary layer reference sites. We describe the characteristics of the dataset as the global total, regional climatological mean, and regional annual fluxes and seasonal cycles. We find that the global total fluxes of the dataset agree with atmospheric CO2 growth observed by the surface-observation network within uncertainty. Averaged between 2010 and 2018, the tropical regions range from close to neutral in tropical South America to a net source in Africa; these contrast with the extra-tropics, which are a net sink of 2.5±0.3 Gt C/year. The regional satellite-constrained NBE estimates provide a unique perspective for understanding the terrestrial biosphere carbon dynamics and monitoring changes in regional contributions to the changes of atmospheric CO2 growth rate. The gridded and regional aggregated dataset can be accessed at https://doi.org/10.25966/4v02-c391 (Liu et al., 2020).

ACS Style

Junjie Liu; Latha Baskaran; Kevin Bowman; David Schimel; A. Anthony Bloom; Nicholas C. Parazoo; Tomohiro Oda; Dustin Carroll; Dimitris Menemenlis; Joanna Joiner; Roisin Commane; Bruce Daube; Lucianna V. Gatti; Kathryn McKain; John Miller; Britton B. Stephens; Colm Sweeney; Steven Wofsy. Carbon Monitoring System Flux Net Biosphere Exchange 2020 (CMS-Flux NBE 2020). Earth System Science Data 2021, 13, 299 -330.

AMA Style

Junjie Liu, Latha Baskaran, Kevin Bowman, David Schimel, A. Anthony Bloom, Nicholas C. Parazoo, Tomohiro Oda, Dustin Carroll, Dimitris Menemenlis, Joanna Joiner, Roisin Commane, Bruce Daube, Lucianna V. Gatti, Kathryn McKain, John Miller, Britton B. Stephens, Colm Sweeney, Steven Wofsy. Carbon Monitoring System Flux Net Biosphere Exchange 2020 (CMS-Flux NBE 2020). Earth System Science Data. 2021; 13 (2):299-330.

Chicago/Turabian Style

Junjie Liu; Latha Baskaran; Kevin Bowman; David Schimel; A. Anthony Bloom; Nicholas C. Parazoo; Tomohiro Oda; Dustin Carroll; Dimitris Menemenlis; Joanna Joiner; Roisin Commane; Bruce Daube; Lucianna V. Gatti; Kathryn McKain; John Miller; Britton B. Stephens; Colm Sweeney; Steven Wofsy. 2021. "Carbon Monitoring System Flux Net Biosphere Exchange 2020 (CMS-Flux NBE 2020)." Earth System Science Data 13, no. 2: 299-330.

Journal article
Published: 12 January 2021 in Atmospheric Chemistry and Physics
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We introduce a transformed isentropic coordinate Mθe, defined as the dry air mass under a given equivalent potential temperature surface (θe) within a hemisphere. Like θe, the coordinate Mθe follows the synoptic distortions of the atmosphere but, unlike θe, has a nearly fixed relationship with latitude and altitude over the seasonal cycle. Calculation of Mθe is straightforward from meteorological fields. Using observations from the recent HIAPER Pole-to-Pole Observations (HIPPO) and Atmospheric Tomography Mission (ATom) airborne campaigns, we map the CO2 seasonal cycle as a function of pressure and Mθe, where Mθe is thereby effectively used as an alternative to latitude. We show that the CO2 seasonal cycles are more constant as a function of pressure using Mθe as the horizontal coordinate compared to latitude. Furthermore, short-term variability in CO2 relative to the mean seasonal cycle is also smaller when the data are organized by Mθe and pressure than when organized by latitude and pressure. We also present a method using Mθe to compute mass-weighted averages of CO2 on a hemispheric scale. Using this method with the same airborne data and applying corrections for limited coverage, we resolve the average CO2 seasonal cycle in the Northern Hemisphere (mass-weighted tropospheric climatological average for 2009–2018), yielding an amplitude of 7.8 ± 0.14 ppm and a downward zero-crossing on Julian day 173 ± 6.1 (i.e., late June). Mθe may be similarly useful for mapping the distribution and computing inventories of any long-lived chemical tracer.

ACS Style

Yuming Jin; Ralph F. Keeling; Eric J. Morgan; Eric Ray; Nicholas C. Parazoo; Britton B. Stephens. A mass-weighted isentropic coordinate for mapping chemical tracers and computing atmospheric inventories. Atmospheric Chemistry and Physics 2021, 21, 217 -238.

AMA Style

Yuming Jin, Ralph F. Keeling, Eric J. Morgan, Eric Ray, Nicholas C. Parazoo, Britton B. Stephens. A mass-weighted isentropic coordinate for mapping chemical tracers and computing atmospheric inventories. Atmospheric Chemistry and Physics. 2021; 21 (1):217-238.

Chicago/Turabian Style

Yuming Jin; Ralph F. Keeling; Eric J. Morgan; Eric Ray; Nicholas C. Parazoo; Britton B. Stephens. 2021. "A mass-weighted isentropic coordinate for mapping chemical tracers and computing atmospheric inventories." Atmospheric Chemistry and Physics 21, no. 1: 217-238.

Preprint content
Published: 29 December 2020
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Caroline A. Famiglietti; T. Luke Smallman; Paul A. Levine; Sophie Flack-Prain; Gregory R. Quetin; Victoria Meyer; Nicholas C. Parazoo; Stephanie G. Stettz; Yan Yang; Damien Bonal; A. Anthony Bloom; Mathew Williams; Alexandra G. Konings. Supplementary material to "Optimal model complexity for terrestrial carbon cycle prediction". 2020, 1 .

AMA Style

Caroline A. Famiglietti, T. Luke Smallman, Paul A. Levine, Sophie Flack-Prain, Gregory R. Quetin, Victoria Meyer, Nicholas C. Parazoo, Stephanie G. Stettz, Yan Yang, Damien Bonal, A. Anthony Bloom, Mathew Williams, Alexandra G. Konings. Supplementary material to "Optimal model complexity for terrestrial carbon cycle prediction". . 2020; ():1.

Chicago/Turabian Style

Caroline A. Famiglietti; T. Luke Smallman; Paul A. Levine; Sophie Flack-Prain; Gregory R. Quetin; Victoria Meyer; Nicholas C. Parazoo; Stephanie G. Stettz; Yan Yang; Damien Bonal; A. Anthony Bloom; Mathew Williams; Alexandra G. Konings. 2020. "Supplementary material to "Optimal model complexity for terrestrial carbon cycle prediction"." , no. : 1.

Preprint content
Published: 29 December 2020
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The terrestrial carbon cycle plays a critical role in modulating the interactions of climate with the Earth system, but different models often make vastly different predictions of its behavior. Efforts to reduce model uncertainty have commonly focused on model structure, namely by introducing additional processes and increasing structural complexity. However, the extent to which increased structural complexity can directly improve predictive skill is unclear. While adding processes may improve realism, the resulting models are often encumbered by a greater number of poorly-determined or over-generalized parameters. To guide efficient model development, here we map the theoretical relationship between model complexity and predictive skill. To do so, we developed 16 structurally distinct carbon cycle models spanning an axis of complexity and incorporated them into a model–data fusion system. We calibrated each model at 6 globally-distributed eddy covariance sites with long observation time series and under 42 data scenarios that resulted in different degrees of parameter uncertainty. For each combination of site, data scenario, and model, we then predicted net ecosystem exchange (NEE) and leaf area index (LAI) for validation against independent local site data. Though the maximum model complexity we evaluated is lower than most traditional terrestrial biosphere models, the complexity range we explored provides universal insight into the inter-relationship between structural uncertainty, parametric uncertainty, and model forecast skill. Specifically, increased complexity only improves forecast skill if parameters are adequately informed (e.g., when NEE observations are used for calibration). Otherwise, increased complexity can degrade skill and an intermediate-complexity model is optimal. This finding remains consistent regardless of whether NEE or LAI is predicted. Our COMPLexity EXperiment (COMPLEX) highlights the importance of robust, observation-based parameterization for land surface modeling and suggests that data characterizing net carbon fluxes will be key to improving decadal predictions of high-dimensional terrestrial biosphere models.

ACS Style

Caroline A. Famiglietti; T. Luke Smallman; Paul A. Levine; Sophie Flack-Prain; Gregory R. Quetin; Victoria Meyer; Nicholas C. Parazoo; Stephanie G. Stettz; Yan Yang; Damien Bonal; A. Anthony Bloom; Mathew Williams; Alexandra G. Konings. Optimal model complexity for terrestrial carbon cycle prediction. 2020, 2020, 1 -42.

AMA Style

Caroline A. Famiglietti, T. Luke Smallman, Paul A. Levine, Sophie Flack-Prain, Gregory R. Quetin, Victoria Meyer, Nicholas C. Parazoo, Stephanie G. Stettz, Yan Yang, Damien Bonal, A. Anthony Bloom, Mathew Williams, Alexandra G. Konings. Optimal model complexity for terrestrial carbon cycle prediction. . 2020; 2020 ():1-42.

Chicago/Turabian Style

Caroline A. Famiglietti; T. Luke Smallman; Paul A. Levine; Sophie Flack-Prain; Gregory R. Quetin; Victoria Meyer; Nicholas C. Parazoo; Stephanie G. Stettz; Yan Yang; Damien Bonal; A. Anthony Bloom; Mathew Williams; Alexandra G. Konings. 2020. "Optimal model complexity for terrestrial carbon cycle prediction." 2020, no. : 1-42.

Article
Published: 28 December 2020
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The ACT-America Earth Venture mission conducted five airborne campaigns across four seasons from 2016-2019, to study the transport and fluxes of Greenhouse gases across the eastern United States (US). Unprecedented spatial sampling of atmospheric tracers (CO2, CO, and COS) related to biospheric processes offers opportunities to improve our qualitative and quantitative understanding of seasonal and spatial patterns of biospheric carbon uptake. Here, we examine co-variation of boundary layer enhancements of CO2, CO, and COS across three diverse regions: the crop-dominated Midwest, evergreen-dominated South, and deciduous broadleaf-dominated Northeast. To understand the biogeochemical processes controlling these tracers, we compare the observed co-variation to simulated co-variation resulting from model- and satellite- constrained surface carbon fluxes. We found indication of a common terrestrial biogenic sink of CO2 and COS and secondary production of CO from biogenic sources in summer throughout the eastern US. Stomatal conductance likely drives fluxes through diffusion of CO2 and COS into leaves and emission of biogenic volatile organic compounds into the atmosphere. ACT-America airborne campaigns filled a critical sampling gap in the southern US, providing information about seasonal carbon uptake in southern temperate forests, and demanding a deeper investigation of underlying biological processes and climate sensitivities. Satellite- constrained carbon fluxes capture much of the observed seasonal and spatial variability, but underestimate the magnitude of net CO2 and COS depletion in the Southeast, indicating a stronger than expected net sink in late summer.

ACS Style

Nicholas C Parazoo; Kevin W. Bowman; Bianca C. Baier; Junjie Liu; Meemong Lee; Le Kuai; Yoichi Shiga; Ian T. Baker; Mary Whelan; Sha Feng; Maarten C. Krol; Colm Sweeney; Kenneth J. Davis. Covariation of airborne biogenic tracers (CO2, COS, and CO) supports stronger than expected growing season photosynthetic uptake in the southeastern US. 2020, 1 .

AMA Style

Nicholas C Parazoo, Kevin W. Bowman, Bianca C. Baier, Junjie Liu, Meemong Lee, Le Kuai, Yoichi Shiga, Ian T. Baker, Mary Whelan, Sha Feng, Maarten C. Krol, Colm Sweeney, Kenneth J. Davis. Covariation of airborne biogenic tracers (CO2, COS, and CO) supports stronger than expected growing season photosynthetic uptake in the southeastern US. . 2020; ():1.

Chicago/Turabian Style

Nicholas C Parazoo; Kevin W. Bowman; Bianca C. Baier; Junjie Liu; Meemong Lee; Le Kuai; Yoichi Shiga; Ian T. Baker; Mary Whelan; Sha Feng; Maarten C. Krol; Colm Sweeney; Kenneth J. Davis. 2020. "Covariation of airborne biogenic tracers (CO2, COS, and CO) supports stronger than expected growing season photosynthetic uptake in the southeastern US." , no. : 1.

Research article
Published: 17 December 2020 in Biogeosciences
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Inter-annual variations in the tropical land carbon (C) balance are a dominant component of the global atmospheric CO2 growth rate. Currently, the lack of quantitative knowledge on processes controlling net tropical ecosystem C balance on inter-annual timescales inhibits accurate understanding and projections of land–atmosphere C exchanges. In particular, uncertainty on the relative contribution of ecosystem C fluxes attributable to concurrent forcing anomalies (concurrent effects) and those attributable to the continuing influence of past phenomena (lagged effects) stifles efforts to explicitly understand the integrated sensitivity of a tropical ecosystem to climatic variability. Here we present a conceptual framework – applicable in principle to any land biosphere model – to explicitly quantify net biospheric exchange (NBE) as the sum of anomaly-induced concurrent changes and climatology-induced lagged changes to terrestrial ecosystem C states (NBE = NBECON+NBELAG). We apply this framework to an observation-constrained analysis of the 2001–2015 tropical C balance: we use a data–model integration approach (CARbon DAta-MOdel fraMework – CARDAMOM) to merge satellite-retrieved land-surface C observations (leaf area, biomass, solar-induced fluorescence), soil C inventory data and satellite-based atmospheric inversion estimates of CO2 and CO fluxes to produce a data-constrained analysis of the 2001–2015 tropical C cycle. We find that the inter-annual variability of both concurrent and lagged effects substantially contributes to the 2001–2015 NBE inter-annual variability throughout 2001–2015 across the tropics (NBECON IAV = 80 % of total NBE IAV, r = 0.76; NBELAG IAV = 64 % of NBE IAV, r = 0.61), and the prominence of NBELAG IAV persists across both wet and dry tropical ecosystems. The magnitude of lagged effect variations on NBE across the tropics is largely attributable to lagged effects on net primary productivity (NPP; NPPLAG IAV 113 % of NBELAG IAV, r = −0.93, p value < 0.05), which emerge due to the dependence of NPP on inter-annual variations in foliar C and plant-available H2O states. We conclude that concurrent and lagged effects need to be explicitly and jointly resolved to retrieve an accurate understanding of the processes regulating the present-day and future trajectory of the terrestrial land C sink.

ACS Style

A. Anthony Bloom; Kevin W. Bowman; Junjie Liu; Alexandra G. Konings; John R. Worden; Nicholas C. Parazoo; Victoria Meyer; John T. Reager; Helen M. Worden; Zhe Jiang; Gregory R. Quetin; T. Luke Smallman; Jean-François Exbrayat; Yi Yin; Sassan S. Saatchi; Mathew Williams; David S. Schimel. Lagged effects regulate the inter-annual variability of the tropical carbon balance. Biogeosciences 2020, 17, 6393 -6422.

AMA Style

A. Anthony Bloom, Kevin W. Bowman, Junjie Liu, Alexandra G. Konings, John R. Worden, Nicholas C. Parazoo, Victoria Meyer, John T. Reager, Helen M. Worden, Zhe Jiang, Gregory R. Quetin, T. Luke Smallman, Jean-François Exbrayat, Yi Yin, Sassan S. Saatchi, Mathew Williams, David S. Schimel. Lagged effects regulate the inter-annual variability of the tropical carbon balance. Biogeosciences. 2020; 17 (24):6393-6422.

Chicago/Turabian Style

A. Anthony Bloom; Kevin W. Bowman; Junjie Liu; Alexandra G. Konings; John R. Worden; Nicholas C. Parazoo; Victoria Meyer; John T. Reager; Helen M. Worden; Zhe Jiang; Gregory R. Quetin; T. Luke Smallman; Jean-François Exbrayat; Yi Yin; Sassan S. Saatchi; Mathew Williams; David S. Schimel. 2020. "Lagged effects regulate the inter-annual variability of the tropical carbon balance." Biogeosciences 17, no. 24: 6393-6422.

Journal article
Published: 17 December 2020 in AGU Advances
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Satellite remote sensing observations show an increased greenness trend over land in recent decades. While greenness observations can indicate increased productivity, estimation of total annual productivity is highly dependent on vegetation response to climate and environmental conditions. Models have been struggling to determine how much carbon is taken up by plants as a result of increased atmospheric CO2 fertilization. Current remote sensing light use efficiency (LUE) models contain considerable uncertainty due to the lack of spatial and temporal variability in maximum LUE parameter and climate sensitivity defined for global plant functional types (PFTs). We used the optimum LUE (LUEopt) previously derived from the global FLUXNET network to improve estimation of global gross primary productivity (GPP) for the period 1982–2016. Our results indicate increasing GPP in northern latitudes owing to reduced cold temperature constraints on plant growth, thereby suggesting increasing negative carbon‐climate feedback in high latitudes. In the tropics, by contrast, our results indicate an emerging positive climate feedback, mainly due to increasing atmospheric vapor pressure deficit (VPD). Further pervasive VPD increase is likely to continue to reduce global GPP and amplify carbon emissions.

ACS Style

Nima Madani; Nicholas C. Parazoo; John S. Kimball; Ashley P. Ballantyne; Rolf H. Reichle; Marco Maneta; Sassan Saatchi; Paul I. Palmer; Zhihua Liu; Torbern Tagesson. Recent Amplified Global Gross Primary Productivity Due to Temperature Increase Is Offset by Reduced Productivity Due to Water Constraints. AGU Advances 2020, 1, 1 .

AMA Style

Nima Madani, Nicholas C. Parazoo, John S. Kimball, Ashley P. Ballantyne, Rolf H. Reichle, Marco Maneta, Sassan Saatchi, Paul I. Palmer, Zhihua Liu, Torbern Tagesson. Recent Amplified Global Gross Primary Productivity Due to Temperature Increase Is Offset by Reduced Productivity Due to Water Constraints. AGU Advances. 2020; 1 (4):1.

Chicago/Turabian Style

Nima Madani; Nicholas C. Parazoo; John S. Kimball; Ashley P. Ballantyne; Rolf H. Reichle; Marco Maneta; Sassan Saatchi; Paul I. Palmer; Zhihua Liu; Torbern Tagesson. 2020. "Recent Amplified Global Gross Primary Productivity Due to Temperature Increase Is Offset by Reduced Productivity Due to Water Constraints." AGU Advances 1, no. 4: 1.

Journal article
Published: 15 December 2020 in Remote Sensing
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It is important to understand the distribution of irrigated and non-irrigated vegetation in rapidly expanding urban areas that are experiencing climate-induced changes in water availability, such as Los Angeles, California. Mapping irrigated vegetation in Los Angeles is necessary for developing sustainable water use practices and accurately accounting for the megacity’s carbon exchange and water balance changes. However, pre-existing maps of irrigated vegetation are largely limited to agricultural regions and are too coarse to resolve heterogeneous urban landscapes. Previous research suggests that irrigation has a strong cooling effect on vegetation, especially in semi-arid environments. The July 2018 launch of the ECOsystem Spaceborne Thermal Radiometer on Space Station (ECOSTRESS) offers an opportunity to test this hypothesis using retrieved land surface temperature (LST) data in complex, heterogeneous urban/non-urban environments. In this study, we leverage Landsat 8 optical imagery and 30 m sharpened afternoon summertime ECOSTRESS LST, then apply very high-resolution (0.6–10 m) vegetation fraction weighting to produce a map of irrigated and non-irrigated vegetation in Los Angeles. This classification was compared to other classifications using different combinations of sensors in order to offer a preliminary accuracy and uncertainty assessment. This approach verifies that ECOSTRESS LST data provides an accurate map (98.2% accuracy) of irrigated urban vegetation in southern California that has the potential to reduce uncertainties in regional carbon and hydrological cycle models.

ACS Style

Red Coleman; Natasha Stavros; Glynn Hulley; Nicholas Parazoo. Comparison of Thermal Infrared-Derived Maps of Irrigated and Non-Irrigated Vegetation in Urban and Non-Urban Areas of Southern California. Remote Sensing 2020, 12, 4102 .

AMA Style

Red Coleman, Natasha Stavros, Glynn Hulley, Nicholas Parazoo. Comparison of Thermal Infrared-Derived Maps of Irrigated and Non-Irrigated Vegetation in Urban and Non-Urban Areas of Southern California. Remote Sensing. 2020; 12 (24):4102.

Chicago/Turabian Style

Red Coleman; Natasha Stavros; Glynn Hulley; Nicholas Parazoo. 2020. "Comparison of Thermal Infrared-Derived Maps of Irrigated and Non-Irrigated Vegetation in Urban and Non-Urban Areas of Southern California." Remote Sensing 12, no. 24: 4102.