Global surface-ocean pCO2 and sea–air CO2 flux variability from an observation-driven ocean mixed-layer scheme

A temporally and spatially resolved estimate of the global surface-ocean CO₂ partial pressure field and the sea–air CO₂ flux is presented, obtained by fitting a simple data-driven diagnostic model of ocean mixed-layer biogeochemistry to surface-ocean CO₂ partial pressure data from the SOCAT v1.5 database. Results include seasonal, interannual, and short-term (daily) variations. In most regions, estimated seasonality is well constrained from the data, and compares well to the widely used monthly climatology by Takahashi et al. (2009). Comparison to independent data tentatively supports the slightly higher seasonal variations in our estimates in some areas. We also fitted the diagnostic model to atmospheric CO₂ data. The results of this are less robust, but in those areas where atmospheric signals are not strongly influenced by land flux variability, their seasonality is nevertheless consistent with the results based on surface-ocean data. From a comparison with an independent seasonal climatology of surface-ocean nutrient concentration, the diagnostic model is shown to capture relevant surface-ocean biogeochemical processes reasonably well. Estimated interannual variations will be presented and discussed in a companion paper

Quantifying the effect of forest age in annual net forest carbon balance

Forests dominate carbon (C) exchanges between the terrestrial biosphere and the atmosphere on land. In the long term, the net carbon flux between forests and the atmosphere has been significantly impacted by changes in forest cover area and structure due to ecological disturbances and management activities. Current empirical approaches for estimating net ecosystem productivity (NEP) rarely consider forest age as a predictor, which represents variation in physiological processes that can respond differently to environmental drivers, and regrowth following disturbance. Here, we conduct an observational synthesis to empirically determine to what extent climate, soil properties, nitrogen deposition, forest age and management influence the spatial and interannual variability of forest NEP across 126 forest eddy-covariance flux sites worldwide. The empirical models explained up to 62% and 71% of spatio-temporal and across-site variability of annual NEP, respectively. An investigation of model structures revealed that forest age was a dominant factor of NEP spatio-temporal variability in both space and time at the global scale as compared to abiotic factors, such as nutrient availability, soil characteristics and climate. These findings emphasize the importance of forest age in quantifying spatio-temporal variation in NEP using empirical approaches

Improving Estimates of Gross Primary Productivity by Assimilating Solar-Induced Fluorescence Satellite Retrievals in a Terrestrial Biosphere Model Using a Process-Based SIF Model

Abstract Over the last few years, solar-induced chlorophyll fluorescence (SIF) observations from space have emerged as a promising resource for evaluating the spatio-temporal distribution of gross primary productivity (GPP) simulated by global terrestrial biosphere models. SIF can be used to improve GPP simulations by optimizing critical model parameters through statistical Bayesian data assimilation techniques. A prerequisite is the availability of a functional link between GPP and SIF in terrestrial biosphere models. Here we present the development of a mechanistic SIF observation operator in the ORCHIDEE (Organizing Carbon and Hydrology In Dynamic Ecosystems) terrestrial biosphere model. It simulates the regulation of photosystem II fluorescence quantum yield at the leaf level thanks to a novel parameterization of non-photochemical quenching as a function of temperature, photosynthetically active radiation, and normalized quantum yield of photochemistry. It emulates the radiative transfer of chlorophyll fluorescence to the top of the canopy using a parametric simplification of the SCOPE (Soil Canopy Observation Photosynthesis Energy) model. We assimilate two years of monthly OCO-2 (Orbiting Carbon Observatory-2) SIF product at 0.5° (2015?2016) to optimize ORCHIDEE photosynthesis and phenological parameters over an ensemble of grid points for all plant functional types. The impact on the simulated GPP is considerable with a large decrease of the global scale budget by 28 GtC/year over the period 1990?2009. The optimized GPP budget (134/136 GtC/year over 1990?2009/2001?2009) remarkably agrees with independent GPP estimates, FLUXSAT (137 GtC/year over 2001?2009) in particular and FLUXCOM (121 GtC/year over 1990?2009). Our results also suggest a biome dependency of the SIF-GPP relationship that needs to be improved for some plant functional types.Peer reviewe

Plant Regrowth as a Driver of Recent Enhancement of Terrestrial CO2 Uptake

The increasing strength of land CO2 uptake in the 2000s has been attributed to a stimulating effect of rising atmospheric CO2 on photosynthesis (CO2 fertilization). Using terrestrial biosphere models, we show that enhanced CO2 uptake is induced not only by CO2 fertilization but also an increasing uptake by plant regrowth (accounting for 0.33 ± 0.10 Pg C/year increase of CO2 uptake in the 2000s compared with the 1960s-1990s) with its effect most pronounced in eastern North America, southern‐eastern Europe, and southeastern temperate Eurasia. Our analysis indicates that ecosystems in North America and Europe have established the current productive state through regrowth since the 1960s, and those in temperate Eurasia are still in a stage from regrowth following active afforestation in the 1980s-1990s. As the strength of model representation of CO2 fertilization is still in debate, plant regrowth might have a greater potential to sequester carbon than indicated by this study

Harnessing Remote Sensing to Accomplish Full Carbon Accounting: Workshop Report

The workshop "Harnessing Remote Sensing to Accomplish Full Carbon Accounting" was held on December 9-11th, 1999 at IIASA with the intention of meeting the following objectives: (1) To Promote the mutual interests of remote sensing and carbon science communities by exchanging the ideas regarding the requirements for carbon accounting and the current available products derived from remote sensing land information systems; (2) To produce strategic recommendations on how to improve FCA at different scales with the use of remote sensing tools; and, (3) To develop a Framework to Apply Recommendations for Sub-global and National-Level Case Studies. Although these ambitious targets were only part met, three discussion group sessions resulted in describing: What is required to implement full carbon accounting; How remote sensing can be used to assist this implementation; and, How remote sensing can be used to reduce the uncertainties related to FCA. This report summarizes the presentations, discussions and results of this workshop and outlines the next steps to be taken by IIASA

A Synthesis Program: Reducing Uncertainties of the Terrestrial Biosphere Carbon Cycle at Various Spatio Temporal Scales

The terrestrial biosphere plays an important role in the global carbon cycle, and disturbance fire and climate extreme drought have strong direct and indirect impacts on the carbon fluxes. In addition, the lateral dissolved organic carbon (DOC) flux from soils to inland waters represents an important component of the terrestrial biosphere carbon cycle. Fires play an important role in the terrestrial biosphere carbon cycle, not only through direct carbon release but also contributing to a potential long-term storage as pyrogenic carbon (PyC). PyC is formed through fires, and because it may resist further biological and chemical degradation, is more stable in soil and sediment than original biomass. Chapter 1 presents estimates of global PyC production. Worldwide, droughts are becoming more frequent with increasing weather extremes, resulting in substantial impacts on land-atmosphere carbon exchange. However, the patterns of carbon fluxes in response to droughts differ across biomes and time scales due to variations in the adaptation and resilience of different plant species, soil properties, and available water and nutrients. In chapter 2, I examined the biome-scale spatial patterns in the response of carbon fluxes to droughts at different time scales. The export of dissolved organic carbon (DOC) from a watershed is a critical flux of terrestrial biosphere carbon cycles. Advanced understanding of how environmental factors drive the temporal patterns of this biogeochemical process and their relative magnitudes of impacts is necessary to accurately model and evaluate terrestrial carbon storage and fluxes. In chapter 3, I examined the impacts of environmental factors on the temporal patterns of DOC export and their relative magnitudes, as well as the autocorrelation of DOC export. The lateral flux of dissolved organic carbon (DOC) from soils to inland waters and ultimately delivered to the ocean represents a fundamental component of the global carbon cycle. To estimate the production, delivery and potential fates of DOC flux from terrestrial through aquatic ecosystems to the ocean, I developed a process-based terrestrial-aquatic DOC fluxes model (TAF-DOC), which has the ability to estimate the spatial and temporal dynamics of DOC flux through incorporating various environmental factors

Northern Eurasia Future Initiative (NEFI): facing the challenges and pathways of global change in the twenty-first century

During the past several decades, the Earth system has changed significantly, especially across Northern Eurasia. Changes in the socio-economic conditions of the larger countries in the region have also resulted in a variety of regional environmental changes that can have global consequences. The Northern Eurasia Future Initiative (NEFI) has been designed as an essential continuation of the Northern Eurasia Earth Science Partnership Initiative (NEESPI), which was launched in 2004. NEESPI sought to elucidate all aspects of ongoing environmental change, to inform societies and, thus, to better prepare societies for future developments. A key principle of NEFI is that these developments must now be secured through science-based strategies co-designed with regional decision-makers to lead their societies to prosperity in the face of environmental and institutional challenges. NEESPI scientific research, data, and models have created a solid knowledge base to support the NEFI program. This paper presents the NEFI research vision consensus based on that knowledge. It provides the reader with samples of recent accomplishments in regional studies and formulates new NEFI science questions. To address these questions, nine research foci are identified and their selections are briefly justified. These foci include warming of the Arctic; changing frequency, pattern, and intensity of extreme and inclement environmental conditions; retreat of the cryosphere; changes in terrestrial water cycles; changes in the biosphere; pressures on land use; changes in infrastructure; societal actions in response to environmental change; and quantification of Northern Eurasia’s role in the global Earth system. Powerful feedbacks between the Earth and human systems in Northern Eurasia (e.g., mega-fires, droughts, depletion of the cryosphere essential for water supply, retreat of sea ice) result from past and current human activities (e.g., large-scale water withdrawals, land use, and governance change) and potentially restrict or provide new opportunities for future human activities. Therefore, we propose that integrated assessment models are needed as the final stage of global change assessment. The overarching goal of this NEFI modeling effort will enable evaluation of economic decisions in response to changing environmental conditions and justification of mitigation and adaptation efforts

The future of Earth observation in hydrology

In just the past 5 years, the field of Earth observation has progressed beyond the offerings of conventional space-agency-based platforms to include a plethora of sensing opportunities afforded by CubeSats, unmanned aerial vehicles (UAVs), and smartphone technologies that are being embraced by both for-profit companies and individual researchers. Over the previous decades, space agency efforts have brought forth well-known and immensely useful satellites such as the Landsat series and the Gravity Research and Climate Experiment (GRACE) system, with costs typically of the order of 1 billion dollars per satellite and with concept-to-launch timelines of the order of 2 decades (for new missions). More recently, the proliferation of smart-phones has helped to miniaturize sensors and energy requirements, facilitating advances in the use of CubeSats that can be launched by the dozens, while providing ultra-high (3-5 m) resolution sensing of the Earth on a daily basis. Start-up companies that did not exist a decade ago now operate more satellites in orbit than any space agency, and at costs that are a mere fraction of traditional satellite missions. With these advances come new space-borne measurements, such as real-time high-definition video for tracking air pollution, storm-cell development, flood propagation, precipitation monitoring, or even for constructing digital surfaces using structure-from-motion techniques. Closer to the surface, measurements from small unmanned drones and tethered balloons have mapped snow depths, floods, and estimated evaporation at sub-metre resolutions, pushing back on spatio-temporal constraints and delivering new process insights. At ground level, precipitation has been measured using signal attenuation between antennae mounted on cell phone towers, while the proliferation of mobile devices has enabled citizen scientists to catalogue photos of environmental conditions, estimate daily average temperatures from battery state, and sense other hydrologically important variables such as channel depths using commercially available wireless devices. Global internet access is being pursued via high-altitude balloons, solar planes, and hundreds of planned satellite launches, providing a means to exploit the "internet of things" as an entirely new measurement domain. Such global access will enable real-time collection of data from billions of smartphones or from remote research platforms. This future will produce petabytes of data that can only be accessed via cloud storage and will require new analytical approaches to interpret. The extent to which today's hydrologic models can usefully ingest such massive data volumes is unclear. Nor is it clear whether this deluge of data will be usefully exploited, either because the measurements are superfluous, inconsistent, not accurate enough, or simply because we lack the capacity to process and analyse them. What is apparent is that the tools and techniques afforded by this array of novel and game-changing sensing platforms present our community with a unique opportunity to develop new insights that advance fundamental aspects of the hydrological sciences. To accomplish this will require more than just an application of the technology: in some cases, it will demand a radical rethink on how we utilize and exploit these new observing systems