A 4D-Var inversion system based on the icosahedral grid model (NICAM-TM 4D-Var v1.0) – Part 2: Optimization scheme and identical twin experiment of atmospheric  CO&amp;lt;sub&amp;gt;2&amp;lt;/sub&amp;gt; inversion

Niwa, Yosuke; Fujii, Yosuke; Sawa, Yousuke; Iida, Yosuke; Ito, Akihiko; Satoh, Masaki; Imasu, Ryoichi; Tsuboi, Kazuhiro; Matsueda, Hidekazu; Saigusa, Nobuko

doi:10.5194/gmd-10-2201-2017

Cited by 34 publications

(34 citation statements)

References 61 publications

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“…Permafrost is defined as frozen soil, sediment, or rock having temperatures at or below 0 • C for at least 2 consecutive years (Harris et al, 1988). The total extent of permafrost in the Northern Hemisphere is about 14 million km 2 or 15 % of the exposed land surface (Obu et al, 2019). As the climate warms, large areas of permafrost are also warming, and if soil temperatures pass 0 • C, thawing of the permafrost occurs.…”

Section: Terrestrial Permafrost and Hydratesmentioning

confidence: 99%

“…As the climate warms, large areas of permafrost are also warming, and if soil temperatures pass 0 • C, thawing of the permafrost occurs. Permafrost thaw is most pronounced in southern and spatially isolated permafrost zones, but it also occurs in northern continuous permafrost (Obu et al, 2019). Thaw occurs either as a gradual, often widespread, deepening of the active layer or as more rapid localized thaw associated with loss of massive ground ice (thermokarst) (Schuur et al, 2015).…”

Section: Terrestrial Permafrost and Hydratesmentioning

confidence: 99%

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The Global Methane Budget 2000–2017

Saunois

Stavert

Poulter

et al. 2020

Earth Syst. Sci. Data

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1,639

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Abstract. Understanding and quantifying the global methane (CH4) budget is important for assessing realistic pathways to mitigate climate change. Atmospheric emissions and concentrations of CH4 continue to increase, making CH4 the second most important human-influenced greenhouse gas in terms of climate forcing, after carbon dioxide (CO2). The relative importance of CH4 compared to CO2 depends on its shorter atmospheric lifetime, stronger warming potential, and variations in atmospheric growth rate over the past decade, the causes of which are still debated. Two major challenges in reducing uncertainties in the atmospheric growth rate arise from the variety of geographically overlapping CH4 sources and from the destruction of CH4 by short-lived hydroxyl radicals (OH). To address these challenges, we have established a consortium of multidisciplinary scientists under the umbrella of the Global Carbon Project to synthesize and stimulate new research aimed at improving and regularly updating the global methane budget. Following Saunois et al. (2016), we present here the second version of the living review paper dedicated to the decadal methane budget, integrating results of top-down studies (atmospheric observations within an atmospheric inverse-modelling framework) and bottom-up estimates (including process-based models for estimating land surface emissions and atmospheric chemistry, inventories of anthropogenic emissions, and data-driven extrapolations). For the 2008–2017 decade, global methane emissions are estimated by atmospheric inversions (a top-down approach) to be 576 Tg CH4 yr−1 (range 550–594, corresponding to the minimum and maximum estimates of the model ensemble). Of this total, 359 Tg CH4 yr−1 or ∼ 60 % is attributed to anthropogenic sources, that is emissions caused by direct human activity (i.e. anthropogenic emissions; range 336–376 Tg CH4 yr−1 or 50 %–65 %). The mean annual total emission for the new decade (2008–2017) is 29 Tg CH4 yr−1 larger than our estimate for the previous decade (2000–2009), and 24 Tg CH4 yr−1 larger than the one reported in the previous budget for 2003–2012 (Saunois et al., 2016). Since 2012, global CH4 emissions have been tracking the warmest scenarios assessed by the Intergovernmental Panel on Climate Change. Bottom-up methods suggest almost 30 % larger global emissions (737 Tg CH4 yr−1, range 594–881) than top-down inversion methods. Indeed, bottom-up estimates for natural sources such as natural wetlands, other inland water systems, and geological sources are higher than top-down estimates. The atmospheric constraints on the top-down budget suggest that at least some of these bottom-up emissions are overestimated. The latitudinal distribution of atmospheric observation-based emissions indicates a predominance of tropical emissions (∼ 65 % of the global budget, < 30∘ N) compared to mid-latitudes (∼ 30 %, 30–60∘ N) and high northern latitudes (∼ 4 %, 60–90∘ N). The most important source of uncertainty in the methane budget is attributable to natural emissions, especially those from wetlands and other inland waters. Some of our global source estimates are smaller than those in previously published budgets (Saunois et al., 2016; Kirschke et al., 2013). In particular wetland emissions are about 35 Tg CH4 yr−1 lower due to improved partition wetlands and other inland waters. Emissions from geological sources and wild animals are also found to be smaller by 7 Tg CH4 yr−1 by 8 Tg CH4 yr−1, respectively. However, the overall discrepancy between bottom-up and top-down estimates has been reduced by only 5 % compared to Saunois et al. (2016), due to a higher estimate of emissions from inland waters, highlighting the need for more detailed research on emissions factors. Priorities for improving the methane budget include (i) a global, high-resolution map of water-saturated soils and inundated areas emitting methane based on a robust classification of different types of emitting habitats; (ii) further development of process-based models for inland-water emissions; (iii) intensification of methane observations at local scales (e.g., FLUXNET-CH4 measurements) and urban-scale monitoring to constrain bottom-up land surface models, and at regional scales (surface networks and satellites) to constrain atmospheric inversions; (iv) improvements of transport models and the representation of photochemical sinks in top-down inversions; and (v) development of a 3D variational inversion system using isotopic and/or co-emitted species such as ethane to improve source partitioning. The data presented here can be downloaded from https://doi.org/10.18160/GCP-CH4-2019 (Saunois et al., 2020) and from the Global Carbon Project.

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Section: Terrestrial Permafrost and Hydratesmentioning

confidence: 99%

Section: Terrestrial Permafrost and Hydratesmentioning

confidence: 99%

The Global Methane Budget 2000–2017

Saunois

Stavert

Poulter

et al. 2020

Earth Syst. Sci. Data

Self Cite

1,639

1,245

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show abstract

“…CC BY 4.0 License. has been used for ecological studies of site-global scale (e.g., Ito and Inatomi, 2012b), impact assessments of climate change (e.g., Warszawski et al, 2013;Ito et al, 2016), prior to CO2 flux inversion studies (e.g., Maksyutov et al, 2013;Niwa et al, 2017), and contemporary assessments of CO2, CH4, and N2O emissions in the Global Carbon Projects (Le 220 Quéré et al, 2016;Saunois et al, 2016;Tian et al, 2018). The early version of the model (Sim-CYCLE; Ito and Oikawa, 2002) was actually used as the land carbon cycle component in the first stage of the C4MIP project (Friedlingstein et al, 2006;Yoshikawa et al, 2008).…”

Section: Land Biogeochemical Processesmentioning

confidence: 99%

Description of the MIROC-ES2L Earth system model and evaluation of its climate–biogeochemical processes and feedbacks

Hajima¹,

Watanabe²,

Yamamoto³

et al. 2019

Preprint

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Abstract. This study developed a new Model for Interdisciplinary Research on Climate, Earth System version2 for Long-term simulations (MIROC-ES2L) Earth system model (ESM) using a state-of-the-art climate model as the physical core. This model embeds a terrestrial biogeochemical component with explicit carbon–nitrogen interaction to account for soil nutrient control on plant growth and the land carbon sink. The model’s ocean biogeochemical component is largely updated to simulate biogeochemical cycles of carbon, nitrogen, phosphorus, iron, and oxygen such that oceanic primary productivity can be controlled by multiple nutrient limitations. The ocean nitrogen cycle is coupled with the land component via river discharge processes, and external inputs of iron from pyrogenic and lithogenic sources are considered. Comparison of a historical simulation with observation studies showed the model could reproduce reasonable historical changes in climate, the carbon cycle, and other biogeochemical variables together with reasonable spatial patterns of distribution of the present-day condition. The model demonstrated historical human perturbation of the nitrogen cycle through land use and agriculture, and it simulated the resultant impact on the terrestrial carbon cycle. Sensitivity analyses in preindustrial conditions revealed modeled ocean biogeochemistry could be changed regionally (but substantially) by nutrient inputs from the atmosphere and rivers. Through an idealized experiment of a 1 %CO2 increase scenario, we found the transient climate response (TCR) in the model is 1.5 K, i.e., approximately 70 % that of our previous model. The cumulative airborne fraction (AF) is also reduced by 15 % because of the intensified land carbon sink, resulting in an AF close to the multimodel mean of the Coupled Model Intercomparison Project Phase 5 (CMIP5) ESMs. The transient climate response to cumulative carbon emission (TCRE) is 1.3 K EgC−1, i.e., slightly smaller than the average of the CMIP5 ESMs, suggesting optimistic model performance in future climate projections. This model and the simulation results are contributing to the Coupled Model Intercomparison Project Phase 6 (CMIP6). The ESM could help further understanding of climate–biogeochemical interaction mechanisms, projections of future environmental changes, and exploration of our future options regarding sustainable development by evolving the processes of climate, biogeochemistry, and human activities in a holistic and interactive manner.

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“…Here, we used the linear option of the NICAM‐TM for the strict linear requirement of the conjugate BFGS method. NICAM‐TM 4D‐Var originally uses POpULar for optimisation (Niwa et al ., 2017b). In this study, we replaced it with the linear POpULar as described in Section 3.2.1.…”

Section: Methodsmentioning

confidence: 99%

“…The synthetic observational data of atmospheric CO 2 concentrations assumed weekly flask sampling at 65 ground‐based stations (see Niwa et al . (2017b) for the detailed list). Therefore, the numbers of observations for the low‐ (1‐month‐long: 4 weeks) and high‐ (1‐year‐long: 52 weeks) resolution experiments were 260 (= m low ) and 3,380 (= m high ), respectively.…”

Section: Methodsmentioning

confidence: 99%

A conjugate BFGS method for accurate estimation of a posterior error covariance matrix in a linear inverse problem

Niwa

Fujii

2020

Quart J Royal Meteoro Soc

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One effective data assimilation/inversion method is the four‐dimensional variational method (4D‐Var). However, it is a non‐trivial task for a conventional 4D‐Var to estimate a posterior error covariance matrix. This study proposes a method to estimate a posterior error covariance matrix applied to the linear inverse problem of an atmospheric constituent. The method was constructed within a 4D‐Var framework using a quasi‐Newton method with the Broyden–Fletcher–Goldfarb–Shanno (BFGS) algorithm. The proposed method was constructed such that conjugacy among the set of increment vector pairs was ensured. It is theoretically demonstrated that, when this conjugate property is coupled with preconditioning, an analytical solution of a posterior error covariance matrix could be obtained from the same number of vector pairs as observations. Furthermore, to accelerate the speed of convergence, the method can be coupled with an ensemble approach. By performing a simple advection test, it was confirmed that the proposed method could obtain an analytical matrix of the posterior error covariance within the same number of iterations as the observations. Furthermore, the method was also evaluated using an atmospheric CO2 inverse problem, which demonstrated its practical utility. The evaluation revealed that the proposed method could provide accurate estimates not only of the diagonal but also of the off‐diagonal elements of the posterior error covariance matrix. Although far more expensive than optimal state estimation, the computational efficiency was found to be reasonable for practical use, especially in conjunction with an ensemble approach. The accurate estimation of a posterior error covariance matrix resulting from the proposed method could provide valuable quantitative information regarding the uncertainties of estimated variables as well as the observational impacts, which would be beneficial for designing observation networks. Furthermore, error correlations derived from the estimated off‐diagonal elements could benefit the interpretation of optimised parameter variations.

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A 4D-Var inversion system based on the icosahedral grid model (NICAM-TM 4D-Var v1.0) – Part 2: Optimization scheme and identical twin experiment of atmospheric CO<sub>2</sub> inversion

Cited by 34 publications

References 61 publications

The Global Methane Budget 2000–2017

The Global Methane Budget 2000–2017

Description of the MIROC-ES2L Earth system model and evaluation of its climate–biogeochemical processes and feedbacks

A conjugate BFGS method for accurate estimation of a posterior error covariance matrix in a linear inverse problem

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