54 research outputs found

    Land surface model parameter optimisation using in situ flux data: comparison of gradient-based versus random search algorithms (a case study using ORCHIDEE v1.9.5.2)

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    Land surface models (LSMs), which form the land component of earth system models, rely on numerous processes for describing carbon, water and energy budgets, often associated with highly uncertain parameters. Data assimilation (DA) is a useful approach for optimising the most critical parameters in order to improve model accuracy and refine future climate predictions. In this study, we compare two different DA methods for optimising the parameters of seven plant functional types (PFTs) of the ORCHIDEE LSM using daily averaged eddy-covariance observations of net ecosystem exchange and latent heat flux at 78 sites across the globe. We perform a technical investigation of two classes of minimisation methods – local gradient-based (the L-BFGS-B algorithm, limited memory Broyden–Fletcher–Goldfarb–Shanno algorithm with bound constraints) and global random search (the genetic algorithm) – by evaluating their relative performance in terms of the model–data fit and the difference in retrieved parameter values. We examine the performance of each method for two cases: when optimising parameters at each site independently (“single-site” approach) and when simultaneously optimising the model at all sites for a given PFT using a common set of parameters (“multi-site” approach). We find that for the single site case the random search algorithm results in lower values of the cost function (i.e. lower model–data root mean square differences) than the gradient-based method; the difference between the two methods is smaller for the multi-site optimisation due to a smoothing of the cost function shape with a greater number of observations. The spread of the cost function, when performing the same tests with 16 random first-guess parameters, is much larger with the gradient-based method, due to the higher likelihood of being trapped in local minima. When using pseudo-observation tests, the genetic algorithm results in a closer approximation of the true posterior parameter value in the L-BFGS-B algorithm. We demonstrate the advantages and challenges of different DA techniques and provide some advice on using it for the LSM parameter optimisation.</p

    Participant retention in follow-up studies of prematurely born children

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    Background: Follow-up studies of infants born prematurely are essential to understand the long-term consequences of preterm birth and the efficacy of interventions delivered in the neonatal period. Retention of participants for follow up studies, however, is challenging, with attrition rates of up to 70%. Our aim was to examine retention rates in two follow-up studies of prematurely born children and identify participant or study characteristics that were associated with higher attrition, and to discuss retention strategies with regard to the literature. Methods: Data from children recruited at birth to one of two studies of prematurely born infants were assessed. The two studies were the United Kingdom Oscillation Study (UKOS, a randomised study comparing two modes of neonatal ventilation in infants born less than 29weeks of gestational age (GA)), and an observational study examining the impact of viral lower respiratory tract infections in infancy in those born less than 36weeks of GA (virus study). The UKOS participants, but not those in the virus study, had regularly been contacted throughout the follow-up period. UKOS subjects were followed up at 11 to 14years of age and subjects in the virus study at 5–7 years of age. At follow up in both studies, pulmonary function and respiratory morbidity were assessed. Retention rates to follow-up in the two studies and baseline characteristics of those who were and were not retained were assessed. Results: Retention was significantly higher in UKOS than the virus study (61% versus 35%, p <0.0001). Subjects lost to UKOS follow up had greater deprivation scores (p <0.001), a greater likelihood of intrauterine tobacco exposure (p =0.001) and were more likely to be of non-white ethnicity (p <0.001). In the virus study, those lost to follow-up had higher birth weights (p =0.036) and were less likely to be oxygen dependent at hospital discharge (p =0.003) or be part of a multiple birth (p =0.048). Conclusions: Higher retention was demonstrated when there was regular contact in the follow-up period. Both social factors and initial illness severity affected the retention into follow-up studies of prematurely born infants, though these factors were not consistent across the two studies.KHP Challenge Fund; National Institute for Health Research (NIHR) Biomedical Research Centre based at Guy’s and St Thomas’ NHS Foundation Trust and King’s College Londo

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

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    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

    The Importance of Consistent Global Forest Aboveground Biomass Product Validation

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    Several upcoming satellite missions have core science requirements to produce data for accurate forest aboveground biomass mapping. Largely because of these mission datasets, the number of available biomass products is expected to greatly increase over the coming decade. Despite the recognized importance of biomass mapping for a wide range of science, policy and management applications, there remains no community accepted standard for satellite-based biomass map validation. The Committee on Earth Observing Satellites (CEOS) is developing a protocol to fill this need in advance of the next generation of biomass-relevant satellites, and this paper presents a review of biomass validation practices from a CEOS perspective. We outline the wide range of anticipated user requirements for product accuracy assessment and provide recommendations for the validation of biomass products. These recommendations include the collection of new, high-quality in situ data and the use of airborne lidar biomass maps as tools toward transparent multi-resolution validation. Adoption of community-vetted validation standards and practices will facilitate the uptake of the next generation of biomass products
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