Assessing model performance by weather regime transitions

Having the ability to stratify a model&#8217;s performance by weather type is not only beneficial to a weather forecaster when making decisions, but it is also important for end users, whether they be scientists looking to improve the model, or a customer wishing to know the value of a forecast under a specific set of circumstances.At the MET Office, Decider is a tool which assigns a dominant weather type to a set of ensemble members, to predict the probability of a weather type occurring. The weather type is chosen from either a set of 30 or 8 sub-types, where a weather type is pre-determined objectively by clustering a 154 year record of sea level pressure anomaly fields. &#160;There is also a record of daily weather type classifications derived from analysis fields and so information of model performance for these weather types could be invaluable in reducing model error if combined with the predictions from Decider.Early trials of assessing model performance by weather type revealed that larger errors occur when the weather type persisted for a single day, rather than longer timescales, and so this suggests that it would be beneficial to examine weather type transition periods.To examine this, we expand the weather type methodology to include multiple time periods. The current methodology uses 12Z analyses to identify the weather type, and so we first assess model performance as a sensitivity study to the analysis time.Transition days are identified when the weather type changes during a pre-defined validation period, which allows separation into either night/day weather type transitions, or a change in weather type over a full 24-hour period.We will present early results of this work and demonstrate the impact of model performance when stratifying by regime transitions.

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Development and application of the WRFPLUS-Chem online chemistry adjoint and WRFDA-Chem assimilation system

Geoscientific Model Development ◽

10.5194/gmd-8-1857-2015 ◽

2015 ◽

Vol 8 (6) ◽

pp. 1857-1876 ◽

Cited By ~ 11

Author(s):

J. J. Guerrette ◽

D. K. Henze

Keyword(s):

Land Surface ◽

Vertical Mixing ◽

Model Performance ◽

Land Surface Model ◽

Sensitivity Study ◽

Climate Impacts ◽

Surface Model ◽

Time Period ◽

Develop Land ◽

The Impact

Abstract. Here we present the online meteorology and chemistry adjoint and tangent linear model, WRFPLUS-Chem (Weather Research and Forecasting plus chemistry), which incorporates modules to treat boundary layer mixing, emission, aging, dry deposition, and advection of black carbon aerosol. We also develop land surface and surface layer adjoints to account for coupling between radiation and vertical mixing. Model performance is verified against finite difference derivative approximations. A second-order checkpointing scheme is created to reduce computational costs and enable simulations longer than 6 h. The adjoint is coupled to WRFDA-Chem, in order to conduct a sensitivity study of anthropogenic and biomass burning sources throughout California during the 2008 Arctic Research of the Composition of the Troposphere from Aircraft and Satellites (ARCTAS) field campaign. A cost-function weighting scheme was devised to reduce the impact of statistically insignificant residual errors in future inverse modeling studies. Results of the sensitivity study show that, for this domain and time period, anthropogenic emissions are overpredicted, while wildfire emission error signs vary spatially. We consider the diurnal variation in emission sensitivities to determine at what time sources should be scaled up or down. Also, adjoint sensitivities for two choices of land surface model (LSM) indicate that emission inversion results would be sensitive to forward model configuration. The tools described here are the first step in conducting four-dimensional variational data assimilation in a coupled meteorology–chemistry model, which will potentially provide new constraints on aerosol precursor emissions and their distributions. Such analyses will be invaluable to assessments of particulate matter health and climate impacts.

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The effect of marine aggregate parameterisations on nutrients and oxygen minimum zones in a global biogeochemical model

Biogeosciences ◽

10.5194/bg-16-3095-2019 ◽

2019 ◽

Vol 16 (15) ◽

pp. 3095-3111 ◽

Cited By ~ 1

Author(s):

Daniela Niemeyer ◽

Iris Kriest ◽

Andreas Oschlies

Keyword(s):

Model Calibration ◽

Model Performance ◽

Sensitivity Study ◽

Global Model ◽

Particle Aggregation ◽

Biogeochemical Model ◽

Regional Patterns ◽

Oxygen Minimum Zones ◽

The Impact ◽

Oxygen Minimum

Abstract. Particle aggregation determines the particle flux length scale and affects the marine oxygen concentration and thus the volume of oxygen minimum zones (OMZs) that are of special relevance for ocean nutrient cycles and marine ecosystems and that have been found to expand faster than can be explained by current state-of-the-art models. To investigate the impact of particle aggregation on global model performance, we carried out a sensitivity study with different parameterisations of marine aggregates and two different model resolutions. Model performance was investigated with respect to global nutrient and oxygen concentrations, as well as extent and location of OMZs. Results show that including an aggregation model improves the representation of OMZs. Moreover, we found that besides a fine spatial resolution of the model grid, the consideration of porous particles, an intermediate-to-high particle sinking speed and a moderate-to-high stickiness improve the model fit to both global distributions of dissolved inorganic tracers and regional patterns of OMZs, compared to a model without aggregation. Our model results therefore suggest that improvements not only in the model physics but also in the description of particle aggregation processes can play a substantial role in improving the representation of dissolved inorganic tracers and OMZs on a global scale. However, dissolved inorganic tracers are apparently not sufficient for a global model calibration, which could necessitate global model calibration against a global observational dataset of marine organic particles.

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The Impact of Cumulus Parameterization Schemes on the Simulation of Tropical Cyclone “Roanu” Over the Bay of Bengal Using WRF Model

Dhaka University Journal of Science ◽

10.3329/dujs.v68i1.54601 ◽

2020 ◽

Vol 68 (1) ◽

pp. 87-94

Author(s):

Saifullah ◽

Md Idris Ali ◽

Ashik Imran

Keyword(s):

Tropical Cyclone ◽

Bay Of Bengal ◽

Wrf Model ◽

Absolute Error ◽

Sensitivity Study ◽

Cumulus Parameterization ◽

Weather Research And Forecasting ◽

Sea Level Pressure ◽

Cumulus Parameterization Schemes ◽

The Impact

A sensitivity study has been made on cumulus parameterization (CP) schemes of Weather Research and Forecasting (WRF) model for the simulation of tropical cyclone Roanu which formed over Bay of Bengal during May 2016. The model was run for 72 hours with different CP schemes such as Kain–Fritsch (KF), Betts-Miller-Janjic (BMJ), Grell–Freit as Ensemble (GFE), Grell 3D Ensemble (G3E) and Grell–Devenyi (GD) Ensemble schemes to study the variation in track, intensity. The landfall position error is minimum for BMJ scheme but the time delayed only 1.5-5 hours for all schemes except GD scheme. The Root Mean Square Error (RMSE) and Mean Absolute Error (MAE) of minimum sea level pressure and maximum wind speed is smaller for BMJ, GFE, GD schemes. The RMSE-MAE of rainfall is minimum for BMJ and G3E schemes. Except GD scheme all the other schemes give the better result. Dhaka Univ. J. Sci. 68(1): 87-94, 2020 (January)

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The effect of marine aggregate parameterisations on global biogeochemical model performance

10.5194/bg-2019-122 ◽

2019 ◽

Author(s):

Daniela Niemeyer ◽

Iris Kriest ◽

Andreas Oschlies

Keyword(s):

Model Calibration ◽

Model Performance ◽

Sensitivity Study ◽

Global Scale ◽

Global Model ◽

Particle Aggregation ◽

Biogeochemical Model ◽

Regional Patterns ◽

High Particle ◽

The Impact

Abstract. Particle aggregation determines the particle flux length scale, possibly the marine oxygen concentration and thus affecting the volume of oxygen minimum zones (OMZs) that are of special relevance for ocean nutrient cycles and marine ecosystems, and that have been found to expand faster than can be explained by current state-of-the-art models. To investigate the impact of particle aggregation on global model performance, we carried out a sensitivity study with different parameterisations of marine aggregates and two different model resolutions. Model performance was investigated with respect to global nutrient and oxygen concentrations, as well as extent and location of OMZs. Results show that including an aggregation model improves the representation of OMZs. Moreover, we found that besides a fine spatial resolution of the model grid, the consideration of porous particles, an intermediate to high particle sinking speed and a moderate to high stickiness improve the model fit to both, global distributions of dissolved inorganic tracers and regional patterns of OMZs, compared to a model without aggregation. Our model results therefore suggest that improvements not only in the model physics, but also in the description of particle aggregation processes can play a substantial role in improving the representation of dissolved inorganic tracers and OMZs on a global scale. However, dissolved inorganic tracers are apparently not sufficient for a global model calibration, which could necessitate global model calibration against a global observational dataset of marine organic particles.

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Early Outcomes of Coronary Endarterectomy in Patients Undergoing Coronary Artery Bypass Surgery

The Heart Surgery Forum ◽

10.1532/hsf.1352 ◽

2016 ◽

Vol 19 (2) ◽

pp. 059

Author(s):

Amin Bagheri ◽

Ahmad Masoumi ◽

Jamshid Bagheri

Keyword(s):

Coronary Artery ◽

Coronary Artery Bypass ◽

Coronary Artery Bypass Surgery ◽

Bypass Surgery ◽

Artery Bypass ◽

Adverse Outcomes ◽

Supraventricular Arrhythmia ◽

Coronary Endarterectomy ◽

Early Results ◽

The Impact

Background: Coronary endarterectomy (CE) is performed as an adjunct to coronary artery bypass surgery (CABG); however, the efficacy of this technique is still controversial. We aimed to evaluate the impact of CE combined with CABG when compared with isolated CABG. Methods: Patients who underwent CABG between July 2007 and June 2014 were included. 70 of 2452 patients (2.8%) underwent CE in addition to CABG. Early results were compared with isolated CABG and predictors of adverse outcome were measured in stepwise multivariate logistic regression analyses. Results: The incidence of comorbidities including prior myocardial infarction, diabetes mellitus, and three-vessel coronary disease in CE patients was higher; however, mortality (4.3% versus control 3.6%; P = .762) and postoperative complications were not significantly increased in this group of patients (except supraventricular arrhythmia). Although age greater than 70 years, impaired ejection fraction, intraoperative intraaortic balloon pump, and prolonged cardiopulmonary bypass time were important predictors of adverse outcomes, CE was not associated with increased mortality or postoperative morbidities. Conclusion: Despite the higher risk profile of patients who underwent CE, this technique was not identified as an independent risk factor for adverse postoperative outcomes.

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The impact of anatomical uncertainties on the predictions of a musculoskeletal hand model – a sensitivity study

Computer Methods in Biomechanics & Biomedical Engineering ◽

10.1080/10255842.2021.1940974 ◽

2021 ◽

pp. 1-9

Author(s):

Maximilian Melzner ◽

Franz Süß ◽

Sebastian Dendorfer

Keyword(s):

Sensitivity Study ◽

Hand Model ◽

The Impact

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Modeling Bacterial Regrowth and Trihalomethane Formation in Water Distribution Systems

Water ◽

10.3390/w13040463 ◽

2021 ◽

Vol 13 (4) ◽

pp. 463

Author(s):

Gopinathan R. Abhijith ◽

Leonid Kadinski ◽

Avi Ostfeld

Keyword(s):

Distribution Systems ◽

Water Distribution ◽

Mechanistic Model ◽

Water Distribution Systems ◽

Sensitivity Study ◽

Operating Conditions ◽

Growth Rate Constant ◽

Model Parameters ◽

Bacterial Regrowth ◽

The Impact

The formation of bacterial regrowth and disinfection by-products is ubiquitous in chlorinated water distribution systems (WDSs) operated with organic loads. A generic, easy-to-use mechanistic model describing the fundamental processes governing the interrelationship between chlorine, total organic carbon (TOC), and bacteria to analyze the spatiotemporal water quality variations in WDSs was developed using EPANET-MSX. The representation of multispecies reactions was simplified to minimize the interdependent model parameters. The physicochemical/biological processes that cannot be experimentally determined were neglected. The effects of source water characteristics and water residence time on controlling bacterial regrowth and Trihalomethane (THM) formation in two well-tested systems under chlorinated and non-chlorinated conditions were analyzed by applying the model. The results established that a 100% increase in the free chlorine concentration and a 50% reduction in the TOC at the source effectuated a 5.87 log scale decrement in the bacteriological activity at the expense of a 60% increase in THM formation. The sensitivity study showed the impact of the operating conditions and the network characteristics in determining parameter sensitivities to model outputs. The maximum specific growth rate constant for bulk phase bacteria was found to be the most sensitive parameter to the predicted bacterial regrowth.

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Subseasonal relationship between Arctic and Eurasian surface air temperature

Scientific Reports ◽

10.1038/s41598-021-83486-5 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Hye-Jin Kim ◽

Seok-Woo Son ◽

Woosok Moon ◽

Jong-Seong Kug ◽

Jaeyoung Hwang

Keyword(s):

Air Temperature ◽

Diabatic Heating ◽

Surface Air Temperature ◽

Significant Negative Correlation ◽

Cold Season ◽

Reanalysis Data ◽

Necessary Condition ◽

Sea Level Pressure ◽

Blocking High ◽

Pressure Anomaly

AbstractThe subseasonal relationship between Arctic and Eurasian surface air temperature (SAT) is re-examined using reanalysis data. Consistent with previous studies, a significant negative correlation is observed in cold season from November to February, but with a local minimum in late December. This relationship is dominated not only by the warm Arctic-cold Eurasia (WACE) pattern, which becomes more frequent during the last two decades, but also by the cold Arctic-warm Eurasia (CAWE) pattern. The budget analyses reveal that both WACE and CAWE patterns are primarily driven by the temperature advection associated with sea level pressure anomaly over the Ural region, partly cancelled by the diabatic heating. It is further found that, although the anticyclonic anomaly of WACE pattern mostly represents the Ural blocking, about 20% of WACE cases are associated with non-blocking high pressure systems. This result indicates that the Ural blocking is not a necessary condition for the WACE pattern, highlighting the importance of transient weather systems in the subseasonal Arctic-Eurasian SAT co-variability.

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The Impact of Probability Density Functions Assessment on Model Performance for Slope Stability Analysis

Geosciences ◽

10.3390/geosciences11080322 ◽

2021 ◽

Vol 11 (8) ◽

pp. 322

Author(s):

Evelina Volpe ◽

Luca Ciabatta ◽

Diana Salciarini ◽

Stefania Camici ◽

Elisabetta Cattoni ◽

...

Keyword(s):

Probability Density ◽

Central Italy ◽

Model Performance ◽

Probability Density Functions ◽

Slope Instability ◽

Complex Nature ◽

Density Functions ◽

Umbria Region ◽

Input Variables ◽

The Impact

The development of forecasting models for the evaluation of potential slope instability after rainfall events represents an important issue for the scientific community. This topic has received considerable impetus due to the climate change effect on territories, as several studies demonstrate that an increase in global warming can significantly influence the landslide activity and stability conditions of natural and artificial slopes. A consolidated approach in evaluating rainfall-induced landslide hazard is based on the integration of rainfall forecasts and physically based (PB) predictive models through deterministic laws. However, considering the complex nature of the processes and the high variability of the random quantities involved, probabilistic approaches are recommended in order to obtain reliable predictions. A crucial aspect of the stochastic approach is represented by the definition of appropriate probability density functions (pdfs) to model the uncertainty of the input variables as this may have an important effect on the evaluation of the probability of failure (PoF). The role of the pdf definition on reliability analysis is discussed through a comparison of PoF maps generated using Monte Carlo (MC) simulations performed over a study area located in the Umbria region of central Italy. The study revealed that the use of uniform pdfs for the random input variables, often considered when a detailed geotechnical characterization for the soil is not available, could be inappropriate.

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