Academic literature on the topic 'Run-Time bias-Correction'

AbstractThis article proposes asymptotically unbiased estimators of autocovariances and autocorrelations for panel data with both individual and time effects. We show that the conventional autocovariance estimators suffer from the bias caused by the elimination of individual and time effects. The bias related to individual effects is proportional to the long-run variance, and it related to time effects is proportional to the value of the estimated autocovariance. For the conventional autocorrelation estimators, the elimination of time effects does not cause a bias while the elimination of individual effects does. We develop methods to estimate the long-run variance and propose bias-corrected estimators based on the proposed long-run variance estimator. We also consider the half-panel jackknife estimation for bias correction. The theoretical results are given by employing double asymptotics under which both the number of observations and the length of the time series tend to infinity. Monte Carlo simulations show that the asymptotic theory provides a good approximation to the actual bias and that the proposed bias-correction methods work well.

The mode bias is present and time-dependent due to imperfect configurations. Data assimilation is the process by which observations are used to correct the model forecast, and is affected by the bias. How to reduce the bias is an important issue. This paper investigates the roles of a simple bias correction scheme in ocean data assimilation. In this scheme, the misfits between modeled and monthly temperature and salinity with interannual variability from the Met Office Hadley Centre subsurface temperature and salinity data set (EN4.2.2) are used for the innovations in assimilation via the Ensemble Optimal Interpolation method. Two assimilation experiments are implemented to evaluate the impacts of bias correction. The first experiment is a data assimilation system without bias correction. In the second experiment, the bias correction is applied in assimilation. For comparison, the nature run with no assimilation and no bias correction is also conducted. When the bias correction is not applied, the assimilation alone leads to a rising trend in the heat and salt content that is not found in the observations. It is a spurious temporal variability due to the effect of the bias on the data assimilation. Meanwhile, the assimilation experiment without bias correction also produces significant negative impacts on the subsurface salinity. The experiment with bias correction performs best with notable improvements over the results of the other two experiments.

Abstract The import and export price indices of an economy are usually compiled by some Laspeyres type index. It is well known that such an index formula is prone to substitution bias. Therefore, also the terms of trade (ratio of export and import price index) are likely to be distorted. The underlying substitution bias accumulates over time. The present article introduces a simple and transparent retroactive correction approach that addresses the source of the substitution bias and produces meaningful long-run time series of import and export price levels and, therefore, of the terms of trade. Furthermore, an empirical case study is conducted that demonstrates the efficacy and versatility of the correction approach.

Abstract. Possible future climate change effects on drought severity in Poland are estimated for six ENSEMBLE climate projections using the Standard Precipitation Index (SPI). The time series of precipitation represent six different RCM/GCM run under the A1B SRES scenario for the period 1971–2099. Monthly precipitation values were used to estimate the Standard Precipitation Index (SPI) for multiple time scales (1, 3, 6, 12 and 24 months) for a spatial resolution of 25 km × 25 km for the whole country. Trends in SPI were analysed using a Mann–Kendall test with Sen's slope estimator for each 25 km × 25 km grid cell for each RCM/GCM projection and timescale, and results obtained for uncorrected precipitation and bias corrected precipitation were compared. Bias correction was achieved using a distribution-based quantile mapping (QM) method in which the climate model precipitation series were adjusted relative to gridded E-OBS precipitation data for Poland. The results show that the spatial pattern of the trend depends on the climate model, the time scale considered and on the bias correction. The effect of change on the projected trend due to bias correction is small compared to the variability among climate models. We also summarise the mechanisms underlying the influence of bias correction on trends using a simple example of a linear bias correction procedure. In the case of precipitation the bias correction by QM does not change the direction of changes but can change the slope of trend. We also have noticed that the results for the same GCM, with differing RCMs, are characterized by similar pattern of changes, although this behaviour is not seen at all time scales and seasons.

Recent study points to the value of a non-linear heart rate variability (HRV) biomarker using detrended fluctuation analysis (DFA a1) for aerobic threshold determination (HRVT). Significance of recording artefact, correction methods and device bias on DFA a1 during exercise and HRVT is unclear. Gas exchange and HRV data were obtained from 17 participants during an incremental treadmill run using both ECG and Polar H7 as recording devices. First, artefacts were randomly placed in the ECG time series to equal 1, 3 and 6% missed beats with correction by Kubios software’s automatic and medium threshold method. Based on linear regression, Bland Altman analysis and Wilcoxon paired testing, there was bias present with increasing artefact quantity. Regardless of artefact correction method, 1 to 3% missed beat artefact introduced small but discernible bias in raw DFA a1 measurements. At 6% artefact using medium correction, proportional bias was found (maximum 19%). Despite this bias, the mean HRVT determination was within 1 bpm across all artefact levels and correction modalities. Second, the HRVT ascertained from synchronous ECG vs. Polar H7 recordings did show an average bias of minus 4 bpm. Polar H7 results suggest that device related bias is possible but in the reverse direction as artefact related bias.

To investigate the ability of dynamical seasonal climate predictions for Vietnam, the RegCM4.2 is employed to perform seasonal prediction of 2 m mean (T2m), maximum (Tx), and minimum (Tn) air temperature for the period from January 2012 to November 2013 by downscaling the NCEP Climate Forecast System (CFS) data. For model bias correction, the model and observed climatology is constructed using the CFS reanalysis and observed temperatures over Vietnam for the period 1980–2010, respectively. The RegCM4.2 forecast is run four times per month from the current month up to the next six months. A model ensemble prediction initialized from the current month is computed from the mean of the four runs within the month. The results showed that, without any bias correction (CTL), the RegCM4.2 forecast has very little or no skill in both tercile and value predictions. With bias correction (BAS), model predictions show improved skill. The experiment in which the results from the BAS experiment are further successively adjusted (SUC) with model bias at one-month lead time of the previous run showed further improvement compared to CTL and BAS. Skill scores of the tercile probability forecasts were found to exceed 0.3 for most of the target months.

We develop a class of tests for time‐series models such as multiple regression with growing dimension, infinite‐order autoregression, and nonparametric sieve regression. Examples include the Chow test and general linear restriction tests of growing rank p. Employing such increasing p asymptotics, we introduce a new scale correction to conventional test statistics, which accounts for a high‐order long‐run variance (HLV), which emerges as p grows with sample size. We also propose a bias correction via a null‐imposed bootstrap to alleviate finite‐sample bias without sacrificing power unduly. A simulation study shows the importance of robustifying testing procedures against the HLV even when p is moderate. The tests are illustrated with an application to the oil regressions in Hamilton (2003).

Satellite precipitation estimates (SPE) provide useful input for hydrological modeling. However, hydrological modeling is frequently hindered by large bias and errors in SPE, inducing the necessity for bias corrections. Traditional distribution mapping bias correction of daily precipitation commonly uses Bernoulli and gamma distributions to separately model the probability and intensities of precipitation and is insufficient towards extremes. This study developed an improved distribution mapping bias correction method, which established a censored shifted mixture distribution (CSMD) as a transfer function when mapping raw precipitation to the reference data. CSMD coupled the censored shifted statistical distribution to jointly model both the precipitation occurrence probability and intensity with a mixture of gamma and generalized Pareto distributions to enhance extreme-value modeling. The CSMD approach was applied to correct the up-to-date SPE of Integrated Multi-satelliE Retrievals for Global Precipitation Measurement (GPM) with near-real-time “Early” run (IMERG-E) over the Yangtze River basin. To verify the hydrological response of bias-corrected IMERG-E, the streamflow of the Wujiang River basin was simulated using Ge´nie Rural with 6 parameters (GR6J) and Coupled Routing Excess Storage (CREST) models. The results showed that the bias correction using both BerGam (traditional bias correction combining Bernoulli with gamma distributions) and the improved CSMD could reduce the systematic errors of IMERG-E. Furthermore, CSMD outperformed BerGam in correcting overall precipitation (with the median of mean absolute errors of 2.46 mm versus 2.81 mm for CSMD and BerGam respectively, and the median of modified Nash–Sutcliffe efficiency of 0.39 versus 0.29) and especially in extreme values for uniform format and particular attention paid to extremes. In addition, the hydrological effect that CSMD correction exerted on IMERG-E, driving GR6J and CREST rainfall-runoff modeling, outperformed that of the BerGam correction. This study provides a promising integrated distribution mapping framework to correct the biased daily SPE, contributing to more reliable hydrological forecasts by informing accurate precipitation forcing.

Le Maroc est l'une des régions les plus vulnérables au changement climatique. Il se caractérise par des interactions complexes entre diverses caractéristiques géographiques, notamment l'océan Atlantique, la mer Méditerranée, les montagnes du Haut Atlas et le Sahara. Il est essentiel de comprendre la variabilité spatio-temporelle du climat dans cette région pour une meilleure gestion des ressources. Les modèles climatiques globaux jouent un rôle important dans ce contexte, car ce sont les seuls modèles à prendre en compte tous les réservoirs d'eau et d'énergie, y compris les réservoirs à mouvement lent comme les océans, qui modulent le climat et son évolution. Cependant, les modèles climatiques globaux sont encore sujets à des biais systématiques qui limitent leurs performances et ont généralement des résolutions grossières, limitant leur utilisation pour l’évaluation d’aspects locaux. Les modèles climatiques régionaux peuvent améliorer la représentation de certains processus (processus orographiques, brises, etc.). Cependant, ils présentent des défauts qui peuvent altérer de manière significative la crédibilité des trajectoires du changement climatique, car il est impossible de distinguer l'impact des biais systématiques dans les modèles globaux de forçage du rôle d'une meilleure description de petite échelle.Ce travail explore différentes manières de surmonter ces limitations.Dans la première partie, nous évaluons une gamme de différents ensembles à haute résolution, issus de la réduction d'échelle statistique (NEXGDDP) et dynamique (Euro-CORDEX et Euro-CORDEX ajusté au biais) tout en analysant la valeur ajoutée potentielle que la correction du biais "a posteriori" peut avoir sur la simulation des précipitations et des températures moyennes et extrêmes sur le Maroc.Dans la deuxième partie, nous utilisons le modèle LMDZ, la composante atmosphérique de la dernière version du modèle de l’IPSL, dans une configuration couplée avec le modèle de surface terrestre ORCHIDEE. Nous avons conçu une configuration du modèle à grille raffinée adaptée aux études régionales sur le Maroc, qui est suffisamment stable numériquement pour exécuter des simulations de changement climatique et qui permet i) une haute résolution sur la région et ii) une résolution suffisante à l'extérieur du zoom pour reproduire la circulation de grande échelle. Nous utilisons une méthode de correction de biais en ligne, qui consiste à corriger les erreurs systématiques des variables atmosphériques de grande échelle à l'aide des statistiques d'une simulation guidée par des réanalyses climatologiques. Cette approche permet de travailler avec une résolution fine à un coût de calcul modéré sans compromettre la cohérence entre les climats global et régional, cruciale pour le Maroc.L’évaluation du climat présent (1979-2014) a mis en évidence des améliorations notables après raffinement de la grille, notamment dans la circulation générale moyenne. La simulation libre à grille zoomée se compare favorablement aux observations de précipitations et de températures à l'échelle locale. Le climat moyen est considérablement amélioré après la correction de biais par rapport aux simulations non corrigées, et des améliorations dans le transport d’humidité, des précipitations et de la température de l’air sont observés.Pour le climat futur, la température de surface de la mer (SST) et la concentration de glace de mer (SIC) déduites de quatre modèles CMIP6 couplés, forcés par les gaz à effet de serre et les aérosols correspondant au scénario Shared Socioeconomic Pathway-8.5 (SSP-8.5), sont utilisées pour forcer la configuration régionale corrigée du LMDZ6-OR. Des simulations de 20 ans sont produites pour un niveau de réchauffement global de 3 Kelvin afin d'évaluer la réponse du climat régional moyen, des précipitations et de la température au changement des SST et SIC
Morocco is one of the most vulnerable regions to climate change. Its climate is characterized by complex interactions between various geographical features, including the Atlantic Ocean, the Mediterranean Sea, the High Atlas Mountains, and the Sahara Desert. Understanding the spatiotemporal variability of climatic patterns in this region is crucial for effective climate change adaptation strategies, natural resource management, and sustainable development planning. Global climate models (GCMs) play a significant role within this context, as they are the only models to take into account all the water and energy reservoirs, including slow-moving reservoirs such as the oceans, which modulate the climate and its evolution. Yet, global climate models are still subject to systematic biases that constrain their performance and have generally coarse resolutions, limiting the assessment of local climate patterns. Regional climate models can improve the representation of certain processes (orographic processes, breezes, etc.). They do, however, have flaws that can significantly alter the credibility of climate change trajectories, as it is impossible to distinguish the impact of systematic biases in the forcing GCMs from the role of better small-scale description.This work explores different ways of overcoming these limitations.In the first part, we evaluate a range of different widely used high-resolution ensembles issued from statistical (NEXGDDP) and dynamical (Euro-CORDEX and bias-adjusted Euro-CORDEX) downscaling while investigating the potential added value that “a posteriori'' bias adjustment may have on the simulation of mean and extreme precipitation and temperature over Morocco.In the second part, we use the LMDZ model, the atmospheric component of the latest version of the IPSL model (IPSLCM6), in a coupled configuration with the ORCHIDEE land-surface model. We designed a refined-grid configuration of the model adapted for regional studies over Morocco that is numerically stable enough for running climate change simulations and allows i) a high resolution over the region and ii) a sufficient resolution on the outside of the zoom area to reproduce large-scale patterns. To deal with the systematic large-scale dynamical biases, a run-time bias correction approach, which consists of bias-correcting the systematic errors in large-scale atmospheric variables using the statistics of a nudged simulation towards climate reanalysis, is used. This method allows for high resolution at a moderate computational cost without compromising the coherence between the global and regional climates. Indeed, preserving this coherence is crucial for Morocco since large-scale circulation patterns play a vital role in shaping regional climate patterns in the region.The evaluation of the present climate (1979–2014) has shown significant improvements after grid refinement, particularly in the mean general circulation. The free refined-grid run compares favorably to precipitation and temperature observations at the local scale. The mean climate is considerably improved after bias correction compared to the uncorrected simulations, and improvements in moisture transport, precipitation and air temperature are observed.For future climate, sea surface temperature (SST) and sea ice concentration (SIC) deduced from four coupled CMIP6 models, forced by greenhouse gases and aerosols corresponding to the Shared Socioeconomic Pathway-8.5 (SSP-8.5) scenario, are used to force the corrected regional configuration of LMDZ6-OR. Twenty-year simulations are produced for a global warming level of 3 Kelvin to assess the response of mean regional climate, precipitation and temperature to changes in SST and SIC

Abstract DNV initiated the TAM JIP in 2019 motivated by i) that the industry has experienced mooring line failures where non-optimal operation of thruster assisted mooring systems is believed to be a contributing factor, and ii) that last generation semi-submersible drilling units rely more heavily on their thruster systems. Through the TAM JIP, DNV has studied how thruster assisted mooring (TAM) systems should be safely operated, and how to adjust the design requirements accordingly. It is vital that the design analyses reflect how the TAM system will be operated offshore - this has not always been the case in the past. Central in the work has been analyses of real operations, a parametric study on the performance of a TAM operation and experience shared by the participants. This paper presents analysis guidance for thruster assisted mooring. The results are also used to give recommendations for how to operate a TAM unit, and this is presented in a companion paper at OTC 2023 /1/. The parametric study was performed in time domain for 3 TAM units of different sizes at 3 water depths and a range of metocean conditions and controller settings. Both a Kalman filter controller and an idealized controller representing assumptions in a frequency domain analysis have been studied. The analysis models used in the parametric study have been benchmarked towards both measurements from real operations and a state-of-the-art TAM controller to ensure realistic results. The study showed that it is feasible to establish a time domain analysis approach that allows for modelling non-linearities such as thrust limitations and thruster delays. In time domain analyses, the use of rotatable thrusters when the mean load is small may induce excessive azimuthing in thrusters. Such cases should be modelled by fixed direction thrusters. In real operations this is avoided by operating thrusters in bias groups. For frequency domain analyses correction factors for low-frequency motions have been proposed in lower sea states. For high sea states when constant thrust is applied no such correction factors are needed. Furthermore, it is always important to check that max thrust is not exceeded in the analyses. The validity of frequency domain programs, commonly used in analysis of TAM operations, has previously been found to be inaccurate /2/. Furthermore, it has been a discussion in the industry how, and if these frequency domain analyses can be run ensuring conservative results. Through a systematic study in the JIP guidance for analyses in both time domain and frequency domain are given. Thus, implementation of the findings provided in this paper will give the industry more realistic analysis of TAM operations than what has been common practice.