Tendency Error Research Articles

A stochastic method for improving seasonal predictions

Ensemble seasonal forecasts during boreal winter suffer from insufficient spread and systematic errors. In this study we suggest a new stochastic dynamics method to address both issues at a time. Our technique relies on random additive corrections of initial tendency error estimates of the atmospheric component of the CNRM‐CM5.1 global climate model, using ERA‐Interim as a reference over a 1979–2010 hindcast period. The random method improves deterministic scores for 500‐hPa geopotential height forecasts over the Northern Hemisphere extratropics (NH Z500), and increases the ensemble spread. An optimal method consisting in drawing the error corrections within the current month of the hindcast period illustrates the high potential of future improvements, with NH Z500 anomaly correlation reaching 0.65 and North Atlantic Oscillation index correlation 0.71 with ERA‐Interim. These substantial improvements using current year corrections pave the way for future forecasting methods using classification criteria on the correction population.

A New Method for Exploring Coupled Land–Atmosphere Dynamics

Abstract This paper proposes a new method for investigating coupled land–atmosphere interactions. The method is to apply an empirical correction technique to distinct components of a model and then examine differences between forecasts of the empirically corrected models. The correction technique is based on adding a time-dependent term to the tendency equations that subtracts the estimated tendency error at every time step. This methodology can be interpreted more generally as a series of data assimilation experiments in which only certain components of a coupled model are assimilated at a time. The correction is applied to a state-of-the-art coupled land–atmosphere model in three different ways, namely, to the atmosphere only, to the land only, and to the land and atmosphere simultaneously. The land–atmosphere interactions are inferred from monthly-mean differences between experiments. The results suggest that the land–atmosphere coupling in midlatitudes can be understood from straightforward water balance considerations, whereas the coupling in the deep tropics involves a more complicated change in regional circulation. Specifically, in midlatitudes, moisture injected into the soil is transferred to the atmosphere directly above, which in turn advects downstream and subsequently moistens the atmosphere in the downwind regions to produce positive precipitation anomalies. In the deep tropics, the regional circulation, including precipitation, is sensitive to perturbations and has no obvious relation to corrections in the atmosphere or land. The similarity of biases among different models suggests that the conclusions and methodology may be relevant to other models.

Empirical Correction of the NCEP Global Forecast System

Abstract This paper examines the extent to which an empirical correction method can improve forecasts of the National Centers for Environmental Prediction (NCEP) operational Global Forecast System. The empirical correction is based on adding a forcing term to the prognostic equations equal to the negative of the climatological tendency errors. The tendency errors are estimated by a least squares method using 6-, 12-, 18-, and 24-h forecast errors. Tests on independent verification data show that the empirical correction significantly reduces temperature biases nearly everywhere at all lead times up to at least 5 days but does not significantly reduce biases in forecast winds and humidity. Decomposing mean-square error into bias and random components reveals that the reduction in total mean-square error arises solely from reduction in bias. Interestingly, the empirical correction increases the random error slightly, but this increase is argued to be an artifact of the change in variance in the forecasts. The empirical correction also is found to reduce the bias more than traditional “after the fact” corrections. The latter result might be a consequence of the very different sample sizes available for estimation, but this difference in sample size is unavoidable in operational situations in which limited calibration data are available for a given forecast model.

West African Monsoon observed with ground‐based GPS receivers during African Monsoon Multidisciplinary Analysis (AMMA)

A ground‐based GPS network has been established over West Africa in the framework of African Monsoon Multidisciplinary Analysis (AMMA) in tight cooperation between French and African institutes. The experimental setup is described and preliminary highlights are given for different applications using these data. Precipitable water vapor (PWV) estimates from GPS are used for evaluating numerical weather prediction (NWP) models and radiosonde humidity data. Systematic tendency errors in model forecasts are evidenced. Correlated biases in NWP model analyses and radiosonde data are evidenced also, which emphasize the importance of radiosonde humidity data in this region. PWV and precipitation are tightly correlated at seasonal and intraseasonal timescales. Almost no precipitation occurs when PWV is smaller than 30 kg m−2. This limit in PWV also coincides well with the location of the intertropical discontinuity. Five distinct phases in the monsoon season are determined from the GPS PWV, which correspond either to transition or stationary periods of the West African Monsoon system. They may serve as a basis for characterizing interannual variability. Significant oscillations in PWV are observed with 10‐ to 15‐day and 15‐ to 20‐day periods, which suggest a strong impact of atmospheric circulation on moisture and precipitation. The presence of a diurnal cycle oscillation in PWV with marked seasonal evolutions is found. This oscillation involves namely different phasing of moisture fluxes in different layers implying the low‐level jet, the return flow, and the African Easterly Jet. The broad range of timescales observed with the GPS systems shows a high potential for investigating many atmospheric processes of the West African Monsoon.

Empirical Correction of a Coupled Land–Atmosphere Model

Abstract This paper investigates empirical strategies for correcting the bias of a coupled land–atmosphere model and tests the hypothesis that a bias correction can improve the skill of such models. The correction strategies investigated include 1) relaxation methods, 2) nudging based on long-term biases, and 3) nudging based on tendency errors. The last method involves estimating the tendency errors of prognostic variables based on short forecasts—say lead times of 24 h or less—and then subtracting the climatological mean value of the tendency errors at every time step. By almost any measure, the best correction strategy is found to be nudging based on tendency errors. This method significantly reduces biases in the long-term forecasts of temperature and soil moisture, and preserves the variance of the forecast field, unlike relaxation methods. Tendency errors estimated from ten 1-day forecasts produced just as effective corrections as tendency errors estimated from all days in a month, implying that the method is trivial to implement by modern standards. Disappointingly, none of the methods investigated consistently improved the random error variance of the model, although this finding may be model dependent. Nevertheless, the empirical correction method is argued to be worthwhile even if it improves only the bias, because the method has only marginal impacts on the numerical speed and represents forecast error in the form of a tendency error that can be compared directly to other terms in the tendency equations, which in turn provides clues as to the source of the forecast error.

Neuropsychological Characteristics of Highly Dissociative Healthy Individuals

ABSTRACT Objective: Dissociative disorders are characterized by disturbances in several neuropsychological domains, especially attention, memory, and consciousness. As a tendency to dissociate can also be observed in healthy individuals, and may be a risk factor for the development of dissociative disorders and posttraumatic stress disorder (PTSD), we were interested in the neuropsychological characteristics of these participants. Method: We examined attention, memory, and executive control functions in 17 high and 17 low dissociators without any psychiatric or neurological disorder and without prior experiences of trauma. Results: High dissociators showed relative performance deficiencies in tasks of memory for associative, context-dependent verbal material, visuospatial working memory, and executive control functions in terms of a heightened perseveration tendency and false positive errors. Conclusion: These cognitive deficits are consistent with models of dissociative disorders and dissociation in PTSD assuming a hippocampal and prefrontal dysfunction as a core factor. Mild cognitive impairments in otherwise healthy high dissociators may constitute a risk factor for the development of later PTSD or dissociative disorders.

Reduced Atmospheric Models Using Dynamically Motivated Basis Functions

Abstract Nonlinear deterministic reduced models of large-scale atmospheric dynamics are constructed. The dynamical framework is a quasigeostrophic three-level spectral model with realistic mean state and variability as well as Pacific–North America (PNA) and North Atlantic Oscillation (NAO) patterns. The study addresses the problem of finding appropriate basis functions for efficiently capturing the dynamics and a comparison between different choices of basis functions; it focuses on highly truncated models, keeping only 10–15 modes. The reduced model is obtained by a projection of the equations of motion onto a truncated basis spanned by empirically determined modes. The total energy metric is used in the projection; the nonlinear terms of the low-order model then conserve total energy. Apart from retuning the coefficient of horizontal diffusion, no empirical terms are fitted in the dynamical equations of the low-order model in order to properly preserve the physics of the system. Using the methodology of principal interaction patterns (PIPs), a basis is derived that carefully compromises minimizing tendency error with maximizing explained variance in the resolved modes. A new PIP algorithm is introduced that is more compact and robust than earlier PIP algorithms; a top-down approach is adopted, removing modes from the system one by one. The mean state and standard deviation of the streamfunction as well as transient momentum fluxes are well reproduced by a PIP model with only 10 modes. Probability density functions are accurately modeled and autocorrelation functions are captured fairly well using 15 modes. Reduced models based on PIPs are substantially superior to reduced models based on empirical orthogonal functions (EOFs). The leading PIPs have a higher projection onto the PNA and NAO teleconnection patterns than the corresponding EOFs. Both with EOFs and PIPs, the interactions between the resolved modes are predominantly linear and the improvement of PIP models on EOF models stems entirely from better modeling these linear interactions although the full nonlinear tendencies are optimized. There is considerable influence of smaller-scale modes on the large-scale modes due to nonlinear coupling that is not well captured by either EOFs or PIPs. This nonlinear backscattering possibly plays a role in generating the low-frequency variability of the model. The results call for a nonlinear and/or stochastic closure scheme in which PIPs may be suitable basis functions.

Numerical Problems Associated with Tropical Cyclone Intensity Prediction Using a Sophisticated Coupled Typhoon-Ocean Model

When tropical cyclone (TC) intensity is predicted using a sophisticated numerical model under a given initial condition with a typhoon bogus, numerical problems, particularly associated with the tendency errors, arise as well as problems related to the intensity limitation due to relatively coarse horizontal resolution. In order to investigate the problems, numerical experiments are performed for nine TCs in the western North Pacific from 2000 to 2002 using the typhoon model (TYM) and typhoon-ocean coupled model (CTYM). CTYM reduces the overdevelopment that occurs in the later integration predicted by TYM due to local sea surface cooling caused by the passage of TCs. However, CTYM hardly improves the tendency errors that occur in the early integration. The errors are found in all predictions using CTYM with each of the three physical schemes and have different characteristics for typhoons Bilis (2000), Wutip (2001), and Phanfone (2002). The TC thermodynamic structures of Wutip also differ from the three predictions using CTYM with each of the three schemes even at almost the same integration time and central pressure. Under the steady-state assumption, we estimate the maximum potential intensity (MPI) for three schemes and two TCs from the two-dimensional axisymmetrical mean structure. Assuming that the MPI is estimated from the net gain energy through the isothermal process scale-analyzed from the Colioris force and adiabatic process from the centrifugal force, it is found that predominance of convective available potential energy due to the adiabatic process leads to the underdevelopment of TCs. The improvement of physical schemes in CTYM is planned for the underdevelopment: revising a surface boundary formulation or introducing a sophisticated planetary boundary formulation contributes to increasing the energy caused by the isothermal process, while revising the precipitation or cumulus parameterization contributes to reducing the energy caused by the adiabatic process.

Validity threats: overcoming interference with proposed interpretations of assessment data.

Factors that interfere with the ability to interpret assessment scores or ratings in the proposed manner threaten validity. To be interpreted in a meaningful manner, all assessments in medical education require sound, scientific evidence of validity. The purpose of this essay is to discuss 2 major threats to validity: construct under-representation (CU) and construct-irrelevant variance (CIV). Examples of each type of threat for written, performance and clinical performance examinations are provided. The CU threat to validity refers to undersampling the content domain. Using too few items, cases or clinical performance observations to adequately generalise to the domain represents CU. Variables that systematically (rather than randomly) interfere with the ability to meaningfully interpret scores or ratings represent CIV. Issues such as flawed test items written at inappropriate reading levels or statistically biased questions represent CIV in written tests. For performance examinations, such as standardised patient examinations, flawed cases or cases that are too difficult for student ability contribute CIV to the assessment. For clinical performance data, systematic rater error, such as halo or central tendency error, represents CIV. The term face validity is rejected as representative of any type of legitimate validity evidence, although the fact that the appearance of the assessment may be an important characteristic other than validity is acknowledged. There are multiple threats to validity in all types of assessment in medical education. Methods to eliminate or control validity threats are suggested.

Is a Central Tendency Error Inherent in the Use of Semantic Differential Scales in Different Cultures?

This paper examines the effect of alternative scale formats on reporting the nature and extent of attitudes toward grocery supermarkets on bipolar semantic differential measurement scales. A traditional one-stage format and an alternative two-stage format were tested in two studies conducted in different countries. In general, the two-stage format generated the greatest percentage of extreme-position (i.e. greatest amount) responses across scales, indicating that the more usual traditional one-stage format is subject to a central tendency form-related error. A test of predictive ability showed that the two-stage format was a better predictor of shopping behaviour in one country, whereas the results for the other country were mixed, although for the most part the two-stage format did a better job of prediction. Consequently, a question can be raised about the etic attributes of this measurement scale.

Principles of disaster management lesson 11: personnel evaluation.

A disaster manager must be able to evaluate staff members in order to make effective staffing decisions during the transitions between phases of a disaster and to help improve the performance of the operation by determining what aspects of an individual's work needs improvement. Criteria for personnel appraisal and measures of performance, objective or subjective, are essential to conduct a fair and thorough evaluation. Errors introduce bias into the appraisal in the form of a "halo" effect, harsh or lenient ratings, a central tendency error, or recency effect, but recognition of these errors helps reduce their effect. A results-based appraisal program is favored because it focuses on what the worker achieves. Regular appraisal periods are suggested for optimal improvement in performance. Suggestions are given for an effective personnel appraisal, such as focusing on positive work performance, being aware of biases in judging people, and being specific when citing examples of work performance.

Correction of Systematic Errors in Coupled GCM Forecasts

The prognostic tendency (PT) correction method is applied in an attempt to reduce systematic errors in coupled GCM seasonal forecasts. The PT method computes the systematic initial tendency error (SITE) of the coupled model and subtracts it from the discrete prognostic equations. In this study, the PT correction is applied only to the three-dimensional ocean temperature. The SITE is computed by calculating a climatologically averaged difference between coupled model initial conditions and resulting forecasts at very short lead times and removing the observed mean seasonal tendency. Two sets of coupled GCM forecasts, one using an annual mean SITE correction and the other using a SITE correction that is a function of season, are compared with a control set of uncorrected forecasts. Each set consists of 17 12-month forecasts starting on 1 January from 1980 through 1996. The PT correction is found to be an effective method for maintaining a more realistic forecast climatology by reducing systematic ocean temperature errors that lead to a relaxation of the tropical Pacific thermocline slope and a weak tropical SST annual cycle in the control set. The annual mean PT correction, which allows the model to freely generate its own seasonal cycle, leads to increased prediction skill for tropical Pacific SSTs while the seasonally varying PT correction has no impact on this skill. Physical mechanisms responsible for improvements in the coupled model’s annual cycle and forecast skill are investigated. The annual mean structure of the tropical Pacific thermocline is found to be essential for producing a realistic SST annual cycle. The annul mean PT correction helps to maintain a realistic thermocline slope that allows surface winds to impact the annual cycle of SST in the eastern Pacific. Forecast skill is increased if the coupled model correctly captures dynamical modes related to ENSO. The annual mean correction leads to a model ENSO that is best characterized as a delayed oscillator mode while the control model appears to have a more stationary ENSO mode; this apparently has a positive impact on ENSO forecast skill in the PT corrected model.

Using tendency errors to tune the parameterisation of unresolved dynamical scale interactions in atmospheric general circulation models

Using tendency errors to tune the parameterisation of unresolved dynamical scale interactions in atmospheric general circulation models

Using tendency errors to tune the parameterisation of unresolved dynamical scale interactions in atmospheric general circulation models

A parameterisation of non-linear dynamical interactions with unresolved scales is needed inmost atmospheric models to ensure realistic fluxes of energy and enstrophy near and at thetruncation limit. In this paper, a minimisation of tendency errors in low to medium resolutionversions of the ARPEGE/IFS and the ECHAM4 spectral general circulation models is soughtin order to obtain spectral empirical interaction functions (EIFs) to be used in the formulationof horizontal diffusion. The tendency errors are calculated relative to high resolution adiabaticversions of the models themselves, meaning that the EIFs reflect all non-linear adiabatic processes.Different EIFs are obtained for vorticity, divergence and temperature. The most strikingfeature is that the vorticity and temperature EIFs have non-negligible negative values for lowwave numbers in large parts of the troposphere. This implies that these waves are enhanced inamplitude due to non-linear interactions with unresolved scales. For low resolution models thegeneration/dissipation of kinetic energy due to the interactions is not well parameterised byeither the standard horizontal diffusion in the models, or the EIFs computed here. When theEIFs are used in the formulation of horizontal diffusion it is seen that the kinetic energyspectrum is closer to observations than in the original model versions. Furthermore, the largescale systematic model errors are reduced in a medium resolution simulation, while less clearimprovement is seen in a simulation at low resolution. It is argued that the technique used inthis paper is quite general and may be used to develop a more realistic parameterisation ofunresolved dynamical scale interactions. The method should, with some modifications, also beapplicable in semi-Lagrangian spectral models and in grid point models.

A Statistical Closure of a Low-Order Barotropic Model

In this paper, an attempt to close a low-order barotropic model for the neglected interactions in a perfect model setting is described. A barotropic T21 model with forcing and dissipation included is reformulated in terms of its EOFs. The EOFs are calculated from a long integration, and evolution equations are derived for the EOF amplitudes. A low-order EOF model is obtained by retaining only the 20 most dominant EOF structures and neglecting interactions with the remaining 211 EOFs. An attempt is made to describe the tendency error of the EOF model with a linear combination of resolved EOF amplitudes plus their quadratic combinations. The linear combination minimizes in a least squares sense the tendency error of the EOF model on the attractor of the full T21 model. It is found that, only if quadratic combinations of EOF amplitudes are taken into account, the closure reduces the tendency error substantially. The impact of the closure on the forecast skill of the EOF model is studied by making 100 3-week forecasts starting from independent initial conditions on the attractor of T21. The average useful forecast range increases from 12 days without closure to 18 days with closure. However, the method seems questionable in two aspects. First, the corrections to the coefficients of the evolution equations of the EOF amplitudes are as large as the coefficients themselves. Second, the closed EOF model could not simulate the climate. The closed model does not conserve energy in the absence of forcing and dissipation, and for this reason does not possess a stable attractor. Modifications to the proposed closure are mentioned to solve this problem. In conclusion, the proposed closure without the mentioned modifications leads to a statistical model that has an improved predictive skill but fails to simulate the climate of the original T21 barotropic model.

Systematic Tendency Error in Budget Calculations

Abstract Atmospheric budget calculations suffer from various observational and numerical errors. This paper demonstrates that all budget calculations applied to a large number of samples suffer from additional errors originating from systematic tendency errors of the budget equation used. Quantitative evaluation of this systematic tendency error for various types of budget computations showed that the systematic tendency errors are generally comparable in magnitude to the leading terms in the budget equations. Because of this error, the calculated budget does not satisfy conservation properties under steady conditions.

The Diagnosis of Mechanical Dissipation in the Atmosphere from Large-Scale Balance Requirements

The momentum budget for January 1987 is evaluated with global observations analyzed at the European Centre for Medium-Range Weather Forecasts (ECMWF). The dissipation term is diagnosed from the budget as a balance requirement, that is, as that required to balance the sum of the advection, Coriolis, pressure gradient, and local tendency terms. This is then compared with the parameterized subgrid-scale effects in the ECMWF model's momentum equation, with a view of identifying possible errors in those parameterizations. The balance requirement does not support the high parameterized values of orographically induced gravity-wave drag in the lower stratosphere. A deeper analysis also does not suggest a major role for turbulent vertical transports above the boundary layer. On the other hand, our budget does indicate that more effort be spent on a better representation of the potential enstrophy cascade associated with Rossby wave breaking in the upper troposphere. These statements are qualified by the errors in the balance requirement itself. The extent to which this is a problem is discussed. A distinctive feature of these calculations is their internal consistency., that is, all the terms in the budget are evaluated as in the version of the ECMWF model used for assimilating the observations. This offers several advantages, not the least of which is that it makes our budget residuals identical to the systematic initial tendency errors of the operational weather forecasts, thus facilitating their computation and routine monitoring. As such, our calculations explain a large fraction of the systematic short-range forecast errors and, because of their local character, provide clues as to the possible sources of those errors. Experiments with and without gravity-wave drag are described to illustrate its large contribution during this period to the southerly wind error of the operational weather forecasts at 70 mb over western North America.

Preliminary Assessment of Format-Specific Central Tendency and Leniency Error in Summated Rating Scales

Data for 4-, 5-, and 7-position Likert formats from 292 undergraduates showed systematic error varied among formats, i.e., central tendency errors tended to increase with increasing numbers of categories and to reduce variances expected.

A Monte Carlo Simulation of Effects of Central Tendency Error on the Magnitude of Cronbach's Coefficient Alpha

Relationships between central tendency error and estimates of reliability based on Cronbach's coefficient alpha were explored. Using a Monte Carlo simulation, no differences were found between the means of distributions of alphas derived from “central tendency biased data” and “random data.” Further it was found that alphas' constancy was the result of systematic reduction in the item standard deviations and increase in inter-item correlations associated with central tendency error. It was noted, however, that in this simulation “equal error” among the test items was assumed; further research with other assumptions is recommended.

BEHAVIORALLY BASED RATING SCALES: EFFECTS OF SPECIFIC ANCHORS AND DISGUISED SCALE CONTINUA

The psychometric properties of behaviorally based rating scales contrasted by (1) disguised versus obvious scale format and (2) specific anchors versus more general descriptions of behavior were compared. Results indicated no consistent differences in leniency or central tendency errors among the scales. Both multitrait‐multirater ANOVA and factor analyses favored obvious scale methods to a disguised mixed standard scale format. No firm conclusions could be drawn regarding the effects of specificity of behavioral anchors.