Representation of model error in a convective-scale ensemble prediction system

In this paper ensembles of forecasts (of up to six hours) are studied from a convection-permitting model with a representation of model error due to unresolved processes. The ensemble prediction system (EPS) used is an experimental convection-permitting version of the UK Met Office’s 24- member Global and Regional Ensemble Prediction System (MOGREPS). The method of representing model error variability, which perturbs parameters within the model’s parameterisation schemes, has been modified and we investigate the impact of applying this scheme in different ways. These are: a control ensemble where all ensemble members have the same parameter values; an ensemble where the parameters are different between members, but fixed in time; and ensembles where the parameters are updated randomly every 30 or 60 min. The choice of parameters and their ranges of variability have been determined from expert opinion and parameter sensitivity tests. A case of frontal rain over the southern UK has been chosen, which has a multi-banded rainfall structure. The consequences of including model error variability in the case studied are mixed and are summarised as follows. The multiple banding, evident in the radar, is not captured for any single member. However, the single band is positioned in some members where a secondary band is present in the radar. This is found for all ensembles studied. Adding model error variability with fixed parameters in time does increase the ensemble spread for near-surface variables like wind and temperature, but can actually decrease the spread of the rainfall. Perturbing the parameters periodically throughout the forecast does not further increase the spread and exhibits “jumpiness” in the spread at times when the parameters are perturbed. Adding model error variability gives an improvement in forecast skill after the first 2–3 h of the forecast for near-surface temperature and relative humidity. For precipitation skill scores, adding model error variability has the effect of improving the skill in the first 1–2 h of the forecast, but then of reducing the skill after that. Complementary experiments were performed where the only difference between members was the set of parameter values (i.e. no initial condition variability). The resulting spread was found to be significantly less than the spread from initial condition variability alone.

Exploring writing in products in students with language impairments and autism spectrum disorders

Oral language skills scaffold written text production; students with oral language difficulties often experience writing problems. The current study examines the ways in which oral language problems experienced by students with language impairment (LI) and students with autism spectrum disorders (ASD) impact on their production of written text. One hundred and fifty seven participants (Mage = 10;2) with LI or ASD completed standardized measures of oral language, transcription, working memory, and nonverbal ability and produced a written narrative text assessed for productivity, grammatical accuracy, and quality. Measures of transcription, productivity, and grammatical accuracy, but not text quality, were poorer for students with LI. Transcription skills accounted for the majority of variance in the writing of the LI cohort. For the ASD cohort, handwriting, oral language and autism symptomatology were significant predictors. When students with ASD also experienced language problems, their performance was equivalent to that observed in the LI cohort.

A route to systematic error in forecasts of Rossby waves

Recent work has shown that both the amplitude of upper-level Rossby waves and the tropopause sharpness decrease with forecast lead time for several days in some operational weather forecast systems. In this contribution, the evolution of error growth in a case study of this forecast error type is diagnosed through analysis of operational forecasts and hindcast simulations. Potential vorticity (PV) on the 320-K isentropic surface is used to diagnose Rossby waves. The Rossby-wave forecast error in the operational ECMWF high-resolution forecast is shown to be associated with errors in the forecast of a warm conveyor belt (WCB) through trajectory analysis and an error metric for WCB outflows. The WCB forecast error is characterised by an overestimation of WCB amplitude, a location of the WCB outflow regions that is too far to the southeast, and a resulting underestimation of the magnitude of the negative PV anomaly in the outflow. Essentially the same forecast error development also occurred in all members of the ECMWF Ensemble Prediction System and the Met Office MOGREPS-15 suggesting that in this case model error made an important contribution to the development of forecast error in addition to initial condition error. Exploiting this forecast error robustness, a comparison was performed between the realised flow evolution, proxied by a sequence of short-range simulations, and a contemporaneous forecast. Both the proxy to the realised flow and the contemporaneous forecast a were produced with the Met Office Unified Model enhanced with tracers of diabatic processes modifying potential temperature and PV. Clear differences were found in the way potential temperature and PV are modified in the WCB between proxy and forecast. These results demonstrate that differences in potential temperature and PV modification in the WCB can be responsible for forecast errors in Rossby waves.

Diagnosing observation error correlations for Doppler radar radial winds in the Met Office UKV model using observation-minus-background and observation-minus-analysis statistics

With the development of convection-permitting numerical weather prediction the efficient use of high resolution observations in data assimilation is becoming increasingly important. The operational assimilation of these observations, such as Dopplerradar radial winds, is now common, though to avoid violating the assumption of un- correlated observation errors the observation density is severely reduced. To improve the quantity of observations used and the impact that they have on the forecast will require the introduction of the full, potentially correlated, error statistics. In this work, observation error statistics are calculated for the Doppler radar radial winds that are assimilated into the Met Office high resolution UK model using a diagnostic that makes use of statistical averages of observation-minus-background and observation-minus-analysis residuals. This is the first in-depth study using the diagnostic to estimate both horizontal and along-beam correlated observation errors. By considering the new results obtained it is found that the Doppler radar radial wind error standard deviations are similar to those used operationally and increase as the observation height increases. Surprisingly the estimated observation error correlation length scales are longer than the operational thinning distance. They are dependent on both the height of the observation and on the distance of the observation away from the radar. Further tests show that the long correlations cannot be attributed to the use of superobservations or the background error covariance matrix used in the assimilation. The large horizontal correlation length scales are, however, in part, a result of using a simplified observation operator.

Argument structures in Chinese university students’ argumentative writing: a contrastive study

Situated within a Systemic Functional Linguistics genre paradigm, this study adopted a function-based linguistic approach to examine the argument structures in English writing produced by Chinese university students of English as foreign language (EFL). Their English writing was contrasted with three other sets of argumentative essays in order to explore differences and similarities in the use of argument structures. The four sets of essays were produced by three groups of university students: native English- and Chinese-speaking university students and Chinese university EFL students. Participants’ interviews and questionnaire responses were also collected. The study found that most native English-speaking participants used an analytical arguing strategy, while most Chinese-speaking university participants preferred a hortatory argument structure both in their English and Chinese writing. It was also found that Chinese participants’ English writing was influenced by both English and Chinese.

The acquisition of verbal paradigms in Dutch and Greek L2 children: cross-linguistic differences and inflectional defaults

Previous research with children learning a second language (L2) has reported errors with verb inflection and cross-linguistic variation in accuracy and error patterns. However, owing to the cross-linguistic complexity and diversity of different verbal paradigms, the cross-linguistic effects on the nature of default forms has not been directly addressed in L2 acquisition studies. In the present study, we compared accuracy and error patterns in verbal agreement inflections in L2 children acquiring Dutch and Greek, keeping the children’s L1 constant (Turkish). Results showed that inflectional defaults in Greek follow universal predictions regarding the morphological underspecification of paradigms. However, the same universal predictions do not apply to the same extent to Dutch. It is argued that phonological properties of inflected forms should be taken into account to explain cross-linguistic differences in the acquisition of inflection. By systematically comparing patterns in child L2 Dutch and Greek, this study shows how universal mechanisms and target language properties work in tandem in the acquisition of inflectional paradigms.

An idealized study of coupled atmosphere-ocean 4D-Var in the presence of model error

Atmosphere only and ocean only variational data assimilation (DA) schemes are able to use window lengths that are optimal for the error growth rate, non-linearity and observation density of the respective systems. Typical window lengths are 6-12 hours for the atmosphere and 2-10 days for the ocean. However, in the implementation of coupled DA schemes it has been necessary to match the window length of the ocean to that of the atmosphere, which may potentially sacrifice the accuracy of the ocean analysis in order to provide a more balanced coupled state. This paper investigates how extending the window length in the presence of model error affects both the analysis of the coupled state and the initialized forecast when using coupled DA with differing degrees of coupling. Results are illustrated using an idealized single column model of the coupled atmosphere-ocean system. It is found that the analysis error from an uncoupled DA scheme can be smaller than that from a coupled analysis at the initial time, due to faster error growth in the coupled system. However, this does not necessarily lead to a more accurate forecast due to imbalances in the coupled state. Instead coupled DA is more able to update the initial state to reduce the impact of the model error on the accuracy of the forecast. The effect of model error is potentially most detrimental in the weakly coupled formulation due to the inconsistency between the coupled model used in the outer loop and uncoupled models used in the inner loop.