Weather forecast and earth system models usually have a number of parameters, which are often optimized manually by trial and error. Several studies have proposed objective methods to estimate model parameters using data assimilation techniques. This paper provides a review of the previous studies and illustrates the application of ensemble-based data assimilation to the estimation of temporally varying model parameters in a simple low-resolution atmospheric general circulation model known as the SPEEDY model. As shown in previous studies, our results highlight that data assimilation techniques are efficient optimization methods which can be used for parameter estimation in complex geophysical models and that the estimated parameters have a positive effect on short-to medium-range numerical weather prediction.

The Weather and Research Forecast model is tested over South America in different configurations to identify the one that gives the best estimates of observed surface variables. Systematic, nonsystematic, and total errors are computed for 48-h forecasts initialized with the NCEP Global Data Assimilation System (GDAS). There is no unique model design that best fits all variables over the whole domain, and nonsystematic errors for all configurations differ little from one another; such differences are in most cases smaller than the observed day-to-day variability. An ensemble mean consisting of runs with different parameterizations gives the best skill for the whole domain. Surface variables are highly sensitive to the choice of land surface models. Surface temperature is well represented by the Noah land model, but dewpoint temperature is best estimated by the simplest land surface model considered here, which specifies soil moisture based on climatology. This underlines the need for better understanding of humid processes at the subgrid scale. Surface wind errors decrease the intensity of the low-level jet, reducing expected heat and moisture advection over southeast South America (SESA), with negative precipitation errors over SESA and positive biases over the South Atlantic convergence zone (SACZ). This pattern of errors suggests feedbacks between wind errors, precipitation, and surface processes as follows: an increase of precipitation over the SACZ produces compensating descent in SESA, with more stable stratification, less rain, less soil moisture, and decreased rain. This is a clear example of how local errors are related to regional circulation, and suggests that improvement of model performance requires not only better parameterizations at the subgrid scales, but also improved regional models.

JUAN Josh RUIZ, ANTONIO ALDAZ, and MANUEL DOM~NGUEZ. Can. J. Chem. 55,2799Chem. 55, (1977. A polarographic study of the oxidation mechanism of L-ascorbic acid and of the reduction mechanism of dehydro-L-ascorbic acid was carried out in an acid medium.For L-ascorbic acid, the oxidation process involves a two electron transfer and obeys the overall reactionThe polarographic curve shows that the limiting current is governed by diffusion. On the rising portion of the wave, the two electron oxidation process consists of two consecutive one electron transfers, the second being the rate determining step (rds). The reaction orders, together with the Tafel slopes, were calculated.The reduction of dehydro-L-ascorbic acid at the limiting current is kinetically controlled and involves a two electron transfer. The reaction kinetic pathways were studied and the reaction orders and Tafel slope were calculated. It is deduced that, for low overvoltages, the second one electron transfer is the rate determining step. Pour I'acide L-ascorbique, le processus d'oxydation implique un transfert de deux tlectrons et est soumis a la reaction gtnerale La courbe polarographique montre que le courant limitant est gouvernt par la diffusion. Sur la portion montante de la vague, le processus d'oxydation a deux tlectrons implique deux transferts successifs d'un tlectron, le deuxieme ttant l'ttape detern~inante de la vitesse de la rtaction. Les ordres de la rtaction ainsi que les pentes de Tafel ont t t t calcults.La rtduction de I'acide dthydro-L-ascorbique, a courant limitant, est contrBlke cinktiquement et implique un transfert de deux tlectrons. On a ttudie les chemins reactionnels cinttiques et on a calcult les ordres de la reaction et la pente de Tafel. On en dtduit qu'a de bas survoltages, le deuxieme transfert d'un Clectron est l'ttape dtterminante de la vitesse de la rtaction.[Traduit par le journal]

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Sudden local severe weather is a threat, and we explore what the highest-end supercomputing and sensing technologies can do to address this challenge. Here we show that using the Japanese flagship “K” supercomputer, we can synergistically integrate “big simulations” of 100 parallel simulations of a convective weather system at 100-m grid spacing and “big data” from the next-generation phased array weather radar that produces a high-resolution 3-dimensional rain distribution every 30 s—two orders of magnitude more data than the currently used parabolic-antenna radar. This “big data assimilation” system refreshes 30-min forecasts every 30 s, 120 times more rapidly than the typical hourly updated systems operated at the world’s weather prediction centers. A real high-impact weather case study shows encouraging results of the 30-s-update big data assimilation system.

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Previous studies suggest that the enhanced meridional extent of some South American low-level jet events (known as Chaco jets) is a consequence of a positive feedback between the low-level wind and strong convection that is usually observed at their exit region. To assess how this interaction takes place, a Chaco low-level jet event observed between 18 and 19 December 2002 (i.e., during the South America Low-Level Jet Experiment) and the associated mesoscale convective system that evolved at its exit region have been selected to perform numerical experiments where diabatic heating effects associated with phase changes can be quantified. This case study has also been used to analyze the diurnal oscillations related to planetary boundary layer (PBL) mechanisms in order to describe whether the observed evolution of the low-level wind can be explained either by PBL-related forcing or by the interaction with convection. The sensitivity experiments confirm that there is a positive feedback at low levels between convection and the northerly wind flow that becomes accelerated and also aids in the identification of a strong coupling between organized convection and the upper-level circulation, resulting in an increase of the upper-level jet strength downstream of the simulated precipitation area. A conceptual model of how these systems (i.e., convection, low-and upper-level jets) mutually interact is proposed, which differs from coupling mechanisms documented for the Great Plains low-level jet.

We describe a new approach allowing for systematic causal attribution of weather and climaterelated events, in near-real time. The method is purposely designed to facilitate its implementation at meteorological centers by relying on data treatments that are routinely performed when numerically forecasting the weather. Namely, we show that causal attribution can be obtained as a by-product of so-called data as-A. Hannart