The Reanalysis for the Global Ensemble Forecast System, version 12.

NOAA has created a global reanalysis data set, intended primarily for initialization of reforecasts for its Global Ensemble Forecast System, version 12 (GEFSv12), which provides ensemble forecasts out to +35 days lead time. The reanalysis covers the period 2000-2019. It assimilates most of the observations that were assimilated into the operational data assimilation system used for initializing global predictions. These include a variety of conventional data, infrared and microwave radiances, Global Positioning System radio occultations, and more. The reanalysis quality is generally superior to that from NOAA’s previous-generation Climate Forecast System Reanalysis (CFSR), demonstrated in the fit of short-term forecasts to the observations and in the skill of 5-day deterministic forecasts initialized from CFSR vs. GEFSv12. Skills of reforecasts initialized from the new reanalyses are similar but slightly lower than skills initialized from a pre-operational version of the real-time data assimilation system conducted at the higher, operational resolution. Control member reanalysis data on vertical pressure levels are made publicly available.

Case Dependence of Multiscale Interactions between Multisource Perturbations for Convection-Permitting Ensemble Forecasting during SCMREX

This study examines the case dependence of the multiscale characteristics of initial condition (IC) and model physics (MO) perturbations and their interactions in a convection-permitting ensemble prediction system (CPEPS), focusing on the 12-h forecasts of precipitation perturbation energy. The case dependence of forecast performances of various ensemble configurations is also examined to gain guidance for CPEPS design. Heavy-rainfall cases over Southern China during the Southern China Monsoon Rainfall Experiment (SCMREX) in May 2014 were discriminated between the strongly and weakly forced events in terms of synoptic-scale forcing, each of which included 10 cases. In the cases with weaker forcing, MO perturbations showed larger influences while the enhancements of convective activities relative to the control member due to IC perturbations were less evident, leading to smaller dispersion reduction due to adding MO perturbations to IC perturbations. Such dispersion reduction was more sensitive to IC and MO perturbation methods in the weakly and strongly forced cases, respectively. The dispersion reduction improved the probabilistic forecasts of precipitation, with more evident improvements in the cases with weaker forcing. To improve the benefits of dispersion reduction in forecasts, it is instructive to elaborately consider the case dependence of dispersion reduction, especially the various sensitivities of dispersion reduction to different-source perturbation methods in various cases, in CPEPS design.

High-response electrorheological servo valve

The demand of more powerful and high-dynamic hydraulic actuators gives the servo valve as a control member an increasingly important role. The valve should provide the hydraulic actuator with sufficient volume flow over wide frequency range to achieve large strains at high operating frequencies. Here, the electrorheological effect as an electrohydraulic valve drive offers great potential. It converts the electrical input signal directly into a controlling mechanical quantity within a few milliseconds and provides theoretically unlimited strain. Thus, the electrorheological effect has the ability to increase the performance of conventional hydraulic systems. This work presents a two-stage servo valve with an electrorheological pilot stage. Furthermore, it introduces a model to describe the static and dynamic properties of the system. The model is validated on the basis of measurement results.

Global Assessments of Surface Winds and Waves From an Ensemble Forecast System Using Satellite Data

This paper evaluates the 10-m wind intensities and significant wave heights from the NCEP Ensemble Forecast System using altimeter data. A total of 20 perturbed members plus a control member (deterministic run) compose the ensemble. The assessment is focused on the comparison between the control run and the ensemble mean, in terms of benefits presented by four error metrics. Four satellite missions are selected for the assessments, obtained from AVISO and NESDIS/NOAA databases. Results show that the scatter components of the errors strongly depends on the latitude, were extra-tropical locations at longer forecast times present large errors. A significant improvement using the ensemble forecast compared to deterministic runs was verified at these locations, where the RMSE of day 10 was reduced from 5 to 3.5 m/s for U10 and from 1.8 to 1.3 meters for Hs.

Bending test of a composite steel-timber beam jointed by bolts

<p>In light of global environment issues, the authors proposed a building system comprising steel and timber structure (Hereafter referred to as CSTS), which consist of rolled-H section steel and timber. The CSTS is assumed to adapt for mid-rise story building steel structures. It is a design method of the CSTS that uses the concept of a damage-controlled structure characterized by using buckling-restrained braces as a seismic response control member. It is assumed to use materials such as a cross laminated timber(CLT) for floor structure of the CSTS. The hysteresis model of the CSTS is established based on the available experimental data. Assuming practicality, bending test of the composite steel-timber beam members jointed by bolts is conducted. Behaviour of the composite steel-timber beam members affected by different intervals of bolted joints is evaluated.</p>

Assessments of Surface Winds and Waves from the NCEP Ensemble Forecast System

The error characteristics of surface waves and winds produced by ensemble forecasts issued by the National Centers for Environmental Prediction are analyzed as a function of forecast range and severity. Eight error metrics are compared, separating the scatter component of the error from the systematic bias. Ensemble forecasts of extreme winds and extreme waves are compared to deterministic forecasts for long lead times, up to 10 days. A total of 29 metocean buoys is used to assess 1 year of forecasts (2016). The Global Wave Ensemble Forecast System (GWES) performs 10-day forecasts four times per day, with a spatial resolution of 0.5° and a temporal resolution of 3 h, using a 20-member ensemble plus a control member (deterministic) forecast. The largest errors in GWES, beyond forecast day 3, are found to be associated with winds above 14 m s−1 and waves above 5 m. Extreme percentiles after the day-8 forecast reach 30% of underestimation for both 10-m-height wind (U10) and significant wave height (Hs). The comparison of probabilistic wave forecasts with deterministic runs shows an impressive improvement of predictability on the scatter component of the errors. The error for surface winds drops from 5 m s−1 in the deterministic runs, associated with extreme events at longer forecast ranges, to values around 3 m s−1 using the ensemble approach. As a result, GWES waves are better predicted, with a reduction in error from 2 m to less than 1.5 m for Hs. Nevertheless, under extreme conditions, critical systematic and scatter errors are identified beyond the day-6 and day-3 forecasts, respectively.

Short-range solar radiation forecasts over Sweden

In this article the performance for short-range solar radiation forecasts by the global deterministic and ensemble models from the European Centre for Medium-Range Weather Forecasts (ECMWF) is compared with an ensemble of the regional mesoscale model HARMONIE-AROME used by the national meteorological services in Sweden, Norway and Finland. Note however that only the control members and the ensemble means are included in the comparison. The models resolution differs considerably with 18 km for the ECMWF ensemble, 9 km for the ECMWF deterministic model, and 2.5 km for the HARMONIE-AROME ensemble. The models share the same radiation code. It turns out that they all underestimate systematically the Direct Normal Irradiance (DNI) for clear-sky conditions. Except for this shortcoming, the HARMONIE-AROME ensemble model shows the best agreement with the distribution of observed Global Horizontal Irradiance (GHI) and DNI values. During mid-day the HARMONIE-AROME ensemble mean performs best. The control member of the HARMONIE-AROME ensemble also scores better than the global deterministic ECMWF model. This is an interesting result since mesoscale models have so far not shown good results when compared to the ECMWF models. Three days with clear, mixed and cloudy skies are used to illustrate the possible added value of a probabilistic forecast. It is shown that in these cases the mesoscale ensemble could provide decision support to a grid operator in terms of forecasts of both the amount of solar power and its probabilities.