Simulation of Severe Thunderstorms in Conjugation of Westerly and Easterly on 31 March 2019 in Bangladesh

The diagnostic and prognostic studies of thunderstorms/squalls are very important to save live and loss of properties. The present study aims at diagnose the different tropospheric parameters, instability and synoptic conditions associated the severe thunderstorms with squalls, which occurred at different places in Bangladesh on 31 March 2019. For prognostic purposes, the severe thunderstorms occurred on 31 March 2019 have been numerically simulated. In this regard, the Weather Research and Forecasting (WRF) model is used to predict different atmospheric conditions associated with the severe storms. The study domain is selected for 9 km horizontal resolution, which almost covers the south Asian region. Numerical experiments have been conducted with the combination of WRF single-moment 6 class (WSM6) microphysics scheme with Yonsei University (YSU) PBL scheme in simulation of the squall events. Model simulated results are compared with the available observations. The observed values of CAPE at Kolkata both at 0000 and 1200 UTC were 2680.4 and 3039.9 J kg-1 respectively on 31 March 2019 and are found to be comparable with the simulated values. The area averaged actual rainfall for 24 hrs is found is 22.4 mm, which complies with the simulated rainfall of 20-25 mm for 24 hrs. Journal of Engineering Science 12(3), 2021, 29-43

Application of Bias Correction to Improve WRF Ensemble Wind Speed Forecast

Surface wind speed forecast from an operational WRF Ensemble Prediction System (WEPS) was verified, and the system-bias representations of the WEPS were investigated. Results indicated that error characteristics of the ensemble 10-m wind speed forecast were diurnally variated and clustered with the usage of the planetary boundary layer (PBL) scheme. To correct the error characteristics of the ensemble wind speed forecast, three system-bias representations with decaying average algorithms were studied. One of the three system-bias representations is represented by the forecast error of the ensemble mean (BC01), and others are assembled from each PBC group (BC03) as well as an independent member (BC20). System bias was calculated daily and updated within a 5-month duration, and the verification was conducted in the last month, including 316 gauges around Taiwan. Results show that the mean of the calibrated ensemble (BC03) was significantly improved as the calibrated ensemble (BC20), but both demonstrated insufficient ensemble spread. However, the calibrated ensemble, BC01, with the best dispersion relation could be extracted as a more valuable deterministic forecast via the probability matched mean method (PMM).

The Sensitivity of the Fitch Wind Farm Parameterization to a Three-Dimensional Planetary Boundary Layer Scheme

Wind plant wake impacts can be estimated with a number of simulation methodologies, each with its own fidelity and sensitivity to model inputs. In turbine-free mesoscale simulations, hub-height wind speeds can significantly vary with the choice of a planetary boundary layer (PBL) scheme. However, the sensitivity of wind plant wakes to a PBL scheme has not been explored because, until now, wake parameterizations were only compatible with one PBL scheme. We couple the Fitch wind farm parameterization with the new NCAR 3DPBL scheme and compare the resulting wakes to those simulated with a widely used PBL scheme. First, we simulate a wind plant in a pseudo-steady state under idealized stable, neutral, and unstable conditions with two PBL schemes: MYNN and the NCAR 3DPBL. For these idealized scenarios, MYNN consistently predicts internal wakes that are 0.25–1.5 m s−1 stronger than internal 3DPBL wakes. However, because MYNN predicts stronger inflow winds than the 3DPBL, MYNN predicts average capacity factors that are as large as 13 percentage points higher than with the 3DPBL, depending on the stability. To extend this sensitivity study, we conduct a month-long case study with both PBL schemes centered on the Vineyard Wind 1 lease area in the mid-Atlantic United States. Under stable and unstable conditions averaged across the month, MYNN again predicts stronger internal waking—by about 0.25 m s−1. However, again due to stronger plant inflow wind speeds in MYNN, the 3DPBL generates 4.7 %–7.8 % less power than MYNN in August 2020, depending on the turbine build-out scenario. Differences between PBL schemes can be even larger for individual instances in time. These simulations suggest that PBL schemes represent a meaningful source of modeled wind resource uncertainty; therefore, we recommend incorporating PBL variability into future wind plant planning sensitivity studies as well as wind forecasting studies.

Bayesian model averaging of the RegCM temperature projections: a Canadian case study

The choices of physical schemes coupled in the regional climate model (RegCM), the input general circulation model (GCM) results, and the emission scenarios may cause considerable uncertainties in future temperature projections. Therefore, the ensemble approach, which can be used to reflect these uncertainties, is highly desired. In this study, the probabilistic projections for future temperature are generated at 88 Canadian climate stations based on the developed RegCM ensemble and obtained Bayesian model averaging (BMA) weights. The BMA weights indicate that the RegCM coupled with the holtslag PBL scheme driven by the HadGEM can provide relatively reliable temperature projections at most climate stations. It is also suggested that the BMA approach is effective in simulating temperature over middle and eastern Canada through taking the advantage of each ensemble member. However, the effectiveness of the BMA method is limited when all the models in the ensemble cannot simulate the temperature robustly. The projected results demonstrate that the temperature will increase continuously in the future, while the temperature increase under RCP8.5 will be significantly larger than that under RCP4.5.

Influence on the temperature estimation of the planetary boundary layer scheme with different minimum eddy diffusivity in WRF v3.9.1.1

The minimum eddy diffusivity (Kzmin⁡) in the planetary boundary layer (PBL) scheme can influence the model performance when simulating meteorological parameters such as temperature. However, detailed studies on the sensitivities of the simulated temperatures to the settings of Kzmin⁡ are still lacking. Thus, in this study we evaluated the performance of the ACM2 (Asymmetrical Convective Model version 2) scheme in the WRF (Weather Research and Forecasting) model with different Kzmin⁡ settings when simulating the spatiotemporal distribution of the temperature in the region of Beijing, China. Five constant values and a function were implemented in the model to calculate Kzmin⁡, and the simulation results with different Kzmin⁡ settings were compared and analyzed. The results show that the increase in Kzmin⁡ leads to an elevation of the 2 m temperature, especially at nighttime. We figured out that the deviation in the 2 m temperature at night is mainly caused by the different estimations of the turbulent mixing under stable conditions in simulation scenarios with different Kzmin⁡ settings. Moreover, the spatial distribution of the temperature deviation indicates that under various underlying surface categories, the change in Kzmin⁡ exerts a distinct influence on the prediction of the 2 m temperature. This influence was found to be stronger during the nighttime than during the daytime, in plain areas than in mountain areas, and in urban areas than in non-urban areas. During the night in the urban areas, the influence on the simulated 2 m temperature brought about by the change in Kzmin⁡ is the strongest. In addition, the model performance using a functional-type Kzmin⁡ in the ACM2 scheme for capturing the spatiotemporal distribution of the temperature in this region was also compared with that using a constant Kzmin⁡.

“Gray Zone” Simulations using a Three-Dimensional Planetary Boundary Layer Parameterization in the Weather Research and Forecasting Model

Generating accurate weather forecasts of planetary boundary layer (PBL) properties is challenging in many geographical regions, oftentimes due to complex topography or horizontal variability in, for example, land characteristics. While recent advances in high-performance computing platforms have led to an increase in the spatial resolution of numerical weather prediction (NWP) models, the horizontal grid cell spacing (Δ x) of many regional-scale NWP models currently fall within or are beginning to approach the gray zone (i.e., Δ x ≈ 100 – 1000 m). At these grid cell spacings, three-dimensional (3D) effects are important, as the most energetic turbulent eddies are neither fully parameterized (as in traditional mesoscale simulations) nor fully resolved [as in traditional large eddy simulations (LES)]. In light of this modeling challenge, we have implemented a 3D PBL parameterization for high-resolution mesoscale simulations using the Weather Research and Forecasting model. The PBL scheme, which is based on the algebraic model developed by Mellor and Yamada, accounts for the 3D effects of turbulence by calculating explicitly the momentum, heat, and moisture flux divergences in addition to the turbulent kinetic energy. In this study, we present results from idealized simulations in the gray zone that illustrate the benefit of using a fully consistent turbulence closure framework under convective conditions. While the 3D PBL scheme reproduces the evolution of convective features more appropriately than the traditional 1D PBL scheme, we highlight the need to improve the turbulent length scale formulation.

A Single Column Model Evaluation of Mixing Length Formulations and Constraints for the sa-TKE-EDMF Planetary Boundary Layer Parameterization

Parameterizing boundary layer turbulence is a critical component of numerical weather prediction and the representation of turbulent mixing of momentum, heat, and other tracers. The components that make up a boundary layer scheme can vary considerably, with each scheme having a combination of processes that are physically represented along with tuning parameters that optimize performance. Isolating a component of a PBL scheme to examine its impact is essential for understanding the evolution of boundary layer profiles and their impact on the mean structure. In this study we conduct three experiments with the scale-aware TKE eddy-diffusivity mass-flux (sa-TKE-EDMF) scheme: 1) releasing the upper limit constraints placed on mixing lengths, 2) incrementally adjusting the tuning coefficient related to wind shear in the modified Bougeault and Lacarrere (BouLac) mixing length formulation, and 3) replacing the current mixing length formulations with those used in the MYNN scheme. A diagnostic approach is adopted to characterize the bulk representation of turbulence within the residual layer and boundary layer in order to understand the importance of different terms in the TKE budget as well as to assess how the balance of terms changes between mixing length formulations. Although our study does not seek to determine the best formulation, it was found that strong imbalances led to considerably different profile structures both in terms of the resolved and subgrid fields. Experiments where this balance was preserved showed a minor impact on the mean structure regardless of the turbulence generated. Overall, it was found that changes to mixing length formulations and/or constraints had stronger impacts during the day while remaining partially insensitive during the evening.

Role of Advection of Parameterized Turbulence Kinetic Energy in Idealized Tropical Cyclone Simulations

Horizontal homogeneity is typically assumed in the design of planetary boundary layer (PBL) parameterizations in weather prediction models. Consistent with this assumption, PBL schemes with predictive equations for subgrid turbulence kinetic energy (TKE) typically neglect advection of TKE. However, tropical cyclone (TC) boundary layers are inhomogeneous, particularly in the eyewall. To gain further insight, this study examines the effect of advection of TKE using the Mellor-Yamada-Nakanishi-Niino (MYNN) PBL scheme in idealized TC simulations. The analysis focuses on two simulations, one that includes TKE advection (CTL) and one that does not (NoADV). Results show that relatively large TKE in the eyewall above 2 km is predominantly attributable to vertical advection of TKE in CTL. Interestingly, buoyancy production of TKE is negative in this region in both simulations; thus, buoyancy effects cannot explain observed columns of TKE in TC eyewalls. Both horizontal and vertical advection of TKE tends to reduce TKE and vertical viscosity (Km) in the near-surface inflow layer, particularly in the eyewall of TCs. Results also show that the simulated TC in CTL has slightly stronger maximum winds, slightly smaller radius of maximum wind (RMW), and ~5% smaller radius of gale-force wind than in NoADV. These differences are consistent with absolute angular momentum being advected to smaller radii in CTL. Sensitivity simulations further reveal that the differences between CTL and NoADV are more attributable to vertical advection (rather than horizontal advection) of TKE. Recommendations for improvements of PBL schemes that use predictive equations for TKE are also discussed.

SINFONY - the combination of Nowcasting and Numerical Weather Prediction at the convective scale at DWD

<p>There are different "optimal" forecast methods for different forecast lead times and different weather phenomena. Focusing on precipitation and convective events up to some hours ahead, radar extrapolation techniques (Nowcasting) show good skill up to about 2 h ahead (depending on the situation), while numerical weather prediction (NWP) outperforms Nowcasting only at later hours. Ensembles of both Nowcasting and NWP help to assess forecast uncertainties.</p><p>DWD's new Seamless INtegrated FOrecastiNg sYstem (SINFONY) combines forecast information from Nowcasting and NWP in an optimized way and as a function of lead time to generate seamless probabilistic precipitation forecasts from minutes to 12 hours. After four years of research and development, SINFONY is about to come to life in the upcoming two years, with an initial focus on the prediction of severe convective events.</p><p>For the development of SINFONY, different interdisciplinary teams work closely together in developing</p><ul><li>Radar Nowcasting ensembles for precipitation, reflectivity and convective cell objects</li> <li>Hourly SINFONY-RUC-EPS NWP on the km-scale with extensive data assimilation of high-resolution remote sensing (radial wind, reflectivity and cell objects from volume radar scans; Meteosat VIS channels; lightning)</li> <li>Optimal combination of Nowcasting and NWP ensemble forecasts in observation space (precipitation, radar reflectivity and cell objects)</li> <li>Systems for common Nowcasting and NWP verification of precipitation, reflectivity and objects.</li> </ul><p>For the SINFONY-RUC-EPS, new innovative and efficient forward operators for volume radar scans and visible satellite data enable direct operational assimilation of these data in an LETKF framework. Advanced model physics (stochastic PBL scheme, 2-moment bulk cloud mircophysics) contribute to an improved forecast of convective clouds.</p><p>As input for the combination of NWP and Nowcasting information, SINFONY-RUC-EPS generates simulated reflectivity volume scan ensembles of the entire German radar network every 5 min online during its forecast runs. Ensembles of composites and cell object tracks are generated by the same compositing and cell detection- and tracking methods/software packages, which are applied to generate the Nowcasting information.</p><p>To help evolve DWD's warning process for convective events towards a flexible "warn-on-objects", our Nowcasting- and NWP cell object ensemble forecasts are then blended into a seamless forecast ("probability objects") in a pragmatic way. Gridded combined precipitation and reflectivity ensembles are also under development, targeted towards hydrological warnings.</p><p>In addition to the development of SINFONY itself, focus is also put on the interaction with users (e.g. from flood forecasting centres) along the weather information value chain for co-designing the development of new forecast products and approaches to improve the prediction and warning process.</p><p>This presentation will introduce the goal and the concept of SINFONY and provide an overview on the ongoing developments as well as on the incipient interaction with users.</p>

Influence on the Temperature Estimation by the Planetary Boundary Layer Scheme with Different Minimum Eddy Diffusivity in WRF v3.9.1.1

The minimum eddy diffusivity (Kzmin) in the planetary boundary layer (PBL) scheme is able to influence the performance of the model in simulating meteorological parameters such as the temperature. However, detailed studies on the sensitivities of the simulated temperature to the settings of Kzmin are still lacking. Thus, in this study, we evaluated the performance of the ACM2 (Asymmetrical Convective Model, version 2) scheme in the WRF (Weather Research and Forecasting) model with different settings of Kzmin, in simulating the spatiotemporal distribution of the temperature in the region of Beijing, China. Five constant values as well as a function were implemented in the model to calculate Kzmin, and the simulation results with different settings of Kzmin were compared and analyzed. The results show that the increase of Kzmin leads to an elevation of the 2-m temperature, especially in the nighttime. We figured out that the deviation of the 2-m temperature at night is mainly caused by the different estimation of the turbulent mixing under stable conditions in simulation scenarios with different Kzmin settings. Moreover, the spatial distribution of the temperature deviation indicates that under various underlying surface categories, the change of Kzmin exerts a different influence on the prediction of the 2-m temperature, and the influence was found stronger during the nighttime than during the daytime, in plain areas than in mountain areas, in urban areas than in non-urban areas. In the nighttime of the urban areas, the influence on the simulated 2-m temperature brought about by the change of Kzmin was found the strongest. In addition, we found that the implementation of a functional type Kzmin in the ACM2 scheme helps to improve the performance of the model in capturing the diurnal change and the vertical distribution of the temperature in this region, compared with that using a constant Kzmin.