scholarly journals Numerically consistent budgets of energy, momentum and mass in Cartesian coordinates: Application to the WRF model

2021 ◽  
Author(s):  
Matthias Göbel ◽  
Stefano Serafin ◽  
Mathias Walter Rotach
Keyword(s):  
Coordinate Transformation ◽  
Weather Prediction ◽  
Potential Temperature ◽  
Wrf Model ◽  
Numerical Weather Prediction Model ◽  
Layer Growth ◽  
Mountain Range ◽  
Convective Boundary ◽  
Terrain Following ◽  
Water Vapor Mixing Ratio

Abstract. Numerically accurate budgeting of the forcing terms in the governing equations of a numerical weather prediction model is hard to achieve. Because individual budget terms are generally two to three orders of magnitude larger than the resulting tendency, exact closure of the budget can only be achieved if the contributing terms are calculated consistently with the model numerics. We present WRFlux, an open-source software that allows precise budget evaluation for the WRF model, as well as transformation of the budget equations from the terrain-following grid of the model to the Cartesian coordinate system. The theoretical framework of the numerically consistent coordinate transformation is also applicable to other models. We demonstrate the performance and a possible application of WRFlux with an idealized simulation of convective boundary layer growth over a mountain range. We illustrate the effect of inconsistent approximations by comparing the results of WRFlux with budget calculations using a lower-order advection operator and two alternative formulations of the coordinate transformation. With WRFlux, the sum of all forcing terms for potential temperature, water vapor mixing ratio and momentum agrees with the respective model tendencies to high precision. In contrast, the approximations lead to large residuals: The root mean square error between the sum of the diagnosed forcing terms and the actual tendency is one to three orders of magnitude larger than with WRFlux. Furthermore, WRFlux decomposes the resolved advection into mean advective and resolved turbulence components, which is useful in the analysis of large-eddy simulation output.

scholarly journals Evaluation of the WRF Model to Simulate a High-Intensity Rainfall Event over Kampala, Uganda

Water ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 873
Author(s):  
Yakob Umer ◽  
Janneke Ettema ◽  
Victor Jetten ◽  
Gert-Jan Steeneveld ◽  
Reinder Ronda
Keyword(s):  
High Intensity ◽  
Flood Hazard ◽  
Weather Prediction ◽  
Wrf Model ◽  
Numerical Weather Prediction Model ◽  
Rainfall Event ◽  
Weather Research And Forecasting ◽  
Event Triggering ◽  
Rain Events

Simulating high-intensity rainfall events that trigger local floods using a Numerical Weather Prediction model is challenging as rain-bearing systems are highly complex and localized. In this study, we analyze the performance of the Weather Research and Forecasting (WRF) model’s capability in simulating a high-intensity rainfall event using a variety of parameterization combinations over the Kampala catchment, Uganda. The study uses the high-intensity rainfall event that caused the local flood hazard on 25 June 2012 as a case study. The model capability to simulate the high-intensity rainfall event is performed for 24 simulations with a different combination of eight microphysics (MP), four cumulus (CP), and three planetary boundary layer (PBL) schemes. The model results are evaluated in terms of the total 24-h rainfall amount and its temporal and spatial distributions over the Kampala catchment using the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) analysis. Rainfall observations from two gauging stations and the CHIRPS satellite product served as benchmark. Based on the TOPSIS analysis, we find that the most successful combination consists of complex microphysics such as the Morrison 2-moment scheme combined with Grell-Freitas (GF) and ACM2 PBL with a good TOPSIS score. However, the WRF performance to simulate a high-intensity rainfall event that has triggered the local flood in parts of the catchment seems weak (i.e., 0.5, where the ideal score is 1). Although there is high spatial variability of the event with the high-intensity rainfall event triggering the localized floods simulated only in a few pockets of the catchment, it is remarkable to see that WRF is capable of producing this kind of event in the neighborhood of Kampala. This study confirms that the capability of the WRF model in producing high-intensity tropical rain events depends on the proper choice of parametrization combinations.

scholarly journals Does the Representation of Flow Structure and Turbulence at a Cold Front Converge on Multiscale Observations with Model Resolution?

2017 ◽  
Vol 145 (11) ◽  
pp. 4345-4363 ◽  
Author(s):  
Ben Harvey ◽  
John Methven ◽  
Chloe Eagle ◽  
Humphrey Lean
Keyword(s):  
Flow Structure ◽  
Cold Front ◽  
Spatial Scales ◽  
Weather Prediction ◽  
Turbulent Fluxes ◽  
Numerical Weather Prediction Model ◽  
Shear Instability ◽  
Small Scale ◽  
Convective Boundary ◽  
Direct Evaluation

In situ aircraft observations are used to interrogate the ability of a numerical weather prediction model to represent flow structure and turbulence at a narrow cold front. Simulations are performed at a range of nested resolutions with grid spacings of 12 km down to 100 m, and the convergence with resolution is investigated. The observations include the novel feature of a low-altitude circuit around the front that is closed in the frame of reference of the front, thus allowing the direct evaluation of area-average vorticity and divergence values from circuit integrals. As such, the observational strategy enables a comparison of flow structures over a broad range of spatial scales, from the size of the circuit itself ([Formula: see text]100 km) to small-scale turbulent fluctuations ([Formula: see text]10 m). It is found that many aspects of the resolved flow converge successfully toward the observations with resolution if sampling uncertainty is accounted for, including the area-average vorticity and divergence measures and the narrowest observed cross-frontal width. In addition, there is a gradual handover from parameterized to resolved turbulent fluxes of moisture and momentum as motions in the convective boundary layer behind the front become partially resolved in the highest-resolution simulations. In contrast, the parameterized turbulent fluxes associated with subgrid-scale shear-driven turbulence ahead of the front do not converge on the observations. The structure of frontal rainbands associated with a shear instability along the front also does not converge with resolution, indicating that the mechanism of the frontal instability may not be well represented in the simulations.

scholarly journals Evaluation of PBL Parameterizations in WRF at Subkilometer Grid Spacings: Turbulence Statistics in the Dry Convective Boundary Layer

2016 ◽  
Vol 144 (3) ◽  
pp. 1161-1177 ◽  
Author(s):  
Hyeyum Hailey Shin ◽  
Jimy Dudhia
Keyword(s):  
Boundary Layer ◽  
Mass Flux ◽  
Weather Prediction ◽  
Wrf Model ◽  
Eddy Diffusivity ◽  
Weather Research And Forecasting ◽  
Turbulence Statistics ◽  
Convective Boundary ◽  
Large Eddies ◽  
Horizontal Grid

Abstract Planetary boundary layer (PBL) parameterizations in mesoscale models have been developed for horizontal resolutions that cannot resolve any turbulence in the PBL, and evaluation of these parameterizations has been focused on profiles of mean and parameterized flux. Meanwhile, the recent increase in computing power has been allowing numerical weather prediction (NWP) at horizontal grid spacings finer than 1 km, at which kilometer-scale large eddies in the convective PBL are partly resolvable. This study evaluates the performance of convective PBL parameterizations in the Weather Research and Forecasting (WRF) Model at subkilometer grid spacings. The evaluation focuses on resolved turbulence statistics, considering expectations for improvement in the resolved fields by using the fine meshes. The parameterizations include four nonlocal schemes—Yonsei University (YSU), asymmetric convective model 2 (ACM2), eddy diffusivity mass flux (EDMF), and total energy mass flux (TEMF)—and one local scheme, the Mellor–Yamada–Nakanishi–Niino (MYNN) level-2.5 model. Key findings are as follows: 1) None of the PBL schemes is scale-aware. Instead, each has its own best performing resolution in parameterizing subgrid-scale (SGS) vertical transport and resolving eddies, and the resolution appears to be different between heat and momentum. 2) All the selected schemes reproduce total vertical heat transport well, as resolved transport compensates differences of the parameterized SGS transport from the reference SGS transport. This interaction between the resolved and SGS parts is not found in momentum. 3) Those schemes that more accurately reproduce one feature (e.g., thermodynamic transport, momentum transport, energy spectrum, or probability density function of resolved vertical velocity) do not necessarily perform well for other aspects.

On the Assessment of a Numerical Weather Prediction Model for Solar Photovoltaic Power Forecasts in Cities

2019 ◽  
Vol 141 (6) ◽  
Author(s):  
Harold Gamarro ◽  
Jorge E. Gonzalez ◽  
Luis E. Ortiz
Keyword(s):  
New York ◽  
Weather Prediction ◽  
Wrf Model ◽  
Urban Canopy ◽  
Region Of Interest ◽  
Integrated Approach ◽  
Numerical Weather Prediction Model ◽  
Recent Developments ◽  
Sky Conditions ◽  
The City

Recent developments in the weather research and forecasting (WRF) model have made it possible to accurately estimate incident solar radiation. This study couples the WRF-solar modifications with a multilayer urban canopy and building energy model (BEM) to create a unified WRF forecasting system called urban WRF–solar (uWRF-solar). This paper tests the integrated approach in the New York City (NYC) metro region as a sample case. Hourly forecasts are validated against ground station data collected at ten different sites in and around the city. Validation is carried out independently for clear, cloudy, and overcast sky conditions. Results indicate that the uWRF-solar model can forecast solar irradiance considerably well for the global horizontal irradiance (GHI) with an R2 value of 0.93 for clear sky conditions, 0.61 for cloudy sky conditions, and finally, 0.39 for overcast conditions. Results are further used to directly forecast solar power production in the region of interest, where evaluations of generation potential are done at the city scale. Outputs show a gradient of power generation produced by the potential available solar energy on the entire uWRF-solar grid. In total, the city has a city photovoltaic (PV) potential of 118 kWh/day/m2 and 3.65 MWh/month/m2.

scholarly journals Representation of the grey zone of turbulence in the atmospheric boundary layer

2016 ◽  
Vol 13 ◽  
pp. 63-67 ◽  
Author(s):  
Rachel Honnert
Keyword(s):  
Boundary Layer ◽  
Weather Prediction ◽  
Numerical Weather Prediction Model ◽  
Grey Zone ◽  
Shallow Convection ◽  
Convective Boundary ◽  
Boundary Layer Height ◽  
Eddy Simulation ◽  
Layer Structures ◽  
Large Eddy

Abstract. Numerical weather prediction model forecasts at horizontal grid lengths in the range of 100 to 1 km are now possible. This range of scales is the "grey zone of turbulence". Previous studies, based on large-eddy simulation (LES) analysis from the MésoNH model, showed that some assumptions of some turbulence schemes on boundary-layer structures are not valid. Indeed, boundary-layer thermals are now partly resolved, and the subgrid remaining part of the thermals is possibly largely or completely absent from the model columns. First, some modifications of the equations of the shallow convection scheme have been tested in the MésoNH model and in an idealized version of the operational AROME model at resolutions coarser than 500 m. Secondly, although the turbulence is mainly vertical at mesoscale (>  2 km resolution), it is isotropic in LES (<  100 m resolution). It has been proved by LES analysis that, in convective boundary layers, the horizontal production of turbulence cannot be neglected at resolutions finer than half of the boundary-layer height. Thus, in the grey zone, fully unidirectional turbulence scheme should become tridirectional around 500 m resolution. At Météo-France, the dynamical turbulence is modelled by a K-gradient in LES as well as at mesoscale in both MésoNH and AROME, which needs mixing lengths in the formulation. Vertical and horizontal mixing lengths have been calculated from LES of neutral and convective cases at resolutions in the grey zone.

Objectively Determined Fair-Weather CBL Depths in the ARW-WRF Model and Their Comparison to CASES-97 Observations

2013 ◽  
Vol 141 (1) ◽  
pp. 30-54 ◽  
Author(s):  
Margaret A. LeMone ◽  
Mukul Tewari ◽  
Fei Chen ◽  
Jimy Dudhia
Keyword(s):  
Boundary Layer ◽  
Potential Temperature ◽  
Wrf Model ◽  
Grid Spacing ◽  
Fair Weather ◽  
Free Atmosphere ◽  
Convective Boundary ◽  
Surface Exchange ◽  
Weather Observations ◽  
Horizontal Grid

Abstract High-resolution 24-h runs of the Advanced Research version of the Weather Research and Forecasting Model are used to test eight objective methods for estimating convective boundary layer (CBL) depth h, using four planetary boundary layer schemes: Yonsei University (YSU), Mellor–Yamada–Janjic (MYJ), Bougeault–LaCarrere (BouLac), and quasi-normal scale elimination (QNSE). The methods use thresholds of virtual potential temperature Θυ, turbulence kinetic energy (TKE), Θυ,z, or Richardson number. Those that identify h consistent with values found subjectively from modeled Θυ profiles are used for comparisons to fair-weather observations from the 1997 Cooperative Atmosphere–Surface Exchange Study (CASES-97). The best method defines h as the lowest level at which Θυ,z = 2 K km−1, working for all four schemes, with little sensitivity to horizontal grid spacing. For BouLac, MYJ, and QNSE, TKE thresholds did poorly for runs with 1- and 3-km grid spacing, producing irregular h growth not consistent with Θυ-profile evolution. This resulted from the vertical velocity W associated with resolved CBL eddies: for W &gt; 0, TKE profiles were deeper and Θυ profiles more unstable than for W &lt; 0. For the 1-km runs, 25-point spatial averaging was needed for reliable TKE-based h estimates, but thresholds greater than free-atmosphere values were sensitive to horizontal grid spacing. Matching Θυ(h) to Θυ(0.05h) or Θυ at the first model level were often successful, but the absence of eddies for 9-km grids led to more unstable Θυ profiles and often deeper h. Values of h for BouLac, MYJ, and QNSE, are mostly smaller than observed, with YSU values close to slightly high, consistent with earlier results.

Development and Validation of an Operational, Cloud-Assimilating Numerical Weather Prediction Model for Solar Irradiance Forecasting

2012 ◽  
Author(s):  
Patrick J. Mathiesen ◽  
Craig Collier ◽  
Jan P. Kleissl
Keyword(s):  
Numerical Weather Prediction ◽  
Solar Irradiance ◽  
San Diego ◽  
Initial Conditions ◽  
Weather Prediction ◽  
Wrf Model ◽  
Numerical Weather Prediction Model ◽  
Numerical Weather ◽  
The North ◽  
Marine Layer

For solar irradiance forecasting, the operational numerical weather prediction (NWP) models (e.g. the North American Model (NAM)) have excellent coverage and are easily accessible. However, their accuracy in predicting cloud cover and irradiance is largely limited by coarse resolutions (> 10 km) and generalized cloud-physics parameterizations. Furthermore, with hourly or longer temporal output, the operational NWP models are incapable of forecasting intra-hour irradiance variability. As irradiance ramp rates often exceed 80% of clear sky irradiance in just a few minutes, this deficiency greatly limits the applicability of the operational NWP models for solar forecasting. To address these shortcomings, a high-resolution, cloud-assimilating model was developed at the University of California, San Diego (UCSD) and Garrad-Hassan, America, Inc (GLGH). Based off of the Weather and Research Forecasting (WRF) model, an operational 1.3 km-gridded solar forecast is implemented for San Diego, CA that is optimized to simulate local meteorology (specifically, summertime marine layer fog and stratus conditions) and sufficiently resolved to predict intra-hour variability. To produce accurate cloud-field initializations, a direct cloud assimilation system (WRF-CLDDA) was also developed. Using satellite imagery and ground weather station reports, WRF-CLDDA statistically populates the initial conditions by directly modifying cloud hydrometeors (cloud water and water vapor content). When validated against the dense UCSD pyranometer network, WRF-CLDDA produced more accurate irradiance forecasts than the NAM and more frequently predicted marine layer fog and stratus cloud conditions.

The Use of High-Resolution Sounding Data to Evaluate and Optimize Nonlocal PBL Schemes for Simulating the Slightly Stable Upper Convective Boundary Layer

2019 ◽  
Vol 147 (10) ◽  
pp. 3825-3841 ◽  
Author(s):  
Xiao-Ming Hu ◽  
Ming Xue ◽  
Xiaolan Li
Keyword(s):  
Boundary Layer ◽  
Convective Boundary Layer ◽  
Thermal Structure ◽  
Potential Temperature ◽  
Wrf Model ◽  
Radiosonde Data ◽  
Neutral Stability ◽  
Convective Boundary ◽  
Early Afternoon ◽  
Peak Value

Abstract Since the 1950s, a countergradient flux term has been added to some K-profile-based first-order PBL schemes, allowing them to simulate the slightly statically stable upper part of the convective boundary layer (CBL) observed in a limited number of aircraft soundings. There is, however, substantial uncertainty in inferring detailed CBL structure, particularly the level of neutral stability (zn), from such a limited number of soundings. In this study, composite profiles of potential temperature are derived from multiyear early afternoon radiosonde data over Beijing, China. The CBLs become slightly stable above zn ~ 0.31–0.33zi, where zi is the CBL depth. These composite profiles are used to evaluate two K-profile PBL schemes, the Yonsei University (YSU) and Shin–Hong (SH) schemes, and to optimize the latter through parameter calibration. In one-dimensional simulations using the WRF Model, YSU simulates a stable CBL above zn ~ 0.24zi, while default SH simulates a thick superadiabatic lower CBL with zn ~ 0.45zi. Experiments with the analytic solution of a K-profile PBL model show that adjusting the countergradient flux profile leads to significant changes in the thermal structure of CBL, informing the calibration of SH. The SH scheme replaces the countergradient heat flux term in its predecessor YSU scheme with a three-layer nonlocal heating profile, with fnl specifying the peak value and z*SL specifying the height of this peak value. Increasing fnl to 1.1 lowers zn, but to too low a value, while simultaneously increasing z*SL to 0.4 leads to a more appropriate zn ~ 0.36zi. The calibrated SH scheme performs better than YSU and default SH for real CBLs.

scholarly journals Verification of Convection-Allowing WRF Model Forecasts of the Planetary Boundary Layer Using Sounding Observations

2013 ◽  
Vol 28 (3) ◽  
pp. 842-862 ◽  
Author(s):  
Michael C. Coniglio ◽  
James Correia ◽  
Patrick T. Marsh ◽  
Fanyou Kong
Keyword(s):  
Boundary Layer ◽  
Planetary Boundary Layer ◽  
Mixed Layer ◽  
Mesoscale Model ◽  
Cloud Model ◽  
Potential Temperature ◽  
Wrf Model ◽  
Thermodynamic Characteristics ◽  
Convective Boundary ◽  
Local Schemes

Abstract This study evaluates forecasts of thermodynamic variables from five convection-allowing configurations of the Weather Research and Forecasting Model (WRF) with the Advanced Research core (WRF-ARW). The forecasts vary only in their planetary boundary layer (PBL) scheme, including three “local” schemes [Mellor–Yamada–Janjić (MYJ), quasi-normal scale elimination (QNSE), and Mellor–Yamada–Nakanishi–Niino (MYNN)] and two schemes that include “nonlocal” mixing [the asymmetric cloud model version 2 (ACM2) and the Yonei University (YSU) scheme]. The forecasts are compared to springtime radiosonde observations upstream from deep convection to gain a better understanding of the thermodynamic characteristics of these PBL schemes in this regime. The morning PBLs are all too cool and dry despite having little bias in PBL depth (except for YSU). In the evening, the local schemes produce shallower PBLs that are often too shallow and too moist compared to nonlocal schemes. However, MYNN is nearly unbiased in PBL depth, moisture, and potential temperature, which is comparable to the background North American Mesoscale model (NAM) forecasts. This result gives confidence in the use of the MYNN scheme in convection-allowing configurations of WRF-ARW to alleviate the typical cool, moist bias of the MYJ scheme in convective boundary layers upstream from convection. The morning cool and dry biases lead to an underprediction of mixed-layer CAPE (MLCAPE) and an overprediction of mixed-layer convective inhibition (MLCIN) at that time in all schemes. MLCAPE and MLCIN forecasts improve in the evening, with MYJ, QNSE, and MYNN having small mean errors, but ACM2 and YSU having a somewhat low bias. Strong observed capping inversions tend to be associated with an underprediction of MLCIN in the evening, as the model profiles are too smooth. MLCAPE tends to be overpredicted (underpredicted) by MYJ and QNSE (MYNN, ACM2, and YSU) when the observed MLCAPE is relatively small (large).

scholarly journals CASA Prediction System over Dallas–Fort Worth Urban Network: Blending of Nowcasting and High-Resolution Numerical Weather Prediction Model

2020 ◽  
Vol 37 (2) ◽  
pp. 211-228
Author(s):  
Chandrasekar Radhakrishnan ◽  
V. Chandrasekar
Keyword(s):  
High Resolution ◽  
Lead Time ◽  
Weather Prediction ◽  
Wrf Model ◽  
Predictive Ability ◽  
Numerical Weather Prediction Model ◽  
Urban Region ◽  
Fort Worth ◽  
Urban Network ◽  
Nwp Model

AbstractThis study targeted improving Collaborative Adaptive Sensing of the Atmosphere’s (CASA) 6-h lead time predictive ability by blending the radar-based nowcast with the NWP model over the Dallas–Fort Worth (DFW) urban radar network. This study also depicts the recent updates in CASA’s real-time reflectivity nowcast system by assessing nine precipitation cases over the DFW urban region. CASA’s nowcast framework displayed better primer outcomes than the WRF Model forecast for the lead time of 1 h and 30 min. After that time, the predictive ability of the nowcast framework began decreasing compared to the WRF Model. To broaden CASA’s predictive system lead time to 6 h, the WRF Model forecasts were blended with Dynamic and Adaptive Radar Tracking of Storms (DARTS) nowcast. The HRRR model analysis was used as initial and boundary conditions in the WRF Model. The high-resolution dual-pol radar observations were assimilated into the WRF Model through the 3DVAR data assimilation technique. Three kinds of blending strategies were used and the results were compared: 1) hyperbolic tangent curve (HTW), 2) critical success index (CSIW), and 3) salient cross dissolve (Sal CD). The sensitivity studies were conducted to decide desirable parameters in the blending techniques. The outcomes proved that blending enhanced the prediction skills. Also, the overall performance of blending relies on the accuracy of the WRF forecast. Even though blending results are mixed, the HTW-based technique performed better than the other two techniques.

Sign in / Sign up

Export Citation Format

Share Document