scholarly journals Model inter-comparison for short-range forecasts over the southern African domain

2021 ◽  
Vol 117 (9/10) ◽  
Author(s):  
Patience T. Mulovhedzi ◽  
Gift T. Rambuwani ◽  
Mary-Jane Bopape ◽  
Robert Maisha ◽  
Nkwe Monama
Keyword(s):  
Wind Speed ◽  
South African ◽  
Weather Prediction ◽  
Weather Research And Forecasting ◽  
Small Scale ◽  
Spatial Coverage ◽  
Critical Issues ◽  
Scale Modelling ◽  
The Tropics ◽  
Horizontal Grid

Numerical weather prediction (NWP) models have been increasing in skill and their capability to simulate weather systems and provide valuable information at convective scales has improved in recent years. Much effort has been put into developing NWP models across the globe. Representation of physical processes is one of the critical issues in NWP, and it differs from one model to another. We investigated the performance of three regional NWP models used by the South African Weather Service over southern Africa, to identify the model that produces the best deterministic forecasts for the study domain. The three models – Unified Model (UM), Consortium for Small-scale Modelling (COSMO) and Weather Research and Forecasting (WRF) – were run at a horizontal grid spacing of about 4.4 km. Model forecasts for precipitation, 2-m temperature, and wind speed were verified against different observations. Snow was evaluated against reported snow records. Both the temporal and spatial verification of the model forecasts showed that the three models are comparable, with slight variations. Temperature and wind speed forecasts were similar for the three different models. Accumulated precipitation was mostly similar, except where WRF captured small rainfall amounts from a coastal low, while it over-estimated rainfall over the ocean. The UM showed a bubble-like shape towards the tropics, while COSMO cut-off part of the rainfall band that extended from the tropics to the sub-tropics. The COSMO and WRF models simulated a larger spatial coverage of precipitation than UM and snow-report records.

scholarly journals EMPOL 1.0: a new parameterization of pollen emission in numerical weather prediction models

2013 ◽  
Vol 6 (6) ◽  
pp. 1961-1975 ◽  
Author(s):  
K. Zink ◽  
A. Pauling ◽  
M. W. Rotach ◽  
H. Vogel ◽  
P. Kaufmann ◽  
...  
Keyword(s):  
Numerical Weather Prediction ◽  
Prediction Models ◽  
Weather Prediction ◽  
Birch Pollen ◽  
Small Scale ◽  
Pollen Emission ◽  
Numerical Weather ◽  
Pollen Concentrations ◽  
Scale Modelling ◽  
Reactive Trace Gases

Abstract. Simulating pollen concentrations with numerical weather prediction (NWP) systems requires a parameterization for pollen emission. We have developed a parameterization that is adaptable for different plant species. Both biological and physical processes of pollen emission are taken into account by parameterizing emission as a two-step process: (1) the release of the pollen from the flowers, and (2) their entrainment into the atmosphere. Key factors influencing emission are temperature, relative humidity, the turbulent kinetic energy and precipitation. We have simulated the birch pollen season of 2012 using the NWP system COSMO-ART (Consortium for Small-scale Modelling – Aerosols and Reactive Trace Gases), both with a parameterization already present in the model and with our new parameterization EMPOL. The statistical results show that the performance of the model can be enhanced by using EMPOL.

Analysis of Idealized Tropical Cyclone Simulations Using the Weather Research and Forecasting Model: Sensitivity to Turbulence Parameterization and Grid Spacing

2009 ◽  
Vol 137 (2) ◽  
pp. 745-765 ◽  
Author(s):  
Kevin A. Hill ◽  
Gary M. Lackmann
Keyword(s):  
Wind Speed ◽  
Tropical Cyclone ◽  
Maximum Intensity ◽  
Weather Research And Forecasting ◽  
Grid Spacing ◽  
Exchange Coefficient ◽  
Model Sensitivity ◽  
Wind Speeds ◽  
Horizontal Grid ◽  
Weather Research

Abstract The Weather Research and Forecasting Advanced Research Model (WRF-ARW) was used to perform idealized tropical cyclone (TC) simulations, with domains of 36-, 12-, and 4-km horizontal grid spacing. Tests were conducted to determine the sensitivity of TC intensity to the available surface layer (SL) and planetary boundary layer (PBL) parameterizations, including the Yonsei University (YSU) and Mellor–Yamada–Janjic (MYJ) schemes, and to horizontal grid spacing. Simulations were run until a quasi-steady TC intensity was attained. Differences in minimum central pressure (Pmin) of up to 35 hPa and maximum 10-m wind (V10max) differences of up to 30 m s−1 were present between a convection-resolving nested domain with 4-km grid spacing and a parent domain with cumulus parameterization and 36-km grid spacing. Simulations using 4-km grid spacing are the most intense, with the maximum intensity falling close to empirical estimates of maximum TC intensity. Sensitivity to SL and PBL parameterization also exists, most notably in simulations with 4-km grid spacing, where the maximum intensity varied by up to ∼10 m s−1 (V10max) or ∼13 hPa (Pmin). Values of surface latent heat flux (LHFLX) are larger in MYJ than in YSU at the same wind speeds, and the differences increase with wind speed, approaching 1000 W m−2 at wind speeds in excess of 55 m s−1. This difference was traced to a larger exchange coefficient for moisture, CQ, in the MYJ scheme. The exchange coefficients for sensible heat (Cθ) and momentum (CD) varied by <7% between the SL schemes at the same wind speeds. The ratio Cθ/CD varied by <5% between the schemes, whereas CQ/CD was up to 100% larger in MYJ, and the latter is theorized to contribute to the differences in simulated maximum intensity. Differences in PBL scheme mixing also likely played a role in the model sensitivity. Observations of the exchange coefficients, published elsewhere and limited to wind speeds <30 m s−1, suggest that CQ is too large in the MYJ SL scheme, whereas YSU incorporates values more consistent with observations. The exchange coefficient for momentum increases linearly with wind speed in both schemes, whereas observations suggest that the value of CD becomes quasi-steady beyond some critical wind speed (∼30 m s−1).

scholarly journals COSMIC Radio Occultation Processing: Cross-Center Comparison and Validation

2011 ◽  
Vol 28 (6) ◽  
pp. 737-751 ◽  
Author(s):  
Michael E. Gorbunov ◽  
A. V. Shmakov ◽  
Stephen S. Leroy ◽  
Kent B. Lauritsen
Keyword(s):  
Data Processing ◽  
Radio Occultation ◽  
Weather Prediction ◽  
Processing System ◽  
Fourier Integral ◽  
Small Scale ◽  
Cosmic Radio ◽  
Structural Uncertainty ◽  
Height Range ◽  
The Tropics

Abstract A radio occultation data processing system (OCC) was developed for numerical weather prediction and climate benchmarking. The data processing algorithms use the well-established Fourier integral operator–based methods, which ensure a high accuracy of retrievals. The system as a whole, or in its parts, is currently used at the Global Navigation Satellite System Receiver for Atmospheric Sounding (GRAS) Satellite Application Facility at the Danish Meteorological Institute, German Weather Service, and Wegener Center for Climate and Global Change. A statistical comparison of the inversions of the Constellation Observing System for Meteorology, Ionosphere and Climate (COSMIC) data by the system herein, University Corporation for Atmospheric Research (UCAR) data products, and ECMWF analyses is presented. Forty days of 2007 and 2008 were processed (from 5 days in the middle of each season) for the comparison of OCC and ECMWF, and 20 days of April 2009 were processed for the comparison of OCC, UCAR, and ECMWF. The OCC and UCAR inversions are consistent. For the tropics, the systematic difference between OCC and UCAR in the retrieved refractivity in the 2–30-km height interval does not exceed 0.1%; in particular, in the 9–25-km interval it does not exceed 0.03%. Below 1 km in the tropics the OCC – UCAR bias reaches 0.2%, which is explained by different cutoff and filtering schemes implemented in the two systems. The structure of the systematic OCC – ECMWF difference below 4 km changes in 2007, 2008, and 2009, which is explained by changes in the ECMWF analyses and assimilation schemes. It is estimated that in the 4–30-km height range the OCC occultation processing system obtains refractivities with a bias not exceeding 0.2%. The random error ranges from 0.3%–0.5% in the upper troposphere–lower stratosphere to about 2% below 4 km. The estimate of the bias below 4 km can currently be done with an accuracy of 0.5%–1% resulting from the structural uncertainty of the radio occultation (RO) data reflecting the insufficient knowledge of the atmospheric small-scale structures and instrumental errors. The OCC – UCAR bias is below the level of the structural uncertainty.

Disentangling the mechanisms of wave-convection coupling in the tropics

2020 ◽  
Author(s):  
Corinna Hoose ◽  
Hyunju Jung ◽  
Peter Knippertz ◽  
Tijana Janjic ◽  
Yvonne Ruckstuhl ◽  
...  
Keyword(s):  
Data Assimilation ◽  
General Circulation ◽  
Rainfall Variability ◽  
Weather Prediction ◽  
Equatorial Waves ◽  
Model Errors ◽  
Grid Spacing ◽  
Budget Analysis ◽  
The Tropics ◽  
Horizontal Grid

<p><span><span>Tropical weather prediction remains one of the main challenges in atmospheric science due to a combination of insufficient observations, data assimilation algorithms optimized for midlatitudes and large model errors. Due to a strong dependency of many people in the tropics on rainfall variability, combined with a high vulnerability, improved precipitation forecasts have the potential to create substantial benefits in areas such as agriculture, water management, energy production and disease prevention.</span></span></p><p><span><span>Recent studies found that the coupling of equatorial waves to convection is key to improving weather forecasts in the tropics on the synoptic to subseasonal timescale but many models struggle to realistically represent this coupling. Here we use aquaplanet simulations with the ICOsahedral Nonhydrostatic (ICON) model with a 13 km horizontal grid spacing to study the underlying mechanisms of convectively coupled equatorial waves in an idealized framework. We filter the divergence at 200 hPa using a standard wave filtering tool tapering to zero that allows us to identify dynamical characteristics of convectively coupled waves in our simulations. To diagnose thermodynamical aspects of wave-convection couplings, we compare the obtained waves to the total precipitable water and analyze the spatial variance of the budget analysis for column-integrated moist static energy. The same filtering tool and diagnostics are carried out on a realistic ICON simulation with a 2.5 km horizontal grid spacing from the DYnamics of the Atmospheric general circulation Modeled On Non-hydrostatic Domains (DYAMOND) project.</span></span></p><p><span><span>In the future we plan to run and analyze idealized tropical channel simulations with 2.5 km horizontal resolution, i.e. using the same grid spacing as in the DYAMOND simulation. The comparison between the idealized and the realistic simulations identifies mechanisms of wave-convection coupling. In addition, we will apply this set of diagnostics to forecast experiments using different approaches of data assimilation.</span></span></p><p> </p>

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.

scholarly journals Sensitivity experiments of a severe rainfall event in north-western Italy: 17 August 2006

2008 ◽  
Vol 2 (1) ◽  
pp. 133-138 ◽  
Author(s):  
M. Milelli ◽  
E. Oberto ◽  
A. Parodi
Keyword(s):  
Weather Prediction ◽  
Numerical Weather Prediction Model ◽  
Precipitation Forecast ◽  
Small Scale ◽  
Moist Convection ◽  
Cosmo Model ◽  
Quantitative Precipitation Forecast ◽  
Scale Modelling ◽  
North Western ◽  
Priority Project

Abstract. This study is embedded into a wider project named "Tackle deficiencies in Quantitative Precipitation Forecast (QPF)'' in the framework of the COSMO (COnsortium for Small-scale MOdelling) community. In fact QPF is an important purpose of a numerical weather prediction model, for forecasters and customers. Unfortunately, precipitation is also a very difficult parameter to forecast quantitatively. This priority project aims at looking into the COSMO Model deficiencies concerning QPF by running different numerical simulations of various events not correctly predicted by the model. In particular, this work refers to a severe event (moist convection) happened in Piemonte region during summer 2006. On one side the results suggest that details in orography representation have a strong influence on accuracy of QPF. On the other side COSMO Model exhibits a poor sensitivity on changes in numerical and physical settings when measured in terms of QPF improvements. The conclusions, although not too general, give some hint towards the behaviour of the COSMO Model in a typical convective situation.

scholarly journals Incorporation of the Rotor-Equivalent Wind Speed into the Weather Research and Forecasting Model’s Wind Farm Parameterization

2019 ◽  
Vol 147 (3) ◽  
pp. 1029-1046 ◽  
Author(s):  
Stephanie Redfern ◽  
Joseph B. Olson ◽  
Julie K. Lundquist ◽  
Christopher T. M. Clack
Keyword(s):  
Wind Speed ◽  
Wind Shear ◽  
High Stability ◽  
Wind Farm ◽  
Weather Prediction ◽  
Weather Research And Forecasting ◽  
Neutral Stability ◽  
High Wind ◽  
Rotor Disk ◽  
Weather Research

Abstract Wind power installations have been increasing in recent years. Because wind turbines can influence local wind speeds, temperatures, and surface fluxes, weather forecasting models should consider their effects. Wind farm parameterizations do currently exist for numerical weather prediction models. They generally consider two turbine impacts: elevated drag in the region of the wind turbine rotor disk and increased turbulent kinetic energy production. The wind farm parameterization available in the Weather Research and Forecasting (WRF) Model calculates this drag and TKE as a function of hub-height wind speed. However, recent work has suggested that integrating momentum over the entire rotor disk [via a rotor-equivalent wind speed (REWS)] is more appropriate, especially for cases with high wind shear. In this study, we implement the REWS in the WRF wind farm parameterization and evaluate its impacts in an idealized environment, with varying amounts of wind speed shear and wind directional veer. Specifically, we evaluate three separate cases: neutral stability with low wind shear, high stability with high wind shear, and high stability with nonlinear wind shear. For most situations, use of the REWS with the wind farm parameterization has marginal impacts on model forecasts. However, for scenarios with highly nonlinear wind shear, the REWS can significantly affect results.

scholarly journals Wind Speed Control of Tropical Orographic Convection

2014 ◽  
Vol 71 (7) ◽  
pp. 2695-2712 ◽  
Author(s):  
Alison D. Nugent ◽  
Ronald B. Smith ◽  
Justin R. Minder
Keyword(s):  
Wind Speed ◽  
Windward Side ◽  
Trade Wind ◽  
Weather Research And Forecasting ◽  
Forecasting Model ◽  
Tropical Atmosphere ◽  
Cumulus Clouds ◽  
Convective Clouds ◽  
Orographic Convection ◽  
The Tropics

Abstract This study compares observations from the Dominica Experiment (DOMEX) field campaign with 3D and 2D Weather Research and Forecasting Model (WRF) simulations to understand how ambient upstream wind speed controls the transition from thermally to mechanically forced moist orographic convection. The environment is a conditionally unstable, tropical atmosphere with shallow trade wind cumulus clouds. Three flow indices are defined to quantify the convective transition: horizontal divergence aloft, cloud location, and island surface temperature. As wind speed increases, horizontal airflow divergence from plume detrainment above the mountain changes to convergence associated with plunging flow, convective clouds relocate from the leeward to the windward side of the mountain as mechanically triggered convection takes over, and the daytime mountaintop temperature decreases because of increased ventilation and cloud shading. Possible mechanisms by which wind speed controls island precipitation are also discussed. The result is a clearer understanding of orographic convection in the tropics.

scholarly journals Improved Gridded Wind Speed Forecasts by Statistical Postprocessing of Numerical Models with Block Regression

2016 ◽  
Vol 31 (6) ◽  
pp. 1929-1945 ◽  
Author(s):  
Michaël Zamo ◽  
Liliane Bel ◽  
Olivier Mestre ◽  
Joël Stein
Keyword(s):  
Wind Speed ◽  
Random Forests ◽  
Numerical Weather Prediction ◽  
Prediction Models ◽  
Numerical Models ◽  
Weather Prediction ◽  
Forecast Errors ◽  
Near Surface ◽  
Numerical Weather ◽  
Spatial Coverage

Abstract Numerical weather forecast errors are routinely corrected through statistical postprocessing by several national weather services. These statistical postprocessing methods build a regression function called model output statistics (MOS) between observations and forecasts that is based on an archive of past forecasts and associated observations. Because of limited spatial coverage of most near-surface parameter measurements, MOS have been historically produced only at meteorological station locations. Nevertheless, forecasters and forecast users increasingly ask for improved gridded forecasts. The present work aims at building improved hourly wind speed forecasts over the grid of a numerical weather prediction model. First, a new observational analysis, which performs better in terms of statistical scores than those operationally used at Météo-France, is described as gridded pseudo-observations. This analysis, which is obtained by using an interpolation strategy that was selected among other alternative strategies after an intercomparison study conducted internally at Météo-France, is very parsimonious since it requires only two additive components, and it requires little computational resources. Then, several scalar regression methods are built and compared, using the new analysis as the observation. The most efficient MOS is based on random forests trained on blocks of nearby grid points. This method greatly improves forecasts compared with raw output of numerical weather prediction models. Furthermore, building each random forest on blocks and limiting those forests to shallow trees does not impair performance compared with unpruned and pointwise random forests. This alleviates the storage burden of the objects and speeds up operations.

scholarly journals High-Definition Hurricanes: Improving Forecasts with Storm-Following Nests

2021 ◽  
pp. 1-57
Author(s):  
Ghassan J. Alaka ◽  
Xuejin Zhang ◽  
Sundararaman G. Gopalakrishnan
Keyword(s):  
Prediction Models ◽  
Weather Prediction ◽  
Weather Research And Forecasting ◽  
Computationally Efficient ◽  
High Definition ◽  
Improvement Program ◽  
Structure Changes ◽  
Model Configuration ◽  
Basin Scale ◽  
Horizontal Grid

AbstractTo forecast tropical cyclone (TC) intensity and structure changes with fidelity, numerical weather prediction models must be “high definition”, i.e., horizontal grid spacing ≤ 3 km, so that they permit clouds and convection and resolve sharp gradients of momentum and moisture in the eyewall and rainbands. However, resolutions in operational global models remain too coarse to accurately predict these structures that are critical to TC intensity. Storm-following nests are a solution to this problem because they are computationally efficient at fine resolutions, providing a practical approach to improve TC intensity forecasts. Under the Hurricane Forecast Improvement Program, the operational Hurricane Weather Research and Forecasting (HWRF) system was developed to include telescopic, storm-following nests for a single TC per model integration. Subsequently, HWRF evolved into a state-of-the-art tool for TC predictions around the globe, although its single-storm nesting approach does not adequately simulate TC-TC interactions as they are observed. Basin-scale HWRF (HWRF-B) was developed later with a multi-storm nesting approach to improve the simulation of TC-TC interactions by producing high-resolution forecasts for multiple TCs simultaneously. In this study, the multi-storm nesting approach in HWRF-B was compared with a single-storm nesting approach using an otherwise identical model configuration. The multi-storm approach demonstrated TC intensity forecast improvements, including more realistic TC-TC interactions. Storm-following nests developed in HWRF and HWRF-B will be foundational to NOAA’s next-generation hurricane application in the Unified Forecast System.

Sign in / Sign up

Export Citation Format

Share Document