scholarly journals A New Vortex Initialization Scheme Coupled with WRF-ARW

2017 ◽  
Vol 2017 ◽  
pp. 1-15 ◽  
Author(s):  
Jimmy Chi Hung Fung ◽  
Guangze Gao
Keyword(s):  
Wind Speed ◽  
Observational Data ◽  
Initial Conditions ◽  
Global Analysis ◽  
Weather Prediction ◽  
Surface Wind ◽  
Computational Cost ◽  
Analysis Data ◽  
Initialization Scheme ◽  
Vortex Initialization

The ability of numerical simulations to predict typhoons has been improved in recent decades. Although the track prediction is satisfactory, the intensity prediction is still far from adequate. Vortex initialization is an efficient method to improve the estimations of the initial conditions for typhoon forecasting. In this paper, a new vortex initialization scheme is developed and evaluated. The scheme requires only observational data of the radius of maximum wind and the max wind speed in addition to the global analysis data. This scheme can also satisfy the vortex boundary conditions, which means that the vortex is continuously merged into the background environment. The scheme has a low computational cost and has the flexibility to adjust the vortex structure. It was evaluated with 3 metrics: track, center sea-level pressure (CSLP), and maximum surface wind speed (MWSP). Simulations were conducted using the WRF-ARW numerical weather prediction model. Super and severe typhoon cases with insufficiently strong initial MWSP were simulated without and with the vortex initialization scheme. The simulation results were compared with the 6-hourly observational data from Hong Kong Observatory (HKO). The vortex initialization scheme improved the intensity (CSLP and MWSP) prediction results. The scheme was also compared with other initialization methods and schemes.

An Investigation of the Stability Dependence of SST-Induced Vertical Mixing over the Ocean in the Operational Met Office Model

2017 ◽  
Vol 30 (1) ◽  
pp. 91-107 ◽  
Author(s):  
Qingtao Song ◽  
Dudley B. Chelton ◽  
Steven K. Esbensen ◽  
Andrew R. Brown
Keyword(s):  
Wind Speed ◽  
Weather Prediction ◽  
Surface Wind ◽  
Vertical Mixing ◽  
Surface Wind Speed ◽  
Satellite Observations ◽  
Sea Surface ◽  
Stable Conditions ◽  
Wide Range ◽  
The Impact

This study presents an assessment of the impact of a March 2006 change in the Met Office operational global numerical weather prediction model through the introduction of a nonlocal momentum mixing scheme. From comparisons with satellite observations of surface wind speed and sea surface temperature (SST), it is concluded that the new parameterization had a relatively minor impact on SST-induced changes in sea surface wind speed in the Met Office model in the September and October 2007 monthly averages over the Agulhas Return Current region considered here. The performance of the new parameterization of vertical mixing was evaluated near the surface layer and further through comparisons with results obtained using a wide range of sensitivity of mixing parameterization to stability in the Weather Research and Forecasting (WRF) Model, which is easily adapted to such sensitivity studies. While the new parameterization of vertical mixing improves the Met Office model response to SST in highly unstable (convective) conditions, it is concluded that significantly enhanced vertical mixing in the neutral to moderately unstable conditions (nondimensional stability [Formula: see text] between 0 and −2) typically found over the ocean is required in order for the model surface wind response to SST to match the satellite observations. Likewise, the reduced mixing in stable conditions in the new parameterization is also relatively small; for the range of the gradient Richardson number typically found over the ocean, the mixing was reduced by a maximum of only 10%, which is too small by more than an order of magnitude to be consistent with the satellite observations.

scholarly journals Regionally Enhanced Global (REG) 4D-Var

2018 ◽  
Vol 146 (12) ◽  
pp. 4015-4038
Author(s):  
Michael A. Herrera ◽  
Istvan Szunyogh ◽  
Adam Brainard ◽  
David D. Kuhl ◽  
Karl Hoppel ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Prediction Models ◽  
Initial Conditions ◽  
Weather Prediction ◽  
Computational Cost ◽  
Limited Area ◽  
Atmospheric Flow ◽  
Forecast Performance ◽  
Limited Area Model ◽  
Area Model

Abstract A regionally enhanced global (REG) data assimilation (DA) method is proposed. The technique blends high-resolution model information from a single or multiple limited-area model domains with global model and observational information to create a regionally enhanced analysis of the global atmospheric state. This single analysis provides initial conditions for both the global and limited-area model forecasts. The potential benefits of the approach for operational data assimilation are (i) reduced development cost, (ii) reduced overall computational cost, (iii) improved limited-area forecast performance from the use of global information about the atmospheric flow, and (iv) improved global forecast performance from the use of more accurate model information in the limited-area domains. The method is tested by an implementation on the U.S. Navy’s four-dimensional variational global data assimilation system and global and limited-area numerical weather prediction models. The results of the monthlong forecast experiments suggest that the REG DA approach has the potential to deliver the desired benefits.

scholarly journals An EC-Earth coupled atmosphere-ocean single-column model (AOSCM) for studying coupled marine and polar processes

2018 ◽  
Author(s):  
Kerstin Hartung ◽  
Gunilla Svensson ◽  
Hamish Struthers ◽  
Anna-Lena Deppenmeier ◽  
Wilco Hazeleger
Keyword(s):  
Sea Ice ◽  
Initial Conditions ◽  
Global Climate ◽  
Global Climate Model ◽  
Weather Prediction ◽  
Computational Cost ◽  
Global Climate Models ◽  
The Arctic ◽  
Small Scale ◽  
Single Column

Abstract. Single-column models (SCM) have been used as a tool to develop numerical weather prediction and global climate models for several decades. SCMs decouple small-scale processes from large-scale forcing and thus allow to test physical parameterizations in a controlled environment with reduced computational cost. Typically, either the ocean, sea-ice or atmosphere is fully modelled and assumptions have to be made on the boundary conditions from other subsystems, adding a potential source of errors. Here, we present a fully coupled atmosphere-ocean SCM (AOSCM), including sea-ice, which is related to the global climate model EC-Earth, consisting of NEMO3.6, LIM3, OpenIFS cycle 40r1, and OASIS3-MCT. The AOSCM is tested at three locations: the tropical Atlantic, the midlatitude Pacific and the Arctic. At all three locations in-situ observations are available for comparison. Evaluating model performance with buoy data, soundings and ship based observations, we find that the coupled AOSCM can capture the observed atmospheric and oceanic evolution. Model evolution is sensitive to the initial conditions and forcing data imposed on the column. Coupling several model components while alongside using them individually can help disentangle model feedbacks. Although the model can be extended, we demonstrate that already in the current setup it is a valuable tool to advance our understanding in marine and polar boundary layer processes and the interactions of their coupled components.

The impact of atmosphere-ocean-wave coupling on extreme surface wind forecasts

2021 ◽  
Author(s):  
Emanuele Silvio Gentile ◽  
Suzanne L. Gray ◽  
Janet F. Barlow ◽  
Huw W. Lewis ◽  
John M. Edwards
Keyword(s):  
Wind Speed ◽  
Wind Waves ◽  
Surface Wind ◽  
Computational Cost ◽  
Sea Surface ◽  
Model Systems ◽  
Sea State ◽  
Extreme Surface ◽  
Wind Speeds ◽  
The Impact

<p>Accurate modelling of air-sea surface exchanges is crucial for reliable extreme surface wind forecasts.  While atmosphere-only weather forecast models represent ocean and wave effects through sea-state independent parametrizations, coupled multi-model systems capture sea-state dynamics by integrating feedbacks between atmosphere, ocean and wave model components.</p><p>Here, we present the results of studying the sensitivity of extreme surface wind speeds to air-sea exchanges at kilometre scale using coupled and uncoupled configurations of the Met Office's UK Regional Coupled Environmental Prediction (UKC4) system. The case period includes the passage of extra-tropical cyclones Helen, Ali, and Bronagh, which brought maximum gusts of 36 ms<sup>-1</sup> over the UK.</p><p>Compared to the atmosphere-only results, coupling to ocean decreases the domain-average sea surface temperature by up to 0.5 K. Inclusion of coupling to waves decreases the 98th percentile 10-m wind speed by up to 2 ms<sup>-1</sup> as young, growing wind waves decrease wind speed by increasing the sea aerodynamic roughness. Impacts on gusts are more modest, with local reductions of up to 1ms <sup>-1,</sup> due to enhanced boundary-layer turbulence which partially offsets air-sea momentum transfer.</p><p>Using a new drag parametrization based on the COARE~4.0 scheme, with a cap on the neutral drag coefficient and decrease for wind speeds exceeding 27 ms<sup>-1 </sup>, the atmosphere-only model achieves equivalent impacts on 10-m wind speeds and gusts as from coupling to waves. Overall, the new drag parametrization achieves the same 20% improvement in forecast 10-m wind skill as coupling to waves, with  the  advantage  of saving the computational cost of the ocean and wave models. </p>

scholarly journals Evaluation of Spaceborne GNSS-R Retrieved Ocean Surface Wind Speed with Multiple Datasets

2019 ◽  
Vol 11 (23) ◽  
pp. 2747 ◽  
Author(s):  
Zhounan Dong ◽  
Shuanggen Jin
Keyword(s):  
Wind Speed ◽  
Weather Prediction ◽  
Surface Wind ◽  
Ocean Surface ◽  
Surface Wind Speed ◽  
Retrieval Algorithm ◽  
Navigation Satellite ◽  
Ocean Surface Wind ◽  
Global Navigation ◽  
Global Navigation Satellite

Spaceborne Global Navigation Satellite Systems-Reflectometry (GNSS-R) can estimate the geophysical parameters by receiving Earth’s surface reflected signals. The CYclone Global Navigation Satellite System (CYGNSS) mission with eight microsatellites launched by NASA in December 2016, which provides an unprecedented opportunity to rapidly acquire ocean surface wind speed globally. In this paper, a refined spaceborne GNSS-R sea surface wind speed retrieval algorithm is presented and validated with the ground surface reference wind speed from numerical weather prediction (NWP) and cross-calibrated multi-platform ocean surface wind vector analysis product (CCMP), respectively. The results show that when the wind speed was less than 20 m/s, the RMS of the GNSS-R retrieved wind could achieve 1.84 m/s in the case where the NWP winds were used as the ground truth winds, while the result was better than the NWP-based retrieved wind speed with an RMS of 1.68 m/s when the CCMP winds were used. The two sets of inversion results were further evaluated by the buoy winds, and the uncertainties from the NWP-derived and CCMP-derived model prediction wind speed were 1.91 m/s and 1.87 m/s, respectively. The accuracy of inversed wind speeds for different GNSS pseudo-random noise (PRN) satellites and types was also analyzed and presented, which showed similar for different PRN satellites and different types of satellites.

scholarly journals Forecasting the Past: Views of Earth from the Moon and Beyond

2020 ◽  
Vol 101 (7) ◽  
pp. E1190-E1200 ◽  
Author(s):  
Philippe Lopez
Keyword(s):  
Initial Conditions ◽  
Weather Prediction ◽  
Analysis Data ◽  
Numerical Weather Prediction Model ◽  
Numerical Weather ◽  
The Past ◽  
Visible Images ◽  
Forecasting System ◽  
High Level ◽  
Level Of Agreement

Abstract As we celebrate the fiftieth anniversary of NASA’s Apollo missions, images of Earth simulated with the ECMWF Integrated Forecasting System (IFS) are visually compared with pictures collected during space missions of the past five decades, in particular from the Apollo missions (1968–72). The numerical weather reforecasts use the latest version of the IFS and are initialized from (re)analysis data, which provide our current best representation of the atmospheric state for any given date back to the 1950s. Visible images of our planet are produced from the IFS with a simple simulator whose main inputs are the solar fluxes at the top of the atmosphere. First, a comparison to recent imagery from deep space illustrates the high level of performance of the IFS on recent dates. Then, the validation of the IFS against photographs taken by Apollo 11 and 17 both in-flight and from the lunar surface exhibits a significant level of agreement, despite the absence or very limited number of satellite observations available. This short study confirms that the combination of high-quality initial conditions with a modern numerical weather prediction model can yield reasonably accurate reforecasts of global meteorological conditions, especially cloud systems, for dates as far back as the late 1960s.

scholarly journals Storm surge and wave simulations in the Gulf of Mexico using a consistent drag relation for atmospheric and storm surge models

2012 ◽  
Vol 12 (7) ◽  
pp. 2399-2410 ◽  
Author(s):  
D. Vatvani ◽  
N. C. Zweers ◽  
M. van Ormondt ◽  
A. J. Smale ◽  
H. de Vries ◽  
...  
Keyword(s):  
Wind Speed ◽  
Gulf Of Mexico ◽  
Drag Coefficient ◽  
Storm Surge ◽  
Weather Prediction ◽  
Surface Wind ◽  
Wave Model ◽  
Water Levels ◽  
Observation Data ◽  
Wave Effects

Abstract. To simulate winds and water levels, numerical weather prediction (NWP) and storm surge models generally use the traditional bulk relation for wind stress, which is characterized by a wind drag coefficient. A still commonly used drag coefficient in those models, some of them were developed in the past, is based on a relation, according to which the magnitude of the coefficient is either constant or increases monotonically with increasing surface wind speed (Bender, 2007; Kim et al., 2008; Kohno and Higaki, 2006). The NWP and surge models are often tuned independently from each other in order to obtain good results. Observations have indicated that the magnitude of the drag coefficient levels off at a wind speed of about 30 m s−1, and then decreases with further increase of the wind speed. Above a wind speed of approximately 30 m s−1, the stress above the air-sea interface starts to saturate. To represent the reducing and levelling off of the drag coefficient, the original Charnock drag formulation has been extended with a correction term. In line with the above, the Delft3D storm surge model is tested using both Charnock's and improved Makin's wind drag parameterization to evaluate the improvements on the storm surge model results, with and without inclusion of the wave effects. The effect of waves on storm surge is included by simultaneously simulating waves with the SWAN model on identical model grids in a coupled mode. However, the results presented here will focus on the storm surge results that include the wave effects. The runs were carried out in the Gulf of Mexico for Katrina and Ivan hurricane events. The storm surge model was initially forced with H*wind data (Powell et al., 2010) to test the effect of the Makin's wind drag parameterization on the storm surge model separately. The computed wind, water levels and waves are subsequently compared with observation data. Based on the good results obtained, we conclude that, for a good reproduction of the storm surges under hurricane conditions, Makin's new drag parameterization is favourable above the traditional Charnock relation. Furthermore, we are encouraged by these results to continue the studies and establish the effect of improved Makin's wind drag parameterization in the wave model. The results from this study will be used to evaluate the relevance of extending the present towards implementation of a similar wind drag parameterization in the SWAN wave model, in line with our aim to apply a consistent wind drag formulation throughout the entire storm surge modelling approach.

Performance of a Dynamic Initialization Scheme in the Coupled Ocean–Atmosphere Mesoscale Prediction System for Tropical Cyclones (COAMPS-TC)

2011 ◽  
Vol 26 (5) ◽  
pp. 650-663 ◽  
Author(s):  
Eric A. Hendricks ◽  
Melinda S. Peng ◽  
Xuyang Ge ◽  
Tim Li
Keyword(s):  
Tropical Cyclone ◽  
Tropical Cyclones ◽  
Initial Conditions ◽  
Layer Structure ◽  
North Pacific Ocean ◽  
Surface Wind ◽  
Naval Research ◽  
Prediction System ◽  
Ocean Atmosphere ◽  
Initialization Scheme

Abstract A dynamic initialization scheme for tropical cyclone structure and intensity in numerical prediction systems is described and tested. The procedure involves the removal of the analyzed vortex and, then, insertion of a new vortex that is dynamically initialized to the observed surface pressure into the numerical model initial conditions. This new vortex has the potential to be more balanced, and to have a more realistic boundary layer structure than by adding synthetic data in the data assimilation procedure to initialize the tropical cyclone in a model. The dynamic initialization scheme was tested on multiple tropical cyclones during 2008 and 2009 in the North Atlantic and western North Pacific Ocean basins using the Naval Research Laboratory’s tropical cyclone version of the Coupled Ocean–Atmosphere Mesoscale Prediction System (COAMPS-TC). The use of this initialization procedure yielded significant improvements in intensity forecasts, with no degradation in track performance. Mean absolute errors in the maximum sustained surface wind were reduced by approximately 5 kt for all lead times up to 72 h.

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