scholarly journals Challenges and Opportunities with New Generation Geostationary Meteorological Satellite Datasets for Analyses and Initial Conditions for Forecasting Hurricane Irma (2017) Rapid Intensification Event

Atmosphere ◽  
2020 ◽  
Vol 11 (11) ◽  
pp. 1200
Author(s):  
Russell L. Elsberry ◽  
Joel W. Feldmeier ◽  
Hway-Jen Chen ◽  
Melinda Peng ◽  
Christopher S. Velden ◽  
...  
Keyword(s):  
Wind Field ◽  
Initial Conditions ◽  
Motion Vector ◽  
Surface Wind ◽  
Rapid Intensification ◽  
Constant Intensity ◽  
Near Surface ◽  
Tc Model ◽  
Hurricane Irma ◽  
Better Than

This study utilizes an extremely high spatial resolution GOES-16 atmospheric motion vector (AMV) dataset processed at 15 min intervals in a modified version of our original dynamic initialization technique to analyze and forecast a rapid intensification (RI) event in Hurricane Irma (2017). The most important modifications are a more time-efficient dynamic initialization technique and adding a near-surface wind field adjustment as a low-level constraint on the distribution of deep convection relative to the translating center. With the new technique, the Coupled Ocean/Atmospheric Mesoscale Prediction System for Tropical Cyclones (COAMPS-TC) model initial wind field at 12.86 km elevation quickly adjusts to the cirrus-level GOES-16 AMVs to better detect the Irma outflow magnitude and areal extent every 15 min, and predicts direct connections to adjacent synoptic circulations much better than a dynamic initialization with only lower-resolution hourly GOES-13 AMVs and also better than a cold-start COAMPS-TC initialization with a bogus vortex. Furthermore, only with the GOES-16 AMVs does the COAMPS-TC model accurately predict the timing of an intermediate 12 h constant-intensity period between two segments of the Irma RI. By comparison, HWRF model study of the Irma case that utilized the same GOES-16 AMV dataset predicted a continuous RI without the intermediate constant-intensity period, and predicted more limited outflow areal extents without strong direct connections with adjacent synoptic circulations.

Evaluation of the Surface Wind Field over Land in WRF Simulations of Hurricane Wilma (2005). Part I: Model Initialization and Simulation Validation

2021 ◽  
Author(s):  
David S. Nolan ◽  
Brian D. McNoldy ◽  
Jimmy Yunge
Keyword(s):  
Wind Field ◽  
Urban Areas ◽  
Initial Conditions ◽  
Surface Wind ◽  
South Florida ◽  
Wind Fields ◽  
Near Surface ◽  
Hurricane Wilma ◽  
Wind Analysis ◽  
Forecasting System

AbstractWhile global and regional dynamical models are used to predict the tracks and intensities of hurricanes over the ocean, these models are not currently used to predict the wind field and other impacts over land. This two-part study performs detailed evaluations of the near-surface, over-land wind fields produced in simulations of Hurricane Wilma (2005) as it traveled across South Florida. This first part describes the production of two high-resolution simulations using the Weather Research and Forecasting Model (WRF), using different boundary layer parameterizations available in WRF: the Mellor-Yamada-Janjić (MYJ) scheme and the Yonsei University (YSU) scheme. Initial conditions from the Global Forecasting System (GFS) are manipulated with a vortex bogussing technique to modify the initial intensity, size, and location of the cyclone. It is found possible through trial and error to successfully produce simulations using both the YSU and MYJ schemes that closely reproduce the track, intensity, and size of Wilma at landfall. For both schemes the storm size and structure also show good agreement with the wind fields diagnosed by H*WIND and the Tropical Cyclone Surface Wind Analysis (TCSWA). Both over water and over land, the YSU scheme has stronger winds over larger areas than MYJ, but the surface winds are more reduced in areas of greater surface roughness, particularly in urban areas. Both schemes produced very similar inflow angles over land and water. The over-land wind fields are examined in more detail in the second part of this study.

Evaluation of the Surface Wind Field over Land in WRF Simulations of Hurricane Wilma (2005). Part II: Surface Winds, Inflow Angles, and Boundary Layer Profiles

2021 ◽  
Author(s):  
David S. Nolan ◽  
Brian D. McNoldy ◽  
Jimmy Yunge ◽  
Forrest J. Masters ◽  
Ian M. Giammanco
Keyword(s):  
Boundary Layer ◽  
Wind Field ◽  
Initial Conditions ◽  
Surface Wind ◽  
Storm Track ◽  
South Florida ◽  
Modeling Framework ◽  
Near Surface ◽  
Hurricane Wilma ◽  
Wind Events

AbstractThis is the second of a two-part study that explores the capabilities of a mesoscale atmospheric model to reproduce the near-surface wind fields in hurricanes over land. The Weather Research and Forecasting Model (WRF) is used with two planetary boundary layer parameterizations: the Yonsei University (YSU) and the Mellor-Yamada-Janjić (MYJ) schemes. The first part presented the modeling framework and initial conditions used to produce simulations of Hurricane Wilma (2005) that closely reproduced the track, intensity, and size of its wind field as it passed over South Florida. This part explores how well these simulations can reproduce the winds at fixed points over land by making comparisons to observations from airports and research weather stations. The results show that peak wind speeds are remarkably well reproduced at several locations. Wind directions are evaluated in terms of the inflow angle relative to the storm center, and the simulated inflow angles are generally smaller than observed. Localized peak wind events are associated with vertical vorticity maxima in the boundary layer with horizontal scales of 5-10 km. The boundary layer winds are compared to wind profiles obtained by velocity-azimuth display (VAD) analyses from National Weather Service Doppler radars at Miami and Key West; results from these comparisons are mixed. Nonetheless the comparisons to surface observations suggest that when short-term hurricane forecasts can sufficiently predict storm track, intensity, and size, they will also be able to provide useful information on extreme winds at locations of interest.

scholarly journals Improving Hurricane Analyses and Predictions with TCI, IFEX Field Campaign Observations, and CIMSS AMVs Using the Advanced Hybrid Data Assimilation System for HWRF. Part I: What is Missing to Capture the Rapid Intensification of Hurricane Patricia (2015) when HWRF is already Initialized with a More Realistic Analysis?

2019 ◽  
Vol 147 (4) ◽  
pp. 1351-1373 ◽  
Author(s):  
Xu Lu ◽  
Xuguang Wang
Keyword(s):  
Data Assimilation ◽  
Initial Conditions ◽  
Surface Wind ◽  
Rapid Intensification ◽  
Model Resolution ◽  
Field Campaign ◽  
Horizontal Diffusion ◽  
Intensity Forecast ◽  
Physics Parameterizations ◽  
Hwrf Model

Abstract Assimilating inner-core observations collected from recent field campaign programs such as Tropical Cyclone Intensity (TCI) and Intensity Forecasting Experiment (IFEX) together with the enhanced atmospheric motion vectors (AMVs) produce realistic three-dimensional (3D) analyses using the newly developed GSI-based, continuously cycled, dual-resolution hybrid ensemble–variational data assimilation (DA) system for the Hurricane Weather Research and Forecasting (HWRF) Model for Hurricane Patricia (2015). However, more persistent surface wind maximum spindown is found in the intensity forecast initialized from the realistic analyses produced by the DA system but not from the unrealistic initial conditions produced through vortex modification. Diagnostics in this study reveal that the spindown issue is likely attributed to the deficient HWRF Model physics that are unable to maintain the realistic 3D structures from the DA analysis. The horizontal diffusion is too strong to maintain the realistically observed vertical oscillation of radial wind near the eyewall region. The vertical diffusion profile cannot produce a sufficiently strong secondary circulation connecting the realistically elevated upper-level outflow produced in the DA analysis. Further investigations with different model physics parameterizations demonstrate that spindown can be alleviated by modifying model physics parameterizations. In particular, a modified turbulent mixing parameterization scheme together with a reduced horizontal diffusion is found to significantly alleviate the spindown issue and to improve the intensity forecast. Additional experiments show that the peak-simulated intensity and rapid intensification rate can be further improved by increasing the model resolution. But the model resolution is not as important as model physics in the spindown alleviation.

The Effects of Vertical Stratification and Land Use Data on Numerical Simulation of Wind Energy Resources

2014 ◽  
Vol 535 ◽  
pp. 135-140
Author(s):  
Yuan Chang Deng ◽  
Zhen Cao Zou
Keyword(s):  
Numerical Simulation ◽  
Land Use ◽  
Wind Field ◽  
Wind Profile ◽  
Surface Wind ◽  
Wrf Model ◽  
Vertical Stratification ◽  
Near Surface ◽  
Wind Field Simulation ◽  
Surface Wind Field

By adjusting the distribution of vertical layers and increasing its number in WRF model, this paper mainly studies the effects of vertical stratification on the near surface wind field and vertical profile simulation. The test outcomes show that moderately increasing vertical layers can effectively improve the near surface wind field simulation results, while it has little influence on the numeral and changing trend of high vertical wind profile. Considering both accuracy and efficiency, it is recommended to set 10~15 layers below 300m. On the basis of this research, instead of USGS data by using the MODIS_30S data, the data underlying surface land in Shenzhen and HK area are updated. Comparative results between the two schemes, due to the roughness and drag coefficient of difference types of surface are not identical; the surface data has a significant impact on wind field and wind profile simulation. Using the MODIS land use data which is more consistent with the actual situation can improve the accuracy of numerical simulation.

scholarly journals Examination of WRF-ARW Experiments Using Different Planetary Boundary Layer Parameterizations to Study the Rapid Intensification and Trajectory of Hurricane Otto (2016)

Atmosphere ◽  
2020 ◽  
Vol 11 (12) ◽  
pp. 1317
Author(s):  
Tito Maldonado ◽  
Jorge A. Amador ◽  
Erick R. Rivera ◽  
Hugo G. Hidalgo ◽  
Eric J. Alfaro
Keyword(s):  
Boundary Layer ◽  
Planetary Boundary Layer ◽  
Initial Conditions ◽  
Surface Wind ◽  
Regional Model ◽  
Horizontal Resolution ◽  
Economic Losses ◽  
Rapid Intensification ◽  
Medium Range Forecast ◽  
Meteorological Features

Hurricane Otto (2016) was characterised by remarkable meteorological features of relevance for the scientific community and society. Scientifically, among the most important attributes of Otto is that it underwent a rapid intensification (RI) process. For society, this cyclone severely impacted Costa Rica and Nicaragua, leaving enormous economic losses and many fatalities. In this study, a set of three numerical simulations are performed to examine the skill of model estimations in reproducing RI and trajectory of Hurricane Otto by comparing the results of a global model to a regional model using three different planetary boundary layer parameterizations (PBL). The objective is to set the basis for future studies that analyse the physical reasons why a particular simulation (associated with a certain model setup) performs better than others in terms of reproducing RI and trajectory. We use the regional model Weather Research and Forecasting—Advanced Research WRF (WRF-ARW) with boundary and initial conditions provided by the Global Forecast System (GFS) analysis (horizontal resolution of 0.5 degrees). The PBL used are the Medium Range Forecast, the Mellor-Yamada-Janjic (MYJ), and the Yonsei University (YSU) parameterizations. The regional model is run in three static domains with horizontal grid spacing of 27, 9 and 3 km, the latter covering the spacial extent of Otto during the simulation period. WRF-ARW results improve the GFS forecast, in almost every aspect evaluated in this study, particularly, the simulated trajectories in WRF-ARW show a better representation of the cyclone path and movement compared to GFS. Even though the MYJ experiment was the only one that exhibited an abrupt 24-h change in the storm’s surface wind, close to the 25-knot threshold, the YSU scheme presented the fastest intensification, closest to reality.

scholarly journals Reconstruction of Near-Surface Tornado Wind Fields from Forest Damage

2010 ◽  
Vol 49 (7) ◽  
pp. 1517-1537 ◽  
Author(s):  
Veronika Beck ◽  
Nikolai Dotzek
Keyword(s):  
Wind Field ◽  
Surface Wind ◽  
Forest Damage ◽  
Wind Fields ◽  
Tree Model ◽  
Translation Speed ◽  
Near Surface ◽  
Additional Information ◽  
Secondary Vortices ◽  
Surface Wind Field

Abstract Tornado intensity is usually inferred from the damage produced. To foster postevent tornado intensity assessments, the authors present a model to reconstruct near-surface wind fields from forest damage patterns. By comparing the structure of observed and simulated damage patterns, essential parameters to describe a tornado near-surface wind field are derived, such as the ratio Gmax between circular and translational velocity, and the deflection angle α between peak wind and pressure gradient. The model consists of a wind field module following the Letzmann analytical tornado model and a tree module based on the mechanistic HWIND tree model to assess tree breakage. Using this method, the velocity components of the near-surface wind field, the track of the tornado center, and the spatial distribution of the Fujita scale along and across the damage path can be assessed. Necessary requirements to apply the model are knowledge of the tornado translation speed (e.g., from radar observations) and a detailed analysis of the forest damage patterns. One of the key findings of this analysis is that the maximum intensity of the tornado is determinable with an uncertainty of only (Gmax + 1) times the variability of the usually well-known tornado translation speed. Further, if Letzmann’s model is applied and the translation speed of the tornado is known, the detailed tree model is unnecessary and could be replaced by an average critical velocity for stem breakage υcrit independent of the tree species. Under this framework, the F3 and F2 ratings of the tornadoes in Milosovice, Czech Republic, on 30 May 2001 and Castellcir, Spain, on 18 October 2006, respectively, could be verified. For the Milosovice event, the uncertainty in peak intensity was only ±6.0 m s−1. Additional information about the structure of the near-surface wind field in the tornado and several secondary vortices was also gained. Further, this model allows for distinguishing downburst damage patterns from those of tornadoes.

scholarly journals Dynamical Downscaling of Surface Air Temperature and Wind Field Variabilities over the Southeastern Levantine Basin, Mediterranean Sea

Climate ◽  
2021 ◽  
Vol 9 (10) ◽  
pp. 150
Author(s):  
Mohamed ElBessa ◽  
Saad Mesbah Abdelrahman ◽  
Kareem Tonbol ◽  
Mohamed Shaltout
Keyword(s):  
Wind Speed ◽  
Air Temperature ◽  
Wind Field ◽  
Climate Model ◽  
Dynamical Downscaling ◽  
Surface Wind ◽  
Surface Air Temperature ◽  
Warming Trend ◽  
Climate Data ◽  
Near Surface

The characteristics of near surface air temperature and wind field over the Southeastern Levantine (SEL) sub-basin during the period 1979–2018 were simulated. The simulation was carried out using a dynamical downscaling approach, which requires running a regional climate model system (RegCM-SVN6994) on the study domain, using lower-resolution climate data (i.e., the fifth generation of ECMWF atmospheric reanalysis of the global climate ERA5 datasets) as boundary conditions. The quality of the RegCM-SVN simulation was first verified by comparing its simulations with ERA5 for the studied region from 1979 to 2018, and then with the available five WMO weather stations from 2007 to 2018. The dynamical downscaling results proved that RegCM-SVN in its current configuration successfully simulated the observed surface air temperature and wind field. Moreover, RegCM-SVN was proved to provide similar or even better accuracy (during extreme events) than ERA5 in simulating both surface air temperature and wind speed. The simulated annual mean T2m by RegCM-SVN (from 1979 to 2018) was 20.9 °C, with a positive warming trend of 0.44 °C/decade over the study area. Moreover, the annual mean wind speed by RegCM-SVN was 4.17 m/s, demonstrating an annual negative trend of wind speed over 92% of the study area. Surface air temperatures over SEL mostly occurred within the range of 4–31 °C; however, surface wind speed rarely exceeded 10 m/s. During the study period, the seasonal features of T2m showed a general warming trend along the four seasons and showed a wind speed decreasing trend during spring and summer. The results of the RegCM-SVN simulation constitute useful information that could be utilized to fully describe the study area in terms of other atmospheric parameters.

scholarly journals On the changes in the sea surface temperature in the benguela upwelling region. Part 2: the long-term tendencies

2019 ◽  
pp. 29-39 ◽  
Author(s):  
A. B. Polonsky ◽  
A. N. Serebrennikov
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Wind Field ◽  
Surface Wind ◽  
Field Structure ◽  
Sea Surface ◽  
Near Surface ◽  
Tangential Wind ◽  
Benguela Upwelling

The paper examines the issue on the long-term trends in the sea surface temperature (SST) in the Benguela upwelling zone and their causes using the daily SST satellite data for 1985–2017’s and the daily near-surface wind for 1988–2017”s. It is shown that in the Benguela upwelling region, there is a significant intensification of driving winds in the last 20 yrs. This is accompanied by a decrease of the thermal upwelling index (taking into account the sign of the index or an increase of its absolute values) in the southern part of the Benguela upwelling, but practically does not influence this indicator in its northern part. The likely reason for this difference is the change in the wind field structure, as a result of which there are opposite trends in the magnitude of the vorticity of the tangential wind stress in different parts of the Benguela upwelling. In the southern part of the Benguela upwelling, both the Ekman’s upwelling and the vertical velocities due to the vorticity of the driving wind intensify, while in the northern part the corresponding trends have the opposite signs. This leads to a partial compensation of these two effects in the northern part of the Benguela upwelling. The reason for the change in the wind field structure is the displacement of the center of the Subtropical High to the south-east and the concomitant reversal of the near-surface wind vector in the coastal zone.

scholarly journals Land Surface Precipitation in MERRA-2

2017 ◽  
Vol 30 (5) ◽  
pp. 1643-1664 ◽  
Author(s):  
Rolf H. Reichle ◽  
Q. Liu ◽  
Randal D. Koster ◽  
Clara S. Draper ◽  
Sarith P. P. Mahanama ◽  
...  
Keyword(s):  
Land Surface ◽  
Initial Conditions ◽  
Meteorological Data ◽  
Surface Air Temperature ◽  
High Latitudes ◽  
Atmospheric Models ◽  
Near Surface ◽  
Surface Precipitation ◽  
Modern Era ◽  
Better Than

Abstract The Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), features several major advances from the original MERRA reanalysis, including the use, outside of high latitudes, of observations-based precipitation data products to correct the precipitation falling on the land surface in the MERRA-2 system. The method for merging the observed precipitation into MERRA-2 has been refined from that of the (land-only) MERRA-Land reanalysis. This paper describes the method and evaluates the MERRA-2 land surface precipitation. Compared to monthly GPCPv2.2 observations, the corrected MERRA-2 precipitation (M2CORR) is better than the precipitation generated by the atmospheric models within the cycling MERRA-2 and MERRA systems. M2CORR is also better than MERRA-Land precipitation over Africa because in MERRA-2 a merged satellite–gauge precipitation product is used instead of the gauge-only data used for MERRA-Land. Compared to 3-hourly TRMM observations, the M2CORR diurnal cycle has better amplitude but less realistic phasing than MERRA-2 model-generated precipitation. Because correcting the precipitation within the coupled atmosphere–land modeling system allows the MERRA-2 near-surface air temperature and humidity to respond to the improved precipitation forcing, MERRA-2 provides more self-consistent surface meteorological data than were available from MERRA-Land, which is important for applications such as land-only modeling studies. Where precipitation observations of sufficient quality are available for use in the reanalysis, the corrections facilitate the seamless spinup of the land surface initial conditions across the MERRA-2 production streams. At high latitudes, however, the lack of reliable precipitation observations results in undesirable land spinup effects that impact mostly the first published year of each MERRA-2 stream (1980, 1992, 2001, and 2011).

scholarly journals Wind field reconstruction with adaptive random Fourier features

2021 ◽  
Vol 477 (2255) ◽  
Author(s):  
Jonas Kiessling ◽  
Emanuel Ström ◽  
Raúl Tempone
Keyword(s):  
Wind Field ◽  
Spatial Interpolation ◽  
Surface Wind ◽  
Sobolev Norm ◽  
Near Surface ◽  
Distance Weighting ◽  
Random Fourier Features ◽  
Sparse Set ◽  
Surface Wind Field ◽  
Inverse Distance

We investigate the use of spatial interpolation methods for reconstructing the horizontal near-surface wind field given a sparse set of measurements. In particular, random Fourier features is compared with a set of benchmark methods including kriging and inverse distance weighting. Random Fourier features is a linear model β ( x ) = ∑ k = 1 K β k   e i ω k x approximating the velocity field, with randomly sampled frequencies ω k and amplitudes β k trained to minimize a loss function. We include a physically motivated divergence penalty | ∇ ⋅ β ( x ) | 2 , as well as a penalty on the Sobolev norm of β . We derive a bound on the generalization error and a sampling density that minimizes the bound. We then devise an adaptive Metropolis–Hastings algorithm for sampling the frequencies of the optimal distribution. In our experiments, our random Fourier features model outperforms the benchmark models.

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