scholarly journals Performance of Forecasts of Hurricanes with and without Upper-Level Troughs over the Mid-Latitudes

Atmosphere ◽  
2020 ◽  
Vol 11 (7) ◽  
pp. 702
Author(s):  
Kazutoshi Sato ◽  
Jun Inoue ◽  
Akira Yamazaki
Keyword(s):  
Initial Time ◽  
Central Position ◽  
Observation Data ◽  
Strong Wind ◽  
Ensemble Forecasts ◽  
Position Errors ◽  
Operational Forecasts ◽  
Radiosonde Observation ◽  
Upper Level ◽  
Atlantic Hurricanes

We investigated the accuracy of operational medium-range ensemble forecasts for 29 Atlantic hurricanes between 2007 and 2019. Upper-level troughs with strong wind promoted northward movement of hurricanes over the mid-latitudes. For hurricanes with upper-level troughs, relatively large errors in the prediction of troughs result in large ensemble spreads, which result in failure to forecast hurricane track. In contrast, for hurricanes without upper-level troughs, mean central position errors are relatively small in all operational forecasts because of the absence of upper-level strong wind around troughs over the mid-latitudes. Hurricane Irma in September 2017 was accompanied by upper-level strong wind around a trough; errors and ensemble spreads for the predicted upper-level trough are small, contributing to smaller errors and small ensemble spreads in the predicted tracks of Irma. Our observing system experiment reveals that inclusion of additional Arctic radiosonde observation data obtained from research vessel Mirai in 2017 improves error and ensemble spread in upper-level trough with strong wind at initial time for forecast, increasing the accuracy of the forecast of the track of Irma in 2017.

scholarly journals A statistical study of gravity waves from radiosonde observations at Wuhan (30° N, 114° E) China

2005 ◽  
Vol 23 (3) ◽  
pp. 665-673 ◽  
Author(s):  
S. D. Zhang ◽  
F. Yi
Keyword(s):  
Gravity Wave ◽  
Gravity Waves ◽  
Extreme Values ◽  
Dynamical Instability ◽  
Strong Wind ◽  
Data Set ◽  
Height Range ◽  
Wave Parameters ◽  
Thermal Structures ◽  
Radiosonde Observation

Abstract. Several works concerning the dynamical and thermal structures and inertial gravity wave activities in the troposphere and lower stratosphere (TLS) from the radiosonde observation have been reported before, but these works were concentrated on either equatorial or polar regions. In this paper, background atmosphere and gravity wave activities in the TLS over Wuhan (30° N, 114° E) (a medium latitudinal region) were statistically studied by using the data from radiosonde observations on a twice daily basis at 08:00 and 20:00 LT in the period between 2000 and 2002. The monthly-averaged temperature and horizontal winds exhibit the essential dynamic and thermal structures of the background atmosphere. For avoiding the extreme values of background winds and temperature in the height range of 11-18km, we studied gravity waves, respectively, in two separate height regions, one is from ground surface to 10km (lower part), and the other is within 18-25km (upper part). In total, 791 and 1165 quasi-monochromatic inertial gravity waves were extracted from our data set for the lower and upper parts, respectively. The gravity wave parameters (intrinsic frequencies, amplitudes, wavelengths, intrinsic phase velocities and wave energies) are calculated and statistically studied. The statistical results revealed that in the lower part, there were 49.4% of gravity waves propagating upward, and the percentage was 76.4% in the upper part. Moreover, the average wave amplitudes and energies are less than those at the lower latitudinal regions, which indicates that the gravity wave parameters have a latitudinal dependence. The correlated temporal evolution of the monthly-averaged wave energies in the lower and upper parts and a subsequent quantitative analysis strongly suggested that at the observation site, dynamical instability (strong wind shear) induced by the tropospheric jet is the main excitation source of inertial gravity waves in the TLS.

scholarly journals Bayesian Model Averaging for Wind Speed Ensemble Forecasts Using Wind Speed and Direction

2017 ◽  
Vol 32 (6) ◽  
pp. 2217-2227 ◽  
Author(s):  
Siri Sofie Eide ◽  
John Bjørnar Bremnes ◽  
Ingelin Steinsland
Keyword(s):  
Wind Speed ◽  
Wind Direction ◽  
Bayesian Model Averaging ◽  
Weather Prediction ◽  
Model Averaging ◽  
Strong Wind ◽  
Ensemble Forecasts ◽  
Wind Speeds ◽  
Low Wind Speeds ◽  
The One

Abstract In this paper, probabilistic wind speed forecasts are constructed based on ensemble numerical weather prediction (NWP) forecasts for both wind speed and wind direction. Including other NWP variables in addition to the one subject to forecasting is common for statistical calibration of deterministic forecasts. However, this practice is rarely seen for ensemble forecasts, probably because of a lack of methods. A Bayesian modeling approach (BMA) is adopted, and a flexible model class based on splines is introduced for the mean model. The spline model allows both wind speed and wind direction to be included nonlinearly. The proposed methodology is tested for forecasting hourly maximum 10-min wind speeds based on ensemble forecasts from the European Centre for Medium-Range Weather Forecasts at 204 locations in Norway for lead times from +12 to +108 h. An improvement in the continuous ranked probability score is seen for approximately 85% of the locations using the proposed method compared to standard BMA based on only wind speed forecasts. For moderate-to-strong wind the improvement is substantial, while for low wind speeds there is generally less or no improvement. On average, the improvement is 5%. The proposed methodology can be extended to include more NWP variables in the calibration and can also be applied to other variables.

scholarly journals Dynamics of Muddy Rain of 15 June 2018 in Nepal

Atmosphere ◽  
2020 ◽  
Vol 11 (5) ◽  
pp. 529
Author(s):  
Ashok Kumar Pokharel ◽  
Tianli Xu ◽  
Xiaobo Liu ◽  
Binod Dawadi
Keyword(s):  
Dust Emission ◽  
Dust Storms ◽  
Strong Wind ◽  
Hysplit Model ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Upper Level ◽  
Terra Satellite ◽  
Negative Buoyancy

It has been revealed from the Modern-Era Retrospective analysis for Research and Applications MERRA analyses, Moderate Resolution Imaging Spectroradiometer MODIS/Terra satellite imageries, Naval Aerosol Analysis and Prediction System NAAPS model outputs, Cloud –Aerosol Lidar and Infrared Pathfinder Satellite Observations CALIPSO imageries, Hybrid Single Particle Lagrangian Integrated Trajectory HYSPLIT model trajectories, atmospheric soundings, and observational records of dust emission that there were multiple dust storms in the far western parts of India from 12 to 15 June 2018 due to thunderstorms. This led to the lifting of the dust from the surface. The entry of dust into the upper air was caused by the generation of a significant amount of turbulent kinetic energy as a function of strong wind shear generated by the negative buoyancy of the cooled air aloft and the convective buoyancy in the lower planetary boundary layer. Elevated dust reached a significant vertical height and was advected towards the northern/northwestern/northeastern parts of India. In the meantime, this dust was carried by northwesterly winds associated with the jets in the upper level, which advected dust towards the skies over Nepal where rainfall was occurring at that time. Consequently, this led to the muddy rain in Nepal.

scholarly journals Assessing the Ensemble Predictability of Precipitation Forecasts for the January 2015 and 2016 East Coast Winter Storms

2017 ◽  
Vol 32 (3) ◽  
pp. 1057-1078 ◽  
Author(s):  
Steven J. Greybush ◽  
Seth Saslo ◽  
Richard Grumm
Keyword(s):  
East Coast ◽  
Initial Conditions ◽  
Wave Pattern ◽  
Forecast Errors ◽  
Ensemble Forecasts ◽  
Winter Storms ◽  
Position Errors ◽  
Skill Scores ◽  
Forecast Lead Time ◽  
East Coast Winter Storms

Abstract The ensemble predictability of the January 2015 and 2016 East Coast winter storms is assessed, with model precipitation forecasts verified against observational datasets. Skill scores and reliability diagrams indicate that the large ensemble spread produced by operational forecasts was warranted given the actual forecast errors imposed by practical predictability limits. For the 2015 storm, uncertainties along the western edge’s sharp precipitation gradient are linked to position errors of the coastal low, which are traced to the positioning of the preceding 500-hPa wave pattern using the ensemble sensitivity technique. Predictability horizon diagrams indicate the forecast lead time in terms of initial detection, emergence of a signal, and convergence of solutions for an event. For the 2016 storm, the synoptic setup was detected at least 6 days in advance by global ensembles, whereas the predictability of mesoscale features is limited to hours. Convection-permitting WRF ensemble forecasts downscaled from the GEFS resolve mesoscale snowbands and demonstrate sensitivity to synoptic and mesoscale ensemble perturbations, as evidenced by changes in location and timing. Several perturbation techniques are compared, with stochastic techniques [the stochastic kinetic energy backscatter scheme (SKEBS) and stochastically perturbed parameterization tendency (SPPT)] and multiphysics configurations improving performance of both the ensemble mean and spread over the baseline initial conditions/boundary conditions (IC/BC) perturbation run. This study demonstrates the importance of ensembles and convective-allowing models for forecasting and decision support for east coast winter storms.

scholarly journals Case Study of a Barrier Wind Corner Jet off the Coast of the Prince Olav Mountains, Antarctica

2012 ◽  
Vol 140 (7) ◽  
pp. 2044-2063 ◽  
Author(s):  
Melissa A. Nigro ◽  
John J. Cassano ◽  
Matthew A. Lazzara ◽  
Linda M. Keller
Keyword(s):  
Strong Wind ◽  
Ice Shelf ◽  
Maximum Wind ◽  
Ross Ice Shelf ◽  
Wind Speeds ◽  
Wind Event ◽  
Transantarctic Mountains ◽  
Upper Level ◽  
Forcing Mechanisms

Abstract The Ross Ice Shelf airstream (RAS) is a barrier parallel flow along the base of the Transantarctic Mountains. Previous research has hypothesized that a combination of katabatic flow, barrier winds, and mesoscale and synoptic-scale cyclones drive the RAS. Within the RAS, an area of maximum wind speed is located to the northwest of the protruding Prince Olav Mountains. In this region, the Sabrina automatic weather station (AWS) observed a September 2009 high wind event with wind speeds in excess of 20 m s−1 for nearly 35 h. The following case study uses in situ AWS observations and output from the Antarctic Mesoscale Prediction System to demonstrate that the strong wind speeds during this event were caused by a combination of various forcing mechanisms, including katabatic winds, barrier winds, a surface mesocyclone over the Ross Ice Shelf, an upper-level ridge over the southern tip of the Ross Ice Shelf, and topographic influences from the Prince Olav Mountains. These forcing mechanisms induced a barrier wind corner jet to the northwest of the Prince Olav Mountains, explaining the maximum wind speeds observed in this region. The RAS wind speeds were strong enough to induce two additional barrier wind corner jets to the northwest of the Prince Olav Mountains, resulting in a triple barrier wind corner jet along the base of the Transantarctic Mountains.

Ensemble-Based Analysis of the May 2010 Extreme Rainfall in Tennessee and Kentucky

2014 ◽  
Vol 142 (1) ◽  
pp. 222-239 ◽  
Author(s):  
Samantha L. Lynch ◽  
Russ S. Schumacher
Keyword(s):  
Mississippi River ◽  
Flash Flood ◽  
Extreme Rainfall ◽  
Heavy Rain ◽  
Heavy Precipitation ◽  
Extreme Rainfall Event ◽  
Ensemble Forecasts ◽  
Surface Cyclone ◽  
Upper Level ◽  
Surrounding Areas

Abstract From 1 to 3 May 2010, persistent heavy rainfall occurred in the Ohio and Mississippi River valleys due to two successive quasi-stationary mesoscale convective systems (MCSs), with locations in central Tennessee accumulating more than 483 mm of rain, and the city of Nashville experiencing a historic flash flood. This study uses operational global ensemble forecasts from the European Centre for Medium-Range Weather Forecasts (ECMWF) to diagnose atmospheric processes and assess forecast uncertainty in this event. Several ensemble analysis methods are used to examine the processes that led to the development and maintenance of this precipitation system. Differences between ensemble members that correctly predicted heavy precipitation and those that did not were determined, in order to pinpoint the processes that were favorable or detrimental to the system's development. Statistical analysis was used to determine how synoptic-scale flows were correlated to 5-day area-averaged precipitation. The precipitation throughout Nashville and the surrounding areas occurred ahead of an upper-level trough located over the central United States. The distribution of precipitation was found to be closely related to the strength of this trough and an associated surface cyclone. In particular, when the upper-level trough was elongated, the surface cyclone remained weaker with a narrower low-level jet from the south. This caused the plume of moisture from the Caribbean Sea to be concentrated over Tennessee and Kentucky, where, in conjunction with focused ascent, heavy rain fell. Relatively small differences in the wind and pressure fields led to important differences in the precipitation forecasts and highlighted some of the uncertainties associated with predicting this extreme rainfall event.

scholarly journals The Dynamics of an Extreme Precipitation Event in Northeastern Vietnam in 2015 and Its Predictability in the ECMWF Ensemble Prediction System

2017 ◽  
Vol 32 (3) ◽  
pp. 1041-1056 ◽  
Author(s):  
Roderick van der Linden ◽  
Andreas H. Fink ◽  
Joaquim G. Pinto ◽  
Tan Phan-Van
Keyword(s):  
Large Scale ◽  
Extreme Event ◽  
Coastal Region ◽  
Economic Loss ◽  
Precipitation Event ◽  
Ensemble Prediction ◽  
Ensemble Forecasts ◽  
Ensemble Prediction System ◽  
Upper Level ◽  
Quang Ninh

Abstract A record-breaking rainfall event occurred in northeastern Vietnam in late July–early August 2015. The coastal region in Quang Ninh Province was hit severely, with station rainfall sums in the range of 1000–1500 mm. The heavy rainfall led to flooding and landslides, which resulted in an estimated economic loss of $108 million (U.S. dollars) and 32 fatalities. Using a multitude of data sources and ECMWF ensemble forecasts, the synoptic–dynamic development and practical predictability of the event is investigated in detail for the 4-day period from 1200 UTC 25 July to 1200 UTC 29 July 2015, during which the major portion of the rainfall was observed. A slowly moving upper-level subtropical trough and the associated surface low in the northern Gulf of Tonkin promoted sustained moisture convergence and convection over northeastern Vietnam. The humidity was advected in a moisture transport band lying across the Indochina Peninsula and emanating from a tropical storm over the Bay of Bengal. Analyses of the ECMWF ensemble forecasts clearly showed a sudden emergence of the predictability of the extreme event at lead times of 3 days that was associated with the correct forecasts of the intensity and location of the subtropical trough in the 51 ensemble members. Thus, the Quang Ninh event is a good example in which the predictability of tropical convection arises from large-scale synoptic forcing; in the present case it was due to a tropical–extratropical interaction that has not been documented before for the region and season.

Towards operational postprocessing of cloud cover at MeteoSwiss

2020 ◽  
Author(s):  
Stephan Hemri ◽  
Christoph Spirig ◽  
Jonas Bhend ◽  
Lionel Moret ◽  
Mark Liniger
Keyword(s):  
Cloud Cover ◽  
Prediction Models ◽  
Weather Prediction ◽  
Weather Forecast ◽  
Forecast Errors ◽  
Observation Data ◽  
Model Output ◽  
Ensemble Forecasts ◽  
Direct Model ◽  
Ensemble Model Output Statistics

<p>Over the last decades ensemble approaches have become state-of-the-art for the quantification of weather forecast uncertainty. Despite ongoing improvements, ensemble forecasts issued by numerical weather prediction models (NWPs) still tend to be biased and underdispersed. Statistical postprocessing has proven to be an appropriate tool to correct biases and underdispersion, and hence to improve forecast skill. Here we focus on multi-model postprocessing of cloud cover forecasts in Switzerland. In order to issue postprocessed forecasts at any point in space, ensemble model output statistics (EMOS) models are trained and verified against EUMETSAT CM SAF satellite data with a spatial resolution of around 2 km over Switzerland. Training with a minimal record length of the past 45 days of forecast and observation data already produced an EMOS model improving direct model output (DMO). Training on a 3 years record of the corresponding season further improved the performance. We evaluate how well postprocessing corrects the most severe forecast errors, like missing fog and low level stratus in winter. For such conditions, postprocessing of cloud cover benefits strongly from incorporating additional predictors into the postprocessing suite. A quasi-operational prototype has been set up and was used to explore meteogram-like visualizations of probabilistic cloud cover forecasts.</p>

The Layered Structure of the Winter Atmospheric Boundary Layer in the Interior of Alaska

2013 ◽  
Vol 52 (4) ◽  
pp. 953-973 ◽  
Author(s):  
John A. Mayfield ◽  
Gilberto J. Fochesatto
Keyword(s):  
Boundary Layer ◽  
Statistical Analysis ◽  
Atmospheric Boundary Layer ◽  
Layered Structure ◽  
High Latitude ◽  
Meteorological Conditions ◽  
Formation Mechanisms ◽  
Observation Data ◽  
Interior Alaska ◽  
Radiosonde Observation

AbstractThe high-latitude winter atmospheric boundary layer of interior Alaska continually exhibits a complex layered structure as a result of extreme meteorological conditions. In this paper the occurrence of elevated inversions (EI), surface-based inversions (SBI), and stratified layers in the sub-Arctic from January 2000 to December 2009 is reported. This statistical analysis is based on radiosonde observation data from the Fairbanks National Weather Service station complemented by Winter Boundary Layer Experiment observations in the period 2010–11. This study found that SBIs occurred 64% of the time. An SBI occurred in combination with one, two, three, or four simultaneous EIs 84.86%, 48.49%, 21.23%, and 7.99% of the time, respectively, in 2326 total cases. The calculated mean SBI height was 377 m; EIs occurred at 1231, 2125, 2720, and 3125 m, respectively. This analysis was able to discriminate between locally controlled inversion layers and synoptic-dependent inversions and to identify their formation mechanisms. It was found that, in the presence of an SBI layer, the first EI layer formed 35.8% of the time under anticyclonic conditions at a mean height of 1249 m and 22% of the time in warm-air-advection situations at a mean height of 1049 m. The remaining 23.4% resulted from combined synoptic situations, and 18.8% were unclassified.

Sensitivity of Idealized Hurricane Intensity and Structures under Varying Background Flows and Initial Vortex Intensities to Different Vertical Resolutions in HWRF

2015 ◽  
Vol 143 (3) ◽  
pp. 914-932 ◽  
Author(s):  
Da-Lin Zhang ◽  
Lin Zhu ◽  
Xuejin Zhang ◽  
Vijay Tallapragada
Keyword(s):  
Structural Changes ◽  
Inner Core ◽  
Vertical Wind Shear ◽  
Initial Time ◽  
Mean Flow ◽  
Hurricane Intensity ◽  
Vertical Grid ◽  
Hurricane Intensification ◽  
Intensity Fluctuations ◽  
Upper Level

Abstract A series of 5-day numerical simulations of idealized hurricane vortices under the influence of different background flows is performed by varying vertical grid resolution (VGR) in different portions of the atmosphere with the operational version of the Hurricane Weather Research and Forecasting Model in order to study the sensitivity of hurricane intensity forecasts to different distributions of VGR. Increasing VGR from 21 to 43 levels produces stronger hurricanes, whereas increasing it further to 64 levels does not intensify the storms further, but intensity fluctuations are much reduced. Moreover, increasing the lower-level VGRs generates stronger storms, but the opposite is true for increased upper-level VGRs. On average, adding mean flow increases intensity fluctuations and variability (between the strongest and weakest hurricanes), whereas adding vertical wind shear (VWS) delays hurricane intensification and then causes more rapid growth in intensity variability. The stronger the VWS, the larger intensity variability and bifurcation rate occur at later stages. These intensity differences are found to be closely related to inner-core structural changes, and they are attributable to how much latent heat could be released in higher-VGR layers, followed by how much moisture content in nearby layers is converged. Hurricane intensity with higher VGRs is shown to be much less sensitive to varying background flows, and stronger hurricane vortices at the model initial time are less sensitive to the vertical distribution of VGR; the opposite is true for relatively uniform VGRs or weaker hurricane vortices. Results reveal that higher VGRs with a near-parabolic or Ω shape tend to produce smoother intensity variations and more typical inner-core structures.

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