[Show abstract][Hide abstract] ABSTRACT: A relocation procedure to initialize tropical cyclones was developed to improve the representation of the initial conditions and the track forecast for Panasonic Weather Solutions Tropical Operational Forecasts. This scheme separates the vortex perturbation and environment field from the first guess, then relocates the initial vortex perturbations to the observed position by merging them with the environment field.
The relationships of wind vector components with stream function and velocity potential are used for separating the vortex disturbance from first guess. For the separation of scalars, a low-pass Barnes filter is employed. The irregular-shaped relocation area corresponding to the specific initial conditions is determined by mapping the edge of the vortex radius in 36 directions. Then, the non-vortex perturbations in the relocation area are removed by a two-pass Barnes filter to retain the vortex perturbations, while the variable fields outside the perimeter of the modified vortex are kept identical to the original first guess.
The potential impacts of this scheme on track forecasts were examined for three hurricane cases in the 2011–12 hurricane season. The experimental results demonstrate that the initialization scheme is able to effectively separate the vortex field from the environment field and maintain a relatively balanced and accurate relocated first guess. As the initial track error is reduced, the following track forecasts are considerably improved. The 72-h average track forecast error was reduced by 32.6% for the cold-start cases, and by 38.4% when using the full-cycling data assimilation because of the accumulated improvements from the initialization scheme.
Full-text · Article · Jan 2014 · Advances in Atmospheric Sciences
[Show abstract][Hide abstract] ABSTRACT: Investigating the characteristics of model-forecast errors using various
statistical and object-oriented methods is necessary for providing
useful guidance to end-users and model developers as well. To this end,
the random and systematic errors (i.e., biases) of the 2-m temperature
and 10-m wind predictions of the NCAR-AirDat weather research and
forecasting (WRF)-based real-time four-dimensional data assimilation
(RTFDDA) and forecasting system are analyzed. This system has been
running operationally over a contiguous United States (CONUS) domain at
a 4-km grid spacing with four forecast cycles daily from June 2009 to
September 2010. In the result an exceptionally useful forecast dataset
was generated and used for studying the error properties of the model
forecasts, in terms of both a longer time period and a broader coverage
of geographic regions than previously studied. Spatiotemporal
characteristics of the errors are investigated based on the 24-h
forecasts between June 2009 and April 2010, and the 72-h forecasts
between May and September 2010. It was found that the biases of both
wind and temperature forecasts vary greatly seasonally and diurnally,
with dependency on the forecast length, station elevation, geographical
location, and meteorological conditions. The temperature showed
systematic cold biases during the daytime at all station elevations and
warm biases during the nighttime above 1,000 m above sea level (ASL),
while below 600 m ASL cold biases occurred during the nighttime. The
forecasts of surface wind speed exhibited strong positive biases during
the nighttime, while the negative biases were observed in the spring and
summer afternoons. The surface wind speed was mostly over-predicted
except for the stations located between 1,000 and 2,100 m ASL, for which
negative biases were identified for most forecast cycles. The highest
wind-speed errors were found over the high terrain and near sea-level
stations. The wind-direction errors were relatively large at the
high-terrain elevation in the Rocky and Appalachian mountain ranges and
the western coastal areas and the error structure exhibited notable
No preview · Article · Sep 2013 · Meteorology and Atmospheric Physics
[Show abstract][Hide abstract] ABSTRACT: Tropospheric Airborne Meteorological Data Reporting (TAMDAR) observations are becoming a major data source for numerical weather prediction (NWP) because of the advantages of their high spatiotemporal resolution and humidity measurements. In this study, the estimation of TAMDAR observational errors, and the impacts of TAMDAR observations with new error statistics on short-term forecasts are presented. The observational errors are estimated by a three-way collocated statistical comparison. This method employs collocated meteorological reports from three data sources:TAMDAR, radiosondes, and the 6-h forecast from a Weather Research and Forecasting Model (WRF). The performance of TAMDAR observations with the new error statistics was then evaluated based on this model, and the WRF Data Assimilation (WRFDA) three-dimensional variational data assimilation (3DVAR) system. The analysis was conducted for both January and June of 2010. The experiments assimilate TAMDAR, as well as other conventional data with the exception of non-TAMDAR aircraft observations, every 6 h, and a 24-h forecast is produced. The standard deviation of the observational error of TAMDAR, which has relatively stable values regardless of season, is comparable to radiosondes for temperature, and slightly smaller than that of a radiosonde for relative humidity. The observational errors in wind direction significantly depend on wind speeds. In general, at low wind speeds, the error in TAMDAR is greater than that of radiosondes; however, the opposite is true for higher wind speeds. The impact ofTAMDARobservations on both the 6- and 24-hWRFforecasts during the studied period is positive when using the default observational aircraft weather report (AIREP) error statistics. The new TAMDAR error statistics presented here bring additional improvement over the default error.
Full-text · Article · Aug 2012 · Weather and Forecasting
[Show abstract][Hide abstract] ABSTRACT: Two numerical simulations were performed to study the ability of a high-resolution mesoscale model to predict the track and
structure of Hurricane Isabel over North Carolina. One simulation (Control) used standard NCEP climatologically-based sea
surface temperature (SST) data for the lower boundary condition while another simulation (Experimental) prescribed real-time
high-resolution SST data for the lower boundary. Results from this study show that both simulations predict the track of Isabel
over North Carolina reasonably well, although the track predicted by the experimental simulation agrees more closely with
observations. The experimental simulation more closely agrees with observations of the intensity of Isabel and the amount
and spatial distribution of precipitation. These results reinforce the importance of accurate high-resolution SST data on
numerical simulations of tropical cyclones.
[Show abstract][Hide abstract] ABSTRACT: The Flux-Adjusting Surface Data Assimilation System (FASDAS) uses the surface observational analysis to directly assimilate surface layer temperature and water vapor mixing ratio and to indirectly assimilate soil moisture and soil temperature in numerical model predictions. Both soil moisture and soil temperature are important variables in the development of deep convection. In this study, FASDAS coupled within the fifth-generation Pennsylvania State University-NCAR Mesoscale Model (MM5) was used to study con- vective initiation over the International H2O Project (IHOP_2002) region, utilizing the analyzed surface observations collected during IHOP_2002. Two 72-h numerical simulations were performed. A control simulation was run that assimilated all available IHOP_2002 measurements into the standard MM5 four- dimensional data assimilation. An experimental simulation was also performed that assimilated all available IHOP_2002 measurements into the FASDAS version of the MM5, where surface observations were used for the FASDAS coupling. Results from this case study suggest that the use of FASDAS in the experimental simulation led to the generation of greater amounts of precipitation over a more widespread area as compared to the standard MM5 FDDA used in the control simulation. This improved performance is attributed to better simulation of surface heat fluxes and their gradients.
Preview · Article · Jan 2006 · Monthly Weather Review
[Show abstract][Hide abstract] ABSTRACT: Following the collapse of the New York City World Trade Center towers on September 11, 2001, Local, State and Federal agencies initiated numerous air monitoring activities to better understand the impact of emissions from the disaster. A study of the estimated pathway that a potential plume of emissions would likely track was completed to support the U.S. EPA’s initial exposure assessments. The plume from the World Trade Center was estimated using the CALMET-CALPUFF dispersion modeling system. The following is the first of two reports that compares several meteorological models, including the CALMET diagnostic model, the Advanced Regional Prediction System (ARPS) and 5th Generation Mesoscale Model (MM5) in the complex marine-influenced urban setting of NYC. Results indicate wind speed, in most cases, is greater in CALMET than the two mesoscale models because the CALMET micrometeorological processor does not properly adjust the wind field for surface roughness variations that exits in a major built-up urban area. Small-scale circulations, which were resolved by the mesoscale models, were not well simulated by CALMET. Independent wind observations in Lower Manhattan suggest that the wind direction estimates of CALMET possess a high degree of error because of the urban influence. Wind speed is on average 1.5 ms−1 stronger in CALMET than what observations indicate. The wind direction downwind of the city is rotated 25–34 clockwise in CALMET, relative to what observations indicate.
Preview · Article · Sep 2005 · Pure and Applied Geophysics
[Show abstract][Hide abstract] ABSTRACT: Observations from two SOund Detection And Ranging (SODAR) units, a 10 m micrometeorological tower and five Automated Surface Observing Stations (ASOS) were examined during several synoptic scale flow regimes over New York City after the World Trade Center disaster on September 11, 2001. An ARPS model numerical simulation was conducted to explore the complex mesoscale boundary layer structure over New York City. The numerical investigation examined the urban heat island, urban roughness effect and sea breeze structure over the New York City region. Estimated roughness lengths varied from 0.7 m with flow from the water to 4 m with flow through Manhattan. A nighttime mixed layer was observed over lower Manhattan, indicating the existence of an urban heat island. The ARPS model simulated a sea-breeze front moving through lower Manhattan during the study period consistent with the observations from the SODARs and the 10-m tower observations. Wind simulations showed a slowing and cyclonic turning of the 10-m air flow as the air moved over New York City from the ocean. Vertical profiles of simulated TKE and wind speeds showed a maximum in TKE over lower Manhattan during nighttime conditions. It appears that this TKE maximum is directly related to the influences of the urban heat island.
Preview · Article · Jan 2005 · Pure and Applied Geophysics
[Show abstract][Hide abstract] ABSTRACT: The effects of sea surface temperature (SST) on the mesoscale boundary layer structure off the southeastern US coast were studied. The weather prediction models used by the forecasters include GFS, RUC and Eta with grid spacings of 50, 20 and 12 km. The PSU/NCAR mesoscale model 5 (MM5) is used to study the mesoscale structure off the southeastern US coastline which was a terrain folowing fully compressible primitive equation model with nonhydrostatic dynamics. The results show that the SST's in the Control Simulation are 5C warmer than in the Experimental Simulation within 2 km of Cape Hatteras.
[Show abstract][Hide abstract] ABSTRACT: Evapotranspiration measurements were taken at 14 locations across North Carolina using an ETgage that allows distilled water to evaporate through a waterproof surface. Equivalent surface turbulent latent heat fluxes were derived from evapotranspiration values. Variations in latent heat flux and evapotranspiration were analyzed across North Carolina to investigate its dependence on soil type, land use and initial soil moisture. The Sandhills region experiences the largest amount of evapotranspiration in the state with the mountain region having the least. Estimations of latent heat flux using Priestley-Taylor and Penman-Monteith methods are compared with observations. A mesoscale numerical simulation was performed for the period, 00Z August 14, 2003 to 00Z August 16, 2003. Penman-Monteith and Priestley-Taylor methods of obtaining latent heat flux were applied using simulated atmospheric parameters and compared with observations. Priestley-Taylor method appears to have a higher degree of accuracy as compared to Penman-Monteith method at the selected locations across the state.