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Abstract
An integrated analysis of photographic and Doppler radar observations of a tornadic storm during the Convection Initiation and Downburst Experiment (CINDE) is presented. High-resolution single-Doppler radar measurements are combined with cloud photogrammetry to reveal the detailed structural relationship of the hook echo and the misocyclone with visual features of the tornado. Vertical cross sections of dual-Doppler winds in the plane of the photographs were also examined to determine the complex motions within and surrounding the vortex. The tornado was found to be within a weak-echo hole of the hook echo. The hole progressed upward above cloud base as the tornado matured. An annulus of higher reflectivity that formed a book echo is hypothesized to have been composed of sparse but large raindrops. The airflow fields suggest that vortex breakdown and axial downdrafts were present near the ground at early stages shortly after the tornado became visible. Later, axial upward flow dominated at all levels until the collapse of the vortex.
Abstract
An integrated analysis of photographic and Doppler radar observations of a tornadic storm during the Convection Initiation and Downburst Experiment (CINDE) is presented. High-resolution single-Doppler radar measurements are combined with cloud photogrammetry to reveal the detailed structural relationship of the hook echo and the misocyclone with visual features of the tornado. Vertical cross sections of dual-Doppler winds in the plane of the photographs were also examined to determine the complex motions within and surrounding the vortex. The tornado was found to be within a weak-echo hole of the hook echo. The hole progressed upward above cloud base as the tornado matured. An annulus of higher reflectivity that formed a book echo is hypothesized to have been composed of sparse but large raindrops. The airflow fields suggest that vortex breakdown and axial downdrafts were present near the ground at early stages shortly after the tornado became visible. Later, axial upward flow dominated at all levels until the collapse of the vortex.
Abstract
The climatology of heavy rain events from hourly precipitation observations by Brooks and Stensrud is revisited in this study using two high-resolution precipitation datasets that incorporate both gauge observations and radar estimates. Analyses show a seasonal cycle of heavy rain events originating along the Gulf Coast and expanding across the eastern two-thirds of the United States by the summer, comparing well to previous findings. The frequency of extreme events is estimated, and may provide improvements over prior results due to both the increased spatial resolution of these data and improved techniques used in the estimation. The diurnal cycle of heavy rainfall is also examined, showing distinct differences in the strength of the cycle between seasons.
Abstract
The climatology of heavy rain events from hourly precipitation observations by Brooks and Stensrud is revisited in this study using two high-resolution precipitation datasets that incorporate both gauge observations and radar estimates. Analyses show a seasonal cycle of heavy rain events originating along the Gulf Coast and expanding across the eastern two-thirds of the United States by the summer, comparing well to previous findings. The frequency of extreme events is estimated, and may provide improvements over prior results due to both the increased spatial resolution of these data and improved techniques used in the estimation. The diurnal cycle of heavy rainfall is also examined, showing distinct differences in the strength of the cycle between seasons.
Abstract
A tornado climatology for Finland is constructed from 1796 to 2007. The climatology consists of two datasets. A historical dataset (1796–1996) is largely constructed from newspaper archives and other historical archives and datasets, and a recent dataset (1997–2007) is largely constructed from eyewitness accounts sent to the Finnish Meteorological Institute and news reports. This article describes the process of collecting and evaluating possible tornado reports. Altogether, 298 Finnish tornado cases compose the climatology: 129 from the historical dataset and 169 from the recent dataset. An annual average of 14 tornado cases occur in Finland (1997–2007). A case with a significant tornado (F2 or stronger) occurs in our database on average every other year, composing 14% of all tornado cases. All documented tornadoes in Finland have occurred between April and November. As in the neighboring countries in northern Europe, July and August are the months with the maximum frequency of tornado cases, coincident with the highest lightning occurrence both over land and sea. Waterspouts tend to be favored later in the summer, peaking in August. The peak month for significant tornadoes is August. The diurnal peak for tornado cases is 1700–1859 local time.
Abstract
A tornado climatology for Finland is constructed from 1796 to 2007. The climatology consists of two datasets. A historical dataset (1796–1996) is largely constructed from newspaper archives and other historical archives and datasets, and a recent dataset (1997–2007) is largely constructed from eyewitness accounts sent to the Finnish Meteorological Institute and news reports. This article describes the process of collecting and evaluating possible tornado reports. Altogether, 298 Finnish tornado cases compose the climatology: 129 from the historical dataset and 169 from the recent dataset. An annual average of 14 tornado cases occur in Finland (1997–2007). A case with a significant tornado (F2 or stronger) occurs in our database on average every other year, composing 14% of all tornado cases. All documented tornadoes in Finland have occurred between April and November. As in the neighboring countries in northern Europe, July and August are the months with the maximum frequency of tornado cases, coincident with the highest lightning occurrence both over land and sea. Waterspouts tend to be favored later in the summer, peaking in August. The peak month for significant tornadoes is August. The diurnal peak for tornado cases is 1700–1859 local time.
Abstract
Numerical forecasts from a pilot program on short-range ensemble forecasting at the National Centers for Environmental Prediction are examined. The ensemble consists of 10 forecasts made using the 80-km Eta Model and 5 forecasts from the regional spectral model. Results indicate that the accuracy of the ensemble mean is comparable to that from the 29-km Meso Eta Model for both mandatory level data and the 36-h forecast cyclone position. Calculations of spread indicate that at 36 and 48 h the spread from initial conditions created using the breeding of growing modes technique is larger than the spread from initial conditions created using different analyses. However, the accuracy of the forecast cyclone position from these two initialization techniques is nearly identical. Results further indicate that using two different numerical models assists in increasing the ensemble spread significantly.
There is little correlation between the spread in the ensemble members and the accuracy of the ensemble mean for the prediction of cyclone location. Since information on forecast uncertainty is needed in many applications, and is one of the reasons to use an ensemble approach, the lack of a correlation between spread and forecast uncertainty presents a challenge to the production of short-range ensemble forecasts.
Even though the ensemble dispersion is not found to be an indication of forecast uncertainty, significant spread can occur within the forecasts over a relatively short time period. Examples are shown to illustrate how small uncertainties in the model initial conditions can lead to large differences in numerical forecasts from an identical numerical model.
Abstract
Numerical forecasts from a pilot program on short-range ensemble forecasting at the National Centers for Environmental Prediction are examined. The ensemble consists of 10 forecasts made using the 80-km Eta Model and 5 forecasts from the regional spectral model. Results indicate that the accuracy of the ensemble mean is comparable to that from the 29-km Meso Eta Model for both mandatory level data and the 36-h forecast cyclone position. Calculations of spread indicate that at 36 and 48 h the spread from initial conditions created using the breeding of growing modes technique is larger than the spread from initial conditions created using different analyses. However, the accuracy of the forecast cyclone position from these two initialization techniques is nearly identical. Results further indicate that using two different numerical models assists in increasing the ensemble spread significantly.
There is little correlation between the spread in the ensemble members and the accuracy of the ensemble mean for the prediction of cyclone location. Since information on forecast uncertainty is needed in many applications, and is one of the reasons to use an ensemble approach, the lack of a correlation between spread and forecast uncertainty presents a challenge to the production of short-range ensemble forecasts.
Even though the ensemble dispersion is not found to be an indication of forecast uncertainty, significant spread can occur within the forecasts over a relatively short time period. Examples are shown to illustrate how small uncertainties in the model initial conditions can lead to large differences in numerical forecasts from an identical numerical model.
