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- Author or Editor: John S. Snook x
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Abstract
Banded cloudiness and precipitation are sometimes observed in convectively stable environments. These observations are often attributed to conditional symmetric instability (CSI). High-resolution operational instruments in the wind-profiler network and the WSR-88D radar network are beginning to provide real-time data that can enhance the evaluation of CSI conditions. These systems, combined with operational mesoscale models and the advanced meteorological computer workstation, are providing the opportunity to efficiently assess CSI on the meso-β scale (20–200 km) in real time. CSI theory is reviewed and techniques to apply CSI theory utilizing the new operational instrumentation are discussed. A case study is presented to illustrate current CSI evaluation techniques.
Abstract
Banded cloudiness and precipitation are sometimes observed in convectively stable environments. These observations are often attributed to conditional symmetric instability (CSI). High-resolution operational instruments in the wind-profiler network and the WSR-88D radar network are beginning to provide real-time data that can enhance the evaluation of CSI conditions. These systems, combined with operational mesoscale models and the advanced meteorological computer workstation, are providing the opportunity to efficiently assess CSI on the meso-β scale (20–200 km) in real time. CSI theory is reviewed and techniques to apply CSI theory utilizing the new operational instrumentation are discussed. A case study is presented to illustrate current CSI evaluation techniques.
Abstract
The National Weather Service (NWS) developed the Olympic Weather Support System (OWSS) to provide specialized operational weather support for the 1996 Centennial Olympic Games in Atlanta. Operational implementation of the National Oceanic and Atmospheric Administration Forecast Systems Laboratory’s Local Analysis and Prediction System (LAPS) was a key element of the OWSS. LAPS is a complete, three-dimensional data assimilation system that produced subhourly atmospheric analyses on an 8-km grid covering all the Olympic venues. The LAPS analyses also provided initial conditions to the Regional Atmospheric Modeling System (RAMS) mesoscale forecast model. RAMS forecasts were generated at least every 3 h using 8- or 2-km grids. For the first time, a comprehensive operational analysis and forecast system operated in a local NWS forecast office to support meso-β-scale forecasts and warnings. Numerous benefits of LAPS–RAMS to the local forecast office were demonstrated. The OWSS, with LAPS–RAMS included, provided a precursory view of the enhanced operational mesoscale forecast capabilities that can be available to the NWS and other forecast offices in the near future.
Abstract
The National Weather Service (NWS) developed the Olympic Weather Support System (OWSS) to provide specialized operational weather support for the 1996 Centennial Olympic Games in Atlanta. Operational implementation of the National Oceanic and Atmospheric Administration Forecast Systems Laboratory’s Local Analysis and Prediction System (LAPS) was a key element of the OWSS. LAPS is a complete, three-dimensional data assimilation system that produced subhourly atmospheric analyses on an 8-km grid covering all the Olympic venues. The LAPS analyses also provided initial conditions to the Regional Atmospheric Modeling System (RAMS) mesoscale forecast model. RAMS forecasts were generated at least every 3 h using 8- or 2-km grids. For the first time, a comprehensive operational analysis and forecast system operated in a local NWS forecast office to support meso-β-scale forecasts and warnings. Numerous benefits of LAPS–RAMS to the local forecast office were demonstrated. The OWSS, with LAPS–RAMS included, provided a precursory view of the enhanced operational mesoscale forecast capabilities that can be available to the NWS and other forecast offices in the near future.
Abstract
Over the 3-day period of 24–26 October 1997, a powerful winter storm was the cause of two exceptional weather phenomena: 1) blizzard conditions from Wyoming to southern New Mexico along the Front Range of the Rocky Mountains and 2) hurricane-force winds at the surface near Steamboat Springs, Colorado, with the destruction of about 5300 ha of old-growth forest. This rare event was caused by a deep, cutoff low pressure system that provided unusually strong, deep easterly flow over the Front Range for an extended period. The event was characterized by highly variable snowfall and some very large snowfall totals; over a horizontal distance of 15 km, in some cases, snowfall varied by as much as 1.0 m, with maximum total snowfall depths near 1.5 m. Because this variability was caused, in part, by terrain effects, this work investigates the capability of a mesoscale model constructed in terrain-following coordinates (the Regional Atmospheric Modeling System: RAMS) to forecast small-scale (meso γ), orographically forced spatial variability of the snowfall. There are few investigations of model-forecast liquid precipitation versus observations at meso-γ-scale horizontal grid spacing. Using a limited observational dataset, mean absolute percent errors of precipitation (liquid equivalent) of 41% and 9% were obtained at horizontal grid spacings of 5.00 and 1.67 km, respectively. A detailed, high-temporal-resolution (30-min intervals) comparison of modeled versus actual snowfall rates at a fully instrumented snow measurement testing site shows significant model skill. A companion paper, Part II, will use the same RAMS simulations to describe the observations and modeling of the simultaneous mountain-windstorm-induced forest blowdown event.
Abstract
Over the 3-day period of 24–26 October 1997, a powerful winter storm was the cause of two exceptional weather phenomena: 1) blizzard conditions from Wyoming to southern New Mexico along the Front Range of the Rocky Mountains and 2) hurricane-force winds at the surface near Steamboat Springs, Colorado, with the destruction of about 5300 ha of old-growth forest. This rare event was caused by a deep, cutoff low pressure system that provided unusually strong, deep easterly flow over the Front Range for an extended period. The event was characterized by highly variable snowfall and some very large snowfall totals; over a horizontal distance of 15 km, in some cases, snowfall varied by as much as 1.0 m, with maximum total snowfall depths near 1.5 m. Because this variability was caused, in part, by terrain effects, this work investigates the capability of a mesoscale model constructed in terrain-following coordinates (the Regional Atmospheric Modeling System: RAMS) to forecast small-scale (meso γ), orographically forced spatial variability of the snowfall. There are few investigations of model-forecast liquid precipitation versus observations at meso-γ-scale horizontal grid spacing. Using a limited observational dataset, mean absolute percent errors of precipitation (liquid equivalent) of 41% and 9% were obtained at horizontal grid spacings of 5.00 and 1.67 km, respectively. A detailed, high-temporal-resolution (30-min intervals) comparison of modeled versus actual snowfall rates at a fully instrumented snow measurement testing site shows significant model skill. A companion paper, Part II, will use the same RAMS simulations to describe the observations and modeling of the simultaneous mountain-windstorm-induced forest blowdown event.
Abstract
A devastating winter storm affected the Rocky Mountain states over the 3-day period of 24–26 October 1997. Blizzard conditions persisted over the foothills and adjoining plains from Wyoming to southern New Mexico, with maximum total snowfall amounts near 1.5 m. ( of this two-part paper describes the observations and modeling of this blizzard event.) During the morning of 25 October 1997, wind gusts in excess of 50 m s−1 were estimated west of the Continental Divide near Steamboat Springs in northern Colorado. These winds flattened approximately 5300 ha (13 000 acres) of old-growth forest in the Routt National Forest and Mount Zirkel Wilderness. Observations, analysis, and numerical modeling were used to examine the kinematics of this extreme event. A high-resolution, local-area model (the Regional Atmospheric Modeling System) was used to investigate the ability of a local model to capture the timing and strength of the windstorm and the aforementioned blizzard. Results indicated that a synergistic combination of strong cross-barrier easterly flow; very cold lower-tropospheric air over Colorado, which modified the stability profile; and the presence of a critical layer led to devastating downslope winds. The high-resolution simulations demonstrated the potential for accurately capturing mesoscale spatial and temporal features of a downslope windstorm more than 1 day in advance. These simulations were quasi forecast in nature, because a combination of two 48-h Eta Model forecasts were used to specify the lateral boundary conditions. Increased predictive detail of the windstorm was also found by decreasing the horizontal grid spacing from 5 to 1.67 km in the local-area model simulations.
Abstract
A devastating winter storm affected the Rocky Mountain states over the 3-day period of 24–26 October 1997. Blizzard conditions persisted over the foothills and adjoining plains from Wyoming to southern New Mexico, with maximum total snowfall amounts near 1.5 m. ( of this two-part paper describes the observations and modeling of this blizzard event.) During the morning of 25 October 1997, wind gusts in excess of 50 m s−1 were estimated west of the Continental Divide near Steamboat Springs in northern Colorado. These winds flattened approximately 5300 ha (13 000 acres) of old-growth forest in the Routt National Forest and Mount Zirkel Wilderness. Observations, analysis, and numerical modeling were used to examine the kinematics of this extreme event. A high-resolution, local-area model (the Regional Atmospheric Modeling System) was used to investigate the ability of a local model to capture the timing and strength of the windstorm and the aforementioned blizzard. Results indicated that a synergistic combination of strong cross-barrier easterly flow; very cold lower-tropospheric air over Colorado, which modified the stability profile; and the presence of a critical layer led to devastating downslope winds. The high-resolution simulations demonstrated the potential for accurately capturing mesoscale spatial and temporal features of a downslope windstorm more than 1 day in advance. These simulations were quasi forecast in nature, because a combination of two 48-h Eta Model forecasts were used to specify the lateral boundary conditions. Increased predictive detail of the windstorm was also found by decreasing the horizontal grid spacing from 5 to 1.67 km in the local-area model simulations.
Abstract
The weather and climate greatly affect socioeconomic activities on multiple temporal and spatial scales. From a climate perspective, atmospheric and ocean characteristics have determined the life, evolution, and prosperity of humans and other species in different areas of the world. On smaller scales, the atmospheric and sea conditions affect various sectors such as civil protection, food security, communications, transportation, and insurance. It becomes evident that weather and ocean forecasting is high-value information highlighting the need for state-of-the-art forecasting systems to be adopted. This importance has been acknowledged by the authorities of Saudi Arabia entrusting the National Center for Meteorology (NCM) to provide high-quality weather and climate analytics. This led to the development of a numerical weather prediction (NWP) system. The new system includes weather, wave, and ocean circulation components and has been operational since 2020 enhancing the national capabilities in NWP. Within this article, a description of the system and its performance is discussed alongside future goals.
Abstract
The weather and climate greatly affect socioeconomic activities on multiple temporal and spatial scales. From a climate perspective, atmospheric and ocean characteristics have determined the life, evolution, and prosperity of humans and other species in different areas of the world. On smaller scales, the atmospheric and sea conditions affect various sectors such as civil protection, food security, communications, transportation, and insurance. It becomes evident that weather and ocean forecasting is high-value information highlighting the need for state-of-the-art forecasting systems to be adopted. This importance has been acknowledged by the authorities of Saudi Arabia entrusting the National Center for Meteorology (NCM) to provide high-quality weather and climate analytics. This led to the development of a numerical weather prediction (NWP) system. The new system includes weather, wave, and ocean circulation components and has been operational since 2020 enhancing the national capabilities in NWP. Within this article, a description of the system and its performance is discussed alongside future goals.
