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Richard H. Grumm

Abstract

The performance of the Aviation Run (AVN) of the National Meteorological Center's (NMC) Global Spectral Model (GSM) in predicting surface cyclones was examined during the autumn of 1990 through the winter of 1992, a period during which the resolution of the model was increased with the implementation of the triangular truncation 126 (T126) GSM, and the GSM analysis scheme was changed. The results indicate that the finer resolution T126 GSM produces stronger and deeper cyclones than the old T80 GSM.

These results also revealed that the errors in AVN position forecasts of surface cyclones were smaller than those found in the NMC Nested Grid Model (NGM). The geographical distribution of the pressure errors were similar to those found in the NGM over eastern North America and the adjacent western Atlantic Ocean. Negative pressure errors, indicative of overdeepening of surface cyclones, dominated the mountainous regions of western North America. Positive pressure errors, indicative of underdeepening of surface cyclones, dominated most of the western Atlantic.

The AVN tended to underpredict the 1000-500-mb thickness over surface cyclones, especially during the first 36 h of the forecast cycle. This cold bias decreased with forecast length and in the T80 version of the AVN became a warm bias at the later forecast periods during several months.

The skill in the AVN, measured by examining the sign of the forecast and observed 12-h pressure changes, the number of nonobserved and nonforecast cyclones, and skill indices revealed that the AVN is superior to the NGM in predicting the development and life cycle of surface cyclones. The AVN is able to forecast the sign of the 12-h pressure change greater than 80% of the time for the first 36 h of the forecast cycle and 74% of the time at 72 h. The results indicate that the T126 AVN performs at a skill comparable to the skill of the 48 h NGM cyclone forecasts. These results imply that the T126 AVN forecasts are accurate enough to provide guidance for basic weather forecasts to three days as has been done for the two-day forecasts for the past 25–30 years.

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Richard H. Grumm

No abstract available.

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Charles Warner and Richard H. Grumm

Abstract

A monsoon depression over the Bay of Bengal on 7 July 1979 has been studied using a variety of observations, in particular, cloud photographs from aircraft. Ascent in the lower troposphere was concentrated in mesoscale features of cumulus clouds covering ∼1% of the inner area (3 × 105 km2) of the depression. Across these mesoscale features discontinuities in thermal fields were found along with abrupt wind shifts.

Much of the volume of the depression featured thin fragmentary layers of stratus, implying an absence of strong vertical motion. Observed by photography, individual rising cumulus towers were of width up to a few kilometers, increasing with height; rise rates of towers reached 9 m s−1. Measured with aircraft instruments, mean updrafts in cumulus clouds were ∼2.5 m s−1. In cumulus populations scattered throughout the storm, number densities of cumulus ranged from ∼1 km−2 for fractus to ∼1 per 1500 km2 for Congestus. Congestus penetrating the 500 (300) hPa level were ∼1 per 3200 (13 000) km2. Fractional area coverage by cumulus updrafts was ∼0.5% in humilis, less in other categories. Coverage by cumulus updrafts was roughly 20 times less than coverage by inert remnants of cumulus. Cloudy ascending motion in populations of cumulus was generally on the order of hundredths of Pascals per second. It appeared to be mostly compensated by local subsidence. Great number densities of humilis were found moistening the central area following subsidence and drying.

Total cloud cover was dominated by mid-level thin fragmentary status layers and cumulus debris. There was extensive anvil cloud based at ∼400 hPa, apparently arising from cumulus.

Detailed observations were made of a cloud line growing out of the southwesterly flow south of the center of the depression. The line was followed for 3 h on GOES-1 visible imagery. It propagated faster than the low-level winds. Aircraft altimetry showed an abrupt height drop from 6097 to 6090 m at 483 hPa, over a distance of 50 km from southeast to northwest through the line. Southwesterly momentum was lifted from 900 to 600 hPa and from southeast to northwest through the line. Other colocated singularities in convection and wind fields were found.

Ascent in the lower troposphere over the depression as a whole (1066 km2) was assessed from aircraft and dropwindsonde data to be approximately −0.3 Pa s−1.

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Richard H. Grumm and Robert Hart

Abstract

Forecasting significant weather events, such as floods, heat waves, arctic outbreaks, ice storms, large severe weather outbreaks, and major winter storms, is a critical function for all weather services. However, conventional pressure level geopotential and temperature fields often are insufficient to determine whether an event represents a large departure from normal. This is largely due to the variability that exists throughout the year and regionally throughout the world. What represents an unusual departure from average conditions in fall may not be as unusual in winter. What is an unusual departure from average conditions in California may be normal in New England. This paper presents a method, normalized field departures from local climatology, that gives forecasters guidance on the relative rarity of events. Thus, in this paper a method is presented to help forecasters identify potentially significant weather events. The focus of this paper is on significant winter storms. However, a record winter warmth event is shown to demonstrate the broad potential use of this method.

The results suggest that many record snowstorms in the literature were associated with storms that departed significantly from normal. Using model data, it is demonstrated that models can successfully forecast events that represent a significant departure from normal. In fact, the results suggest that the models are quite successful at forecasting unusually strong weather systems in the short range (2–3 days) and show some success out to 6 days.

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Richard H. Grumm and John R. Gyakum

Abstract

An examination is made of the current National Meteorological Center (NMC) operational models’ ability to forecast surface anticyclones. A study of the 1981–82 cold season reveals systematic underprediction of the phenomenon on the part of both the Limited Area Fine Mesh (LFM) and spectral models. However, the LFM forecasts weaker anticyclones than does the spectral model. This difference is apparent in the region of eastern North America and the western Atlantic Ocean. The systematic underprediction found in this study is as great as Colucci and Bosart found for NMC's six-layer primitive equation model.

No overall systematic forecast bias is found for the 1000–500 mb mean temperatures over the surface anti-cyclones. However, excessively warm temperatures are forecast in the Pacific northwest region of both models, and the LFM forecasts erroneously cold temperatures in the western Atlantic basin south of 40°N. The spectral model shows a significant improvement over the LFM in this latter region.

The mean anticyclone displacement error for both models at 48-h range is about 500 km. There is also a tendency for both models to place anticyclones erroneously to the south and east of their observed positions, suggesting the models' translation of these anticyclones to be too fast. Colucci and Bosart also found a fast bias, but this study suggests an overall improvement in anticyclone placement.

Finally, a case of a recent poorly forecasted anticyclone-cyclone complex illustrates the deleterious effects those forecasts can have in the attempt to correctly forecast significant precipitation events. Our study shows an unforecasted precipitation event to have occurred in a lower troposphere warm advection region associated with a poorly forecasted surface anticyclone.

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Richard H. Grumm and Anthony L. Siebers

Abstract

Results from a study examining the performance of the nested grid model (NGM) and the aviation run of the global spectral model (AVN) in predicting surface cyclones during January 1990 revealed that the AVN slightly outperformed the NGM in forecasting cyclone central pressures and placement. Although both models performed better for deepening systems than filling systems, the AVN outperformed the NGM in predicting the characteristics of filling cyclones.

Overall, the NGM tended to overdeepen surface cyclones. A large part of the pressure error was due to the model's inability to properly fill cyclones and a tendency to forecast systems to deepen when they were observed to be filling.

The AVN tended to underdeepen surface cyclones with the deepening rate errors near 2 mb at 12 h and less than 1 mb by 48 h. The overall pressure errors for deepening cyclones appeared to be linked to a spin-up problem in the AVN and may have also been associated with the AVN cold bias in 1000- to 500-mb thickness forecasts.

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David J. Nicosia and Richard H. Grumm

Abstract

The National Centers for Environmental Prediction’s 29-km version Meso Eta Model and Weather Surveillance Radar-1988 Doppler base reflectivity data were used to diagnose intense mesoscale snowbands in three northeastern United States snowstorms. Snowfall rates within these snowbands were extreme and, in one case, were close to 15 cm (6 in.) per hour. The heaviest total snowfall with each snowstorm was largely associated with the positioning of these mesoscale snowbands. Each snowstorm exhibited strong midlevel frontogenesis in conjunction with a deep layer of negative equivalent potential vorticity (EPV). The frontogenesis and negative EPV were found in the deformation zone, north of the developing midlevel cyclone. Cross-sectional analyses (oriented perpendicular to the isotherms) indicated that the mesoscale snowbands formed in close correlation to the intense midlevel frontogenesis and deep layer of negative EPV.

It was found that the EPV was significantly reduced on the warm side of the midlevel frontogenetic region as midlevel dry air, associated with a midlevel dry tongue jet, overlaid a low-level moisture-laden easterly jet, north of each low-level cyclone. The continual reduction of EPV on the warm side of the frontogenetic region is postulated to have created the deep layer of negative EPV in the warm advection zone of each cyclone. The negative EPV was mainly associated with conditional symmetric instability (CSI). Each case exhibited a much smaller region of conditional instability (CI) on the warm side of the frontogenesis maximum for a short period of time. The CSI and, to a lesser extent, CI are postulated to have been released as air parcels ascended the moist isentropes, north of the warm front, upon reaching saturation. This likely was a major factor in the mesoscale band formation and heavy snowfall with each snowstorm.

The results indicate that model frontogenesis and EPV fields can be used to predict the potential development of mesoscale snowbands. When a deep layer of negative EPV and strong midlevel frontogenesis are forecast by the models, forecasters can anticipate the regions where mesoscale snowbands may form. Inspection of saturation equivalent potential temperature in conjunction with EPV is suggested to determine whether CI is present in a negative EPV region. If CI is present in addition to CSI, then upright convection may dominate over slantwise convection leading to heavier snowfall rates. The region where the frontogenesis and negative EPV are forecast to persist the longest (usually left of the 700-hPa low track) is where the heaviest storm total snowfall will occur. Once mesoscale bands are detected on radar, accurate short-term forecasts of areas that will receive heavy snowfall can be made.

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Randall A. Graham and Richard H. Grumm

Abstract

Synoptic-scale weather events over the western United States are objectively ranked based on their associated tropospheric anomalies. Data from the NCEP 6-h reanalysis fields from 1948 to 2006 are compared to a 30-yr (1971–2000) reanalysis climatology. The relative rarity of an event is measured by the number of standard deviations that the 1000–200-hPa height, temperature, wind, and moisture fields depart from climatology. The top 20 synoptic-scale events were identified over the western United States, adjacent eastern Pacific Ocean, Mexico, and Canada. Events that composed the top 20 tended to be very anomalous in several, if not all four, of the atmospheric variables. The events included the northern Intermountain West region heavy rainfall and Yellowstone tornado of mid-July 1987 (ranked 5th), the Montana floods of September 1986 (ranked 4th), and the historic 1962 “Columbus Day” windstorm in the Pacific Northwest (ranked 10th). In addition, the top 10 most anomalous events were identified for each month and for each of the variables investigated revealing additional significant weather events.

Finally, anomaly return periods were computed for each variable at a variety of levels. To place a given anomaly in perspective for a specific level or element, forecasters need information on the frequency with which that anomaly is observed. These return periods can be utilized by forecasters to compare forecast anomalies to the actual occurrence of similar anomalies for the element and level of interest to gauge the potential significance of the event. It is believed that this approach may allow forecasters to better understand the historical significance of an event and provide additional information to the user community.

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Robert J. Oravec and Richard H. Grumm

Abstract

A study of rapidly deepening cyclones (RDC) produced by the National Meteorological Center's (NMC) Nested Grid Model (NGM) was conducted over a three-year period from the winter of 1988/89 through the autumn of 1991. The axis of RDCs was observed over the western Atlantic 0cean from off the mid-Atlantic coast northeastward to the southern tip of Greenland, and a smaller axis was observed over the eastern Pacific over the Gulf of Alaska and southern Alaska. Relatively few RDCs occurred over the eastern Pacific during the winter and spring, with the maximum distribution occurring during the autumn.

The ability of the NGM to forecast RDCs was a function of both the forecast length and the season. The NGM's ability to simulate RDCs was greatest at 12 h and steadily decreased with forecast length. Similarly, the false alarm rate (FAR) was lowest at 12 h and steadily increased with forecast length through 48 h. The ability of the NGM to detect RDCs was greatest in the winter and decreased during the spring and fall.

There was a smaller decrease in probability of detection in the middle of the forecast cycle during the winter and spring that may be attributed to spinup problems in the NGM during the initialization of the model. Similar trends in the FAR were noted, with a decrease in FAR beyond 12 h during the winter seasons.

The results from this study showed the NGM was too slow to deepen RDCs at all 12-h forecast periods, with the pressure errors increasing with forecast length. The NGM also had a cold bias in the 1000–500-mb thickness forecasts over the RDCs. However, the NGM showed exceptional skill in correctly forecasting the sign of the 12-h pressure change for the RDCs. During the three winter seasons the NGM rarely misforecast the sign of the 12-h forecast pressure change during rapid cyclogenesis.

Over the western Atlantic the NGM was too slow to move the RDCs to the east The overall position errors for RDCs were approximately 10% smaller than the position errors for all cyclones in the NGM at all forecast periods.

An examination of two RDC events revealed significant differences in the NGM's ability to forecast the rapid deepening. During the ERICA IOP 4 cyclone, the NGM forecast the cyclone fairly well, showing its bias of being too slow to deepen the RDCs and too slow to move it eastward. Much poorer skill in forecasting the 4 January 1992 cyclone off the coast of the Carolinas occurred with the NGM having significant problems resolving subgrid-scale processes as the storm deepened rapidly as it crossed the warm Gulf Stream waters.

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Richard H. Grumm and Anthony L. Siebers

Abstract

Preliminary results from a study examining the performance of the nested grid model (NGM) in predicting cyclones covering a period from 13 November 1988 to 31 Match 1989 reveal that the NGM tends to overdevelop surface cyclones over continental regimes and underdevelop surface cyclones in oceanic regimes. The results also indicate an overall cold bias in the model forecasts of thickness and 850 mb temperatures over the cyclone center. Displacement error data indicate the NGM tends to move cyclones too slowly in the southern half of the forecast domain.

A semiautomated method has been developed at the National Meteorological Center (NMC) to track and verify sea level pressure features in the NGM. The method allows the user to interactively track a system, store its coordinates, and then retrieve information about the system from selected model forecast and analysis grids. This information can then be used to determine systematic forecast errors, compare past forecasts with the most recent forecast, and produce climatological tracks of forecast and observed systems.

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