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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

A quantitative assessment has been made of the surface anticyclone forecast errors found in the operational nested grid model (NGM) run at the National Meteorological Center (NMC). Preliminary results covering a period from 1 December 1988 to 31 August 1989 reveal that the NGM predicts the central pressure of surface anticyclones to be too low over much of central and eastern North America during the winter and spring, especially along the track of transient anticyclones. The NGM tends to predict surface anticyclone pressure to be too high over the eastern Pacific and portions of the western Atlantic during winter, spring and summer. Pressure errors grow by forecast length and season. The 48-h forecast errors are larger in magnitude and better defined than the 24-h forecasts. The winter and spring pressure errors are better organized and have larger magnitudes than in summer.

Thickness (1000–500 mb) errors over the anticyclone center indicate an overall warm bias, especially over the North American continent and the adjacent western Atlantic Ocean, where anticyclones tend to be transient. Areas of negative thickness errors (cold bias) are found over the oceans and the elevated terrain of western North America. In general, the model places surface anticyclones too far south and east of the verifying position in the colder months.

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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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Neil A. Stuart and Richard H. Grumm

Abstract

Forecasting major winter storms is a critical function for all weather services. Conventional model-derived fields from numerical weather prediction models most frequently utilized by operational forecasters, such as pressure level geopotential height, temperature fields, quantitative precipitation forecasts, and model output statistics, are often insufficient to determine whether a winter storm represents a large departure from normal, or has the potential to produce significant snowfall. This paper presents a method, using normalized departures from climatology, to assist forecasters in identifying long-duration and potentially significant winter storms. The focus of this paper is on anomalous low- and upper-level wind anomalies associated with winter storms along the U.S. east coast.

Observed and forecast low-level (850 hPa) and upper-level (300 and 250 hPa) easterly wind anomalies are compared with a 30-yr (1961–90) reanalysis climatology. Anomalous easterly low-level winds are correlated with enhanced low-level forcing and frontogenesis. Strong low-level winds can also contribute to enhanced precipitation rates. Upper-level winds that are anomalously below normal, represented as easterly wind anomalies, are also correlated with systems that are cut off from the main belt of westerlies, which may result in slower movement of the system, leading to long-duration events. The proposed method of evaluating easterly wind anomalies is shown to assist in identifying potentially slow-moving storms with extended periods of enhanced precipitation.

To illustrate this method, winter storms on 25–26 December 2002 and 2–4 January 2003 will be compared with past historical winter storms. The results suggest that the low- and upper-level wind anomalies in the two recent snowstorms share common characteristics with several record snowstorms over the past 52 yr. Many of these storms were associated with easterly wind anomalies that departed significantly (2 or more standard deviations) from normal. The examination of climatic anomalies from model forecasts may assist forecasters in identifying significant winter storms in the short range (2–3 days) and potentially out to ranges as long as 7 days when ensemble forecast guidance is utilized.

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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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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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