Two to Six Hour Severe Local Storm Probabilities: An Operational Forecasting System

Charba, Jerome P.

doi:10.1175/1520-0493(1979)107<0268:ttshsl>2.0.co;2

Cited by 33 publications

(21 citation statements)

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“…In a different effort, surface MFC and its time tendency were included in screening regression procedures (Charba 1975) for the development of an objective severe weather forecast method devised by the Techniques Development Laboratory (TDL) and transmitted to NSSFC and local NWS offices beginning in May 1972. Interestingly, surface MFC was typically the top predictor selected in 1974 and 1975 versions of the regression equations that forecasted severe-storm report location (Charba 1975).…”

Section: Application Of Mfc To Midlatitude Convectionmentioning

confidence: 99%

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The Use of Moisture Flux Convergence in Forecasting Convective Initiation: Historical and Operational Perspectives

Banacos¹,

Schultz

2005

Weather and Forecasting

257

171

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Moisture flux convergence (MFC) is a term in the conservation of water vapor equation and was first calculated in the 1950s and 1960s as a vertically integrated quantity to predict rainfall associated with synoptic-scale systems. Vertically integrated MFC was also incorporated into the Kuo cumulus parameterization scheme for the Tropics. MFC was eventually suggested for use in forecasting convective initiation in the midlatitudes in 1970, but practical MFC usage quickly evolved to include only surface data, owing to the higher spatial and temporal resolution of surface observations. Since then, surface MFC has been widely applied as a short-term (0-3 h) prognostic quantity for forecasting convective initiation, with an emphasis on determining the favorable spatial location(s) for such development.A scale analysis shows that surface MFC is directly proportional to the horizontal mass convergence field, allowing MFC to be highly effective in highlighting mesoscale boundaries between different air masses near the earth's surface that can be resolved by surface data and appropriate grid spacing in gridded analyses and numerical models. However, the effectiveness of boundaries in generating deep moist convection is influenced by many factors, including the depth of the vertical circulation along the boundary and the presence of convective available potential energy (CAPE) and convective inhibition (CIN) near the boundary. Moreover, lower-and upper-tropospheric jets, frontogenesis, and other forcing mechanisms may produce horizontal mass convergence above the surface, providing the necessary lift to bring elevated parcels to their level of free convection without connection to the boundary layer. Case examples elucidate these points as a context for applying horizontal mass convergence for convective initiation. Because horizontal mass convergence is a more appropriate diagnostic in an ingredients-based methodology for forecasting convective initiation, its use is recommended over MFC.

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Section: Application Of Mfc To Midlatitude Convectionmentioning

confidence: 99%

“…Interestingly, surface MFC was typically the top predictor selected in 1974 and 1975 versions of the regression equations that forecasted severe-storm report location (Charba 1975).…”

Section: Application Of Mfc To Midlatitude Convectionmentioning

confidence: 99%

The Use of Moisture Flux Convergence in Forecasting Convective Initiation: Historical and Operational Perspectives

Banacos¹,

Schultz

2005

Weather and Forecasting

257

171

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“…Stability threshold : > 28°( h) Modified K index (Charba, 1979) Modified K index = (T --T 500 ) + T (Curtis & Panofsky, 1958) Modified Showalter index = T 500 -T pm 500 where T pm 500 is the temperature of a parcel lifted dry adiabatically from 850 hPa to its condensation level and then lifted moist adiabatically up to 500 hPa. The initial parcel has the mean moisture content of the 850-500 hPa layer.…”

Section: Discussionmentioning

confidence: 99%

“…(l) Modified Total Totals (Charba, 1979) Modified Total Totals = T -+ T -d -2T 500 see the Modified K index for notation.…”

Section: Stability Threshold: > 70%mentioning

confidence: 99%

Diagnostic tools using a mesoscale NWP model for the early warning of convection

1998

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A mesoscale numerical weather prediction model and its associated diagnostics are evaluated to gauge their ability to forecast convection and the convective environment for ten case‐study days. The diagnostic indices and parameters evaluated are those used to assess atmospheric instability, mesoscale forcing, inhibition and low‐level moisture supply. In addition, bulk Richardson number and helicity diagnostics are examined for convection organisation. Convection over mountainous regions is not considered. The case‐study days are grouped according to their synoptic type in order to evaluate the usefulness of the forecast diagnostics. In the evaluation it is found that by combining the CAPE (convective available potential energy) and low‐level relative humidity diagnostics one can delineate quite large areas where convective triggering is possible and outside which convection will not develop. Organisation of the mesoscale convective systems is also considered. It is found that forecast strong low‐level shears tend to be well correlated with observed linear convective systems. A set of stability indices are evaluated quantitatively and qualitatively by comparing the forecast stability indices with observations at a sounding location. CAPE and a simple index based on a moist temperature difference between two layers (Adedokun2) are identified as the most useful forecast stability indices for all of the cases. Copyright © 1998 Royal Meteorological Society

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“…Various studies have used statistical regression equations for this purpose, which by combining a number of indexes increase predictability to more than that by use of each index individually. It is important to note that coefficients of these indexes in an equation are dependent on the geographic location and the season (Charba, 1979;Hughes, 2004;Sánchez et al, 2009). The same equation cannot be applied to a region without first validating it using real data.…”

Section: Introductionmentioning

confidence: 99%

Spatial distribution of thermodynamic conditions of severe storms in southwestern Europe

Gascón

Merino

Sánchez

et al. 2015

Atmospheric Research

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Two to Six Hour Severe Local Storm Probabilities: An Operational Forecasting System

Cited by 33 publications

References 0 publications

The Use of Moisture Flux Convergence in Forecasting Convective Initiation: Historical and Operational Perspectives

The Use of Moisture Flux Convergence in Forecasting Convective Initiation: Historical and Operational Perspectives

Diagnostic tools using a mesoscale NWP model for the early warning of convection

Spatial distribution of thermodynamic conditions of severe storms in southwestern Europe

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