Thunderstorm predictors and their forecast skill for the Netherlands

Haklander, Alwin J.; Delden, Aarnout van

doi:10.1016/s0169-8095(03)00056-5

Cited by 166 publications

(138 citation statements)

References 17 publications

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“…CAPE values less than 300 J kg −1 show little or no convective potential, and CIN values greater than 200 J kg −1 are sufficient to prevent convection (Knutsvig, 2009). Haklander et al (2003) examined 32 different indices and parameters, especially in the Netherlands, to gain statistical information on these parameters and compare their ability to forecast thunderstorms. Haklander and Delton (2003) have estimated the probability of a thunderstorm as a function of various thunderstorm predictors.…”

Section: Introductionmentioning

confidence: 99%

“…Haklander et al (2003) examined 32 different indices and parameters, especially in the Netherlands, to gain statistical information on these parameters and compare their ability to forecast thunderstorms. Haklander and Delton (2003) have estimated the probability of a thunderstorm as a function of various thunderstorm predictors. They found that the thunderstorm probability depends on the following parameters (in order of importance): latent instability (especially near the surface), potential instability and conditional instability.…”

Section: Introductionmentioning

confidence: 99%

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Instability indices and forecasting thunderstorms: the case of 30 April 2009

Tajbakhsh

Ghafarian

Sahraian

2012

Nat. Hazards Earth Syst. Sci.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Instability indices and forecasting thunderstorms: the case of 30 April 2009

Tajbakhsh

Ghafarian

Sahraian

2012

Nat. Hazards Earth Syst. Sci.

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“…These so-called convective parameters and indices reflect the potential for thunderstorm development according to the prevailing properties of the air mass. In many studies, the efficiency of the various indices derived from the observed vertical profiles for thunderstorm prediction was investigated, for example by Schulz (1989), Lee and Passner (1993), Fuelberg and Biggar (1994), Huntrieser et al (1997), Haklander and Van Delden (2003), and Manzato (2005). However, little attention has been paid so far to the index-based prediction of severe thunderstorms.…”

Section: Introductionmentioning

confidence: 99%

The skill of convective parameters and indices to predict isolated and severe thunderstorms

Kunz¹

2007

Nat. Hazards Earth Syst. Sci.

160

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Abstract. The preconvective environment on days with ordinary, widespread, and severe thunderstorms in Southwest Germany was investigated. Various thermodynamic and kinetic parameters calculated from radiosoundings at 12:00 UTC were verified against subsequent thunderstorm observations derived from SYNOP station data, radar data, and damage reports of a building insurance company. The skill of the convective parameters and indices to predict thunderstorms was evaluated by means of probability distribution functions, probabilities of thunderstorms according to an index threshold, and skill scores like the Heidke Skill Score (HSS) that are based on categorical verification.For the ordinary decision as to whether a thunderstorm day was expected or not, the best results were obtained with the original Lifted Index (80% prediction probability for LI≤−1.73; HSS=0.57 for LI≤1.76), the Showalter Index, and the modified K-Index. Considering days with isolated compared to widespread thunderstorms, the best performance is reached by the Deep Convective Index. For days with severe thunderstorms that caused damage due to hail, local storms or floods, the best prediction skill is found again for the Lifted Index and the Deep Convective Index, but also for the Potential Instability Index, the Delta-θ e Index, and a version of the CAPE, where the lifting profile is determined by averaging over the lowest 100 hPa.

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“…On the other hand, the Heidke Skill Score takes into account correct detections that were not due to chance and is thus more appropriate in the case where rare events can occur. Haklander and Van Delden [2003] have taken this a step further and combined the best of the two skill scores to formulate a normalized skill score (NSS). NSS is defined as…”

Section: 1002/2016ea000168mentioning

confidence: 99%

A method for automated snow avalanche debris detection through use of synthetic aperture radar (SAR) imaging

Vickers

Eckerstorfer

Malnes

et al. 2016

Earth and Space Science

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Avalanches are a natural hazard that occur in mountainous regions of Troms County in northern Norway during winter and can cause loss of human life and damage to infrastructure. Knowledge of when and where they occur especially in remote, high mountain areas is often lacking due to difficult access. However, complete, spatiotemporal avalanche activity data sets are important for accurate avalanche forecasting, as well as for deeper understanding of the link between avalanche occurrences and the triggering snowpack and meteorological factors. It is therefore desirable to develop a technique that enables active mapping and monitoring of avalanches over an entire winter. Avalanche debris can be observed remotely over large spatial areas, under all weather and light conditions by synthetic aperture radar (SAR) satellites. The recently launched Sentinel-1A satellite acquires SAR images covering the entire Troms County with frequent updates. By focusing on a case study from New Year 2015 we use Sentinel-1A images to develop an automated avalanche debris detection algorithm that utilizes change detection and unsupervised object classification methods. We compare our results with manually identified avalanche debris and field-based images to quantify the algorithm accuracy. Our results indicate that a correct detection rate of over 60% can be achieved, which is sensitive to several algorithm parameters that may need revising. With further development and refinement of the algorithm, we believe that this method could play an effective role in future operational monitoring of avalanches within Troms and has potential application in avalanche forecasting areas worldwide.

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Thunderstorm predictors and their forecast skill for the Netherlands

Cited by 166 publications

References 17 publications

Instability indices and forecasting thunderstorms: the case of 30 April 2009

Instability indices and forecasting thunderstorms: the case of 30 April 2009

The skill of convective parameters and indices to predict isolated and severe thunderstorms

A method for automated snow avalanche debris detection through use of synthetic aperture radar (SAR) imaging

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