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Enregistrement W6963713872 · doi:10.22111/gdij.2012.321

Temporal and Spatial Analysis of Hail in IranDr. Manuchehr Farajzadeh Associated Professor of Remote SensingUniversity of Tarbiat ModaresTaher MostafapoorM. Sc of ClimatologyUniversity of Tarbiat Modares

2012· article· en· W6963713872 sur OpenAlexaboutno aff

Notice bibliographique

RevueDOAJ (DOAJ: Directory of Open Access Journals) · 2012
Typearticle
Langueen
DomaineEarth and Planetary Sciences
ThématiqueMeteorological Phenomena and Simulations
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésThunderstormDamagesStatistical analysisSpatial distributionTornadoAgriculture

Résumé

récupéré en direct d'OpenAlex

Introduction Hail is one of the most important climatic hazards in the world and Iran. Hail is a phenomena related to thunderstorm which occurrs in unstable atmosphere with high level of moisture. Hail damages human and agricultural products. The damage of hail is serious in comparing with tornadoes and storms. Most of these damages occurrs in agriculture sector and on the crops, so that sometimes all the annual crops are destroyed in a few minutes. Iran has a mountainous condition in Alborz and Zageos area that in association with climatic system creates a suitable area for hail occurrence. In order to prevent the damages of hail, it is necessary to study the frequency and other climatic features. In this study, the temporal and spatial distributions of hail have been investigated in Iran. Data and Method The present study has concentrated on the observation data from 67 synoptic stations of a 20-years period (1986-2005), and the spatial distribution has been demonstrated on the country map. In this research, the analyses have been performed by statistical method. At first, the data collected through statistical tests, were examined and then the related data base has been created.the next process was the extract of frequencies for each station, which is performed by SPSS software. After that the calculated frequencies has been entered in to GIS software (ArcGIS) frequency mapshas been prepared and analyzed. Discussion and Results The prepared geographical distribution maps indicate the frequency concentration in Iran. Maximum amount of frequency is 4.7 which has been recorded on northern, western and eastern stations of Ilam and other stations are Abali with the average of 4.3 and Maragheh station with an annual mean of 3.2. Regarding the hail seasonal distribution, the highest amount is recorded in spring in which the highest frequency of 1.7 has been recorded for Abali weather station. After spring, the second one is winter which is recorded for Ilam of about 2.5. Autumn and summer have the low frequency so that in most stations, the hail precipitation in summer is zero and in autumn it reaches to 0.1. The monthly distribution of hail precipitation belongs to March, April and May months. The highest frequencies of hail occurred in March with 22 cases and April and December with 21 cases which recorded for Ilam and Abali weather stations. Regarding the hourly distribution of hail, the highest amount of hail is recorded between 6 am to 15 pm on Greenwich Time (9:30 am to 18:30 pm for local time). The analysis indicated that distribution of hail occurrence in Iran as a common phenomenon has not been the same for all the regions but it mainly occurres in special regions. It is entirely due to the climatic changes and topography conditions, because the condition for unstable atmospheric systems is suitable for the occurrence of hail. The temporal conditions for occurrence of this phenomenon are on late March and early April. In that time of year, the whole country is influenced by Mediterranean systems moving from west. During this time the temperature difference in plains and mountain regions covered with snow and the topographical condition of main regions which hail is occurred, an increase in temperature can be obsereved. Moreover, the hail occurrence especially at early hours in the afternoon, in which the temperatures difference between the mountain and plain regions is significant is probably one of the reasons of hail occurrence in this time of a day. Conclusion The analysis shows that hail is concentrated on east ranges of Zagros extending toward north west of Iran on a direct line to the boarders of Ilam province and also concentrated on the southern parts of central Alborz range, from this point to the southern parts of the country, the hail frequency is decreased and in some stations located in the southern parts of Iran, the hail is almost zero. There are two weather stations in the eastern parts of the country namely Birjand and Torbatheydarye where a higher level of hail is recorded in comparing to the other parts of the country probably due to high altitudes such as Qayenat Mountain ranges and Birjand. Keywords: Hail - Hailstorm- Thunderstorm- Temporal and spatial distribution- Iran. References 1- AbdeManafi, Dina (2004). The study of erratic indicators, wind right angle cut and the situation of moisture at the time of hail precipitation, an M.A thesis, Tehran university. 2- Alizadeh, Amin (2006). The principles of applied hydrology, Astane Ghodse Razavi Publications. 3- AminiLeyla et al ( 2003). The study of synoptic-thermodynamic of hail precipitation in Isfahan province, 11th conference on geophysics of Iran. 4- Charles, A. & Doswell, C,A (1993). Scientific Approaches for very short range forecasting of severe convective storms in the united state of America. 5- Etkin, David & Erik Brun (2001). Canada’s Hail Climatology:1977-1993, LCLR Research, No 14. 6- Ezatyan Victoria (2003). Physic processes in increasing the atmosphere disorders, 11th conference of geophysics. 7- Temporal and Spatial Analysis of Hail in Iran Frisby, E.m (1961). Relationship of ground hail damage patterns to features of synoptic map in the upper Great plain of the united state. J.Appl. meteorology. No1. 8- Giaiotti, Dario &etc (2003). The climatology of hail in the plain of Friuli Venezia Giulia , Atmospheric Research ,No 67 -68. 9- Huff, f.a (1964). correlation Between summer hail patterns in Illinois and Associated climatological events, Journal of Applied meteorology, No 3. 10- Kawyani, Mohammadreza&Alijani,Behlool (2006). The principles of Climatology. 11- Qorbani,Azam (2006). the analysis and study of hail phenomenon and cloud classification using GIS and RS in Zayande Rood basin, an M.A thesis, the university of Tarbyat Moalem. 12- Mir Moosavi, SayedHoseyn & Akbarzadeh, Yunes (2009).The study of disorder indicators in forming hail at Tabriza aerology station, FazayeJoghrafyayi, NO9-25, 105, 95. 13- Mir Musavi, SeyedHoseyn & Akbarzade, Yunes (2009). applying poacen and negative functions in evaluating the occurrence possibilities of hail precipitation (case study): East Azerbaijan province, geography and environmental planning (the university of Isfahan scientific magazine) NO 36,73,84. 14- Saanayi, Bahram et al (2003).The study of hail statistic models in Iran, Niwar Journal,48and 49. 15- Seyf, Mehrzad (1996). The study of the distribution of hail precipitation in Iran and its case study, a thesis for getting M.A degree, Tehran university. 16- Sioutas,M. & Flocas, Ha (2004). Hailstorms in northern Greece: synoptic patterns and thermodynamic environment, Applied Climatology, No 75. 17- "The study of avalanche phenomenon, gale and hail in different regions of Iran", third report, volume one, determining the potentials of climate disasters in Iran. 18- Vinet, Freddy (2001). Climatology of hail in France, Atmospheric Research, No 56. 19- Weorer, john & Lindsey, d (2004). Some overlooked severe Thunderstorms Characteristic observed.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,001
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,020
Score d'incertitude au seuil0,040

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0000,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0010,002
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,195
Tête enseignante GPT0,453
Écart entre enseignants0,258 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2012
Routes d'admission1
Résumé présentoui

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