INCREASE OF PRECIPITATION WITH ALTITUDE<sup>1</sup>

Henry, Alfred J.

doi:10.1175/1520-0493(1919)47<33:iopwa>2.0.co;2

Cited by 28 publications

(25 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…On a global average, temperature decreases 6.5°C per 1000 m increase in altitude (Lutgens & Tarbuck 1995), although this rate varies with location and season. Precipitation usually increases with elevation (Henry 1919, Varney 1920, Hevesi et al 1992, Daly et al 1994, but the rate of increase varies substantially, depending on factors that affect the amount of moisture in the air, such as rain shadows or the distance from large water bodies (Schermerhorn 1967, Dingman 1981, Daly et al 1994.…”

Section: Introductionmentioning

confidence: 99%

Mapping monthly precipitation, temperature, and solar radiation for Ireland with polynomial regression and a digital elevation model

Goodale¹,

Aber²,

Ollinger³

1998

Clim. Res.

146

View full text Add to dashboard Cite

A 1 km 2 resolution digital elevation model (DEM) of Ireland was constructed and used as the basis for generating digital maps of the climate parameters required to run a model of ecosystem carbon and water cycling. The DEM had mean absolute errors of 30 m or less for most of Ireland. The ecosystem model requires inputs of monthly precipitation, monthly averaged maximum and minimum daily temperature, and monthly averaged daily solar radiation. Long-term (1951Long-term ( to 1980 averaged monthly data were obtained from sites measuring precipitation (618 sites), temperature (62 sites), and the number of hours of bright sunshine per day ('sunshine hours') (61 sites). Polynomial regression was used to derive a simple model for each monthly climate variable to relate climate to position and elevation on the DEM. Accuracy assessments with subsets of each climate data set determined that polynomial regression can predict average monthly climate in Ireland with mean absolute errors of 5 to 15 mm for monthly precipitation, 0.2 to 0.5°C for monthly averaged maximum and minimum temperature, and 6 to 15 min for monthly averaged sunshine hours. The polynomial regression estimates of climate were compared with estimates from a modified inverse-distance-squared interpolation. Prediction accuracy did not differ between the 2 methods, but the polynomial regression models demanded less time to generate and less computer storage space, greatly decreasing the time required for regional modeling runs.

show abstract

Section: Introductionmentioning

confidence: 99%

Mapping monthly precipitation, temperature, and solar radiation for Ireland with polynomial regression and a digital elevation model

Goodale¹,

Aber²,

Ollinger³

1998

Clim. Res.

146

View full text Add to dashboard Cite

show abstract

“…The orographic effect may be the reason to increase the parameters A in the high altitude zone. The rainfall intensity can be increased due to the ascending air current following the mountain slopes, which can also be strengthened when the humidity and wind velocity are all high [26][27][28][29][30][31].…”

Section: Parameter Estimation Of Z-r Relationmentioning

confidence: 99%

Calibrating Radar Data in an Orographic Setting: A Case Study for the Typhoon Nakri in the Hallasan Mountain, Korea

Yoo

2017

Atmosphere

View full text Add to dashboard Cite

Abstract:The Typhoon Nakri passed the Jeju Island in Korea (1-3 August 2014) and recorded one-day rainfall of 1182 mm at Witse-Oreum (a place name where a small volcanic cone is) of the Hallasan Mountain, Korea. This one-day rainfall amount was the highest rainfall that was ever recorded in Korea. As the altitude of Witse-Oreum is 1673 m, it was believed that the orographic effect enhanced the rainfall depth significantly. It was also argued that the maximum rainfall could be recorded in some other locations in the Hallasan Mountain. In this study, the rainfall event due to the Typhoon Nakri in the Jeju Island was analyzed using the radar and rain gauge data that were collected during this rainfall event. Fortunately, two radars are available on the eastern and western side of the Jeju Island. The entire Hallasan Mountain is covered by these two radars. A total of 23 rain gauges are also available in the Jeju Island. As a first step, independent ground-level Z-R relations were derived for every 250 m interval from the sea-level. Each Z-R relation was then applied to the corresponding-altitude radar reflectivity data to generate the rain rate field over the Jeju Island. Finally, the generated radar rain rate data were examined fully to evaluate the orographic effect in the Hallasan Mountain, also to locate the point where the maximum rain rate was recorded. This result shows that the maximum one-day rainfall amount could be up to 1500 mm, which was about 30% higher than the rain gauge measurement.

show abstract

“…Yağışın düşmeye başladığı bu sınır oldukça değişkendir. Heney (1919) maksimum yağış kuşağının enleme bağlı olarak değiştiğini tropiklerde bu sınırın 1000 m altına inerken ılıman kuşakta en yüksek seviyeye eriştiğini ve ılıman kuşakta bu sınırın 1400-1500 civarında olduğunu belirtmektedir. Bu sınırın Kayalık Dağları ve Alp Dağları'nda 3000-4000 m'den, tropikal bölgelerde 1000-2000 metrelerden geçtiği belirtilmektedir (Barry ve Chorkey 2003, Erinç 1984.…”

Section: Veri Ve Metodolojiunclassified

Türkiye’nin Su Potansiyelinin Belirlenmesinde Yeni Bir Yaklaşım

Çiçek¹,

Ataol²

2009

View full text Add to dashboard Cite

Öz: Türkiye'de meteorolojik gözlemler Devlet Meteoroloji İşleri Genel Müdürlüğü (DMİ) ve Devlet Su İşleri Genel Müdürlüğü (DSİ) tarafından gerçekleştirilmektedir. Ancak farklı amaçlarla ölçüm yapan bu iki kurumun yayınlarında, yıllık ortalama yağış tutarlarında farklılıklar görülmektedir. Türkiye'nin yıllık ortalama yağış tutarını DMİ 626.6 mm (1971-2000 ortalaması), DSİ ise 643 mm olarak hesaplamaktadır. DSİ bu ortalama yağış tutarını temel alarak Türkiye'ye düşen toplam yağış miktarını ve buna göre de su potansiyelini hesaplamaktadır. Bu çalışmada DMİ tarafından işletilen 252 istasyonun uzun yıllık ortalama yağış tutarları hesaplanmış ve Türkiye'nin topografyası dikkate alınarak Coğrafi Bilgi Sistemleri (CBS) yardımı ile yeni bir yağış dağılış haritası yapılmıştır. Gerek tüm ülkenin gerekse 26 yağış havzasının yıllık ortalama yağış tutarları hesap edilerek su potansiyelleri yeniden belirlenmiştir. Bu yeni hesaba göre Türkiye'nin yıllık ortalama yağış tutarı 727 mm, toplam yağışı 567 milyar m 3 olarak bulunmuştur. Bu değerler DSİ'nin yıllık ortalama yağış tutarından 84 mm, yıllık toplam yağış tutarından 66 milyar m 3 daha fazladır. Buna göre Türkiye'nin yıllık kullanılabilir su potansiyel 112 milyar m 3 'ten 127 milyar m 3 'e çıkmaktadır Anahtar Kelimeler: Türkiye, yıllık yağış ortalaması, yıllık su potansiyeli, akarsu havzası Abstract: In Turkey, meteorological observations are performed by State Meteorological Service (SMS), General Directorate of State Hydraulic Works (SHW). These two state organizations perform the measurements for different purposes. The annual average precipitation amount calculated and published by these organizations are different. Turkey's annual average precipitation for period of the 1971-2000 was calculated as 624.6 mm by SMS and 643 mm by SHW. Based on this annual average precipitation, SHW calculates the water potential of Turkey. In this study, using the data recorded by SMS at 252 stations, the annual average precipitation amounts have been calculated by utilizing the Geographic Information Systems (GIS) considering the topography of Turkey, and a new precipitation distribution map was formed the water potential of Turkey was determined calculating the annual average precipitation of whole country and 26 different ,precipitation basins. Based on these new calculation, the annual average precipitation amount of Turkey was found as 727 mm, and the total annual precipitation amount was found as 567 billion cubic meter. These values are different from the values calculated by SHW. The annual average precipitation of 84 mm and the total annual precipitation of 66 billion cubic meter calculated in this study are higher than that are calculated by SHW. According to this new calculation, the annual useable water potential of Turkey is 127 billion cubic meter. SHW calculates the annual useable water potential as 112 million cubic meters.

show abstract

INCREASE OF PRECIPITATION WITH ALTITUDE¹

Cited by 28 publications

References 0 publications

Mapping monthly precipitation, temperature, and solar radiation for Ireland with polynomial regression and a digital elevation model

Mapping monthly precipitation, temperature, and solar radiation for Ireland with polynomial regression and a digital elevation model

Calibrating Radar Data in an Orographic Setting: A Case Study for the Typhoon Nakri in the Hallasan Mountain, Korea

Türkiye’nin Su Potansiyelinin Belirlenmesinde Yeni Bir Yaklaşım

Contact Info

Product

Resources

About

INCREASE OF PRECIPITATION WITH ALTITUDE1

Cited by 28 publications

References 0 publications

Mapping monthly precipitation, temperature, and solar radiation for Ireland with polynomial regression and a digital elevation model

Mapping monthly precipitation, temperature, and solar radiation for Ireland with polynomial regression and a digital elevation model

Calibrating Radar Data in an Orographic Setting: A Case Study for the Typhoon Nakri in the Hallasan Mountain, Korea

Türkiye’nin Su Potansiyelinin Belirlenmesinde Yeni Bir Yaklaşım

Contact Info

Product

Resources

About

INCREASE OF PRECIPITATION WITH ALTITUDE¹