Arid
DOI10.1016/j.agrformet.2020.108306
An improved method to estimate actual vapor pressure without relative humidity data
Qiu, Rangjian; Li, Longan; Kang, Shaozhong; Liu, Chunwei; Wang, Zhenchang; Cajucom, Edward P.; Zhang, Baozhong; Agathokleous, Evgenios
通讯作者Qiu, RJ (corresponding author), Nanjing Univ Informat Sci & Technol, Sch Appl Meteorol, Jiangsu Key Lab Agr Meteorol, Nanjing 210044, Peoples R China.
来源期刊AGRICULTURAL AND FOREST METEOROLOGY
ISSN0168-1923
EISSN1873-2240
出版年2021
卷号298
英文摘要Estimating actual vapor pressure (e(a)) without relative humidity (RH) data continues to draw research attention. One of the accurate ways to estimate e(a) is through estimation of dew point temperature (T-dew) from minimum (T-min) or mean temperature (T-mean). Two existing methods have been largely used to estimate e(a). The first method (method I) assumes that T-dew is close to T-min. The other one (method II) adjusts T-dew from T-min with piecewise correction factors (a(T)) from sub-humid to hyper arid regions, and from T-mean with a fixed correction factor, a(D), in humid regions. Here, two methods are proposed to estimate e(a). The first method (method III) adjusts T-dew from T-min with dynamic a(T) based on the correlation function between a(T) and aridity index (AI) regardless of climate zones. The second method (method IV) adjusts T-dew from T-min with dynamic a(T) when AI < 1.00 and from T-mean with a(D) when AI >= 1.00. The performance of four methods was evaluated based on data from 886 meteorological stations distributed from hyper-arid to humid regions. Results showed that there was a significant logarithmic correlation function between a(T) and AI, but no significant correlation between a(T) and AI. Daily values of e(a) estimated by method I were greatly overestimated in semi-arid to hyper-arid regions, but were reasonably estimated in humid regions. The accuracy of method II was improved in hyper-arid to dry sub-humid regions but decreased in humid regions, compared to method I. The proposed methods (III and IV) further improved the accuracy and produced reasonable estimation of daily e(a) in hyper-arid to humid regions, and method III produced a slightly better performance than method IV. Similar results were also observed for estimation of monthly e(a). Therefore, the proposed method III is highly recommended to estimate daily and monthly e(a) when RH data are unavailable.
英文关键词Aridity index Dew point temperature Dynamic correction factor Limited data Relative humidity
类型Article
语种英语
收录类别SCI-E
WOS记录号WOS:000610797100021
WOS关键词DAILY REFERENCE EVAPOTRANSPIRATION ; LIMITED DATA ; TEMPERATURE ; MODEL ; CLIMATES ; ETO
WOS类目Agronomy ; Forestry ; Meteorology & Atmospheric Sciences
WOS研究方向Agriculture ; Forestry ; Meteorology & Atmospheric Sciences
来源机构中国农业大学 ; 南京信息工程大学 ; 河海大学
资源类型期刊论文
条目标识符http://119.78.100.177/qdio/handle/2XILL650/347622
作者单位[Qiu, Rangjian; Li, Longan; Liu, Chunwei; Agathokleous, Evgenios] Nanjing Univ Informat Sci & Technol, Sch Appl Meteorol, Jiangsu Key Lab Agr Meteorol, Nanjing 210044, Peoples R China; [Kang, Shaozhong] China Agr Univ, Ctr Agr Water Res China, Beijing 100083, Peoples R China; [Wang, Zhenchang] Hohai Univ, Coll Water Conservancy & Hydropower Engn, Nanjing 210098, Peoples R China; [Cajucom, Edward P.] Geophys & Astron Serv Adm DOST PAGASA, Dept Sci & Technol Philippine Atmospher, Quezon City 1100, Philippines; [Zhang, Baozhong] China Inst Water Resources & Hydropower Res, State Key Lab Simulat & Regulat Water Cycle River, Beijing 100038, Peoples R China
推荐引用方式
GB/T 7714
Qiu, Rangjian,Li, Longan,Kang, Shaozhong,et al. An improved method to estimate actual vapor pressure without relative humidity data[J]. 中国农业大学, 南京信息工程大学, 河海大学,2021,298.
APA Qiu, Rangjian.,Li, Longan.,Kang, Shaozhong.,Liu, Chunwei.,Wang, Zhenchang.,...&Agathokleous, Evgenios.(2021).An improved method to estimate actual vapor pressure without relative humidity data.AGRICULTURAL AND FOREST METEOROLOGY,298.
MLA Qiu, Rangjian,et al."An improved method to estimate actual vapor pressure without relative humidity data".AGRICULTURAL AND FOREST METEOROLOGY 298(2021).
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