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_D 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.

_在没有相对湿度（RH）数据的情况下估计实际蒸气压（e _a）继续引起研究关注。之一来估计准确的方法Ë_一个是通过露点温度（估计Ť_露水从最小值（）Ť_分钟）或平均温度（Ť_平均值）。现有的两种方法已被广泛用于估计e _a。第一种方法（方法I）假设T _dew接近T _min。另一个（方法II）从T _min调整T_露在半湿润地区到高干旱地区使用分段校正因子（a _T），在湿润地区使用T_表示校正因子为_D的固定值。在此，提出了两种估计e _a的方法。第一种方法（方法III）调整Ť_露水从Ť_分钟使用动态一个_Ť基于之间的相关函数一个_Ť并且无论气候区的干燥指数（AI）。第二种方法（方法IV）利用动态A _T从T _min调整T_露水当AI <1.00和从Ť_平均值与一个_d时AI≥1.00。根据从886个气象站（从高干旱地区到潮湿地区）的数据评估了四种方法的性能。结果表明，有之间的对数显著相关函数一个_Ť和AI，但之间没有显著相关一个_d和AI。e _a的每日值通过方法I估算的值在半干旱至高干旱地区被大大高估，但在潮湿地区则被合理估算。与方法I相比，方法II的准确性在高干旱至半湿润地区有所提高，但在潮湿区域却有所降低。所提出的方法（III和IV）进一步提高了准确性，并合理估计_了在高湿度下的每日e _a -在潮湿地区，方法III的性能比方法IV略好。每月e _a的估计也观察到类似的结果。因此，强烈建议在没有RH数据的情况下，建议的方法III估计每日和每月e _a。