SPWV-H: A Spatially-enhanced Vertical Adjustment Model for Global Precipitable Water Vapor

<b>SPWV-H</b> is a MATLAB-based computational model designed for estimating global precipitable water vapor (PWV) based on a spatially-enhanced vertical adjustment approach. The model interpolates PWV values from surface grid data, accounting for height-dependent variations and geographic location. By integrating both exponential interpolation and cubic polynomial adjustments, this model allows for accurate estimations of PWV across different altitudes and latitudes.Key Features:<b>Grid-based Interpolation</b>: The model uses surface grid data from three distinct datasets (SPWV-H1, SPWV-H2, SPWV-H3) to estimate PWV values.<b>Vertical Adjustment</b>: Implements an exponential model for height-based interpolation and applies a cubic polynomial correction for low-latitude regions where no land is present.<b>Fourier-based Time Variability</b>: The model incorporates Fourier terms based on the day of year (DOY) to account for annual and semi-annual PWV cycles, making it suitable for time-series analysis.<b>Geographic Flexibility</b>: PWV estimates are adjusted for different geographic regions, with special consideration for low-latitude zones (between -30° and 30° latitude).Applications:<b>Climate Studies</b>: Useful for analyzing water vapor variations over time and space, especially in the context of climate change and atmospheric water cycle studies.<b>Weather and Climate Modeling</b>: Enhances numerical weather prediction models by providing accurate vertical PWV profiles.<b>Hydrological Studies</b>: Can be used to estimate water vapor contributions to precipitation and soil moisture in regional hydrological models.Requirements:<b>MATLAB</b> (Version R2016b or later).Data files for the three SPWV grid datasets (<code>SPWV-H1.txt</code>, <code>SPWV-H2.txt</code>, <code>SPWV-H3.txt</code>).How to Use:<b>Load Grid Data</b>: The model requires pre-processed grid data that contains surface-level PWV values and geographic coordinates (latitude, longitude, height).<b>Set Initial Parameters</b>: Define input parameters such as the beginning and ending height (in km), the initial PWV value (in mm), latitude, longitude, and day of the year (DOY).<b>Run the Model</b>: Call the <code>PWV_Interpolation_Model.m</code> script, which applies the vertical adjustment and spatial interpolation to compute the PWV for specified regions and heights.Citation:Yang, H., Ferreira, V., He, X., Zhan, W., Wang, X., Ji, S., 2025. Spatially enhanced interpolating vertical adjustment model for precipitable water vapor. J. Geod. 99, 12. https://doi.org/10.1007/s00190-025-01936-8

**SPWV-H**是一款基于MATLAB开发的计算模型，旨在通过空间增强型垂直校正方法估算全球大气可降水量（Precipitable Water Vapor，PWV）。该模型基于地表格网数据插值得到PWV数值，同时考虑高度相关的变化特征与地理位置因素。通过结合指数插值与三次多项式校正方法，该模型可在不同海拔与纬度区域实现高精度的PWV估算。

核心特性：
**基于格网的插值**：该模型采用三类独立数据集（SPWV-H1、SPWV-H2、SPWV-H3）的地表格网数据开展PWV估算。
**垂直校正**：针对基于高度的插值采用指数模型，并对无陆地覆盖的低纬度区域应用三次多项式校正。
**基于傅里叶变换的时间变异性处理**：该模型引入基于年积日（day of year，DOY）的傅里叶项，以表征PWV的年周期与半年周期变化，适用于时间序列分析场景。
**地理适应性**：针对不同地理区域调整PWV估算结果，特别针对纬度范围为-30°至30°的低纬度区域进行优化处理。

应用场景：
**气候研究**：可用于分析水汽在时间与空间维度的变化特征，尤其适用于气候变化与大气水循环相关研究。
**气象与气候模拟**：通过提供高精度的垂直PWV廓线，可优化数值天气预报模型的性能。
**水文研究**：可在区域水文模型中估算水汽对降水与土壤湿度的贡献量。

运行要求：
MATLAB（R2016b及更高版本）。
三类SPWV格网数据集的数据文件（SPWV-H1.txt、SPWV-H2.txt、SPWV-H3.txt）。

使用方法：
**加载格网数据**：模型需导入已预处理的格网数据，其中需包含地表PWV数值与地理坐标（纬度、经度、海拔）。
**设置初始参数**：需定义输入参数，包括起止海拔（单位：km）、初始PWV数值（单位：mm）、纬度、经度以及年积日（DOY）。
**运行模型**：调用`PWV_Interpolation_Model.m`脚本，该脚本将执行垂直校正与空间插值操作，计算指定区域与海拔下的PWV数值。

引用格式：
Yang, H., Ferreira, V., He, X., Zhan, W., Wang, X., Ji, S., 2025. 面向大气可降水量的空间增强插值垂直校正模型. J. Geod. 99, 12. https://doi.org/10.1007/s00190-025-01936-8