High-precision forecasting of 1 km resolution PWV and ZTD over China based on the Pangu-Weather system

IF 4.5 2区地球科学 Q1 METEOROLOGY & ATMOSPHERIC SCIENCES

Atmospheric Research Pub Date : 2026-04-15 Epub Date: 2026-01-11 DOI:10.1016/j.atmosres.2026.108771

Zhihao Wang , Hongzhou Chai , Yuhao Ye , Min Wang , Peng Chen

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引用次数: 0

Abstract

As key tropospheric parameters, zenith total delay (ZTD) and precipitable water vapor (PWV) serve as core data supports for precise positioning of the Global Navigation Satellite System (GNSS), meteorological monitoring, and disaster early warning. However, existing observation and estimation methods generally suffer from technical bottlenecks, including insufficient spatiotemporal resolution, poor real-time performance, and data blind spots. To address this problem, this study proposes a novel retrieval method based on the Pangu-Weather system, aiming to achieve 7-day high-precision real-time forecasting of PWV and ZTD with 1 km resolution over the China. Using ERA5 reanalysis data as the initial field, the Pangu-Weather system is utilized to forecast meteorological parameters for the next 7 days, and preliminary PWV and ZTD products (Pangu-PWV, Pangu-ZTD) are obtained through integral calculation. Subsequently, based on GNSS data, a multilayer perceptron (MLP) is employed to establish the mapping relationship between latitude, longitude, digital elevation model (DEM), Normalized Difference Vegetation Index (NDVI), time, and tropospheric parameters. The Pangu products are calibrated to the ground height, generating high-precision PWV and ZTD products with 1 km resolution (MLP-PWV, MLP-ZTD). Accuracy verification results indicate that the RMSE between MLP-PWV and GNSS-PWV is 3.63 mm, and the R² is 0.95. For MLP-ZTD and GNSS-ZTD, the RMSE is 26.55 mm and the R² is 0.99, both demonstrating excellent spatiotemporal consistency. Application analysis using typhoon Doksuri in 2023 as a case study shows that MLP-PWV can accurately depict the spatial distribution of PWV during hazardous weather processes, overcoming the limitation that Pangu-PWV is unable to reliably calculate PWV above the Earth's surface. This study provides reliable data support for real-time monitoring of tropospheric parameters with high spatiotemporal resolution.

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基于盘古天气系统的中国1公里分辨率PWV和ZTD高精度预报

天顶总延迟（ZTD）和可降水量（PWV）作为对流层的关键参数，是全球卫星导航系统（GNSS）精确定位、气象监测和灾害预警的核心数据支撑。然而，现有的观测和估算方法普遍存在时空分辨率不足、实时性差、数据盲点等技术瓶颈。针对这一问题，本研究提出了一种基于盘古气象系统的新型检索方法，旨在实现中国上空1 km分辨率的PWV和ZTD的7 d高精度实时预报。以ERA5再分析资料为初始场，利用盘古天气系统预报未来7 d的气象参数，通过积分计算得到盘古PWV和ZTD的初步产品（盘古PWV、盘古ZTD）。随后，基于GNSS数据，利用多层感知器（MLP）建立经纬度、数字高程模型（DEM）、归一化植被指数（NDVI）、时间和对流层参数之间的映射关系。盘古产品经地面高度标定，生成1公里分辨率的高精度PWV和ZTD产品（MLP-PWV, MLP-ZTD）。精度验证结果表明，MLP-PWV与GNSS-PWV的RMSE为3.63 mm， R2为0.95。MLP-ZTD和GNSS-ZTD的均方根误差为26.55 mm， R2为0.99，均具有较好的时空一致性。以2023年台风“Doksuri”为例进行的应用分析表明，MLP-PWV能够准确描述危险天气过程中PWV的空间分布，克服了Pangu-PWV无法可靠计算地表以上PWV的局限性。该研究为高时空分辨率对流层参数的实时监测提供了可靠的数据支持。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Atmospheric Research 地学-气象与大气科学

CiteScore

9.40

自引率

10.90%

发文量

460

审稿时长

47 days

期刊介绍： The journal publishes scientific papers (research papers, review articles, letters and notes) dealing with the part of the atmosphere where meteorological events occur. Attention is given to all processes extending from the earth surface to the tropopause, but special emphasis continues to be devoted to the physics of clouds, mesoscale meteorology and air pollution, i.e. atmospheric aerosols; microphysical processes; cloud dynamics and thermodynamics; numerical simulation, climatology, climate change and weather modification.