Atmospheric Water Vapor Monitoring and Analysis

Atmospheric water vapour is a key driver of weather, climate variability and the hydrological cycle. Its distribution and temporal variability influence cloud formation, precipitation processes and radiative forcing. Accurate monitoring of water vapour at multiple scales—from local to global—is essential for improving numerical weather prediction, climate trend analysis and extreme event forecasting. Traditional in situ radiosonde measurements provide high-vertical-resolution profiles but are limited in spatial coverage. Satellite sensors, ground-based remote-sensing instruments and dense networks of Global Navigation Satellite System (GNSS) receivers now complement radiosondes by delivering continuous, high-frequency estimates of integrated and slant water vapour. Advances in retrieval algorithms, empirical tropospheric delay models and tomographic techniques have further refined our ability to characterise both the hydrostatic and wet components of atmospheric delay. Emerging approaches in machine learning, data assimilation and the fusion of multi-sensor observations are enhancing the spatiotemporal resolution of water vapour products. These developments underpin better representation of moisture processes in operational forecasting systems, more reliable early warnings for extreme precipitation and drought, and more robust assessments of long-term climatic moisture trends.

Research from Nature Portfolio

Recent studies have demonstrated the potential of GNSS-derived precipitable water vapour (PWV) as a tool for short-term rainfall forecasting. One seminal work developed an algorithm that tracks rapid increases in PWV from a network of continuously operating reference stations. Validation over multiple rainfall events showed a forecasting accuracy of around 80% with a false alarm rate comparable to existing methods. The approach proved adaptable across different climatic regions and event types, illustrating the feasibility of integrating high-density PWV observations into nowcasting systems and conventional weather prediction models to improve lead-time and reliability.

Atmospheric Water Vapor Monitoring and Analysis publication trend

The graph below shows the total number of articles in atmospheric water vapor monitoring and analysis across all publications each year (not limited to Nature Index journals).

Technical terms

Precipitable Water Vapour (PWV): The total amount of water vapour in a vertical column of atmosphere, typically expressed in millimetres or kilograms per square metre.

Integrated Water Vapour (IWV): A measure equivalent to PWV, representing the vertically integrated water vapour content of the entire atmospheric column.

Zenith Wet Delay (ZWD): The component of GNSS signal delay at the zenith direction caused by water vapour, used to infer PWV.

Global Navigation Satellite System (GNSS): Satellite constellations and ground-based receivers used to derive atmospheric delays for water vapour estimation and positioning.

Slant Delay: The atmospheric signal delay measured along an oblique path (non-vertical) between a satellite and a ground receiver, essential for tomographic retrievals.

References

1. An enhanced integrated water vapour dataset from more than 10 000 global ground-based GPS stations in 2020. Earth System Science Data (2023).
2. Improving the capability of water vapor retrieval from Landsat 8 using ensemble machine learning. International Journal of Applied Earth Observation and Geoinformation (2023).
3. A Global Model for Estimating Tropospheric Delay and Weighted Mean Temperature Developed with Atmospheric Reanalysis Data from 1979 to 2017. Remote Sensing (2019).
4. Establishing a method of short-term rainfall forecasting based on GNSS-derived PWV and its application. Scientific Reports (2017).