Cloud vertical structure across China from a national Ka-band cloud radar network: thermodynamic, dynamical, and land-surface controls
- 1Chinese Academy of Meteorological Sciences (Beijing, China)
Abstract
Cloud vertical structure (CVS) plays a fundamental role in regulating the Earth's radiation budget and hydrological cycle, yet its representation in numerical weather prediction and climate models remains highly uncertain, largely due to limited high-resolution regional observations. Using a newly established national network of 80 Ka-band millimeter-wave cloud radars (MMCRs), here we present a high-spatiotemporal-resolution (vertical resolution of 30 m, temporal resolution of 1 min) characterization of CVS across China based on one year (2024) of observations, and quantify its thermodynamic, dynamical, and land-surface controls. Cloud boundaries are retrieved using an improved algorithm that integrates height-dependent radar sensitivity with variance-based clutter suppression. Results show that the national annual mean cloud occurrence frequency is 56.7 ± 7.2 %, dominated by single-layer clouds (34.7 ± 4.0 %), followed by two-layer (14.7 ± 3.2 %) and multi-layer clouds (7.1 ± 2.4 %). Spatially, single-layer clouds prevail over arid northwestern China, whereas multi-layer clouds are more frequent in humid southeastern region. Cloud base height (CBH) exhibits strong seasonality (summer > spring > autumn > winter), with notably low CBH over the Tibetan Plateau. Diurnally, summer clouds show a pronounced afternoon peak between 3 and 9 km, while winter clouds remain largely below 3 km and peak near sunrise. Thermodynamic conditions exert the primary control on CVS. Higher 2 m specific humidity promotes deeper cloud development and raises cloud top height (CTH), whereas enhanced lower-tropospheric stability suppresses vertical cloud growth and lowers both CBH and CTH. Dynamical forcing further modulates cloud structure: stronger vertical wind shear (VWS) generally inhibits vertical cloud development, reducing CBH, CTH and cloud thickness, while moderate VWS can enhance organization under unstable conditions. Joint dependence analyses reveal that moisture, stability, and shear act in a coupled manner, with moisture being the dominant driver and stability and shear serving as strong regulators. In addition, land-surface characteristics significantly influence CBH, especially for afternoon single-layer low clouds, which exhibit a mean CBH is 21.7 % higher than the all-hour low clouds, with the strongest enhancement over evergreen broadleaf forests (+41.7 % ). These findings provide the first observationally constrained, national-scale assessment of CVS based on this radar network, offering quantitative benchmarks for evaluating and improving cloud parameterizations in weather and climate models.
Versions
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BibTeX
@article{xu2026cloud,
title = {{Cloud vertical structure across China from a national Ka-band cloud radar network: thermodynamic, dynamical, and land-surface controls}},
author = {Hui Xu and Jianping Guo and Jianbo Deng and Rongfang Yang and Deli Meng and Zhen Zhang and Ning Li and Yuping Sun and Shuairu Jiang and Tianmeng Chen and Juan Chen and Liping Zeng and Yongshui Zhou and Bing Tong},
journal = {Atmospheric Chemistry and Physics},
year = {2026},
month = oct,
doi = {10.5194/acp-26-14303-2026},
url = {https://acp.copernicus.org/articles/26/14303/2026/},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Cloud vertical structure across China from a national Ka-band cloud radar network: thermodynamic, dynamical, and land-surface controls
AU - Hui Xu
AU - Jianping Guo
AU - Jianbo Deng
AU - Rongfang Yang
AU - Deli Meng
AU - Zhen Zhang
AU - Ning Li
AU - Yuping Sun
AU - Shuairu Jiang
AU - Tianmeng Chen
AU - Juan Chen
AU - Liping Zeng
AU - Yongshui Zhou
AU - Bing Tong
PY - 2026
DA - 2026/10/12
JO - Atmospheric Chemistry and Physics
DO - 10.5194/acp-26-14303-2026
UR - https://acp.copernicus.org/articles/26/14303/2026/
AB - Cloud vertical structure (CVS) plays a fundamental role in regulating the Earth's radiation budget and hydrological cycle, yet its representation in numerical weather prediction and climate models remains highly uncertain, largely due to limited high-resolution regional observations. Using a newly established national network of 80 Ka-band millimeter-wave cloud radars (MMCRs), here we present a high-spatiotemporal-resolution (vertical resolution of 30 m, temporal resolution of 1 min) characterization of CVS across China based on one year (2024) of observations, and quantify its thermodynamic, dynamical, and land-surface controls. Cloud boundaries are retrieved using an improved algorithm that integrates height-dependent radar sensitivity with variance-based clutter suppression. Results show that the national annual mean cloud occurrence frequency is 56.7 ± 7.2 %, dominated by single-layer clouds (34.7 ± 4.0 %), followed by two-layer (14.7 ± 3.2 %) and multi-layer clouds (7.1 ± 2.4 %). Spatially, single-layer clouds prevail over arid northwestern China, whereas multi-layer clouds are more frequent in humid southeastern region. Cloud base height (CBH) exhibits strong seasonality (summer > spring > autumn > winter), with notably low CBH over the Tibetan Plateau. Diurnally, summer clouds show a pronounced afternoon peak between 3 and 9 km, while winter clouds remain largely below 3 km and peak near sunrise. Thermodynamic conditions exert the primary control on CVS. Higher 2 m specific humidity promotes deeper cloud development and raises cloud top height (CTH), whereas enhanced lower-tropospheric stability suppresses vertical cloud growth and lowers both CBH and CTH. Dynamical forcing further modulates cloud structure: stronger vertical wind shear (VWS) generally inhibits vertical cloud development, reducing CBH, CTH and cloud thickness, while moderate VWS can enhance organization under unstable conditions. Joint dependence analyses reveal that moisture, stability, and shear act in a coupled manner, with moisture being the dominant driver and stability and shear serving as strong regulators. In addition, land-surface characteristics significantly influence CBH, especially for afternoon single-layer low clouds, which exhibit a mean CBH is 21.7 % higher than the all-hour low clouds, with the strongest enhancement over evergreen broadleaf forests (+41.7 % ). These findings provide the first observationally constrained, national-scale assessment of CVS based on this radar network, offering quantitative benchmarks for evaluating and improving cloud parameterizations in weather and climate models.
SN - 1680-7324
ER -