Li et al. (2025) Global Low Clouds Evolution and Their Meteorological Drivers Across Multiple Timescales

⚠️ Warning: This summary was generated from the abstract only, as the full text was not available.

Identification

• Journal: Remote Sensing
• Year: 2025
• Date: 2025-12-17
• Authors: Yize Li, Jinming Ge, Yue Hu, Ziwei Xu, Jiajing Du, Qingyu Mu
• DOI: 10.3390/rs17244045

Research Groups

Not available in the provided text.

Short Summary

This study investigates the timescale-dependent relationships between low cloud amount (stratocumulus, cumulus, stratus) and meteorological conditions over global land and ocean, revealing that these interactions are nonlinear and vary significantly across short (≤1 year), medium (1–8 years), and long (>8 years) timescales, as well as in their long-term trends.

Objective

• To isolate low cloud amount across multiple intrinsic timescales and trends using Ensemble Empirical Mode Decomposition and link them to meteorological variables, thereby moving beyond static, linear assumptions to improve cloud parameterizations and reduce climate projection uncertainties.

Study Configuration

• Spatial Scale: Global land and ocean.
• Temporal Scale: 1987–2016 (30 years), analyzed across short (≤1 year), medium (1–8 years), and long (>8 years) timescales, and long-term trends.

Methodology and Data

• Models used: Ensemble Empirical Mode Decomposition (EEMD) method for signal decomposition.
• Data sources: ISCCP-H cloud observations, ERA5 reanalysis data.

Main Results

• Trends show a nonlinear increase in stratocumulus (Sc) and a significant nonlinear decline in cumulus (Cu), while stratus (St) exhibits weaker trends.
• At short timescales (≤1 year), Sc and Cu over land are primarily influenced by near-surface heating, whereas sea surface temperature and surface sensible heat flux (SHF) dominate over ocean.
• At medium timescales (1–8 years), SHF becomes dominant over land, largely reflecting ENSO-related induced surface anomalies. SHF remains dominant over ocean.
• At long timescales (>8 years), atmospheric stability and wind speed influence continental clouds, while SHF remains dominant over ocean.
• Trend components reveal that Sc and Cu are most sensitive to temperature changes, whereas St responds to mid-level humidity over ocean and SHF over land.
• Overall, low cloud variability and trends are explained by distinct meteorological controls that change across timescales, cloud types, and surface regimes, rather than a single linear mechanism.

Contributions

• Demonstrates the critical importance of considering timescale-dependent and nonlinear cloud–meteorology relationships, challenging the prevailing assumption of static, linear interactions.
• Provides a more nuanced understanding of low cloud feedback mechanisms, which is crucial for improving cloud parameterizations in climate models.
• Offers insights that can help reduce uncertainties in future climate projections by better representing complex cloud processes.

Funding

Not available in the provided text.

Citation

@article{Li2025Global,
  author = {Li, Yize and Ge, Jinming and Hu, Yue and Xu, Ziwei and Du, Jiajing and Mu, Qingyu},
  title = {Global Low Clouds Evolution and Their Meteorological Drivers Across Multiple Timescales},
  journal = {Remote Sensing},
  year = {2025},
  doi = {10.3390/rs17244045},
  url = {https://doi.org/10.3390/rs17244045}
}