ERA5 Cloud Height Bias Correction Data for the Tibetan Plateau

WEI ZHAO's dataset, published on figshare in April 2026, contains data for mitigating systematic biases in cloud base height estimates over the Tibetan Plateau. It includes ground-based lidar and CALIPSO satellite-derived cloud base heights, along with ERA5 reanalysis meteorological variables from October 2021 to December 2024. The 5.9 MB dataset is provided in CSV and NC formats.

Use Cases

• Reproducing a machine learning framework for bias correction based on the described lidar, satellite, and reanalysis data.
• Analyzing relationships between cloud base height and meteorological variables like specific humidity and temperature.
• Studying spatial patterns of cloud properties over the Tibetan Plateau based on geographic coordinates and surface attributes.
• Validating or refining ERA5 reanalysis cloud data using ground and satellite observations.

Strengths

• Includes three distinct data sources (ground lidar, CALIPSO satellite, ERA5 reanalysis) for cross-validation.
• Covers a three-year time range from October 2021 to December 2024.
• Contains key ERA5 variables for reproduction, including specific humidity, temperature, and cloud water content.

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.

Provenance

Source

figshare, author WEI ZHAO.

Collection Method

Utilizes a two-step machine learning framework with ground-based lidar, CALIPSO satellite retrievals, and ERA5 reanalysis data.

Time Range

October 2021 to December 2024.

Freshness

Last updated 2026-04-15 07:01:08; freshness should be verified.

Geography

Tibetan Plateau.