Spatial distribution of air temperature in high-elevation glacierized regions: from observations in four catchments on the Tibetan Plateau
收藏DataCite Commons2025-08-19 更新2026-05-07 收录
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资源简介:
Project: Heat Island Intensity Prediction in an Intelligent Sponge Urban System in the Qinghai-Tibet Plateau - This project investigates how intelligent sponge city technologies can mitigate urban heat islands (UHI) in the Qinghai-Tibet Plateau. It aims to develop scalable models for climate-resilient urban planning in high-altitude regions through a series of targeted experiments.
Supported by grant LJ200080773 ('Intelligent Urban Rainwater Collection Module System Application'), this project develops a machine learning framework for urban heat island (UHI) prediction in sponge cities. The framework integrates thermal infrared remote sensing and meteorological data to jointly analyze UHI intensity and rainwater storage capacity, supporting ecological runoff management and heat mitigation strategies.
Summary: This experiment contains 30-meter resolution near-surface air temperature datasets for four glacier regions (Guliya, Aru, Naimona’nyi, Dunde) on the Qinghai-Tibet Plateau, derived by integrating in situ measurements (automatic weather stations and loggers; January-November 2019) with Landsat 8/9 thermal infrared data. The datasets, spanning elevations of 4,947–6,078 m and temperatures from −42°C to +16°C, address data gaps through masked nearest-neighbor interpolation and Kriging (for clustered outliers ≥5), with spatial smoothing to minimize observational noise. Validation against ground measurements employs Root Mean Square Error (RMSE) of °C and standard deviation (SD) of °C metrics, visualized via Temperature_Error graphs. The glaciers-representing diverse climatic zones-include Guliya (ice cap, westerlies-dominated), Aru (valley glacier), Naimona’nyi (Himalayan slopes), and Dunde (Qilian Mountains, transitional climate). Supported by elevation data from the Topographic Data of Qinghai-Tibet Plateau (2021) and temperature data from the GATP Dataset (doi:10.26050/WDCC/GATP). These spatially interpolated temperature distributions serve as a reference for assessing cryospheric and climate models in high-altitude regions.
提供机构:
World Data Center for Climate (WDCC) at DKRZ
创建时间:
2025-08-19



