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Longwave radiation (LWR) is a critical factor in surface energy balance and greenhouse effect studies, and its accurate measurement is essential for understanding climate change. However, existing remote sensing-based LWR products still have room for improvement in terms of spatiotemporal coverage, resolution, and accuracy. To address this issue, we developed the LWR Component of the global Long-term Earth System spatiotemporally Seamless Radiation budget dataset (LessRad). LessRad provides high-resolution (0.05°, hourly) LWR components including longwave downward radiation (LWDR), longwave upward radiation (LWUR), and longwave net radiation (LWNR). It extends the temporal coverage to 41 years (1982-2022) and outperforms existing comparable products. For LWDR and LWUR, rigorous validation against 565 ground-based observation sites demonstrates high accuracy, with correlation coefficients (R) of 0.94 and 0.97, biases of -4.39 W/m and -0.14 W/m, and root mean square errors (RMSE) of 24.74 W/m and 20.42 W/m, respectively. The high quality and extensive coverage make the LessRad LWR dataset an invaluable resource for fine-scale analysis of global surface radiation dynamics.
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http://dx.doi.org/10.1038/s41597-025-05886-w | DOI Listing |
Sci Data
September 2025
School of Geospatial Engineering and Science, Sun Yat-sen University & Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, 519000, China.
Longwave radiation (LWR) is a critical factor in surface energy balance and greenhouse effect studies, and its accurate measurement is essential for understanding climate change. However, existing remote sensing-based LWR products still have room for improvement in terms of spatiotemporal coverage, resolution, and accuracy. To address this issue, we developed the LWR Component of the global Long-term Earth System spatiotemporally Seamless Radiation budget dataset (LessRad).
View Article and Find Full Text PDFACS Appl Mater Interfaces
August 2025
College of Electrical Engineering & New Energy, Hubei Provincial Engineering Technology Research Center for Microgrid, China Three Gorges University, Yichang, Hubei 443002, PR China.
Passive daytime radiative cooling (PDRC) technology relies on reflecting solar visible light that carries high energy and radiating surface heat to a low-temperature cold background in the long-wave infrared band, thereby achieving clean energy-saving cooling. However, the irreversibility of high flux heat flow is often present in practical applications, resulting in the inability to maximize the cooling effect produced by radiative cooling. In this study, we developed an integrated radiative cooling (RC) film with high thermal conductivity for efficient cooling (DPHA film) by strategically constructing internal thermal channels within the RC interface.
View Article and Find Full Text PDFAdv Mater
August 2025
School of Materials Science and Engineering, Zhejiang University, Hangzhou, 310058, China.
Intelligent modulation of solar and thermal radiation for a smart window, including visible, near-infrared (NIR), and long-wave infrared (LWIR) spectral tri-bands (0.38-25 µm), to achieve indoor comfort and energy efficiency is a critical frontier in sustainable building design. However, independent regulations of multi-functional radiation of visible lighting, NIR heating, and LWIR radiative cooling for dynamic operational requirements and weather conditions are not fully solved.
View Article and Find Full Text PDFOptical resonators with high Q-factor are of interest in infrared thermal sensors for their high-temperature sensitivity. Thin-film lithium niobate (LN), with low propagation loss in near-infrared, is a competitive material for a comparative advantage in thermal-optic coefficient and wider absorption range from longwave infrared (LWIR) to terahertz frequencies if compared with SiN and SiO. Here, we present an LWIR sensor on the LN-photonic platform, where a high-Q microring resonator is monolithically integrated with a broadband LWIR radiation absorber, compatible with the multilayer-stacked LN photonic circuits.
View Article and Find Full Text PDFAccurate emissivity assessment is crucial for real temperature measurements using remote sensing methods and infrared signature modeling. This study introduces a novel method, to our knowledge, for determining the emissivity of materials. Samples were stabilized at 343.
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