The study of shortwave(SW) radiation and its interactions with our planet has proven critical for advancing the understanding of the Earth–atmosphere system. Here, the author shares an accessible and high-level persp...The study of shortwave(SW) radiation and its interactions with our planet has proven critical for advancing the understanding of the Earth–atmosphere system. Here, the author shares an accessible and high-level perspective on recent progress, surprises encountered, and promising future research directionsa. A brief context for the study of SW radiation is provided, after which three specific aspects are focused upon that the author considers particularly important. First, the significance of three-dimensional(3D) SW radiative effects is highlighted via impacts on surface downward SW radiation in complex cloud fields. Crucially, it is shown that probability distributions of surface radiation can only be reliably simulated when accounting for 3D effects, which has implications for various applications and next-generation atmospheric modeling. Second, the significance of the often overlooked diurnal cycle in global top-of-atmosphere upward SW radiation is underscored by quantifying the controlling properties and processes. Opportunities for improved future satellite observations of the global diurnal cycle are noted. Third, the wealth of information provided by the spectral dimension of SW radiation is demonstrated through the extraction and attribution of SW spectral signatures. It is argued that further exploration of the spectral dimension, aided by the recently launched and upcoming suite of spectrally resolved SW satellite observations, promises a new era of SW radiation research.展开更多
Efficiently monitoring Soil Organic Carbon(SOC)in farmlands is crucial for environmental and agricul-tural sustainability.Currently,crop spectral variables are primarily employed to estimate SOC in low-relief farmland...Efficiently monitoring Soil Organic Carbon(SOC)in farmlands is crucial for environmental and agricul-tural sustainability.Currently,crop spectral variables are primarily employed to estimate SOC in low-relief farmlands.To enhance SOC estimation,further crop information needs to be excavated.Addi-tionally,few studies have considered the sample size in modeling SOC estimation,which may lead to precision loss and cost waste.Therefore,this study proposed a novel method to improve SOC estimation in low-relief farmlands.This method considers more information on crop growth and minimum sample size.The results showed that:(1)time-series NDVI was established as the characteristic crop spectral variables,based on crop spectral variables extracted from eight-day time-series reflectance products.(2)Seventeen harmonic component variables were derived from time-series NDVI via Fourier trans-formation.(3)Six crop spectral variables and seven harmonic component variables were determined as the optimal SOC estimators.(4)The convolutional neural network model provided higher SOC estimation accuracy(R^(2)=0.81,NRMSE=7.09%)than the random forest model and the back propagation neural network model.And the minimum sample size based on the optimal model was determined to be 250.(5)The proposed method improved SOC estimation at the regional scale,achieving a 2.54%reduction in NRMSE compared to the NDVI-based model.These findings suggest that the proposed method holds the potential for efficient SOC estimation in low-relief farmlands.展开更多
In this paper, the preliminary data from University of Michigan Radio Astronomy Observatory database （UMRAO） are used to discuss the radio spectral index properties of 8 BL Lacs. To do so, we calculated the radio sp...In this paper, the preliminary data from University of Michigan Radio Astronomy Observatory database （UMRAO） are used to discuss the radio spectral index properties of 8 BL Lacs. To do so, we calculated the radio spectral index, a （F oc va）, which was obtained by fitting the averaged flux densities in the bands （4.8 GHZ, 8 GHz, and 14.5 GHz） by binning the original for 7 d. We also calculated the time delay between the averaged lightcurves and the spectral variance. Our calculations and analysis give the following results. 1） The averaged logarithmic flux density at 8 GHz （logF） and the corresponding spectral index （or） have strong correlation for all the BL Lacs; 2） the lightcurves and the spectral variability have the similar profile for all the BL Lacs; 3） the lightcurves delay spectral variability for all sources but PKS 0735＋178, with the delay time ranging from 31 d to 125 d.展开更多
基金the NOAA Atmospheric Science for Renewable Energy (ASRE) programthe Earth Venture Continuity 1 (EVC-1) Libera project under NASA Contract 80LARC20D0006the NOAA cooperative agreement with CIRES,NA22OAR4320151。
文摘The study of shortwave(SW) radiation and its interactions with our planet has proven critical for advancing the understanding of the Earth–atmosphere system. Here, the author shares an accessible and high-level perspective on recent progress, surprises encountered, and promising future research directionsa. A brief context for the study of SW radiation is provided, after which three specific aspects are focused upon that the author considers particularly important. First, the significance of three-dimensional(3D) SW radiative effects is highlighted via impacts on surface downward SW radiation in complex cloud fields. Crucially, it is shown that probability distributions of surface radiation can only be reliably simulated when accounting for 3D effects, which has implications for various applications and next-generation atmospheric modeling. Second, the significance of the often overlooked diurnal cycle in global top-of-atmosphere upward SW radiation is underscored by quantifying the controlling properties and processes. Opportunities for improved future satellite observations of the global diurnal cycle are noted. Third, the wealth of information provided by the spectral dimension of SW radiation is demonstrated through the extraction and attribution of SW spectral signatures. It is argued that further exploration of the spectral dimension, aided by the recently launched and upcoming suite of spectrally resolved SW satellite observations, promises a new era of SW radiation research.
基金supported by the National Key Research and Development Program of China(2021YFD20002).
文摘Efficiently monitoring Soil Organic Carbon(SOC)in farmlands is crucial for environmental and agricul-tural sustainability.Currently,crop spectral variables are primarily employed to estimate SOC in low-relief farmlands.To enhance SOC estimation,further crop information needs to be excavated.Addi-tionally,few studies have considered the sample size in modeling SOC estimation,which may lead to precision loss and cost waste.Therefore,this study proposed a novel method to improve SOC estimation in low-relief farmlands.This method considers more information on crop growth and minimum sample size.The results showed that:(1)time-series NDVI was established as the characteristic crop spectral variables,based on crop spectral variables extracted from eight-day time-series reflectance products.(2)Seventeen harmonic component variables were derived from time-series NDVI via Fourier trans-formation.(3)Six crop spectral variables and seven harmonic component variables were determined as the optimal SOC estimators.(4)The convolutional neural network model provided higher SOC estimation accuracy(R^(2)=0.81,NRMSE=7.09%)than the random forest model and the back propagation neural network model.And the minimum sample size based on the optimal model was determined to be 250.(5)The proposed method improved SOC estimation at the regional scale,achieving a 2.54%reduction in NRMSE compared to the NDVI-based model.These findings suggest that the proposed method holds the potential for efficient SOC estimation in low-relief farmlands.
基金supported by the National Natural Science Foundation of China (Grant Nos.10633010 and 11173009)the Bureau of Education of Guangzhou Municipality (Grant No.11 Sui-Jiao-Ke[2009])+3 种基金Guangdong Province Universities and Colleges Pearl River Scholar Funded Scheme(GDUPS)(2009)Yangcheng Scholar Funded Scheme(Grant No.10A027S)the Joint Laboratory for Optical Astronomy of Chinese Academy of Sciencessupported by the University of Michigan and the National Science Foundation
文摘In this paper, the preliminary data from University of Michigan Radio Astronomy Observatory database （UMRAO） are used to discuss the radio spectral index properties of 8 BL Lacs. To do so, we calculated the radio spectral index, a （F oc va）, which was obtained by fitting the averaged flux densities in the bands （4.8 GHZ, 8 GHz, and 14.5 GHz） by binning the original for 7 d. We also calculated the time delay between the averaged lightcurves and the spectral variance. Our calculations and analysis give the following results. 1） The averaged logarithmic flux density at 8 GHz （logF） and the corresponding spectral index （or） have strong correlation for all the BL Lacs; 2） the lightcurves and the spectral variability have the similar profile for all the BL Lacs; 3） the lightcurves delay spectral variability for all sources but PKS 0735＋178, with the delay time ranging from 31 d to 125 d.
