收稿：2017-01-12，
录用：2017-6-13，
纸质出版：2017-09-15
移动端阅览
云层对地气系统辐射能量平衡有重要的调节作用，然而传统1维大气辐射传输模型仅能考虑晴空和全云两种情况。为了更好地研究云层对地表短波辐射的影响，以大气辐射传输模型SBDART(Santa Barbara Disort Atmospheric Radiative Transfer)为基础，在短波辐射传输基本方程中引入半球天空有效云覆盖度和区域真实云覆盖度两个关键云参数，考虑太阳方向和半球天空云层覆盖情况，对模型进行几何关系的修正。结合短波辐射的影响因素和SBDART模型的内置参数，选择13个参数，使用全局定量敏感性分析软件SimLab对修正后的模型进行参数敏感性分析及应用讨论。研究结果表明：该模型能够较好地描述云层对地表短波辐射的影响；对下行短波辐射和地表短波净辐射而言，太阳天顶角和地表反照率的影响最为显著；两个云覆盖参数在很大程度上也影响了地表短波辐射分量；在模型实际应用过程中，敏感性较强的6个参数均可以通过卫星遥感数据得到，模型具有较好的应用前景。由此可见，改进的短波辐射传输模型能够更好地考虑不同云层条件下、不同太阳–云–观测几何下的短波辐射传输问题，有利于提高短波辐射参量的遥感反演精度。
Clouds
being the most abundant and variable factor in the atmosphere
are critical to the modification of Earth–atmosphere energy balance. The effects of clouds on radiation should therefore be carefully and thoroughly considered. However
traditional atmospheric radiative transfer models only consider two extreme situations
namely
all clear and overcast. To understand the influence of clouds on surface shortwave radiation and improve the accuracy of shortwave radiative components derived from remote sensing dataset
we propose a novel radiative transfer model to analyze the cloud conditions in this work. Based on the traditional one-dimensional radiative transfer model Santa Barbara DISORT Atmospheric Radiative Transfer (SBDART)
this study first classifies the actual sun/cloud-viewing geometric conditions into nine subtypes
considering whether the directions of the sun and sensor are obscured by clouds. Then
the original formula of land surface downward radiative components is expanded. Two cloud fraction parameters (i.e.
hemispherical effective cloud fraction and regional cloud fraction) are introduced to the formula to establish an improved shortwave radiative transfer model
namely
the SBDART-CF model. Based on the formula
the nine subtypes are summarized into two types
that is
the situations where the direction of the sun is either obscured by the cloud or not. Then
the atmospheric spherical albedo and atmospheric transmission of different cloud conditions are compared to narrow the range of cloud parameters. Other thirteen parameters
such as solar zenith angle
surface albedo
and cloud thickness
among others
are introduced to the following sensitive analysis. Finally
the effects of the above-mentioned model parameters on the surface shortwave radiative components under different circumstances are calculated and analyzed by using SimLab software
which employs a global quantitative sensitivity analysis method. The proposed shortwave radiative transfer model can efficiently describe the influence of clouds on the surface shortwave radiation by considering the cloud horizontal distribution in the sky. Solar zenith angle and surface albedo both play significant roles in the modification of downward shortwave radiation and surface net shortwave radiation. Hemispherical effective cloud fraction and regional cloud fraction also considerably affect the radiation components. Six factors that are also important to the model can be easily derived from the satellite products and therefore can contribute to the model application effectively. Water vapor
ozone
and carbon dioxide column volume exert minimal effects on the surface shortwave radiation components under all the considered conditions. The above analysis results show that the proposed SBDART-CF model can deal with shortwave radiative problems under different cloud conditions. Therefore
the model can effectively accomplish the radiative component estimation from remotely sensed datasets.
Achad M, López M L, Palancar G G and Toselli B M. 2013. Retrieving the relative contribution of aerosol types from single particle analysis and radiation measurements and calculations: a comparison of two independent approaches. Journal of Aerosol Science, 64: 11–23
Chen L, Yan G J, Wang T X, Ren H Z, Calbó J, Zhao J and McKenzie R. 2012. Estimation of surface shortwave radiation components under all sky conditions: modeling and sensitivity analysis. Remote Sensing of Environment, 123: 457–469
Confalonieri R, Bellocchi G, Tarantola S, Acutis M, Donatelli M and Genovese G. 2010. Sensitivity analysis of the rice model WARM in Europe: exploring the effects of different locations, climates and methods of analysis on model sensitivity to crop parameters. Environmental Modeling and Software, 25(4): 479–488
Confalonieri R. 2010. Monte Carlo based sensitivity analysis of two crop simulators and considerations on model balance. European Journal of Agronomy, 33(2): 89–93
Dahlback A and Stamnes K. 1991. A new spherical model for computing the radiation field available for photolysis and heating at twilight. Planetary and Space Science, 39(5): 671–683
Drouet J L, Capian N, Fiorelli J L, Blanfort V, Capitaine M, Duretz S, Gabrielle B, Martin R, Lardy R, Cellier P and Soussana J F. 2011. Sensitivity analysis for models of greenhouse gas emissions at farm level. Case study of N 2 O emissions simulated by the CERES-EGC model. Environmental Pollution, 159(11): 3156–3161
Harrison E F, Minnis P, Barkstrom B R, Ramanathan V, Cess R D and Gibson G G. 1990. Seasonal variation of cloud radiative forcing derived from the Earth radiation budget experiment. Journal of Geophysical Research: Atmospheres, 95(D11): 18687–18703
Kneizys F X, Shettle E P, Abreu L W, Chetwynd J H and Anderson G P. 1988. User guide to LOWTRAN7. Hanscom, MA: Air Force Geophysics Laboratory: 1–4
Lam C C, Leung P T and Young K. 1992. Explicit asymptotic formulas for the positions, widths, and strengths of resonances in Mie scattering. Journal of the Optical Society of America B, 9(9): 1585–1592
Liang S L. 2005. Quantitative Remote Sensing of Land Surfaces. New York: John Wiley and Sons: 140
O’Hirok W and Gautier C. 1998. A three-dimensional radiative transfer model to investigate the solar radiation within a cloudy atmosphere. Part II: spectral effects. Journal of the Atmospheric Sciences, 55(19): 3065–3076
Oreopoulos L and Cahalan R F. 2005. Cloud inhomogeneity from MODIS. Journal of Climate, 18(23): 5110–5124
Pinker R T, Liu H, Osborne S R and Akoshile C. 2010. Radiative effects of aerosols in sub-Sahel Africa: dust and biomass burning. Journal of Geophysical Research: Atmospheres, 115(D15): D15205
Pinker R T, Ttarpley J D, Laszlo I, Mitchell K E, Houser P R, Wood E F, Schaake J C, Robock A, Lohmann D, Cosgrove B A, Sheffield J, Duan Q Y, Luo L F and Higgins R W. 2003. Surface radiation budgets in support of the GEWEX Continental-Scale International Project (GCIP) and the GEWEX Americas Prediction Project (GAPP), including the North American Land Data Assimilation System (NLDAS) project. Journal of Geophysical Research: Atmospheres, 108(D22): 8844
Ricchiazzi P, Yang S, Gautier C and Sowle D. 1998. SBDART: a research and teaching software tool for plane-parallel radiative transfer in the earth’s atmosphere. Bulletin of the American Meteorological Society, 79(10): 2101–2114
Richter G M, Acutis M, Trevisiol P, Latiri K and Confalonieri R. 2010. Sensitivity analysis for a complex crop model applied to Durum wheat in the Mediterranean. European Journal of Agronomy, 32(2): 127–136
Stamnes K, Tsay S C, Wiscombe W and Jayaweera K. 1988. Numerically stable algorithm for discrete-ordinate-method radiative transfer in multiple scattering and emitting layered media. Applied Optics, 27(12): 2502–2509
Stevens B and Bony S. 2013. Climate change. What are climate models missing. Science, 340(6136): 1053–1054
Stull R B. 1988. An Introduction to Boundary Layer Meteorology. Netherlands: Springer: 545–558
Viúdez-Mora A. 2011. Atmospheric Downwelling Longwave Radiation at the Surface During Cloudless and Overcast Conditions. Measurements and Modeling. Catalonia: Universitat de Girona: 10–15
Zhang Y, Rossow W B, Lacis A A, Oinas V and Mishchenko M. 2004. Calculation of radiative fluxes from the surface to top of atmosphere based on ISCCP and other global data sets: Refinements of the radiative transfer model and the input data. Journal of Geophysics Research, 109(19): 2156–2202
相关作者
相关机构
京公网安备11010802024621
