Parametric model to estimate clear‐sky longwave irradiance at the surface on the basis of vertical distribution of humidity and temperature

Dupont, Jean-Charles; Haeffelin, Martial; Drobinski, Philippe; Besnard, T.

doi:10.1029/2007jd009046

Cited by 26 publications

(27 citation statements)

References 27 publications

(88 reference statements)

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“…The effective emissivity depends on the vertical structure of the atmosphere and those formulae that only rely on surface information must be applied with caution. Several authors evidenced different behaviour of the empirical parameterisations when applied to day time or night time data (Paltridge, 1970;Arnfield, 1979;AladosArboledas and Jiménez, 1988;Tang et al, 2004;Dupont et al, 2008), with an overestimation effect during the day time. Alados-Arboledas (1993) showed that the use of a single expression based on screen level variables for the whole day requires the inclusion of a day-night correction term, taking into account the day-night differences in the vertical structure of the atmosphere and thus the effective emissivity regime.…”

Section: Parameterisations With Locally Fitted Coefficientsmentioning

confidence: 99%

“…Most of these parameterisations were derived for night-time data using local empirical coefficients (Brunt, 1932;Idso and Jackson, 1969;Brutsaert, 1975;Idso, 1981). Several authors (Paltridge, 1970;Berdahl and Fromberg, 1982;Alados-Arboledas and Jiménez, 1988;Alados-Arboledas, 1993;Dupont et al, 2008) pointed out the differences between the day and night effective emissivity regimes. Results of this type suggest that the evaluation of various LW parameterisations covering the complete daily cycle would provide useful information for a variety of applications.…”

Section: Introductionmentioning

confidence: 99%

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Estimation of downwelling longwave irradiance under all‐sky conditions

Alados

Foyo-Moreno

Alados-Arboledas

2011

Intl Journal of Climatology

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This work is focused on the characterization and parameterisation of the downward atmospheric irradiance (LW) for clear and cloudy skies. LW is a component of the surface radiation budget that is present throughout the day. Unlike solar irradiance, LW is not measured routinely in extended networks, so it must be estimated indirectly. We evaluated five parameterisations for estimating LW under clear skies. After some consideration regarding the local fitting of the parameterisations, we analysed their different behaviour during day and night and propose a correction model for this effect. We use measurements registered at Tabernas (Spain) from 2001 to 2003. For the locally adjusted parameterisations the root mean square deviation (RMSD) and the mean bias deviation (MBD) are smaller than 5.7 and 0.6%, respectively. The combination of the more complex correction parameterisation of the day/night differences with the locally adjusted formula of Brutsaert and the original formula of Berdalh and Martin leads to estimations with RMSD below 3.1%. Using data registered at Palaiseau (France) the proposed parameterisations yields MBD close to 0% and RMSD below 3.2%. Cloudy conditions were analysed and two different approaches were used to estimate the cloud effect. Both approaches determine all sky LW using a clear-sky formulae and a cloud modification factor, computed with the solar global irradiance on a horizontal surface. The results show that LW can be estimated under all-sky conditions during the daytime with a RMSD of 5.8 and 6.2%, and a MBD of 1.6 and −2.2% for the Crawford and Duchon scheme and the parameterisation in k t , respectively, at Tabernas. The application of the same parameterisations to Palaiseau yields RMSD of 6.7 and 7.7%, and MBD of −2.5 and 0.7%.

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Section: Parameterisations With Locally Fitted Coefficientsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Estimation of downwelling longwave irradiance under all‐sky conditions

Alados

Foyo-Moreno

Alados-Arboledas

2011

Intl Journal of Climatology

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“…Considering that the MODIS TOA brightness temperature errors are 0.25 K for channels 28, 33, 34 and 35, 0.05 K for channels 29, 31 and 32, and 0.35 K for channel 36, respectively, δ(L DSLR ) can be acquired with Equation (8). Here, we adopted an uncertainty of the WVC for MODIS product of 0.5 g/cm 2 [64], so the corresponding DSLR AOD errors for VZA = 0 • and z = 0 km are as follows.…”

Section: Sensitivity Analysismentioning

confidence: 99%

“…DSLR is the result of atmospheric scattering, absorption and emission in the entire vertical column, and it can be accurately calculated with complex radiative transfer models for which the concentrations of atmospheric constituents and the vertical distribution of temperature, water vapor, aerosol and clouds as the input parameters [4][5][6][7]. It is therefore necessary to evaluate accurately these parameters if one wants to reduce uncertainties in computing their radiative effects [8,9]. However, acquisition of these parameters is difficult and they are varying rapidly, at a daily or even hourly scale.…”

Section: Introductionmentioning

confidence: 99%

Estimation of Downwelling Surface Longwave Radiation under Heavy Dust Aerosol Sky

Wang

Tang

et al. 2017

Remote Sensing

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Abstract:The variation of aerosols, especially dust aerosol, in time and space plays an important role in climate forcing studies. Aerosols can effectively reduce land surface longwave emission and re-emit energy at a colder temperature, which makes it difficult to estimate downwelling surface longwave radiation (DSLR) with satellite data. Using the latest atmospheric radiative transfer code (MODTRAN 5.0), we have simulated the outgoing longwave radiation (OLR) and DSLR under different land surface types and atmospheric profile conditions. The results show that dust aerosol has an obvious "warming" effect to longwave radiation compared with other aerosols; that aerosol longwave radiative forcing (ALRF) increased with the increasing of aerosol optical depth (AOD); and that the atmospheric water vapor content (WVC) is critical to the understanding of ALRF. A method is proposed to improve the accuracy of DSLR estimation from satellite data for the skies under heavy dust aerosols. The AOD and atmospheric WVC under cloud-free conditions with a relatively simple satellite-based radiation model yielding the high accurate DSLR under heavy dust aerosol are used explicitly as model input to reduce the effects of dust aerosol on the estimation of DSLR. Validations of the proposed model with satellites data and field measurements show that it can estimate the DSLR accurately under heavy dust aerosol skies. The root mean square errors (RMSEs) are 20.4 W/m 2 and 24.2 W/m 2 for Terra and Aqua satellites, respectively, at the Yingke site, and the biases are 2.7 W/m 2 and 9.6 W/m 2 , respectively. For the Arvaikheer site, the RMSEs are 23.2 W/m 2 and 19.8 W/m 2 for Terra and Aqua, respectively, and the biases are 7.8 W/m 2 and 10.5 W/m 2 , respectively. The proposed method is especially applicable to acquire relatively high accurate DSLR under heavy dust aerosol using MODIS data with available WVC and AOD data.

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“…Ruckstuhl et al (2007) showed that the monthly mean LDR can be effectively modeled from specific humidity or water vapor obtaining differences < 5 %. Dupont et al (2008) presented a more sophisticated parameterization based on the vertical profiles of temperature and humidity obtaining uncertainties of ∼ 5 W m −2 for cloud-free conditions, for both daytime and night-time.…”

Section: R D García Et Al: Comparison Of Observed and Modeled Ldr mentioning

confidence: 99%

Comparison of observed and modeled cloud-free longwave downward radiation (2010–2016) at the high mountain BSRN Izaña station

et al. 2018

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Abstract. A 7-year (2010-2016) comparison study between measured and simulated longwave downward radiation (LDR) under cloud-free conditions was performed at the Izaña Atmospheric Observatory (IZO, Spain). This analysis encompasses a total of 2062 cases distributed approximately evenly between day and night. Results show an excellent agreement between Baseline Surface Radiation Network (BSRN) measurements and simulations with libRadtran V2.0.1 and MODerate resolution atmospheric TRANsmission model (MODTRAN) V6 radiative transfer models (RTMs). Mean bias (simulated − measured) of < 1.1 % and root mean square of the bias (RMS) of < 1 % are within the instrumental error (2 %). These results highlight the good agreement between the two RTMs, proving to be useful tools for the quality control of LDR observations and for detecting temporal drifts in field instruments. The standard deviations of the residuals, associated with the RTM input parameters uncertainties are rather small, 0.47 and 0.49 % for libRadtran and MODTRAN, respectively, at daytime, and 0.49 to 0.51 % at night-time. For precipitable water vapor (PWV) > 10 mm, the observed night-time difference between models and measurements is +5 W m −2 indicating a scale change of the World Infrared Standard Group of Pyrgeometers (WISG), which serves as reference for atmospheric longwave radiation measurements. Preliminary results suggest a possible impact of dust aerosol on infrared radiation during daytime that might not be correctly parametrized by the models, resulting in a slight underestimation of the modeled LDR, of about −3 W m −2 , for relatively high aerosol optical depth (AOD > 0.20).

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Parametric model to estimate clear‐sky longwave irradiance at the surface on the basis of vertical distribution of humidity and temperature

Cited by 26 publications

References 27 publications

Estimation of downwelling longwave irradiance under all‐sky conditions

Estimation of downwelling longwave irradiance under all‐sky conditions

Estimation of Downwelling Surface Longwave Radiation under Heavy Dust Aerosol Sky

Comparison of observed and modeled cloud-free longwave downward radiation (2010–2016) at the high mountain BSRN Izaña station

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