The clear sky downwelling longwave radiation at the surface in current and future climates

Author(s):  
Callum J. Shakespeare ◽  
Michael L. Roderick
2014 ◽  
Vol 27 (19) ◽  
pp. 7250-7269 ◽  
Author(s):  
Neil P. Barton ◽  
Stephen A. Klein ◽  
James S. Boyle

Abstract Previous research has found that global climate models (GCMs) usually simulate greater lower tropospheric stabilities compared to reanalysis data. To understand the origins of this bias, the authors examine hindcast simulations initialized with reanalysis data of six GCMs and find that four of the six models simulate within five days a positive bias in Arctic lower tropospheric stability during the Arctic polar night over sea ice regions. These biases in lower tropospheric stability are mainly due to cold biases in surface temperature, as very small potential temperature biases exist aloft. Similar to previous research, polar night surface temperature biases in the hindcast runs relate to all-sky downwelling longwave radiation in the models, which very much relates to the cloud liquid water. Also found herein are clear-sky longwave radiation biases and a fairly large clear-sky longwave radiation bias in the day one hindcast. This clear-sky longwave bias is analyzed by running the same radiation transfer model for each model’s temperature and moisture profile, and the model spread in clear-sky downwelling longwave radiation with the same radiative transfer model is found to be much less, suggesting that model differences other than temperature and moisture are aiding in the spread in downwelling longwave radiation. The six models were also analyzed in Atmospheric Model Intercomparison Project (AMIP) mode to determine if hindcast simulations are analogous to free-running simulations. Similar winter lower tropospheric stability biases occur in four of the six models with surface temperature biases relating to the winter lower tropospheric stability values.


2019 ◽  
Vol 32 (22) ◽  
pp. 7935-7949 ◽  
Author(s):  
Israel Silber ◽  
Johannes Verlinde ◽  
Sheng-Hung Wang ◽  
David H. Bromwich ◽  
Ann M. Fridlind ◽  
...  

Abstract The surface downwelling longwave radiation component (LW↓) is crucial for the determination of the surface energy budget and has significant implications for the resilience of ice surfaces in the polar regions. Accurate model evaluation of this radiation component requires knowledge about the phase, vertical distribution, and associated temperature of water in the atmosphere, all of which control the LW↓ signal measured at the surface. In this study, we examine the LW↓ model errors found in the Antarctic Mesoscale Prediction System (AMPS) operational forecast model and the ERA5 model relative to observations from the ARM West Antarctic Radiation Experiment (AWARE) campaign at McMurdo Station and the West Antarctic Ice Sheet (WAIS) Divide. The errors are calculated separately for observed clear-sky conditions, ice-cloud occurrences, and liquid-bearing cloud-layer (LBCL) occurrences. The analysis results show a tendency in both models at each site to underestimate the LW↓ during clear-sky conditions, high error variability (standard deviations > 20 W m−2) during any type of cloud occurrence, and negative LW↓ biases when LBCLs are observed (bias magnitudes >15 W m−2 in tenuous LBCL cases and >43 W m−2 in optically thick/opaque LBCLs instances). We suggest that a generally dry and liquid-deficient atmosphere responsible for the identified LW↓ biases in both models is the result of excessive ice formation and growth, which could stem from the model initial and lateral boundary conditions, microphysics scheme, aerosol representation, and/or limited vertical resolution.


2013 ◽  
Vol 52 (7) ◽  
pp. 1525-1539 ◽  
Author(s):  
Rosie Howard ◽  
Roland Stull

AbstractAccurately calculating the surface radiation budget of a groomed ski run is crucial when determining snow surface temperature and other snow-related variables, knowledge of which is important for ski racing. Downwelling longwave radiation can compose a large part of the surface radiation budget in mountainous terrain. At a location on a ski run, a portion of the downwelling longwave radiation comes from the sky and a portion comes from tall evergreen trees. Infrared photographs taken during daytime at a ski run on Whistler Mountain, British Columbia, Canada, for a clear-sky day in February 2012 show that trees can enhance the downwelling longwave radiation at the center of the ski run considerably, with a maximum estimated enhancement of 75.6 ± 16.8 W m−2 for trees in direct sunlight. The average needle and trunk brightness temperatures from the IR photographs were correlated with measured meteorological data. Regressions were found to allow estimation of longwave radiation from trees using nearby routine meteorological data. Absolute errors in tree longwave radiation estimations using the derived trunk and needle temperatures did not exceed 4 W m−2. The effect of the intervening air upon longwave radiative transfer between trees and the point of interest on the ski run was found to be small for these very short pathlengths of 50 m or less. These results can be used to improve calculations of the surface radiation budget of a groomed ski run under clear skies.


2013 ◽  
Vol 52 (7) ◽  
pp. 1540-1553 ◽  
Author(s):  
Rosie Howard ◽  
Roland Stull

AbstractThe surface radiation budget of a groomed ski run is important to ski racing. Variables such as snow-surface temperature and liquid water content depend upon the surface radiation budget and are crucial to preparing fast skis. This case study focuses on downwelling longwave radiation, measurements of which were made at a point on a ski run on Whistler Mountain, British Columbia, Canada, throughout a 5-day clear-sky intensive observation period. Tall trees often dominate the horizon of a point on a ski run, and so contributions to total downwelling longwave radiation from trees and sky were treated separately. The “LWRAD” longwave radiative flux model estimated the total downwelling longwave radiation by first calculating thermal contributions from the trees, incorporating regressions for tree temperature that use routine meteorological measurements. Contributions from each azimuth direction were determined with horizon-elevation angles from a theodolite survey. Thermal emissions were weighted accordingly and summed. Sky contributions were estimated using the “libRadtran” radiative transfer model with input of local atmospheric profiles of temperature and humidity and were added to tree emissions. Two clear-sky emissivity parameterizations using screen-height measurements were tested for comparison. LWRAD total downwelling longwave radiation varies between 235 and 265 W m−2 and compares well to measurements, with correlation coefficient squared (r2) of 0.96. These results can be used to improve estimates of downwelling longwave radiation for a groomed ski run.


2021 ◽  
Author(s):  
Gitanjali Thakur ◽  
Stan Schymanski ◽  
Kaniska Mallick ◽  
Ivonne Trebs

<p>The surface energy balance (SEB) is defined as the balance between incoming energy from the sun and outgoing energy from the Earth’s surface. All components of the SEB depend on land surface temperature (LST). Therefore, LST is an important state variable that controls the energy and water exchange between the Earth’s surface and the atmosphere. LST can be estimated radiometrically, based on the infrared radiance emanating from the surface. At the landscape scale, LST is derived from thermal radiation measured using  satellites.  At the plot scale, eddy covariance flux towers commonly record downwelling and upwelling longwave radiation, which can be inverted to retrieve LST  using the grey body equation :<br>             R<sub>lup</sub> = εσ T<sub>s</sub><sup>4</sup> + (1 − ε) R<sub> ldw         </sub>(1)<br>where R<sub>lup</sub> is the upwelling longwave radiation, R<sub>ldw</sub> is the downwelling longwave radiation, ε is the surface emissivity, <em>T<sub>s</sub>  </em>is the surface temperature and σ  is the Stefan-Boltzmann constant. The first term is the temperature-dependent part, while the second represents reflected longwave radiation. Since in the past downwelling longwave radiation was not measured routinely using flux towers, it is an established practice to only use upwelling longwave radiation for the retrieval of plot-scale LST, essentially neglecting the reflected part and shortening Eq. 1 to:<br>               R<sub>lup</sub> = εσ T<sub>s</sub><sup>4 </sup>                       (2)<br>Despite  widespread availability of downwelling longwave radiation measurements, it is still common to use the short equation (Eq. 2) for in-situ LST retrieval. This prompts the question if ignoring the downwelling longwave radiation introduces a bias in LST estimations from tower measurements. Another associated question is how to obtain the correct ε needed for in-situ LST retrievals using tower-based measurements.<br>The current work addresses these two important science questions using observed fluxes at eddy covariance towers for different land cover types. Additionally, uncertainty in retrieved LST and emissivity due to uncertainty in input fluxes was quantified using SOBOL-based uncertainty analysis (SALib). Using landscape-scale emissivity obtained from satellite data (MODIS), we found that the LST  obtained using the complete equation (Eq. 1) is 0.5 to 1.5 K lower than the short equation (Eq. 2). Also, plot-scale emissivity was estimated using observed sensible heat flux and surface-air temperature differences. Plot-scale emissivity obtained using the complete equation was generally between 0.8 to 0.98 while the short equation gave values between 0.9 to 0.98, for all land cover types. Despite additional input data for the complete equation, the uncertainty in plot-scale LST was not greater than if the short equation was used. Landscape-scale daytime LST obtained from satellite data (MODIS TERRA) were strongly correlated with our plot-scale estimates, but on average higher by 0.5 to 9 K, regardless of the equation used. However, for most sites, the correspondence between MODIS TERRA LST and retrieved plot-scale LST estimates increased significantly if plot-scale emissivity was used instead of the landscape-scale emissivity obtained from satellite data.</p>


Author(s):  
S. V. S. Sai Krishna ◽  
P. Manavalan ◽  
P. V. N. Rao

Daily net surface radiation fluxes are estimated for Indian land mass at spatial grid intervals of 0.1 degree. Two approaches are employed to obtain daily net radiation for four sample days viz., November 19, 2013, December 16, 2013, January 8, 2014 and March 20, 2014. Both the approaches compute net shortwave and net longwave fluxes, separately and sum them up to obtain net radiation. The first approach computes net shortwave radiation using daily insolation product of Kalpana VHRR and 15 days time composited broadband albedo product of Oceansat OCM2. The net outgoing longwave radiation is computed using Stefan Boltzmann equation corrected for humidity and cloudiness. In the second approach, instantaneous clear-sky net-shortwave radiation is estimated using computed clear-sky incoming shortwave radiation and the gridded MODIS 16-day time composited albedo product. The net longwave radiation is obtained by estimating outgoing and incoming longwave radiation fluxes, independently. In this, MODIS derived surface emissivity and skin temperature parameters are used for estimating outgoing longwave radiation component. In both the approaches, surface air temperature data required for estimation of net longwave radiation fluxes are extracted from India Meteorological Department’s (IMD) Automatic Weather Station (AWS) records. Estimates by the two different approaches are evaluated by comparing daily net radiation fluxes with CERES based estimates corresponding to the sample days, through statistical measures. The estimated all sky daily net radiation using the first approach compared well with CERES SYN1deg daily average net radiation with r<sup>2</sup> values of the order of 0.7 and RMS errors of the order of 8&ndash;16 w/m<sup>2</sup>.


2020 ◽  
Vol 12 (11) ◽  
pp. 1834
Author(s):  
Boxiong Qin ◽  
Biao Cao ◽  
Hua Li ◽  
Zunjian Bian ◽  
Tian Hu ◽  
...  

Surface upward longwave radiation (SULR) is a critical component in the calculation of the Earth’s surface radiation budget. Multiple clear-sky SULR estimation methods have been developed for high-spatial resolution satellite observations. Here, we comprehensively evaluated six SULR estimation methods, including the temperature-emissivity physical methods with the input of the MYD11/MYD21 (TE-MYD11/TE-MYD21), the hybrid methods with top-of-atmosphere (TOA) linear/nonlinear/artificial neural network regressions (TOA-LIN/TOA-NLIN/TOA-ANN), and the hybrid method with bottom-of-atmosphere (BOA) linear regression (BOA-LIN). The recently released MYD21 product and the BOA-LIN—a newly developed method that considers the spatial heterogeneity of the atmosphere—is used initially to estimate SULR. In addition, the four hybrid methods were compared with simulated datasets. All the six methods were evaluated using the Moderate Resolution Imaging Spectroradiometer (MODIS) products and the Surface Radiation Budget Network (SURFRAD) in situ measurements. Simulation analysis shows that the BOA-LIN is the best one among four hybrid methods with accurate atmospheric profiles as input. Comparison of all the six methods shows that the TE-MYD21 performed the best, with a root mean square error (RMSE) and mean bias error (MBE) of 14.0 and −0.2 W/m2, respectively. The RMSE of BOA-LIN, TOA-NLIN, TOA-LIN, TOA-ANN, and TE-MYD11 are equal to 15.2, 16.1, 17.2, 21.2, and 18.5 W/m2, respectively. TE-MYD21 has a much better accuracy than the TE-MYD11 over barren surfaces (NDVI < 0.3) and a similar accuracy over non-barren surfaces (NDVI ≥ 0.3). BOA-LIN is more stable over varying water vapor conditions, compared to other hybrid methods. We conclude that this study provides a valuable reference for choosing the suitable estimation method in the SULR product generation.


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