Assessment of Radiative Effect of Hydrometeors in Rapid Radiative Transfer Model in Support of Satellite Cloud and Precipitation Microwave Data Assimilation

2016 ◽  
pp. 337-360
Author(s):  
Peiming Dong ◽  
Wei Han ◽  
Wei Li ◽  
Shuanglong Jin
Keyword(s):  
Radiative Transfer ◽  
Data Assimilation ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Radiative Effect ◽  
Microwave Data

Radiative forcing over the Arctic of aerosols from the August 2017 Canadian and Greenlandic wildfires

2021 ◽  
Author(s):  
Filippo Calì Quaglia ◽  
Daniela Meloni ◽  
Alcide Giorgio di Sarra ◽  
Tatiana Di Iorio ◽  
Virginia Ciardini ◽  
...  
Keyword(s):  
Radiative Transfer ◽  
Radiative Forcing ◽  
Solar Zenith Angle ◽  
Surface Albedo ◽  
High Arctic ◽  
The Arctic ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Aerosol Layer ◽  
Radiative Effect

<p>Extended and intense wildfires occurred in Northern Canada and, unexpectedly, on the Greenlandic West coast during summer 2017. The thick smoke plume emitted into the atmosphere was transported to the high Arctic, producing one of the largest impacts ever observed in the region. Evidence of Canadian and Greenlandic wildfires was recorded at the Thule High Arctic Atmospheric Observatory (THAAO, 76.5°N, 68.8°W, www.thuleatmos-it.it) by a suite of instruments managed by ENEA, INGV, Univ. of Florence, and NCAR. Ground-based observations of the radiation budget have allowed quantification of the surface radiative forcing at THAAO. </p><p>Excess biomass burning chemical tracers such as CO, HCN, H2CO, C2H6, and NH3 were  measured in the air column above Thule starting from August 19 until August 23. The aerosol optical depth (AOD) reached a peak value of about 0.9 on August 21, while an enhancement of wildfire compounds was  detected in PM10. The measured shortwave radiative forcing was -36.7 W/m2 at 78° solar zenith angle (SZA) for AOD=0.626.</p><p>MODTRAN6.0 radiative transfer model (Berk et al., 2014) was used to estimate the aerosol radiative effect and the heating rate profiles at 78° SZA. Measured temperature profiles, integrated water vapour, surface albedo, spectral AOD and aerosol extinction profiles from CALIOP onboard CALIPSO were used as model input. The peak  aerosol heating rate (+0.5 K/day) was  reached within the aerosol layer between 8 and 12 km, while the maximum radiative effect (-45.4 W/m2) is found at 3 km, below the largest aerosol layer.</p><p>The regional impact of the event that occurred on August 21 was investigated using a combination of atmospheric radiative transfer modelling with measurements of AOD and ground surface albedo from MODIS. The aerosol properties used in the radiative transfer model were constrained by in situ measurements from THAAO. Albedo data over the ocean have been obtained from Jin et al. (2004). Backward trajectories produced through HYSPLIT simulations (Stein et al., 2015) were also employed to trace biomass burning plumes.</p><p>The radiative forcing efficiency (RFE) over land and ocean was derived, finding values spanning from -3 W/m2 to -132 W/m2, depending on surface albedo and solar zenith angle. The fire plume covered a vast portion of the Arctic, with large values of the daily shortwave RF (< -50 W/m2) lasting for a few days. This large amount of aerosol is expected to influence cloud properties in the Arctic, producing significant indirect radiative effects.</p>

scholarly journals Parameterization of Vegetation Scattering Albedo in the Tau-Omega Model for Soil Moisture Retrieval on Croplands

2020 ◽  
Vol 12 (18) ◽  
pp. 2939
Author(s):  
Chang-Hwan Park ◽  
Thomas Jagdhuber ◽  
Andreas Colliander ◽  
Johan Lee ◽  
Aaron Berg ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Radiative Transfer ◽  
Data Assimilation ◽  
Brightness Temperature ◽  
Microwave Remote Sensing ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Time Varying ◽  
Vegetation Fraction ◽  
Omega Model

An accurate radiative transfer model (RTM) is essential for the retrieval of soil moisture (SM) from microwave remote sensing data, such as the passive microwave measurements from the Soil Moisture Active Passive (SMAP) mission. This mission delivers soil moisture products based upon L-band brightness temperature data, via retrieval algorithms for surface and root-zone soil moisture, the latter is retrieved using data assimilation and model support. We found that the RTM based on the tau-omega (τ-ω) model can suffer from significant errors over croplands in the simulation of brightness temperature (Tb) (in average between −9.4K and +12.0K for single channel algorithm (SCA); −8K and +9.7K for dual-channel algorithm (DCA)) if the vegetation scattering albedo (omega) is set constant and temporal variations are not considered. In order to reduce this uncertainty, we propose a time-varying parameterization of omega for the widely established zeroth order radiative transfer τ-ω model. The main assumption is that omega can be expressed by a functional relationship between vegetation optical depth (tau) and the Green Vegetation Fraction (GVF). Assuming allometry in the tau-omega relationship, a power-law function was established and it is supported by correlating measurements of tau and GVF. With this relationship, both tau and omega increase during the development of vegetation. The application of the proposed time-varying vegetation scattering albedo results in a consistent improvement for the unbiased root mean square error of 16% for SCA and 15% for DCA. The reduction for positive and negative biases was 45% and 5% for SCA and 26% and 12% for DCA, respectively. This indicates that vegetation dynamics within croplands are better represented by a time-varying single scattering albedo. Based on these results, we anticipate that the time-varying omega within the tau-omega model will help to mitigate potential estimation errors in the current SMAP soil moisture products (SCA and DCA). Furthermore, the improved tau-omega model might serve as a more accurate observation operator for SMAP data assimilation in weather and climate prediction model.

SHDOMPPDA: A Radiative Transfer Model for Cloudy Sky Data Assimilation

2007 ◽  
Vol 64 (11) ◽  
pp. 3854-3864 ◽  
Author(s):  
K. Franklin Evans
Keyword(s):  
Radiative Transfer ◽  
Data Assimilation ◽  
Spherical Harmonics ◽  
Forward Model ◽  
Radiative Transfer Model ◽  
Computational Time ◽  
Transfer Model ◽  
Discrete Ordinate Method ◽  
Discrete Ordinate ◽  
Plane Parallel

Abstract The spherical harmonics discrete ordinate method for plane-parallel data assimilation (SHDOMPPDA) model is an unpolarized plane-parallel radiative transfer forward model, with corresponding tangent linear and adjoint models, suitable for use in assimilating cloudy sky visible and infrared radiances. It is derived from the spherical harmonics discrete ordinate method plane-parallel (SHDOMPP, also described in this article) version of the spherical harmonics discrete ordinate method (SHDOM) model for three-dimensional atmospheric radiative transfer. The inputs to the SHDOMPPDA forward model are profiles of pressure, temperature, water vapor, and mass mixing ratio and number concentration for a number of hydrometeor species. Hydrometeor optical properties, including detailed phase functions, are determined from lookup tables as a function of mass mean radius. The SHDOMPP and SHDOMPPDA algorithms and construction of the tangent-linear and adjoint models are described. The SHDOMPPDA forward model is validated against the Discrete Ordinate Radiative Transfer Model (DISORT) by comparing upwelling radiances in multiple directions from 100 cloud model columns at visible and midinfrared wavelengths. For this test in optically thick clouds the computational time for SHDOMPPDA is comparable to DISORT for visible reflection, and roughly 5 times faster for thermal emission. The tangent linear and adjoint models are validated by comparison to finite differencing of the forward model.

scholarly journals Advanced Doubling–Adding Method for Radiative Transfer in Planetary Atmospheres

2006 ◽  
Vol 63 (12) ◽  
pp. 3459-3465 ◽  
Author(s):  
Quanhua Liu ◽  
Fuzhong Weng
Keyword(s):  
Radiative Transfer ◽  
Data Assimilation ◽  
Satellite Data ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Thermal Source ◽  
New Development ◽  
Joint Center ◽  
Computational Resources ◽  
Computation Codes

The doubling–adding method (DA) is one of the most accurate tools for detailed multiple-scattering calculations. The principle of the method goes back to the nineteenth century in a problem dealing with reflection and transmission by glass plates. Since then the doubling–adding method has been widely used as a reference tool for other radiative transfer models. The method has never been used in operational applications owing to tremendous demand on computational resources from the model. This study derives an analytical expression replacing the most complicated thermal source terms in the doubling–adding method. The new development is called the advanced doubling–adding (ADA) method. Thanks also to the efficiency of matrix and vector manipulations in FORTRAN 90/95, the advanced doubling–adding method is about 60 times faster than the doubling–adding method. The radiance (i.e., forward) computation code of ADA is easily translated into tangent linear and adjoint codes for radiance gradient calculations. The simplicity in forward and Jacobian computation codes is very useful for operational applications and for the consistency between the forward and adjoint calculations in satellite data assimilation. ADA is implemented into the Community Radiative Transfer Model (CRTM) developed at the U.S. Joint Center for Satellite Data Assimilation.

scholarly journals Development of an OMI AI data assimilation scheme for aerosol modeling over bright surfaces – a step toward direct radiance assimilation in the UV spectrum

2020 ◽  
Author(s):  
Jianglong Zhang ◽  
Robert J. D. Spurr ◽  
Jeffrey S. Reid ◽  
Peng Xian ◽  
Peter R. Colarco ◽  
...  
Keyword(s):  
Radiative Transfer ◽  
Data Assimilation ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Uv Spectrum ◽  
Model Simulations ◽  
Monitoring Instrument ◽  
Radiance Assimilation ◽  
Data Assimilation Scheme ◽  
Assimilation Scheme

Abstract. Using the Vector LInearized Discrete Ordinate Radiative Transfer (VLIDORT) code as the main driver for forward model simulations, a first-of-its-kind data assimilation scheme has been developed for assimilating Ozone Monitoring Instrument (OMI) aerosol index (AI) measurements into the Naval Aerosol Analysis and Predictive System (NAAPS). This study suggests both RMSE and absolute errors can be significantly reduced in NAAPS analyses with the use of OMI AI data assimilation, when compared to values from NAAPS natural runs. Improvements in model simulations demonstrate the utility of OMI AI data assimilation for improving the accuracy of aerosol model analysis over cloudy regions and bright surfaces. However, the OMI AI data assimilation alone does not out-perform aerosol data assimilation that uses passive-based aerosol optical depth (AOD) products over cloud free skies and dark surfaces. Further, as AI assimilation requires the deployment of a fully-multiple-scatter-aware radiative transfer model in the forward simulations, computational burden is an issue. Nevertheless, the newly-developed modeling system contains the necessary ingredients for assimilation of radiances in the ultra-violet (UV) spectrum, and our study shows the potential of direct radiance assimilation at both UV and visible spectrums, possibly coupled with AOD assimilation, for aerosol applications in the future. Additional data streams can be added, including data from TROPOspheric Monitoring Instrument (TROPOMI), Ozone Mapping and Profiler Suite (OMPS) and eventually with the Plankton, Aerosol, Cloud and ocean Ecosystem (PACE) mission.

scholarly journals Longwave Radiative Effect of the Cloud-Aerosol Transition Zone Based on CERES Observations

2021 ◽  
Author(s):  
Babak Jahani ◽  
Hendrik Andersen ◽  
Josep Calbó ◽  
Josep-Abel González ◽  
Jan Cermak
Keyword(s):  
Radiative Transfer ◽  
Transition Zone ◽  
Radiant Energy ◽  
Energy System ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Radiative Effect ◽  
Radiative Effects ◽  
Clear Sky ◽  
Moderate Resolution Imaging Spectroradiometer

Abstract. This study presents an approach for quantification of cloud-aerosol transition zone broadband longwave radiative effects at the top of the atmosphere (TOA) during daytime over the ocean, based on satellite observations and radiative transfer simulation. Specifically, we used several products from MODIS (Moderate Resolution Imaging Spectroradiometer) and CERES (Clouds and the Earth’s Radiant Energy System) sensors for identification and selection of CERES footprints with horizontally homogeneous transition zone and clear-sky conditions. For the selected transition zone footprints, radiative effect was calculated as the difference between the instantaneous CERES TOA upwelling broadband longwave radiance observations and corresponding clear-sky radiance simulations. The clear-sky radiances were simulated using the Santa Barbara DISORT Atmospheric Radiative Transfer model fed by the hourly ERA5 reanalysis (fifth generation ECMWF reanalysis) atmospheric and surface data. The CERES radiance observations corresponding to the clear-sky footprints detected were also used for validating the simulated clear-sky radiances. We tested this approach using the radiative measurements made by the MODIS and CERES instruments onboard Aqua platform over the south-eastern Atlantic Ocean during August 2010. For the studied period and domain, transition zone radiative effect (given in flux units) is on average equal to 8.0 ± 3.7 W m−2 (heating effect; median: 5.4 W m−2), although cases with radiative effects as large as 50 W m−2 were found.

scholarly journals The Successive-Order-of-Interaction Radiative Transfer Model. Part II: Model Performance and Applications

2006 ◽  
Vol 45 (10) ◽  
pp. 1403-1413 ◽  
Author(s):  
Christopher W. O’Dell ◽  
Andrew K. Heidinger ◽  
Thomas Greenwald ◽  
Peter Bauer ◽  
Ralf Bennartz
Keyword(s):  
Radiative Transfer ◽  
Data Assimilation ◽  
Weather Prediction ◽  
Model Performance ◽  
Optimal Estimation ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Computationally Efficient ◽  
Wide Range ◽  
Infrared Wavelengths

Abstract Radiative transfer models for scattering atmospheres that are accurate yet computationally efficient are required for many applications, such as data assimilation in numerical weather prediction. The successive-order-of-interaction (SOI) model is shown to satisfy these demands under a wide range of conditions. In particular, the model has an accuracy typically much better than 1 K for most microwave and submillimeter cases in precipitating atmospheres. Its speed is found to be comparable to or faster than the commonly used though less accurate Eddington model. An adjoint has been written for the model, and so Jacobian sensitivities can be quickly calculated. In addition to a conventional error assessment, the correlation between errors in different microwave channels is also characterized. These factors combine to make the SOI model an appealing candidate for many demanding applications, including data assimilation and optimal estimation, from microwave to thermal infrared wavelengths.

scholarly journals An update on the RTTOV fast radiative transfer model (currently at version 12)

2018 ◽  
Author(s):  
Roger Saunders ◽  
James Hocking ◽  
Emma Turner ◽  
Peter Rayer ◽  
David Rundle ◽  
...  
Keyword(s):  
User Interface ◽  
Radiative Transfer ◽  
Data Assimilation ◽  
Graphical User Interface ◽  
Jacobian Matrix ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Satellite Retrieval ◽  
Radiance Assimilation ◽  
Atmospheric State

Abstract. This paper gives an update of the RTTOV (Radiative Transfer for TOVS) fast radiative transfer model which is widely used in the satellite retrieval and data assimilation communities. RTTOV is a fast radiative transfer model for simulating top of atmosphere radiances from passive visible, infrared and microwave downward-viewing satellite radiometers. In addition to the forward model, it also optionally computes the tangent linear, adjoint and Jacobian matrix providing changes in radiances for profile variable perturbations assuming a linear relationship about a given atmospheric state. This makes it a useful tool for developing physical retrievals from satellite radiances, for direct radiance assimilation in NWP models, for simulating future instruments and for training or teaching with a graphical user interface. An overview of the RTTOV model is given highlighting the updates and increased capability of the latest versions and gives some examples of its current performance when compared with more accurate line by line radiative transfer models and a few selected observations. The improvement over the original version of the model released in 1999 is demonstrated.

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