scholarly journals Assessment and Validation of i-Skyradiometer Retrievals Using Broadband Flux and MODIS Data

2014 ◽  
Vol 2014 ◽  
pp. 1-8
Author(s):  
S. Dipu ◽  
G. Pandithurai ◽  
A. S. Panicker ◽  
T. Takamura ◽  
Dong-In Lee ◽  
...  
Keyword(s):  
Radiative Transfer ◽  
Climate Models ◽  
Surface Radiation ◽  
Combination Method ◽  
New Combination ◽  
Radiative Transfer Model ◽  
Retrieval Algorithm ◽  
Transfer Model ◽  
Cloud Parameters ◽  
Radiation Measurements

Ground-based network of cloud measurements is presently limited and there exists uncertainty in the cloud microphysical parameters derived from ground-based measurements. Bias in the i-skyradiometer derived cloud optical depth (τc) and droplet effective radius (Reff) and the importance of these parameters in the parameterization of clouds in climate models have made us intend to develop a possible method for improving these parameters. A new combination method, which uses zenith sky transmittance and surface radiation measurements, has been proposed in the present study to improve the retrievals. The i-skyradiometer derived parametersτcandReffhave been provided as a first guess to a radiative transfer model (SBDART) and a new retrieval algorithm has been implemented to obtain the best combination ofτcandReffhaving minimum bias (−0.09 and −2.5) between the simulated global and diffuse fluxes at the surface with the collocated surface radiation measurements. The new retrieval method has improvedτcandReffvalues compared to those derived using the transmittance only method and are in good agreement with the MODIS satellite retrievals. The study therefore suggests a possible improvement of the i-skyradiometer derived cloud parameters using observed radiation fluxes and a radiative transfer model.

Impact of 3D cloud structures on tropospheric NO2 column measurements from UV-VIS sounders

2021 ◽  
Author(s):  
Huan Yu ◽  
Arve Kylling ◽  
Claudia Emde ◽  
Bernhard Mayer ◽  
Michel Van Roozendael ◽  
...  
Keyword(s):  
Radiative Transfer ◽  
Synthetic Data ◽  
Sensitivity Study ◽  
Trace Gas ◽  
Radiative Transfer Model ◽  
Retrieval Algorithm ◽  
Transfer Model ◽  
Boundary Layer Clouds ◽  
Cloud Parameters ◽  
The Impact

<p>Operational retrievals of tropospheric trace gases from space-borne spectrometers are made using 1D radiative transfer models. To minimize cloud effects generally only partially cloudy pixels are analysed using simplified cloud contamination treatments based on radiometric cloud fraction estimates and photon path length corrections based on oxygen collision pair (O2-O2) or O2A-absorption band measurements. In reality, however, the impact of clouds can be much more complex, involving unresolved sub-pixel clouds, scattering of clouds in neighbouring pixels, and cloud shadow effects, such that 3D radiation scattering from unresolved boundary layer clouds may give significant biases in the trace gas retrievals. In order to quantify this impact, we use the MYSTIC 3D radiative transfer model to generate synthetic data. The realistic 3D cloud fields, needed for MYSTIC input, are generated by the ICOsahedral Non-hydrostatic (ICON) atmosphere model for a region including Germany, the Netherlands and parts of other surrounding countries. The retrieval algorithm is applied to the synthetic data and comparison to the known input trace gas concentrations yields the retrieval error due to 3D cloud effects. <br>In this study, we study NO2, which is a key tropospheric trace gas measured by TROPOMI and the future atmospheric Sentinels (S4 and S5). The work starts with a sensitivity study for the simulations with a simple 2D box cloud. The influence of cloud parameters (e.g., cloud top height, cloud optical thickness), observation geometry, and spatial resolution are studied, and the most significant dependences of retrieval biases are identified and investigated. Several approaches to correct the NO2 retrieval in the cloud shadow are explored and ultimately applied to both synthetic data with realistic 3D clouds and real observations.</p>

scholarly journals Potential of Hyperspectral Thermal Infrared Spaceborne Measurements to Retrieve Ice Cloud Physical Properties: Case Study of IASI and IASI-NG

2020 ◽  
Vol 13 (1) ◽  
pp. 116
Author(s):  
Lucie Leonarski ◽  
Laurent C.-Labonnote ◽  
Mathieu Compiègne ◽  
Jérôme Vidot ◽  
Anthony J. Baran ◽  
...  
Keyword(s):  
Radiative Transfer ◽  
Signal To Noise Ratio ◽  
Thermal Infrared ◽  
Radiative Transfer Model ◽  
Retrieval Algorithm ◽  
Transfer Model ◽  
Water Path ◽  
Ice Cloud ◽  
Ice Water Path ◽  
Ice Water

The present study aims to quantify the potential of hyperspectral thermal infrared sounders such as the Infrared Atmospheric Sounding Interferometer (IASI) and the future IASI next generation (IASI-NG) for retrieving the ice cloud layer altitude and thickness together with the ice water path. We employed the radiative transfer model Radiative Transfer for TOVS (RTTOV) to simulate cloudy radiances using parameterized ice cloud optical properties. The radiances have been computed from an ice cloud profile database coming from global operational short-range forecasts at the European Center for Medium-range Weather Forecasts (ECMWF) which encloses the normal conditions, typical variability, and extremes of the atmospheric properties over one year (Eresmaa and McNally (2014)). We performed an information content analysis based on Shannon’s formalism to determine the amount and spectral distribution of the information about ice cloud properties. Based on this analysis, a retrieval algorithm has been developed and tested on the profile database. We considered the signal-to-noise ratio of each specific instrument and the non-retrieved atmospheric and surface parameter errors. This study brings evidence that the observing system provides information on the ice water path (IWP) as well as on the layer altitude and thickness with a convergence rate up to 95% and expected errors that decrease with cloud opacity until the signal saturation is reached (satisfying retrievals are achieved for clouds whose IWP is between about 1 and 300 g/m2).

scholarly journals Comparison of measured brightness temperatures from SMOS with modelled ones from ORCHIDEE and H-TESSEL over the Iberian Peninsula

2015 ◽  
Vol 12 (12) ◽  
pp. 13019-13067
Author(s):  
A. Barella-Ortiz ◽  
J. Polcher ◽  
P. de Rosnay ◽  
M. Piles ◽  
E. Gelati
Keyword(s):  
Soil Moisture ◽  
Radiative Transfer ◽  
Iberian Peninsula ◽  
Land Surface ◽  
Function Analysis ◽  
Microwave Emission ◽  
Radiative Transfer Model ◽  
Retrieval Algorithm ◽  
Transfer Model ◽  
Brightness Temperatures

Abstract. L-Band radiometry is considered to be one of the most suitable techniques to estimate surface soil moisture by means of remote sensing. Brightness temperatures are key in this process, as they are the main input in the retrieval algorithm. The work exposed compares brightness temperatures measured by the Soil Moisture and Ocean Salinity (SMOS) mission to two different sets of modelled ones, over the Iberian Peninsula from 2010 to 2012. The latter were estimated using a radiative transfer model and state variables from two land surface models: (i) ORganising Carbon and Hydrology In Dynamic EcosystEms (ORCHIDEE) and (ii) Hydrology – Tiled ECMWF Scheme for Surface Exchanges over Land (H-TESSEL). The radiative transfer model used is the Community Microwave Emission Model (CMEM). A good agreement in the temporal evolution of measured and modelled brightness temperatures is observed. However, their spatial structures are not consistent between them. An Empirical Orthogonal Function analysis of the brightness temperature's error identifies a dominant structure over the South-West of the Iberian Peninsula which evolves during the year and is maximum in Fall and Winter. Hypotheses concerning forcing induced biases and assumptions made in the radiative transfer model are analysed to explain this inconsistency, but no candidate is found to be responsible for it at the moment. Further hypotheses are proposed at the end of the paper.

scholarly journals Gauss–Seidel limb scattering (GSLS) radiative transfer model development in support of the Ozone Mapping and Profiler Suite (OMPS) limb profiler mission

2015 ◽  
Vol 15 (6) ◽  
pp. 3007-3020 ◽  
Author(s):  
R. Loughman ◽  
D. Flittner ◽  
E. Nyaku ◽  
P. K. Bhartia
Keyword(s):  
Radiative Transfer ◽  
Model Development ◽  
Model Atmosphere ◽  
Radiative Transfer Model ◽  
Retrieval Algorithm ◽  
Transfer Model ◽  
Process Data ◽  
Variable Surface ◽  
Height Dependence ◽  
Minimal Effort

Abstract. The Gauss–Seidel limb scattering (GSLS) radiative transfer (RT) model simulates the transfer of solar radiation through the atmosphere and is imbedded in the retrieval algorithm used to process data from the Ozone Mapping and Profiler Suite (OMPS) limb profiler (LP), which was launched on the Suomi NPP satellite in October 2011. A previous version of this model has been compared with several other limb scattering RT models in previous studies, including Siro, MCC++, CDIPI, LIMBTRAN, SASKTRAN, VECTOR, and McSCIA. To address deficiencies in the GSLS radiance calculations revealed in earlier comparisons, several recent changes have been added that improve the accuracy and flexibility of the GSLS model, including 1. improved treatment of the variation of the extinction coefficient with altitude, both within atmospheric layers and above the nominal top of the atmosphere; 2. addition of multiple-scattering source function calculations at multiple solar zenith angles along the line of sight (LOS); 3. introduction of variable surface properties along the limb LOS, with minimal effort required to add variable atmospheric properties along the LOS as well; 4. addition of the ability to model multiple aerosol types within the model atmosphere. The model improvements 1 and 2 are verified by comparison to previously published results (using standard radiance tables whenever possible), demonstrating significant improvement in cases for which previous versions of the GSLS model performed poorly. The single-scattered radiance errors that were as high as 4% in earlier studies are now generally reduced to 0.3%, while total radiance errors generally decline from 10% to 1–3%. In all cases, the tangent height dependence of the GSLS radiance error is greatly reduced.

Evaluation of shortwave radiation fluxes in the multi-layer SPARTACUS-Urban scheme using DART

2021 ◽  
Author(s):  
Megan Stretton ◽  
William Morrison ◽  
Robin Hogan ◽  
Sue Grimmond
Keyword(s):  
Radiative Transfer ◽  
Urban Form ◽  
Climate Models ◽  
Weather Prediction ◽  
Computational Cost ◽  
Three Dimensional ◽  
Shortwave Radiation ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Urban Structure

<p>The heterogenous structure of cities impacts radiative exchanges (e.g. albedo and heat storage). Numerical weather prediction (NWP) models often characterise the urban structure with an infinite street canyon – but this does not capture the three-dimensional urban form. SPARTACUS-Urban (SU) - a fast, multi-layer radiative transfer model designed for NWP - is evaluated using the explicit Discrete Anisotropic Radiative Transfer (DART) model for shortwave fluxes across several model domains – from a regular array of cubes to real cities .</p><p>SU agrees with DART (errors < 5.5% for all variables) when the SU assumptions of building distribution are fulfilled (e.g. randomly distribution). For real-world areas with pitched roofs, SU underestimates the albedo (< 10%) and shortwave transmission to the surface (< 15%), and overestimates wall-plus-roof absorption (9-27%), with errors increasing with solar zenith angle. SU should be beneficial to weather and climate models, as it allows more realistic urban form (cf. most schemes) without large increases in computational cost.</p>

scholarly journals Evaluation of Cirrus Parameterizations for Radiative Flux Computations in Climate Models Using TOVS–ScaRaB Satellite Observations

2007 ◽  
Vol 20 (17) ◽  
pp. 4459-4475 ◽  
Author(s):  
C. J. Stubenrauch ◽  
F. Eddounia ◽  
J. M. Edwards ◽  
A. Macke
Keyword(s):  
Optical Properties ◽  
Radiative Transfer ◽  
Climate Models ◽  
Radiative Flux ◽  
Satellite Observations ◽  
Radiation Budget ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Ice Crystal ◽  
Infrared Observation

Abstract Combined simultaneous satellite observations are used to evaluate the performance of parameterizations of the microphysical and optical properties of cirrus clouds used for radiative flux computations in climate models. Atmospheric and cirrus properties retrieved from Television and Infrared Observation Satellite (TIROS-N) Operational Vertical Sounder (TOVS) observations are given as input to the radiative transfer model developed for the Met Office climate model to simulate radiative fluxes at the top of the atmosphere (TOA). Simulated cirrus shortwave (SW) albedos are then compared to those retrieved from collocated Scanner for Radiation Budget (ScaRaB) observations. For the retrieval, special care has been given to angular direction models. Three parameterizations of cirrus ice crystal optical properties are represented in the Met Office radiative transfer model. These parameterizations are based on different physical approximations and different hypotheses on crystal habit. One parameterization assumes pristine ice crystals and two ice crystal aggregates. By relating the cirrus ice water path (IWP) retrieved from the effective infrared emissivity to the cirrus SW albedo, differences between the parameterizations are amplified. This study shows that pristine crystals seem to be plausible only for cirrus with IWP less than 30 g m−2. For larger IWP, ice crystal aggregates lead to cirrus SW albedos in better agreement with the observations. The data also indicate that climate models should allow the cirrus effective ice crystal diameter (De) to increase with IWP, especially in the range up to 30 g m−2. For cirrus with IWP less than 20 g m−2, this would lead to SW albedos that are about 0.02 higher than the ones of a constant De of 55 μm.

scholarly journals Mesoscale Simulations of Australian Direct Normal Irradiance, Featuring an Extreme Dust Event

2018 ◽  
Vol 57 (3) ◽  
pp. 493-515 ◽  
Author(s):  
S. K. Mukkavilli ◽  
A. A. Prasad ◽  
R. A. Taylor ◽  
A. Troccoli ◽  
M. J. Kay
Keyword(s):  
Radiative Transfer ◽  
Climate Models ◽  
Global Climate ◽  
Weather Prediction ◽  
Wrf Model ◽  
Global Climate Models ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Dust Event ◽  
Direct Normal Irradiance

AbstractDirect normal irradiance (DNI) is the main input for concentrating solar power (CSP) technologies—an important component in future energy scenarios. DNI forecast accuracy is sensitive to radiative transfer schemes (RTSs) and microphysics in numerical weather prediction (NWP) models. Additionally, NWP models have large regional aerosol uncertainties. Dust aerosols can significantly attenuate DNI in extreme cases, with marked consequences for applications such as CSP. To date, studies have not compared the skill of different physical parameterization schemes for predicting hourly DNI under varying aerosol conditions over Australia. The authors address this gap by aiming to provide the first Weather and Forecasting (WRF) Model DNI benchmarks for Australia as baselines for assessing future aerosol-assimilated models. Annual and day-ahead simulations against ground measurements at selected sites focusing on an extreme dust event are run. Model biases are assessed for five shortwave RTSs at 30- and 10-km grid resolutions, along with the Thompson aerosol-aware scheme in three different microphysics configurations: no aerosols, fixed optical properties, and monthly climatologies. From the annual simulation, the best schemes were the Rapid Radiative Transfer Model for global climate models (RRTMG), followed by the new Goddard and Dudhia schemes, despite the relative simplicity of the latter. These top three RTSs all had 1.4–70.8 W m−2 lower mean absolute error than persistence. RRTMG with monthly aerosol climatologies was the best combination. The extreme dust event had large DNI mean bias overpredictions (up to 4.6 times), compared to background aerosol results. Dust storm–aware DNI forecasts could benefit from RRTMG with high-resolution aerosol inputs.

scholarly journals Aerosol trends as a potential driver of regional climate in the central United States: evidence from observations

2017 ◽  
Vol 17 (22) ◽  
pp. 13559-13572 ◽  
Author(s):  
Daniel H. Cusworth ◽  
Loretta J. Mickley ◽  
Eric M. Leibensperger ◽  
Michael J. Iacono
Keyword(s):  
United States ◽  
Radiative Transfer ◽  
Southeastern United States ◽  
Radiant Energy ◽  
Surface Radiation ◽  
Radiation Budget ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Clear Sky

Abstract. In situ surface observations show that downward surface solar radiation (SWdn) over the central and southeastern United States (US) has increased by 0.58–1.0 Wm−2 a−1 over the 2000–2014 time frame, simultaneously with reductions in US aerosol optical depth (AOD) of 3.3–5.0  ×  10−3 a−1. Establishing a link between these two trends, however, is challenging due to complex interactions between aerosols, clouds, and radiation. Here we investigate the clear-sky aerosol–radiation effects of decreasing US aerosols on SWdn and other surface variables by applying a one-dimensional radiative transfer to 2000–2014 measurements of AOD at two Surface Radiation Budget Network (SURFRAD) sites in the central and southeastern United States. Observations characterized as clear-sky may in fact include the effects of thin cirrus clouds, and we consider these effects by imposing satellite data from the Clouds and Earth's Radiant Energy System (CERES) into the radiative transfer model. The model predicts that 2000–2014 trends in aerosols may have driven clear-sky SWdn trends of +1.35 Wm−2 a−1 at Goodwin Creek, MS, and +0.93 Wm−2 a−1 at Bondville, IL. While these results are consistent in sign with observed trends, a cross-validated multivariate regression analysis shows that AOD reproduces 20–26 % of the seasonal (June–September, JJAS) variability in clear-sky direct and diffuse SWdn at Bondville, IL, but none of the JJAS variability at Goodwin Creek, MS. Using in situ soil and surface flux measurements from the Ameriflux network and Illinois Climate Network (ICN) together with assimilated meteorology from the North American Land Data Assimilation System (NLDAS), we find that sunnier summers tend to coincide with increased surface air temperature and soil moisture deficits in the central US. The 1990–2015 trends in the NLDAS SWdn over the central US are also of a similar magnitude to our modeled 2000–2014 clear-sky trends. Taken together, these results suggest that climate and regional hydrology in the central US are sensitive to the recent reductions in aerosol concentrations. Our work has implications for severely polluted regions outside the US, where improvements in air quality due to reductions in the aerosol burden could inadvertently pose an enhanced climate risk.

scholarly journals Improved OSIRIS NO<sub>2</sub> retrieval algorithm: Description and validation

2016 ◽  
Author(s):  
Christopher E. Sioris ◽  
Landon A. Rieger ◽  
Nicholas D. Lloyd ◽  
Adam E. Bourassa ◽  
Chris Z. Roth ◽  
...  
Keyword(s):  
Radiative Transfer ◽  
Nitrogen Dioxide ◽  
Polar Vortex ◽  
Bias Reduction ◽  
Radiative Transfer Model ◽  
Retrieval Algorithm ◽  
Transfer Model ◽  
Reconstruction Technique ◽  
Spectral Fitting ◽  
Infrared Imager

Abstract. A new retrieval algorithm for OSIRIS (Optical Spectrograph and Infrared Imager System) nitrogen dioxide (NO2) profiles is described and validated. The algorithm relies on spectral fitting to obtain line-of-sight (LOS) column densities of NO2 followed by inversion using an algebraic reconstruction technique and the SaskTran spherical radiative transfer model to obtain vertical profiles of local number density. The validation covers different latitudes (tropical to polar), years (2002–2012), all seasons (winter, spring, summer, and autumn), different concentrations of nitrogen dioxide (from deNOxified polar vortex to polar summer), a large range of solar zenith angles (68.6 to 90.5°) and altitudes between 10.5 and 39 km, thereby covering the full retrieval range of a typical OSIRIS NO2 profile. The use of a larger spectral fitting window than used in previous retrievals reduces retrieval uncertainties and the scatter in the retrieved profiles due to noisy radiances. Improvements are also demonstrated through the validation in terms of bias reduction at 15–17 km relative to the OSIRIS operational v3.0 algorithm. By accounting for the diurnal variation along the LOS in the two-dimensional radiative transfer model, the scatter of the differences relative to the correlative balloon NO2 profile data is reduced.

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