Retrieving clear-sky atmospheric parameters from SEVIRI and ABI infrared radiances

2008 ◽  
Vol 113 (D15) ◽  
Author(s):  
Xin Jin ◽  
Jun Li ◽  
Timothy J. Schmit ◽  
Jinlong Li ◽  
Mitchell D. Goldberg ◽  
...  
Keyword(s):  
Atmospheric Parameters ◽  
Clear Sky ◽  
Infrared Radiances

scholarly journals Sensitivity of Atmospheric Motion Vectors Height Assignment Methods to Semitransparent Cloud Properties Using Simulated Meteosat-8 Radiances

2010 ◽  
Vol 49 (6) ◽  
pp. 1205-1218 ◽  
Author(s):  
Régis Borde ◽  
Philippe Dubuisson
Keyword(s):  
Initial Pressure ◽  
Cloud Microphysics ◽  
Atmospheric Parameters ◽  
Ice Clouds ◽  
Clear Sky ◽  
Cloud Properties ◽  
Atmospheric Motion ◽  
Height Assignment ◽  
Cloud Top Pressure ◽  
Atmospheric Motion Vectors

Abstract This paper presents the sensitivity to various atmospheric parameters of two height assignment methods that aim to retrieve the cloud-top height of semitransparent clouds. The use of simulated Meteosat-8 radiances has the advantage that the pressure retrieved by a given method can be compared to the initial pressure set to the cloud in the model, which is exactly known. The methods retrieve the pressure of a perfectly opaque cloud to within a few hectopascals. However, considering more realistic ice clouds, methods are sensitive to all of the tested atmospheric parameters and, especially, to the cloud microphysics, which can bias the results of the CO2-slicing method by several tens of hectopascals. The cloud-top pressure retrieval is especially difficult for thinner clouds with optical thicknesses smaller than 2, for which the errors can reach several tens of hectopascals. The methods have also been tested after introducing realistic perturbations in the temperature and humidity profiles and on the clear-sky surface radiances. The corresponding averages of errors on the retrieved pressures are also very large, especially for thin clouds. In multilayer cloud situations the height assignment methods do not work properly, placing the cloud-top height somewhere between the two cloud layers for most cirrus cloud layers with optical thicknesses between 0.1 and 10.

scholarly journals All-sky assimilation of infrared radiances sensitive to mid- and upper-tropospheric moisture and cloud

2019 ◽  
Vol 12 (9) ◽  
pp. 4903-4929 ◽  
Author(s):  
Alan J. Geer ◽  
Stefano Migliorini ◽  
Marco Matricardi
Keyword(s):  
Weather Forecasting ◽  
Deep Convection ◽  
Cloud Detection ◽  
Clear Sky ◽  
Atmospheric Sounding ◽  
Beneficial Impact ◽  
Infrared Radiances ◽  
The Tropics ◽  
The Impact ◽  
Better Than

Abstract. All-sky assimilation of infrared (IR) radiances has not yet become operational at any weather forecasting centre, but it promises to bring new observations in sensitive areas and avoid the need for cloud detection. A new all-sky IR configuration gives results comparable to (and in some areas better than) clear-sky assimilation of the same data, meaning that operational implementation is now feasible. The impact of seven upper-tropospheric water vapour (WV) sounding channels from the Infrared Atmospheric Sounding Interferometer (IASI) is evaluated in both all-sky and clear-sky approaches. All-sky radiative transfer simulations (and the forecast model's cloud fields) are now sufficiently accurate that systematic errors are comparable to those of clear-sky assimilation outside of a few difficult areas such as deep convection. All-sky assimilation brings 65 % more data than clear-sky assimilation globally, with the biggest increases in midlatitude storm tracks and tropical convective areas. However, all-sky gives slightly less weight to any one observation than in the clear-sky approach. In the midlatitudes, all-sky and clear-sky assimilation have similarly beneficial impact on mid- and upper-tropospheric dynamical forecast fields. Here the addition of data in cloudy areas is offset by the slightly lower weight given to the observations. But in the tropics, all-sky assimilation is significantly more beneficial than clear-sky assimilation, with improved dynamical short-range forecasts throughout the troposphere and stratosphere.

scholarly journals Uncertainties of parameterized surface downward clear-sky shortwave and all-sky longwave radiation.

2012 ◽  
Vol 12 (11) ◽  
pp. 5077-5098 ◽  
Author(s):  
S. Gubler ◽  
S. Gruber ◽  
R. S. Purves
Keyword(s):  
Model Uncertainty ◽  
Input Data ◽  
Monte Carlo Model ◽  
Surface Radiation ◽  
Radiation Budget ◽  
Atmospheric Parameters ◽  
Clear Sky ◽  
Environmental Models ◽  
Relative Standard ◽  
Downward Radiation

Abstract. As many environmental models rely on simulating the energy balance at the Earth's surface based on parameterized radiative fluxes, knowledge of the inherent model uncertainties is important. In this study we evaluate one parameterization of clear-sky direct, diffuse and global shortwave downward radiation (SDR) and diverse parameterizations of clear-sky and all-sky longwave downward radiation (LDR). In a first step, SDR is estimated based on measured input variables and estimated atmospheric parameters for hourly time steps during the years 1996 to 2008. Model behaviour is validated using the high quality measurements of six Alpine Surface Radiation Budget (ASRB) stations in Switzerland covering different elevations, and measurements of the Swiss Alpine Climate Radiation Monitoring network (SACRaM) in Payerne. In a next step, twelve clear-sky LDR parameterizations are calibrated using the ASRB measurements. One of the best performing parameterizations is elected to estimate all-sky LDR, where cloud transmissivity is estimated using measured and modeled global SDR during daytime. In a last step, the performance of several interpolation methods is evaluated to determine the cloud transmissivity in the night. We show that clear-sky direct, diffuse and global SDR is adequately represented by the model when using measurements of the atmospheric parameters precipitable water and aerosol content at Payerne. If the atmospheric parameters are estimated and used as a fix value, the relative mean bias deviance (MBD) and the relative root mean squared deviance (RMSD) of the clear-sky global SDR scatter between between −2 and 5%, and 7 and 13% within the six locations. The small errors in clear-sky global SDR can be attributed to compensating effects of modeled direct and diffuse SDR since an overestimation of aerosol content in the atmosphere results in underestimating the direct, but overestimating the diffuse SDR. Calibration of LDR parameterizations to local conditions reduces MBD and RMSD strongly compared to using the published values of the parameters, resulting in relative MBD and RMSD of less than 5% respectively 10% for the best parameterizations. The best results to estimate cloud transmissivity during nighttime were obtained by linearly interpolating the average of the cloud transmissivity of the four hours of the preceeding afternoon and the following morning. Model uncertainty can be caused by different errors such as code implementation, errors in input data and in estimated parameters, etc. The influence of the latter (errors in input data and model parameter uncertainty) on model outputs is determined using Monte Carlo. Model uncertainty is provided as the relative standard deviation σrel of the simulated frequency distributions of the model outputs. An optimistic estimate of the relative uncertainty σrel resulted in 10% for the clear-sky direct, 30% for diffuse, 3% for global SDR, and 3% for the fitted all-sky LDR.

scholarly journals All-sky assimilation of infrared radiances sensitive to mid- and upper-tropospheric moisture and cloud

2019 ◽  
Author(s):  
Alan J. Geer ◽  
Stefano Migliorini ◽  
Marco Matricardi
Keyword(s):  
Weather Forecasting ◽  
Deep Convection ◽  
Cloud Detection ◽  
Clear Sky ◽  
Atmospheric Sounding ◽  
Beneficial Impact ◽  
Infrared Radiances ◽  
The Tropics ◽  
The Impact ◽  
Better Than

Abstract. All-sky assimilation of infrared (IR) radiances has not yet become operational at any weather forecasting centre but it promises to bring new observations in sensitive areas and it avoids the need for cloud detection. A new all-sky IR configuration gives results comparable to (and in some areas better than) clear-sky assimilation of the same data, meaning that operational implementation is now feasible. The impact of 7 upper-tropospheric water vapour (WV) sounding channels from the Infrared Atmospheric Sounding Interferometer (IASI) is evaluated in both all-sky and clear-sky approaches. All-sky radiative transfer simulations (and the forecast model’s cloud fields) are now sufficiently accurate that systematic errors are comparable to those of clear-sky assimilation outside of a few difficult areas such as deep-convection. All-sky assimilation brings 65 % more data than clear-sky assimilation globally, with the biggest increases in midlatitude storm tracks and tropical convective areas. However all-sky gives slightly less weight to any one observation than in the clear-sky approach. In the midlatitudes, all-sky and clear-sky assimilation have similarly beneficial impact on mid- and upper-tropospheric dynamical forecast fields. Here the addition of data in cloudy areas is offset by the slightly lower weight given to the observations. But in the tropics, all-sky assimilation is significantly more beneficial than clear-sky assimilation, with improved dynamical short-range forecasts throughout the troposphere and stratosphere.

scholarly journals Correction of albedo measurements due to unknown geometry

2015 ◽  
Vol 9 (3) ◽  
pp. 2709-2744 ◽  
Author(s):  
U. Weiser ◽  
M. Olefs ◽  
W. Schöner ◽  
G. Weyss ◽  
B. Hynek
Keyword(s):  
Energy Balance ◽  
Snow Cover ◽  
Measured Data ◽  
Atmospheric Conditions ◽  
Atmospheric Parameters ◽  
Radiative Balance ◽  
Reference Measurement ◽  
Clear Sky ◽  
The Difference ◽  
Geometric Effects

Abstract. The diurnal albedo variation of glaciers on clear sky days can be relatively high due to geometric effects induced by tilt errors. In the present paper, these tilt errors of albedo measurements are corrected in cases where tilts of both, the sensors and the slopes are not accurately measured. For this method of correction, a nearby reference measurement with a horizontally levelled sensor is needed to determine atmospheric parameters. Based on that a model is developed that is fitted to the measured data to determine tilts and directions of sensors and slopes, which vary daily due to changing atmospheric conditions and snow cover. Once these parameters are determined, the albedo, the radiative balance and the energy balance can be corrected. The differences between measured and corrected values show an obvious under- or overestimation of albedo, depending on the direction of the slope. It is also demonstrated that the difference between measured and corrected albedo is highest for high solar zenith angles.

scholarly journals A simple method to calculate average spectra of clear sky solar radiation and their dependence on the atmospheric parameters

1985 ◽  
Vol 20 (2) ◽  
pp. 109-120 ◽  
Author(s):  
U. Amato ◽  
V. Cuomo ◽  
R. Guzzi ◽  
M. Macchiato ◽  
R. Rizzi ◽  
...  
Keyword(s):  
Solar Radiation ◽  
Atmospheric Parameters ◽  
Simple Method ◽  
Clear Sky

Evaluation of net shortwave radiation over China with a regional climate model

2020 ◽  
Vol 80 (2) ◽  
pp. 147-163
Author(s):  
X Liu ◽  
Y Kang ◽  
Q Liu ◽  
Z Guo ◽  
Y Chen ◽  
...  
Keyword(s):  
Regional Climate Model ◽  
Climate Model ◽  
Regional Climate ◽  
Radiant Energy ◽  
Energy System ◽  
Radiation Budget ◽  
Shortwave Radiation ◽  
Monsoon Region ◽  
Clear Sky ◽  
Sky Conditions

The regional climate model RegCM version 4.6, developed by the European Centre for Medium-Range Weather Forecasts Reanalysis, was used to simulate the radiation budget over China. Clouds and the Earth’s Radiant Energy System (CERES) satellite data were utilized to evaluate the simulation results based on 4 radiative components: net shortwave (NSW) radiation at the surface of the earth and top of the atmosphere (TOA) under all-sky and clear-sky conditions. The performance of the model for low-value areas of NSW was superior to that for high-value areas. NSW at the surface and TOA under all-sky conditions was significantly underestimated; the spatial distribution of the bias was negative in the north and positive in the south, bounded by 25°N for the annual and seasonal averaged difference maps. Compared with the all-sky condition, the simulation effect under clear-sky conditions was significantly better, which indicates that the cloud fraction is the key factor affecting the accuracy of the simulation. In particular, the bias of the TOA NSW under the clear-sky condition was <±10 W m-2 in the eastern areas. The performance of the model was better over the eastern monsoon region in winter and autumn for surface NSW under clear-sky conditions, which may be related to different levels of air pollution during each season. Among the 3 areas, the regional average biases overall were largest (negative) over the Qinghai-Tibet alpine region and smallest over the eastern monsoon region.

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