scholarly journals Twilight tropospheric and stratospheric photodissociation rates derived from balloon borne radiation measurements

2002 ◽  
Vol 2 (3) ◽  
pp. 715-738
Author(s):  
A. Kylling ◽  
T. Danielsen ◽  
M. Blumthaler ◽  
J. Schreder ◽  
B. Johnsen
Keyword(s):  
State Of The Art ◽  
Spectral Characteristics ◽  
Calibration Procedure ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Balloon Flight ◽  
Center Wavelength ◽  
Model Simulations ◽  
Stratospheric Balloon ◽  
Radiation Measurements

Abstract. A new ligthweight multichannel moderate bandwidth filter instrument designed to be flown on balloons, is described. The instrument measures the radiation field within the short UV (center wavelength at 312nm) and long UV (center wavelength at 340nm). The angular and spectral characteristics of the instrument are discussed and the calibration procedure outlined. Measurements made during a stratospheric balloon flight at twilight conditions from Gap-Tallard, France, are presented and compared with state-of-the-art radiative transfer model simulations. The model simulations and the measurements agree within ±10% (±20%) for solar zenith angles smaller than 93° (90°) for the 340 (312)nm channel. Based on the model simulations of the measured radiation, actinic flux spectra are reconstructed. These are used to calculate various photodissociation rates.

scholarly journals Twilight tropospheric and stratospheric photodissociation rates derived from balloon borne radiation measurements

2003 ◽  
Vol 3 (2) ◽  
pp. 377-385 ◽  
Author(s):  
A. Kylling ◽  
T. Danielsen ◽  
M. Blumthaler ◽  
J. Schreder ◽  
B. Johnsen
Keyword(s):  
State Of The Art ◽  
Spectral Characteristics ◽  
Calibration Procedure ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Balloon Flight ◽  
Center Wavelength ◽  
Model Simulations ◽  
Stratospheric Balloon ◽  
Radiation Measurements

Abstract. A new ligthweight multichannel moderate bandwidth filter instrument designed to be flown on balloons, is described. The instrument measures the radiation field within the short UV (center wavelength at 312 nm) and long UV (center wavelength at 340 nm). The angular and spectral characteristics of the instrument are discussed and the calibration procedure outlined. Measurements made during a stratospheric balloon flight at twilight conditions from Gap-Tallard, France, are presented and compared with state-of-the-art radiative transfer model simulations. The model simulations and the measurements agree within ±10% (±20%) for solar zenith angles smaller than 93° (90°) for the 340 (312) nm channel. Based on the model simulations of the measured radiation, actinic flux spectra are reconstructed. These are used to calculate various photodissociation rates.

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 An Innovative Calibration Method for the Inversion of Satellite Observations

2010 ◽  
Vol 49 (12) ◽  
pp. 2458-2473 ◽  
Author(s):  
Filipe Aires ◽  
Frédéric Bernardo ◽  
Héléne Brogniez ◽  
Catherine Prigent
Keyword(s):  
Water Vapor ◽  
Single Channel ◽  
Weather Prediction ◽  
Calibration Method ◽  
Calibration Procedure ◽  
Satellite Observations ◽  
Radiative Transfer Model ◽  
Sensor Calibration ◽  
Transfer Model ◽  
Nwp Model

Abstract Retrieval schemes often use two important components: 1) a radiative transfer model (RTM) inside the retrieval procedure or to construct the learning dataset for the training of the statistical retrieval algorithms and 2) a numerical weather prediction (NWP) model to provide a first guess or, again, to construct a learning dataset. This is particularly true in operational centers. As a consequence, any physical retrieval or similar method is limited by inaccuracies in the RTM and NWP models on which it is based. In this paper, a method for partially compensating for these errors as part of the sensor calibration is presented and evaluated. In general, RTM/NWP errors are minimized as best as possible prior to the training of the retrieval method, and then tolerated. The proposed method reduces these unknown and generally nonlinear residual errors by training a separate preprocessing neural network (NN) to produce calibrated radiances from real satellite data that approximate those radiances produced by the “flawed” NWP and RTM models. The final “compensated/flawed” retrieval assures better internal consistency of the retrieval procedure and then produces more accurate results. To the authors’ knowledge, this type of NN model has not been used yet for this purpose. The calibration approach is illustrated here on one particular application: the retrieval of atmospheric water vapor from the Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E) and the Humidity Sounder for Brazil (HSB) measurements for nonprecipitating scenes, over land and ocean. Before being inverted, the real observations are “projected” into the space of the RTM simulation space from which the retrieval is designed. Validation of results is performed with radiosonde measurements and NWP analysis departures. This study shows that the NN calibration of the AMSR-E/HSB observations improves water vapor inversion, over ocean and land, for both clear and cloudy situations. The NN calibration is efficient and very general, being applicable to a large variety of problems. The nonlinearity of the NN allows for the calibration procedure to be state dependent and adaptable to specific cases (e.g., the same correction will not be applied to medium-range measurement and to extreme conditions). Its multivariate nature allows for a full exploitation of the complex correlation structure among the instrument channels, making the calibration of each single channel more robust. The procedure would make it possible to project the satellite observations in a reference observational space defined by radiosonde measurements, RTM simulations, or other instrument observational space.

scholarly journals A New Method to Calibrate Shortwave Solar Radiation Measurements

2014 ◽  
Vol 31 (6) ◽  
pp. 1321-1329 ◽  
Author(s):  
Jinhuan Qiu ◽  
Xiangao Xia ◽  
Jianghui Bai ◽  
Pucai Wang ◽  
Xuemei Zong ◽  
...  
Keyword(s):  
New Method ◽  
Radiative Transfer Model ◽  
Maximum Deviation ◽  
Transfer Model ◽  
Transfer Coefficients ◽  
Calibration Transfer ◽  
The World ◽  
Potential Applications ◽  
Atmospheric Transmittance ◽  
Radiation Measurements

Abstract A method is proposed to simultaneously calibrate shortwave (0.3–4 μm) global, direct, and scattering solar irradiance (GSI, DSI, and SSI, respectively) measurements. The method uses the World Radiation Reference (WRR) as a calibration standard and on-site radiation measurements as inputs. Two simple but effective techniques are used in the calibration. The first is to scale SSI and GSI detection sensitivities under overcast skies, which is based on the assumption that SSI should be equal to GSI if DSI is completely scattered and absorbed. The second is a new method to retrieve aerosol optical thickness (AOT), using the ratio of horizontal DSI (HDSI) to GSI measurements under clear and clean conditions. Thereafter, retrieved AOTs are used to drive a radiative transfer model to calculate atmospheric transmittance and then a ratio of GSI to the transmittance. Deviation of this ratio to the WRR is regarded as an indicator of GSI uncertainty, and the calibration transfer coefficient is derived as the WRR ratio. The method is applied to calibrate radiation measurements at Xianghe, China, during 2005. It is estimated from the derived transfer coefficients on 36 clear and clean days that uncertainties of DSI, GSI, and SSI measurements are within −4.0% to 2.9%, −5.9% to 2.4%, and −6.1% to 4.9%, respectively. The calibration is further validated based on comparisons of AOT at 750 nm retrieved from HDSI/GSI to Aerosol Robotic Network (AERONET) AOT products. The maximum deviation between two AOT products is 0.026. The unique advantage of this method lies in its potential applications in correcting historic radiation measurements and monitoring radiometer performance.

scholarly journals A Methodology to Determine Recipe Adjustments for Multispectral Composites Derived from Next-Generation Advanced Satellite Imagers

2018 ◽  
Vol 35 (3) ◽  
pp. 643-664 ◽  
Author(s):  
Emily Berndt ◽  
Nicholas Elmer ◽  
Lori Schultz ◽  
Andrew Molthan
Keyword(s):  
Linear Regression ◽  
Brightness Temperature ◽  
Infrared Imaging ◽  
Spectral Response ◽  
Spectral Characteristics ◽  
Japan Meteorological Agency ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Next Generation ◽  
Temperature Offset

AbstractThe European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) began creating multispectral [i.e., red–green–blue (RGB)] composites in the early 2000s with the advent of the Meteosat-8 Spinning Enhanced Visible and Infrared Imager (SEVIRI). As new satellite sensors—for example, the Himawari-8 Advanced Himawari Imager (AHI) and the Geostationary Operational Environmental Satellite Advanced Baseline Imager (ABI)—become available, there is a need to adjust the EUMETSAT RGB standard thresholds (i.e., recipes) to account for differences in spectral characteristics, spectral response, and atmospheric absorption in order to maintain an interpretation consistent with legacy composites. For the purpose of comparing RGB composites derived from nonoverlapping geostationary sensors, an adjustment technique was applied to the Suomi National Polar-Orbiting Partnership (Suomi-NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) to create an intermediate reference sensor (i.e., SEVIRI proxy). Brightness temperature offset values between each AHI and SEVIRI proxy band centered near 3.9, 8.6, 11.0, and 12.0 µm were determined with this technique and through line-by-line radiative transfer model simulations. The relationship between measured brightness temperature of AHI and the SEVIRI proxy was determined though linear regression similar to research by the Japan Meteorological Agency. The linear regression coefficients were utilized to determine the RGB recipe adjustments. Adjusting the RGB recipes to account for the differences in spectral characteristics results in RGB composites consistent with legacy EUMETSAT composites. The methodology was applied to an example of the Nighttime Microphysics RGB, confirming the Japan Meteorological Agency adjustments and demonstrating a simple methodology to determine recipe adjustments for RGB composites derived with next-generation sensors.

scholarly journals CANOPY MODELING OF AQUATIC VEGETATION: CONSTRUCTION OF SUBMERGED VEGETATION INDEX

2018 ◽  
Vol XLII-3 ◽  
pp. 1253-1258
Author(s):  
Z. Ma ◽  
G. Zhou
Keyword(s):  
Vegetation Index ◽  
Aquatic Vegetation ◽  
Spectral Characteristics ◽  
Vegetation Indices ◽  
Simulated Data ◽  
Radiative Transfer Model ◽  
Future Research ◽  
Transfer Model ◽  
Submerged Vegetation ◽  
Terrestrial Vegetation

The unique spectral characteristics of submerged vegetation in wetlands determine that the conventional terrestrial vegetation index cannot be directly employed to species identification and parameter inversion of submerged vegetation. Based on the Aquatic Vegetation Radiative Transfer model (AVRT), this paper attempts to construct an index suitable for submerged vegetation, the model simulated data and a scene of Sentinel-2A image in Taihu Lake, China are utilized for assessing the performance of the newly constructed indices and the existent vegetation indices. The results show that the angle index composed by 525 nm, 555 nm and 670 nm can resist the effects of water columns and is more sensitive to vegetation parameters such as LAI. Furthermore, it makes a well discrimination between submerged vegetation and water bodies in the satellite data. We hope that the new index will provide a theoretical basis for future research.

scholarly journals Calibration and Validation of Antenna and Brightness Temperatures from Metop-C Advanced Microwave Sounding Unit-A (AMSU-A)

2020 ◽  
Vol 12 (18) ◽  
pp. 2978
Author(s):  
Banghua Yan ◽  
Junye Chen ◽  
Cheng-Zhi Zou ◽  
Khalil Ahmad ◽  
Haifeng Qian ◽  
...  
Keyword(s):  
Radiative Transfer ◽  
Data Quality ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Model Simulations ◽  
Calibration And Validation ◽  
Microwave Sounding Unit ◽  
Data Record ◽  
Microwave Sounding ◽  
Advanced Microwave Sounding Unit

This study carries out the calibration and validation of Antenna Temperature Data Record (TDR) and Brightness Temperature Sensor Data Record (SDR) data from the last National Oceanic and Atmospheric Administration (NOAA) Advanced Microwave Sounding Unit-A (AMSU-A) flown on the Meteorological Operational satellite programme (MetOp)-C satellite. The calibration comprises the selection of optimal space view positions for the instrument and the determination of coefficients in calibration equations from the Raw Data Record (RDR) to TDR and SDR. The validation covers the analyses of the instrument noise equivalent differential temperature (NEDT) performance and the TDR and SDR data quality from the launch until 15 November 2019. In particular, the Metop-C data quality is assessed by comparing to radiative transfer model simulations and observations from Metop-A/B AMSU-A, respectively. The results demonstrate that the on-orbit instrument NEDTs have been stable since launch and continue to meet the specifications at most channels except for channel 3, whose NEDT exceeds the specification after April 2019. The quality of the Metop-C AMSU-A data for all channels except channel 3 have been reliable since launch. The quality at channel 3 is degraded due to the noise exceeding the specification. Compared to its TDR data, the Metop-C AMSU-A SDR data exhibit a reduced and more symmetric scan angle-dependent bias against radiative transfer model simulations, demonstrating the great performance of the TDR to SDR conversion coefficients. Additionally, the Metop-C AMSU-A data quality agrees well with Metop-A/B AMSU-A data, with an averaged difference in the order of 0.3 K, which is confirmed based on Simultaneous Nadir Overpass (SNO) inter-sensor comparisons between Metop-A/B/C AMSU-A instruments via either NOAA-18 or NOAA-19 AMSU-A as a transfer.

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