Impact of Slant-Path Radiative Transfer in the Simulation and Assimilation of Satellite Radiances in Environment Canada’s Weather Forecast System

Shahabadi, Maziar Bani; Aparicio, Josep M.; Garand, Louis

doi:10.1175/mwr-d-18-0126.1

Cited by 3 publications

(1 citation statement)

References 16 publications

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“…This was shown, in particular, for the physical interactions between the observed phenomena and the measurement process (e.g., W. Bell et al., 2010; John & Buehler, 2004; Joiner & Poli, 2005). These iterative improvements enable researchers to continue extracting ever‐increasing value from these observations for societal applications, such as Numerical Weather Prediction (e.g., Shahabadi et al., 2018). Furthermore, such enhanced understanding also helps to refine the design of new‐generation instruments or data records.…”

Section: Methodsmentioning

confidence: 99%

Radiance Simulations in Support of Climate Services

Poli,

Roebeling,

John

et al. 2023

Earth and Space Science

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Climate services are largely supported by climate reanalyses and by satellite Fundamental (Climate) Data Records (F(C)DRs). This paper demonstrates how the development and the uptake of F(C)DR benefit from radiance simulations, using reanalyses and radiative transfer models. We identify three classes of applications, with examples for each application class. The first application is to validate assumptions during F(C)DR development. Hereto we show the value of applying advanced quality controls to geostationary European (Meteosat) images. We also show the value of a cloud mask to study the spatio‐temporal coherence of the impact of the Mount Pinatubo volcanic eruption between Advanced Very High Resolution Radiometer (AVHRR) and the High‐resolution Infrared Radiation Sounder (HIRS) data. The second application is to assess the coherence between reanalyses and observations. Hereto we show the capability of reanalyses to reconstruct spectra observed by the Spektrometer Interferometer (SI‐1) flown on a Soviet satellite in 1979. We also present a first attempt to estimate the random uncertainties from this instrument. Finally, we investigate how advanced bias correction can help to improve the coherence between reanalysis and Nimbus‐3 Medium‐Resolution Infrared Radiometer (MRIR) in 1969. The third application is to inform F(C)DR users about particular quality aspects. We show how simulations can help to make a better‐informed use of the corresponding F(C)DR, taking as examples the Nimbus‐7 Scanning Multichannel Microwave Radiometer (SMMR), the Meteosat Second Generation (MSG) imager, and the Defense Meteorological Satellite Program (DMSP) Special Sensor Microwave Water Vapor Profiler (SSM/T‐2).

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Section: Methodsmentioning

confidence: 99%

Radiance Simulations in Support of Climate Services

Poli,

Roebeling,

John

et al. 2023

Earth and Space Science

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Implementation of Slant-Path Radiative Transfer in Environment Canada’s Global Deterministic Weather Prediction System

Shahabadi¹,

Buehner²,

Aparicio³

et al. 2020

Monthly Weather Review

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The standard approach for assimilating satellite radiance observations is to interpolate all vertical levels of the background state and analysis increment to the same horizontal location for input to the radiative transfer model. This can add significant error for observations with large zenith angle. The impact of accounting for the true slanted satellite-viewing geometry was tested by modifying the horizontal interpolation routines in Environment and Climate Change Canada’s Global Deterministic Weather Prediction System. Consequently, model variables are interpolated to a different horizontal position at each model level, for either just the innovation or both the innovation and increment calculation. When this slant-path operator is used for simulation of radiances, reductions in innovation standard deviation, up to 4.5%, for upper-tropospheric and stratospheric temperature and humidity channels of ATMS, AMSU-A, MHS, and CrIS instruments have similar magnitudes as reported in previous studies. In data assimilation experiments, statistically significant reductions in innovation standard deviation (up to 0.3%) for global GPSRO observations are obtained, due to an improved background state. Verification of short- and medium-range forecasts against Era5, and own analyses over the region poleward of 60°S show statistically significant reductions of error standard deviation by 2%-3% for wind and temperature in upper troposphere and lower stratosphere. These positive impacts are mostly due to performing slant-path interpolation on the background state, while also using slant-path on the analysis increment has little additional impact. This is expected since the analysis increment in this global configuration has lower spatial resolution, with grid spacing comparable with the maximum horizontal position error from not using the slant-path operator.

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Toward All-Sky Assimilation of Microwave Temperature Sounding Channels in Environment Canada’s Global Deterministic Weather Prediction System

Shahabadi

Buehner

2021

Monthly Weather Review

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The all-sky assimilation of radiances from microwave instruments is developed in the 4D-EnVar analysis system at Environment and Climate Change Canada (ECCC). Assimilation of cloud-affected radiances from Advanced Microwave Sounding Unit A (AMSUA) temperature sounding channels 4 and 5 for non-precipitating scenes over the ocean surface is the focus of this study. Cloud-affected radiances are discarded in the ECCC operational data assimilation system due to the limitations of forecast model physics, radiative transfer models, and the strong non-linearity of the observation operator. In addition to using symmetric estimate of innovation standard deviation for quality control, a state-dependent observation error inflation is employed at the analysis stage. The background state clouds are scaled by a factor of 0.5 to compensate for a systematic overestimation by the forecast model, before being used in the observation operator. The changes in the fit of the background state to observations show mixed results. The number of AMSUA channels 4 and 5 assimilated observations in the all-sky experiment is 5-12% higher than in the operational system. The all-sky approach improves temperature analysis when verified against ECMWF operational analysis in the areas where the extra cloud-affected observations were assimilated. Statistically significant reductions in error standard deviation by 1-4% for the analysis and forecasts of temperature, specific humidity, and horizontal wind speed up to maximum 4 days were achieved in the all-sky experiment in the lower troposphere. These improvements result mainly from the use of cloud information for computing the observation-minus-background departures. The operational implementation of all-sky assimilation is planned for Fall 2021.

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Impact of Slant-Path Radiative Transfer in the Simulation and Assimilation of Satellite Radiances in Environment Canada’s Weather Forecast System

Cited by 3 publications

References 16 publications

Radiance Simulations in Support of Climate Services

Radiance Simulations in Support of Climate Services

Implementation of Slant-Path Radiative Transfer in Environment Canada’s Global Deterministic Weather Prediction System

Toward All-Sky Assimilation of Microwave Temperature Sounding Channels in Environment Canada’s Global Deterministic Weather Prediction System

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