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

Saunders, Roger; Hocking, James; Turner, Emma; Rayer, Peter; Rundle, David; Brunel, Pascal; Vidot, Jérôme; Roquet, Pascale; Matricardi, Marco; Geer, Alan; Bormann, Niels; Lupu, Cristina

doi:10.5194/gmd-11-2717-2018

Cited by 378 publications

(264 citation statements)

References 63 publications

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“…; Saunders et al . ) is used for clear‐sky conditions and the RTTOV‐SCATT model is used for cloudy and precipitating conditions (Bauer et al . ; Geer et al .…”

Section: Ecmwf Integrated Forecasting System (Ifs)mentioning

confidence: 99%

Use and impact of Arctic observations in the ECMWF Numerical Weather Prediction system

Lawrence

Bormann

Sandu

et al. 2019

Quart J Royal Meteoro Soc

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111

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This paper presents an assessment of the usage of Arctic atmospheric observations in the Numerical Weather Prediction (NWP) system of the European Centre for Medium‐Range Weather Forecasts, and of their impact on the quality of short‐ to medium‐range forecasts. The Arctic has low coverage of conventional data north of 70°N but one of the highest levels of coverage of satellite sounding data on Earth. The impact of Arctic observations on forecast skill was assessed by performing Observing System Experiments, in which different observation types were removed from the full observing system. This assessment was complemented by an analysis of Forecast Sensitivity to Observation Impact diagnostics. To our knowledge it is the first time that comprehensive numerical experimentation has been carried out to explore the role of different Arctic observations in a state‐of‐the‐art global operational NWP system. All Arctic observations were found to have a positive impact on forecast skill in the Arctic region, with the greatest tropospheric impacts on both short‐ and medium‐range forecasts due to microwave, conventional and infrared sounding observations. Results indicate the great importance of microwave sounding data and conventional data, which are found to be the key observing systems in the summer and winter seasons, respectively. These observations were found to have positive and statistically significant impacts on forecasts not only in the Arctic but also in the midlatitude regions at longer lead times. Differences between the seasons are most likely due to problems assimilating microwave sounding observations over snow and sea ice, leading to a reduced impact in winter. There is also the suggestion of increased importance of conventional data in winter, and other factors may also play a role.

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“…; Saunders et al . ) is used for clear‐sky conditions and the RTTOV‐SCATT model is used for cloudy and precipitating conditions (Bauer et al . ; Geer et al .…”

Section: Ecmwf Integrated Forecasting System (Ifs)mentioning

confidence: 99%

Use and impact of Arctic observations in the ECMWF Numerical Weather Prediction system

Lawrence

Bormann

Sandu

et al. 2019

Quart J Royal Meteoro Soc

Self Cite

111

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“…Idealised 1D‐Var experiments were conducted to investigate whether SAPHIR observations provide a more accurate estimate of the atmospheric moisture profile than other microwave instruments (ATMS, MHS and AMSR‐2) as suggested by the qualitative comparison of weighting functions shown in Figure . Five experiments were run using a 1D‐Var to perform retrievals based on synthetic observations, with RTTOV12 used as the observation operator (Smith, ; Saunders et al, ). A set of synthetic brightness‐temperature observations were generated from 1,333 70‐level tropical input profiles (Smith, ) which acted as a proxy for the true state of the atmosphere (or “truth”).…”

Section: D‐var Experimentsmentioning

confidence: 99%

Benefits of assimilating SAPHIR observations on analysis and forecasts of tropical fields in the Met Office global model

Doherty

Rani

Newman

et al. 2018

Quart J Royal Meteoro Soc

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The Sondeur Atmosphérique du Profil d'Humidité Intertropicale par Radiométrie (SAPHIR) instrument provides improved sampling of tropical atmospheric moisture vertically, horizontally and temporally. The impact of these unique characteristics is investigated through: an idealised study of retrieved humidity profiles; single‐observation experiments; assimilation experiments in a global NWP system; and an investigation into the spin‐down of precipitation in the early phase of the forecast. SAPHIR offers improved performance over similar satellite instruments, and beneficial impacts were found in all investigations. When assimilated in conjunction with observations from the Advanced Microwave Scanning Radiometer imager AMSR‐2 the impact is further improved. Retrieval studies showed the errors in retrievals from SAPHIR were lower than those obtained from MHS or ATMS at all levels above 600 hPa. Single‐observation experiments showed that, when assimilated together with AMSR‐2, AMSR‐2‐driven humidity increments were modified to give more realistic vertical structure. In assimilation experiments employing a near‐operational configuration of the Met Office global model, the assimilation of clear‐sky SAPHIR data improved the root‐mean‐square errors of a number of forecast metrics, most notably temperature at 250 hPa (improved by 2%), relative humidity at 500 hPa (2%) and wind at 500 hPa (1%) at forecast lead times of 12 and 24 h. The results of this work form a clear recommendation for future remote‐sensing missions including both SAPHIR and AMSR‐2 channel configurations.

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“…For MWHTS, the surface emissivity affects the measurements of the two window Channels 1, 10, temperature sounding Channels 7-9 and water vapor sounding Channel 15, whose peak WF heights are closer to the surface. In RTTOV [34], over ocean, the surface emissivities are computed by the Faste Emissivity (FASTEM)-5 model [34], over land, a Tool to Estimate Land-Surface Emissivities at Microwave frequencies (TELSEM) emissivity atlas is used [35].…”

Section: Forward Model Simulationsmentioning

confidence: 99%

Bias Correction for Retrieval of Atmospheric Parameters from the Microwave Humidity and Temperature Sounder Onboard the Fengyun-3C Satellite

Wang

2016

Atmosphere

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Abstract:The microwave humidity and temperature sounder (MWHTS) on the Fengyun (FY)-3C satellite measures the outgoing radiance from the Earth's surface and atmospheric constituents. MWHTS, which makes measurements in the isolated oxygen absorption line near 118 GHz and the vicinity of the strong water vapor absorption line around 183 GHz, can provide fine vertical distribution structures of both atmospheric humidity and temperature. However, in order to obtain the accurate soundings of humidity and temperature by physical retrieval methods, the bias between the observed and simulated radiance calculated by the radiative transfer model from the background or first guess profiles must be corrected. In this study, two bias correction methods are developed through the correlation analysis between MWHTS measurements and air mass identified by the first guess profiles of the physical inversion; one is the linear regression correction (LRC), and the other is the neural network correction (NNC), representing the linear and nonlinear relationships between MWHTS measurements and air mass, respectively. The correction methods have been applied to MWHTS observed brightness temperatures over the geographic area (180 • W-180 • E, 60 • S-60 • N). The corrected results are evaluated by the probability density function of the differences between corrected observations and simulated values and the root mean square errors (RMSE) with respect to simulated observations. The numerical results show that the NNC method has better performance, especially in MWHTS Channels 1 and 7-9, whose peak weight function heights are close to the surface. In order to assess the effects of bias correction methods proposed in this study on the retrieval accuracy, a one-dimensional variational system was built and applied to the MWHTS brightness temperatures to estimate the atmospheric temperature and humidity profiles. The retrieval results also show that NNC has better performance. An indication of the stability and robustness of the NNC method is given, which suggests that the NNC method has promising application perspectives in the physical retrieval.

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

Cited by 378 publications

References 63 publications

Use and impact of Arctic observations in the ECMWF Numerical Weather Prediction system

Use and impact of Arctic observations in the ECMWF Numerical Weather Prediction system

Benefits of assimilating SAPHIR observations on analysis and forecasts of tropical fields in the Met Office global model

Bias Correction for Retrieval of Atmospheric Parameters from the Microwave Humidity and Temperature Sounder Onboard the Fengyun-3C Satellite

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