Articles | Volume 11, issue 7
https://doi.org/10.5194/gmd-11-2717-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-11-2717-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
10 Jul 2018
Model description paper |
| 10 Jul 2018
| 10 Jul 2018
An update on the RTTOV fast radiative transfer model (currently at version 12)
Roger Saunders
CORRESPONDING AUTHOR
Met Office, Fitzroy Rd., Exeter, UK
James Hocking
Met Office, Fitzroy Rd., Exeter, UK
Emma Turner
Met Office, Fitzroy Rd., Exeter, UK
Peter Rayer
Met Office, Fitzroy Rd., Exeter, UK
David Rundle
Met Office, Fitzroy Rd., Exeter, UK
Pascal Brunel
MeteoFrance/CMS, Avenue de Lorraine, Lannion, France
Jerome Vidot
MeteoFrance/CMS, Avenue de Lorraine, Lannion, France
Pascale Roquet
MeteoFrance/CMS, Avenue de Lorraine, Lannion, France
Marco Matricardi
ECMWF, Shinfield Park, Reading, UK
Alan Geer
ECMWF, Shinfield Park, Reading, UK
Niels Bormann
ECMWF, Shinfield Park, Reading, UK
Cristina Lupu
ECMWF, Shinfield Park, Reading, UK
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Atmos. Meas. Tech., 9, 841–857, https://doi.org/10.5194/amt-9-841-2016, https://doi.org/10.5194/amt-9-841-2016, 2016
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By modeling the Special Sensor Microwave Imager/Sounder's mesospheric measurements, inversions methods can be applied to retreive mesospheric temperatures. We compare the fast forward model used by Met Office with reference simulations and find that there is a reasonable agreement between both models and measurements. Thus we recommend that the fast model is used in data assimilation to improve mesospheric temperature retrievals.
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This study provides a detailed description of the radar simulator available within version 13 of the RTTOV software. It is applied to the Météo-France global numerical weather prediction model, with the objective of simulating Dual-frequency Precipitation Radar reflectivity observations. Additionally, the simulation of the bright-band is addressed, and then successfully applied to model forecasts for the purpose of classifying the model columns between stratiform and convective categories.
Bruna Barbosa Silveira, Emma Catherine Turner, and Jérôme Vidot
Atmos. Meas. Tech., 17, 1279–1296, https://doi.org/10.5194/amt-17-1279-2024, https://doi.org/10.5194/amt-17-1279-2024, 2024
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A fast radiative transfer model, used to speed up the full spectral simulation of meteorological satellite channels in weather forecast models, is tested using 25 000 modelled atmospheres. The differences between calculations from the fast and the high-resolution reference models are examined for nine historic weather satellite instruments. The study confirms that a reduced set of 83 atmospheric profiles is robust enough to estimate the scale of the differences obtained from the larger sample.
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Geosci. Model Dev., 14, 7497–7526, https://doi.org/10.5194/gmd-14-7497-2021, https://doi.org/10.5194/gmd-14-7497-2021, 2021
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Satellite observations of radiation from the earth can have strong sensitivity to cloud and precipitation in the atmosphere, with applications in weather forecasting and the development of models. Computing the radiation received at the satellite sensor using radiative transfer theory requires a simulation of the optical properties of a volume containing a large number of cloud and precipitation particles. This article describes the physics used to generate these
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Geosci. Model Dev., 14, 5467–5485, https://doi.org/10.5194/gmd-14-5467-2021, https://doi.org/10.5194/gmd-14-5467-2021, 2021
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Numerical weather predictions combine data from satellites with atmospheric forecasts. Some satellites measure the radiance emitted by the Earth's surface. To use this data, one must have knowledge of the surface properties, like the temperature of the thin layer above the surface. Error in this temperature leads to a misuse of the satellite data and affects the quality of the weather forecast. We updated our approach to better estimate this temperature, which should help improve the forecast.
Alan J. Geer
Atmos. Meas. Tech., 14, 5369–5395, https://doi.org/10.5194/amt-14-5369-2021, https://doi.org/10.5194/amt-14-5369-2021, 2021
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Satellite observations sensitive to cloud and precipitation help improve the quality of weather forecasts. However, they are sensitive to things that models do not forecast, such as the shapes and sizes of snow and ice particles. These details can be estimated from the observations themselves and then incorporated in the satellite simulators used in weather forecasting. This approach, known as parameter estimation, will be increasingly useful to build models of poorly known physical processes.
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RTTOV is a fast radiative transfer model for simulating passive satellite-based observations at visible, infrared, and microwave wavelengths. A core part of the model is a parameterisation of the absorption of radiation by the various gases present in the atmosphere. We present a new parameterisation that performs well compared to the existing one in terms of accuracy and can be developed further more easily. The new parameterisation is implemented in the latest release, RTTOV v13.0.
Vasileios Barlakas, Alan J. Geer, and Patrick Eriksson
Atmos. Meas. Tech., 14, 3427–3447, https://doi.org/10.5194/amt-14-3427-2021, https://doi.org/10.5194/amt-14-3427-2021, 2021
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Oriented nonspherical ice particles induce polarization that is ignored when cloud-sensitive satellite observations are used in numerical weather prediction systems. We present a simple approach for approximating particle orientation, requiring minor adaption of software and no additional calculation burden. With this approach, the system realistically simulates the observed polarization patterns, increasing the physical consistency between instruments with different polarizations.
Robin J. Hogan and Marco Matricardi
Geosci. Model Dev., 13, 6501–6521, https://doi.org/10.5194/gmd-13-6501-2020, https://doi.org/10.5194/gmd-13-6501-2020, 2020
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A key component of computer models used to predict weather and climate is the radiation scheme, which calculates how solar and infrared radiation heats and cools the atmosphere and surface, including the important role of greenhouse gases. This paper describes the experimental protocol and large datasets for a new project, CKDMIP, to evaluate and improve the accuracy of the treatment of atmospheric gases in the radiation schemes used worldwide, as well as their computational speed.
Alan J. Geer, Stefano Migliorini, and Marco Matricardi
Atmos. Meas. Tech., 12, 4903–4929, https://doi.org/10.5194/amt-12-4903-2019, https://doi.org/10.5194/amt-12-4903-2019, 2019
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Satellite radiance observations have only recently become usable in conditions of cloud and precipitation for the initialization of weather forecasts. The move to
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Alan J. Geer
Atmos. Meas. Tech., 12, 3629–3657, https://doi.org/10.5194/amt-12-3629-2019, https://doi.org/10.5194/amt-12-3629-2019, 2019
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Using more satellite data in cloudy areas helps improve weather forecasts, but all-sky assimilation is still tricky, particularly for infrared data. To allow the use of hyperspectral infrared sounder radiances in all-sky conditions, an error model is developed that, in the presence of cloud, broadens the correlations between channels and increases error variances. After fixing problems of gravity wave and bias amplification, the results of all-sky assimilation trials were promising.
Domenico Cimini, James Hocking, Francesco De Angelis, Angela Cersosimo, Francesco Di Paola, Donatello Gallucci, Sabrina Gentile, Edoardo Geraldi, Salvatore Larosa, Saverio Nilo, Filomena Romano, Elisabetta Ricciardelli, Ermann Ripepi, Mariassunta Viggiano, Lorenzo Luini, Carlo Riva, Frank S. Marzano, Pauline Martinet, Yun Young Song, Myoung Hwan Ahn, and Philip W. Rosenkranz
Geosci. Model Dev., 12, 1833–1845, https://doi.org/10.5194/gmd-12-1833-2019, https://doi.org/10.5194/gmd-12-1833-2019, 2019
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Katrin Lonitz and Alan J. Geer
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Yannick Kangah, Philippe Ricaud, Jean-Luc Attié, Naoko Saitoh, Jérôme Vidot, Pascal Brunel, and Samuel Quesada-Ruiz
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2018-21, https://doi.org/10.5194/amt-2018-21, 2018
Revised manuscript not accepted
Javier Andrey-Andrés, Nadia Fourrié, Vincent Guidard, Raymond Armante, Pascal Brunel, Cyril Crevoisier, and Bernard Tournier
Atmos. Meas. Tech., 11, 803–818, https://doi.org/10.5194/amt-11-803-2018, https://doi.org/10.5194/amt-11-803-2018, 2018
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A new generation of the Infrared Atmospheric Sounding Interferometer (IASI) sounders, whose highly accurate measurements are commonly used in environment applications, has already been designed: IASI New Generation (IASI-NG). A database of IASI and IASI-NG simulated observations was built to set a common framework for future impact studies. This first study showed the IASI-NG benefit with an improvement of the temperature retrievals throughout the atmosphere and a lower benefit for the humidity.
Francesco De Angelis, Domenico Cimini, Ulrich Löhnert, Olivier Caumont, Alexander Haefele, Bernhard Pospichal, Pauline Martinet, Francisco Navas-Guzmán, Henk Klein-Baltink, Jean-Charles Dupont, and James Hocking
Atmos. Meas. Tech., 10, 3947–3961, https://doi.org/10.5194/amt-10-3947-2017, https://doi.org/10.5194/amt-10-3947-2017, 2017
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Modern data assimilation systems require knowledge of the typical differences between observations and model background (O–B). This work illustrates a 1-year O–B analysis for ground-based microwave radiometer (MWR) observations in clear-sky conditions for a prototype network of six MWRs in Europe. Observations are MWR brightness temperatures (TB). Background profiles extracted from the output of a convective-scale model are used to simulate TB through the radiative transfer model RTTOV-gb.
John C. Kealy, Franco Marenco, John H. Marsham, Luis Garcia-Carreras, Pete N. Francis, Michael C. Cooke, and James Hocking
Atmos. Chem. Phys., 17, 5789–5807, https://doi.org/10.5194/acp-17-5789-2017, https://doi.org/10.5194/acp-17-5789-2017, 2017
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Using novel methods of cloud detection from aircraft data over the Sahara desert, we evaluate the performance of the Meteosat satellite in measuring cloud properties: namely, the cloud mask and the cloud-top height. We find that the cloud mask can justifiably be used for many applications (such as creating a detailed Saharan cloud climatology), and we also discuss its limitations. As for the cloud-top height, we show that the dataset cannot yet be considered robust in this part of the world.
Emma C. Turner, Stafford Withington, David A. Newnham, Peter Wadhams, Anna E. Jones, and Robin Clancy
Atmos. Meas. Tech., 9, 5461–5485, https://doi.org/10.5194/amt-9-5461-2016, https://doi.org/10.5194/amt-9-5461-2016, 2016
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Observations of the submillimetre part of the electromagnetic spectrum have previously been the domain of the astronomical community. However, new technological
advances in the superconducting detectors field are offering the atmospheric sciences unexplored opportunities to perform useful spectroscopy in this region,
exploiting existing radio telescope sites. Example simulations at six sites are presented for HBr, HOBr, HO2 and N2O showing the need for broad
high-resolution measurements.
Francesco De Angelis, Domenico Cimini, James Hocking, Pauline Martinet, and Stefan Kneifel
Geosci. Model Dev., 9, 2721–2739, https://doi.org/10.5194/gmd-9-2721-2016, https://doi.org/10.5194/gmd-9-2721-2016, 2016
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Ground-based microwave radiometers (MWRs) offer to bridge the observational gap in the atmospheric boundary layer. Currently MWRs are operational at many sites worldwide. However, their potential is largely under-exploited, partly due to the lack of a fast radiative transfer model (RTM) suited for data assimilation into numerical weather prediction models. Here we propose and test an RTM, building on satellite heritage and adapting for ground-based MWRs, which addresses this shortage.
Hélène Brogniez, Stephen English, Jean-François Mahfouf, Andreas Behrendt, Wesley Berg, Sid Boukabara, Stefan Alexander Buehler, Philippe Chambon, Antonia Gambacorta, Alan Geer, William Ingram, E. Robert Kursinski, Marco Matricardi, Tatyana A. Odintsova, Vivienne H. Payne, Peter W. Thorne, Mikhail Yu. Tretyakov, and Junhong Wang
Atmos. Meas. Tech., 9, 2207–2221, https://doi.org/10.5194/amt-9-2207-2016, https://doi.org/10.5194/amt-9-2207-2016, 2016
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Because a systematic difference between measurements of water vapor performed by space-borne observing instruments in the microwave spectral domain and their numerical modeling was recently highlighted, this work discusses and gives an overview of the various errors and uncertainties associated with each element in the comparison process. Indeed, the knowledge of absolute errors in any observation of the climate system is key, more specifically because we need to detect small changes.
Richard Larsson, Mathias Milz, Peter Rayer, Roger Saunders, William Bell, Anna Booton, Stefan A. Buehler, Patrick Eriksson, and Viju O. John
Atmos. Meas. Tech., 9, 841–857, https://doi.org/10.5194/amt-9-841-2016, https://doi.org/10.5194/amt-9-841-2016, 2016
Short summary
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By modeling the Special Sensor Microwave Imager/Sounder's mesospheric measurements, inversions methods can be applied to retreive mesospheric temperatures. We compare the fast forward model used by Met Office with reference simulations and find that there is a reasonable agreement between both models and measurements. Thus we recommend that the fast model is used in data assimilation to improve mesospheric temperature retrievals.
M. S. Johnston, G. Holl, J. Hocking, S. J. Cooper, and D. Chen
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amtd-8-11753-2015, https://doi.org/10.5194/amtd-8-11753-2015, 2015
Preprint withdrawn
A. J. Geer and F. Baordo
Atmos. Meas. Tech., 7, 1839–1860, https://doi.org/10.5194/amt-7-1839-2014, https://doi.org/10.5194/amt-7-1839-2014, 2014
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Angeline G. Pendergrass, Michael P. Byrne, Oliver Watt-Meyer, Penelope Maher, and Mark J. Webb
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Allison A. Wing, Levi G. Silvers, and Kevin A. Reed
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This paper presents the experimental design for a model intercomparison project to study tropical clouds and climate. It is a follow-up from a prior project that used a simplified framework for tropical climate. The new project adds one new component – a specified pattern of sea surface temperatures as the lower boundary condition. We provide example results from one cloud-resolving model and one global climate model and test the sensitivity to the experimental parameters.
Philip G. Sansom and Jennifer L. Catto
Geosci. Model Dev., 17, 6137–6151, https://doi.org/10.5194/gmd-17-6137-2024, https://doi.org/10.5194/gmd-17-6137-2024, 2024
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Weather fronts bring a lot of rain and strong winds to many regions of the mid-latitudes. We have developed an updated method of identifying these fronts in gridded data that can be used on new datasets with small grid spacing. The method can be easily applied to different datasets due to the use of open-source software for its development and shows improvements over similar previous methods. We present an updated estimate of the average frequency of fronts over the past 40 years.
Kelly M. Núñez Ocasio and Zachary L. Moon
Geosci. Model Dev., 17, 6035–6049, https://doi.org/10.5194/gmd-17-6035-2024, https://doi.org/10.5194/gmd-17-6035-2024, 2024
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TAMS is an open-source Python-based package for tracking and classifying mesoscale convective systems that can be used to study observed and simulated systems. Each step of the algorithm is described in this paper with examples showing how to make use of visualization and post-processing tools within the package. A unique and valuable feature of this tracker is its support for unstructured grids in the identification stage and grid-independent tracking.
Irene C. Dedoussi, Daven K. Henze, Sebastian D. Eastham, Raymond L. Speth, and Steven R. H. Barrett
Geosci. Model Dev., 17, 5689–5703, https://doi.org/10.5194/gmd-17-5689-2024, https://doi.org/10.5194/gmd-17-5689-2024, 2024
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Atmospheric model gradients provide a meaningful tool for better understanding the underlying atmospheric processes. Adjoint modeling enables computationally efficient gradient calculations. We present the adjoint of the GEOS-Chem unified chemistry extension (UCX). With this development, the GEOS-Chem adjoint model can capture stratospheric ozone and other processes jointly with tropospheric processes. We apply it to characterize the Antarctic ozone depletion potential of active halogen species.
Sylvain Mailler, Sotirios Mallios, Arineh Cholakian, Vassilis Amiridis, Laurent Menut, and Romain Pennel
Geosci. Model Dev., 17, 5641–5655, https://doi.org/10.5194/gmd-17-5641-2024, https://doi.org/10.5194/gmd-17-5641-2024, 2024
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We propose two explicit expressions to calculate the settling speed of solid atmospheric particles with prolate spheroidal shapes. The first formulation is based on theoretical arguments only, while the second one is based on computational fluid dynamics calculations. We show that the first method is suitable for virtually all atmospheric aerosols, provided their shape can be adequately described as a prolate spheroid, and we provide an implementation of the first method in AerSett v2.0.2.
Hejun Xie, Lei Bi, and Wei Han
Geosci. Model Dev., 17, 5657–5688, https://doi.org/10.5194/gmd-17-5657-2024, https://doi.org/10.5194/gmd-17-5657-2024, 2024
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A radar operator plays a crucial role in utilizing radar observations to enhance numerical weather forecasts. However, developing an advanced radar operator is challenging due to various complexities associated with the wave scattering by non-spherical hydrometeors, radar beam propagation, and multiple platforms. In this study, we introduce a novel radar operator named the Accurate and Efficient Radar Operator developed by ZheJiang University (ZJU-AERO) which boasts several unique features.
Jonathan J. Day, Gunilla Svensson, Barbara Casati, Taneil Uttal, Siri-Jodha Khalsa, Eric Bazile, Elena Akish, Niramson Azouz, Lara Ferrighi, Helmut Frank, Michael Gallagher, Øystein Godøy, Leslie M. Hartten, Laura X. Huang, Jareth Holt, Massimo Di Stefano, Irene Suomi, Zen Mariani, Sara Morris, Ewan O'Connor, Roberta Pirazzini, Teresa Remes, Rostislav Fadeev, Amy Solomon, Johanna Tjernström, and Mikhail Tolstykh
Geosci. Model Dev., 17, 5511–5543, https://doi.org/10.5194/gmd-17-5511-2024, https://doi.org/10.5194/gmd-17-5511-2024, 2024
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The YOPP site Model Intercomparison Project (YOPPsiteMIP), which was designed to facilitate enhanced weather forecast evaluation in polar regions, is discussed here, focussing on describing the archive of forecast data and presenting a multi-model evaluation at Arctic supersites during February and March 2018. The study highlights an underestimation in boundary layer temperature variance that is common across models and a related inability to forecast cold extremes at several of the sites.
Hossain Mohammed Syedul Hoque, Kengo Sudo, Hitoshi Irie, Yanfeng He, and Md Firoz Khan
Geosci. Model Dev., 17, 5545–5571, https://doi.org/10.5194/gmd-17-5545-2024, https://doi.org/10.5194/gmd-17-5545-2024, 2024
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Using multi-platform observations, we validated global formaldehyde (HCHO) simulations from a chemistry transport model. HCHO is a crucial intermediate in the chemical catalytic cycle that governs the ozone formation in the troposphere. The model was capable of replicating the observed spatiotemporal variability in HCHO. In a few cases, the model's capability was limited. This is attributed to the uncertainties in the observations and the model parameters.
Zijun Liu, Li Dong, Zongxu Qiu, Xingrong Li, Huiling Yuan, Dongmei Meng, Xiaobin Qiu, Dingyuan Liang, and Yafei Wang
Geosci. Model Dev., 17, 5477–5496, https://doi.org/10.5194/gmd-17-5477-2024, https://doi.org/10.5194/gmd-17-5477-2024, 2024
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In this study, we completed a series of simulations with MPAS-Atmosphere (version 7.3) to study the extreme precipitation event of Henan, China, during 20–22 July 2021. We found the different performance of two built-in parameterization scheme suites (mesoscale and convection-permitting suites) with global quasi-uniform and variable-resolution meshes. This study holds significant implications for advancing the understanding of the scale-aware capability of MPAS-Atmosphere.
Laurent Menut, Arineh Cholakian, Romain Pennel, Guillaume Siour, Sylvain Mailler, Myrto Valari, Lya Lugon, and Yann Meurdesoif
Geosci. Model Dev., 17, 5431–5457, https://doi.org/10.5194/gmd-17-5431-2024, https://doi.org/10.5194/gmd-17-5431-2024, 2024
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A new version of the CHIMERE model is presented. This version contains both computational and physico-chemical changes. The computational changes make it easy to choose the variables to be extracted as a result, including values of maximum sub-hourly concentrations. Performance tests show that the model is 1.5 to 2 times faster than the previous version for the same setup. Processes such as turbulence, transport schemes and dry deposition have been modified and updated.
G. Alexander Sokolowsky, Sean W. Freeman, William K. Jones, Julia Kukulies, Fabian Senf, Peter J. Marinescu, Max Heikenfeld, Kelcy N. Brunner, Eric C. Bruning, Scott M. Collis, Robert C. Jackson, Gabrielle R. Leung, Nils Pfeifer, Bhupendra A. Raut, Stephen M. Saleeby, Philip Stier, and Susan C. van den Heever
Geosci. Model Dev., 17, 5309–5330, https://doi.org/10.5194/gmd-17-5309-2024, https://doi.org/10.5194/gmd-17-5309-2024, 2024
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Building on previous analysis tools developed for atmospheric science, the original release of the Tracking and Object-Based Analysis (tobac) Python package, v1.2, was open-source, modular, and insensitive to the type of gridded input data. Here, we present the latest version of tobac, v1.5, which substantially improves scientific capabilities and computational efficiency from the previous version. These enhancements permit new uses for tobac in atmospheric science and potentially other fields.
Taneil Uttal, Leslie M. Hartten, Siri Jodha Khalsa, Barbara Casati, Gunilla Svensson, Jonathan Day, Jareth Holt, Elena Akish, Sara Morris, Ewan O'Connor, Roberta Pirazzini, Laura X. Huang, Robert Crawford, Zen Mariani, Øystein Godøy, Johanna A. K. Tjernström, Giri Prakash, Nicki Hickmon, Marion Maturilli, and Christopher J. Cox
Geosci. Model Dev., 17, 5225–5247, https://doi.org/10.5194/gmd-17-5225-2024, https://doi.org/10.5194/gmd-17-5225-2024, 2024
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A Merged Observatory Data File (MODF) format to systematically collate complex atmosphere, ocean, and terrestrial data sets collected by multiple instruments during field campaigns is presented. The MODF format is also designed to be applied to model output data, yielding format-matching Merged Model Data Files (MMDFs). MODFs plus MMDFs will augment and accelerate the synergistic use of model results with observational data to increase understanding and predictive skill.
Chongzhi Yin, Shin-ichiro Shima, Lulin Xue, and Chunsong Lu
Geosci. Model Dev., 17, 5167–5189, https://doi.org/10.5194/gmd-17-5167-2024, https://doi.org/10.5194/gmd-17-5167-2024, 2024
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We investigate numerical convergence properties of a particle-based numerical cloud microphysics model (SDM) and a double-moment bulk scheme for simulating a marine stratocumulus case, compare their results with model intercomparison project results, and present possible explanations for the different results of the SDM and the bulk scheme. Aerosol processes can be accurately simulated using SDM, and this may be an important factor affecting the behavior and morphology of marine stratocumulus.
Alberto Martilli, Negin Nazarian, E. Scott Krayenhoff, Jacob Lachapelle, Jiachen Lu, Esther Rivas, Alejandro Rodriguez-Sanchez, Beatriz Sanchez, and José Luis Santiago
Geosci. Model Dev., 17, 5023–5039, https://doi.org/10.5194/gmd-17-5023-2024, https://doi.org/10.5194/gmd-17-5023-2024, 2024
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Here, we present a model that quantifies the thermal stress and its microscale variability at a city scale with a mesoscale model. This tool can have multiple applications, from early warnings of extreme heat to the vulnerable population to the evaluation of the effectiveness of heat mitigation strategies. It is the first model that includes information on microscale variability in a mesoscale model, something that is essential for fully evaluating heat stress.
Nathan P. Arnold
Geosci. Model Dev., 17, 5041–5056, https://doi.org/10.5194/gmd-17-5041-2024, https://doi.org/10.5194/gmd-17-5041-2024, 2024
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Earth system models often represent the land surface at smaller scales than the atmosphere, but surface–atmosphere coupling uses only aggregated surface properties. This study presents a method to allow heterogeneous surface properties to modify boundary layer updrafts. The method is tested in single column experiments. Updraft properties are found to reasonably covary with surface conditions, and simulated boundary layer variability is enhanced over more heterogeneous land surfaces.
Enrico Dammers, Janot Tokaya, Christian Mielke, Kevin Hausmann, Debora Griffin, Chris McLinden, Henk Eskes, and Renske Timmermans
Geosci. Model Dev., 17, 4983–5007, https://doi.org/10.5194/gmd-17-4983-2024, https://doi.org/10.5194/gmd-17-4983-2024, 2024
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Nitrogen dioxide (NOx) is produced by sources such as industry and traffic and is directly linked to negative impacts on health and the environment. The current construction of emission inventories to keep track of NOx emissions is slow and time-consuming. Satellite measurements provide a way to quickly and independently estimate emissions. In this study, we apply a consistent methodology to derive NOx emissions over Germany and illustrate the value of having such a method for fast projections.
Yuhan Xu, Sheng Fang, Xinwen Dong, and Shuhan Zhuang
Geosci. Model Dev., 17, 4961–4982, https://doi.org/10.5194/gmd-17-4961-2024, https://doi.org/10.5194/gmd-17-4961-2024, 2024
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Recent atmospheric radionuclide leakages from unknown sources have posed a new challenge in nuclear emergency assessment. Reconstruction via environmental observations is the only feasible way to identify sources, but simultaneous reconstruction of the source location and release rate yields high uncertainties. We propose a spatiotemporally separated reconstruction strategy that avoids these uncertainties and outperforms state-of-the-art methods with respect to accuracy and uncertainty ranges.
Shaokun Deng, Shengmu Yang, Shengli Chen, Daoyi Chen, Xuefeng Yang, and Shanshan Cui
Geosci. Model Dev., 17, 4891–4909, https://doi.org/10.5194/gmd-17-4891-2024, https://doi.org/10.5194/gmd-17-4891-2024, 2024
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Global offshore wind power development is moving from offshore to deeper waters, where floating offshore wind turbines have an advantage over bottom-fixed turbines. However, current wind farm parameterization schemes in mesoscale models are not applicable to floating turbines. We propose a floating wind farm parameterization scheme that accounts for the attenuation of the significant wave height by floating turbines. The results indicate that it has a significant effect on the power output.
Virve Eveliina Karsisto
Geosci. Model Dev., 17, 4837–4853, https://doi.org/10.5194/gmd-17-4837-2024, https://doi.org/10.5194/gmd-17-4837-2024, 2024
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RoadSurf is an open-source library that contains functions from the Finnish Meteorological Institute’s road weather model. The evaluation of the library shows that it is well suited for making road surface temperature forecasts. The evaluation was done by making forecasts for about 400 road weather stations in Finland with the library. Accurate forecasts help road authorities perform salting and plowing operations at the right time and keep roads safe for drivers.
Perrine Hamel, Martí Bosch, Léa Tardieu, Aude Lemonsu, Cécile de Munck, Chris Nootenboom, Vincent Viguié, Eric Lonsdorf, James A. Douglass, and Richard P. Sharp
Geosci. Model Dev., 17, 4755–4771, https://doi.org/10.5194/gmd-17-4755-2024, https://doi.org/10.5194/gmd-17-4755-2024, 2024
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The InVEST Urban Cooling model estimates the cooling effect of vegetation in cities. We further developed an algorithm to facilitate model calibration and evaluation. Applying the algorithm to case studies in France and in the United States, we found that nighttime air temperature estimates compare well with reference datasets. Estimated change in temperature from a land cover scenario compares well with an alternative model estimate, supporting the use of the model for urban planning decisions.
Gerrit Kuhlmann, Erik Koene, Sandro Meier, Diego Santaren, Grégoire Broquet, Frédéric Chevallier, Janne Hakkarainen, Janne Nurmela, Laia Amorós, Johanna Tamminen, and Dominik Brunner
Geosci. Model Dev., 17, 4773–4789, https://doi.org/10.5194/gmd-17-4773-2024, https://doi.org/10.5194/gmd-17-4773-2024, 2024
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We present a Python software library for data-driven emission quantification (ddeq). It can be used to determine the emissions of hot spots (cities, power plants and industry) from remote sensing images using different methods. ddeq can be extended for new datasets and methods, providing a powerful community tool for users and developers. The application of the methods is shown using Jupyter notebooks included in the library.
Wendell W. Walters, Masayuki Takeuchi, Nga L. Ng, and Meredith G. Hastings
Geosci. Model Dev., 17, 4673–4687, https://doi.org/10.5194/gmd-17-4673-2024, https://doi.org/10.5194/gmd-17-4673-2024, 2024
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The study introduces a novel chemical mechanism for explicitly tracking oxygen isotope transfer in oxidized reactive nitrogen and odd oxygen using the Regional Atmospheric Chemistry Mechanism, version 2. This model enhances our ability to simulate and compare oxygen isotope compositions of reactive nitrogen, revealing insights into oxidation chemistry. The approach shows promise for improving atmospheric chemistry models and tropospheric oxidation capacity predictions.
Bing Zhang, Mingjian Zeng, Anning Huang, Zhengkun Qin, Couhua Liu, Wenru Shi, Xin Li, Kefeng Zhu, Chunlei Gu, and Jialing Zhou
Geosci. Model Dev., 17, 4579–4601, https://doi.org/10.5194/gmd-17-4579-2024, https://doi.org/10.5194/gmd-17-4579-2024, 2024
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By directly analyzing the proximity of precipitation forecasts and observations, a precipitation accuracy score (PAS) method was constructed. This method does not utilize a traditional contingency-table-based classification verification; however, it can replace the threat score (TS), equitable threat score (ETS), and other skill score methods, and it can be used to calculate the accuracy of numerical models or quantitative precipitation forecasts.
Hai Bui, Mostafa Bakhoday-Paskyabi, and Mohammadreza Mohammadpour-Penchah
Geosci. Model Dev., 17, 4447–4465, https://doi.org/10.5194/gmd-17-4447-2024, https://doi.org/10.5194/gmd-17-4447-2024, 2024
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We developed a new wind turbine wake model, the Simple Actuator Disc for Large Eddy Simulation (SADLES), integrated with the widely used Weather Research and Forecasting (WRF) model. WRF-SADLES accurately simulates wind turbine wakes at resolutions of a few dozen meters, aligning well with idealized simulations and observational measurements. This makes WRF-SADLES a promising tool for wind energy research, offering a balance between accuracy, computational efficiency, and ease of implementation.
Changliang Shao and Lars Nerger
Geosci. Model Dev., 17, 4433–4445, https://doi.org/10.5194/gmd-17-4433-2024, https://doi.org/10.5194/gmd-17-4433-2024, 2024
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This paper introduces and evaluates WRF-PDAF, a fully online-coupled ensemble data assimilation (DA) system. A key advantage of the WRF-PDAF configuration is its ability to concurrently integrate all ensemble states, eliminating the need for time-consuming distribution and collection of ensembles during the coupling communication. The extra time required for DA amounts to only 20.6 % per cycle. Twin experiment results underscore the effectiveness of the WRF-PDAF system.
Jan Clemens, Lars Hoffmann, Bärbel Vogel, Sabine Grießbach, and Nicole Thomas
Geosci. Model Dev., 17, 4467–4493, https://doi.org/10.5194/gmd-17-4467-2024, https://doi.org/10.5194/gmd-17-4467-2024, 2024
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Lagrangian transport models simulate the transport of air masses in the atmosphere. For example, one model (CLaMS) is well suited to calculating transport as it uses a special coordinate system and special vertical wind. However, it only runs inefficiently on modern supercomputers. Hence, we have implemented the benefits of CLaMS into a new model (MPTRAC), which is already highly efficient on modern supercomputers. Finally, in extensive tests, we showed that CLaMS and MPTRAC agree very well.
Manuel López-Puertas, Federico Fabiano, Victor Fomichev, Bernd Funke, and Daniel R. Marsh
Geosci. Model Dev., 17, 4401–4432, https://doi.org/10.5194/gmd-17-4401-2024, https://doi.org/10.5194/gmd-17-4401-2024, 2024
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The radiative infrared cooling of CO2 in the middle atmosphere is crucial for computing its thermal structure. It requires one however to include non-local thermodynamic equilibrium processes which are computationally very expensive, which cannot be afforded by climate models. In this work, we present an updated, efficient, accurate and very fast (~50 µs) parameterization of that cooling able to cope with CO2 abundances from half the pre-industrial values to 10 times the current abundance.
Felix Wieser, Rolf Sander, Changmin Cho, Hendrik Fuchs, Thorsten Hohaus, Anna Novelli, Ralf Tillmann, and Domenico Taraborrelli
Geosci. Model Dev., 17, 4311–4330, https://doi.org/10.5194/gmd-17-4311-2024, https://doi.org/10.5194/gmd-17-4311-2024, 2024
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The chemistry scheme of the atmospheric box model CAABA/MECCA is expanded to achieve an improved aerosol formation from emitted organic compounds. In addition to newly added reactions, temperature-dependent partitioning of all new species between the gas and aqueous phases is estimated and included in the pre-existing scheme. Sensitivity runs show an overestimation of key compounds from isoprene, which can be explained by a lack of aqueous-phase degradation reactions and box model limitations.
Zehua Bai, Qizhong Wu, Kai Cao, Yiming Sun, and Huaqiong Cheng
Geosci. Model Dev., 17, 4383–4399, https://doi.org/10.5194/gmd-17-4383-2024, https://doi.org/10.5194/gmd-17-4383-2024, 2024
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There is relatively limited research on the application of scientific computing on RISC CPU platforms. The MIPS architecture CPUs, a type of RISC CPUs, have distinct advantages in energy efficiency and scalability. The air quality modeling system can run stably on the MIPS and LoongArch platforms, and the experiment results verify the stability of scientific computing on the platforms. The work provides a technical foundation for the scientific application based on MIPS and LoongArch.
Yafang Guo, Chayan Roychoudhury, Mohammad Amin Mirrezaei, Rajesh Kumar, Armin Sorooshian, and Avelino F. Arellano
Geosci. Model Dev., 17, 4331–4353, https://doi.org/10.5194/gmd-17-4331-2024, https://doi.org/10.5194/gmd-17-4331-2024, 2024
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This research focuses on surface ozone (O3) pollution in Arizona, a historically air-quality-challenged arid and semi-arid region in the US. The unique characteristics of this kind of region, e.g., intense heat, minimal moisture, and persistent desert shrubs, play a vital role in comprehending O3 exceedances. Using the WRF-Chem model, we analyzed O3 levels in the pre-monsoon month, revealing the model's skill in capturing diurnal and MDA8 O3 levels.
Christoph Fischer, Andreas H. Fink, Elmar Schömer, Marc Rautenhaus, and Michael Riemer
Geosci. Model Dev., 17, 4213–4228, https://doi.org/10.5194/gmd-17-4213-2024, https://doi.org/10.5194/gmd-17-4213-2024, 2024
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This study presents a method for identifying and tracking 3-D potential vorticity structures within African easterly waves (AEWs). Each identified structure is characterized by descriptors, including its 3-D position and orientation, which have been validated through composite comparisons. A trough-centric perspective on the descriptors reveals the evolution and distinct characteristics of AEWs. These descriptors serve as valuable statistical inputs for the study of AEW-related phenomena.
Sandro Vattioni, Andrea Stenke, Beiping Luo, Gabriel Chiodo, Timofei Sukhodolov, Elia Wunderlin, and Thomas Peter
Geosci. Model Dev., 17, 4181–4197, https://doi.org/10.5194/gmd-17-4181-2024, https://doi.org/10.5194/gmd-17-4181-2024, 2024
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We investigate the sensitivity of aerosol size distributions in the presence of strong SO2 injections for climate interventions or after volcanic eruptions to the call sequence and frequency of the routines for nucleation and condensation in sectional aerosol models with operator splitting. Using the aerosol–chemistry–climate model SOCOL-AERv2, we show that the radiative and chemical outputs are sensitive to these settings at high H2SO4 supersaturations and how to obtain reliable results.
Najmeh Kaffashzadeh and Abbas-Ali Aliakbari Bidokhti
Geosci. Model Dev., 17, 4155–4179, https://doi.org/10.5194/gmd-17-4155-2024, https://doi.org/10.5194/gmd-17-4155-2024, 2024
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This paper assesses the capability of two state-of-the-art global datasets in simulating surface ozone over Iran using a new methodology. It is found that the global model data need to be downscaled for regulatory purposes or policy applications at local scales. The method can be useful not only for the evaluation but also for the prediction of other chemical species, such as aerosols.
Franciscus Liqui Lung, Christian Jakob, A. Pier Siebesma, and Fredrik Jansson
Geosci. Model Dev., 17, 4053–4076, https://doi.org/10.5194/gmd-17-4053-2024, https://doi.org/10.5194/gmd-17-4053-2024, 2024
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Traditionally, high-resolution atmospheric models employ periodic boundary conditions, which limit simulations to domains without horizontal variations. In this research open boundary conditions are developed to replace the periodic boundary conditions. The implementation is tested in a controlled setup, and the results show minimal disturbances. Using these boundary conditions, high-resolution models can be forced by a coarser model to study atmospheric phenomena in realistic background states.
Caroline Arnold, Shivani Sharma, Tobias Weigel, and David S. Greenberg
Geosci. Model Dev., 17, 4017–4029, https://doi.org/10.5194/gmd-17-4017-2024, https://doi.org/10.5194/gmd-17-4017-2024, 2024
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In atmospheric models, rain formation is simplified to be computationally efficient. We trained a machine learning model, SuperdropNet, to emulate warm-rain formation based on super-droplet simulations. Here, we couple SuperdropNet with an atmospheric model in a warm-bubble experiment and find that the coupled simulation runs stable and produces reasonable results, making SuperdropNet a viable ML proxy for droplet simulations. We also present a comprehensive benchmark for coupling architectures.
Byoung-Joo Jung, Benjamin Ménétrier, Chris Snyder, Zhiquan Liu, Jonathan J. Guerrette, Junmei Ban, Ivette Hernández Baños, Yonggang G. Yu, and William C. Skamarock
Geosci. Model Dev., 17, 3879–3895, https://doi.org/10.5194/gmd-17-3879-2024, https://doi.org/10.5194/gmd-17-3879-2024, 2024
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We describe the multivariate static background error covariance (B) for the JEDI-MPAS 3D-Var data assimilation system. With tuned B parameters, the multivariate B gives physically balanced analysis increment fields in the single-observation test framework. In the month-long cycling experiment with a global 60 km mesh, 3D-Var with static B performs stably. Due to its simple workflow and minimal computational requirements, JEDI-MPAS 3D-Var can be useful for the research community.
Michal Belda, Nina Benešová, Jaroslav Resler, Peter Huszár, Ondřej Vlček, Pavel Krč, Jan Karlický, Pavel Juruš, and Kryštof Eben
Geosci. Model Dev., 17, 3867–3878, https://doi.org/10.5194/gmd-17-3867-2024, https://doi.org/10.5194/gmd-17-3867-2024, 2024
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For modeling atmospheric chemistry, it is necessary to provide data on emissions of pollutants. These can come from various sources and in various forms, and preprocessing of the data to be ingestible by chemistry models can be quite challenging. We developed the FUME processor to use a database layer that internally transforms all input data into a rigid structure, facilitating further processing to allow for emission processing from the continental to the street scale.
Bent Harnist, Seppo Pulkkinen, and Terhi Mäkinen
Geosci. Model Dev., 17, 3839–3866, https://doi.org/10.5194/gmd-17-3839-2024, https://doi.org/10.5194/gmd-17-3839-2024, 2024
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Probabilistic precipitation nowcasting (local forecasting for 0–6 h) is crucial for reducing damage from events like flash floods. For this goal, we propose the DEUCE neural-network-based model which uses data and model uncertainties to generate an ensemble of potential precipitation development scenarios for the next hour. Trained and evaluated with Finnish precipitation composites, DEUCE was found to produce more skillful and reliable nowcasts than established models.
Emma Howard, Steven Woolnough, Nicholas Klingaman, Daniel Shipley, Claudio Sanchez, Simon C. Peatman, Cathryn E. Birch, and Adrian J. Matthews
Geosci. Model Dev., 17, 3815–3837, https://doi.org/10.5194/gmd-17-3815-2024, https://doi.org/10.5194/gmd-17-3815-2024, 2024
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This paper describes a coupled atmosphere–mixed-layer ocean simulation setup that will be used to study weather processes in Southeast Asia. The set-up has been used to compare high-resolution simulations, which are able to partially resolve storms, to coarser simulations, which cannot. We compare the model performance at representing variability of rainfall and sea surface temperatures across length scales between the coarse and fine models.
Álvaro González-Cervera and Luis Durán
EGUsphere, https://doi.org/10.5194/egusphere-2024-958, https://doi.org/10.5194/egusphere-2024-958, 2024
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RASCAL is an open-source Python tool designed for reconstructing daily climate observations, especially in regions with complex local phenomena. It merges large-scale weather patterns with local weather using the Analog Method. Evaluations in central Spain show that RASCAL outperforms ERA20C reanalysis in reconstructing precipitation and temperature. RASCAL offers opportunities of broad scientific applications, from short-term forecasts to local-scale climate change scenarios.
Phuong Loan Nguyen, Lisa V. Alexander, Marcus J. Thatcher, Son C. H. Truong, Rachael N. Isphording, and John L. McGregor
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-84, https://doi.org/10.5194/gmd-2024-84, 2024
Revised manuscript accepted for GMD
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We apply a comprehensive approach to select a subset of CMIP6 that is suitable for dynamical downscaling over Southeast Asia by considering model performance, model independence, data availability, and future climate change spread. The standardised benchmarking framework is applied to identify a subset of models through two stages of assessment: statistical-based and process-based metrics. We finalize a sub-set of two independent models for dynamical downscaling over Southeast Asia.
Andrés Yarce Botero, Michiel van Weele, Arjo Segers, Pier Siebesma, and Henk Eskes
Geosci. Model Dev., 17, 3765–3781, https://doi.org/10.5194/gmd-17-3765-2024, https://doi.org/10.5194/gmd-17-3765-2024, 2024
Short summary
Short summary
HARMONIE WINS50 reanalysis data with 0.025° × 0.025° resolution from 2019 to 2021 were coupled with the LOTOS-EUROS Chemical Transport Model. HARMONIE and ECMWF meteorology configurations against Cabauw observations (52.0° N, 4.9° W) were evaluated as simulated NO2 concentrations with ground-level sensors. Differences in crucial meteorological input parameters (boundary layer height, vertical diffusion coefficient) between the hydrostatic and non-hydrostatic models were analysed.
Cited articles
Aires, F., Prigent, C., Bernardo, F., Jiménez, C., Saunders, R., and Brunel, P.: A Tool to Estimate Land-Surface Emissivities at Microwave frequencies (TELSEM) for use in numerical weather prediction, Q. J. Roy. Meteor. Soc., 137, 690–699, 2011.
Andersson, E., Haseler, J., Undén, P., Courtier, P., Kelly, G., Vasiljevic, D., Brankovic, C., Gaffard, C., Hollingsworth, A., Jakob, C., Janssen, P., Klinker, E., Lanzinger, A., Miller, M., Rabier, F., Simmons, A., Strauss, B., Viterbo, P., Cardinali, C., and Thépaut, J.-N.: The ECMWF implementation of three-dimensional variational assimilation (3D-Var). III: Experimental results, Q. J. Roy. Meteor. Soc., 124, 1831–1860, https://doi.org/10.1002/qj.49712455004, 1998.
Andrey-Andrés, J., Fourrié, N., Guidard, V., Armante, R., Brunel, P., Crevoisier, C., and Tournier, B.: A simulated observation database to assess the impact of the IASI-NG hyperspectral infrared sounder, Atmos. Meas. Tech., 11, 803–818, https://doi.org/10.5194/amt-11-803-2018, 2018.
Aumann, H., Xiuhong, C., Fishbein, E., Geer, A., Havemann, S., Huang, X., Liu, X., Liuzzi, G., DeSouza-Machado, S., Manning, E. M., Masiello, G., Matricardi, M., Moradi, I., Natrai, V., Serio, C., Strow, L., Vidot, J., Wilson, C., Wu, W., Yang, Q., and Yung, Y. L.: Evaluation of Radiative Transfer Models with Clouds, J. Geophys. Res.-Atmos., 123, https://doi.org/10.1029/2017JD028063, online first, 2018.
Baran, A. J., Francis, P. N., Labonnote, L.-C., and Doutriaux-Boucher, M.: A scattering phase function for ice cloud: Tests of applicability using aircraft and satellite multi-angle multi-wavelength radiance measurements of cirrus, Q. J. Roy. Meteor. Soc., 127, 2395–2416, 2001.
Baran, A. J., Cotton, R., Furtado, K., Havemann, S., Labonnote, L.-C., Marenco, F., Smith, A., and Thelen, J.-C.: A self-consistent scattering model for cirrus. II: The high and low frequencies, Q. J. Roy. Meteor. Soc., 140, 1039–1057, https://doi.org/10.1002/qj.2193, 2014.
Baum, B. A., Yang, P., Heymsfield, A. J., Schmitt, C., Xie, Y., Bansemer, A., Hu, Y. X., and Zhang, Z.: Improvements to shortwave bulk scattering and absorption models for the remote sensing of ice clouds, J. Appl. Meteorol. Clim., 50, 1037–1056, 2011.
Bauer, P.: Including a melting layer in microwave radiative transfer simulation for clouds, Atmos. Res., 67, 9–30, 2001.
Bauer, P., Moreau, E., Chevallier, F., and O'Keeffe, U.: Multiple-scattering microwave radiative transfer for data assimilation applications, Q. J. Roy. Meteor. Soc., 132, 1259–1281, https://doi.org/10.1256/qj.05.153, 2006.
Bauer, P., Geer, A. J., Lopez, P., and Salmond, D.: Direct 4D-Var assimilation of all-sky radiances. Part I: Implementation, Q. J. Roy. Meteor. Soc., 136, 1868–1885, https://doi.org/10.1002/qj.659, 2010.
Blackmore, T. A., Saunders, R., and Keogh, S. J.: Verifying NWP model analyses and forecasts using simulated satellite imagery, in: Proceedings of the 2014 EUMETSAT Meteorological Satellite Conference, 22–26 September 2014, Geneva, available at: https://www.eumetsat.int/website/home/News/ConferencesandEvents/DAT_2076129.html (last access: 22 June 2018), Session 8: Oral proceedings, 2014.
Bodas-Salcedo, A., Webb, M. J., Bony, S., Chepfer, H., Dufresne, J., Klein, S. A., Zhang, Y., Marchand, R., Haynes, J. M., Pincus, R., and John, V. O.: COSP: Satellite simulation software for model assessment, B. Am. Meteorol. Soc., 92, 1023–1043, https://doi.org/10.1175/2011BAMS2856.1, 2011.
Borbas, E. E. and Ruston, B. C.: The RTTOV UWiremis IR land surface emissivity module, NWP SAF report, available at: http://nwpsaf.eu/vs_reports/nwpsaf-mo-vs-042.pdf (last access: 22 June 2018), 2010.
Borbas, E. E, Hulley, G., Knuteson, R., and Feltz, M.: MEaSUREs Unified and Coherent Land Surface Temperature and Emissivity (LST&E) Earth System Data Record (ESDR): The Combined ASTER and MODIS Emissivity database over Land (CAMEL) User's guide, Technical documentation, 30 pp., available at: https://lpdaac.usgs.gov/sites/default/files/public/product_documentation/cam5k30_v1_user_guide_atbd.pdf (last access: 2 July 2018), 2017.
Bormann, N., Geer, A., and English, S. J.: Evaluation of the microwave ocean surface emissivity model FASTEM-5 in the IFS, ECMWF, Technical Memorandum 667, 18 pp., 2012.
Boudala, F. S., Isaac, G. A., Fu, Q., and Cober, S. G.: Parameterization of effective ice particle size for high-latitude clouds, Int. J. Climatol., 22, 1267–1284, 2002.
Chandrasekhar, S.: Radiative Transfer, Dover, New York, 1960.
Chen, Y., Weng, F., Han, Y., and Liu, Q.: Validation of the community radiative transfer model (CRTM) by using CloudSat Data, J. Geophys. Res., 113, 2156–2202, 2008.
Chevallier, F., Chédin, A., Chéruy, F., and Morcrette, J. J.: TIGR-like atmospheric profile databases for accurate flux computation, Q. J. Roy. Meteor. Soc., 126, 777–785, 2000.
Chevallier, F., Di Michele, S., and Mc Nally A.: Diverse profile datasets from the ECMWF 91-level short-range forecasts, ECMWF, NWP SAF Technical Report, 10, 14 pp., 2006.
Chou, M.-D., Lee, K.-T., Tsay, S.-C., and Fu, Q.: Parameterization for Cloud Longwave scattering for use in Atmospheric Models, J. Climate, 12, 159–169, 1999.
Clough, S. A., Shephard, M. W., Mlawer, E. J., Delamere, J. S., Iacono, M. J., Cady-Pereira, K., Boukabara, S., and Brown, P. D.: Atmospheric radiative transfer modeling: a summary of the AER codes, Short Communication, J. Quant. Spectrosc. Ra., 91, 233–244, 2005.
Ding, S., Yang, P., Weng, F., Liu, Q., Han, Y., Van Delst, P., Li, J., and Baum, B.: Validation of the community radiative transfer model, J. Quant. Spectrosc. Ra., 112, 1050–1064, 2011.
English, S. J., Poulsen, C., and Smith, A. J.: Forward modelling for liquid water cloud and land surface emissivity. Proceedings of ECMWF/EUMETSAT workshop on the use of ATOVS data for NWP assimilation, ECMWF, Reading, RG2 9AX, UK, 91–96, 2000.
Eyre, J. R.: A fast radiative transfer model for satellite sounding systems, ECMWF, Technical Memorandum, 176, 28 pp., 1991.
Eyre, J. R. and Woolf, H.: Transmittance of atmospheric gases in the microwave region, Appl. Optics, 27, 3244–3249, 1988.
Eyre, J. R., Kelly, G. A., McNally, A. P., Andersson, E., and Persson, A.: Assimilation of TOVS radiance information through one-dimensional variational analysis, Q. J. Roy. Meteor. Soc., 119, 1427–1463, https://doi.org/10.1002/qj.49711951411, 1993.
Funke, B., López-Puertas, M., García-Comas, M., Kaufmann, M., Höpfner, M., and Stiller G. P.: GRANADA: A Generic RAdiative traNsfer AnD non-LTE population algorithm, J. Quant. Spectrosc. Ra., 113, 1771–1817, 2012.
Garand, L., Turner, D. S., Larocque, M., Bates, J., Boukabara, S., Brunel, P., Chevallier, F., Deblonde, G., Engelen, R., Hollingshead, M., Jackson, D., Jedlovec, G., Joiner, J., Kleespies, T., McKague, D. S., McMillin, L., Moncet, J.-L., Pardo, J. R., Rayer, P. J., Salathe, E., Saunders, R., Scott, N. A., Van Delst, P., and Woolf, H.: Radiance and Jacobian intercomparison of radiative transfer models applied to HIRS and AMSU channels, J. Geophys. Res., 106, 24017–24031, https://doi.org/10.1029/2000JD000184, 2001.
Geer, A. J. and Baordo, F.: Improved scattering radiative transfer for frozen hydrometeors at microwave frequencies, Atmos. Meas. Tech., 7, 1839–1860, https://doi.org/10.5194/amt-7-1839-2014, 2014.
Geer, A. J., Bauer, P., and O'Dell, C. W.: A revised cloud overlap scheme for fast microwave radiative transfer in rain and cloud, J. Appl. Meteorol. Clim., 48, 2257–2270, 2009.
Geer, A. J., Baordo, F., Bormann, N., Chambon, P., English, S. J., Kazumori, M., Lawrence, H., Lean, P., Lonitz, K., and Lupu, C.: The growing impact of satellite observations sensitive to humidity, cloud and precipitation, Q. J. Roy. Meteor. Soc., 143, 3189–3206, https://doi.org/10.1002/qj.3172, 2017.
Gordon, I. E., Rothman, L. S., Hill, C., et al.: The HITRAN2016 Molecular Spectroscopic Database, J. Quant. Spectrosc. Ra., 203, 3–69, https://doi.org/10.1016/j.jqsrt.2017.06.038, 2017.
Havemann, S.: The development of a fast radiative transfer model based on an empirical orthogonal functions (EOF) technique, SPIE, 6405, 348–358, 2006.
Havemann, S., Thelen, J.-C., and Taylor, J. P.: The Havemann-Taylor Fast Radiative Transfer Code: Exact fast radiative transfer for scattering atmospheres using Principal Components (PCs), Current problems in atmospheric radiation (IRS 2008) Edited by: Nakajima, T; Yamasoe, MA Book Series: AIP Conference Proceedings Volume: 1100 Pages: 38-40, 2009.
Hess, M., Koepke, P., and Schult, I. : Optical Properties of Aerosols and Clouds: the software package OPAC, B. Am. Meteorol. Soc., 79, 831–844, 1998.
Hocking, J.: Interpolation methods in the RTTOV fast radiative transfer model, Met Office Forecasting Research Technical Report 590, available at: http://www.metoffice.gov.uk/binaries/content/assets/mohippo/pdf/i/k/frtr590.pdf (last access: 2 July 2018), 2014.
Hocking, J.: A visible/infrared multiple-scattering model for RTTOV, NWP SAF report, available at: http://nwpsaf.eu/publications/tech_reports/nwpsaf-mo-tr-031.pdf (last access: 2 July 2018), 2015.
Hocking, J., Rayer, P., Rundle, D., Saunders, R. W., Matricardi, M., Geer, A., Brunel, P., and Vidot, J.: RTTOV v12 User Guide, NWP SAF, available at: https://www.nwpsaf.eu/site/software/rttov/documentation/ (last access: 2 July 2018), 2017.
Joseph, J. H., Wiscombe, W. J., and Weinman, J. A.: The Delta-Eddington Approximation for Radiative Flux Transfer, J. Atmos. Sci., 33, 2452–2459, 1976.
Karbou, F., Gérard, E., and Rabier, F.: Microwave land emissivity and skin temperature for AMSU-A and -B assimilation over land, Q. J. Roy. Meteor. Soc., 132, 2333–2355, https://doi.org/10.1256/qj.05.216, 2006.
Karbou, F., Gérard, E., and Rabier, F. : Global 4DVAR assimilation and forecast experiments using AMSU observations over land. Part I: Impacts of various land surface emissivity parameterizations, Weather Forecast., 25, 5–19, 2010.
Kazumori, M. and English, S. J.: Use of the ocean surface wind direction signal in microwave radiance assimilation, Q. J. Roy. Meteor. Soc., 141, 1354–1375, 2015.
Li, J., Wolf, W. W., Menzel, W. P., Zhang, W., Huang, H. L., and Achtor, T. H.: Global soundings of the atmosphere from ATOVS measurements: The algorithm and validation, J. Appl. Meteorol., 39, 1248–1268, 2000.
Liebe, H. J., Manabe, T., and Hufford, G. A.: Millimeter-wave attenuation and delay rates due to fog/cloud conditions, IEEE T. Antenn. Propag., 37, 1617–1612, 1989.
Liljegren, J. C., Boukabara, S. A., Cady-Pereira, K., and Clough, S. A.: The effect of the half-width of the 22-GHz water vapor line on retrievals of temperature and water vapor profiles with a 12-channel microwave radiometer, IEEE T. Geosci. Remote, 43, 1102–1108, 2005.
Liu, G.: A database of microwave single-scattering properties for non-spherical ice particles, B. Am. Meteorol. Soc., 111, 1563–1570, 2008.
Liu, X., Smith, W. L., Zhou, D. K., and Larar, A.: Principal component-based radiative transfer model for hyperspectral sensors: Theoretical concept, Appl. Optics, 45, 201–209, 2006.
Liu, Q., Weng, F., and English, S.: An improved fast microwave water emissivity model, IEEE, T. Geosci. Remote, 49, 1238–1250, 2011.
Lupu, C. and Geer, A. J.: Operational implementation of RTTOV-11 in the IFS, ECMWF, Research Dept., Technical Memorandum, 748, 19 pp., 2015.
Lupu, C. and Wilhelmsson T.: A guide to simulated satellite images in the IFS, ECMWF Research Department Memorandum RD16-064, 10 pp., available at: https://software.ecmwf.int/wiki/display/FCST/Simulated+satellite+data?preview=/55127736/97382070/A_guide_to_simulated_satellite_images_in_the_IFS.pdf (last access: 2 July 2018), 2016.
Matricardi, M.: RTIASI-4, a new version of the ECMWF fast radiative transfer model for the infrared atmospheric sounding intererometer, ECMWF, Technical Memorandum, 425, 63 pp., 2003.
Matricardi, M.: The inclusion of aerosols and clouds in RTIASI, the ECMWF fast radiative transfer model for the Infrared Atmospheric Sounding Interferometer, ECMWF, Technical Memorandum, 474, 53 pp., 2005.
Matricardi, M.: The generation of RTTOV regression coefficients for IASI and AIRS using a new profile training set and a new line-by-line database, ECMWF, Technical Memorandum, 564, 47 pp., 2008.
Matricardi, M.: A principal component based version of the RTTOV fast radiative transfer model, Q. J. Roy. Meteor. Soc., 136, 1823–1835, https://doi.org/10.1002/qj.680, 2010.
Matricardi, M. and McNally, A.: The direct assimilation of principal components of IASI spectra in the ECMWF 4D-Var, Q. J. Roy. Meteor. Soc., 140, 573–582, 2014.
Matricardi, M., Chevallier, F., Kelly, G., and Thepaut, J.-N.: An improved general fast radiative transfer model for the assimilation of radiance observations, Q. J. Roy. Meteor. Soc., 130, 153–173, 2004.
Matricardi, M., López Puertas, M., and Funke, B.: Modeling of nonlocal thermodynamic equilibrium effects in the principal component based version of the RTTOV fast radiative transfer model, J. Geophys. Res.-Atmos., 123, 5741–5761, https://doi.org/10.1029/2018JD028657, 2018.
McFarquhar, G. M., Iacobellis, S., and Somerville, R. C. J.: SCM simulations of tropical ice clouds using observationally based parameterizations of microphysics, J. Climate, 16, 1643–1664, 2003.
McMillin, L. M. and Fleming, H. E.: Atmospheric Transmittance of an Absorbing Gas: A Computationally Fast and Accurate Transmittance Model for Absorbing Gases with Constant Mixing Ratios in Inhomogeneous Atmospheres, Appl. Optics, 15, 358–363, 1976.
McMillin, L. M., Crone, L. J., and Kleespies, T. J.: Atmospheric transmittance of an absorbing gas. 5. Improvements to the OPTRAN approach, Appl. Optics, 34, 8396–8399, 1995.
McMillin, L. M., Xiong, Han, X., Y., Kleespies, T. J., and Van Delst, P.: Atmospheric transmittance of an absorbing gas. 7. Further improvements to the OPTRAN 6 approach, Appl. Optics, 45, 2028–2034. https://doi.org/10.1364/AO.45.002028, 2006.
Moncet, J., Uymin, G., Liang, P., and Lipton, A. E.: Fast and Accurate Radiative Transfer in the Thermal Regime by Simultaneous Optimal Spectral Sampling over All Channels, J. Atmos. Sci., 72, 2622–2641, https://doi.org/10.1175/JAS-D-14-0190.1, 2015.
Ou, S. C. and Liou, K. N.: Ice microphysics and climatic temperature feedback, Atmos. Res., 35, 127–138, 1995.
Payne, V. H., Delamere, J. S., Cady-Pereira, K. E., Gamache, R. R., Moncet, J.-L., Mlawer, E. J., and Clough, S. A.: Air-broadened half-widths of the 22- and 183-GHz water-vapor lines, IEEE T. Geosci. Remote, 46, 3601–3617, 2008.
Poli, P., Dee, D., Saunders, R., John, V., Rayer, P., Schulz, J., Holmlund, K., Coppens, D., Klaes, D., Johnson, J., Esfandiari, A., Gerasimov, I., Zamkoff, E., Al-Jazrawi, A., Santek, D., Albani, M., Brunel, P., Fennig, K., Schröeder, M., Kobayashi, S., Oertel, D., Döehler, W., Späenkuch, D., and Bojinski, S.: Recent advances in satellite data rescue, B. Am. Meteorol. Soc., 98, 1471–1484, https://doi.org/10.1175/BAMS-D-15-00194.1, 2017.
Prigent, C., Aires, F., Wang, D., Fox, S., and Harlow, C.: Sea-surface emissivity parametrization from microwaves to millimetre waves, Q. J. Roy. Meteor. Soc., 143, 596–605, https://doi.org/10.1002/qj.2953, 2017.
Rayer, P. J.: Fast transmittance model for satellite sounding, Appl. Optics, 34, 7387–7394, 1995.
Rochon, Y. J., Garand, L., Turner, D. S., and Polavarapu, S.: Jacobian mapping between vertical coordinate systems in data assimilation, Q. J. Roy. Meteor. Soc., 133, 1547–1558, https://doi.org/10.1002/qj.117, 2007.
Rothman, L. S., Gordon, I. E., Babikov, Y., et al.: The HITRAN2012 molecular spectroscopic database, J. Quant. Spectrosc. Ra., 130, 4–50, https://doi.org/10.1016/j.jqsrt.2013.07.002, 2013.
Saunders, R., Matricardi, M., and Brunel, P.: An improved fast radiative transfer model for assimilation of satellite radiance observations, Q. J. Roy. Meteor. Soc., 125, 1407–1425, https://doi.org/10.1002/qj.1999.49712555615, 1999.
Saunders, R., Brunel, P., English, S., Bauer, P., O'Keefe, U., Francis, P. N., and Rayer, P.: RTTOV-8 science and validation report, 46 pp., available at: https://nwpsaf.eu/oldsite/deliverables/rtm/rttov8_svr.pdf (last access: 2 July 2018), 2006.
Saunders, R., Rayer, P., Brunel, P., von Engeln, A., Bormann, N., Strow, L., Hannon, S., Heilliette, S., Liu, X., Miskolczi, F., Han, Y., Masiello, G., Moncet, J.-L., Uymin, G., Sherlock, V., and Turner, D. S.: A comparison of radiative transfer models for simulating Atmospheric Infrared Sounder (AIRS) radiances, J. Geophys. Res., 112, D01S90, https://doi.org/10.1029/2006JD007088, 2007.
Saunders, R., Hocking, J., Rundle, D., Rayer, P., Havemann, S., Matricardi, M., Geer, A., Lupu, C., Brunel, P., and Vidot, J.: RTTOV v12 science and validation report, 78 pp., available at: https://www.nwpsaf.eu/site/download/documentation/rtm/docs_rttov12/rttov12_svr.pdf (last access: 2 July 2018), 2017.
Scheck, L.: Comparison of MFASIS and RTTOV-DOM, NWP SAF report, 18 pp., available at: http://nwpsaf.eu/vs_reports/nwpsaf-mo-vs-054.pdf (last access: 2 July 2018), 2016.
Scheck, L., Frerebeau, P., Buras-Schnell, R., and Mayer, B.: A fast radiative transfer method for the simulation of visible satellite imagery, J. Quant. Spectrosc. Ra., 175, 54–67, 2016.
Sherlock, V. and Saunders, R.: ISEM-6: Infrared surface emissivity model for RTTOV-6, in: Tech. Proc. 11th Int. ATOVS Study Conf., 20–26 September 2000, Bureau of Meteorology Research Centre, Budapest, Hungary, 383–389, 2000.
Stamnes, K., Tsay, S.-C., Wiscombe, W., and Jayaweera, K.: Numerically stable algorithm for discrete-ordinate-method radiative transfer in multiple-scattering and emitting layered media, Appl. Optics, 27, 2502–2509, 1988.
Tretyakov, M. Yu., Koshelev, M. A., Dorovskikh, V. V., Makarov, D. S., and Rosenkranz, P. W.: 60-GHz oxygen band: precise broadening and central frequencies of fine structure lines, absolute absorption profile at atmospheric pressure, and revision of mixing coefficients', J. Mol. Spectrosc., 231, 1–14, https://doi.org/10.1016/j.jms.2004.11.011, 2005.
Turner, E. C. and Tett, S. F. B.: Using longwave HIRS radiances to test climate models, Clim. Dynam., 43, 1103, https://doi.org/10.1007/s00382-013-1959-6, 2014.
U.S. Standard Atmosphere: U.S. Government Printing Office, Washington, D.C., 1976.
Vidot, J. and Borbás, É.: Land surface VIS/NIR BRDF atlas for RTTOV-11: model and validation against SEVIRI land SAF albedo product, Q. J. Roy. Meteor. Soc., 140, 2186–2196, https://doi.org/10.1002/qj.2288, 2014.
Vidot, J., Baran, A. J., and Brunel, P.: A new ice cloud parameterization for infrared radiative transfer simulation of cloudy radiances: Evaluation and optimization with IIR observations and ice cloud profile retrieval products, J. Geophys. Res.-Atmos., 120, 6937–6951, https://doi.org/10.1002/2015JD023462, 2015.
Vidot, J., Brunel, P., Dumont, M., Carmagnola, C., and Hocking, J.: The VIS/NIR Land and Snow BRDF Atlas for RTTOV: Comparison between MODIS MCD43C1 C5 and C6, Remote Sens., 10, 21, https://doi.org/10.3390/rs10010021, 2018.
Wyser, K.: The effective radius in ice clouds, J. Climate, 11, 1793–1802, 1998.
Short summary
This paper describes a fast atmospheric radiative transfer model, RTTOV, which is widely used in the satellite retrieval and weather forecast model assimilation communities. It computes top-of-atmosphere radiances for visible, infrared and microwave downward-viewing satellite radiometers. It enables the satellite data, which are a key part of the observing system, to be optimally used with forecast models. The developments made to RTTOV over the past 20 years are summarised.
This paper describes a fast atmospheric radiative transfer model, RTTOV, which is widely used in...
