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
Related authors
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
Short summary
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.
Rohit Mangla, Mary Borderies, Philippe Chambon, Alan Geer, and James Hocking
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-131, https://doi.org/10.5194/amt-2024-131, 2024
Revised manuscript accepted for AMT
Short summary
Short summary
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
Short summary
Short summary
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.
Alan J. Geer, Peter Bauer, Katrin Lonitz, Vasileios Barlakas, Patrick Eriksson, Jana Mendrok, Amy Doherty, James Hocking, and Philippe Chambon
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
Short summary
Short summary
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
bulkoptical properties.
Sebastien Massart, Niels Bormann, Massimo Bonavita, and Cristina Lupu
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
Short summary
Short summary
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
Short summary
Short summary
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.
James Hocking, Jérôme Vidot, Pascal Brunel, Pascale Roquet, Bruna Silveira, Emma Turner, and Cristina Lupu
Geosci. Model Dev., 14, 2899–2915, https://doi.org/10.5194/gmd-14-2899-2021, https://doi.org/10.5194/gmd-14-2899-2021, 2021
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
Satellite radiance observations have only recently become usable in conditions of cloud and precipitation for the initialization of weather forecasts. The move to
all-skyassimilation started with data from the microwave part of the spectrum, with substantial benefit to the quality of operational forecasts. The current work shows a framework in which cloudy infrared data, with its stronger and more non-linear sensitivity, can also benefit operational-quality forecasts.
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
Short summary
Short summary
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
Short summary
Short summary
The fast radiative transfer model RTTOV-gb was developed to foster ground-based microwave radiometer data assimilation into numerical weather prediction models, as introduced in a companion paper (https://doi.org/10.5194/gmd-9-2721-2016). Here we present the updates and new features of the current version (v1.0), which is freely accessible online.
Maxence Descheemaecker, Matthieu Plu, Virginie Marécal, Marine Claeyman, Francis Olivier, Youva Aoun, Philippe Blanc, Lucien Wald, Jonathan Guth, Bojan Sič, Jérôme Vidot, Andrea Piacentini, and Béatrice Josse
Atmos. Meas. Tech., 12, 1251–1275, https://doi.org/10.5194/amt-12-1251-2019, https://doi.org/10.5194/amt-12-1251-2019, 2019
Short summary
Short summary
The future Flexible Combined Imager (FCI) on board MeteoSat Third Generation is expected to improve the detection and the quantification of aerosols. The study assesses the potential of FCI/VIS04 channel for monitoring air pollution in Europe. An observing system simulation experiment in MOCAGE is developed, and they show a large positive impact of the assimilation over a 4-month period and particularly during a severe pollution episode. The added value of geostationary data is also assessed.
Katrin Lonitz and Alan J. Geer
Atmos. Meas. Tech., 12, 405–429, https://doi.org/10.5194/amt-12-405-2019, https://doi.org/10.5194/amt-12-405-2019, 2019
Short summary
Short summary
Permittivity models for microwave frequencies of liquid water below 0°C are poorly constrained due to limited laboratory experiments and observations, especially for high microwave frequencies. This uncertainty translates directly into errors in retrieved liquid water paths of up to 80 %. This study investigates the effect of different liquid water permittivity models including models based on the most recent observations.
Fabien Carminati, Stefano Migliorini, Bruce Ingleby, William Bell, Heather Lawrence, Stuart Newman, James Hocking, and Andrew Smith
Atmos. Meas. Tech., 12, 83–106, https://doi.org/10.5194/amt-12-83-2019, https://doi.org/10.5194/amt-12-83-2019, 2019
Short summary
Short summary
The GRUAN processor is a software developed to collocate radiosonde profiles and numerical weather prediction model fields, simulate top-of-atmosphere brightness temperature at frequencies used by space-borne instruments, and propagate the radiosonde uncertainties in that simulation. This work responds to an identified lack of metrologically traceable characterisation of uncertainties in model fields that are increasingly used for the validation and calibration of space-borne instruments.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
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
Related subject area
Atmospheric sciences
Evaluation of dust emission and land surface schemes in predicting a mega Asian dust storm over South Korea using WRF-Chem
Sensitivity studies of a four-dimensional local ensemble transform Kalman filter coupled with WRF-Chem version 3.9.1 for improving particulate matter simulation accuracy
A Bayesian method for predicting background radiation at environmental monitoring stations in local-scale networks
Inclusion of the ECMWF ecRad radiation scheme (v1.5.0) in the MAR (v3.14), regional evaluation for Belgium, and assessment of surface shortwave spectral fluxes at Uccle
Development of a fast radiative transfer model for ground-based microwave radiometers (ARMS-gb v1.0): validation and comparison to RTTOV-gb
Indian Institute of Tropical Meteorology (IITM) High-Resolution Global Forecast Model version 1: an attempt to resolve monsoon prediction deadlock
Cell-tracking-based framework for assessing nowcasting model skill in reproducing growth and decay of convective rainfall
NeuralMie (v1.0): an aerosol optics emulator
Simulation performance of planetary boundary layer schemes in WRF v4.3.1 for near-surface wind over the western Sichuan Basin: a single-site assessment
FootNet v1.0: development of a machine learning emulator of atmospheric transport
Updates and evaluation of NOAA's online-coupled air quality model version 7 (AQMv7) within the Unified Forecast System
Quantifying the analysis uncertainty for nowcasting application
Improving the ensemble square root filter (EnSRF) in the Community Inversion Framework: a case study with ICON-ART 2024.01
The MESSy DWARF (based on MESSy v2.55.2)
An enhanced emission module for the PALM model system 23.10 with application for PM10 emission from urban domestic heating
Identifying lightning processes in ERA5 soundings with deep learning
Sensitivity of predicted ultrafine particle size distributions in Europe to different nucleation rate parameterizations using PMCAMx-UF v2.2
Explaining neural networks for detection of tropical cyclones and atmospheric rivers in gridded atmospheric simulation data
PALACE v1.0: Paranal Airglow Line And Continuum Emission model
Accurate space-based NOx emission estimates with the flux divergence approach require fine-scale model information on local oxidation chemistry and profile shapes
Exploring a high-level programming model for the NWP domain using ECMWF microphysics schemes
Quantifying uncertainties in satellite NO2 superobservations for data assimilation and model evaluation
ML-AMPSIT: Machine Learning-based Automated Multi-method Parameter Sensitivity and Importance analysis Tool
Coupling the urban canopy model TEB (SURFEXv9.0) with the radiation model SPARTACUS-Urbanv0.6.1 for more realistic urban radiative exchange calculation
Forecasting contrail climate forcing for flight planning and air traffic management applications: the CocipGrid model in pycontrails 0.51.0
Simulation of the heat mitigation potential of unsealing measures in cities by parameterizing grass grid pavers for urban microclimate modelling with ENVI-met (V5)
AI-NAOS: an AI-based nonspherical aerosol optical scheme for the chemical weather model GRAPES_Meso5.1/CUACE
Orbital-Radar v1.0.0: a tool to transform suborbital radar observations to synthetic EarthCARE cloud radar data
The Modular and Integrated Data Assimilation System at Environment and Climate Change Canada (MIDAS v3.9.1)
A new set of indicators for model evaluation complementing to FAIRMODE’s MQO
Modeling of polycyclic aromatic hydrocarbons (PAHs) from global to regional scales: model development (IAP-AACM_PAH v1.0) and investigation of health risks in 2013 and 2018 in China
LIMA (v2.0): A full two-moment cloud microphysical scheme for the mesoscale non-hydrostatic model Meso-NH v5-6
SLUCM+BEM (v1.0): a simple parameterisation for dynamic anthropogenic heat and electricity consumption in WRF-Urban (v4.3.2)
NAQPMS-PDAF v2.0: a novel hybrid nonlinear data assimilation system for improved simulation of PM2.5 chemical components
Source-specific bias correction of US background and anthropogenic ozone modeled in CMAQ
Observational operator for fair model evaluation with ground NO2 measurements
Valid time shifting ensemble Kalman filter (VTS-EnKF) for dust storm forecasting
The third Met Office Unified Model-JULES Regional Atmosphere and Land Configuration, RAL3
An updated parameterization of the unstable atmospheric surface layer in the Weather Research and Forecasting (WRF) modeling system
The impact of cloud microphysics and ice nucleation on Southern Ocean clouds assessed with single-column modeling and instrument simulators
An updated aerosol simulation in the Community Earth System Model (v2.1.3): dust and marine aerosol emissions and secondary organic aerosol formation
Exploring ship track spreading rates with a physics-informed Langevin particle parameterization
Do data-driven models beat numerical models in forecasting weather extremes? A comparison of IFS HRES, Pangu-Weather, and GraphCast
Development of the MPAS-CMAQ coupled system (V1.0) for multiscale global air quality modeling
UA-ICON with NWP physics package (version: ua-icon-2.1): mean state and variability of the middle atmosphere
Assessment of object-based indices to identify convective organization
Diagnosis of winter precipitation types using Spectral Bin Model (SBM): Comparison of five methods using ICE-POP 2018 field experiment data
The Global Forest Fire Emissions Prediction System version 1.0
Impact of Multiple Radar Wind Profilers Data Assimilation on Convective Scale Short-Term Rainfall Forecasts: OSSE Studies over the Beijing-Tianjin-Hebei region
NEIVAv1.0: Next-generation Emissions InVentory expansion of Akagi et al. (2011) version 1.0
Ji Won Yoon, Seungyeon Lee, Ebony Lee, and Seon Ki Park
Geosci. Model Dev., 18, 2303–2328, https://doi.org/10.5194/gmd-18-2303-2025, https://doi.org/10.5194/gmd-18-2303-2025, 2025
Short summary
Short summary
This study evaluates the Weather Research and Forecasting Model (WRF) coupled with Chemistry (WRF-Chem) to predict a mega Asian dust storm (ADS) over South Korea on 28–29 March 2021. We assessed combinations of five dust emission and four land surface schemes by analyzing meteorological and air quality variables. The best scheme combination reduced the root mean square error (RMSE) for particulate matter 10 (PM10) by up to 29.6 %, demonstrating the highest performance.
Jianyu Lin, Tie Dai, Lifang Sheng, Weihang Zhang, Shangfei Hai, and Yawen Kong
Geosci. Model Dev., 18, 2231–2248, https://doi.org/10.5194/gmd-18-2231-2025, https://doi.org/10.5194/gmd-18-2231-2025, 2025
Short summary
Short summary
The effectiveness of this assimilation system and its sensitivity to the ensemble member size and length of the assimilation window are investigated. This study advances our understanding of the selection of basic parameters in the four-dimensional local ensemble transform Kalman filter assimilation system and the performance of ensemble simulation in a particulate-matter-polluted environment.
Jens Peter Karolus Wenceslaus Frankemölle, Johan Camps, Pieter De Meutter, and Johan Meyers
Geosci. Model Dev., 18, 1989–2003, https://doi.org/10.5194/gmd-18-1989-2025, https://doi.org/10.5194/gmd-18-1989-2025, 2025
Short summary
Short summary
To detect anomalous radioactivity in the environment, it is paramount that we understand the natural background level. In this work, we propose a statistical model to describe the most likely background level and the associated uncertainty in a network of dose rate detectors. We train, verify, and validate the model using real environmental data. Using the model, we show that we can correctly predict the background level in a subset of the detector network during a known
anomalous event.
Jean-François Grailet, Robin J. Hogan, Nicolas Ghilain, David Bolsée, Xavier Fettweis, and Marilaure Grégoire
Geosci. Model Dev., 18, 1965–1988, https://doi.org/10.5194/gmd-18-1965-2025, https://doi.org/10.5194/gmd-18-1965-2025, 2025
Short summary
Short summary
The MAR (Modèle Régional Atmosphérique) is a regional climate model used for weather forecasting and studying the climate over various regions. This paper presents an update of MAR thanks to which it can precisely decompose solar radiation, in particular in the UV (ultraviolet) and photosynthesis ranges, both being critical to human health and ecosystems. As a first application of this new capability, this paper presents a method for predicting UV indices with MAR.
Yi-Ning Shi, Jun Yang, Wei Han, Lujie Han, Jiajia Mao, Wanlin Kan, and Fuzhong Weng
Geosci. Model Dev., 18, 1947–1964, https://doi.org/10.5194/gmd-18-1947-2025, https://doi.org/10.5194/gmd-18-1947-2025, 2025
Short summary
Short summary
Direct assimilation of observations from ground-based microwave radiometers (GMRs) holds significant potential for improving forecast accuracy. Radiative transfer models (RTMs) play a crucial role in direct data assimilation. In this study, we introduce a new RTM, the Advanced Radiative Transfer Modeling System – Ground-Based (ARMS-gb), designed to simulate brightness temperatures observed by GMRs along with their Jacobians. Several enhancements have been incorporated to achieve higher accuracy.
R. Phani Murali Krishna, Siddharth Kumar, A. Gopinathan Prajeesh, Peter Bechtold, Nils Wedi, Kumar Roy, Malay Ganai, B. Revanth Reddy, Snehlata Tirkey, Tanmoy Goswami, Radhika Kanase, Sahadat Sarkar, Medha Deshpande, and Parthasarathi Mukhopadhyay
Geosci. Model Dev., 18, 1879–1894, https://doi.org/10.5194/gmd-18-1879-2025, https://doi.org/10.5194/gmd-18-1879-2025, 2025
Short summary
Short summary
The High-Resolution Global Forecast Model (HGFM) is an advanced iteration of the operational Global Forecast System (GFS) model. HGFM can produce forecasts at a spatial scale of ~6 km in tropics. It demonstrates improved accuracy in short- to medium-range weather prediction over the Indian region, with notable success in predicting extreme events. Further, the model will be entrusted to operational forecasting agencies after validation and testing.
Jenna Ritvanen, Seppo Pulkkinen, Dmitri Moisseev, and Daniele Nerini
Geosci. Model Dev., 18, 1851–1878, https://doi.org/10.5194/gmd-18-1851-2025, https://doi.org/10.5194/gmd-18-1851-2025, 2025
Short summary
Short summary
Nowcasting models struggle with the rapid evolution of heavy rain, and common verification methods are unable to describe how accurately the models predict the growth and decay of heavy rain. We propose a framework to assess model performance. In the framework, convective cells are identified and tracked in the forecasts and observations, and the model skill is then evaluated by comparing differences between forecast and observed cells. We demonstrate the framework with four open-source models.
Andrew Geiss and Po-Lun Ma
Geosci. Model Dev., 18, 1809–1827, https://doi.org/10.5194/gmd-18-1809-2025, https://doi.org/10.5194/gmd-18-1809-2025, 2025
Short summary
Short summary
Particles in the Earth's atmosphere strongly impact the planet's energy budget, and atmosphere simulations require accurate representation of their interaction with light. This work introduces two approaches to represent light scattering by small particles. The first is a scattering simulator based on Mie theory implemented in Python. The second is a neural network emulator that is more accurate than existing methods and is fast enough to be used in climate and weather simulations.
Qin Wang, Bo Zeng, Gong Chen, and Yaoting Li
Geosci. Model Dev., 18, 1769–1784, https://doi.org/10.5194/gmd-18-1769-2025, https://doi.org/10.5194/gmd-18-1769-2025, 2025
Short summary
Short summary
This study evaluates the performance of four planetary boundary layer (PBL) schemes in near-surface wind fields over the Sichuan Basin, China. Using 112 sensitivity experiments with the Weather Research and Forecasting (WRF) model and focusing on 28 wind events, it is found that wind direction was less sensitive to the PBL schemes. The quasi-normal scale elimination (QNSE) scheme captured temporal variations best, while the Mellor–Yamada–Janjić (MYJ) scheme had the least error in wind speed.
Tai-Long He, Nikhil Dadheech, Tammy M. Thompson, and Alexander J. Turner
Geosci. Model Dev., 18, 1661–1671, https://doi.org/10.5194/gmd-18-1661-2025, https://doi.org/10.5194/gmd-18-1661-2025, 2025
Short summary
Short summary
It is computationally expensive to infer greenhouse gas (GHG) emissions using atmospheric observations. This is partly due to the detailed model used to represent atmospheric transport. We demonstrate how a machine learning (ML) model can be used to simulate high-resolution atmospheric transport. This type of ML model will help estimate GHG emissions using dense observations, which are becoming increasingly common with the proliferation of urban monitoring networks and geostationary satellites.
Wei Li, Beiming Tang, Patrick C. Campbell, Youhua Tang, Barry Baker, Zachary Moon, Daniel Tong, Jianping Huang, Kai Wang, Ivanka Stajner, and Raffaele Montuoro
Geosci. Model Dev., 18, 1635–1660, https://doi.org/10.5194/gmd-18-1635-2025, https://doi.org/10.5194/gmd-18-1635-2025, 2025
Short summary
Short summary
The study describes the updates of NOAA's current UFS-AQMv7 air quality forecast model by incorporating the latest scientific and structural changes in CMAQv5.4. An evaluation during the summer of 2023 shows that the updated model overall improves the simulation of MDA8 O3 by reducing the bias by 8%–12% in the contiguous US. PM2.5 predictions have mixed results due to wildfire, highlighting the need for future refinements.
Yanwei Zhu, Aitor Atencia, Markus Dabernig, and Yong Wang
Geosci. Model Dev., 18, 1545–1559, https://doi.org/10.5194/gmd-18-1545-2025, https://doi.org/10.5194/gmd-18-1545-2025, 2025
Short summary
Short summary
Most works have delved into convective weather nowcasting, and only a few works have discussed the nowcasting uncertainty for variables at the surface level. Hence, we proposed a method to estimate uncertainty. Generating appropriate noises associated with the characteristic of the error in analysis can simulate the uncertainty of nowcasting. This method can contribute to the estimation of near–surface analysis uncertainty in both nowcasting applications and ensemble nowcasting development.
Joël Thanwerdas, Antoine Berchet, Lionel Constantin, Aki Tsuruta, Michael Steiner, Friedemann Reum, Stephan Henne, and Dominik Brunner
Geosci. Model Dev., 18, 1505–1544, https://doi.org/10.5194/gmd-18-1505-2025, https://doi.org/10.5194/gmd-18-1505-2025, 2025
Short summary
Short summary
The Community Inversion Framework (CIF) brings together methods for estimating greenhouse gas fluxes from atmospheric observations. The initial ensemble method implemented in CIF was found to be incomplete and could hardly be compared to other ensemble methods employed in the inversion community. In this paper, we present and evaluate a new implementation of the ensemble mode, building upon the initial developments.
Astrid Kerkweg, Timo Kirfel, Duong H. Do, Sabine Griessbach, Patrick Jöckel, and Domenico Taraborrelli
Geosci. Model Dev., 18, 1265–1286, https://doi.org/10.5194/gmd-18-1265-2025, https://doi.org/10.5194/gmd-18-1265-2025, 2025
Short summary
Short summary
Normally, the Modular Earth Submodel System (MESSy) is linked to complete dynamic models to create chemical climate models. However, the modular concept of MESSy and the newly developed DWARF component presented here make it possible to create simplified models that contain only one or a few process descriptions. This is very useful for technical optimisation, such as porting to GPUs, and can be used to create less complex models, such as a chemical box model.
Edward C. Chan, Ilona J. Jäkel, Basit Khan, Martijn Schaap, Timothy M. Butler, Renate Forkel, and Sabine Banzhaf
Geosci. Model Dev., 18, 1119–1139, https://doi.org/10.5194/gmd-18-1119-2025, https://doi.org/10.5194/gmd-18-1119-2025, 2025
Short summary
Short summary
An enhanced emission module has been developed for the PALM model system, improving flexibility and scalability of emission source representation across different sectors. A model for parametrized domestic emissions has also been included, for which an idealized model run is conducted for particulate matter (PM10). The results show that, in addition to individual sources and diurnal variations in energy consumption, vertical transport and urban topology play a role in concentration distribution.
Gregor Ehrensperger, Thorsten Simon, Georg J. Mayr, and Tobias Hell
Geosci. Model Dev., 18, 1141–1153, https://doi.org/10.5194/gmd-18-1141-2025, https://doi.org/10.5194/gmd-18-1141-2025, 2025
Short summary
Short summary
As lightning is a brief and localized event, it is not explicitly resolved in atmospheric models. Instead, expert-based auxiliary descriptions are used to assess it. This study explores how AI can improve our understanding of lightning without relying on traditional expert knowledge. We reveal that AI independently identified the key factors known to experts as essential for lightning in the Alps region. This shows how knowledge discovery could be sped up in areas with limited expert knowledge.
David Patoulias, Kalliopi Florou, and Spyros N. Pandis
Geosci. Model Dev., 18, 1103–1118, https://doi.org/10.5194/gmd-18-1103-2025, https://doi.org/10.5194/gmd-18-1103-2025, 2025
Short summary
Short summary
The effect of the assumed atmospheric nucleation mechanism on particle number concentrations and size distribution was investigated. Two quite different mechanisms involving sulfuric acid and ammonia or a biogenic organic vapor gave quite similar results which were consistent with measurements at 26 measurement stations across Europe. The number of larger particles that serve as cloud condensation nuclei showed little sensitivity to the assumed nucleation mechanism.
Tim Radke, Susanne Fuchs, Christian Wilms, Iuliia Polkova, and Marc Rautenhaus
Geosci. Model Dev., 18, 1017–1039, https://doi.org/10.5194/gmd-18-1017-2025, https://doi.org/10.5194/gmd-18-1017-2025, 2025
Short summary
Short summary
In our study, we built upon previous work to investigate the patterns artificial intelligence (AI) learns to detect atmospheric features like tropical cyclones (TCs) and atmospheric rivers (ARs). As primary objective, we adopt a method to explain the AI used and investigate the plausibility of learned patterns. We find that plausible patterns are learned for both TCs and ARs. Hence, the chosen method is very useful for gaining confidence in the AI-based detection of atmospheric features.
Stefan Noll, Carsten Schmidt, Patrick Hannawald, Wolfgang Kausch, and Stefan Kimeswenger
EGUsphere, https://doi.org/10.5194/egusphere-2024-3512, https://doi.org/10.5194/egusphere-2024-3512, 2025
Short summary
Short summary
Non-thermal emission from chemical reactions in the Earth's middle und upper atmosphere strongly contributes to the brightness of the night sky below about 2.3 µm. The new Paranal Airglow Line and Continuum Emission model calculates the emission spectrum and its variability with an unprecedented accuracy. Relying on a large spectroscopic data set from astronomical spectrographs and theoretical molecular/atomic data, it is valuable for airglow research and astronomical observatories.
Felipe Cifuentes, Henk Eskes, Enrico Dammers, Charlotte Bryan, and Folkert Boersma
Geosci. Model Dev., 18, 621–649, https://doi.org/10.5194/gmd-18-621-2025, https://doi.org/10.5194/gmd-18-621-2025, 2025
Short summary
Short summary
We tested the capability of the flux divergence approach (FDA) to reproduce known NOx emissions using synthetic NO2 satellite column retrievals from high-resolution model simulations. The FDA accurately reproduced NOx emissions when column observations were limited to the boundary layer and when the variability of the NO2 lifetime, the NOx : NO2 ratio, and NO2 profile shapes were correctly modeled. This introduces strong model dependency, reducing the simplicity of the original FDA formulation.
Stefano Ubbiali, Christian Kühnlein, Christoph Schär, Linda Schlemmer, Thomas C. Schulthess, Michael Staneker, and Heini Wernli
Geosci. Model Dev., 18, 529–546, https://doi.org/10.5194/gmd-18-529-2025, https://doi.org/10.5194/gmd-18-529-2025, 2025
Short summary
Short summary
We explore a high-level programming model for porting numerical weather prediction (NWP) model codes to graphics processing units (GPUs). We present a Python rewrite with the domain-specific library GT4Py (GridTools for Python) of two renowned cloud microphysics schemes and the associated tangent-linear and adjoint algorithms. We find excellent portability, competitive GPU performance, robust execution on diverse computing architectures, and enhanced code maintainability and user productivity.
Pieter Rijsdijk, Henk Eskes, Arlene Dingemans, K. Folkert Boersma, Takashi Sekiya, Kazuyuki Miyazaki, and Sander Houweling
Geosci. Model Dev., 18, 483–509, https://doi.org/10.5194/gmd-18-483-2025, https://doi.org/10.5194/gmd-18-483-2025, 2025
Short summary
Short summary
Clustering high-resolution satellite observations into superobservations improves model validation and data assimilation applications. In our paper, we derive quantitative uncertainties for satellite NO2 column observations based on knowledge of the retrievals, including a detailed analysis of spatial error correlations and representativity errors. The superobservations and uncertainty estimates are tested in a global chemical data assimilation system and are found to improve the forecasts.
Dario Di Santo, Cenlin He, Fei Chen, and Lorenzo Giovannini
Geosci. Model Dev., 18, 433–459, https://doi.org/10.5194/gmd-18-433-2025, https://doi.org/10.5194/gmd-18-433-2025, 2025
Short summary
Short summary
This paper presents the Machine Learning-based Automated Multi-method Parameter Sensitivity and Importance analysis Tool (ML-AMPSIT), a computationally efficient tool that uses machine learning algorithms for sensitivity analysis in atmospheric models. It is tested with the Weather Research and Forecasting (WRF) model coupled with the Noah-Multiparameterization (Noah-MP) land surface model to investigate sea breeze circulation sensitivity to vegetation-related parameters.
Robert Schoetter, Robin James Hogan, Cyril Caliot, and Valéry Masson
Geosci. Model Dev., 18, 405–431, https://doi.org/10.5194/gmd-18-405-2025, https://doi.org/10.5194/gmd-18-405-2025, 2025
Short summary
Short summary
Radiation is relevant to the atmospheric impact on people and infrastructure in cities as it can influence the urban heat island, building energy consumption, and human thermal comfort. A new urban radiation model, assuming a more realistic form of urban morphology, is coupled to the urban climate model Town Energy Balance (TEB). The new TEB is evaluated with a reference radiation model for a variety of urban morphologies, and an improvement in the simulated radiative observables is found.
Zebediah Engberg, Roger Teoh, Tristan Abbott, Thomas Dean, Marc E. J. Stettler, and Marc L. Shapiro
Geosci. Model Dev., 18, 253–286, https://doi.org/10.5194/gmd-18-253-2025, https://doi.org/10.5194/gmd-18-253-2025, 2025
Short summary
Short summary
Contrails forming in some atmospheric conditions may persist and become strongly warming cirrus, while in other conditions may be neutral or cooling. We develop a contrail forecast model to predict contrail climate forcing for any arbitrary point in space and time and explore integration into flight planning and air traffic management. This approach enables contrail interventions to target high-probability high-climate-impact regions and reduce unintended consequences of contrail management.
Nils Eingrüber, Alina Domm, Wolfgang Korres, and Karl Schneider
Geosci. Model Dev., 18, 141–160, https://doi.org/10.5194/gmd-18-141-2025, https://doi.org/10.5194/gmd-18-141-2025, 2025
Short summary
Short summary
Climate change adaptation measures like unsealings can reduce urban heat stress. As grass grid pavers have never been parameterized for microclimate model simulations with ENVI-met, a new parameterization was developed based on field measurements. To analyse the cooling potential, scenario analyses were performed for a densely developed area in Cologne. Statistically significant average cooling effects of up to −11.1 K were found for surface temperature and up to −2.9 K for 1 m air temperature.
Xuan Wang, Lei Bi, Hong Wang, Yaqiang Wang, Wei Han, Xueshun Shen, and Xiaoye Zhang
Geosci. Model Dev., 18, 117–139, https://doi.org/10.5194/gmd-18-117-2025, https://doi.org/10.5194/gmd-18-117-2025, 2025
Short summary
Short summary
The Artificial-Intelligence-based Nonspherical Aerosol Optical Scheme (AI-NAOS) was developed to improve the estimation of the aerosol direct radiation effect and was coupled online with a chemical weather model. The AI-NAOS scheme considers black carbon as fractal aggregates and soil dust as super-spheroids, encapsulated with hygroscopic aerosols. Real-case simulations emphasize the necessity of accurately representing nonspherical and inhomogeneous aerosols in chemical weather models.
Lukas Pfitzenmaier, Pavlos Kollias, Nils Risse, Imke Schirmacher, Bernat Puigdomenech Treserras, and Katia Lamer
Geosci. Model Dev., 18, 101–115, https://doi.org/10.5194/gmd-18-101-2025, https://doi.org/10.5194/gmd-18-101-2025, 2025
Short summary
Short summary
The Python tool Orbital-Radar transfers suborbital radar data (ground-based, airborne, and forward-simulated numerical weather prediction model) into synthetic spaceborne cloud profiling radar data, mimicking platform-specific instrument characteristics, e.g. EarthCARE or CloudSat. The tool's novelty lies in simulating characteristic errors and instrument noise. Thus, existing data sets are transferred into synthetic observations and can be used for satellite calibration–validation studies.
Mark Buehner, Jean-Francois Caron, Ervig Lapalme, Alain Caya, Ping Du, Yves Rochon, Sergey Skachko, Maziar Bani Shahabadi, Sylvain Heilliette, Martin Deshaies-Jacques, Weiguang Chang, and Michael Sitwell
Geosci. Model Dev., 18, 1–18, https://doi.org/10.5194/gmd-18-1-2025, https://doi.org/10.5194/gmd-18-1-2025, 2025
Short summary
Short summary
The Modular and Integrated Data Assimilation System (MIDAS) software is described. The flexible design of MIDAS enables both deterministic and ensemble prediction applications for the atmosphere and several other Earth system components. It is currently used for all main operational weather prediction systems in Canada and also for sea ice and sea surface temperature analysis. The use of MIDAS for multiple Earth system components will facilitate future research on coupled data assimilation.
Alexander de Meij, Cornelis Cuvelier, Philippe Thunis, and Enrico Pisoni
EGUsphere, https://doi.org/10.5194/egusphere-2024-3690, https://doi.org/10.5194/egusphere-2024-3690, 2025
Short summary
Short summary
We assess the relevance and utility indicators developed within FAIRMODE by evaluating 9 CAMS models in calculated air pollutant values. For NO2, the results highlight difficulties at traffic stations. For PM2.5 and PM10 the bias and Winter-Summer gradients reveal issues. O3 evaluation shows that e.g. seasonal gradients are useful. Overall, the indicators provide valuable insights into model limitations, yet there is a need to reconsider the strictness of some indicators for certain pollutants.
Zichen Wu, Xueshun Chen, Zifa Wang, Huansheng Chen, Zhe Wang, Qing Mu, Lin Wu, Wending Wang, Xiao Tang, Jie Li, Ying Li, Qizhong Wu, Yang Wang, Zhiyin Zou, and Zijian Jiang
Geosci. Model Dev., 17, 8885–8907, https://doi.org/10.5194/gmd-17-8885-2024, https://doi.org/10.5194/gmd-17-8885-2024, 2024
Short summary
Short summary
We developed a model to simulate polycyclic aromatic hydrocarbons (PAHs) from global to regional scales. The model can reproduce PAH distribution well. The concentration of BaP (indicator species for PAHs) could exceed the target values of 1 ng m-3 over some areas (e.g., in central Europe, India, and eastern China). The change in BaP is lower than that in PM2.5 from 2013 to 2018. China still faces significant potential health risks posed by BaP although the Action Plan has been implemented.
Marie Taufour, Jean-Pierre Pinty, Christelle Barthe, Benoît Vié, and Chien Wang
Geosci. Model Dev., 17, 8773–8798, https://doi.org/10.5194/gmd-17-8773-2024, https://doi.org/10.5194/gmd-17-8773-2024, 2024
Short summary
Short summary
We have developed a complete two-moment version of the LIMA (Liquid Ice Multiple Aerosols) microphysics scheme. We have focused on collection processes, where the hydrometeor number transfer is often estimated in proportion to the mass transfer. The impact of these parameterizations on a convective system and the prospects for more realistic estimates of secondary parameters (reflectivity, hydrometeor size) are shown in a first test on an idealized case.
Yuya Takane, Yukihiro Kikegawa, Ko Nakajima, and Hiroyuki Kusaka
Geosci. Model Dev., 17, 8639–8664, https://doi.org/10.5194/gmd-17-8639-2024, https://doi.org/10.5194/gmd-17-8639-2024, 2024
Short summary
Short summary
A new parameterisation for dynamic anthropogenic heat and electricity consumption is described. The model reproduced the temporal variation in and spatial distributions of electricity consumption and temperature well in summer and winter. The partial air conditioning was the most critical factor, significantly affecting the value of anthropogenic heat emission.
Hongyi Li, Ting Yang, Lars Nerger, Dawei Zhang, Di Zhang, Guigang Tang, Haibo Wang, Yele Sun, Pingqing Fu, Hang Su, and Zifa Wang
Geosci. Model Dev., 17, 8495–8519, https://doi.org/10.5194/gmd-17-8495-2024, https://doi.org/10.5194/gmd-17-8495-2024, 2024
Short summary
Short summary
To accurately characterize the spatiotemporal distribution of particulate matter <2.5 µm chemical components, we developed the Nested Air Quality Prediction Model System with the Parallel Data Assimilation Framework (NAQPMS-PDAF) v2.0 for chemical components with non-Gaussian and nonlinear properties. NAQPMS-PDAF v2.0 has better computing efficiency, excels when used with a small ensemble size, and can significantly improve the simulation performance of chemical components.
T. Nash Skipper, Christian Hogrefe, Barron H. Henderson, Rohit Mathur, Kristen M. Foley, and Armistead G. Russell
Geosci. Model Dev., 17, 8373–8397, https://doi.org/10.5194/gmd-17-8373-2024, https://doi.org/10.5194/gmd-17-8373-2024, 2024
Short summary
Short summary
Chemical transport model simulations are combined with ozone observations to estimate the bias in ozone attributable to US anthropogenic sources and individual sources of US background ozone: natural sources, non-US anthropogenic sources, and stratospheric ozone. Results indicate a positive bias correlated with US anthropogenic emissions during summer in the eastern US and a negative bias correlated with stratospheric ozone during spring.
Li Fang, Jianbing Jin, Arjo Segers, Ke Li, Ji Xia, Wei Han, Baojie Li, Hai Xiang Lin, Lei Zhu, Song Liu, and Hong Liao
Geosci. Model Dev., 17, 8267–8282, https://doi.org/10.5194/gmd-17-8267-2024, https://doi.org/10.5194/gmd-17-8267-2024, 2024
Short summary
Short summary
Model evaluations against ground observations are usually unfair. The former simulates mean status over coarse grids and the latter the surrounding atmosphere. To solve this, we proposed the new land-use-based representative (LUBR) operator that considers intra-grid variance. The LUBR operator is validated to provide insights that align with satellite measurements. The results highlight the importance of considering fine-scale urban–rural differences when comparing models and observation.
Mijie Pang, Jianbing Jin, Arjo Segers, Huiya Jiang, Wei Han, Batjargal Buyantogtokh, Ji Xia, Li Fang, Jiandong Li, Hai Xiang Lin, and Hong Liao
Geosci. Model Dev., 17, 8223–8242, https://doi.org/10.5194/gmd-17-8223-2024, https://doi.org/10.5194/gmd-17-8223-2024, 2024
Short summary
Short summary
The ensemble Kalman filter (EnKF) improves dust storm forecasts but faces challenges with position errors. The valid time shifting EnKF (VTS-EnKF) addresses this by adjusting for position errors, enhancing accuracy in forecasting dust storms, as proven in tests on 2021 events, even with smaller ensembles and time intervals.
Mike Bush, David L. A. Flack, Huw W. Lewis, Sylvia I. Bohnenstengel, Chris J. Short, Charmaine Franklin, Adrian P. Lock, Martin Best, Paul Field, Anne McCabe, Kwinten Van Weverberg, Segolene Berthou, Ian Boutle, Jennifer K. Brooke, Seb Cole, Shaun Cooper, Gareth Dow, John Edwards, Anke Finnenkoetter, Kalli Furtado, Kate Halladay, Kirsty Hanley, Margaret A. Hendry, Adrian Hill, Aravindakshan Jayakumar, Richard W. Jones, Humphrey Lean, Joshua C. K. Lee, Andy Malcolm, Marion Mittermaier, Saji Mohandas, Stuart Moore, Cyril Morcrette, Rachel North, Aurore Porson, Susan Rennie, Nigel Roberts, Belinda Roux, Claudio Sanchez, Chun-Hsu Su, Simon Tucker, Simon Vosper, David Walters, James Warner, Stuart Webster, Mark Weeks, Jonathan Wilkinson, Michael Whitall, Keith D. Williams, and Hugh Zhang
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-201, https://doi.org/10.5194/gmd-2024-201, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
RAL configurations define settings for the Unified Model atmosphere and Joint UK Land Environment Simulator. The third version of the Regional Atmosphere and Land (RAL3) science configuration for kilometre and sub-km scale modelling represents a major advance compared to previous versions (RAL2) by delivering a common science definition for applications in tropical and mid-latitude regions. RAL3 has more realistic precipitation distributions and improved representation of clouds and visibility.
Prabhakar Namdev, Maithili Sharan, Piyush Srivastava, and Saroj Kanta Mishra
Geosci. Model Dev., 17, 8093–8114, https://doi.org/10.5194/gmd-17-8093-2024, https://doi.org/10.5194/gmd-17-8093-2024, 2024
Short summary
Short summary
Inadequate representation of surface–atmosphere interaction processes is a major source of uncertainty in numerical weather prediction models. Here, an effort has been made to improve the Weather Research and Forecasting (WRF) model version 4.2.2 by introducing a unique theoretical framework under convective conditions. In addition, to enhance the potential applicability of the WRF modeling system, various commonly used similarity functions under convective conditions have also been installed.
Andrew Gettelman, Richard Forbes, Roger Marchand, Chih-Chieh Chen, and Mark Fielding
Geosci. Model Dev., 17, 8069–8092, https://doi.org/10.5194/gmd-17-8069-2024, https://doi.org/10.5194/gmd-17-8069-2024, 2024
Short summary
Short summary
Supercooled liquid clouds (liquid clouds colder than 0°C) are common at higher latitudes (especially over the Southern Ocean) and are critical for constraining climate projections. We compare a single-column version of a weather model to observations with two different cloud schemes and find that both the dynamical environment and atmospheric aerosols are important for reproducing observations.
Yujuan Wang, Peng Zhang, Jie Li, Yaman Liu, Yanxu Zhang, Jiawei Li, and Zhiwei Han
Geosci. Model Dev., 17, 7995–8021, https://doi.org/10.5194/gmd-17-7995-2024, https://doi.org/10.5194/gmd-17-7995-2024, 2024
Short summary
Short summary
This study updates the CESM's aerosol schemes, focusing on dust, marine aerosol emissions, and secondary organic aerosol (SOA) . Dust emission modifications make deflation areas more continuous, improving results in North America and the sub-Arctic. Humidity correction to sea-salt emissions has a minor effect. Introducing marine organic aerosol emissions, coupled with ocean biogeochemical processes, and adding aqueous reactions for SOA formation advance the CESM's aerosol modelling results.
Lucas A. McMichael, Michael J. Schmidt, Robert Wood, Peter N. Blossey, and Lekha Patel
Geosci. Model Dev., 17, 7867–7888, https://doi.org/10.5194/gmd-17-7867-2024, https://doi.org/10.5194/gmd-17-7867-2024, 2024
Short summary
Short summary
Marine cloud brightening (MCB) is a climate intervention technique to potentially cool the climate. Climate models used to gauge regional climate impacts associated with MCB often assume large areas of the ocean are uniformly perturbed. However, a more realistic representation of MCB application would require information about how an injected particle plume spreads. This work aims to develop such a plume-spreading model.
Leonardo Olivetti and Gabriele Messori
Geosci. Model Dev., 17, 7915–7962, https://doi.org/10.5194/gmd-17-7915-2024, https://doi.org/10.5194/gmd-17-7915-2024, 2024
Short summary
Short summary
Data-driven models are becoming a viable alternative to physics-based models for weather forecasting up to 15 d into the future. However, it is unclear whether they are as reliable as physics-based models when forecasting weather extremes. We evaluate their performance in forecasting near-surface cold, hot, and windy extremes globally. We find that data-driven models can compete with physics-based models and that the choice of the best model mainly depends on the region and type of extreme.
David C. Wong, Jeff Willison, Jonathan E. Pleim, Golam Sarwar, James Beidler, Russ Bullock, Jerold A. Herwehe, Rob Gilliam, Daiwen Kang, Christian Hogrefe, George Pouliot, and Hosein Foroutan
Geosci. Model Dev., 17, 7855–7866, https://doi.org/10.5194/gmd-17-7855-2024, https://doi.org/10.5194/gmd-17-7855-2024, 2024
Short summary
Short summary
This work describe how we linked the meteorological Model for Prediction Across Scales – Atmosphere (MPAS-A) with the Community Multiscale Air Quality (CMAQ) air quality model to form a coupled modelling system. This could be used to study air quality or climate and air quality interaction at a global scale. This new model scales well in high-performance computing environments and performs well with respect to ground surface networks in terms of ozone and PM2.5.
Markus Kunze, Christoph Zülicke, Tarique Adnan Siddiqui, Claudia Christine Stephan, Yosuke Yamazaki, Claudia Stolle, Sebastian Borchert, and Hauke Schmidt
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-191, https://doi.org/10.5194/gmd-2024-191, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
We present the Icosahedral Nonhydrostatic (ICON) general circulation model with upper atmosphere extension with the physics package for numerical weather prediction (UA-ICON(NWP)). The parameters for the gravity wave parameterizations were optimized, and realistic modelling of the thermal and dynamic state of the mesopause regions was achieved. UA-ICON(NWP) now shows a realistic frequency of major sudden stratospheric warmings and well-represented solar tides in temperature.
Giulio Mandorli and Claudia J. Stubenrauch
Geosci. Model Dev., 17, 7795–7813, https://doi.org/10.5194/gmd-17-7795-2024, https://doi.org/10.5194/gmd-17-7795-2024, 2024
Short summary
Short summary
In recent years, several studies focused their attention on the disposition of convection. Lots of methods, called indices, have been developed to quantify the amount of convection clustering. These indices are evaluated in this study by defining criteria that must be satisfied and then evaluating the indices against these standards. None of the indices meet all criteria, with some only partially meeting them.
Wonbae Bang, Jacob Carlin, Kwonil Kim, Alexander Ryzhkov, Guosheng Liu, and Gyuwon Lee
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-179, https://doi.org/10.5194/gmd-2024-179, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
Microphysics model-based diagnosis such as the spectral bin model (SBM) recently has been attempted to diagnose winter precipitation types. In this study, the accuracy of SBM-based precipitation type diagnosis is compared with other traditional methods. SBM have relatively higher accuracy about snow and wetsnow events whereas lower accuracy about rain event. When microphysics scheme in the SBM was optimized for the corresponding region, accuracy about rain events was improved.
Kerry Anderson, Jack Chen, Peter Englefield, Debora Griffin, Paul A. Makar, and Dan Thompson
Geosci. Model Dev., 17, 7713–7749, https://doi.org/10.5194/gmd-17-7713-2024, https://doi.org/10.5194/gmd-17-7713-2024, 2024
Short summary
Short summary
The Global Forest Fire Emissions Prediction System (GFFEPS) is a model that predicts smoke and carbon emissions from wildland fires. The model calculates emissions from the ground up based on satellite-detected fires, modelled weather and fire characteristics. Unlike other global models, GFFEPS uses daily weather conditions to capture changing burning conditions on a day-to-day basis. GFFEPS produced lower carbon emissions due to the changing weather not captured by the other models.
Juan Zhao, Jianping Guo, and Xiaohui Zheng
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-194, https://doi.org/10.5194/gmd-2024-194, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
A series of observing system simulation experiments are conducted to assess the impact of multiple radar wind profiler (RWP) networks on convective scale numerical weather prediction. Results from three southwest-type heavy rainfall cases in the Beijing-Tianjin-Hebei region suggest the added forecast skill of ridge and foothill networks associated with the Taihang Mountains over the existing RWP network. This research provides valuable guidance for designing optimal RWP networks in the region.
Samiha Binte Shahid, Forrest G. Lacey, Christine Wiedinmyer, Robert J. Yokelson, and Kelley C. Barsanti
Geosci. Model Dev., 17, 7679–7711, https://doi.org/10.5194/gmd-17-7679-2024, https://doi.org/10.5194/gmd-17-7679-2024, 2024
Short summary
Short summary
The Next-generation Emissions InVentory expansion of Akagi (NEIVA) v.1.0 is a comprehensive biomass burning emissions database that allows integration of new data and flexible querying. Data are stored in connected datasets, including recommended averages of ~1500 constituents for 14 globally relevant fire types. Individual compounds were mapped to common model species to allow better attribution of emissions in modeling studies that predict the effects of fires on air quality and climate.
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...
