Articles | Volume 12, issue 9
https://doi.org/10.5194/gmd-12-3939-2019
© Author(s) 2019. 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-12-3939-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model evaluation paper
| 
06 Sep 2019
Model evaluation paper |
| 06 Sep 2019
| 06 Sep 2019
Evaluation of WRF-DART (ARW v3.9.1.1 and DART Manhattan release) multiphase cloud water path assimilation for short-term solar irradiance forecasting in a tropical environment
Frederik Kurzrock
CORRESPONDING AUTHOR
Institut de Recherche pour le Développement (IRD), UMR 228, ESPACE-DEV, Université de La Réunion, Saint-Denis, La Réunion, France
Reuniwatt SAS, Sainte Clotilde, La Réunion, France
Hannah Nguyen
Reuniwatt SAS, Sainte Clotilde, La Réunion, France
Jerome Sauer
Reuniwatt SAS, Sainte Clotilde, La Réunion, France
Fabrice Chane Ming
Laboratoire de l’Atmosphère et des Cyclones, UMR8105, UMR CNRS – Météo-France – Université, Université de La Réunion, La Réunion, France
Sylvain Cros
Reuniwatt SAS, Sainte Clotilde, La Réunion, France
William L. Smith Jr.
Climate Science Branch (E302), NASA Langley Research Center, Hampton, Virginia, USA
Patrick Minnis
Climate Science Branch (E302), NASA Langley Research Center, Hampton, Virginia, USA
Rabindra Palikonda
Climate Science Branch (E302), NASA Langley Research Center, Hampton, Virginia, USA
Thomas A. Jones
Cooperative Institute for Mesoscale Meteorological Studies, University of Oklahoma, Norman, Oklahoma, USA
Caroline Lallemand
Reuniwatt SAS, Sainte Clotilde, La Réunion, France
Laurent Linguet
Institut de Recherche pour le Développement (IRD), UMR 228, ESPACE-DEV, Université de Guyane, Cayenne, Guyane, France
Gilles Lajoie
Institut de Recherche pour le Développement (IRD), UMR 228, ESPACE-DEV, Université de La Réunion, Saint-Denis, La Réunion, France
Related authors
No articles found.
Sunny Sun-Mack, Patrick Minnis, Yan Chen, Gang Hong, and William L. Smith Jr.
Atmos. Meas. Tech., 17, 3323–3346, https://doi.org/10.5194/amt-17-3323-2024, https://doi.org/10.5194/amt-17-3323-2024, 2024
Short summary
Short summary
Multilayer clouds (MCs) affect the radiation budget differently than single-layer clouds (SCs) and need to be identified in satellite images. A neural network was trained to identify MCs by matching imagery with lidar/radar data. This method correctly identifies ~87 % SCs and MCs with a net accuracy gain of 7.5 % over snow-free surfaces. It is more accurate than most available methods and constitutes a first step in providing a reasonable 3-D characterization of the cloudy atmosphere.
Armin Sorooshian, Mikhail D. Alexandrov, Adam D. Bell, Ryan Bennett, Grace Betito, Sharon P. Burton, Megan E. Buzanowicz, Brian Cairns, Eduard V. Chemyakin, Gao Chen, Yonghoon Choi, Brian L. Collister, Anthony L. Cook, Andrea F. Corral, Ewan C. Crosbie, Bastiaan van Diedenhoven, Joshua P. DiGangi, Glenn S. Diskin, Sanja Dmitrovic, Eva-Lou Edwards, Marta A. Fenn, Richard A. Ferrare, David van Gilst, Johnathan W. Hair, David B. Harper, Miguel Ricardo A. Hilario, Chris A. Hostetler, Nathan Jester, Michael Jones, Simon Kirschler, Mary M. Kleb, John M. Kusterer, Sean Leavor, Joseph W. Lee, Hongyu Liu, Kayla McCauley, Richard H. Moore, Joseph Nied, Anthony Notari, John B. Nowak, David Painemal, Kasey E. Phillips, Claire E. Robinson, Amy Jo Scarino, Joseph S. Schlosser, Shane T. Seaman, Chellappan Seethala, Taylor J. Shingler, Michael A. Shook, Kenneth A. Sinclair, William L. Smith Jr., Douglas A. Spangenberg, Snorre A. Stamnes, Kenneth L. Thornhill, Christiane Voigt, Holger Vömel, Andrzej P. Wasilewski, Hailong Wang, Edward L. Winstead, Kira Zeider, Xubin Zeng, Bo Zhang, Luke D. Ziemba, and Paquita Zuidema
Earth Syst. Sci. Data, 15, 3419–3472, https://doi.org/10.5194/essd-15-3419-2023, https://doi.org/10.5194/essd-15-3419-2023, 2023
Short summary
Short summary
The NASA Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment (ACTIVATE) produced a unique dataset for research into aerosol–cloud–meteorology interactions. HU-25 Falcon and King Air aircraft conducted systematic and spatially coordinated flights over the northwest Atlantic Ocean. This paper describes the ACTIVATE flight strategy, instrument and complementary dataset products, data access and usage details, and data application notes.
Hannah M. Nguyen, Jiangping He, and Martin J. Wooster
Atmos. Chem. Phys., 23, 2089–2118, https://doi.org/10.5194/acp-23-2089-2023, https://doi.org/10.5194/acp-23-2089-2023, 2023
Short summary
Short summary
This work presents novel advances in the estimation of open biomass burning emissions via the first fully "top-down" approach to exploit satellite-derived observations of fire radiative power and carbon monoxide over Africa. We produce a 16-year record of fire-generated CO emissions and dry matter consumed per unit area for Africa and evaluate these emissions estimates through their use in an atmospheric model, whose simulation output is then compared to independent satellite observations of CO.
David Painemal, Douglas Spangenberg, William L. Smith Jr., Patrick Minnis, Brian Cairns, Richard H. Moore, Ewan Crosbie, Claire Robinson, Kenneth L. Thornhill, Edward L. Winstead, and Luke Ziemba
Atmos. Meas. Tech., 14, 6633–6646, https://doi.org/10.5194/amt-14-6633-2021, https://doi.org/10.5194/amt-14-6633-2021, 2021
Short summary
Short summary
Cloud properties derived from satellite sensors are critical for the global monitoring of climate. This study evaluates satellite-based cloud properties over the North Atlantic using airborne data collected during NAAMES. Satellite observations of droplet size and cloud optical depth tend to compare well with NAAMES data. The analysis indicates that the satellite pixel resolution and the specific viewing geometry need to be taken into account in research applications.
Hong Chen, Sebastian Schmidt, Michael D. King, Galina Wind, Anthony Bucholtz, Elizabeth A. Reid, Michal Segal-Rozenhaimer, William L. Smith, Patrick C. Taylor, Seiji Kato, and Peter Pilewskie
Atmos. Meas. Tech., 14, 2673–2697, https://doi.org/10.5194/amt-14-2673-2021, https://doi.org/10.5194/amt-14-2673-2021, 2021
Short summary
Short summary
In this paper, we accessed the shortwave irradiance derived from MODIS cloud optical properties by using aircraft measurements. We developed a data aggregation technique to parameterize spectral surface albedo by snow fraction in the Arctic. We found that undetected clouds have the most significant impact on the imagery-derived irradiance. This study suggests that passive imagery cloud detection could be improved through a multi-pixel approach that would make it more dependable in the Arctic.
Benjamin R. Scarino, Kristopher Bedka, Rajendra Bhatt, Konstantin Khlopenkov, David R. Doelling, and William L. Smith Jr.
Atmos. Meas. Tech., 13, 5491–5511, https://doi.org/10.5194/amt-13-5491-2020, https://doi.org/10.5194/amt-13-5491-2020, 2020
Short summary
Short summary
This paper highlights a technique for facilitating anvil cloud detection based on visible observations that relies on comparative analysis with expected cloud reflectance for a given set of angles. A 1-year database of anvil-identified pixels, as determined from IR observations, from several geostationary satellites was used to construct a bidirectional reflectance distribution function model to quantify typical anvil reflectance across almost all expected viewing, solar, and azimuth angles.
David Painemal, Fu-Lung Chang, Richard Ferrare, Sharon Burton, Zhujun Li, William L. Smith Jr., Patrick Minnis, Yan Feng, and Marian Clayton
Atmos. Chem. Phys., 20, 7167–7177, https://doi.org/10.5194/acp-20-7167-2020, https://doi.org/10.5194/acp-20-7167-2020, 2020
Short summary
Short summary
Aerosol–cloud interactions (ACIs) are the most uncertain aspect of anthropogenic forcing. Although satellites provide the observational dataset for the global ACI quantification, retrievals are limited to vertically integrated quantities (e.g., aerosol optical depth – AOD), which are typically used as an aerosol proxy. This study demonstrates that matching vertically resolved aerosol from CALIOP at the cloud-layer height with satellite cloud retrievals reduces uncertainties in ACI estimates.
Wenying Su, Patrick Minnis, Lusheng Liang, David P. Duda, Konstantin Khlopenkov, Mandana M. Thieman, Yinan Yu, Allan Smith, Steven Lorentz, Daniel Feldman, and Francisco P. J. Valero
Atmos. Meas. Tech., 13, 429–443, https://doi.org/10.5194/amt-13-429-2020, https://doi.org/10.5194/amt-13-429-2020, 2020
Short summary
Short summary
The Deep Space Climate Observatory (DSCOVR) provides continuous full-disk global broadband irradiance measurements over most of the sunlit side of the Earth. The three active cavity radiometers measure the total radiant energy from the sunlit side of the Earth in shortwave (SW; 0.2–4 µm), total (0.4–100 µm), and near-infrared (NIR; 0.7–4 µm) channels. In this paper, the algorithm used to derive daytime shortwave and longwave fluxes from NISTAR measurements is presented.
Jeffrey S. Reid, Derek J. Posselt, Kathleen Kaku, Robert A. Holz, Gao Chen, Edwin W. Eloranta, Ralph E. Kuehn, Sarah Woods, Jianglong Zhang, Bruce Anderson, T. Paul Bui, Glenn S. Diskin, Patrick Minnis, Michael J. Newchurch, Simone Tanelli, Charles R. Trepte, K. Lee Thornhill, and Luke D. Ziemba
Atmos. Chem. Phys., 19, 11413–11442, https://doi.org/10.5194/acp-19-11413-2019, https://doi.org/10.5194/acp-19-11413-2019, 2019
Short summary
Short summary
The scientific community often focuses on the vertical transport of pollutants by clouds for those with bases at the planetary boundary layer (such as typical fair-weather cumulus) and the outflow from thunderstorms at their tops. We demonstrate complex aerosol and cloud features formed in mid-level thunderstorm outflow. These layers have strong relationships to mid-level tropospheric clouds, an important but difficult to model or monitor cloud regime for climate studies.
David P. Duda, Sarah T. Bedka, Patrick Minnis, Douglas Spangenberg, Konstantin Khlopenkov, Thad Chee, and William L. Smith Jr.
Atmos. Chem. Phys., 19, 5313–5330, https://doi.org/10.5194/acp-19-5313-2019, https://doi.org/10.5194/acp-19-5313-2019, 2019
Short summary
Short summary
We use one year (2012) of satellite imagery obtained from two NASA research satellites, Terra and Aqua, to detect linear contrail coverage and to estimate their physical properties over the Northern Hemisphere. The satellite-derived properties are compared with results collected from the same sensors in 2006 to estimate whether the impact of contrail coverage on climate has changed. The study is the first of its kind to measure contrail properties over a near-global scale from satellite imagery.
Young-Hee Ryu, Alma Hodzic, Jerome Barre, Gael Descombes, and Patrick Minnis
Atmos. Chem. Phys., 18, 7509–7525, https://doi.org/10.5194/acp-18-7509-2018, https://doi.org/10.5194/acp-18-7509-2018, 2018
Short summary
Short summary
We investigate whether errors in cloud predictions can significantly impact the ability of air quality models to predict surface ozone over the US during summer 2013. The comparison with satellite data shows that the model predicts ~ 55 % of clouds in the right locations and underpredicts cloud thickness. The error in daytime ozone is estimated to be 1–5 ppb and represents ~ 40 % of the ozone bias. The accurate predictions of clouds particularly benefits ozone predictions in urban areas.
Christopher R. Yost, Kristopher M. Bedka, Patrick Minnis, Louis Nguyen, J. Walter Strapp, Rabindra Palikonda, Konstantin Khlopenkov, Douglas Spangenberg, William L. Smith Jr., Alain Protat, and Julien Delanoe
Atmos. Meas. Tech., 11, 1615–1637, https://doi.org/10.5194/amt-11-1615-2018, https://doi.org/10.5194/amt-11-1615-2018, 2018
Short summary
Short summary
Accretion of cloud ice particles upon engine or instrument probe surfaces can cause engine malfunction or even power loss, and therefore it is important for aircraft to avoid flight through clouds that may have produced large quantities of ice particles. This study introduces a method by which potentially hazardous conditions can be detected using satellite imagery. It was found that potentially hazardous conditions were often located near or beneath very cold clouds and thunderstorm updrafts.
Benjamin R. Scarino, Patrick Minnis, Thad Chee, Kristopher M. Bedka, Christopher R. Yost, and Rabindra Palikonda
Atmos. Meas. Tech., 10, 351–371, https://doi.org/10.5194/amt-10-351-2017, https://doi.org/10.5194/amt-10-351-2017, 2017
Short summary
Short summary
Global coverage of remotely sensed skin temperature, along with cloud/surface radiation parameters, produced in near-real time and from historical satellite data, is beneficial for weather and climate purposes. One key drawback is the dependence on view angle. Therefore, this article serves to validate a global, satellite-based skin temperature product, while highlighting an empirically adjusted theoretical model of satellite LST angular anisotropy, and the benefits gained from its application.
Ulrich Schumann, Robert Baumann, Darrel Baumgardner, Sarah T. Bedka, David P. Duda, Volker Freudenthaler, Jean-Francois Gayet, Andrew J. Heymsfield, Patrick Minnis, Markus Quante, Ehrhard Raschke, Hans Schlager, Margarita Vázquez-Navarro, Christiane Voigt, and Zhien Wang
Atmos. Chem. Phys., 17, 403–438, https://doi.org/10.5194/acp-17-403-2017, https://doi.org/10.5194/acp-17-403-2017, 2017
Short summary
Short summary
The initially linear clouds often seen behind aircraft are known as contrails. Contrails are prototype cirrus clouds forming under well-known conditions, but with less certain life cycle and climate effects. This paper collects contrail data from a large set of measurements and compares them among each other and with models. The observations show consistent contrail properties over a wide range of aircraft and atmosphere conditions. The dataset is available for further research.
Shuaiqi Tang, Shaocheng Xie, Yunyan Zhang, Minghua Zhang, Courtney Schumacher, Hannah Upton, Michael P. Jensen, Karen L. Johnson, Meng Wang, Maike Ahlgrimm, Zhe Feng, Patrick Minnis, and Mandana Thieman
Atmos. Chem. Phys., 16, 14249–14264, https://doi.org/10.5194/acp-16-14249-2016, https://doi.org/10.5194/acp-16-14249-2016, 2016
Short summary
Short summary
Data observed during the Green Ocean Amazon (GoAmazon2014/5) experiment are used to derive the large-scale fields in this study. The morning propagating convective systems are active during the wet season but rare during the dry season. The afternoon convections are active in both seasons, with heating and moistening in the lower level corresponding to the vertical convergence of eddy fluxes. Case study shows distinguish large-scale environments for three types of convective systems in Amazonia.
J. M. Creamean, A. P. Ault, A. B. White, P. J. Neiman, F. M. Ralph, P. Minnis, and K. A. Prather
Atmos. Chem. Phys., 15, 6535–6548, https://doi.org/10.5194/acp-15-6535-2015, https://doi.org/10.5194/acp-15-6535-2015, 2015
Short summary
Short summary
Aerosols impact how clouds and precipitation form. In the California Sierra Nevada, we found that the formation and resulting amount of rain and snow were impacted by mineral dust, bioparticles such as bacteria, and biomass burning and pollution particles during three winter seasons. Dust and bioparticles from distant sources impacted high-altitude clouds by forming ice, leading to more precipitation, whereas local biomass burning and pollution entered the base of clouds, leading to less rain.
C. Liu, P. Yang, P. Minnis, N. Loeb, S. Kato, A. Heymsfield, and C. Schmitt
Atmos. Chem. Phys., 14, 13719–13737, https://doi.org/10.5194/acp-14-13719-2014, https://doi.org/10.5194/acp-14-13719-2014, 2014
Short summary
Short summary
An ice cloud model is developed by assuming an ice cloud to be an ensemble of columns and aggregates with specific habit fractions at each particle size bin. The microphysical and optical properties of this two-habit model (THM) are compared with both laboratory and in situ measurements. When the THM is applied to ice cloud property retrieval, excellent spectral consistency is achieved. A comparison between observed and theoretical polarized reflectivities illustrates the applicability of THM.
T. F. Eck, B. N. Holben, J. S. Reid, A. Arola, R. A. Ferrare, C. A. Hostetler, S. N. Crumeyrolle, T. A. Berkoff, E. J. Welton, S. Lolli, A. Lyapustin, Y. Wang, J. S. Schafer, D. M. Giles, B. E. Anderson, K. L. Thornhill, P. Minnis, K. E. Pickering, C. P. Loughner, A. Smirnov, and A. Sinyuk
Atmos. Chem. Phys., 14, 11633–11656, https://doi.org/10.5194/acp-14-11633-2014, https://doi.org/10.5194/acp-14-11633-2014, 2014
U. Hamann, A. Walther, B. Baum, R. Bennartz, L. Bugliaro, M. Derrien, P. N. Francis, A. Heidinger, S. Joro, A. Kniffka, H. Le Gléau, M. Lockhoff, H.-J. Lutz, J. F. Meirink, P. Minnis, R. Palikonda, R. Roebeling, A. Thoss, S. Platnick, P. Watts, and G. Wind
Atmos. Meas. Tech., 7, 2839–2867, https://doi.org/10.5194/amt-7-2839-2014, https://doi.org/10.5194/amt-7-2839-2014, 2014
A. Oumbe, Z. Qu, P. Blanc, M. Lefèvre, L. Wald, and S. Cros
Geosci. Model Dev., 7, 1661–1669, https://doi.org/10.5194/gmd-7-1661-2014, https://doi.org/10.5194/gmd-7-1661-2014, 2014
J. Fan, L. R. Leung, P. J. DeMott, J. M. Comstock, B. Singh, D. Rosenfeld, J. M. Tomlinson, A. White, K. A. Prather, P. Minnis, J. K. Ayers, and Q. Min
Atmos. Chem. Phys., 14, 81–101, https://doi.org/10.5194/acp-14-81-2014, https://doi.org/10.5194/acp-14-81-2014, 2014
D. Painemal, P. Minnis, and S. Sun-Mack
Atmos. Chem. Phys., 13, 9997–10003, https://doi.org/10.5194/acp-13-9997-2013, https://doi.org/10.5194/acp-13-9997-2013, 2013
Related subject area
Atmospheric sciences
Exploring the footprint representation of microwave radiance observations in an Arctic limited-area data assimilation system
Analysis of model error in forecast errors of extended atmospheric Lorenz 05 systems and the ECMWF system
Description and validation of Vehicular Emissions from Road Traffic (VERT) 1.0, an R-based framework for estimating road transport emissions from traffic flows
AeroMix v1.0.1: a Python package for modeling aerosol optical properties and mixing states
Impact of ITCZ width on global climate: ITCZ-MIP
Deep-learning-driven simulations of boundary layer clouds over the Southern Great Plains
Mixed-precision computing in the GRIST dynamical core for weather and climate modelling
A conservative immersed boundary method for the multi-physics urban large-eddy simulation model uDALES v2.0
RCEMIP-II: mock-Walker simulations as phase II of the radiative–convective equilibrium model intercomparison project
Objective identification of meteorological fronts and climatologies from ERA-Interim and ERA5
TAMS: a tracking, classifying, and variable-assigning algorithm for mesoscale convective systems in simulated and satellite-derived datasets
Development of the adjoint of the unified tropospheric–stratospheric chemistry extension (UCX) in GEOS-Chem adjoint v36
New explicit formulae for the settling speed of prolate spheroids in the atmosphere: theoretical background and implementation in AerSett v2.0.2
ZJU-AERO V0.5: an Accurate and Efficient Radar Operator designed for CMA-GFS/MESO with the capability to simulate non-spherical hydrometeors
The Year of Polar Prediction site Model Intercomparison Project (YOPPsiteMIP) phase 1: project overview and Arctic winter forecast evaluation
Evaluating CHASER V4.0 global formaldehyde (HCHO) simulations using satellite, aircraft, and ground-based remote-sensing observations
Global variable-resolution simulations of extreme precipitation over Henan, China, in 2021 with MPAS-Atmosphere v7.3
The CHIMERE chemistry-transport model v2023r1
tobac v1.5: introducing fast 3D tracking, splits and mergers, and other enhancements for identifying and analysing meteorological phenomena
Merged Observatory Data Files (MODFs): an integrated observational data product supporting process-oriented investigations and diagnostics
Simulation of marine stratocumulus using the super-droplet method: numerical convergence and comparison to a double-moment bulk scheme using SCALE-SDM 5.2.6-2.3.1
WRF-Comfort: simulating microscale variability in outdoor heat stress at the city scale with a mesoscale model
Representing effects of surface heterogeneity in a multi-plume eddy diffusivity mass flux boundary layer parameterization
FLEXPART version 11: Improved accuracy, efficiency, and flexibility
Can TROPOMI NO2 satellite data be used to track the drop in and resurgence of NOx emissions in Germany between 2019–2021 using the multi-source plume method (MSPM)?
A spatiotemporally separated framework for reconstructing the sources of atmospheric radionuclide releases
A parameterization scheme for the floating wind farm in a coupled atmosphere–wave model (COAWST v3.7)
RoadSurf 1.1: open-source road weather model library
Calibrating and validating the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) urban cooling model: case studies in France and the United States
The ddeq Python library for point source quantification from remote sensing images (version 1.0)
Incorporating Oxygen Isotopes of Oxidized Reactive Nitrogen in the Regional Atmospheric Chemistry Mechanism, version 2 (ICOIN-RACM2)
Development of the MPAS-CMAQ Coupled System (V1.0) for Multiscale Global Air Quality Modeling
A general comprehensive evaluation method for cross-scale precipitation forecasts
Implementation of a Simple Actuator Disk for Large-Eddy Simulation in the Weather Research and Forecasting Model (WRF-SADLES v1.2) for wind turbine wake simulation
WRF-PDAF v1.0: implementation and application of an online localized ensemble data assimilation framework
Implementation and evaluation of diabatic advection in the Lagrangian transport model MPTRAC 2.6
An improved and extended parameterization of the CO2 15 µm cooling in the middle and upper atmosphere (CO2_cool_fort-1.0)
Development of a multiphase chemical mechanism to improve secondary organic aerosol formation in CAABA/MECCA (version 4.7.0)
Application of regional meteorology and air quality models based on the microprocessor without interlocked piped stages (MIPS) and LoongArch CPU platforms
Investigating ground-level ozone pollution in semi-arid and arid regions of Arizona using WRF-Chem v4.4 modeling
An objective identification technique for potential vorticity structures associated with African easterly waves
Importance of microphysical settings for climate forcing by stratospheric SO2 injections as modeled by SOCOL-AERv2
Assessment of surface ozone products from downscaled CAMS reanalysis and CAMS daily forecast using urban air quality monitoring stations in Iran
Open boundary conditions for atmospheric large-eddy simulations and their implementation in DALES4.4
Efficient and stable coupling of the SuperdropNet deep-learning-based cloud microphysics (v0.1.0) with the ICON climate and weather model (v2.6.5)
Three-dimensional variational assimilation with a multivariate background error covariance for the Model for Prediction Across Scales – Atmosphere with the Joint Effort for Data assimilation Integration (JEDI-MPAS 2.0.0-beta)
FUME 2.0 – Flexible Universal processor for Modeling Emissions
DEUCE v1.0: a neural network for probabilistic precipitation nowcasting with aleatoric and epistemic uncertainties
Evaluation of multi-season convection-permitting atmosphere – mixed-layer ocean simulations of the Maritime Continent
RASCAL v1.0.0: An Open Source Tool for Climatological Time Series Reconstruction and Extension
Máté Mile, Stephanie Guedj, and Roger Randriamampianina
Geosci. Model Dev., 17, 6571–6587, https://doi.org/10.5194/gmd-17-6571-2024, https://doi.org/10.5194/gmd-17-6571-2024, 2024
Short summary
Short summary
Satellite observations provide crucial information about atmospheric constituents in a global distribution that helps to better predict the weather over sparsely observed regions like the Arctic. However, the use of satellite data is usually conservative and imperfect. In this study, a better spatial representation of satellite observations is discussed and explored by a so-called footprint function or operator, highlighting its added value through a case study and diagnostics.
Hynek Bednář and Holger Kantz
Geosci. Model Dev., 17, 6489–6511, https://doi.org/10.5194/gmd-17-6489-2024, https://doi.org/10.5194/gmd-17-6489-2024, 2024
Short summary
Short summary
The forecast error growth of atmospheric phenomena is caused by initial and model errors. When studying the initial error growth, it may turn out that small-scale phenomena, which contribute little to the forecast product, significantly affect the ability to predict this product. With a negative result, we investigate in the extended Lorenz (2005) system whether omitting these phenomena will improve predictability. A theory explaining and describing this behavior is developed.
Giorgio Veratti, Alessandro Bigi, Sergio Teggi, and Grazia Ghermandi
Geosci. Model Dev., 17, 6465–6487, https://doi.org/10.5194/gmd-17-6465-2024, https://doi.org/10.5194/gmd-17-6465-2024, 2024
Short summary
Short summary
In this study, we present VERT (Vehicular Emissions from Road Traffic), an R package designed to estimate transport emissions using traffic estimates and vehicle fleet composition data. Compared to other tools available in the literature, VERT stands out for its user-friendly configuration and flexibility of user input. Case studies demonstrate its accuracy in both urban and regional contexts, making it a valuable tool for air quality management and transport scenario planning.
Sam P. Raj, Puna Ram Sinha, Rohit Srivastava, Srinivas Bikkina, and Damu Bala Subrahamanyam
Geosci. Model Dev., 17, 6379–6399, https://doi.org/10.5194/gmd-17-6379-2024, https://doi.org/10.5194/gmd-17-6379-2024, 2024
Short summary
Short summary
A Python successor to the aerosol module of the OPAC model, named AeroMix, has been developed, with enhanced capabilities to better represent real atmospheric aerosol mixing scenarios. AeroMix’s performance in modeling aerosol mixing states has been evaluated against field measurements, substantiating its potential as a versatile aerosol optical model framework for next-generation algorithms to infer aerosol mixing states and chemical composition.
Angeline G. Pendergrass, Michael P. Byrne, Oliver Watt-Meyer, Penelope Maher, and Mark J. Webb
Geosci. Model Dev., 17, 6365–6378, https://doi.org/10.5194/gmd-17-6365-2024, https://doi.org/10.5194/gmd-17-6365-2024, 2024
Short summary
Short summary
The width of the tropical rain belt affects many aspects of our climate, yet we do not understand what controls it. To better understand it, we present a method to change it in numerical model experiments. We show that the method works well in four different models. The behavior of the width is unexpectedly simple in some ways, such as how strong the winds are as it changes, but in other ways, it is more complicated, especially how temperature increases with carbon dioxide.
Tianning Su and Yunyan Zhang
Geosci. Model Dev., 17, 6319–6336, https://doi.org/10.5194/gmd-17-6319-2024, https://doi.org/10.5194/gmd-17-6319-2024, 2024
Short summary
Short summary
Using 2 decades of field observations over the Southern Great Plains, this study developed a deep-learning model to simulate the complex dynamics of boundary layer clouds. The deep-learning model can serve as the cloud parameterization within reanalysis frameworks, offering insights into improving the simulation of low clouds. By quantifying biases due to various meteorological factors and parameterizations, this deep-learning-driven approach helps bridge the observation–modeling divide.
Siyuan Chen, Yi Zhang, Yiming Wang, Zhuang Liu, Xiaohan Li, and Wei Xue
Geosci. Model Dev., 17, 6301–6318, https://doi.org/10.5194/gmd-17-6301-2024, https://doi.org/10.5194/gmd-17-6301-2024, 2024
Short summary
Short summary
This study explores strategies and techniques for implementing mixed-precision code optimization within an atmosphere model dynamical core. The coded equation terms in the governing equations that are sensitive (or insensitive) to the precision level have been identified. The performance of mixed-precision computing in weather and climate simulations was analyzed.
Sam O. Owens, Dipanjan Majumdar, Chris E. Wilson, Paul Bartholomew, and Maarten van Reeuwijk
Geosci. Model Dev., 17, 6277–6300, https://doi.org/10.5194/gmd-17-6277-2024, https://doi.org/10.5194/gmd-17-6277-2024, 2024
Short summary
Short summary
Designing cities that are resilient, sustainable, and beneficial to health requires an understanding of urban climate and air quality. This article presents an upgrade to the multi-physics numerical model uDALES, which can simulate microscale airflow, heat transfer, and pollutant dispersion in urban environments. This upgrade enables it to resolve realistic urban geometries more accurately and to take advantage of the resources available on current and future high-performance computing systems.
Allison A. Wing, Levi G. Silvers, and Kevin A. Reed
Geosci. Model Dev., 17, 6195–6225, https://doi.org/10.5194/gmd-17-6195-2024, https://doi.org/10.5194/gmd-17-6195-2024, 2024
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
Lucie Bakels, Daria Tatsii, Anne Tipka, Rona Thompson, Marina Dütsch, Michael Blaschek, Petra Seibert, Katharina Baier, Silvia Bucci, Massimo Cassiani, Sabine Eckhardt, Christine Groot Zwaaftink, Stephan Henne, Pirmin Kaufmann, Vincent Lechner, Christian Maurer, Marie D. Mulder, Ignacio Pisso, Andreas Plach, Rakesh Subramanian, Martin Vojta, and Andreas Stohl
EGUsphere, https://doi.org/10.5194/egusphere-2024-1713, https://doi.org/10.5194/egusphere-2024-1713, 2024
Short summary
Short summary
Computer models are essential for improving our understanding of how gases and particles move in the atmosphere. We present an update of the atmospheric transport model FLEXPART. FLEXPART 11 is more accurate due to a reduced number of interpolations and a new scheme for wet deposition. It can simulate non-spherical aerosols, and includes linear chemical reactions. It is parallelised using OpenMP and includes new user options. A new user manual details how to use FLEXPART 11.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
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. Discuss., https://doi.org/10.5194/gmd-2024-52, https://doi.org/10.5194/gmd-2024-52, 2024
Preprint under review for GMD
Short summary
Short summary
This work describe how we linked 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 in a global scale. This new model scales well on high performance computing environment and performs well with respect to ground surface networks in terms of ozone and PM2.5.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
Cited articles
Anderson, J., Hoar, T., Raeder, K., Liu, H., Collins, N., Torn, R., and
Avellano, A.: The Data Assimilation Research Testbed: A Community
Facility, B. Am. Meteorol. Soc., 90, 1283–1296,
https://doi.org/10.1175/2009BAMS2618.1, 2009. a, b
Anderson, J. L.: An Ensemble Adjustment Kalman Filter for Data
Assimilation, Mon. Weather Rev., 129, 2884–2903,
https://doi.org/10.1175/1520-0493(2001)129<2884:AEAKFF>2.0.CO;2,
2001. a
Anderson, J. L.: An adaptive covariance inflation error correction algorithm
for ensemble filters, Tellus A, 59, 210–224,
https://doi.org/10.1111/j.1600-0870.2006.00216.x, 2007. a
Anderson, J. L.: Spatially and temporally varying adaptive covariance inflation
for ensemble filters, Tellus A, 61, 72–83,
https://doi.org/10.1111/j.1600-0870.2008.00361.x, 2009. a
Badosa, J., Haeffelin, M., and Chepfer, H.: Scales of spatial and temporal
variation of solar irradiance on Reunion tropical island, Sol. Energy, 88,
42–56, https://doi.org/10.1016/j.solener.2012.11.007, 2013. a, b
Badosa, J., Haeffelin, M., Kalecinski, N., Bonnardot, F., and Jumaux, G.:
Reliability of day-ahead solar irradiance forecasts on Reunion Island
depending on synoptic wind and humidity conditions, Sol. Energy, 115,
306–321, https://doi.org/10.1016/j.solener.2015.02.039, 2015. a, b
Barker, D., Huang, X.-Y., Liu, Z., Auligné, T., Zhang, X., Rugg, S., Ajjaji,
R., Bourgeois, A., Bray, J., Chen, Y., Demirtas, M., Guo, Y.-R., Henderson,
T., Huang, W., Lin, H.-C., Michalakes, J., Rizvi, S., and Zhang, X.: The
Weather Research and Forecasting Model's Community
Variational/Ensemble Data Assimilation System: WRFDA, B. Am.
Meteorol. Soc., 93, 831–843, https://doi.org/10.1175/BAMS-D-11-00167.1, 2012. a
Bessafi, M., Mihailović, D., Malinović-Milićević, S., Mihailović, A.,
Jumaux, G., Bonnardot, F., Fanchette, Y., and Chabriat, J.-P.: Spatial and
Temporal Non-Linear Dynamics Analysis and Predictability of
Solar Radiation Time Series for La Reunion Island (France),
Entropy, 20, 946, https://doi.org/10.3390/e20120946, 2018. a
Diagne, M., David, M., Lauret, P., Boland, J., and Schmutz, N.: Review of solar
irradiance forecasting methods and a proposition for small-scale insular
grids, Renew. Sust. Energ. Rev., 27, 65–76, https://doi.org/10.1016/j.rser.2013.06.042,
2013. a
Dillon, M. E., Skabar, Y. G., Ruiz, J., Kalnay, E., Collini, E. A.,
Echevarría, P., Saucedo, M., Miyoshi, T., and Kunii, M.: Application of the
WRF-LETKF Data Assimilation System over Southern South
America: Sensitivity to Model Physics, Weather Forecast., 31,
217–236, https://doi.org/10.1175/WAF-D-14-00157.1, 2016. a
Dudhia, J.: Numerical Study of Convection Observed during the Winter
Monsoon Experiment Using a Mesoscale Two-Dimensional Model, J.
Atmos. Sci., 46, 3077–3107,
https://doi.org/10.1175/1520-0469(1989)046<3077:NSOCOD>2.0.CO;2,
1989. a
Espinar, B., Blanc, P., Wald, L., Hoyer-Klick, C., Homscheidt, M. S., and
Wanderer, T.: On quality control procedures for solar radiation and
meteorological measures, from subhourly to monthly average time periods, EGU
General Assembly, Vienna, Austria, 22–27 April, 2012. a
Gaspari, G. and Cohn, S. E.: Construction of correlation functions in two and
three dimensions, Q. J. Roy. Meteor. Soc., 125, 723–757,
https://doi.org/10.1002/qj.49712555417, 1999. a
Haiden, T. and Trentmann, J.: Verification of cloudiness and radiation
forecasts in the greater Alpine region, Meteorol. Z., 25, 3–15,
https://doi.org/10.1127/metz/2015/0630, 2015. a
Hohenegger, C. and Schär, C.: Predictability and Error Growth Dynamics
in Cloud-Resolving Models, J. Atmos. Sci., 64, 4467–4478,
https://doi.org/10.1175/2007JAS2143.1, 2007. a
Kain, J. S.: The Kain-Fritsch Convective Parameterization: An
Update, J. Appl. Meteorol., 43, 170–181,
https://doi.org/10.1175/1520-0450(2004)043<0170:TKCPAU>2.0.CO;2,
2004. a
Kalnay, E.: Atmospheric Modeling, Data Assimilation, and
Predictability, Cambridge University Press, New York, 2003. a
Kurzrock, F., Cros, S., Chane-Ming, F., Otkin, J. A., Hutt, A., Linguet, L.,
Lajoie, G., and Potthast, R.: A Review of the Use of Geostationary
Satellite Observations in Regional-Scale Models for Short-term
Cloud Forecasting, Meteorol. Z., 27, 277–298, https://doi.org/10.1127/metz/2018/0904, 2018. a, b, c, d
Kurzrock, F.: WRF-DART namelists for GMDD paper Kurzrock et al., 2019, Zenodo, https://doi.org/10.5281/zenodo.3354950, 2019. a
Lara-Fanego, V., Ruiz-Arias, J. A., Pozo-Vázquez, A. D., Gueymard, C. A., and
Tovar-Pescador, J.: Evaluation of DNI forecast based on the WRF mesoscale
atmospheric model for CPV applications, in: AIP Conference
Proceedings, vol. 1477, 317–322, Toledo, Spain, 16–18 April 2012,
https://doi.org/10.1063/1.4753895, 2012. a, b
López-Coto, I., Bosch, J. L., Mathiesen, P., and Kleissl, J.: Comparison
between several parameterization schemes in WRF for solar forecasting in
coastal zones, in: SOLAR Conference Proceedings, Baltimore, Maryland,
USA, 16–20 April, 2013. a
Mass, C. F., Ovens, D., Westrick, K., and Colle, B. A.: Does Increasing
Horizontal Resolution Produce More Skillful Forecasts?, B. Am.
Meteorol. Soc., 83, 407–430,
https://doi.org/10.1175/1520-0477(2002)083<0407:DIHRPM>2.3.CO;2,
2002. a
Minnis, P., Nguyen, L., Palikonda, R., Heck, P. W., Spangenberg, D. A.,
Doelling, D. R., Ayers, J. K., Smith Jr., W. L., Khaiyer, M. M., Trepte,
Q. Z., Avey, L. A., Chang, F.-L., Yost, C. R., Chee, T. L., and Szedung,
S.-M.: Near-real time cloud retrievals from operational and research
meteorological satellites, in: Proceedings Volume 7107, Remote Sensing
of Clouds and the Atmosphere XIII, p. 710703, Cardiff, Wales, UK, 15–18
September 2008, https://doi.org/10.1117/12.800344, 2008. a
Minnis, P., Sun-Mack, S., Young, D. F., Heck, P. W., Garber, D. P., Chen, Y.,
Spangenberg, D. A., Arduini, R. F., Trepte, Q. Z., Smith, W. L., Ayers,
J. K., Gibson, S. C., Miller, W. F., Hong, G., Chakrapani, V., Takano, Y.,
Liou, K.-N., Xie, Y., and Yang, P.: CERES Edition-2 Cloud Property
Retrievals Using TRMM VIRS and Terra and Aqua MODIS Data,
Part I: Algorithms, IEEE T. Geosci. Remote, 49, 4374–4400,
https://doi.org/10.1109/TGRS.2011.2144601, 2011. a
Minnis, P., Bedka, K., Trepte, Q., Yost, C. R., Bedka, S. T., Scarino, B.,
Khlopenkov, K., and Khaiyer, M. M.: A consistent long-term cloud and clear-sky radiation property dataset from the Advanced Very High Resolution Radiometer (AVHRR), NOAA CDR Program Document: CDRP-ATBD-0826, 19 September, 159 pp., https://doi.org/10.7289/V5HT2M8T, 2016. a, b, c
Otkin, J. A.: Clear and cloudy sky infrared brightness temperature assimilation
using an ensemble Kalman filter, J. Geophys. Res.-Atmos., 115, D19207,
https://doi.org/10.1029/2009JD013759, 2010. a
Otkin, J. A.: Assessing the impact of the covariance localization radius when
assimilating infrared brightness temperature observations using an ensemble
Kalman filter, Mon. Weather Rev., 140, 543–561,
https://doi.org/10.1175/MWR-D-11-00084.1, 2012. a
Pan, Y., Zhu, K., Xue, M., Wang, X., Hu, M., Benjamin, S. G., Weygandt, S. S.,
and Whitaker, J. S.: A GSI-Based Coupled EnSRF-En3DVar Hybrid
Data Assimilation System for the Operational Rapid Refresh
Model: Tests at a Reduced Resolution, Mon. Weather Rev., 142,
3756–3780, https://doi.org/10.1175/MWR-D-13-00242.1, 2014. a
Pérez, J. C., Díaz, J. P., González, A., Expósito, J., Rivera-López, F.,
and Taima, D.: Evaluation of WRF Parameterizations for Dynamical
Downscaling in the Canary Islands, J. Climate, 27, 5611–5631,
https://doi.org/10.1175/JCLI-D-13-00458.1, 2014. a
Rigollier, C., Bauer, O., and Wald, L.: On the clear sky model of the ESRA
– European Solar Radiation Atlas – with respect to the heliosat
method, Sol. Energy, 68, 33–48, https://doi.org/10.1016/S0038-092X(99)00055-9, 2000. a
Ruiz-Arias, J. A., Arbizu-Barrena, C., Santos-Alamillos, F. J., Tovar-Pescador,
J., and Pozo-Vázquez, D.: Assessing the Surface Solar Radiation
Budget in the WRF Model: A Spatiotemporal Analysis of the Bias
and Its Causes, Mon. Weather Rev., 144, 703–711,
https://doi.org/10.1175/MWR-D-15-0262.1, 2016. a
Schmela, M., Beauvais, A., Chevillard, N., Guillén Paredes, M., Heisz, M., and
Rossi, R.: Global Market Outlook for Solar Power 2018–2022, Tech.
rep., SolarPower Europe,
available at: http://www.solarpowereurope.org/global-market-outlook-2018-2022/ (last access: 4 September 2019),
2018. a
Schraff, C., Reich, H., Rhodin, A., Schomburg, A., Stephan, K., Periáñez, A.,
and Potthast, R.: Kilometre-scale ensemble data assimilation for the COSMO
model (KENDA), Q. J. Roy. Meteor. Soc., 142, 1453–1472,
https://doi.org/10.1002/qj.2748, 2016. a
Sengupta, M., Habte, A., Gueymard, C., Wilbert, S., Renné, D., and Stoffel,
T.: Best Practices Handbook for the Collection and Use of Solar
Resource Data for Solar Energy Applications: Second Edition,
Technical Report, National Renewable Energy Laboratory (NREL), 2017. a
Shepard, D.: A two-dimensional interpolation function for irregularly-spaced
data, in: Proceedings of the 1968 23rd ACM national conference,
517–524, New York, NY, USA, 27–29 August 1968, https://doi.org/10.1145/800186.810616,
1968.
a
Skamarock, W. C., Klemp, J. B., Dudhia, J., Gill, D. O., Barker, D. M., Duda,
M. G., Huang, X.-Y., Wang, W., and Powers, J. G.: A Description of the
Advanced Research WRF Version 3, NCAR Technical Note
NCAR/TN-475+STR, National Center for Atmospheric Research, Boulder, CO,
2008. a
Stöckli, R.: Aerosol Optical Thickness,
available at: https://neo.sci.gsfc.nasa.gov/view.php?datasetId=MYDAL2_M_AER_OD (last access: 4 September 2019),
2018. a
Thompson, G., Field, P. R., Rasmussen, R. M., and Hall, W. D.: Explicit
Forecasts of Winter Precipitation Using an Improved Bulk
Microphysics Scheme. Part II: Implementation of a New Snow
Parameterization, Mon. Weather Rev., 136, 5095–5115,
https://doi.org/10.1175/2008MWR2387.1, 2008. a
Trepte, Q. Z., Minnis, P., Sun-Mack, S., Yost, C. R., Chen, Y., Jin, Z., Chang,
F.-L., Smith, William L., J., Bedka, K. M., and Chee, L.: Global Cloud Detection for CERES Edition 4 Using Terra and Aqua MODIS Data, IEEE
T. Geosci. Remote, in review, 2019. a
UCAR: WRF Physics Use Survey, Tech. rep.,
available: http://www2.mmm.ucar.edu/wrf/users/(last access: 4 September 2019), 2015. a
Verbois, H., Huva, R., Rusydi, A., and Walsh, W.: Solar irradiance forecasting
in the tropics using numerical weather prediction and statistical learning,
Sol. Energy, 162, 265–277, https://doi.org/10.1016/j.solener.2018.01.007, 2018. a
Yang, H. and Kleissl, J.: Preprocessing WRF initial conditions for coastal
stratocumulus forecasting, Sol. Energy, 133, 180–193,
https://doi.org/10.1016/j.solener.2016.04.003, 2016. a
Ying, Y., Zhang, F., and Anderson, J. L.: On the Selection of Localization
Radius in Ensemble Filtering for Multiscale Quasigeostrophic
Dynamics, Mon. Weather Rev., 146, 543–560, https://doi.org/10.1175/MWR-D-17-0336.1,
2018. a
Short summary
This study assesses the assimilation of cloud water path retrievals in three phases (ice, supercooled, and liquid), derived from Meteosat-8, into a limited-area model using an ensemble Kalman filter (EnKF). The ability of the method to improve cloud analyses in the southwest Indian Ocean and short-term forecasts of global horizontal irradiance on Réunion Island is demonstrated using the Data Assimilation Research Testbed (DART) and the Weather Research and Forecasting (WRF) model.
This study assesses the assimilation of cloud water path retrievals in three phases (ice,...
