Articles | Volume 16, issue 15
https://doi.org/10.5194/gmd-16-4551-2023
© Author(s) 2023. 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-16-4551-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model evaluation paper
| 
10 Aug 2023
Model evaluation paper |
| 10 Aug 2023
| 10 Aug 2023
Simulating heat and CO2 fluxes in Beijing using SUEWS V2020b: sensitivity to vegetation phenology and maximum conductance
Yingqi Zheng
State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, China
Institute for Atmospheric and Earth System Research/Physics, Faculty of Science, University of Helsinki, Helsinki, 00560, Finland
College of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing, 100029, China
Minttu Havu
Institute for Atmospheric and Earth System Research/Physics, Faculty of Science, University of Helsinki, Helsinki, 00560, Finland
Huizhi Liu
CORRESPONDING AUTHOR
Department of Atmospheric Sciences, Yunnan University, Kunming, 650091, China
Xueling Cheng
State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, China
College of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing, 100029, China
Yifan Wen
School of Environment, State Key Joint Laboratory of Environment Simulation and Pollution Control, Tsinghua University, Beijing, 100084, China
Hei Shing Lee
Institute for Atmospheric and Earth System Research/Physics, Faculty of Science, University of Helsinki, Helsinki, 00560, Finland
Helsinki Institute of Sustainability Science, University of Helsinki, Helsinki, 00560, Finland
Joyson Ahongshangbam
Institute for Atmospheric and Earth System Research/Physics, Faculty of Science, University of Helsinki, Helsinki, 00560, Finland
Leena Järvi
Institute for Atmospheric and Earth System Research/Physics, Faculty of Science, University of Helsinki, Helsinki, 00560, Finland
Helsinki Institute of Sustainability Science, University of Helsinki, Helsinki, 00560, Finland
Related authors
No articles found.
Esko Karvinen, Leif Backman, Leena Järvi, and Liisa Kulmala
EGUsphere, https://doi.org/10.5194/egusphere-2023-3031, https://doi.org/10.5194/egusphere-2023-3031, 2024
Short summary
Short summary
We measured and modelled soil respiration, a key part of the biogenic carbon cycle, in different urban green space types to assess its dynamics in urban areas. We discovered surprisingly similar soil respiration across the green space types, despite differences in some of its drivers, and that irrigation of green spaces notably elevates soil respiration. Our results encourage further research on the topic, especially on the role of irrigation in controlling urban soil respiration.
Zijun Zhang, Weiqi Xu, Yi Zhang, Wei Zhou, Xiangyu Xu, Aodong Du, Yinzhou Zhang, Hongqin Qiao, Ye Kuang, Xiaole Pan, Zifa Wang, Xueling Cheng, Lanzhong Liu, Qingyang Fu, Douglas R. Worsnop, Jie Li, and Yele Sun
EGUsphere, https://doi.org/10.5194/egusphere-2023-2684, https://doi.org/10.5194/egusphere-2023-2684, 2023
Short summary
Short summary
We investigated aerosol composition, sources, and the interaction between secondary organic aerosol (SOA) and clouds at a regional mountain site in southeastern China. Clouds efficiently scavenge more-oxidized SOA; however, cloud evaporation leads to the production of less-oxidized SOA. The unexpectedly high presence of nitrate in aerosol particles indicates that nitrate formed in polluted areas has undergone interactions with clouds, significantly influencing the regional background site.
Joyson Ahongshangbam, Liisa Kulmala, Jesse Soininen, Yasmin Frühauf, Esko Karvinen, Yann Salmon, Anna Lintunen, Anni Karvonen, and Leena Järvi
Biogeosciences, 20, 4455–4475, https://doi.org/10.5194/bg-20-4455-2023, https://doi.org/10.5194/bg-20-4455-2023, 2023
Short summary
Short summary
Urban vegetation is important for removing urban CO2 emissions and cooling. We studied the response of urban trees' functions (photosynthesis and transpiration) to a heatwave and drought at four urban green areas in the city of Helsinki. We found that tree water use was increased during heatwave and drought periods, but there was no change in the photosynthesis rates. The heat and drought conditions were severe at the local scale but were not excessive enough to restrict urban trees' functions.
Jani Strömberg, Xiaoyu Li, Mona Kurppa, Heino Kuuluvainen, Liisa Pirjola, and Leena Järvi
Atmos. Chem. Phys., 23, 9347–9364, https://doi.org/10.5194/acp-23-9347-2023, https://doi.org/10.5194/acp-23-9347-2023, 2023
Short summary
Short summary
We conclude that with low wind speeds, solar radiation has a larger decreasing effect (53 %) on pollutant concentrations than aerosol processes (18 %). Additionally, our results showed that with solar radiation included, pollutant concentrations were closer to observations (−13 %) than with only aerosol processes (+98 %). This has implications when planning simulations under calm conditions such as in our case and when deciding whether or not simulations need to include these processes.
Shengyue Li, Shuxiao Wang, Qingru Wu, Yanning Zhang, Daiwei Ouyang, Haotian Zheng, Licong Han, Xionghui Qiu, Yifan Wen, Min Liu, Yueqi Jiang, Dejia Yin, Kaiyun Liu, Bin Zhao, Shaojun Zhang, Ye Wu, and Jiming Hao
Earth Syst. Sci. Data, 15, 2279–2294, https://doi.org/10.5194/essd-15-2279-2023, https://doi.org/10.5194/essd-15-2279-2023, 2023
Short summary
Short summary
This study compiled China's emission inventory of air pollutants and CO2 during 2005–2021 (ABaCAS-EI v2.0) based on unified emission-source framework. The emission trends and its drivers are analyzed. Key sectors and regions with higher synergistic reduction potential of air pollutants and CO2 are identified. Future control measures are suggested. The dataset and analyses provide insights into the synergistic reduction of air pollutants and CO2 emissions for China and other developing countries.
Yifan Wen, Shaojun Zhang, Ye Wu, and Jiming Hao
Atmos. Chem. Phys., 23, 3819–3828, https://doi.org/10.5194/acp-23-3819-2023, https://doi.org/10.5194/acp-23-3819-2023, 2023
Short summary
Short summary
This study established a high-resolution vehicular NH3 emission inventory for mainland China to quantify the absolute value and relative importance of on-road NH3 emissions for different regions, seasons and population densities. Our results indicate that the significant role of on-road NH3 emissions in populated urban areas may have been underappreciated, suggesting the control of vehicular NH3 emission can be a feasible and cost-effective way of mitigating haze pollution in urban areas.
Mathew Lipson, Sue Grimmond, Martin Best, Winston T. L. Chow, Andreas Christen, Nektarios Chrysoulakis, Andrew Coutts, Ben Crawford, Stevan Earl, Jonathan Evans, Krzysztof Fortuniak, Bert G. Heusinkveld, Je-Woo Hong, Jinkyu Hong, Leena Järvi, Sungsoo Jo, Yeon-Hee Kim, Simone Kotthaus, Keunmin Lee, Valéry Masson, Joseph P. McFadden, Oliver Michels, Wlodzimierz Pawlak, Matthias Roth, Hirofumi Sugawara, Nigel Tapper, Erik Velasco, and Helen Claire Ward
Earth Syst. Sci. Data, 14, 5157–5178, https://doi.org/10.5194/essd-14-5157-2022, https://doi.org/10.5194/essd-14-5157-2022, 2022
Short summary
Short summary
We describe a new openly accessible collection of atmospheric observations from 20 cities around the world, capturing 50 site years. The observations capture local meteorology (temperature, humidity, wind, etc.) and the energy fluxes between the land and atmosphere (e.g. radiation and sensible and latent heat fluxes). These observations can be used to improve our understanding of urban climate processes and to test the accuracy of urban climate models.
Yamei Shao, Huizhi Liu, Qun Du, Yang Liu, Jihua Sun, and Yaohui Li
Biogeosciences Discuss., https://doi.org/10.5194/bg-2022-131, https://doi.org/10.5194/bg-2022-131, 2022
Manuscript not accepted for further review
Short summary
Short summary
The effects of sky conditions on ecosystem productivity over wetlands received little attention. Based on eddy covariance measurements during 2016–2020, we explored the impact of sky conditions on net ecosystem productivity (NEP) over an alpine marsh wetland in southwest China. We found diffuse radiation played a critical role in the variations of NEP, and gloomier sky condition was conducive to increasing apparent quantum yield and NEP.
Viktoria F. Sofieva, Risto Hänninen, Mikhail Sofiev, Monika Szeląg, Hei Shing Lee, Johanna Tamminen, and Christian Retscher
Atmos. Meas. Tech., 15, 3193–3212, https://doi.org/10.5194/amt-15-3193-2022, https://doi.org/10.5194/amt-15-3193-2022, 2022
Short summary
Short summary
We present tropospheric ozone column datasets that have been created using combinations of total ozone column from OMI and TROPOMI with stratospheric ozone column datasets from several available limb-viewing instruments (MLS, OSIRIS, MIPAS, SCIAMACHY, OMPS-LP, GOMOS). The main results are (i) several methodological developments, (ii) new tropospheric ozone column datasets from OMI and TROPOMI, and (iii) a new high-resolution dataset of ozone profiles from limb satellite instruments.
Minttu Havu, Liisa Kulmala, Pasi Kolari, Timo Vesala, Anu Riikonen, and Leena Järvi
Biogeosciences, 19, 2121–2143, https://doi.org/10.5194/bg-19-2121-2022, https://doi.org/10.5194/bg-19-2121-2022, 2022
Short summary
Short summary
The carbon sequestration potential of two street tree species and the soil beneath them was quantified with the urban land surface model SUEWS and the soil carbon model Yasso. The street tree plantings turned into a modest sink of carbon from the atmosphere after 14 years. Overall, the results indicate the importance of soil in urban carbon sequestration estimations, as soil respiration exceeded the carbon uptake in the early phase, due to the high initial carbon loss from the soil.
Sasu Karttunen, Ewan O'Connor, Olli Peltola, and Leena Järvi
Atmos. Meas. Tech., 15, 2417–2432, https://doi.org/10.5194/amt-15-2417-2022, https://doi.org/10.5194/amt-15-2417-2022, 2022
Short summary
Short summary
To study the complex structure of the lowest tens of metres of atmosphere in urban areas, measurement methods with great spatial and temporal coverage are needed. In our study, we analyse measurements with a promising and relatively new method, distributed temperature sensing, capable of providing detailed information on the near-surface atmosphere. We present multiple ways to utilise these kinds of measurements, as well as important considerations for planning new studies using the method.
Moritz Lange, Henri Suominen, Mona Kurppa, Leena Järvi, Emilia Oikarinen, Rafael Savvides, and Kai Puolamäki
Geosci. Model Dev., 14, 7411–7424, https://doi.org/10.5194/gmd-14-7411-2021, https://doi.org/10.5194/gmd-14-7411-2021, 2021
Short summary
Short summary
This study aims to replicate computationally expensive high-resolution large-eddy simulations (LESs) with regression models to simulate urban air quality and pollutant dispersion. The model development, including feature selection, model training and cross-validation, and detection of concept drift, has been described in detail. Of the models applied, log-linear regression shows the best performance. A regression model can replace LES unless high accuracy is needed.
Viktoria F. Sofieva, Hei Shing Lee, Johanna Tamminen, Christophe Lerot, Fabian Romahn, and Diego G. Loyola
Atmos. Meas. Tech., 14, 2993–3002, https://doi.org/10.5194/amt-14-2993-2021, https://doi.org/10.5194/amt-14-2993-2021, 2021
Short summary
Short summary
Our paper discusses the structure function method, which allows validation of random uncertainties in the data and, at the same time, probing of the small-scale natural variability. We applied this method to the clear-sky total ozone measurements by TROPOMI Sentinel-5P satellite instrument and found that the TROPOMI random error estimation is adequate. The discussed method is a powerful tool, which can be used in various applications.
Mona Kurppa, Pontus Roldin, Jani Strömberg, Anna Balling, Sasu Karttunen, Heino Kuuluvainen, Jarkko V. Niemi, Liisa Pirjola, Topi Rönkkö, Hilkka Timonen, Antti Hellsten, and Leena Järvi
Geosci. Model Dev., 13, 5663–5685, https://doi.org/10.5194/gmd-13-5663-2020, https://doi.org/10.5194/gmd-13-5663-2020, 2020
Short summary
Short summary
High-resolution modelling is needed to solve the aerosol concentrations in a complex urban area. Here, the performance of an aerosol module within the PALM model to simulate the detailed horizontal and vertical distribution of aerosol particles is studied. Further, sensitivity to the meteorological and aerosol boundary conditions is assessed using both model and observation data. The horizontal distribution is sensitive to the wind speed and stability, and the vertical to the wind direction.
Tom V. Kokkonen, Sue Grimmond, Sonja Murto, Huizhi Liu, Anu-Maija Sundström, and Leena Järvi
Atmos. Chem. Phys., 19, 7001–7017, https://doi.org/10.5194/acp-19-7001-2019, https://doi.org/10.5194/acp-19-7001-2019, 2019
Short summary
Short summary
This is the first study to evaluate and correct the WATCH WFDEI reanalysis product in a highly polluted urban environment. It gives an important understanding of the uncertainties in reanalysis products in local-scale urban modelling in polluted environments and identifies and corrects the most important variables in hydrological modelling. This is also the first study to examine the effects of haze on the local-scale urban hydrological cycle.
Mona Kurppa, Antti Hellsten, Pontus Roldin, Harri Kokkola, Juha Tonttila, Mikko Auvinen, Christoph Kent, Prashant Kumar, Björn Maronga, and Leena Järvi
Geosci. Model Dev., 12, 1403–1422, https://doi.org/10.5194/gmd-12-1403-2019, https://doi.org/10.5194/gmd-12-1403-2019, 2019
Short summary
Short summary
This paper describes the implementation of a sectional aerosol module, SALSA, into the PALM model system 6.0. The first evaluation study shows excellent agreements with measurements. Furthermore, we show that ignoring the dry deposition of aerosol particles can overestimate aerosol number concentrations by 20 %, whereas condensation and dissolutional growth increase the total aerosol mass by over 10 % in this specific urban environment.
Qun Du, Huizhi Liu, Lujun Xu, Yang Liu, and Lei Wang
Atmos. Chem. Phys., 18, 15087–15104, https://doi.org/10.5194/acp-18-15087-2018, https://doi.org/10.5194/acp-18-15087-2018, 2018
Short summary
Short summary
Erhai Lake is a subtropical highland shallow lake on the southeast margin of the Tibetan Plateau, which is influenced by both South Asian and East Asian summer monsoons. The substantial difference in atmospheric properties during monsoon and non-monsoon periods has a large effect in regulating turbulent heat and carbon dioxide exchange processes over Erhai Lake. Large difference are found for the factors controlling sensible heat and carbon dioxide flux during monsoon and non-monsoon periods.
Leena Järvi, Üllar Rannik, Tom V. Kokkonen, Mona Kurppa, Ari Karppinen, Rostislav D. Kouznetsov, Pekka Rantala, Timo Vesala, and Curtis R. Wood
Atmos. Meas. Tech., 11, 5421–5438, https://doi.org/10.5194/amt-11-5421-2018, https://doi.org/10.5194/amt-11-5421-2018, 2018
Short summary
Short summary
Identical EC systems on two sides of a building in central Helsinki were used to assess the uncertainty of the vertical fluxes on the single measurement point from July 2013 to September 2015. Sampling at only one point yielded up to 12% underestimation in the cumulative carbon fluxes; for sensible and latent heat the respective values were up to 5 and 8%. The commonly used statistics, kurtosis and skewness, are not necessarily suitable for filtering out data in a densely built urban area.
Qingqing Wang, Yele Sun, Weiqi Xu, Wei Du, Libo Zhou, Guiqian Tang, Chen Chen, Xueling Cheng, Xiujuan Zhao, Dongsheng Ji, Tingting Han, Zhe Wang, Jie Li, and Zifa Wang
Atmos. Chem. Phys., 18, 2495–2509, https://doi.org/10.5194/acp-18-2495-2018, https://doi.org/10.5194/acp-18-2495-2018, 2018
Short summary
Short summary
We conducted the first real-time continuous vertical measurements of particle extinction, NO2, and BC from ground level to 260 m during two severe winter haze episodes in urban Beijing, China. Our results show very complex and dynamic vertical profiles that interact closely with boundary layer and meteorological conditions. Further analysis demonstrate that vertical convection, temperature inversion, and local emissions are three major factors affecting the changes in vertical profiles.
Mikko Auvinen, Leena Järvi, Antti Hellsten, Üllar Rannik, and Timo Vesala
Geosci. Model Dev., 10, 4187–4205, https://doi.org/10.5194/gmd-10-4187-2017, https://doi.org/10.5194/gmd-10-4187-2017, 2017
Short summary
Short summary
Correct spatial interpretation of a micrometeorological measurement requires the determination of its effective source area, or footprint. In urban areas the use of analytical models becomes highly questionable. This work introduces a computational methodology that enables the generation of footprints for complex urban sites. The methodology is based on conducting high-resolution flow and particle analysis on a model that features a detailed topographic description of a real city environment.
Lei Wang, Huizhi Liu, Jihua Sun, and Yaping Shao
Atmos. Chem. Phys., 17, 5119–5129, https://doi.org/10.5194/acp-17-5119-2017, https://doi.org/10.5194/acp-17-5119-2017, 2017
Short summary
Short summary
This study found that the seasonal variation in CO2 exchange over an alpine meadow on the Tibetan Plateau was primarily affected by the seasonal pattern of air temperature, especially in spring and autumn. The annual net ecosystem exchange decreased with mean annual temperature, and then increased when the gross primary production became saturated. This study contributes to the response of the alpine meadow ecosystem to global warming.
Hanna K. Lappalainen, Veli-Matti Kerminen, Tuukka Petäjä, Theo Kurten, Aleksander Baklanov, Anatoly Shvidenko, Jaana Bäck, Timo Vihma, Pavel Alekseychik, Meinrat O. Andreae, Stephen R. Arnold, Mikhail Arshinov, Eija Asmi, Boris Belan, Leonid Bobylev, Sergey Chalov, Yafang Cheng, Natalia Chubarova, Gerrit de Leeuw, Aijun Ding, Sergey Dobrolyubov, Sergei Dubtsov, Egor Dyukarev, Nikolai Elansky, Kostas Eleftheriadis, Igor Esau, Nikolay Filatov, Mikhail Flint, Congbin Fu, Olga Glezer, Aleksander Gliko, Martin Heimann, Albert A. M. Holtslag, Urmas Hõrrak, Juha Janhunen, Sirkku Juhola, Leena Järvi, Heikki Järvinen, Anna Kanukhina, Pavel Konstantinov, Vladimir Kotlyakov, Antti-Jussi Kieloaho, Alexander S. Komarov, Joni Kujansuu, Ilmo Kukkonen, Ella-Maria Duplissy, Ari Laaksonen, Tuomas Laurila, Heikki Lihavainen, Alexander Lisitzin, Alexsander Mahura, Alexander Makshtas, Evgeny Mareev, Stephany Mazon, Dmitry Matishov, Vladimir Melnikov, Eugene Mikhailov, Dmitri Moisseev, Robert Nigmatulin, Steffen M. Noe, Anne Ojala, Mari Pihlatie, Olga Popovicheva, Jukka Pumpanen, Tatjana Regerand, Irina Repina, Aleksei Shcherbinin, Vladimir Shevchenko, Mikko Sipilä, Andrey Skorokhod, Dominick V. Spracklen, Hang Su, Dmitry A. Subetto, Junying Sun, Arkady Y. Terzhevik, Yuri Timofeyev, Yuliya Troitskaya, Veli-Pekka Tynkkynen, Viacheslav I. Kharuk, Nina Zaytseva, Jiahua Zhang, Yrjö Viisanen, Timo Vesala, Pertti Hari, Hans Christen Hansson, Gennady G. Matvienko, Nikolai S. Kasimov, Huadong Guo, Valery Bondur, Sergej Zilitinkevich, and Markku Kulmala
Atmos. Chem. Phys., 16, 14421–14461, https://doi.org/10.5194/acp-16-14421-2016, https://doi.org/10.5194/acp-16-14421-2016, 2016
Short summary
Short summary
After kick off in 2012, the Pan-Eurasian Experiment (PEEX) program has expanded fast and today the multi-disciplinary research community covers ca. 80 institutes and a network of ca. 500 scientists from Europe, Russia, and China. Here we introduce scientific topics relevant in this context. This is one of the first multi-disciplinary overviews crossing scientific boundaries, from atmospheric sciences to socio-economics and social sciences.
Ivan Mammarella, Olli Peltola, Annika Nordbo, Leena Järvi, and Üllar Rannik
Atmos. Meas. Tech., 9, 4915–4933, https://doi.org/10.5194/amt-9-4915-2016, https://doi.org/10.5194/amt-9-4915-2016, 2016
Short summary
Short summary
In this study we have performed an inter-comparison between EddyUH and EddyPro, two public and commonly used software packages for eddy covariance data processing and calculation. The aims are to estimate the flux uncertainty due to the use of different software packages, and to assess the most critical processing steps, determining the largest deviations in the calculated fluxes. We focus not only on water vapour and carbon dioxide fluxes, but also on the methane flux.
Pekka Rantala, Leena Järvi, Risto Taipale, Terhi K. Laurila, Johanna Patokoski, Maija K. Kajos, Mona Kurppa, Sami Haapanala, Erkki Siivola, Tuukka Petäjä, Taina M. Ruuskanen, and Janne Rinne
Atmos. Chem. Phys., 16, 7981–8007, https://doi.org/10.5194/acp-16-7981-2016, https://doi.org/10.5194/acp-16-7981-2016, 2016
Short summary
Short summary
Fluxes of volatile organic compounds (VOCs) were measured above an urban landscape in Helsinki, northern Europe. We found that traffic was a major source for many oxygenated and aromatic VOCs, whereas isoprene originated mostly from the urban vegetation. Overall, the VOC fluxes were quite small in comparison with the earlier urban VOC flux measurements.
L. Järvi, C. S. B. Grimmond, M. Taka, A. Nordbo, H. Setälä, and I. B. Strachan
Geosci. Model Dev., 7, 1691–1711, https://doi.org/10.5194/gmd-7-1691-2014, https://doi.org/10.5194/gmd-7-1691-2014, 2014
L. Liu, F. Hu, and X.-L. Cheng
Nonlin. Processes Geophys., 21, 463–475, https://doi.org/10.5194/npg-21-463-2014, https://doi.org/10.5194/npg-21-463-2014, 2014
K. Wang, C. Liu, X. Zheng, M. Pihlatie, B. Li, S. Haapanala, T. Vesala, H. Liu, Y. Wang, G. Liu, and F. Hu
Biogeosciences, 10, 6865–6877, https://doi.org/10.5194/bg-10-6865-2013, https://doi.org/10.5194/bg-10-6865-2013, 2013
Related subject area
Atmospheric sciences
Validation and analysis of the Polair3D v1.11 chemical transport model over Quebec
Assimilation of GNSS tropospheric gradients into the Weather Research and Forecasting (WRF) model version 4.4.1
Identifying atmospheric rivers and their poleward latent heat transport with generalizable neural networks: ARCNNv1
Assessing acetone for the GISS ModelE2.1 Earth system model
Bergen metrics: composite error metrics for assessing performance of climate models using EURO-CORDEX simulations
A dynamic approach to three-dimensional radiative transfer in subkilometer-scale numerical weather prediction models: the dynamic TenStream solver v1.0
Evaluation and development of surface layer scheme representation of temperature inversions over boreal forests in Arctic wintertime conditions
Modelling wind farm effects in HARMONIE–AROME (cycle 43.2.2) – Part 1: Implementation and evaluation
Analytical and adaptable initial conditions for dry and moist baroclinic waves in the global hydrostatic model OpenIFS (CY43R3)
Challenges of constructing and selecting the “perfect” boundary conditions for the large-eddy simulation model PALM
A machine learning approach for evaluating Southern Ocean cloud radiative biases in a global atmosphere model
Decision Support System version 1.0 (DSS v1.0) for air quality management in Delhi, India
How non-equilibrium aerosol chemistry impacts particle acidity: the GMXe AERosol CHEMistry (GMXe–AERCHEM, v1.0) sub-submodel of MESSy
A grid model for vertical correction of precipitable water vapor over the Chinese mainland and surrounding areas using random forest
MEXPLORER 1.0.0 – a mechanism explorer for analysis and visualization of chemical reaction pathways based on graph theory
Advances and prospects of deep learning for medium-range extreme weather forecasting
An overview of the Western United States Dynamically Downscaled Dataset (WUS-D3)
cloudbandPy 1.0: an automated algorithm for the detection of tropical–extratropical cloud bands
PyRTlib: an educational Python-based library for non-scattering atmospheric microwave radiative transfer computations
Deep learning applied to CO2 power plant emissions quantification using simulated satellite images
Sensitivity of the WRF-Chem v4.4 simulations of ozone and formaldehyde and their precursors to multiple bottom-up emission inventories over East Asia during the KORUS-AQ 2016 field campaign
Optimising urban measurement networks for CO2 flux estimation: a high-resolution observing system simulation experiment using GRAMM/GRAL
Assessment of climate biases in OpenIFS version 43r3 across model horizontal resolutions and time steps
High-resolution multi-scaling of outdoor human thermal comfort and its intra-urban variability based on machine learning
Effects of vertical grid spacing on the climate simulated in the ICON-Sapphire global storm-resolving model
Development of the tangent linear and adjoint models of the global online chemical transport model MPAS-CO2 v7.3
Impacts of updated reaction kinetics on the global GEOS-Chem simulation of atmospheric chemistry
Spatial spin-up of precipitation in limited-area convection-permitting simulations over North America using the CRCM6/GEM5.0 model
Sensitivity of atmospheric rivers to aerosol treatment in regional climate simulations: insights from the AIRA identification algorithm
The implementation of dust mineralogy in COSMO5.05-MUSCAT
Implementation of the ISORROPIA-lite aerosol thermodynamics model into the EMAC chemistry climate model (based on MESSy v2.55): implications for aerosol composition and acidity
Evaluation of surface shortwave downward radiation forecasts by the numerical weather prediction model AROME
GEO4PALM v1.1: an open-source geospatial data processing toolkit for the PALM model system
Modeling collision–coalescence in particle microphysics: numerical convergence of mean and variance of precipitation in cloud simulations using the University of Warsaw Lagrangian Cloud Model (UWLCM) 2.1
Modeling below-cloud scavenging of size-resolved particles in GEM-MACHv3.1
Impacts of a double-moment bulk cloud microphysics scheme (NDW6-G23) on aerosol fields in NICAM.19 with a global 14 km grid resolution
Sensitivity of air quality model responses to emission changes: comparison of results based on four EU inventories through FAIRMODE benchmarking methodology
A simple and realistic aerosol emission approach for use in the Thompson–Eidhammer microphysics scheme in the NOAA UFS Weather Model (version GSL global-24Feb2022)
Representing effects of surface heterogeneity in a multi-plume eddy diffusivity mass flux boundary layer parameterization
On the formation of biogenic secondary organic aerosol in chemical transport models: an evaluation of the WRF-CHIMERE (v2020r2) model with a focus over the Finnish boreal forest
The first application of a numerically exact, higher-order sensitivity analysis approach for atmospheric modelling: implementation of the hyperdual-step method in the Community Multiscale Air Quality Model (CMAQ) version 5.3.2
Development of the adjoint of the GEOS-Chem unified tropospheric-stratospheric chemistry extension (UCX) in GEOS-Chem Adjoint v36
The ddeq Python library for point source quantification from remote sensing images (Version 1.0)
GAN-argcPredNet v2.0: a radar echo extrapolation model based on spatiotemporal process enhancement
Analysis of the GEFS-Aerosols annual budget to better understand aerosol predictions simulated in the model
A model for rapid PM2.5 exposure estimates in wildfire conditions using routinely available data: rapidfire v0.1.3
BoundaryLayerDynamics.jl v1.0: a modern codebase for atmospheric boundary-layer simulations
Investigating Ground-Level Ozone Pollution in Semi-Arid and Arid Regions of Arizona Using WRF-Chem v4.4 Modeling
The wave-age-dependent stress parameterisation (WASP) for momentum and heat turbulent fluxes at sea in SURFEX v8.1
FUME 2.0 – Flexible Universal processor for Modeling Emissions
Shoma Yamanouchi, Shayamilla Mahagammulla Gamage, Sara Torbatian, Jad Zalzal, Laura Minet, Audrey Smargiassi, Ying Liu, Ling Liu, Forood Azargoshasbi, Jinwoong Kim, Youngseob Kim, Daniel Yazgi, and Marianne Hatzopoulou
Geosci. Model Dev., 17, 3579–3597, https://doi.org/10.5194/gmd-17-3579-2024, https://doi.org/10.5194/gmd-17-3579-2024, 2024
Short summary
Short summary
Air pollution is a major health hazard, and chemical transport models (CTMs) are valuable tools that aid in our understanding of the risks of air pollution at both local and regional scales. In this study, the Polair3D CTM of the Polyphemus air quality modeling platform was set up over Quebec, Canada, to assess the model’s capability in predicting key air pollutant species over the region, at seasonal temporal scales and at regional spatial scales.
Rohith Thundathil, Florian Zus, Galina Dick, and Jens Wickert
Geosci. Model Dev., 17, 3599–3616, https://doi.org/10.5194/gmd-17-3599-2024, https://doi.org/10.5194/gmd-17-3599-2024, 2024
Short summary
Short summary
Global Navigation Satellite Systems (GNSS) provides moisture observations through its densely distributed ground station network. In this research, we assimilate a new type of observation called tropospheric gradient observations, which has never been incorporated into a weather model. We develop a forward operator for gradient-based observations and conduct an assimilation impact study. The study shows significant improvements in the model's humidity fields.
Ankur Mahesh, Travis A. O'Brien, Burlen Loring, Abdelrahman Elbashandy, William Boos, and William D. Collins
Geosci. Model Dev., 17, 3533–3557, https://doi.org/10.5194/gmd-17-3533-2024, https://doi.org/10.5194/gmd-17-3533-2024, 2024
Short summary
Short summary
Atmospheric rivers (ARs) are extreme weather events that can alleviate drought or cause billions of US dollars in flood damage. We train convolutional neural networks (CNNs) to detect ARs with an estimate of the uncertainty. We present a framework to generalize these CNNs to a variety of datasets of past, present, and future climate. Using a simplified simulation of the Earth's atmosphere, we validate the CNNs. We explore the role of ARs in maintaining energy balance in the Earth system.
Alexandra Rivera, Kostas Tsigaridis, Gregory Faluvegi, and Drew Shindell
Geosci. Model Dev., 17, 3487–3505, https://doi.org/10.5194/gmd-17-3487-2024, https://doi.org/10.5194/gmd-17-3487-2024, 2024
Short summary
Short summary
This paper describes and evaluates an improvement to the representation of acetone in the GISS ModelE2.1 Earth system model. We simulate acetone's concentration and transport across the atmosphere as well as its dependence on chemistry, the ocean, and various global emissions. Comparisons of our model’s estimates to past modeling studies and field measurements have shown encouraging results. Ultimately, this paper contributes to a broader understanding of acetone's role in the atmosphere.
Alok K. Samantaray, Priscilla A. Mooney, and Carla A. Vivacqua
Geosci. Model Dev., 17, 3321–3339, https://doi.org/10.5194/gmd-17-3321-2024, https://doi.org/10.5194/gmd-17-3321-2024, 2024
Short summary
Short summary
Any interpretation of climate model data requires a comprehensive evaluation of the model performance. Numerous error metrics exist for this purpose, and each focuses on a specific aspect of the relationship between reference and model data. Thus, a comprehensive evaluation demands the use of multiple error metrics. However, this can lead to confusion. We propose a clustering technique to reduce the number of error metrics needed and a composite error metric to simplify the interpretation.
Richard Maier, Fabian Jakub, Claudia Emde, Mihail Manev, Aiko Voigt, and Bernhard Mayer
Geosci. Model Dev., 17, 3357–3383, https://doi.org/10.5194/gmd-17-3357-2024, https://doi.org/10.5194/gmd-17-3357-2024, 2024
Short summary
Short summary
Based on the TenStream solver, we present a new method to accelerate 3D radiative transfer towards the speed of currently used 1D solvers. Using a shallow-cumulus-cloud time series, we evaluate the performance of this new solver in terms of both speed and accuracy. Compared to a 3D benchmark simulation, we show that our new solver is able to determine much more accurate irradiances and heating rates than a 1D δ-Eddington solver, even when operated with a similar computational demand.
Julia Maillard, Jean-Christophe Raut, and François Ravetta
Geosci. Model Dev., 17, 3303–3320, https://doi.org/10.5194/gmd-17-3303-2024, https://doi.org/10.5194/gmd-17-3303-2024, 2024
Short summary
Short summary
Atmospheric models struggle to reproduce the strong temperature inversions in the vicinity of the surface over forested areas in the Arctic winter. In this paper, we develop modified simplified versions of surface layer schemes widely used by the community. Our modifications are used to correct the fact that original schemes place strong limits on the turbulent collapse, leading to a lower surface temperature gradient at low wind speeds. Modified versions show a better performance.
Jana Fischereit, Henrik Vedel, Xiaoli Guo Larsén, Natalie E. Theeuwes, Gregor Giebel, and Eigil Kaas
Geosci. Model Dev., 17, 2855–2875, https://doi.org/10.5194/gmd-17-2855-2024, https://doi.org/10.5194/gmd-17-2855-2024, 2024
Short summary
Short summary
Wind farms impact local wind and turbulence. To incorporate these effects in weather forecasting, the explicit wake parameterization (EWP) is added to the forecasting model HARMONIE–AROME. We evaluate EWP using flight data above and downstream of wind farms, comparing it with an alternative wind farm parameterization and another weather model. Results affirm the correct implementation of EWP, emphasizing the necessity of accounting for wind farm effects in accurate weather forecasting.
Clément Bouvier, Daan van den Broek, Madeleine Ekblom, and Victoria A. Sinclair
Geosci. Model Dev., 17, 2961–2986, https://doi.org/10.5194/gmd-17-2961-2024, https://doi.org/10.5194/gmd-17-2961-2024, 2024
Short summary
Short summary
An analytical initial background state has been developed for moist baroclinic wave simulation on an aquaplanet and implemented into OpenIFS. Seven parameters can be controlled, which are used to generate the background states and the development of baroclinic waves. The meteorological and numerical stability has been assessed. Resulting baroclinic waves have proven to be realistic and sensitive to the jet's width.
Jelena Radović, Michal Belda, Jaroslav Resler, Kryštof Eben, Martin Bureš, Jan Geletič, Pavel Krč, Hynek Řezníček, and Vladimír Fuka
Geosci. Model Dev., 17, 2901–2927, https://doi.org/10.5194/gmd-17-2901-2024, https://doi.org/10.5194/gmd-17-2901-2024, 2024
Short summary
Short summary
Boundary conditions are of crucial importance for numerical model (e.g., PALM) validation studies and have a large influence on the model results, especially when studying the atmosphere of real, complex, and densely built urban environments. Our experiments with different driving conditions for the large-eddy simulation model PALM show its strong dependency on boundary conditions, which is important for the proper separation of errors coming from the boundary conditions and the model itself.
Sonya L. Fiddes, Marc D. Mallet, Alain Protat, Matthew T. Woodhouse, Simon P. Alexander, and Kalli Furtado
Geosci. Model Dev., 17, 2641–2662, https://doi.org/10.5194/gmd-17-2641-2024, https://doi.org/10.5194/gmd-17-2641-2024, 2024
Short summary
Short summary
In this study we present an evaluation that considers complex, non-linear systems in a holistic manner. This study uses XGBoost, a machine learning algorithm, to predict the simulated Southern Ocean shortwave radiation bias in the ACCESS model using cloud property biases as predictors. We then used a novel feature importance analysis to quantify the role that each cloud bias plays in predicting the radiative bias, laying the foundation for advanced Earth system model evaluation and development.
Gaurav Govardhan, Sachin D. Ghude, Rajesh Kumar, Sumit Sharma, Preeti Gunwani, Chinmay Jena, Prafull Yadav, Shubhangi Ingle, Sreyashi Debnath, Pooja Pawar, Prodip Acharja, Rajmal Jat, Gayatry Kalita, Rupal Ambulkar, Santosh Kulkarni, Akshara Kaginalkar, Vijay K. Soni, Ravi S. Nanjundiah, and Madhavan Rajeevan
Geosci. Model Dev., 17, 2617–2640, https://doi.org/10.5194/gmd-17-2617-2024, https://doi.org/10.5194/gmd-17-2617-2024, 2024
Short summary
Short summary
A newly developed air quality forecasting framework, Decision Support System (DSS), for air quality management in Delhi, India, provides source attribution with numerous emission reduction scenarios besides forecasts. DSS shows that during post-monsoon and winter seasons, Delhi and its neighboring districts contribute to 30 %–40 % each to pollution in Delhi. On average, a 40 % reduction in the emissions in Delhi and the surrounding districts would result in a 24 % reduction in Delhi's pollution.
Simon Rosanka, Holger Tost, Rolf Sander, Patrick Jöckel, Astrid Kerkweg, and Domenico Taraborrelli
Geosci. Model Dev., 17, 2597–2615, https://doi.org/10.5194/gmd-17-2597-2024, https://doi.org/10.5194/gmd-17-2597-2024, 2024
Short summary
Short summary
The capabilities of the Modular Earth Submodel System (MESSy) are extended to account for non-equilibrium aqueous-phase chemistry in the representation of deliquescent aerosols. When applying the new development in a global simulation, we find that MESSy's bias in modelling routinely observed reduced inorganic aerosol mass concentrations, especially in the United States. Furthermore, the representation of fine-aerosol pH is particularly improved in the marine boundary layer.
Junyu Li, Yuxin Wang, Lilong Liu, Yibin Yao, Liangke Huang, and Feijuan Li
Geosci. Model Dev., 17, 2569–2581, https://doi.org/10.5194/gmd-17-2569-2024, https://doi.org/10.5194/gmd-17-2569-2024, 2024
Short summary
Short summary
In this study, we have developed a model (RF-PWV) to characterize precipitable water vapor (PWV) variation with altitude in the study area. RF-PWV can significantly reduce errors in vertical correction, enhance PWV fusion product accuracy, and provide insights into PWV vertical distribution, thereby contributing to climate research.
Rolf Sander
Geosci. Model Dev., 17, 2419–2425, https://doi.org/10.5194/gmd-17-2419-2024, https://doi.org/10.5194/gmd-17-2419-2024, 2024
Short summary
Short summary
The open-source software MEXPLORER 1.0.0 is presented here. The program can be used to analyze, reduce, and visualize complex chemical reaction mechanisms. The mathematics behind the tool is based on graph theory: chemical species are represented as vertices, and reactions as edges. MEXPLORER is a community model published under the GNU General Public License.
Leonardo Olivetti and Gabriele Messori
Geosci. Model Dev., 17, 2347–2358, https://doi.org/10.5194/gmd-17-2347-2024, https://doi.org/10.5194/gmd-17-2347-2024, 2024
Short summary
Short summary
In the last decades, weather forecasting up to 15 d into the future has been dominated by physics-based numerical models. Recently, deep learning models have challenged this paradigm. However, the latter models may struggle when forecasting weather extremes. In this article, we argue for deep learning models specifically designed to handle extreme events, and we propose a foundational framework to develop such models.
Stefan Rahimi, Lei Huang, Jesse Norris, Alex Hall, Naomi Goldenson, Will Krantz, Benjamin Bass, Chad Thackeray, Henry Lin, Di Chen, Eli Dennis, Ethan Collins, Zachary J. Lebo, Emily Slinskey, Sara Graves, Surabhi Biyani, Bowen Wang, Stephen Cropper, and the UCLA Center for Climate Science Team
Geosci. Model Dev., 17, 2265–2286, https://doi.org/10.5194/gmd-17-2265-2024, https://doi.org/10.5194/gmd-17-2265-2024, 2024
Short summary
Short summary
Here, we project future climate across the western United States through the end of the 21st century using a regional climate model, embedded within 16 latest-generation global climate models, to provide the community with a high-resolution physically based ensemble of climate data for use at local scales. Strengths and weaknesses of the data are frankly discussed as we overview the downscaled dataset.
Romain Pilon and Daniela I. V. Domeisen
Geosci. Model Dev., 17, 2247–2264, https://doi.org/10.5194/gmd-17-2247-2024, https://doi.org/10.5194/gmd-17-2247-2024, 2024
Short summary
Short summary
This paper introduces a new method for detecting atmospheric cloud bands to identify long convective cloud bands that extend from the tropics to the midlatitudes. The algorithm allows for easy use and enables researchers to study the life cycle and climatology of cloud bands and associated rainfall. This method provides insights into the large-scale processes involved in cloud band formation and their connections between different regions, as well as differences across ocean basins.
Salvatore Larosa, Domenico Cimini, Donatello Gallucci, Saverio Teodosio Nilo, and Filomena Romano
Geosci. Model Dev., 17, 2053–2076, https://doi.org/10.5194/gmd-17-2053-2024, https://doi.org/10.5194/gmd-17-2053-2024, 2024
Short summary
Short summary
PyRTlib is an attractive educational tool because it provides a flexible and user-friendly way to broadly simulate how electromagnetic radiation travels through the atmosphere as it interacts with atmospheric constituents (such as gases, aerosols, and hydrometeors). PyRTlib is a so-called radiative transfer model; these are commonly used to simulate and understand remote sensing observations from ground-based, airborne, or satellite instruments.
Joffrey Dumont Le Brazidec, Pierre Vanderbecken, Alban Farchi, Grégoire Broquet, Gerrit Kuhlmann, and Marc Bocquet
Geosci. Model Dev., 17, 1995–2014, https://doi.org/10.5194/gmd-17-1995-2024, https://doi.org/10.5194/gmd-17-1995-2024, 2024
Short summary
Short summary
Our research presents an innovative approach to estimating power plant CO2 emissions from satellite images of the corresponding plumes such as those from the forthcoming CO2M satellite constellation. The exploitation of these images is challenging due to noise and meteorological uncertainties. To overcome these obstacles, we use a deep learning neural network trained on simulated CO2 images. Our method outperforms alternatives, providing a positive perspective for the analysis of CO2M images.
Kyoung-Min Kim, Si-Wan Kim, Seunghwan Seo, Donald R. Blake, Seogju Cho, James H. Crawford, Louisa K. Emmons, Alan Fried, Jay R. Herman, Jinkyu Hong, Jinsang Jung, Gabriele G. Pfister, Andrew J. Weinheimer, Jung-Hun Woo, and Qiang Zhang
Geosci. Model Dev., 17, 1931–1955, https://doi.org/10.5194/gmd-17-1931-2024, https://doi.org/10.5194/gmd-17-1931-2024, 2024
Short summary
Short summary
Three emission inventories were evaluated for East Asia using data acquired during a field campaign in 2016. The inventories successfully reproduced the daily variations of ozone and nitrogen dioxide. However, the spatial distributions of model ozone did not fully agree with the observations. Additionally, all simulations underestimated carbon monoxide and volatile organic compound (VOC) levels. Increasing VOC emissions over South Korea resulted in improved ozone simulations.
Sanam Noreen Vardag and Robert Maiwald
Geosci. Model Dev., 17, 1885–1902, https://doi.org/10.5194/gmd-17-1885-2024, https://doi.org/10.5194/gmd-17-1885-2024, 2024
Short summary
Short summary
We use the atmospheric transport model GRAMM/GRAL in a Bayesian inversion to estimate urban CO2 emissions on a neighbourhood scale. We analyse the effect of varying number, precision and location of CO2 sensors for CO2 flux estimation. We further test the inclusion of co-emitted species and correlation in the inversion. The study showcases the general usefulness of GRAMM/GRAL in measurement network design.
Abhishek Savita, Joakim Kjellsson, Robin Pilch Kedzierski, Mojib Latif, Tabea Rahm, Sebastian Wahl, and Wonsun Park
Geosci. Model Dev., 17, 1813–1829, https://doi.org/10.5194/gmd-17-1813-2024, https://doi.org/10.5194/gmd-17-1813-2024, 2024
Short summary
Short summary
The OpenIFS model is used to examine the impact of horizontal resolutions (HR) and model time steps. We find that the surface wind biases over the oceans, in particular the Southern Ocean, are sensitive to the model time step and HR, with the HR having the smallest biases. When using a coarse-resolution model with a shorter time step, a similar improvement is also found. Climate biases can be reduced in the OpenIFS model at a cheaper cost by reducing the time step rather than increasing the HR.
Ferdinand Briegel, Jonas Wehrle, Dirk Schindler, and Andreas Christen
Geosci. Model Dev., 17, 1667–1688, https://doi.org/10.5194/gmd-17-1667-2024, https://doi.org/10.5194/gmd-17-1667-2024, 2024
Short summary
Short summary
We present a new approach to model heat stress in cities using artificial intelligence (AI). We show that the AI model is fast in terms of prediction but accurate when evaluated with measurements. The fast-predictive AI model enables several new potential applications, including heat stress prediction and warning; downscaling of potential future climates; evaluation of adaptation effectiveness; and, more fundamentally, development of guidelines to support urban planning and policymaking.
Hauke Schmidt, Sebastian Rast, Jiawei Bao, Amrit Cassim, Shih-Wei Fang, Diego Jimenez-de la Cuesta, Paul Keil, Lukas Kluft, Clarissa Kroll, Theresa Lang, Ulrike Niemeier, Andrea Schneidereit, Andrew I. L. Williams, and Bjorn Stevens
Geosci. Model Dev., 17, 1563–1584, https://doi.org/10.5194/gmd-17-1563-2024, https://doi.org/10.5194/gmd-17-1563-2024, 2024
Short summary
Short summary
A recent development in numerical simulations of the global atmosphere is the increase in horizontal resolution to grid spacings of a few kilometers. However, the vertical grid spacing of these models has not been reduced at the same rate as the horizontal grid spacing. Here, we assess the effects of much finer vertical grid spacings, in particular the impacts on cloud quantities and the atmospheric energy balance.
Tao Zheng, Sha Feng, Jeffrey Steward, Xiaoxu Tian, David Baker, and Martin Baxter
Geosci. Model Dev., 17, 1543–1562, https://doi.org/10.5194/gmd-17-1543-2024, https://doi.org/10.5194/gmd-17-1543-2024, 2024
Short summary
Short summary
The tangent linear and adjoint models have been successfully implemented in the MPAS-CO2 system, which has undergone rigorous accuracy testing. This development lays the groundwork for a global carbon flux data assimilation system, which offers the flexibility of high-resolution focus on specific areas, while maintaining a coarser resolution elsewhere. This approach significantly reduces computational costs and is thus perfectly suited for future CO2 geostationery and imager satellites.
Kelvin H. Bates, Mathew J. Evans, Barron H. Henderson, and Daniel J. Jacob
Geosci. Model Dev., 17, 1511–1524, https://doi.org/10.5194/gmd-17-1511-2024, https://doi.org/10.5194/gmd-17-1511-2024, 2024
Short summary
Short summary
Accurate representation of rates and products of chemical reactions in atmospheric models is crucial for simulating concentrations of pollutants and climate forcers. We update the widely used GEOS-Chem atmospheric chemistry model with reaction parameters from recent compilations of experimental data and demonstrate the implications for key atmospheric chemical species. The updates decrease tropospheric CO mixing ratios and increase stratospheric nitrogen oxide mixing ratios, among other changes.
François Roberge, Alejandro Di Luca, René Laprise, Philippe Lucas-Picher, and Julie Thériault
Geosci. Model Dev., 17, 1497–1510, https://doi.org/10.5194/gmd-17-1497-2024, https://doi.org/10.5194/gmd-17-1497-2024, 2024
Short summary
Short summary
Our study addresses a challenge in dynamical downscaling using regional climate models, focusing on the lack of small-scale features near the boundaries. We introduce a method to identify this “spatial spin-up” in precipitation simulations. Results show spin-up distances up to 300 km, varying by season and driving variable. Double nesting with comprehensive variables (e.g. microphysical variables) offers advantages. Findings will help optimize simulations for better climate projections.
Eloisa Raluy-López, Juan Pedro Montávez, and Pedro Jiménez-Guerrero
Geosci. Model Dev., 17, 1469–1495, https://doi.org/10.5194/gmd-17-1469-2024, https://doi.org/10.5194/gmd-17-1469-2024, 2024
Short summary
Short summary
Atmospheric rivers (ARs) represent a significant source of water but are also related to extreme precipitation events. Here, we present a new regional-scale AR identification algorithm and apply it to three simulations that include aerosol interactions at different levels. The results show that aerosols modify the intensity and trajectory of ARs and redistribute the AR-related precipitation. Thus, the correct inclusion of aerosol effects is important in the simulation of AR behavior.
Sofía Gómez Maqueo Anaya, Dietrich Althausen, Matthias Faust, Holger Baars, Bernd Heinold, Julian Hofer, Ina Tegen, Albert Ansmann, Ronny Engelmann, Annett Skupin, Birgit Heese, and Kerstin Schepanski
Geosci. Model Dev., 17, 1271–1295, https://doi.org/10.5194/gmd-17-1271-2024, https://doi.org/10.5194/gmd-17-1271-2024, 2024
Short summary
Short summary
Mineral dust aerosol particles vary greatly in their composition depending on source region, which leads to different physicochemical properties. Most atmosphere–aerosol models consider mineral dust aerosols to be compositionally homogeneous, which ultimately increases model uncertainty. Here, we present an approach to explicitly consider the heterogeneity of the mineralogical composition for simulations of the Saharan atmospheric dust cycle with regard to dust transport towards the Atlantic.
Alexandros Milousis, Alexandra P. Tsimpidi, Holger Tost, Spyros N. Pandis, Athanasios Nenes, Astrid Kiendler-Scharr, and Vlassis A. Karydis
Geosci. Model Dev., 17, 1111–1131, https://doi.org/10.5194/gmd-17-1111-2024, https://doi.org/10.5194/gmd-17-1111-2024, 2024
Short summary
Short summary
This study aims to evaluate the newly developed ISORROPIA-lite aerosol thermodynamic module within the EMAC model and explore discrepancies in global atmospheric simulations of aerosol composition and acidity by utilizing different aerosol phase states. Even though local differences were found in regions where the RH ranged from 20 % to 60 %, on a global scale the results are similar. Therefore, ISORROPIA-lite can be a reliable and computationally effective alternative to ISORROPIA II in EMAC.
Marie-Adèle Magnaldo, Quentin Libois, Sébastien Riette, and Christine Lac
Geosci. Model Dev., 17, 1091–1109, https://doi.org/10.5194/gmd-17-1091-2024, https://doi.org/10.5194/gmd-17-1091-2024, 2024
Short summary
Short summary
With the worldwide development of the solar energy sector, the need for reliable solar radiation forecasts has significantly increased. However, meteorological models that predict, among others things, solar radiation have errors. Therefore, we wanted to know in which situtaions these errors are most significant. We found that errors mostly occur in cloudy situations, and different errors were highlighted depending on the cloud altitude. Several potential sources of errors were identified.
Dongqi Lin, Jiawei Zhang, Basit Khan, Marwan Katurji, and Laura E. Revell
Geosci. Model Dev., 17, 815–845, https://doi.org/10.5194/gmd-17-815-2024, https://doi.org/10.5194/gmd-17-815-2024, 2024
Short summary
Short summary
GEO4PALM is an open-source tool to generate static input for the Parallelized Large-Eddy Simulation (PALM) model system. Geospatial static input is essential for realistic PALM simulations. However, existing tools fail to generate PALM's geospatial static input for most regions. GEO4PALM is compatible with diverse geospatial data sources and provides access to free data sets. In addition, this paper presents two application examples, which show successful PALM simulations using GEO4PALM.
Piotr Zmijewski, Piotr Dziekan, and Hanna Pawlowska
Geosci. Model Dev., 17, 759–780, https://doi.org/10.5194/gmd-17-759-2024, https://doi.org/10.5194/gmd-17-759-2024, 2024
Short summary
Short summary
In computer simulations of clouds it is necessary to model the myriad of droplets that constitute a cloud. A popular method for this is to use so-called super-droplets (SDs), each representing many real droplets. It has remained a challenge to model collisions of SDs. We study how precipitation in a cumulus cloud depends on the number of SDs. Surprisingly, we do not find convergence in mean precipitation even for numbers of SDs much larger than typically used in simulations.
Roya Ghahreman, Wanmin Gong, Paul A. Makar, Alexandru Lupu, Amanda Cole, Kulbir Banwait, Colin Lee, and Ayodeji Akingunola
Geosci. Model Dev., 17, 685–707, https://doi.org/10.5194/gmd-17-685-2024, https://doi.org/10.5194/gmd-17-685-2024, 2024
Short summary
Short summary
The article explores the impact of different representations of below-cloud scavenging on model biases. A new scavenging scheme and precipitation-phase partitioning improve the model's performance, with better SO42- scavenging and wet deposition of NO3- and NH4+.
Daisuke Goto, Tatsuya Seiki, Kentaroh Suzuki, Hisashi Yashiro, and Toshihiko Takemura
Geosci. Model Dev., 17, 651–684, https://doi.org/10.5194/gmd-17-651-2024, https://doi.org/10.5194/gmd-17-651-2024, 2024
Short summary
Short summary
Global climate models with coarse grid sizes include uncertainties about the processes in aerosol–cloud–precipitation interactions. To reduce these uncertainties, here we performed numerical simulations using a new version of our global aerosol transport model with a finer grid size over a longer period than in our previous study. As a result, we found that the cloud microphysics module influences the aerosol distributions through both aerosol wet deposition and aerosol–cloud interactions.
Alexander de Meij, Cornelis Cuvelier, Philippe Thunis, Enrico Pisoni, and Bertrand Bessagnet
Geosci. Model Dev., 17, 587–606, https://doi.org/10.5194/gmd-17-587-2024, https://doi.org/10.5194/gmd-17-587-2024, 2024
Short summary
Short summary
In our study the robustness of the model responses to emission reductions in the EU is assessed when the emission data are changed. Our findings are particularly important to better understand the uncertainties associated to the emission inventories and how these uncertainties impact the level of accuracy of the resulting air quality modelling, which is a key for designing air quality plans. Also crucial is the choice of indicator to avoid misleading interpretations of the results.
Haiqin Li, Georg A. Grell, Ravan Ahmadov, Li Zhang, Shan Sun, Jordan Schnell, and Ning Wang
Geosci. Model Dev., 17, 607–619, https://doi.org/10.5194/gmd-17-607-2024, https://doi.org/10.5194/gmd-17-607-2024, 2024
Short summary
Short summary
We developed a simple and realistic method to provide aerosol emissions for aerosol-aware microphysics in a numerical weather forecast model. The cloud-radiation differences between the experimental (EXP) and control (CTL) experiments responded to the aerosol differences. The strong positive precipitation biases over North America and Europe from the CTL run were significantly reduced in the EXP run. This study shows that a realistic representation of aerosol emissions should be considered.
Nathan Patrick Arnold
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-245, https://doi.org/10.5194/gmd-2023-245, 2024
Revised manuscript accepted for GMD
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.
Giancarlo Ciarelli, Sara Tahvonen, Arineh Cholakian, Manuel Bettineschi, Bruno Vitali, Tuukka Petäjä, and Federico Bianchi
Geosci. Model Dev., 17, 545–565, https://doi.org/10.5194/gmd-17-545-2024, https://doi.org/10.5194/gmd-17-545-2024, 2024
Short summary
Short summary
The terrestrial ecosystem releases large quantities of biogenic gases in the Earth's Atmosphere. These gases can effectively be converted into so-called biogenic aerosol particles and, eventually, affect the Earth's climate. Climate prediction varies greatly depending on how these processes are represented in model simulations. In this study, we present a detailed model evaluation analysis aimed at understanding the main source of uncertainty in predicting the formation of biogenic aerosols.
Jiachen Liu, Eric Chen, and Shannon L. Capps
Geosci. Model Dev., 17, 567–585, https://doi.org/10.5194/gmd-17-567-2024, https://doi.org/10.5194/gmd-17-567-2024, 2024
Short summary
Short summary
Air pollution harms human life and ecosystems, but its sources are complex. Scientists and policy makers use air pollution models to advance knowledge and inform control strategies. We implemented a recently developed numeral system to relate any set of model inputs, like pollutant emissions from a given activity, to all model outputs, like concentrations of pollutants harming human health. This approach will be straightforward to update when scientists discover new processes in the atmosphere.
Irene Constantina Dedoussi, Daven K. Henze, Sebastian D. Eastham, Raymond L. Speth, and Steven R. H. Barrett
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-233, https://doi.org/10.5194/gmd-2023-233, 2024
Revised manuscript accepted for GMD
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.
Gerrit Kuhlmann, Erik F. M. Koene, Sandro Meier, Diego Santaren, Grégoire Broquet, Frédéric Chevallier, Janne Hakkarainen, Janne Nurmela, Laia Amorós, Johanna Tamminen, and Dominik Brunner
EGUsphere, https://doi.org/10.5194/egusphere-2023-2936, https://doi.org/10.5194/egusphere-2023-2936, 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.
Kun Zheng, Qiya Tan, Huihua Ruan, Jinbiao Zhang, Cong Luo, Siyu Tang, Yunlei Yi, Yugang Tian, and Jianmei Cheng
Geosci. Model Dev., 17, 399–413, https://doi.org/10.5194/gmd-17-399-2024, https://doi.org/10.5194/gmd-17-399-2024, 2024
Short summary
Short summary
Radar echo extrapolation is the common method in precipitation nowcasting. Deep learning has potential in extrapolation. However, the existing models have low prediction accuracy for heavy rainfall. In this study, the prediction accuracy is improved by suppressing the blurring effect of rain distribution and reducing the negative bias. The results show that our model has better performance, which is useful for urban operation and flood prevention.
Li Pan, Partha S. Bhattacharjee, Li Zhang, Raffaele Montuoro, Barry Baker, Jeff McQueen, Georg A. Grell, Stuart A. McKeen, Shobha Kondragunta, Xiaoyang Zhang, Gregory J. Frost, Fanglin Yang, and Ivanka Stajner
Geosci. Model Dev., 17, 431–447, https://doi.org/10.5194/gmd-17-431-2024, https://doi.org/10.5194/gmd-17-431-2024, 2024
Short summary
Short summary
A GEFS-Aerosols simulation was conducted from 1 September 2019 to 30 September 2020 to evaluate the model performance of GEFS-Aerosols. The purpose of this study was to understand how aerosol chemical and physical processes affect ambient aerosol concentrations by placing aerosol wet deposition, dry deposition, reactions, gravitational deposition, and emissions into the aerosol mass balance equation.
Sean Raffuse, Susan O'Neill, and Rebecca Schmidt
Geosci. Model Dev., 17, 381–397, https://doi.org/10.5194/gmd-17-381-2024, https://doi.org/10.5194/gmd-17-381-2024, 2024
Short summary
Short summary
Large wildfires are increasing throughout the western United States, and wildfire smoke is hazardous to public health. We developed a suite of tools called rapidfire for estimating particle pollution during wildfires using routinely available data sets. rapidfire uses official air monitoring, satellite data, meteorology, smoke modeling, and low-cost sensors. Estimates from rapidfire compare well with ground monitors and are being used in public health studies across California.
Manuel F. Schmid, Marco G. Giometto, Gregory A. Lawrence, and Marc B. Parlange
Geosci. Model Dev., 17, 321–333, https://doi.org/10.5194/gmd-17-321-2024, https://doi.org/10.5194/gmd-17-321-2024, 2024
Short summary
Short summary
Turbulence-resolving flow models have strict performance requirements, as simulations often run for weeks using hundreds of processes. Many flow scenarios also require the flexibility to modify physical and numerical models for problem-specific requirements. With a new code written in Julia we hope to make such adaptations easier without compromising on performance. In this paper we discuss the modeling approach and present validation and performance results.
Yafang Guo, Chayan Roychoudhury, Mohammad Amin Mirrezaei, Rajesh Kumar, Armin Sorooshian, and Avelino F. Arellano
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-234, https://doi.org/10.5194/gmd-2023-234, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
This research focuses on surface ozone (O3) pollution in Arizona, a historically air quality-challenged arid/semi-arid region in the US. The unique characteristics of semi-arid/arid regions, e.g., intense heat, minimal moisture, 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.
Marie-Noëlle Bouin, Cindy Lebeaupin Brossier, Sylvie Malardel, Aurore Voldoire, and César Sauvage
Geosci. Model Dev., 17, 117–141, https://doi.org/10.5194/gmd-17-117-2024, https://doi.org/10.5194/gmd-17-117-2024, 2024
Short summary
Short summary
In numerical models, the turbulent exchanges of heat and momentum at the air–sea interface are not represented explicitly but with parameterisations depending on the surface parameters. A new parameterisation of turbulent fluxes (WASP) has been implemented in the surface model SURFEX v8.1 and validated on four case studies. It combines a close fit to observations including cyclonic winds, a dependency on the wave growth rate, and the possibility of being used in atmosphere–wave coupled models.
Michal Belda, Nina Benešová, Jaroslav Resler, Peter Huszár, Ondřej Vlček, Pavel Krč, Jan Karlický, Pavel Juruš, and Kryštof Eben
EGUsphere, https://doi.org/10.5194/egusphere-2023-2740, https://doi.org/10.5194/egusphere-2023-2740, 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 emission processing from continental to street scale.
Cited articles
Alexander, P. J., Bechtel, B., Chow, W. T., Fealy, R., and Mills, G.:
Linking urban climate classification with an urban energy and water budget model: Multi–site and multi–seasonal evaluation, Urban Climate, 17, 196–215, https://doi.org/10.1016/j.uclim.2016.08.003, 2016. a
Alvarez, R. and Weilenmann, M.:
Effect of low ambient temperature on fuel consumption and pollutant and CO2 emissions of hybrid electric vehicles in real-world conditions, Fuel, 97, 119–124, https://doi.org/10.1016/j.fuel.2012.01.022, 2012. a
Ao, X., Grimmond, C., Liu, D., Han, Z., Hu, P., Wang, Y., Zhen, X., and Tan, J.:
Radiation fluxes in a business district of Shanghai, China, J. Appl. Meteorol. Clim., 55, 2451–2468, https://doi.org/10.1175/jamc-d-16-0082.1, 2016. a, b
Ao, X., Grimmond, C., Ward, H., Gabey, A., Tan, J., Yang, X.-Q., Liu, D., Zhi, X., Liu, H., and Zhang, N.:
Evaluation of the Surface Urban Energy and Water balance Scheme (SUEWS) at a dense urban site in Shanghai: Sensitivity to anthropogenic heat and irrigation, J. Hydrometeorol., 19, 1983–2005, https://doi.org/10.1175/jhm-d-18-0057.1, 2018. a, b, c
Awal, M., Ohta, T., Matsumoto, K., Toba, T., Daikoku, K., Hattori, S., Hiyama, T., and Park, H.:
Comparing the carbon sequestration capacity of temperate deciduous forests between urban and rural landscapes in central Japan, Urban For. Urban Gree., 9, 261–270, https://doi.org/10.1016/j.ufug.2010.01.007, 2010. a
Best, M. and Grimmond, C.:
Key conclusions of the first international urban land surface model comparison project, B. Am. Meteorol. Soc., 96, 805–819, https://doi.org/10.1175/bams-d-14-00122.1, 2015. a
Best, M. and Grimmond, C.:
Modeling the partitioning of turbulent fluxes at urban sites with varying vegetation cover, J. Hydrometeorol., 17, 2537–2553, https://doi.org/10.1175/jhm-d-15-0126.1, 2016. a
Björkegren, A. and Grimmond, C.:
Net carbon dioxide emissions from central London, Urban Climate, 23, 131–158, https://doi.org/10.1016/j.uclim.2016.10.002, 2018. a, b
Boegh, E., Soegaard, H., Broge, N., Hasager, C., Jensen, N., Schelde, K., and Thomsen, A.:
Airborne multispectral data for quantifying leaf area index, nitrogen concentration, and photosynthetic efficiency in agriculture, Remote Sens. Environ., 81, 179–193, https://doi.org/10.1016/s0034-4257(01)00342-x, 2002. a
Chen, F., Kusaka, H., Bornstein, R., Ching, J., Grimmond, C., Grossman-Clarke, S., Loridan, T., Manning, K. W., Martilli, A., and Miao, S.:
The integrated WRF/urban modelling system: development, evaluation, and applications to urban environmental problems, Int. J. Climatol., 31, 273–288, https://doi.org/10.1002/joc.2158, 2011. a
Chen, S., Chen, Z., and Zhang, Z.:
The canopy stomatal conductance characteristics of Pinus tabulaeformis and Acer truncatum and their environmental responses in the mountain area of Beijing, Chinese Journal of Plant Ecology, 45, 1329–1340, https://doi.org/10.17521/cjpe.2021.0198, 2021 (in Chinese). a
Cheng, X., Liu, X., Liu, Y., and Hu, F.:
Characteristics of CO2 concentration and flux in the Beijing urban area, J. Geophys. Res.-Atmos., 123, 1785–1801, https://doi.org/10.1002/2017jd027409, 2018. a, b, c
Christen, A., Coops, N., Crawford, B., Kellett, R., Liss, K., Olchovski, I., Tooke, T., Van Der Laan, M., and Voogt, J.:
Validation of modeled carbon-dioxide emissions from an urban neighborhood with direct eddy-covariance measurements, Atmos. Environ., 45, 6057–6069, https://doi.org/10.1016/j.atmosenv.2011.07.040, 2011. a, b, c, d
Chu, H., Luo, X., Ouyang, Z., Chan, W. S., Dengel, S., Biraud, S. C., Torn, M. S., Metzger, S., Kumar, J., and Arain, M. A.:
Representativeness of Eddy-Covariance flux footprints for areas surrounding AmeriFlux sites, Agr. Forest Meteorol., 301, 108350, https://doi.org/10.1016/j.agrformet.2021.108350, 2021. a
Crawford, B. and Christen, A.:
Spatial source attribution of measured urban eddy covariance CO2 fluxes, Theor. Appl. Climatol., 119, 733–755, https://doi.org/10.1007/s00704-014-1124-0, 2015. a
Cucchi, M., Weedon, G. P., Amici, A., Bellouin, N., Lange, S., Müller Schmied, H., Hersbach, H., and Buontempo, C.:
Near surface meteorological variables from 1979 to 2019 derived from bias-corrected reanalysis, Version 2.0, Copernicus Climate Change Service (C3S) Climate Data Store (CDS) [data set], https://doi.org/10.24381/cds.20d54e34 (last access: 11 May 2022), 2021. a, b
Cui, Y., Zhang, W., Wang, C., Streets, D. G., Xu, Y., Du, M., and Lin, J.:
Spatiotemporal dynamics of CO2 emissions from central heating supply in the North China Plain over 2012–2016 due to natural gas usage, Appl. Energ., 241, 245–256, https://doi.org/10.1016/j.apenergy.2019.03.060, 2019. a, b, c
Demuzere, M., Harshan, S., Järvi, L., Roth, M., Grimmond, C., Masson, V., Oleson, K., Velasco, E., and Wouters, H.:
Impact of urban canopy models and external parameters on the modelled urban energy balance in a tropical city, Q. J. Roy. Meteor. Soc., 143, 1581–1596, https://doi.org/10.1002/qj.3028, 2017. a
Dou, J., Grimmond, S., Cheng, Z., Miao, S., Feng, D., and Liao, M.:
Summertime surface energy balance fluxes at two Beijing sites, Int. J. Climatol., 39, 2793–2810, https://doi.org/10.1002/joc.5989, 2019. a
Du, M., Wang, X., Peng, C., Shan, Y., Chen, H., Wang, M., and Zhu, Q.:
Quantification and scenario analysis of CO2 emissions from the central heating supply system in China from 2006 to 2025, Appl. Energ., 225, 869–875, https://doi.org/10.1016/j.apenergy.2018.05.064, 2018. a
Falge, E., Baldocchi, D., Olson, R., Anthoni, P., Aubinet, M., Bernhofer, C., Burba, G., Ceulemans, R., Clement, R., and Dolman, H.:
Gap filling strategies for defensible annual sums of net ecosystem exchange, Agr. Forest Meteorol., 107, 43–69, https://doi.org/10.1016/j.agrformet.2006.03.003, 2001. a
Fiorella, R. P., Bares, R., Lin, J. C., Ehleringer, J. R., and Bowen, G. J.:
Detection and variability of combustion-derived vapor in an urban basin, Atmos. Chem. Phys., 18, 8529–8547, https://doi.org/10.5194/acp-18-8529-2018, 2018. a
Foken, T. and Wichura, B.:
Tools for quality assessment of surface-based flux measurements, Agr. Forest Meteorol., 78, 83–105, https://doi.org/10.1016/0168-1923(95)02248-1, 1996. a
Fontaras, G., Zacharof, N.-G., and Ciuffo, B.:
Fuel consumption and CO2 emissions from passenger cars in Europe–Laboratory versus real-world emissions, Prog. Energ. Combust., 60, 97–131, https://doi.org/10.1016/j.pecs.2016.12.004, 2017. a
Friedl, M. and Sulla-Menashe, D.:
MCD12Q1 MODIS/Terra+Aqua Land Cover Type Yearly L3 Global 500 m SIN Grid V006, USGS [data set], https://doi.org/10.5067/MODIS/MCD12Q1.006 (last access: 19 April 2022), 2019. a
Gong, P., Chen, B., Li, X., Liu, H., Wang, J., Bai, Y., Chen, J., Chen, X., Fang, L., and Feng, S.:
Mapping essential urban land use categories in China (EULUC-China): Preliminary results for 2018, Sci. Bull., 65, 182–187, https://doi.org/10.1016/j.scib.2019.12.007, 2020. a
Grimmond, C. and Oke, T.:
Heat storage in urban areas: Local-scale observations and evaluation of a simple model, J. Appl. Meteorol., 38, 922–940, https://doi.org/10.1175/1520-0450(1999)038<0922:HSIUAL>2.0.CO;2, 1999. a
Grimmond, C. and Oke, T.:
Progress in measuring and observing the urban atmosphere, Theor. Appl. Climatol., 84, 3–22, https://doi.org/10.1007/s00704-005-0140-5, 2006. a
Grimmond, C. S. B., Blackett, M., Best, M., Barlow, J., Baik, J., Belcher, S., Bohnenstengel, S., Calmet, I., Chen, F., and Dandou, A.:
The International Urban Energy Balance Models Comparison Project: First Results from Phase 1, J. Appl. Meteorol. Clim., 49, 1268–1292, https://doi.org/10.1175/2010jamc2354.1, 2010. a
Hansen, N., Auger, A., Ros, R., Finck, S., and Pošík, P.:
Comparing results of 31 algorithms from the black-box optimization benchmarking BBOB-2009, in: Proceedings of the 12th annual conference companion on Genetic and evolutionary computation, Association for Computing Machinery, New York, NY, USA, 1689–1696, https://doi.org/10.1145/1830761.1830790, 2010. a
Havu, M., Lee, H. S., Soininen, J., and Järvi, L.:
Spatial variability of biogenic CO2 flux in Helsinki in 2020 (Version 1), Zenodo [data set], https://doi.org/10.5281/zenodo.7198140, 2022b. a
Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A., Muñoz-Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D., Simmons, A., Soci, C., Abdalla, S., Abellan, X., Balsamo, G., Bechtold, P., Biavati, G., Bidlot, J., Bonavita, M., De Chiara, G., Dahlgren, P., Dee, D., Diamantakis, M., Dragani, R., Flemming, J., Forbes, R., Fuentes, M., Geer, A., Haimberger, L., Healy, S., Hogan, R. J., Hólm, E., Janisková, M., Keeley, S., Laloyaux, P., Lopez, P., Lupu, C., Radnoti, G., de Rosnay, P., Rozum, I., Vamborg, F., Villaume, S., and Thépaut, J.-N.: The ERA5 global reanalysis, Q. J. Roy. Meteor. Soc., 146, 1999–2049, https://doi.org/10.1002/qj.3803, 2020. a
Huete, A.:
A comparison of vegetation indices over a global set of TM images for EOS-MODIS, Remote Sens. Environ., 59, 440–451, https://doi.org/10.1016/s0034-4257(96)00112-5, 1997. a
Järvi, L., Grimmond, C. S. B., Taka, M., Nordbo, A., Setälä, H., and Strachan, I. B.:
Development of the Surface Urban Energy and Water Balance Scheme (SUEWS) for cold climate cities, Geosci. Model Dev., 7, 1691–1711, https://doi.org/10.5194/gmd-7-1691-2014, 2014. a, b, c, d
Järvi, L., Grimmond, C., McFadden, J., Christen, A., Strachan, I., Taka, M., Warsta, L., and Heimann, M.:
Warming effects on the urban hydrology in cold climate regions, Sci. Rep.-UK, 7, 1–8, https://doi.org/10.1038/s41598-017-05733-y, 2017. a
Järvi, L., Havu, M., Ward, H. C., Bellucco, V., McFadden, J. P., Toivonen, T., Heikinheimo, V., Kolari, P., Riikonen, A., and Grimmond, C. S. B.:
Spatial modeling of local-scale biogenic and anthropogenic carbon dioxide emissions in Helsinki, J. Geophys. Res.-Atmos., 124, 8363–8384, https://doi.org/10.1029/2018jd029576, 2019. a, b, c, d, e, f, g, h, i, j, k, l, m, n, o
Jiang, X., Zhang, C., Gao, H., and Miao, S.:
Impacts of urban albedo change on urban heat island in Beijing-A case study, Acta Meteorol. Sin., 65, 301–307, https://doi.org/10.1002/jrs.1570, 2007 (in Chinese). a
Johansson, E. and Emmanuel, R.:
The influence of urban design on outdoor thermal comfort in the hot, humid city of Colombo, Sri Lanka, Int. J. Biometeorol., 51, 119–133, https://doi.org/10.1007/s00484-006-0047-6, 2006. a
Karsisto, P., Fortelius, C., Demuzere, M., Grimmond, C. S. B., Oleson, K., Kouznetsov, R., Masson, V., and Järvi, L.:
Seasonal surface urban energy balance and wintertime stability simulated using three land-surface models in the high-latitude city Helsinki, Q. J. Roy. Meteor. Soc., 142, 401–417, https://doi.org/10.1002/qj.2659, 2016. a
Kokkonen, T., Grimmond, C. S. B., Räty, O., Ward, H., Christen, A., Oke, T., Kotthaus, S., and Järvi, L.:
Sensitivity of Surface Urban Energy and Water Balance Scheme (SUEWS) to downscaling of reanalysis forcing data, Urban Climate, 23, 36–52, https://doi.org/10.1016/j.uclim.2017.05.001, 2018. a
Konopka, J., Heusinger, J., and Weber, S.:
Extensive Urban Green Roof Shows Consistent Annual Net Uptake of Carbon as Documented by 5 Years of Eddy-Covariance Flux Measurements, J. Geophys. Res.-Biogeo., 126, e2020JG005879, https://doi.org/10.1029/2020jg005879, 2021. a
Laine, A., Riutta, T., Juutinen, S., Väliranta, M., and Tuittila, E.-S.:
Acknowledging the spatial heterogeneity in modelling/reconstructing carbon dioxide exchange in a northern aapa mire, Ecol. Model., 220, 2646–2655, https://doi.org/10.1016/j.ecolmodel.2009.06.047, 2009. a
Liu, S., Pang, H., Zhang, N., Xing, M., Wu, S., and Hou, S.:
Temporal variations of the contribution of combustion-derived water vapor to urban humidity during winter in Xi'an, China, Sci. Total Environ., 830, 154711, https://doi.org/10.2139/ssrn.3994594, 2022. a
Liu, Y., Liu, H., Du, Q., and Xu, L.:
Multi-level CO2 fluxes over Beijing megacity with the eddy covariance method, Atmospheric and Oceanic Science Letters, 14, 100079, https://doi.org/10.1016/j.aosl.2021.100079, 2021. a
Loridan, T., Grimmond, C., Offerle, B. D., Young, D. T., Smith, T. E., Järvi, L., and Lindberg, F.:
Local-scale urban meteorological parameterization scheme (LUMPS): longwave radiation parameterization and seasonality-related developments, J. Appl. Meteorol. Clim., 50, 185–202, https://doi.org/10.1175/2010jamc2474.1, 2011. a, b
Lu, P., Yu, Q., Liu, J., and Lee, X.:
Advance of tree-flowering dates in response to urban climate change, Agr. Forest Meteorol., 138, 120–131, https://doi.org/10.1016/j.agrformet.2006.04.002, 2006. a
Luo, Z., Sun, O. J., Ge, Q., Xu, W., and Zheng, J.:
Phenological responses of plants to climate change in an urban environment, Ecol. Res., 22, 507–514, https://doi.org/10.1007/s11284-006-0044-6, 2007. a
Ma, J.:
The study on urban forest structure and eco-service in the Sixth Ring Road of Beijing, Thesis, Chinese Academy of Forestry, Beijing, https://doi.org/10.27625/d.cnki.gzlky.2019.000083, 2019. a
Ma, J., Jia, B., Zhang, W., Liu, X., Li, X., and Liu, J.:
The characteristics of urban forest structure within the Sixth Ring Road of Beijing, Chinese Journal of Ecology, 38, 2318–2325, https://doi.org/10.13292/j.1000-4890.201908.035, 2019. a
Marcotullio, P. J., Sarzynski, A., Albrecht, J., Schulz, N., and Garcia, J.:
The geography of global urban greenhouse gas emissions: An exploratory analysis, Climatic Change, 121, 621–634, https://doi.org/10.1007/s10584-013-0977-z, 2013. a
Masek, J., Vermote, E., Saleous, N., Wolfe, R., Hall, F., Huemmrich, K., Gao, F., Kutler, J., and Lim, T.-K.:
A Landsat Surface Reflectance Dataset for North America, 1990–2000, IEEE Geosci. Remote S., 3, 68–72, https://doi.org/10.1109/lgrs.2005.857030, 2006. a, b
Masson, V., Le Moigne, P., Martin, E., Faroux, S., Alias, A., Alkama, R., Belamari, S., Barbu, A., Boone, A., Bouyssel, F., Brousseau, P., Brun, E., Calvet, J.-C., Carrer, D., Decharme, B., Delire, C., Donier, S., Essaouini, K., Gibelin, A.-L., Giordani, H., Habets, F., Jidane, M., Kerdraon, G., Kourzeneva, E., Lafaysse, M., Lafont, S., Lebeaupin Brossier, C., Lemonsu, A., Mahfouf, J.-F., Marguinaud, P., Mokhtari, M., Morin, S., Pigeon, G., Salgado, R., Seity, Y., Taillefer, F., Tanguy, G., Tulet, P., Vincendon, B., Vionnet, V., and Voldoire, A.:
The SURFEXv7.2 land and ocean surface platform for coupled or offline simulation of earth surface variables and fluxes, Geosci. Model Dev., 6, 929–960, https://doi.org/10.5194/gmd-6-929-2013, 2013. a
Miao, S., Dou, J., Chen, F., Li, J., and Li, A.:
Analysis of observations on the urban surface energy balance in Beijing, Science China Earth Sciences, 55, 1881–1890, https://doi.org/10.1007/s11430-012-4411-6, 2012. a
Moriwaki, R. and Kanda, M.:
Seasonal and diurnal fluxes of radiation, heat, water vapor, and carbon dioxide over a suburban area, J. Appl. Meteorol., 43, 1700–1710, https://doi.org/10.1175/jam2153.1, 2004. a, b, c
Nordbo, A., Karsisto, P., Matikainen, L., Wood, C. R., and Järvi, L.:
Urban surface cover determined with airborne lidar at 2 m resolution–implications for surface energy balance modelling, Urban Climate, 13, 52–72, https://doi.org/10.1016/j.uclim.2015.05.004, 2015. a
Offerle, B., Grimmond, C., and Oke, T. R.:
Parameterization of net all-wave radiation for urban areas, J. Appl. Meteorol. Clim., 42, 1157–1173, https://doi.org/10.1175/1520-0450(2003)042<1157:ponarf>2.0.co;2, 2003. a, b
Oke, T.:
The Heat Island of the Urban Boundary Layer: Characteristics, Causes and Effects, Springer, Dordrecht, https://doi.org/10.1007/978-94-017-3686-2_5, pp. 81–107, 1995. a
Omidvar, H., Sun, T., Grimmond, S., Bilesbach, D., Black, A., Chen, J., Duan, Z., Gao, Z., Iwata, H., and McFadden, J. P.:
Surface Urban Energy and Water Balance Scheme (v2020a) in vegetated areas: parameter derivation and performance evaluation using FLUXNET2015 dataset, Geosci. Model Dev., 15, 3041–3078, https://doi.org/10.5194/gmd-15-3041-2022, 2022. a, b, c, d
Pataki, D. E., Carreiro, M. M., Cherrier, J., Grulke, N. E., Jennings, V., Pincetl, S., Pouyat, R. V., Whitlow, T. H., and Zipperer, W. C.:
Coupling biogeochemical cycles in urban environments: ecosystem services, green solutions, and misconceptions, Front. Ecol. Environ., 9, 27–36, https://doi.org/10.1890/090220, 2011. a
Peters, E. B. and McFadden, J. P.:
Continuous measurements of net CO2 exchange by vegetation and soils in a suburban landscape, J. Geophys. Res.-Biogeo., 117, G03005, https://doi.org/10.1029/2011jg001933, 2012. a
Prairie, Y. T. and Duarte, C. M.:
Direct and indirect metabolic CO2 release by humanity, Biogeosciences, 4, 215–217, https://doi.org/10.5194/bg-4-215-2007, 2007. a
Qian, Y., Chakraborty, T., Li, J., Li, D., He, C., Sarangi, C., Chen, F., Yang, X., and Leung, L. R.:
Urbanization Impact on Regional Climate and Extreme Weather: Current Understanding, Uncertainties, and Future Research Directions, Adv. Atmos. Sci., 39, 819–860, https://doi.org/10.1007/s00376-021-1371-9, 2022. a
Rebmann, C., Göckede, M., Foken, T., Aubinet, M., Aurela, M., Berbigier, P., Bernhofer, C., Buchmann, N., Carrara, A., and Cescatti, A.:
Quality analysis applied on eddy covariance measurements at complex forest sites using footprint modelling, Theor. Appl. Climatol., 80, 121–141, https://doi.org/10.1007/s00704-004-0095-y, 2005. a
Salmon, O. E., Shepson, P. B., Ren, X., Marquardt Collow, A. B., Miller, M. A., Carlton, A. G., Cambaliza, M. O., Heimburger, A., Morgan, K. L., and Fuentes, J. D.:
Urban emissions of water vapor in winter, J. Geophys. Res.-Atmos., 122, 9467–9484, https://doi.org/10.1002/2016jd026074, 2017. a
Sarangi, C., Tripathi, S., Qian, Y., Kumar, S., and Ruby Leung, L.:
Aerosol and urban land use effect on rainfall around cities in Indo–Gangetic Basin from observations and cloud resolving model simulations, J. Geophys. Res.-Atmos., 123, 3645–3667, https://doi.org/10.1002/2017jd028004, 2018. a
Song, Y., Li, F., Wang, X., Xu, C., Zhang, J., Liu, X., and Zhang, H.:
The effects of urban impervious surfaces on eco-physiological characteristics of Ginkgo biloba: A case study from Beijing, China, Urban For. Urban Gree., 14, 1102–1109, https://doi.org/10.1016/j.ufug.2015.10.008, 2015. a
Stagakis, S., Feigenwinter, C., Vogt, R., and Kalberer, M.:
A high-resolution monitoring approach of urban CO2 fluxes. Part 1 – bottom-up model development, Sci. Total Environ., 160216, https://doi.org/10.2139/ssrn.4172744, 2022. a, b
Sun, T. and Grimmond, S.:
A Python-enhanced urban land surface model SuPy (SUEWS in Python, v2019.2): development, deployment and demonstration, Geosci. Model Dev., 12, 2781–2795, https://doi.org/10.5194/gmd-12-2781-2019, 2019. a
Tan, J., Zheng, Y., Tang, X., Guo, C., Li, L., Song, G., Zhen, X., Yuan, D., Kalkstein, A. J., and Li, F.:
The urban heat island and its impact on heat waves and human health in Shanghai, Int. J. Biometeorol., 54, 75–84, https://doi.org/10.1007/s00484-009-0256-x, 2010. a
United Nations Department of Economic and Social Affairs:
World Urbanization Prospects: The 2018 Revision, United Nations, https://doi.org/10.18356/b9e995fe-en, 2019. a
Velasco, E. and Roth, M.:
Cities as net sources of CO2: Review of atmospheric CO2 exchange in urban environments measured by eddy covariance technique, Geography Compass, 4, 1238–1259, https://doi.org/10.1111/j.1749-8198.2010.00384.x, 2010. a
Wang, L., Fan, S., Hu, F., Miao, S., Yang, A., Li, Y., Liu, J., Liu, C., Chen, S., Ho, H. C., Duan, Z., Gao, Z., and Yang, Y.:
Vertical gradient variations in radiation budget and heat fluxes in the urban boundary layer: A comparison study between polluted and clean air episodes in Beijing during winter, J. Geophys. Res.-Atmos., 125, e2020JD032478, https://doi.org/10.1029/2020jd032478, 2020. a
Wang, Y., Li, G., Di, N., Clothier, B., Duan, J., Li, D., Jia, L., Xi, B., and Ma, F.:
Leaf phenology variation within the canopy and its relationship with the transpiration of Populus tomentosa under plantation conditions, Forests, 9, 603, https://doi.org/10.3390/f9100603, 2018. a
Wang, Y., Chang, Q., and Li, X.:
Promoting sustainable carbon sequestration of plants in urban greenspace by planting design: A case study in parks of Beijing, Urban For. Urban Gree., 64, 127291, https://doi.org/10.1016/j.ufug.2021.127291, 2021. a
Ward, H. C., Evans, J. G., and Grimmond, C. S. B.:
Multi-season eddy covariance observations of energy, water and carbon fluxes over a suburban area in Swindon, UK, Atmos. Chem. Phys., 13, 4645–4666, https://doi.org/10.5194/acp-13-4645-2013, 2013. a
Watts, N., Adger, W. N., Agnolucci, P., Blackstock, J., Byass, P., Cai, W., Chaytor, S., Colbourn, T., Collins, M., and Cooper, A.:
Health and climate change: policy responses to protect public health, Lancet, 386, 1861–1914, https://doi.org/10.1016/S0140-6736(15)60854-6, 2015. a
Wen, Y., Zhang, S., Zhang, J., Bao, S., Wu, X., Yang, D., and Wu, Y.:
Mapping dynamic road emissions for a megacity by using open-access traffic congestion index data, Appl. Energ., 260, 114357, https://doi.org/10.1016/j.apenergy.2019.114357, 2020. a, b
Wen, Y., Wu, R., Zhou, Z., Zhang, S., Yang, S., Wallington, T. J., Shen, W., Tan, Q., Deng, Y., and Wu, Y.:
A data-driven method of traffic emissions mapping with land use random forest models, Appl. Energ., 305, 117916, https://doi.org/10.1016/j.apenergy.2021.117916, 2022. a, b
Xu, Y., Li, S., Yuan, X., and Feng, Z.:
Emission characteristics of biogenic volatile compounds (BVOCs) from common greening tree species in northern China and their correlations with photosynthetic parameters, Environmental Science, 41, 3518–3526, https://doi.org/10.13227/j.hjkx.202001180, 2020 (in Chinese). a, b
Yang, D., Zhang, S., Niu, T., Wang, Y., Xu, H., Zhang, K. M., and Wu, Y.:
High-resolution mapping of vehicle emissions of atmospheric pollutants based on large-scale, real-world traffic datasets, Atmos. Chem. Phys., 19, 8831–8843, https://doi.org/10.5194/acp-19-8831-2019, 2019. a, b, c
Zhang, D., Gao, J., Tang, D., Wu, X., Shi, J., Chen, J., Peng, Y., Zhang, S., and Wu, Y.:
Switching on auxiliary devices in vehicular fuel efficiency tests can help cut CO2 emissions by millions of tons, One Earth, 4, 135–145, https://doi.org/10.1016/j.oneear.2020.12.010, 2021. a
Zhang, H., Zhou, L., Huang, X., and Zhang, X.:
Decarbonizing a large City's heating system using heat pumps: A case study of Beijing, Energy, 186, 115820, https://doi.org/10.1016/j.energy.2019.07.150, 2019. a, b
Zhang, S., Wu, Y., Liu, H., Huang, R., Yang, L., Li, Z., Fu, L., and Hao, J.:
Real-world fuel consumption and CO2 emissions of urban public buses in Beijing, Appl. Energ., 113, 1645–1655, https://doi.org/10.1016/j.apenergy.2013.09.017, 2014. a, b
Zhang, X., Mi, F., Lu, N., Yan, N., Kuglerova, L., Yuan, S., Peng, Q., and Ma, O. Z.:
Green space water use and its impact on water resources in the capital region of China, Phys. Chem. Earth Pts. A/B/C, 101, 185–194, https://doi.org/10.1016/j.pce.2017.02.001, 2017.
a
Zhang, Y., Yin, P., Li, X., Niu, Q., Wang, Y., Cao, W., Huang, J., Chen, H., Yao, X., and Yu, L.:
The divergent response of vegetation phenology to urbanization: A case study of Beijing city, China, Sci. Total Environ., 803, 150079, https://doi.org/10.1016/j.scitotenv.2021.150079, 2022. a
Zhao, X., Zhou, Y., Chen, W., Li, X., Li, X., and Li, D.:
Mapping hourly population dynamics using remotely sensed and geospatial data: a case study in Beijing, China, GISci. Remote Sens., 58, 717–732, https://doi.org/10.1080/15481603.2021.1935128, 2021. a
Zheng, Y., Liu, H., and Cheng, X.:
Datasets for simulating heat and CO2 fluxes in Beijing using SUEWS V2020b, Zenodo [data set], https://doi.org/10.5281/zenodo.7427360, 2022. a, b, c
Zhu, X., Ni, G., Cong, Z., Sun, T., and Li, D.:
Impacts of surface heterogeneity on dry planetary boundary layers in an urban-rural setting, J. Geophys. Res.-Atmos., 121, 12164–12179, https://doi.org/10.1002/2016jd024982, 2016. a
Short summary
The performance of the Surface Urban Energy and Water Balance Scheme (SUEWS) is evaluated against the observed surface exchanges (fluxes) of heat and carbon dioxide in a densely built neighborhood in Beijing. The heat flux modeling is noticeably improved by using the observed maximum conductance and by optimizing the vegetation phenology modeling. SUEWS also performs well in simulating carbon dioxide flux.
The performance of the Surface Urban Energy and Water Balance Scheme (SUEWS) is evaluated...
