the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 05 May 2025
Development of UI-WRF-Chem (v1.0) for the MAIA satellite mission: case demonstration
Abstract. The Multi-Angle Imager for Aerosols (MAIA) satellite mission, to be jointly implemented by NASA and the Italian Space Agency with an expected 2026 launch, aims to study how different types of particulate matter (PM) pollution affect human health. The investigation will primarily focus on a discrete set of globally distributed Primary Target Areas (PTAs) containing major metropolitan cities, and will integrate satellite observations, ground observations, and chemical transport model (CTM) outputs to generate maps of near-surface total and speciated PM within the PTAs. In addition, the MAIA investigation will provide satellite measurements of aerosols over a set of Secondary Target Areas (STAs), which are useful for studying air quality more broadly. For the CTM, we have developed a Unified Inputs (of initial and boundary conditions) for WRF-Chem (UI-WRF-Chem) modeling framework to support the MAIA satellite mission. These developments include: (1) application of NASA GEOS FP and MERRA-2 data to provide both meteorological and chemical initial and boundary conditions for performing WRF-Chem simulations of air quality at a fine spatial resolution for both forecast and reanalysis modes; (2) a stand-alone emission preprocessor that ingests both global and regional anthropogenic emission inventories as well as fire emissions; (3) application of MODIS land data to improve land surface properties such as land cover type; (4) application of GLDAS and NLDAS data to constrain surface soil properties such as soil moisture; (5) development of a new soil NOx emission scheme – the Berkeley Dalhousie Iowa Soil NO Parameterization (BDISNP).
Here, we illustrate the model improvements because of these developments over four target areas: Beijing in China, CHN-Beijing (STA); Rome in Italy, ITA-Rome (PTA); Los Angeles in the U.S., USA-Angeles (PTA) and Atlanta in the U.S., USA-Atlanta (PTA). UI-WRF-Chem is configured as 2 nested domains using an outer domain (D1) and inner domain (D2) with a 12 km and 4 km spatial resolution, respectively. For each target area, we first run a suite of sensitivity simulations to test the model sensitivity to different options of physics schemes and then select the optimal combination of physics schemes based on evaluation of model simulated meteorology. For the inner domain (D2), we have chosen to turn off the traditional Grell 3D ensemble (G3D) cumulus scheme. We conduct a case study over USA-Atlanta for June 2022 to demonstrate the impacts of cumulus scheme on precipitation and subsequent surface PM2.5 concentration. Our results show that keeping the G3D cumulus scheme on results in higher precipitation and lower PM2.5 than the simulation with the G3D cumulus scheme off. Compared with surface observations of precipitation and PM2.5 concentration, the sensitivity simulation with the G3D scheme off shows better performance than keeping it on. We focus on two dust intrusion events over CHN-Beijing and ITA-Rome, which occurred in March 2018 and June 2023, respectively. We carry out a suite of sensitivity simulations using UI-WRF-Chem by excluding chemical boundary conditions or including MERRA-2 chemical boundary conditions. Our results show that using MERRA-2 data to provide chemical boundary conditions can help improve model simulation of surface PM concentration and AOD. Some of the target areas have also experienced significant changes in land cover and land use over the past decade. Our case study over CHN-Beijing in July 2018 investigates the impacts of improved land surface properties with timely MODIS land data on capturing the urban heat island phenomena. Model-simulated surface skin temperature shows better agreement with MODIS observed land surface temperature. The updated soil NOx emission scheme leads to higher NO2 vertical column density (VCD) in rural areas over CHN-Beijing target area, which matches better with TROPOMI observed NO2 VCD. This in turn affects the simulation of surface nitrate concentration. Lastly, we conduct a case study over USA-LosAngeles to tune the dust emissions. This gives an example to show the fine-tuning work we do over each target area to investigate the problem specific to that target area as we continue evaluating and improving model performance.
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RC1: 'Comment on egusphere-2025-1360', Anonymous Referee #1, 14 May 2025
This paper focuses on the development of a Unified Inputs for WRF-Chem (UIWRF-Chem) system to support the MAIA satellite mission. The authors propose a framework that integrates NASA’s GEOS-FP and MERRA-2 as initial and boundary conditions, incorporates a stand-alone emissions preprocessor, updates land surface properties, and implements a new NOₓ emission scheme. They test the system’s performance across four MAIA target cities.
Overall, this is a solid and technically sound study. The authors demonstrate a good understanding of the different options available in WRF-Chem and the key differences among them. However, the manuscript currently suffers from a lack of clarity, particularly in the Introduction and Model Description sections. I recommend major revisions before it can be considered for publication.
General Comments:
- Clarify the link to MAIA mission needs. Since the core purpose of this study is to support the MAIA mission, the paper should better articulate MAIA's specific modeling requirements—e.g., what variables are most relevant, what forecast capabilities are needed, and how UIWRF-Chem is designed to meet those needs.
- Improve the Introduction. The rationale for modifying WRF-Chem is not clearly laid out. The authors should explain why it is necessary to update land surface properties, emissions modules, and boundary/initial conditions in the context of MAIA. A clearer articulation of these needs would better frame the scientific motivation.
- Reorganize the Model Description section. The current presentation of model improvements is confusing. I suggest breaking it into clearly labeled subsections, each focused on a single enhancement (e.g., emissions, boundary conditions, NOₓ scheme, land surface update).
- Quantify significance of improvements. While the paper compares results from different modeling schemes, it does not provide evidence of whether the differences are statistically significant or robust across other regions or time periods.
Specific Comments:
- Why use WRF-Chem v3.8.1? Given that WRF-Chem versions above 4.0 are now available (with improvements such as subgrid-scale chemical transport for KF and GF schemes), the authors should justify why UIWRF-Chem is based on v3.8.1. Even though they mention plans to test GF in the future, a more detailed explanation is needed.
- Summarize model setup in a table. Please consider adding a summary table listing the model configuration (e.g., resolution, land surface model, physics schemes, emissions setup, etc.), or update Table S2 accordingly.
- Highlight novelty of new modules. Some of the newly added components appear to be simple integrations into WRF-Chem rather than innovations. The paper should more clearly highlight what is original and novel in this system.
- Table S1. Please consider highlighting the best-performing configurations for easy comparison.
- Figure 5: The comparison may be misleading due to resolution differences—MERRA-2 is coarse and likely underestimates high PM₂.₅ values, whereas WRF-Chem has higher resolution and better captures spatial variability. Consider interpolating WRF-Chem output to the MERRA-2 grid for a fair comparison, or include scatterplots at matched resolution.
- Figure 6: Please emphasize the observational data (e.g., bold lines or larger markers) to improve readability.
- Line 720: Consider discussing why the updated system better captures the observed PM₂.₅ peaks. This would strengthen the case for the model improvements.
- Line 1035: It would be helpful to summarize the sensitivity tests in a table for easier interpretation.
- MAIA compositional data: Since MAIA will retrieve PM component information, the paper should demonstrate how UIWRF-Chem simulates PM species. It would be useful to show comparisons against ground-based observations (e.g., from the IMPROVE network).
- Significance testing: The paper discusses improved performance for certain configurations, but lacks significance tests to demonstrate that the improvements are statistically meaningful. This is important to ensure the optimal setup is not case-specific.
Citation: https://doi.org/10.5194/egusphere-2025-1360-RC1 -
RC2: 'Comment on egusphere-2025-1360', Anonymous Referee #2, 29 May 2025
Zhang et al. present UI-WRF-Chem, a set of unified inputs (initial and boundary conditions) for WRF-Chem in support of the MAIA satellite mission. UI-WRF-Chem provides meteorological inputs as well as emissions; land surface data; and a new soil NOx emissions scheme. A new chemistry scheme based on MADE/SORGAM is also developed, MADE/SORGAM-DustSS, to incorporate GOCART-AFWA emission scheme for matching with the MERRA-2/GEOS-FP dust size bins.
The manuscript details many improvements to provide inputs to WRF-Chem. Of particular note is the development of WEPS as an emissions pre-processor which resolves a point of frustration in offline emissions processing for WRF-Chem. In addition, to support the MAIA satellite mission, UI-WRF-Chem extensively incorporates data from GEOS-FP and MERRA-2 products to the WRF-Chem model pipeline and evaluates many of these developments. These improvements have also been validated in four extensive case studies across the globe. The manuscript is well written and I recommend its publication.
Major comments:
1. The authors evaluate throughout the effect of incorporating "MERRA-2 chemical boundary conditions" into the simulation. Just to confirm that the simulations marked "none" mean zero boundary conditions are input; is this usual in WRF-Chem simulations? Does the common approach of using CAM-chem/WACCM outputs as boundary conditions provide no information for the dust and other aerosols in a WRF-Chem simulation? If CAM-chem/WACCM, as global models, can provide some kind of information, I think it would be a more fair comparison as to whether these conditions can/can not help the regional model capture the long-range transport event.2. UI-WRF-Chem extensively integrates outputs from GEOS-FP and MERRA-2 as inputs for WRF-Chem; many of these improvements are not trivial, e.g., the updates to land input data, a new soil NOx emissions scheme, etc... Do the authors plan to contribute this capability to WPS and the WRF mainline model code in the future?
3. WEPS builds on the existing WRF-Chem emissions processing tools to incorporate several global inventories, as well as allowing NEI and MEIC inventories to replace the global inventory. Is the process of regional inventories to override the global inventory an automated process (i.e., a regional netCDF file can be supplied and it'll overwrite the global inventory?) like in GEOS-Chem's emissions tool, HEMCO, or code changes will be needed? How extensible is WEPS to update with further inventories, and how easy is it to update inventores in the future? For example, I noted that FINN v1.01 is supported but not the more recent FINN v2.5 - will WEPS enable an easier update of the inventores for ingestion into WRF-Chem?
4. I also suggest some presentation improvements: organize the best configuration (of model physics) for each case study domain in a table; also label in the figures the D1 and D2 domains for each case study; at times D1 is the whole region and D1 is marked by a rectangle and inset text could help the reader.
Specific/Minor comments:
L40: "because of" -> I suggest "enabled by".
L223-225: It's not clear what the paragraph is suggesting here. Are you suggesting that the manuscript's use of GEOS-FP and MERRA2 differs from the common practice of using CAM-chem/WACCM outputs as chemical IC/BC (which I believe is the common practice in the WRF-Chem user's guide) or that GEOS-FP and MERRA-2 are different in that they assimilate satellite-based aerosol fields? I would suggest revising this paragraph for clarity.
L425: "sea seal" -> "sea salt"?
L446: "relative humanity" -> "relative humidity"?
L519: "the chemistry will be transported..." -> maybe "the chemical tracers will be transported"?
SI Table S1 Los Angeles Simulation #1: "Li" -> "Lin"Citation: https://doi.org/10.5194/egusphere-2025-1360-RC2 -
AC1: 'Comment on egusphere-2025-1360', Huanxin Zhang, 31 Aug 2025
Dear Editor and Reviewers,
We sincerely thank the reviewers for providing constructive feedback and helpful suggestions to improve our manuscript. Please find attached a PDF file including reviewers’ comments along with our point-by-point responses.
Warm Regards.
Huanxin (Jessie) Zhang, on behalf of all co-authors
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