About

Shu-Hua Chen is a Professor of Meteorology and Mesoscale Meteorologist at the Department of Land, Air and Water Resources at the University of California, Davis. He holds a B.S. in Atmospheric Sciences from National Taiwan University and both an M.S. and a Ph.D. in Earth and Atmospheric Sciences from Purdue University. His academic and research focus includes atmospheric physics and dynamics, mesoscale meteorology, and numerical modeling of the atmosphere. He is a member of the Atmospheric Science Graduate Group and the Graduate Group in Applied Mathematics, contributing to teaching courses such as Atmospheric Physics and Dynamics, Mesoscale Meteorology, and Numerical Modeling of the Atmosphere.

Research topics

• Chemical engineering
• Environmental science
• Environmental engineering
• Chemistry
• Organic chemistry
• Geology
• Materials science
• Climatology
• Meteorology
• Atmospheric sciences
• Geography
• Photochemistry
• Nanotechnology

Selected publications

• Enhancement of piezoelectric performance and mechanical strength by designing esterified lignin-based polyacrylonitrile membrane for piezoelectric sensor

  Iranian Polymer Journal · 2025-03-31 · 1 citations

  article1st author
  PublisherDOI

• Supplementary material to "Numerical Experiments of Cloud Seeding for Mitigating Localization of Heavy Rainfall: A Case Study of Mesoscale Convective System in Japan"

  2025-09-19

  articleOpen access
  PublisherDOI

• The role of mobility and air-conditioning in prenatal temperature exposure and birth outcomes: A prospective birth cohort study in Guangzhou

  Environmental Research · 2025-09-06 · 2 citations

  article
  PublisherDOI

• Fallowed agricultural lands dominate anthropogenic dust sources in California

  Communications Earth & Environment · 2025-04-26 · 10 citations

  articleOpen access

  Abstract Air pollution remains a major problem in many parts of California, significantly impacting public health and regional climate. However, the contribution of anthropogenic dust from agricultural sources, among major pollutants in California’s semi-arid Central Valley, remains largely unclear. Here, we used the Cropland Data Layer from the U.S. Department of Agriculture to identify crop types and land use/cover and leveraged satellite-derived estimates of major dust events between 2008 and 2022 over California. We identified fallowed land—an unplanted agricultural land parcel—as a key anthropogenic dust source in California. Specifically, we find that the Central Valley accounts for about 77% of total fallowed land areas in California, where they are associated with about 88% of major anthropogenic dust events. We also find that the geographic coverage of these fallowed lands expanded between 2008 and 2022 with associated increasing anthropogenic dust activities. Additionally, these anthropogenic dust activities are sensitive to the drought severity over the fallowed lands, with potential cumulative effects on downstream dust burden during prolonged multi-year drought conditions. Overall, our results have important implications for public health, including increased risk for Valley fever and for regional climates, such as increases in extreme precipitation and snowmelt over the Sierra Nevada.

  PublisherOA PDFDOI

• A Numerical Study of the Agricultural Irrigation Effects on Summer Soil Moisture and Near-Surface Meteorology in California’s Central Valley

  Journal of Hydrometeorology · 2025-05-06 · 2 citations

  articleOpen access

  Abstract California’s Central Valley (CV) is one of the most productive agricultural regions in the world, relying significantly on irrigation. This study explores the impacts of agricultural irrigation on soil moisture and near-surface meteorology in the CV. Employing the Weather Research and Forecasting (WRF) Model with a modified irrigation module, the WRF-irrigation simulation (WIR3D) reproduces observed humid surface soil moisture in the CV, as identified by satellite data. Without irrigation effects (WoIR), the model presents a dry surface soil moisture bias, with an average value below 0.05 m 3 m −3 over the CV. A comparison with surface-station observations reveals that the mean bias of the simulated 2-m dewpoint temperature is −1.62°C in WoIR but only 0.05°C in WIR3D. The 2-m temperature change by irrigation could be cooling or warming. The complexity of the temperature change arises from the combination of evapotranspirative cooling, soil heat flux, and radiative feedback, with differences between daytime evapotranspirative cooling and nighttime greenhouse gas effects. Compared with derived planetary boundary layer height (PBLH) from ceilometer observations, irrigation reduces simulated maximum positive PBLH bias by approximately 580 m (53%), resulting in a daily wind speed decrease of 0.5 m s −1 . In addition, this study examines the irrigation spatial heterogeneity effect, and the results show the variations of approximately 30% and 40% differences in PBLH and other near-surface variables between incorporating a county-level versus uniform irrigation rate over the CV. These findings underscore the importance of better integrating irrigation practices to improve weather forecasting in the CV.

  PublisherOA PDFDOI

• A flexible Regional Ocean Modeling System-based hybrid coupled model for El Niño–Southern Oscillation studies – model formulation and performance evaluation

  Geoscientific model development · 2025-09-03 · 4 citations

  articleOpen access

  Abstract. El Niño–Southern Oscillation (ENSO) constitutes the most prominent interannual climate variation mode in the climate system that originates from ocean–atmosphere interactions in the tropical Pacific. Accurately modeling ENSO variation has consistently posed a great challenge, exhibiting strongly model-dependent representations and simulations of ENSO. This study presents a novel hybrid coupled model (HCM), denoted HCMROMS, built upon the Regional Ocean Modeling System (ROMS) that has been widely used for regional modeling studies. For basin-wide applications to the tropical Pacific, here, the ROMS is coupled with a statistical atmospheric model. The statistical atmospheric model is based on singular value decomposition (SVD), capturing interannual relationships of atmospheric perturbations such as wind stress and freshwater flux anomalies with sea surface temperature (SST) anomalies. The model is constructed in a flexible way so that various components representing atmospheric forcing and oceanic biogeochemistry can be easily included as a module in the HCMROMS. Results demonstrate that the HCMROMS can simulate a stable quasi-3-year ENSO cycle when the interannual wind stress coupling coefficient, ατ, is set to 1.5. The HCMROMS reproduces the three-dimensional (3D) evolution of ENSO-related anomalies, revealing that the most pronounced temperature anomalies occur beneath the surface at 150 m. The interannual temperature anomaly budget highlights the dominance of the advection process in simulated ENSO. Vertical mixing contributes negatively to ENSO anomalies, damping temperature anomalies from the surface due to the turbulent heat flux feedback. This newly developed HCMROMS is poised to serve as an efficient modeling tool for ENSO research in the future.

  PublisherOA PDFDOI

• Molecular Dynamics Simulation of the Aggregation Behavior of Typical Aromatic Pollutants and Its Influence on the n-Octanol–Air Partition Coefficient

  Toxics · 2025-08-28

  articleOpen access

  The aggregation behavior of typical aromatic pollutants in the n-octanol phase and its influence on the n-octanol–air partition coefficient (KOA) were investigated using molecular dynamics simulation. The aggregate proportion of selected aromatic pollutants gradually increased with increasing simulation time and then reached a dynamic equilibrium state. It is interesting to find that the higher the concentration of aromatic pollutants, the more aggregates formed in the n-octanol phase. Log KOA values of these aromatic pollutants were subsequently estimated based on the percentages of aggregates and the solvation free energy from the gas phase to the n-octanol phase. The log KOA values were also found to gradually increase with increasing concentration. Therefore, the effect of concentration on KOA should be taken into consideration during the analysis of the environmental behavior and transport of these aromatic pollutants. In addition, it was found that π–π interactions drive the formation of different numbers of aggregates for different aromatic pollutants, a phenomenon that affects the KOA values of aromatic pollutants. The above results shed some light on the effects of aggregates and concentration on the partition behavior of aromatic pollutants and provide a theoretical basis for the correction of KOA of aromatic pollutants in the environment.

  PublisherOA PDFDOI

• Numerical Experiments of Cloud Seeding for Mitigating Localization of Heavy Rainfall: A Case Study of Mesoscale Convective System in Japan

  2025-09-19

  articleOpen accessCorresponding

  Abstract. This study investigated the potential of cloud seeding to mitigate extreme rainfall localization (i.e., overseeding) associated with mesoscale convective systems in Japan. Using a numerical weather prediction model, we conducted cloud seeding experiments by artificially increasing ice nuclei concentrations in a double-moment microphysics scheme for the heavy rainfall event in Hiroshima Prefecture, Japan, in August 2014. We examined the sensitivity of rainfall changes to altitudes and areas of the seeding. The results showed that seeding in the mid–upper troposphere (7.2–8.6 km), where air temperature ranged from −22 °C to −12 °C, resulted in the most pronounced changes in rainfall amount. At these levels, high supercooled cloud water content and strong updrafts favored heterogeneous freezing, resulting in a depletion of moisture and suppression of graupel growth. The cloud seeding led to reduced rainfall within the heavy rainfall region and increased rainfall downstream, demonstrating the hypothesized dispersal mechanism of “overseeding”. Expanding the seeding to cover the upstream region of the heavy rainfall area had a greater impact than increasing vertical thickness of the seeding. The most effective seeding configuration (24 km × 24 km area at 7.2 km) achieved an 11.5 % decrease in area-averaged 3-hr accumulated rainfall and a 32 % decrease as the maximum reduction in 3-hr accumulated rainfall over the heavy rainfall region. Future work should consider more realistic representations of seeding substance (i.e., transport, dispersion, and interactions) and explore a wider range of rainfall events to generalize the applicability of this approach.

  PublisherOA PDFDOI

• SOX4 promotes triple-negative breast cancer progression by promoting SRPX2 transcription to regulate AKR1C1

  Journal of Molecular Histology · 2025-07-15

  article
  PublisherDOI

• Achieving high and stable proton conductivity in PBI membranes at elevated temperatures via starch-induced phosphoric acid retention

  Journal of Membrane Science · 2025-10-17 · 1 citations

  article
  PublisherDOI

Recent grants

• Effects of Saharan Dust on African Easterly Waves and Tropical Cyclones

  NSF · $413k · 2013–2017

• Collaborative Research: Investigating the Characteristics of Lower Tropospheric Airborne GPS Radio Occultation Observations and Their Impact in Hurricane Studies

  NSF · $263k · 2010–2015

Frequent coauthors

• Michael J. Kleeman

  University of California, Davis

  24 shared

• Terrence R. Nathan

  University of California, Davis

  18 shared

• Zhan Zhao

  California Air Resources Board

  18 shared

• Dustin Grogan

  Albany State University

  16 shared

• Hongliang Zhang

  Fudan University

  12 shared

• Jaehwa Lee

  12 shared

• Hsiang‐He Lee

  11 shared

• Jianlin Hu

  11 shared

Education

• PhD, Earth and Atmospheric Sciences

  Purdue University

  1999