About

Xingchao (XC) Chen is an Assistant Professor of Meteorology at Penn State University, specializing in mesoscale meteorology and severe weather, numerical modeling, and data assimilation. His primary research interests involve tropical meteorology and data assimilation, with a focus on understanding and predicting severe weather phenomena and tropical cyclones. Dr. Chen has contributed to advancing the analysis and forecast of hurricanes, the energetics of the South Asian summer monsoon, and the development of convection-permitting air-sea-coupled ensemble data assimilation systems for tropical cyclone prediction. His work emphasizes the importance of mesoscale convective systems in atmospheric transport processes and the improvement of weather prediction models.

Research topics

• Environmental science
• Climatology
• Meteorology
• Geology
• Physics
• Atmospheric sciences
• Geography
• Nanotechnology
• Materials science
• Remote sensing
• Mathematics
• Composite material

Selected publications

• High-resolution VDRAS dataset for the mesoscale convective system on 30th July 2014

  Zenodo (CERN European Organization for Nuclear Research) · 2026-03-30

  datasetOpen access

  The VDRAS output is provided in NetCDF format. The analysis domain is centered at 117°E, 32.1°N with 140 × 140 horizontal grid points and 40 vertical levels. The spatial resolution is 3 km horizontally and 300 m vertically. Each data file contains comprehensively retrieved 3D fields, including wind components (U, V, W), perturbation temperature, pressure, and various water mixing ratios (vapor, cloud, and rain), utilizing WRF forecasts as the background field.

  PublisherDOI

• Roles of Surface Latent Heat Flux and Gravity Waves in Offshore MCS Development in the Coastal Eastern Tropical Pacific

  Journal of Geophysical Research Atmospheres · 2026-04-01

  articleOpen accessCorresponding

  Abstract The eastern tropical Pacific (ETP) coastal region, one of the rainiest places on Earth, is characterized by distinct diurnal offshore rainfall propagation primarily driven by mesoscale convective systems (MCSs). Previous studies have shown that MCS initiation in this region peaks in the early morning, with diurnally generated gravity waves from the Andes proposed as a key triggering mechanism. Additionally, enhanced low‐level moisture has been hypothesized to be a crucial contributing factor in MCS development. However, the relative roles of these processes in triggering MCSs over the region remain insufficiently quantified. This study explores these mechanisms using an ensemble‐based satellite data assimilation experiment focused on a representative nocturnal MCS event. Our results reveal a clear pre‐MCS cooling trend in the lower troposphere, linked to gravity waves generated by afternoon inland convection. Concurrently, substantial low‐level moistening occurs, driven by increased surface latent heat flux and horizontal moisture advection from the Panama low‐level jet. These processes together destabilize the lower troposphere, creating favorable thermodynamic conditions for convection. Additionally, an offshore anabatic surface front enhances low‐level convergence, promoting vertical lifting of unstable air and providing dynamic support for MCS initiation. Sensitivity experiments further demonstrate that MCS development is highly sensitive to low‐level moisture availability, which is strongly influenced by surface wind‐induced evaporation.

  PublisherDOI

• High-resolution VDRAS dataset for the mesoscale convective system on 30th July 2014

  Zenodo (CERN European Organization for Nuclear Research) · 2026-03-30

  datasetOpen access

  The VDRAS output is provided in NetCDF format. The analysis domain is centered at 117°E, 32.1°N with 140 × 140 horizontal grid points and 40 vertical levels. The spatial resolution is 3 km horizontally and 300 m vertically. Each data file contains comprehensively retrieved 3D fields, including wind components (U, V, W), perturbation temperature, pressure, and various water mixing ratios (vapor, cloud, and rain), utilizing WRF forecasts as the background field.

  PublisherDOI

• The Multi-University Consortium for Advanced Data Assimilation Research and Education (CADRE)

  Bulletin of the American Meteorological Society · 2026-04-22

  article

  Abstract The Multi-University Consortium for Advanced Data Assimilation Research and Education (CADRE) is a new initiative recently funded by the National Oceanic and Atmospheric Administration (NOAA) to accelerate data assimilation (DA) research, education, and workforce development. Unlike previous initiatives, CADRE fosters end-to-end, direct, and comprehensive collaboration between university faculty and government agencies. It supports innovative DA research, prepares the next-generation DA workforce, and facilitates the transition of DA research to operational applications. CADRE performs a broad scope of cutting-edge research to address multiscale, nonlinear, and coupled Earth system DA challenges to improve short-range (sub-hourly) to seasonal predictions. It achieves this task through innovative data assimilation algorithm development, novel applications of machine learning (ML) in DA, and optimizing the utilization of existing and new in-situ and remotely sensed observations. Beyond research, CADRE establishes a comprehensive education, workforce development, and community building program, which includes a novel graduate student advising model, new university class curriculum development, public training courses, community scientific workshops, an international exchange program, trans-disciplinary partnerships, an outreach program, and promotion of the open sharing of data, code, and educational materials. Through this unique holistic approach, CADRE is set to strengthen both the intellectual and software infrastructure in the broad community for DA research, increase the number of DA scientists with expanded skill sets, and revolutionize forecasting capabilities.

  PublisherDOI

• Advancing Weather and Climate Science in Mesoamerica and the Caribbean: A Novel Regional Multiweek Convection-Permitting Simulation

  Bulletin of the American Meteorological Society · 2026-03-19

  article

  Abstract Understanding the weather and climate of Mesoamerica and the Caribbean remains challenging due to complex hydroclimate interactions, limited observations, and poor representation of regional processes in global models. We introduce the Mesoamerica Affinity Group (MAAG), a National Science Foundation (NSF) National Center for Atmospheric Research (NCAR) and community initiative that fosters research collaboration to advance weather and climate science, develop convection-permitting datasets, and promote knowledge exchange. MAAG’s first major contribution is a 2-week convection-permitting simulation of Hurricane Maria (2017) using Model for Prediction Across Scales–Atmosphere (MPAS-A), featuring a novel regional 15- to 3-km variable-resolution mesh over the region. Initial evaluation shows that MPAS-A captures key features like precipitation patterns, the intertropical convergence zone, and low-level jets. Some biases remain, particularly in enhanced land convection and slight deviations in Maria’s track. This novel dataset, now publicly available through NCAR’s Data Archive, supports studies of other extreme events and mesoscale convective systems active during the same period. It offers a valuable resource for the research community. MAAG is a new but rapidly growing initiative achieving notable milestones in a short time. It serves as a collaborative platform for codesigning high-resolution modeling experiments aimed at producing actionable weather and climate information. We invite the community to join MAAG, explore this initial dataset, and advance regional weather and climate research. Significance Statement The Mesoamerica Affinity Group (MAAG), a National Science Foundation (NSF) National Center for Atmospheric Research (NCAR) and community initiative, aims at addressing the complex challenges of understanding weather and climate in Mesoamerica and the Caribbean. MAAG’s first major achievement is a 2-week convection-permitting simulation of Hurricane Maria (2017) using a novel 15- to 3-km variable-resolution mesh. This dataset accurately captures key regional features and is publicly available through NCAR’s Data Archive. By fostering collaboration through data production and sharing, monthly group meetings that serve as a platform for networking and knowledge exchange, and the development of advanced high-resolution datasets, MAAG provides a vital resource for advancing regional weather and climate science. The initiative is rapidly growing, serving as a platform for codesigned modeling experiments aimed at producing actionable climate information for academia and different sectors. We invite the scientific community to join MAAG and advance research in this critical region.

  PublisherDOI

• Impact of Penetrating Kelvin Waves on MJO Rainfall Propagation Through Deep Convection Modulation

  Geophysical Research Letters · 2025-05-25 · 1 citations

  articleOpen access1st authorCorresponding

  Abstract The Madden‐Julian Oscillation (MJO) is a dominant intraseasonal oscillation in the tropics. As MJOs propagate over the Indian Ocean, some of them can be penetrated by fast‐moving equatorial Kelvin waves originating to the west of the MJOs. Through a series of sensitivity experiments, we demonstrate that these penetrating Kelvin waves can modulate the eastward propagation speed of MJO rainfall. Deep convection in the western MJO rainfall envelope initiates more frequently and produces greater lifetime rainfall when a convectively active Kelvin phase is present, while the opposite occurs during a convectively suppressed Kelvin phase. This alteration in deep convection activity can lead to notable changes in the propagation of the large‐scale MJO rainfall envelope. The modulation of deep convection lifetime rainfall by penetrating Kelvin waves primarily occurs through their impact on deep convection rainfall area, which is closely related to the variations in lower‐tropospheric moisture induced by the Kelvin waves.

  PublisherOA PDFDOI

• Superwetting-Induced Transfer of AgNWs/PDMS/IL onto the Emissive Layer for Fabrication of a Three-Layered Flexible Electroluminescent Device

  ACS Applied Electronic Materials · 2025-06-18 · 2 citations

  article

  The emergence of flexible electroluminescent (EL) devices has demonstrated significant potential in wearable technology, lighting, and biointegrated electronics, driving the need for efficient and cost-effective fabrication methods. However, the conventional multistep processes for creating five-layer flexible EL devices are often laborious and costly. In this work, we address these challenges by introducing a one-step transfer method for fabricating a three-layered flexible EL device. This innovative approach harnesses superwettability-induced transfer of silver nanowires (AgNWs), ionic liquid (i.e., 1-ethyl-3-methylimidazolium(bis-trifluoromethane sulfonyl)imide, [EMIm]NTf2), and polydimethylsiloxane (PDMS) onto the luminescent layer. The ionic liquid, [EMIm]NTf2, serves to locally organize the AgNWs, while the PDMS acts as a protective layer. This method not only streamlines the fabrication process but also enhances material utilization and enables the creation of continuous luminous patterns, thereby presenting a highly promising solution for rapid prototyping and customization in flexible EL device manufacturing.

  PublisherDOI

• Development of an adaptive meshing upper bound limit analysis method for large deformation axisymmetric geotechnical problems

  Scientific Reports · 2025-02-17 · 5 citations

  articleOpen access1st authorCorresponding

  This research introduces the development of a sequential limit analysis (SLA) method in OPTUM. The plane-strain analysis capability of the original SLA has been extended to encompass both plane-strain and axis-symmetric problems, and the usability has been expanded to a broader spectrum of users. Moreover, refinements in addressing nodal velocities during soil collapse under gravity, specifically in scenarios featuring a stiff soil berm leading to slope instability, have been implemented, to enable proper modelling of more extreme conditions and complex model geometries. A detailed validation has been made against various penetration problems. It is revealed that SLA simulations can be executed with displacement increments at the order of 1% of the characteristic size of the object. In addition, a succinct parametric study on ball penetration is presented. Penetration resistance with strain softening is reduced by up to 34.5% compared to the non-softening case. An equivalent plastic strain factor was adopted to enhance the accuracy of measuring soil strength through ball penetrometer tests. The enhanced SLA method could also serve as a powerful tool for analysing large deformation soil-structure interaction problems for piles, spudcans, and cone / ball penetrometers in offshore engineering.

  PublisherDOI

• Mechanisms Behind the Long‐Distance Diurnal Offshore Precipitation Propagation in Northwestern South America

  Journal of Geophysical Research Atmospheres · 2025-02-07 · 2 citations

  articleOpen accessSenior authorCorresponding

  Abstract Northwestern South America (NWSA) is the rainiest region on Earth, with diurnal precipitation exhibiting extensive westward offshore propagation of up to about 1,200 km in boreal spring (March‐May). The diurnal offshore precipitation propagation begins slowly (3–10 m s −1 ) near the coast of NWSA (<200 km) but accelerates significantly (∼20 m s −1 ) and shows an afternoon enhancement far from the coast (>400 km). However, the driving mechanisms behind this long‐distance precipitation propagation remain unclear. Using a new cloud tracking and classification data set, we found that mesoscale convective systems (MCSs) are the dominant precipitation contributors in the offshore region of NWSA. Cloud tracking shows that the long‐distance propagation and the afternoon enhancement of diurnal precipitation primarily originate from MCSs initiated in the early morning, either over open oceans or from the coast of Central America. Composite tendency analysis shows that MCSs initiated near the coast of Central America have significant upward cooling and moistening signals starting from the surface before initiation. Further analysis of surface diurnal perturbation fields indicates that the land breeze is the primary driving mechanism for MCS initiation. Conversely, for MCSs initiated over open oceans, a significant downward cooling signal from 400 hPa is observed ∼7 hr before initiation, corresponding to the passage of diurnal gravity waves emitted from the Andes. Additionally, our findings highlight the critical role of lower and mid‐level moisture conditions in MCS initiation, alongside the influence of gravity waves.

  PublisherDOI

• Mesoscale Processes Driving Offshore MCS Initiation in the South Asian Summer Monsoon: Insights from an Ensemble-Based Satellite Data Assimilation Experiment

  Journal of the Atmospheric Sciences · 2025-05-26

  articleOpen accessSenior author

  Abstract Mesoscale convective systems (MCSs) are the primary rainfall contributors over the Bay of Bengal (BoB) during the South Asian summer monsoon. Previous studies have established a strong connection between MCS initiation over the BoB and diurnal gravity waves propagating from India. However, the precise role these waves play in triggering offshore MCSs remains unquantified. In this study, we analyze a typical MCS event, representative of the climatological spatiotemporal characteristics of MCS initiation in the region, to investigate the relative roles of diurnal gravity waves and other mesoscale processes in offshore MCS initiation. An ensemble-based satellite data assimilation (DA) experiment is conducted, assimilating all-sky infrared radiances from Meteosat-8 into the Weather Research and Forecasting (WRF) Model. The ensemble forecast, initialized from DA analyses, shows that many ensemble members accurately capture both the timing and location of MCS initiation. The analysis of the “successful” members reveals diurnal gravity waves play a significant role in enhancing lower-tropospheric moisture and destabilizing the offshore environment. Surprisingly, similar gravity waves and destabilization are also present in members that failed to capture MCS initiation. Further analysis indicates that land-breeze front from northern Sri Lanka is a key factor distinguishing successful from “unsuccessful” members, which, in successful members, is strong enough to lift air above the level of free convection (LFC) and lead to MCS initiation. Accurately simulating the land-breeze front depends on the correct representation of pre-MCS clouds and surface winds. This suggests that while diurnal gravity waves contribute to environmental destabilization, surface and boundary layer processes are crucial for the practical predictability of offshore MCS initiation. Significance Statement The majority of summer monsoon rainfall over the Bay of Bengal is attributed to large and long-lasting thunderstorms. Scientists hypothesized atmospheric waves from India play a role in the initiation of these thunderstorms, but the role has not been quantified yet. Therefore, we study a typical thunderstorm using satellite data and computer models. The results show that atmospheric waves from India create an environment that is favorable for thunderstorm formation. However, the favorable environment alone does not guarantee thunderstorm initiation. A key thunderstorm-triggering process is the land breeze from northern Sri Lanka. Accurately simulating the land breeze depends on correctly simulating prestorm clouds and near-surface winds. Assimilation of satellite observations can improve the forecast of thunderstorm initiation.

  PublisherOA PDFDOI

Frequent coauthors

• James H. Ruppert

  University of Oklahoma

  107 shared

• Steven E. Koch

  101 shared

• Yu Du

  Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai)

  101 shared

• Anton Seimon

  Appalachian State University

  101 shared

• Y. Qiang Sun

  Northeast Petroleum University

  101 shared

• Junhong Wei

  101 shared

• L. Ruby Leung

  Pacific Northwest National Laboratory

  43 shared

• Praveen Kumar Pothapakula

  Goethe University Frankfurt

  39 shared

Education

• Ph.D., Department of Atmospheric Science

  Nanjing University

  2016

• B.S. , Department of Atmospheric Science

  Nanjing University of Information Science and Technology

  2011