Yuxiang Ren Meteorology · forecast verification
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About

Yuxiang Ren

Meteorology and forecast verification
Years of operational weather forecasting and observation, now finishing an M.S. in Meteorology. I work on radar nowcasting, dust transport modeling and energy meteorology.
Test first, then conclude.

Based in
Northern China
Focus
Radar nowcasting · energy meteorology
Background
Operational forecasting, 2014–2022
Seeking
PhD (Fall 2027) or research role

PathFrom operational forecasting to research, built on real forecasts and their verification

  1. 2010–2014B.S. Atmospheric SciencesUniversity in China
  2. 2014–2022Operational forecastingShort-, medium-range and nowcasting; surface observation
  3. 2022–2026M.S. MeteorologyThesis: East Asian dust variability and transport
  4. NowNowcasting and energyRadar–NWP verification, wind-power forecasts

Background

From 2014 to 2022 I worked in operational forecasting and observation: short- and medium-range forecasts, severe-weather warnings and nowcasting, plus small tools I wrote to speed up forecast calculations. In 2022 I returned to university for an M.S. in Meteorology. My thesis is on the long-term variability and transport of East Asian dust; outside it I work on radar nowcasting and energy meteorology.

All work Findings

Now

What I am working on

In progress, just finished, and what I am looking for.

In progress

Dust exposure of the northwest China solar corridor

Siting structure and dust-exposure trends; no generation-loss estimate.

Card →
Just finished

Texas wind-power forecast evaluation

Official forecast error, curtailment, and a fair comparison with Pangu-Weather and GraphCast operational forecasts.

Case study →
Looking for

PhD position or research role

AI weather prediction, probabilistic forecasting, radar nowcasting, energy meteorology.

Contact →

Publications

Papers and patent

Co-authored papers are listed by title, with my author position; full author lists are at each DOI.

  1. Ren, Y., et al. (2026). Dual-source transport, vertical evolution, and topographic modulation of the March 2023 East Asian dust storm in the context of 2000–2024 spring dust variability. Atmosphere, 17(8), 740.First author · doi:10.3390/atmos17080740 · code
  2. The reconstruction of FY-4A and FY-4B cloudless top-of-atmosphere radiation and full-coverage particulate matter products reveals the influence of meteorological factors in pollution events. Remote Sensing (2024), 16(18), 3363.Co-author, 4th of 6 · doi:10.3390/rs16183363
  3. High-resolution short-term prediction of the COVID-19 epidemic based on spatial-temporal model modified by historical meteorological data. Fundamental Research (2024), 4(3), 527–539.Co-author, 4th of 9 · doi:10.1016/j.fmre.2024.02.006
  4. Exploring high-resolution near-surface CO concentrations based on Himawari-8 top-of-atmosphere radiation data: Assessing the distribution of city-level CO hotspots in China. Atmospheric Environment (2023), 312, 120021.Co-author, 8th of 8 · doi:10.1016/j.atmosenv.2023.120021
  5. Estimation of the ground-level SO₂ concentration in eastern China based on the LightGBM model and Himawari-8 TOAR. Frontiers in Earth Science (2023), 10, 1037719.Co-author, 3rd of 8 · doi:10.3389/feart.2022.1037719
  6. In preparation: Ren, Y., et al. How robust is the weakening of East Asian spring dust, 2000–2024?Intended for JGR: Atmospheres
  7. Five earlier articles in Chinese journals (2019)Heavy-rainfall case studies and agrometeorological services; three as first author
  8. Chinese utility-model patent: Handheld weather stationZL 2019 2 0409607.3 · second inventor

Open source

Open-source contributions

When my research hits a bug in a community package, I fix it upstream.

pysteps

Merged

Fixed a crash in STEPS blending when forecast timesteps have gaps, found while running my nowcasting study; added the regression test the suite lacked. PR #560

Satpy

Merged

Added PyTroll dependency packages to the show_versions() diagnostics. PR #3426

Py-ART

Merged

Fixed get_nexrad_location() converting station elevation from feet to meters again on every call (KTLX: 369.7 m → 112.7 m); five regression tests. PR #1879

nowcast-bench

Released

My precipitation-nowcasting benchmark: every score carries its sample size, undefined cases are flagged, cross-checked against pysteps. GitHub · PyPI

Skills

Toolbox

  1. ProgrammingPython (NumPy, xarray, pandas, Matplotlib/Cartopy, scikit-learn, PyTorch), Git, pytest, Linux
  2. ModelsWRF-ARW, WRF-Chem, FLEXPART-WRF
  3. RadarPy-ART, pysteps (STEPS blending), NEXRAD Level II, radar product processing, extrapolation and verification
  4. DataERA5, MERRA-2, CAMS, CALIPSO/CALIOP, TOMS/OMI, Himawari-8, FY-4, Sentinel-1/2, Landsat, WeatherBench 2
  5. StatisticsTrend and break-point tests, field significance (FDR), block bootstrap, SOM, cross-validated machine learning

Honors

Honors

  • 2026Silver medal, Kaggle Biohub – Cell Tracking During Development: 154th of 3,947 teams (top 4%), team of two
  • 2024Second-Class Graduate Scholarship
  • 2022–23Third-Class Graduate Scholarship

Let's talk.

A line about the question you are working on, or the position, is the best start.

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