About Me

I am Guangzhi XU, a post-doc researcher in the field of atmospheric sciences.

I obtained my master’s degree in the University of East Anglia in the UK after my graduation from Shandong University with an Environmental Science background, and switched to atmospheric and climatic sciences from then on. At that time it interested me mostly because of its global-scale concern and the beautiful plots people create, and I sometimes feel attracted to those plots for reasons other than science. My postgraduate dissertation was supervised by Prof. Tim Osborn, and it was about tropical cyclone activities in the Indian Ocean, mostly based on an EOF analysis. I was told that it could be made into a publishable work, but due to time limitation I didn’t pursue further.

But I did return back to the UEA after graduation, and did my PhD study again with Tim and Prof. Adrian Matthews, in the Climatic Research Unit. We did some analyses on the atmospheric hydrological cycle at different time scales, using mostly Reanalysis and observational data. The 1st published work1 was about the moisture fluxes related to ENSO, and in that paper I experimented the Self-Organizing map algorithm. Then I quickly worked out another paper2 quantifying the onshore moisture transport by tropical cyclones.

After graduation I worked in the Ocean University of China with Prof. Ping CHANG. We carried out some work3 on the diagnosis of the precipitation decreases induced by the inclusion of meso-scale SST features in the WRF simulations. I was a bit of challenge as the absolute precipitation amount in the winter season in the Southeastern China is pretty low, and extra care is needed in every chain in the analyses to cut down possible errors as much as possible.

After publication of the precipitation analysis work, I moved on to develop a new automated atmospheric river (AR) detection and tracking algorithm4, 5. I have always been interested in such transient, swift and yet power water vapor “flocks”, they bring so much drama to the atmospheric hydrology, although sometimes in a hazardous manner. During summer season they appear as water plumes associated with tropical cyclones, and in the winter atmospheric rivers take the shift. In the method detection/tracking method, I used some image-processing techniques and some ideas that gathered during my spare time, and transformed them into something useful in my research. For instance, the AR axis finding algorithm used the dijkstra’s path-finding algorithm, something I learned when writing a video game.

Looking back at my very limited research career I noticed that I often tend to get distracted by some technical details and spend quite some time on that. I guess there is something intuitively playful inside me that makes me inclined to such “tricks” and get obsessed in experimenting and playing around with them. And that’s also where I spend most of my spare time, reading, watching and writing programs on different math and computer algorithms, or tweaking the OS, editors etc..

The excuse I told myself is that one should get the analyses methods straight before starting to ponder on the physics, and if a hammer is the only tool in one’s armory then he would treat any task as a nail. The correct method can give us a better view of the physical problem, in a new perspective and allow us to gain some insights that often are otherwise obscured.

This is also what I am trying to achieve in this little website: share with you some of my experiences working with some useful algorithms, their programming and applications. Also some useful tools that have proved to be productive in my day-to-day work.

Hope you will enjoy reading such materials.


  1. Xu, G., Osborn, T.J., Matthews, A.J. et al. Different atmospheric moisture divergence responses to extreme and moderate El Niños. Clim Dyn 47, 393–410 (2016). https://doi.org/10.1007/s00382-015-2844-2
  2. Xu, G., Osborn, T.J. & Matthews, A.J. Moisture transport by Atlantic tropical cyclones onto the North American continent. Clim Dyn 48, 3161–3182 (2017). https://doi.org/10.1007/s00382-016-3257-6
  3. Xu, G., Chang, P., Ma, X. et al. Suppression of winter heavy precipitation in Southeastern China by the Kuroshio warm current. Clim Dyn 53, 2437–2450 (2019). https://doi.org/10.1007/s00382-019-04873-3
  4. Xu, G.; Ma, X.; Chang, P.; Wang, L. A Comparison of Northern Hemisphere Atmospheric Rivers Detected by a New Image-Processing Based Method and Magnitude-Thresholding Based Methods. Atmosphere 2020, 11, 628.
  5. Xu, G.; Ma, X.; Chang, P.; Wang, L. Image Processing Based Atmospheric River Tracking Method Version 1 (IPART-1). Geoscientific Model Development 2020 (accepted)