By Lin Xiaoyi

As the sweltering mid-August heat lingers over Beijing, I sit in a classroom at the China Meteorological Administration (CMA) International Cooperation and Training Center. A Chinese language lesson has just ended, and I meet Shahzad Ali Shah, a meteorologist from the Research and Development (R&D) Division of Pakistan’s Meteorological Department. As the teacher dismisses the class, he eagerly joins fellow international trainees to discuss post-class assignments.

Shahzad arrived in March and will spend a full year in Beijing as a visiting scholar, with his formal training running through the end of January 2027. “My Chinese improves every day,” he says, with a modest hope: By the end of his training, he wants to hold basic daily conversations with his Chinese colleagues – not for small talk, but to serve as a living bridge between two countries’ weather agencies.

For a climate scientist, that sounds almost humble. Yet it struck me as the real thread that ties current China-Pakistan meteorological cooperation.

Before coming to China, Shahzad had crafted a comprehensive and ambitious learning agenda: to understand China’s integrated technical system, decode the operational logic behind core technologies, and, above all, dive deep into artificial intelligence. “AI is my top priority,” he tells me.

“China leads in AI across every sector, and weather is no exception.” He aims to grasp the fundamentals of meteorological AI and bring actionable solutions back home to upgrade Pakistan’s forecasting and disaster warning systems.

Among all the technologies he studies, Shahzad focuses most on mastering China’s intelligent meteorological early warning solution MAZU. Far more than the ancient maritime guardian figure that its name evokes, MAZU (Multi-hazard, Alert, Zero-gap, Universal) stands as China’s tailored technical response to the UN’s “Early Warnings for All” initiative.

Pakistan has maintained extensive and long-running meteorological cooperation with China over the years, and MAZU has emerged as the new benchmark of bilateral collaboration.

Shahzad told me what impresses him most about MAZU is not any single groundbreaking gadget, but China’s systematic prowess in integrating satellite surveillance, numerical models, ground observations and AI algorithms into a streamlined, end-to-end early-warning workflow.

Yet beyond the technological sophistication, what truly captivates him is the human-centric philosophy embedded in CMA’s operational approach: AI crunches massive volumes of raw data and flags emerging hazard risks, while seasoned professional meteorologists deliver the final authoritative judgment – the ultimate safety shield for local communities.

For Pakistan, robust early warning systems represent an unnegotiable public safety priority, a cause that Pakistani meteorological authorities have long treated with extreme prudence and forward-thinking planning. Earlier, when I interviewed Furrukh Bashir, director of the R&D Division, I learned that in the past, Pakistani forecasters could access vast amounts of meteorological data, but satellite observations, numerical model outputs and ground-based measurements were scattered across different workstations in incompatible formats. This data fragmentation forced staff to spend excessive time piecing together the current state of the atmosphere and predicting its evolution.

The local deployment of MAZU has resolved this. The platform now incorporates Pakistan’s own 5-km WRF model, ground data and glacial lake flood warnings. During the 2026 monsoon, the locally optimized system assisted in precipitation analysis and flash-flood risk assessment, supporting coordinated national and provincial disaster responses.

This success, however, is only part of the story. In my series of interviews, I found that any team member involved with MAZU repeatedly emphasized the concept of “co-construction,” which means not just technology transfer, but also joint capacity building. That concept resonated with both Shahzad and Bashir.

Bashir once told me how the partnership began. Initially, Pakistani trainees found that a cloud-based system hosted on Chinese servers suffered from network latency when run locally. Most projects would have stalled there. Instead, both sides turned that obstacle into a new starting point. Pakistani experts and Chinese engineers co-developed an on-premise deployment module; dedicated servers were set up in Islamabad; and both teams continued secondary development and customization.

What was ultimately delivered to Pakistan was never merely a closed, rigid software system.

Shahzad explained it bluntly: China did not hand Pakistan an unmodifiable finished product. Instead, it helped Pakistani meteorologists learn to adjust, optimize and upgrade the platform themselves – so that the technology genuinely fits Pakistan’s own conditions.

To me, this approach is far more noteworthy than any technical parameter. AI is now a global variable. The question is no longer just “who has stronger AI,” but can these capabilities cross borders and reach developing countries’ real-world conditions? Can they enable users to eventually own their capacity, rather than permanently rely on external systems?

China is offering a distinctive answer. Pakistan, with its pragmatic and forward-looking approach, is exactly the kind of partner that makes this possible.

Weather knows no borders. The China-Pakistan cooperation on MAZU also stands as a practical statement about how AI should evolve:

Technology must serve human safety and development; innovation must be open and shared; capacity building must move in lockstep with application.

And perhaps the quiet evolution is happening right now in a Beijing classroom this summer – where a Pakistani meteorologist practices his Chinese, one sentence at a time, building bridges that no firewall can block.

The author is a chief reporter with the Global Times. linxiaoyi@globaltimes.com.cn