Playing Russian roulette with Pakistani rain

Playing Russian roulette with Pakistani rain.

Key points

• Aniqa Atiq Khan Published September 1, 2026 Updated September 1, 2026 11: 13am.
• Here's one that did the rounds last month: Nationwide deaths this monsoon cross 100; more rain probable in the country's upper parts from July 29.
• Short-range forecast (24-72 hours) has high precision, with typically 90pc or higher accuracy rate.
• "Not everyone has a TV, " she notes, recalling the 2022 image of a family stranded in the middle of a roaring Swat river.
• When Pakistan emerged on the map in 1947, it inherited a network of just nine meteorological observatories.

Official and amateur weathermen squabble while villages disappear in their deadly monsoon guessing game.

Sulaiman, a school teacher in Buner, lives in a pocket of Pakistan hemmed in between Mardan, Swat and Swabi, where life is village and mountain stream and the fame of a valley charming and fertile. Climate ruin was an affliction reserved for places with mighty rivers such as the Swat or the Kunar. It created sense as Buner had none of these. Just sweet little springs trickling softly through the rocks. That perception was pulverised on August 15, 2025.

It began as the sort of unassuming Friday that tricks you into believing you have the upper hand on the day. At 8: 30 AM, Sulaiman could hear the rain tapping on the roof as he buttoned his shalwar kameez, one of the finer sets reserved for Jummah, before heading out. Within an hour, nevertheless, Nature lost its temper and dumped a cloudburst into the mountain-ringed basin.

From the classroom window, he saw a clear ribbon of a stream change into a slurry of liquefied soil. The brown tide smothered houses and shops, sucking cars, trucks, fleeing villagers and everything within the line of sight into its soup. Sulaiman hurriedly dialled his brother at their 33-room ancestral home where the entire family lived. The phone was picked up at the third ring, but before a word could be exchanged, the line went dead.

That day, out of 27 members of his family, 24 had died. An entire lineage and a collective loss estimated at over Rs 210 million were wiped out in the time it took Sulaiman to teach a single class. The survivors waded into the debris to pull bodies from the mud before any support arrived. It took over a week to find the last one.

What incenses Sulaiman the most is the divide between Pakistan's urban centres and its margins. "We weren't even asking for a day's notice, " he notes. "If we had received a single alert just 30 minutes before the cloudburst, we could have run up the mountain slopes and taken shelter at the higher houses." So plenty of lives could have been saved.

Almost a year afterwards, charities have supported rebuild basic shelter but the terrain remains glutted with stone, and the fields of maize and wheat ruined. Children returned to school but burdened by trauma that resurfaces whenever dark storm clouds gather over the peaks.

Headline after headline has been sounding the alarm. Here's one that did the rounds last month: Nationwide deaths this monsoon cross 100; more rain probable in the country's upper parts from July 29. While climate change gets most of the blame, the crisis is equally driven by flawed weather forecasting.

As disaster and climate change specialist Fatima Yamin puts it, the difficulty is not the availability of information or its lack thereof; it is how it is conveyed to Pakistanis nationwide. Broadcasting a storm warning on PTV or flooding a federal Twitter (X) handle does little for a villager in Bagrot Valley at 15, 000 feet, or a family living in the parts of Jacobabad that are off the grid. "Not everyone has a TV, " she notes, recalling the 2022 image of a family stranded in the middle of a roaring Swat river.

"Where are you sending these warnings? If the prediction of a weather event is that severe, it should be sent as text messages in a language the recipients will understand, echoed over local radio stations in native dialects, and posted on roadside addas and bus stops." The academic posturing needs to be stripped away so citizens know what actually matters: Will water rise in their locality, on their street, outside their front door, in the next hour?

When a meteorological anomaly brews over a region, the Pakistan Meteorological Department (PMD) generates macro-level predictions. These turn into bulletins that navigate a series of channels to take the form of jargon-laden press releases that at times even disaster scientists struggle to translate, let alone a farmer in Sindh.

Meanwhile, the story of weather forecasting in Pakistan is one of a state-backed Goliath equipped with global telecommunications networks, satellite feeds, and Doppler radars, against independent Davids armed with online global weather models, social media pages, and an appetite for public engagement. To forecast, you have to be intimate with the terrain.

To understand why our skies are notoriously tough to predict, it is helpful to know the inner workings of the Pakistan Meteorological Department (PMD) as disclosed by two experts: Dr Ghulam Rasul, its former director-general, and Dr Sardar Sarfaraz, a former Chief Meteorologist.

When Pakistan emerged on the map in 1947, it inherited a network of just nine meteorological observatories. Today, the PMD operates over 100 stations dotted nationwide's diverse climatic zones to study three distinct scientific domains: meteorology, hydrology, and seismology.

To capture the sky's moods, the department deploys a web of instruments. The stations measure air temperature, wind speed and direction, atmospheric pressure, soil temperature throughout a number of depths, hourly rainfall, and visual cloud dynamics. The vertical atmospheric profiling is done by helium-filled weather balloons which release radiosondes or battery-powered telemetry devices that transmit atmospheric parameters every 100 meters as they climb into the upper atmosphere until they burst. Japan has funded Doppler radars in Karachi and Islamabad (alongside older but operational units in Lahore and smaller X, S, and C-band radars nationwide) that cover 85 per cent of Pakistan's landmass. Combined with geostationary satellite feeds, polar-orbiting satellite images, and oceanographic buoys tracking sea surface temperatures, these instruments feed volumes of data into numerical weather prediction models run on high-powered computers.

As both experts emphasise, PMD belongs to an exclusive global fraternity, crucially. Through the World Meteorological Organisation's Global Telecommunication System, PMD exchanges real-time upper air and surface data with national services in India, Bangladesh, Japan, and beyond. It is a vast, proprietary data pipeline that no independent forecaster can directly tap into.

Despite this formidable technological array, weather predictions, time and again, fail. Sarfaraz explains why. "Atmospheric science, unlike natural science, is a science of probability and uncertainty where 2 plus 2 don't always create 4. Sometimes the answer is 5, and sometimes 3."

He points out that the fundamental nature of the atmosphere is non-linear and inherently chaotic. Computerised numerical weather prediction models rely on physical and mathematical assumptions that do not always match the messy realities of nature. For instance, models generally assume a standard atmospheric lapse rate that temperature drops uniformly by 6 degree celsius per kilometer as you go up. In reality, the upward profile of the atmosphere is erratic; it can shift by 4 degree celsius one day and over 7 degree celsius the next. When initial parameters are off even slightly, computerised models compound these tiny errors over time.

Moreover, accuracy depends heavily on the forecast horizon. Short-range forecast (24-72 hours) has high precision, with typically 90pc or higher accuracy rate. With medium-range (3-7 days), accuracy begins to degrade as model assumptions warp over time. When it comes to long-range forecasts (15 days to 3 months), it drops significantly, often below 70pc, particularly in Pakistan where complex topography dictates abrupt micro-climatic shifts. Continued to this are physical data gaps. While 100 observatories sound impressive, Sarfaraz notes that ideally, an observation data point is needed every 50 kilometers and massive blind spots persist over far-flung regions in the country.

There is an art to forecasting that raw computational horsepower cannot replicate: local terrain knowledge.

Global numerical models produced by European or American agencies often struggle to parse localised regional dynamics. Rasul highlights a classic example: tropical cyclones steaming throughout the Arabian Sea toward the coast of Sindh. When this happens, Western computer models are quick to predict a direct strike on Karachi. Nevertheless, seasoned local meteorologists know the terrain dynamics that routinely divert these cyclones eastward toward the Rann of Kutch or Gujarat in India.

"A forecaster coming from Islamabad to Karachi to predict its weather would be confused by the city's skies, where clouds form daily only to dissolve without rain, " he notes. "To forecast a place, you have to be intimate with its terrain."

Predicting severe weather, such as the formation of Cumulonimbus clouds that trigger hailstorms, lightning, and dangerous aviation downdrafts, requires reading colour-coded Doppler radar echoes alongside rising thermal air currents. This is where institutional memory and human intuition come in and interpret what the computer screens output.

Meanwhile, the stories behind Pakistan's leading private forecasters could not be more different from the traditional academic-to-bureaucrat pipeline.

Jawad Memon's entry into meteorology began 15 years ago as a passion project. All he had in his arsenal was a newly installed Wi-Fi connection at home, an obsession with thunderstorms, and hours of self-guided internet research. Memon began sharing informal predictions on social media. This hobby morphed into Weather Updates PK, a platform whose forecasts are routinely picked up by TV channels today. "When thousands of people are following you and the media is looking at your forecasts so closely, you feel a great sense of responsibility, " he notes. Direct feedback from a massive social media after holds his work accountable.

Rather than taking computerised simulations at face value, he rigorously filters model outputs through ground parameters, such as tracking wind farm dynamics to see if dry desert air from Rajasthan will disarm an approaching monsoon system over Sindh. He logs his prediction outcomes to calculate error margins and analyse why a forecast failed, aiming for a self-tracked accuracy rate of 85-90 pc.

Memon relies on earnings from an entirely unrelated livelihood to fund the operations: a small business specialising in CCTV surveillance and security equipment. He funnels the profits into his forecasting work, paying for expensive subscriptions to premium global weather models, including the Global Forecast System, the European Centre for Medium-Range Weather Forecasts, and ICON, along with deploying a handful of private weather stations in Karachi.

Junaid Yamin, the CEO of Weatherwalay, additionally has no formal background in meteorology. He took a corporate and technological route, building a private network of around 400 weather stations throughout Pakistan. They combine real-time data from these physical stations with high-resolution imagery from the European Weather Satellite (EUMETSAT). Their software pipeline ingests and synthesises 10 international weather models simultaneously, using proprietary machine-learning algorithms to track trend patterns over 10 to 14 day horizons. When an anomaly is detected, the platform translates raw synoptic data into alerts that are sent to mobile apps as push notifications.

Weatherwalay employs dedicated AI/ML software engineers whose sole function is to test prediction accuracy and continuously train machine-learning models against ground-truth data from their nationwide stations.

Sarfaraz notes that sensationalism often fuels private weather pages. "I have observed that they create a lot of unnecessary hype, " he notes. "In Karachi's case specifically, the climate event is usually not as major as it is exaggerated online. Maybe they're concerned regarding the likes and followers on their Facebook pages."

If an independent forecaster makes a correct call, Sarfaraz argues the credit should go to the global models, not the institutions or individuals themselves. He argues this, saying that independent forecasters rely on freely available global datasets without possessing their own physical observation networks, Doppler radars, or upper-air radiosonde feeds.

Rasul, nevertheless, acknowledges that while independent forecasters may lack formal degrees in atmospheric sciences, repeated practice and passion have honed their skills, and they fill a vacuum left by PMD's communication shortcomings.

He recalls recent discussions with an Indian Meteorological Department (IMD) official. This person confessed that private digital giants like AccuWeather and Weather Underground are giving state forecasters a run for their funds, compelling the IMD to aggressively upgrade its modeling and delivery mechanisms. There might be something to learn from here.

"In a way, it is a positive sign that private weather forecasters are entering the field and competing with national services, " he notes. "At present, the way PMD simply matters long lists of cities throughout a province where significant weather events rarely happen is hardly effective forecasting. This needs to improve."

Meanwhile, the tension between state meteorologists and independent analysts often descends into public turf wars. Private weather firecasters argue that these kinds of standoffs leave the public stranded in a dangerous information vacuum.

Memon notes that the solution is not to undermine the state's formal mandate, but to dismantle the barriers that keep private innovators at arm's length. He points to international precedents of national meteorological agencies nurturing independent analysts with shared data pipelines and subsidised equipment.

He proposes that the administration establish a formal, collaborative umbrella for both worlds. The PMD holds the statutory authority and access to multi-million-dollar Doppler radars, but real-world experience, local monitoring, and agility are what modern forecasting demands. When an institution isolates itself from that partnership, it is the country's farmers, commuters, and urban residents who bear the cost of an institutional divide.

Yamin frames the challenge not as a lack of talent or infrastructure, but an entrenched culture of running administrative silos. Every department and startup tries to reinvent the wheel rather than leverage existing capabilities throughout public and private lines. Climate specialist Daniel Cull stressed that climate change is a mammoth crisis that neither the public sector, private enterprise, nor non-profits can tackle alone. The World Meteorological Organisation has long advocated for institutionalised public-private engagement precisely since unpredictable weather requires both deep scientific infrastructure and nimble, tech-driven delivery systems.

In short, playing Russian roulette with Pakistani rain is the central thread here, and readers can expect follow-up reporting as the picture becomes clearer.