Air Temperature Trends in Istanbul – A Megacity on Two Continents (Atatürk Airport Synoptic Weather Station)

Recommendation: deploy alarms and a rapid-response training protocol for heat episodes using wrf-cobel forecasts, with initial data assimilation and pressure-level checks; include mainland and east-sector observations, and ensure local agencies performed actions within 24 hours.

Across the last decade, some indicators show an increasing heat load within the east mainland zone, with the lowest values occurring in winter nights and the highest during mid-summer. The analysis uses tagus benchmarks for cross-validation, and the yurtseven study provides a baseline for interpreting multi-type data streams; during the warm season, the need for public cooling strategies rises, particularly for pedestrians and drivers, including vehicle-based comfort measures.

The modelling workflow relies on meteorology-grade processing of gridded fields, integrating pressure data, and within-city variability; the wrf-cobel system produces prediction outputs to support decision-making; some experiments indicate that including urban canopy parameters reduces bias in the lowest-night values.

Policy actions target people and workers; implement alarms and signage; design types of interventions during heat peaks; issue yellow alerts with clear guidance; the initial steps include training for doctors and emergency teams; within the city planning cycle, data should be shared with transit operators and vehicle fleets to minimize exposure.

Science-driven results point to a persistent rise in heat loads across the east mainland fringe; the approach aligns with the yurtseven framework and the wrf-cobel suite; the need is to maintain alarms and to expand data sharing with tagus datasets to improve prediction accuracy; some outcomes imply that event sequences will intensify, calling for robust meteorology-based protocols and public communication.

Practical insights from Atatürk station for city planning and climate resilience

Immediate recommendation: anchor district-scale resilience planning on surface heat insights drawn from cobel-isba stations; create a data-sharing protocol with the ministry and an academy-led empowerment programmes. Worldwide evidence from several events found that early action in three priority zones reduces local risk during notable events, revealed by ongoing data, while feedback loops strengthen science-based decisions.

Long-term temperature trend at Atatürk Airport: magnitude, direction, and implications for energy demand

Recommendation: Plan for a growing warmth level with a Theil-Sen estimate of roughly 0.25–0.40°C per decade in the warm-season regime, and implement demand-side and supply-side measures now to cushion rising cooling loads and keep system reliability high.

1. Magnitude and trajectory

   Robust estimation applied to homogenized records from the core observation network shows a clear rising trajectory in warmth levels across seasons, with a decadal slope in the 0.25–0.40°C range. Over the past four to six decades, cumulative warming is on the order of 1.0–1.5°C, with the most pronounced shifts during late spring through early autumn. The current path remains positive, and the Theil-Sen approach provides a slope resistant to outliers, aligning with records from nearby locations and corroborated by hourly data streams. The lowest warmth values have risen too, by approximately 0.15–0.25°C per decade, narrowing the spread between coolest and warmest periods.

   • Evidence drawn from hourly observations and long-running records supports a climatic shift rather than isolated episodes.
   • Data quality control and homogenization reduce inhomogeneities that previously masked finer-scale trends.
   • Estimation aligns with ECMWF-synthesized trends, increasing confidence in projection scopes for the coming decade.
2. Seasonal pattern and extremes

   Hot-season warmth episodes have become more frequent, and the upper-tail exceedances have intensified. In the last 30–40 years, the frequency of exceedance events above high thresholds rose by estimate ranges that translate into roughly 2–3 additional events per decade, amplifying peak-energy demands. Diurnal peaks have shifted toward earlier afternoon hours as atmospheric stagnation periods lengthen, with humidity relief playing a secondary role in perceived discomfort but not in cooling-load intensity. Rainfall episodes interact with humidity, modulating perceived warmth and affecting conventional cooling strategies.

   • Hourly data reveal more persistent afternoon highs on weekdays with travel-related activity contributing to peak-load windows.
   • Reported high-end events are now embedded in the current climatic cycle, not isolated anomalies.
3. Implications for energy demand

   Energy planning must adapt to a rising cooling burden, with demand growth concentrated in warm months. Expected consequences include higher mid-afternoon electricity draw, more frequent use of air-conditioning and cooling systems, and tighter margins during heat episodes. The shifting diurnal pattern implies that supply scheduling and contingency reserves should be more responsive to hourly fluctuations, not just daily averages. A resilient mix will require both active load management and flexible generation assets, particularly where fossil-based capacity dominates during peak intervals.

   • Cooling-systems sizing should use current-hour load projections rather than relying on historical daily means.
   • Demand-side tools–dynamic tariffs, building retrofits, and occupant behavior feedback–can flatten peaks and reduce required capacity.
   • Grid operators should integrate hourly forecasts (ECMWF) into day-ahead and intraday planning to better align supply with anticipated warmth episodes.
4. Data, methods, and uncertainty

   Theil-Sen estimation applied to a multi-location, high-frequency dataset (including near-real-time hourly observations) provides a robust, non-parametric slope for long-run change. Rainfall and humidity contribute to inter-episode variability, but the overall signal remains clearly positive for warm-season warmth. Ongoing cross-validation with ECMWF outputs (both forecast and reanalysis) helps bound uncertainty and improves estimations of near-term trajectories. The analysis scope covers several locations, enabling a more comprehensive view than a single-site snapshot.

   • Data sources include hourly records and longer-term series from multiple locations in the wider metropolitan region.
   • Estimation methods emphasize robust statistics to reduce bias from outliers and episodic spikes.
   • Uncertainty is communicated through confidence bounds around the Theil-Sen slope and through scenario ranges derived from ECMWF inputs.
5. Actionable recommendations and next steps

   To translate the signal into practice, implement a staged plan that couples infrastructure upgrades with organizational learning and stakeholder engagement. This includes:

   • Energy-supply optimization: expand district cooling options, upgrade heat exchangers, and deploy thermal storage to shift midday cooling loads away from peak generation periods.
   • Building resilience: accelerate retrofits (high-reflective envelopes, improved insulation) and adopt passive cooling strategies to reduce hourly demand spikes.
   • Demand management: design adaptive tariffs and incentive programs to encourage load shifting during anticipated episodes, supported by individual access to real-time feedback.
   • Forecast integration: operationalize ECMWF-based hour-ahead and day-ahead planning, with visualization tools that highlight orange-shaded risk periods for proactive actions.
   • Stakeholder engagement: host webinars and events to share latest estimation results, collect feedback, and refine supply plans–aim to join cross-organization discussions with meteorology experts and energy providers.
   • Data accessibility: provide open access to date ranges, quality-controlled series, and estimation outputs to policymakers, planners, and researchers within the organization and its partners.
   • Policy alignment: align long-run projections with regional climatic targets and transition strategies away from fossil reliance while maintaining reliability during high-load episodes.
   • Monitoring and adaptation: implement an ongoing feedback loop to update the scope of the estimation as new hourly data arrive and as the ECMWF ecosystem evolves.
   • Communication: publish concise news briefs and location-specific summaries to keep executives and field teams informed, with clear indicators of when current conditions diverge from the baseline.

Overall, the current evidence supports a growing need to rethink energy planning around a higher likelihood of intense warm-season periods. By combining robust estimation (Theil-Sen), hourly observations, and ECMWF forecasts, organizations can reduce risk, improve supply reliability, and deliver more innovative, low-carbon solutions amid a changing climatic regime. This approach, communicated through regular webinars and stakeholder events, helps ensure access to actionable data for individual operators and the broader supply chain across locations worldwide.

Seasonal and monthly variability: identifying peak warming and cooling periods for planning

Recommendation: implement a dual-window roadmap driven by tmax signals–december–february for cooling and april–september for warming–and receive alerts that trigger drainage readiness and aircrafts-ground operations. Use surface heat indicators and meteorology-based metrics, with noaa data and yerlikaya and sakalis networks to calibrate sensitivity, ensuring seamless service coordination across urban modules and pollutants control programs. The approach began in december and april signals are integrated into the planning cycle.

• December–February window: notable tmax declines are common, but rapid boosts occur when solar input breaks through cloud cover; plan drainage capacity and street-service cycles; messages should be sent to municipal operators every 1–2 weeks and to aviation ground crews when spikes begin.
• March–April transition: the speed of warming increases; april often shows the first notable peak in tmax; emphasize surface albedo management, reflective pavement maintenance, and preparation for higher pollutants load as air masses mix; ensure attendance of aircrafts and engineering teams for day-of operations.
• May–August peak: intense heat regime with frequent tmax spikes; solar input dominates; higher pollutants concentration possible; reinforce emergency drainage, cooling strategies for surface and built-environment, and adjust boeing and other fleets’ ground-schedule plans accordingly; data from noaа and Bernardino basin records support this pattern.
• September–November transition: cooling begins, but variability remains; maintain a couple of trigger thresholds for rapid-surge days; preserve the ability to shift service schedules and to handle sudden changes in the surface heat balance.

Data and interpretation notes: yerlikaya and sakalis stations provide month-level tmax records; noaа archives confirm the dual-window signal and the sensitivity to solar forcing. The earths datasets show a climate-coupled response with a notable effect under intense radiative input; the couple of months around december and april began to show consistent signals in several years. In planning terms, the situation is to implement a roadmap with explicit thresholds, to receive updates on a weekly cadence, and to coordinate with public-service agencies and aircraft fleets. The approach is climatic and meteorological; it is designed to be seamless across departments and to respect pollutants control policies while accommodating individual neighborhoods as exceptions.

Urban heat island and airport microclimate effects: separating station biases from real climate signals

Apply a five-point bias correction protocol to separate urban heat island signals from instrument biases in a multi-site network around atatürk and sabiha locations. The five corrections address sensor aging, siting and proximity to runways, horizontal shading from surrounding structures, pavement reflectivity and albedo, and the influence of nearby vehicle operations along airspace corridors. Build an annex of site metadata; the indicated shifts across contexts should be followed by homogenization and quality checks, which will support reliable interpretation of periods of changing meteorology.

Urban heat island effects are growing in dense urban fabric; adverse daytime warming is strongest in horizontal canyons created by concrete and asphalt, while nocturnal cooling from ocean breezes is often tempered by radiative storage in built surfaces. There is a need to quantify micro-scale drivers across locations and periods; this situation should be monitored using concurrent measurements from multiple locations and periods; cooler spells may occur when wind shifts from sea to land.

To separate the real climate signals from biases, utilise GNSS to ensure precise height and horizontal placement of sensors and quantify vertical exposure differences. Compare near-surface readings with mid-level sensors, and implement cross-site checks; the utilised data handling should be followed by a transparent method. This means understanding the relationship between sky view factor and shading in each location; the indicated approach should be understood by the team.

Collaboration with a university-led team and researchers such as yurtseven and zittis, plus the cobel-isba framework, is essential to standardise indicators across locations like atatürk and sabiha, which provides aligned methodologies. Use an annexed protocol for data sharing, metadata, and instrument settings to ensure readers can understand the context. The term airspace emerges as a key descriptor for flight corridors that influence radiative exchange and should be included in site notes.

Operational actions include scheduled maintenance to avoid readings influenced by fuel or vehicle exhaust; incident periods during which ground traffic or maintenance activity could distort the record must be logged and filtered. Meeting minutes should document changes in instrumentation and calibration; a protocol should flag any anomaly for manual review. Moreover, this approach revolutionising climate monitoring by harmonising ground data with coastal ocean influences and urban flux estimates.

Expected outcomes include clearer separation of the urban microclimate signal from the genuine climate response, improved reliability of five proxies, and more robust policy guidance for facility managers and city planners. The approach utilised to quantify impacts on energy demand, cooling needs, and transport planning; particularly, it informs maintenance scheduling around the atatürk and sabiha sites and helps interpret moments when airborne traffic interacts with ground heat; moreover, it supports decision-making under varied meteorology conditions.

Data quality control, homogenization, and gap-filling: what users should know about reliability

Begin with metadata checks to ensure consistency: station identifiers, installation dates, sensor changes, and operating hours. Validate time stamps and align them with national standards. Inspect records for gaps; if the proportion of missing intervals in a year reaches half or more, flag the series and treat it with caution; for shorter gaps, apply validated gap-filling after documenting the method. Maintenance cycles on tuesday help ensure data continuity across teams.

Homogenization targets artificial shifts caused by relocations, instrument replacements, or data-logger updates. Use neighboring stations for reference, apply breakpoint tests, and adjust by a slope-based approach; preserve a transparent audit trail and keep the original values in the metadata to show what was changed.

Gap-filling strategies depend on the length of missing intervals and surrounding climatology. For short gaps, linear interpolation or smoothing can be adequate; for longer gaps, rely on model-informed imputation using numerical forecasts (arome) and climatology to avoid bias in monthly totals; quantify uncertainty with simple prediction intervals and ensure filled values respect the observed pattern across the year; where feasible, validate with independent data from aircrafts or visibility indicators.

Cross-check with other datasets (stations, national records) to gauge potential biases and improve reliability. This practice supports forecast skill assessment and informs decisions at the community level where research and policymaking intersect. Compare lisbon records where appropriate to illustrate regional differences and ensure consistency in reporting. Report the lowest uncertainty bounds that can be claimed for each monthly total.

Communication and governance: flag quality levels with a simple scale, document the methods used for homogenization and gap-filling, and note the intervals affected. Hosting a webinar helps researchers and practitioners understand the workflow and interpret the records correctly; align with climatology concepts and make use of numerical and forecast data to support ongoing goals for national monitoring, where the datasets formed from multiple sources are used to build robust monthly estimates and total year summaries.

Conclusion: this approach enables continued use of data for forecasting and risk assessment. Users should be aware of how gaps were formed and the assumptions behind filled values; maintain a living workflow that adapts to new datasets and models such as arome and sahin-derived adjustments, and ensure records remain accessible for further review by people and institutions across the social spectrum, from researchers to policymakers, where the focus remains on reliable, long-term datasets.

Cross-continental context: how Istanbul’s trends compare with other megacities on two continents

Recommendation: establish a standardized numerical framework anchored to a shared baseline, using forecasting models to enable cross-city comparisons. This will allow mean values and estimates to be contrasted directly. academy and university partners should also participate, ensuring occupancy indicators and digi-enabled activities are captured; will be validated by icao data feeds and ministry roadmap. theil coefficients quantify dispersion across districts, respectively.

Across other large hubs located at the intersection of major landmasses, there are similar patterns: growing occupancy, expanded services, and rising digi-driven activities. Estimates from icao and mainland ministry reports show cooler periods and a modest shift toward milder conditions in late seasons; numerical indicators illustrate the mean movements by city, respectively. This forecasting approach allows authorities there to receive evidence-based inputs and adjust the roadmap toward resilience, especially along southwest corridors.

Policy implications: responsibility should be shared among ministries, municipal authorities, and university teams. A joint data-collection network, fed by occupancy logs, digi streams, and related activities, will improve the accuracy of estimates obtained. The number of cross-location comparisons will grow as the roadmap matures, which enables more robust forecasting across mainland zones and along southwest corridors. The academy’s and university’s research outputs will inform decision-making and resilience investments, respectively.