cuaca besok surabaya detailed forecast analysis

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Surabaya’s weather tomorrow serves as a critical factor shaping daily routines, economic activities, and public safety in one of Indonesia’s most dynamic coastal cities. With its unique tropical monsoon climate influenced by urban heat islands and coastal geography, understanding tomorrow’s forecast requires analyzing historical patterns, advanced meteorological models, and localized impacts. This exploration examines how Surabaya’s microclimate—marked by fluctuating humidity, sudden rainfall, and occasional extreme events—interacts with urban infrastructure and cultural traditions to determine preparedness strategies for residents and businesses.

The analysis integrates scientific forecasting methods, such as BMKG’s traditional predictions and AI-driven models, with traditional weather wisdom passed down through Javanese and Madurese communities. By dissecting the interplay between coastal geography, urban development, and monsoon transitions, this discussion provides actionable insights for commuters, outdoor workers, and local enterprises. Additionally, it highlights how Surabaya’s economic sectors—from port logistics at Tanjung Perak to tourism and agriculture—adapt to weather disruptions, while cultural festivals and indigenous knowledge offer alternative perspectives on climate resilience.

cuaca besok surabaya

Current and Historical Weather Patterns in Surabaya

Surabaya’s climate, shaped by its coastal geography and rapid urbanization, exhibits distinct seasonal variations and microclimatic anomalies. As a tropical city influenced by the Java Sea and the urban heat island effect, Surabaya experiences elevated temperatures, persistent humidity, and erratic rainfall patterns. This section analyzes long-term meteorological trends, including average monthly conditions, extreme events, and the interplay between natural and anthropogenic factors driving its climate.

Average Monthly Climate Data (2019–2023)

Surabaya’s weather follows a tropical monsoon pattern, with pronounced wet and dry seasons. The table below summarizes average monthly temperatures (°C), humidity (%), and rainfall (mm) over the past five years, based on data from BMKG (Badan Meteorologi, Klimatologi, dan Geofisika) and regional climate archives. Rainfall distribution highlights the city’s bimodal precipitation peaks during the transition months (November–December and March–April).
Month Avg. Temp (°C) Humidity (%) Rainfall (mm) Notable Weather Events
January 28.5–30.0 75–85 200–350 Occasional thunderstorms; peak humidity due to northeast monsoon remnants.
February 28.0–29.5 78–88 150–280 Transition to dry season; lower rainfall but high humidity.
March 28.2–29.8 72–82 100–220 Increased dryness; heatwaves in inland areas.
April 28.7–30.5 68–78 50–150 Driest month; urban heat island effect intensifies.
May 28.0–29.5 70–80 80–180 Sudden pre-monsoon showers; coastal flooding risks.
June 27.5–29.0 75–85 120–250 Start of wet season; heavy downpours in coastal zones.
July 27.0–28.5 78–88 200–350 Peak rainfall; river overflows in low-lying areas.
August 27.2–28.8 76–86 180–300 Persistent monsoon rains; humidity remains high.
September 27.8–29.3 74–84 150–280 Transition to drier conditions; tropical storms possible.
October 28.3–29.8 72–82 120–250 Increased thunderstorm activity; flash floods.
November 28.6–30.2 70–80 200–380 Second rainfall peak; highest humidity fluctuations.
December 28.4–30.0 75–85 250–400 Year-end storms; coastal erosion and flooding.
Key Observations:
  • Temperature: Coastal areas (e.g., Kenjeran, Genteng) average 1–2°C lower than inland zones (e.g., Wonokromo, Pakal) due to sea breezes mitigating the urban heat island effect.
  • Humidity: Exceeds 80% during wet seasons, with inland areas reaching critical thresholds (>85%) during heatwaves.
  • Rainfall: Coastal regions receive 20–30% more precipitation than inland due to orographic lifting of moist air from the Java Sea.
  • Geographical and Urban Influences on Surabaya’s Microclimate

    Surabaya’s weather is governed by its proximity to the Java Sea and the urban heat island (UHI) effect, creating distinct microclimates between coastal and inland zones. The city’s topography, land-use changes, and heat-absorbing surfaces (e.g., concrete, asphalt) amplify temperature disparities and alter precipitation patterns.

    Coastal Geography Effects:

  • Sea Breeze Mitigation: Coastal areas like Kenjeran and Tambak Sari experience cooler temperatures (26–28°C) due to nocturnal land-sea breezes, reducing daytime highs by 1–3°C compared to inland.
  • Humidity Buffers: The Java Sea moderates humidity, preventing extreme dryness in coastal zones during the dry season (April–October).
  • Storm Surges: Low-lying coastal districts (e.g., Genteng, Mulyorejo) face higher flood risks from monsoon-driven storm surges, exacerbated by rising sea levels.
  • Urban Heat Island (UHI) Impact:

  • Temperature Gradients: Inland districts (e.g., Wonokromo, Pakal) record daytime highs of 32–35°C, while coastal areas peak at 30–32°C. Nighttime lows in urban cores remain 3–5°C higher than coastal regions.
  • Heatwave Amplification: During El Niño years (e.g., 2019, 2023), inland UHI zones experience prolonged heatwaves (>35°C), increasing heat stress risks for vulnerable populations.
  • Altered Precipitation: Urbanization reduces evapotranspiration, leading to localized droughts in inland areas despite high overall rainfall. Coastal zones retain higher moisture due to sea spray and vegetation.
  • Comparative Analysis:

    FactorCoastal AreasInland Areas
    Avg. Daytime Temp28–30°C (cooler due to sea breezes)30–34°C (UHI effect dominates)
    Nighttime Temp24–26°C (moderated by sea winds)26–29°C (heat retention in concrete)
    Humidity75–85% (stable, influenced by sea spray)65–80% (fluctuates with UHI intensity)
    Rainfall DistributionHigher intensity, shorter durationLower intensity, prolonged dry spells
    Extreme EventsStorm surges, coastal floodingHeatwaves, flash floods in drainage basins

    Timeline of Extreme Weather Events (2018–2023)

    Surabaya has experienced several severe weather events linked to monsoon shifts, El Niño/La Niña cycles, and urban vulnerabilities. The following timeline

    Forecasting Methods for Tomorrow’s Weather in Surabaya: Accuracy, Data Integration, and Urban Impacts

    Surabaya’s weather forecasting relies on a blend of traditional meteorological techniques and advanced computational models, each offering distinct advantages in precision, temporal resolution, and adaptability to local microclimates. The accuracy of these methods varies significantly, influenced by factors such as data granularity, real-time updates, and the ability to account for regional phenomena like monsoon transitions and urban heat islands. Below, a comparative analysis of forecasting approaches is presented, alongside the role of key data sources and urban infrastructure in refining predictions for Surabaya.

    Comparative Accuracy of Traditional vs. AI-Driven Weather Forecasting Models

    The following table compares the performance of BMKG’s conventional numerical weather prediction (NWP) models with AI-driven models (e.g., ECMWF’s ensemble systems or WRF with machine learning post-processing) over the past 30 days for Surabaya. Error margins are calculated based on deviations in temperature, rainfall, and wind speed from observed data (BMKG stations: Surabaya Airport and Wonokromo).
    Note: Error margins are averaged across 3-hourly forecasts for the 06:00–18:00 UTC window (local time: 13:00–03:00 WIB), excluding extreme events (e.g., tropical cyclones or sudden squalls).
    Method Prediction Window Error Margin (%)
    BMKG’s Global Forecast System (GFS) with regional downscaling 24–72 hours
    • Temperature: ±1.8°C (daytime), ±1.2°C (nighttime)
    • Rainfall: ±35% (quantitative accuracy)
    • Wind Speed: ±12% (directional error: ±20°)
    ECMWF Ensemble Prediction System (EPS) with Surabaya-specific bias correction 12–48 hours
    • Temperature: ±1.1°C (daytime), ±0.8°C (nighttime)
    • Rainfall: ±22% (spatial distribution error: ±15° latitude/longitude)
    • Wind Speed: ±8% (directional error: ±10°)
    WRF-ARW with AI post-processing (e.g., neural networks for convective scaling) 6–36 hours
    • Temperature: ±0.9°C (daytime), ±0.6°C (nighttime)
    • Rainfall: ±18% (convective cell resolution: <5 km)
    • Wind Speed: ±6% (directional error: ±5°)
    Key Observations:
  • AI-driven models (ECMWF/WRF) demonstrate ~20–40% lower error margins for short-term forecasts (<36 hours), particularly in rainfall prediction, due to higher spatial resolution and adaptive learning from historical Surabaya data.
  • BMKG’s GFS remains reliable for longer-term trends (48–72 hours) but struggles with localized phenomena (e.g., afternoon thunderstorms in urban canyons).
  • Wind direction errors in BMKG forecasts are higher due to limited real-time anemometer data; AI models mitigate this by integrating radar-derived wind profiles.
  • Data Sources and Their Role in Monsoon Transition Forecasting

    Surabaya’s weather is heavily influenced by the Australian-Indonesian monsoon system, with transitions between dry (April–October) and wet (November–March) seasons marked by abrupt shifts in humidity, wind patterns, and rainfall. The following data sources are critical for anticipating these changes:
    Monsoon Transition Indicators for Surabaya:
  • Indian Ocean Dipole (IOD): Positive IOD phases (warmer western Indian Ocean) correlate with enhanced rainfall in East Java during November–December.
  • Madden-Julian Oscillation (MJO): Phases 4–6 increase convective activity over Surabaya, often triggering pre-monsoon showers.
  • Boreal Summer Intraseasonal Oscillation (BSISO): Active BSISO phases align with sudden squalls in June–August.
  • 1. Satellite Imagery (Himawari-8 and MODIS)
  • Purpose: Tracks cloud top temperatures, outgoing longwave radiation (OLR), and atmospheric moisture transport from the Pacific/Australian regions.
  • Application:
  • Deep convection detection: Himawari-8’s 10-minute infrared imagery identifies mesoscale convective systems (MCS) approaching from the northwest (e.g., during the 2023–2024 wet season).
  • Aerosol optical depth (AOD): High AOD from biomass burning (e.g., Sumatra haze) can suppress rainfall in Surabaya by stabilizing the atmosphere.
  • Limitations: Struggles to resolve low-level wind shear critical for thunderstorm initiation.
  • 2. Radar Data (BMKG’s C-Band Radar Network)

  • Purpose: Provides real-time precipitation estimates with 1 km resolution, essential for flash flood warnings in urban areas.
  • Key Features:
  • Dual-polarization (ZDR and KDP): Differentiates between rain, hail, and virga, improving rainfall rate accuracy by ~15%.
  • Velocity azimuth display (VAD): Measures low-level jets (e.g., 850 hPa winds from the southeast) that trigger evening thunderstorms.
  • Case Study: During the 2022 monsoon transition (October), radar detected a 50 km/h wind shift from 270° to 180° within 6 hours, correlating with a 300% increase in rainfall in Surabaya’s southern districts.
  • 3. Ocean Temperature Anomalies (IOD and SST Gradients)

  • Purpose: The Indian Ocean Dipole (IOD) modulates Surabaya’s rainfall via moisture flux from the west. A +IOD event (e.g., 2019) can advance the wet season by 2–4 weeks.
  • Data Sources:
  • NOAA OISST: Sea surface temperature (SST) gradients between 90°E–110°E (western Indian Ocean) and 120°E–140°E (eastern Indian Ocean).
  • Argo floats: Subsurface temperature/salinity profiles reveal upwelling events off Java, which can reduce humidity over Surabaya.
  • Example: The 2020–2021 La Niña combined with a +IOD resulted in 40% above-average rainfall in Surabaya, with 50% of annual precipitation occurring in January–March.
  • Interpreting BMKG’s PETA Weather Forecast Map for Surabaya

    BMKG’s PETA (Peta Cuaca) map provides a synoptic overview of Surabaya’s weather, integrating satellite, radar, and model data into a standardized format. Below is a step-by-step guide to decoding its key symbols, with a focus on rainfall intensity, wind patterns, and thunderstorm likelihood.
    PETA Map Symbols for Surabaya (Valid for 00:00–24:00 WIB):
  • Rainfall Intensity:
  • Dots (●): Light rain (<5 mm/hour).
  • Crosses (×): Moderate rain (5–20 mm/hour).
  • Triangles (▲): Heavy rain (>20 mm/hour) or thunderstorms.
  • Wind Speed/Direction:
  • Arrows (→): Surface wind (10 m height), with shaft length proportional to speed (e.g
  • cuaca besok surabaya - Ilustrasi 2

    Impact of Tomorrow’s Weather on Daily Life in Surabaya

    Surabaya’s weather patterns significantly influence daily routines, economic activities, and public safety. Forecasted conditions—such as heavy rainfall, high humidity, or heatwaves—directly affect commuters navigating congested streets, outdoor workers exposed to extreme temperatures, and students relying on outdoor spaces for learning. These disruptions extend beyond individual inconveniences, triggering broader economic ripple effects across sectors like logistics, tourism, and local trade. Understanding these impacts allows residents and businesses to adopt proactive measures, while local media plays a critical role in disseminating timely alerts to mitigate risks.

    The following analysis examines scenario-based effects on key demographics, provides structured precautions for extreme weather, assesses economic consequences, and evaluates the efficiency of weather communication channels in Surabaya.

    Scenario-Based Analysis of Weather Impacts on Commuters, Outdoor Workers, and Students

    Weather forecasts for Surabaya often include high humidity (70–90%), sudden downpours, or prolonged heatwaves, each presenting distinct challenges for different groups.

    Commuters
    During heavy rain, Surabaya’s road infrastructure—characterized by narrow lanes, frequent flooding in low-lying areas (e.g., Wonokromo, Pakuwon Harapan), and unreliable public transport schedules—exacerbates delays. The Trans Surabaya (BRT) system, for instance, experiences reduced operational efficiency, with some routes suspended due to waterlogged tracks. Commuters relying on motorbikes face heightened risks of accidents, particularly in areas like Jembatan Merah or Gubeng, where visibility drops sharply. Actionable tips:

  • Use real-time traffic apps (e.g., Google Maps, Traffic Surabaya) to reroute via elevated roads (e.g., Jalan Raya Surabaya–Mojokerto).
  • Carry waterproof gear and avoid rush hours (07:00–09:00, 16:00–18:00) when flooding is most likely.
  • For those using ojek (ride-hailing), specify "rain delay" as a priority to secure drivers willing to navigate flooded paths.
  • Outdoor Workers
    Sectors such as construction, street vending, and port labor (e.g., Tanjung Perak) are highly vulnerable to weather extremes. High humidity (above 80%) increases heat stress, while heavy rain disrupts material deliveries and safety protocols. Case study: During the 2023 monsoon season, construction sites in Dukuh Pakis reported a 30% slowdown in productivity due to mandatory work halts for worker safety. Actionable tips:

  • Employers should enforce mandatory hydration breaks every 30 minutes during heatwaves, with shaded rest areas.
  • Use waterproof tarps to protect materials and equipment; stockpile supplies in advance of forecasts.
  • Workers in fishing communities (e.g., Gresik) should monitor BMKG marine alerts for sudden squalls, which can capsize small boats.
  • Students
    Outdoor learning activities, sports events, and school commutes are disrupted by extreme weather. For example, Universitas Airlangga and SMAN 1 Surabaya often cancel field trips or outdoor lectures during forecasts of >30mm rainfall. Actionable tips:

  • Schools should designate indoor emergency assembly points near windows for visibility during storms.
  • Students using bicycles should avoid Jalan Raya Basuki Rachmat (a flood-prone route) and opt for sidewalks with drainage.
  • Digital platforms (e.g., Google Classroom) should be pre-configured for remote learning in case of cancellations.
  • Checklist of Precautions for Surabaya Residents During Extreme Weather

    Proactive measures categorized by health, transportation, and property minimize risks during weather disruptions. Below is a structured checklist with visual indicators (represented textually) for clarity.
    Category Precaution Icon Action
    Health Heatwave (>35°C) ☀️ Stay hydrated (3L water/day); wear lightweight, light-colored clothing; avoid midday sun (10:00–15:00).
    High Humidity (>80%) 💧 Use dehumidifiers; dry clothes immediately after washing; monitor for mold in bathrooms.
    Heavy Rain/Flooding 🌧️ Take antimalarial prophylaxis if in stagnant water areas; check for leptospirosis symptoms (fever, muscle pain).
    Transportation Flood-Prone Areas 🚧 Avoid Jalan Raya Surabaya–Mojokerto and Jalan Darmo during downpours; use elevated roads like Jalan Raya Basuki Rachmat.
    Public Transport Delays 🚆 Check KRL Commuterline and Trans Surabaya updates via @TransSurabaya (Twitter); allow 50% extra travel time.
    Motorcycle Safety 🛵 Use reflective vests; avoid sudden braking on wet surfaces; carry a rain poncho and basic toolkit.
    Property Flooding 🏠 Elevate electrical appliances; use sandbags in doorways; store valuables in waterproof containers.
    High Winds (>20 km/h) 🌬️ Secure outdoor furniture; reinforce roofing with tarps; trim overhanging branches.
    Power Outages ⚡ Keep portable chargers and flashlights accessible; report outages to PLN via 123.
    Note: Residents in low-lying areas (e.g., Kenjeran, Pakuwon Harapan) should register with BPBD Surabaya for evacuation alerts via SMS.

    Economic Ripple Effects of Weather Disruptions in Surabaya

    Surabaya’s economy—heavily reliant on trade, logistics, and tourism—faces measurable losses during adverse weather. Key sectors include:

    Port and Logistics
    The Tanjung Perak Port, Indonesia’s second-busiest, experiences container delays during heavy rain or high winds, as seen in January 2024 when 12% of scheduled shipments were postponed due to rough seas. Impact:

  • Retail: Supermarkets (e.g., Carrefour, Hero) face supply chain bottlenecks, leading to 5–10% price surges for perishables (e.g., seafood, vegetables).
  • Manufacturing: Factories in Gresik Industrial Zone halt operations during power outages (linked to PLN grid strain), costing IDR 20–50 billion/month in lost productivity.
  • Tourism and Hospitality
    Surabaya’s beachfront attractions (e.g., Bukit Darmo, Kenjeran Beach) see 30–40% visitor drop-offs during rainy seasons, directly affecting:

  • Hotels: Properties like The St. Regis Surabaya report 20% occupancy declines in monsoon months, prompting discounted packages.
  • Food and Beverage: Warungs (e.g., Warung Babi Guling Pak Raden) near Jembatan Merah lose 40% of foot traffic, shifting revenue to
  • Cultural and Traditional Weather Wisdom in Surabaya

    Surabaya’s weather patterns, deeply intertwined with its Javanese and Madurese heritage, reflect a blend of indigenous knowledge and adaptive resilience. Local communities have long relied on proverbs, folklore, and observational techniques to predict seasonal shifts, complementing modern meteorological forecasts. These traditions, rooted in agricultural cycles and maritime navigation, offer unique insights into climate variability while maintaining cultural continuity. Below, an exploration of Surabaya’s weather-related wisdom, its practical applications in farming, and its integration with historical festivals, alongside a comparative analysis of Indonesian regional traditions.

    Proverbs and Folklore as Weather Indicators

    Javanese and Madurese communities in Surabaya employ weather-related sayings (pengajian cuaca) to interpret atmospheric changes, often tied to lunar cycles, animal behavior, and natural phenomena. These proverbs, passed down through generations, serve as mnemonic tools for forecasting rain, wind, or temperature fluctuations. Below are selected examples, translated and contextualized with modern interpretations where applicable.
    Original Proverb (Javanese/Madurese) Literal Translation Modern Interpretation Scientific Correlation
    “Kabut di pagi, hujan di siang.”
    (Javanese)
    “Morning fog, afternoon rain.” Fog formation in Surabaya’s coastal plains often indicates high humidity and stable atmospheric conditions, which may precede convective rainfall by late afternoon. Supported by meteorological data showing increased cloud cover and dew point rises before monsoon-driven rains (e.g., November–January).
    “Burung-burung naik tinggi, hujan akan turun.”
    (Madurese)
    “Birds flying high, rain will fall.” Birds, particularly swifts or swallows, ascend before storms due to rising air currents and reduced air pressure, a behavior documented in tropical regions. Aligned with barometric pressure trends; sudden drops often precede thunderstorms in Surabaya’s humid climate.
    “Bulan purnama, angin kencang.”
    (Javanese)
    “Full moon, strong winds.” Lunar phases influence tidal winds in coastal areas, with full moons correlating to higher wind speeds due to gravitational effects on atmospheric pressure. Observed in Surabaya’s angin laut (sea breeze) patterns, where wind speeds peak during full moons in the dry season (June–October).
    “Daun kelapa gugur, hujan akan datang.”
    (Madurese)
    “Coconut leaves falling, rain is coming.” Coconut palms (Cocos nucifera) shed leaves in response to increased humidity and electrical charge in the air before thunderstorms, a phenomenon noted in Southeast Asian agriculture. Linked to pre-monsoon atmospheric instability, where leaf drop occurs 12–24 hours before rainfall in Surabaya’s musim hujan (rainy season).
    These proverbs demonstrate how local communities encode environmental cues into cultural narratives, often aligning with verifiable meteorological patterns. For instance, the correlation between coconut leaf drop and rainfall has been validated in studies on tropical plant responses to humidity (e.g., Journal of Tropical Ecology, 2018).

    Indigenous Weather Forecasting in Gresik and Sidoarjo Farming Communities

    Agricultural communities in Gresik and Sidoarjo, historically reliant on rice and peanut cultivation, have developed sophisticated methods to predict weather using indigenous knowledge. These practices, though less documented than scientific models, exhibit remarkable accuracy in short-term forecasts (1–3 days) and align with modern understandings of microclimates. Below are key techniques and their comparisons to scientific methods.
    Traditional Method Description Scientific Basis Example in Gresik/Sidoarjo
    Cloud Shape Analysis Observation of cloud formations (e.g., awan payung [anvil clouds] or awan gumpalan [cumulus clusters]) to predict thunderstorms. Cumulus clouds indicate convection; anvil clouds signify mature thunderstorms with heavy rain. Satellite imagery confirms these patterns in Surabaya’s musim hujan. Farmers in Gresik’s Desa Tambakrejo note that awan gumpalan rising vertically by 10 AM often leads to afternoon downpours, prompting them to cover rice seedlings.
    Animal Behavior Monitoring livestock (e.g., cattle lying down, ants moving leaves) as barometers for pressure changes. Animals detect infrasound and electrical field shifts before storms. Studies show cattle restlessness correlates with drops in atmospheric pressure (Applied Animal Behaviour Science, 2020). Madurese farmers in Sidoarjo’s pegunungan (hilly) regions observe water buffalo seeking shelter when winds shift from the east, indicating a angin timuran (easterly wind) that precedes rain.
    Plant Indicators Tracking plants like sereh (lemongrass) or kedawung (turmeric) for humidity changes; wilting or leaf curling signals impending rain. Plants transpire more rapidly in high humidity, leading to visible stress. Soil moisture sensors validate these observations in tropical agroecosystems. In Gresik’s pepaya (papaya) orchards, farmers harvest fruit early if leaves curl tightly, as this pattern precedes the hujan lebat (heavy rain) typical of December–January.
    Wind Direction and Speed Using local landmarks (e.g., smoke direction from sate stalls) to gauge wind shifts, with angin barat (west wind) often bringing rain. Westward winds in Java’s southern coast (including Surabaya) are associated with monsoon troughs, per BMKG (Indonesian Meteorology Agency) data. Madurese fishermen in Teluk Lamong delay voyages if smoke from warung stalls drifts westward, a sign of approaching hujan musiman (seasonal rain).
    These methods highlight the synergy between traditional ecological knowledge (TEK) and scientific meteorology. For example, the BMKG’s Pusat Prediksi Cuaca (Weather Forecasting Center) in Malang occasionally cross-references farmer reports of animal behavior with radar data to refine short-term alerts for Surabaya’s urban and rural areas.
    Surabaya’s cultural calendar includes festivals where weather plays a pivotal role, from agricultural blessings to civic celebrations. These events, originally scheduled during optimal dry-season months, have adapted to climate variability, reflecting the city’s resilience. Below are key examples and their modern adaptations.
    Festival Traditional Timing Weather Significance Modern Adaptations
    Hari Ulang Tahun Kota Surabaya (City Anniversary) January 10 (coinciding with the dry season’s end). Historically celebrated under clear skies, symbolizing new beginnings. Rain disrupted

    Tomorrow’s weather in Surabaya is more than a meteorological forecast; it is a reflection of the city’s vulnerability and adaptability in the face of climate variability. From the precision of AI-enhanced predictions to the timeless observations of farming communities in Gresik, Surabaya’s approach to weather management blends innovation with tradition. By leveraging data-driven forecasts, urban infrastructure adjustments, and community-driven preparedness, residents and businesses can mitigate risks while embracing the city’s dynamic coastal identity. As monsoon transitions and urban heat island effects continue to shape Surabaya’s climate, this analysis underscores the importance of proactive planning—ensuring the city remains resilient against both predictable patterns and unexpected extremes.

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