Interactive Index
When you access daily data from Sustax, you are receiving outputs from our advanced climate modeling system. This system integrates historical data (ERA5) and an ensemble of future projections (CMIP6), all meticulously bias-corrected and harmonized by Geoskop’s proprietary algorithms [14] to provide a consistent timeline from 1979 to 2080. For each selected Shared Socioeconomic Pathway (SSP-RCP) scenario, you will get access to:
- The primary daily climate variable value: This is the core projection from our best-estimate model.
- The model spread: This quantifies the uncertainty associated with that projection scenario.
Let’s explore the key daily variables:
Daily Climate Data
Temperature at Surface (tas)
This variable represents the temperature of the air measured at 2 meters (approximately 6.5 feet) above the land, sea, or inland water surface. In Sustax, this is calculated by our models, taking into account atmospheric conditions near the surface, consistent with the standard meteorological practice.
Official Variable Name: 2-meter Air Temperature
Sustax Codename: tas
Unit of Measurement: Averaged degrees Kelvin (K) per day
Interpretation & Use Cases: Daily Temperature at Surface values are fundamental for understanding day-to-day temperature fluctuations and assessing exposure to specific thermal conditions.
- Direct Heat/Cold Stress Assessment: Analyze sequences of daily temperatures to identify potential heatwave or cold spell events affecting human health, livestock, ecosystems, and infrastructure operations (e.g., number of days exceeding a critical high temperature, or falling below a freezing threshold).
- Operational Thresholds: Determine if daily temperatures are projected to exceed operational thresholds for sensitive equipment or outdoor work.
- Input for Detailed Local Models: Daily temperature series can be used as input for more detailed local impact models (e.g., specific crop growth models that require daily inputs, energy balance models for buildings).
- Understanding Daily Variability: Analyze the day-to-day range and variability of temperatures, which can be as important as mean changes.
- Foundation for Monthly Climate Indices: While not direct daily uses, this daily tas data is the foundational input from which Sustax calculates various Monthly Climate Indices like Cooling Degree Days (CDD), Heating Degree Days (HDD), and Growing Degree Days (GDD), which provide aggregated insights for energy demand and agricultural planning.
- Long-term trends in daily tas (when aggregated, e.g., to monthly or annual averages) indicate the overall warming or cooling trajectory for a location.
Total Precipitation (pr)
This variable represents the total accumulated liquid and frozen water (including rain and snow) that falls to the Earth’s surface over the course of a day. It is the sum of large-scale (stratiform) precipitation and convective precipitation (like that from thunderstorms).
Official Variable Name: Total Precipitation
Sustax Codename: pr
Unit of Measurement: Total accumulated meters (m) per day
Interpretation & Use Cases: Total Precipitation is fundamental for assessing water availability, drought risk, and flood risk. Essential for agricultural planning, water resource management, and hydrological modeling. Can also be used to evaluate risks to infrastructure from extreme rainfall events (e.g., urban drainage capacity, landslide risk). Furthermore, it provides long-term changes in pr patterns can indicate shifts in regional climate and water cycles.
- Water Resource Management: Assessing reservoir capacity planning and water supply reliability during drought periods, calculating groundwater recharge rates for aquifer management strategies
- Agriculture & Food Security: Drought stress identification for crop insurance and yield forecasting models and soil erosion risk assessment for conservation planning and sustainable farming practices
- Infrastructure Planning: Urban drainage system capacity evaluation for stormwater management and flood prevention, road and bridge design specifications for extreme precipitation events and green infrastructure sizing (retention ponds, permeable surfaces) for climate resilience
- Insurance & Risk Assessment: Flood damage modeling for property insurance underwriting and premium calculations, agricultural crop loss evaluation for parametric insurance products and business interruption risk assessment for operations dependent on weather conditions
- Energy Sector: Hydroelectric power generation forecasting and reservoir management, solar panel efficiency impacts from cloud cover and precipitation patterns and transmission line maintenance scheduling around severe weather events.
- Public Health & Safety: Landslides and mudslides assessments in mountainous terrain, air quality assessment (as precipitation’s role in washing out pollutants)
Maximum Wind Speed (sfcWindmax)
This variable represents the maximum instantaneous wind gust speed at 10 meters above the Earth’s surface that has occurred since the previous model post-processing step (essentially, the strongest gust of wind recorded for that day). It’s calculated by considering the combined effects of the mean wind speed and turbulence within each model grid box and time step.
Official Variable Name: Maximum 3-seconds Wind Gust at 10-meter height
Sustax Codename: sfcWindmax
Unit of Measurement: Maximum meters per second (m/s) per day
Interpretation & Use Cases: The Maximum 3-seconds Wind Gust at 10-meter is crucial for assessing the risk of wind damage to buildings, infrastructure (e.g., power lines, bridges), and vegetation. Crucial for operational planning and safety in sectors sensitive to high winds. This includes:
- Renewable Energy: Assessing risk to wind turbines (damage or shutdown thresholds) and solar panel installations (structural integrity of panels and tracking systems).
- Construction: Determining safe operating windows for crane operations, work at heights, and the stability of temporary structures.
- Transportation (aerial and maritime): Informing decisions in shipping (port operations, vessel stability) and aviation (take-off/landing conditions, ground operations).
- Agriculture: Assessing risk of crop damage (e.g., lodging of tall crops).
- Insurance: Underwriting policies for property and i damage claims by modeling wind risks, improving premium accuracy.
- Forestry: Predicting tree fall risks in wind-prone forests, guiding reforestation efforts and wildfire prevention strategies
- Public Health: Assessing wind-driven spread of airborne pollutants or allergens during high-gust periods, informing urban planning for vulnerable populations
- Others: Helps in understanding the potential for wind-driven hazards like wildfires or coastal storm surges.
Daily Model Spread
Climate projections inherently involve a degree of uncertainty. This arises from various factors, including the natural variability of the climate system, differences between various climate models (even when run under the same emission scenario), and the assumptions made within those models. “Model spread” is a measure of this uncertainty.
For each Daily Climate Variable and each SSP-RCP scenario, Sustax quantifies the original ensemble’s spread of the underlying CMIP6 climate models used to generate the Sustax data at any day and location. To estimate the model’s spread, the IQR [21] is employed. This is a robust measure, less affected by outliers, and focuses on the spread of the middle 50% of the data.
Interpretation and Importance of the Uncertainty:
- A larger model spread indicates greater disagreement among the underlying climate models, suggesting higher uncertainty in that specific projection.
- A smaller model spread indicates more consensus among the models, suggesting greater confidence in the projection.
- Understanding model spread is crucial for robust risk assessment. It allows users to consider not just the “best estimate” projection but also a plausible range of potential future outcomes. This is vital for sensitivity analysis and developing resilient adaptation strategies that account for a spectrum of possibilities.
- For instance, if the mean projected tas is 25°C but the model spread is 2°C, it suggests that while 25°C is the most likely outcome, daily temperatures could plausibly range roughly between 21°C and 29°C (approximately with a couple of standard deviations, depending on the inherent distribution of the raw CMIP6 models).
- Users should note that the SSP4-3.4 and SSP4-6.0 scenarios exhibit lower model spread than other scenarios, such as SSP2-4.5 and SSP5-8.5. The former are derived from a limited number of modeling centers, whereas the latter benefit from contributions by a much larger number of modelers, notably increasing apparent uncertainty through greater diversity.
It is important to consider that the Spread provided by Sustax represents the Original Systematic Uncertainty (i.e. structural uncertainty) of the multi model ensemble used in each SSP-RCP scenario. It does not represent the Synoptic uncertainty nor the Random uncertainty.