ALICE-LAB offers an extensive dataset encompassing a broad range of hydrologic variables, including precipitation, evapotranspiration, runoff, streamflow, groundwater, and terrestrial water storage, across the entire Thailand and spanning from 1850 to 2100. This comprehensive suite of data reflect various climate change scenarios, providing crucial insights into how shifting climate conditions impact the water cycle. By delivering daily updates, our dataset ensures that researchers, policymakers, and stakeholders have access to the most current and historical hydrologic information, which is vital for informed decision-making and effective water resource management. The ability to analyze these variables over such an extensive temporal and spatial range is indispensable for understanding long-term trends and preparing for future environmental changes.

Figure 1: Daily evapotranspiration for the Chaophraya River Basin, depicting outputs from various climate models under different projection scenarios (top: SSP126, bottom: SSP585). The background lines represent results from individual models, while the overall trend is shown by the black line. This visualization provides insight into how hydrologic responses vary temporally across different climate change scenarios and highlights the associated uncertainties.

Figure 2: Monthly averaged evapotranspiration in December 2100 (end of the century), displayed by different climate models (columns) and climate scenarios (rows). This figure illustrates the spatial variability in hydrologic responses to various climate scenarios, aiding in the accurate deployment of management strategies to address vulnerabilities in different regions.

Climate projections are essential for understanding how future climate conditions will affect various environmental and human systems. By anticipating changes in temperature, precipitation patterns, and other key climate variables, stakeholders can better plan for and mitigate the impacts of climate change. Using an ensemble of climate models is particularly important as it helps to capture a range of possible future scenarios, providing a more robust understanding of potential outcomes and their associated uncertainties. However, traditional climate projection datasets often fall short by not including a comprehensive suite of hydrologic variables such as evapotranspiration, groundwater, and streamflow. This limitation restricts the ability to fully assess the implications of climate change on the water cycle and related resources.

ALICE-LAB addresses this gap by integrating forcing data from multiple climate models and scenarios into our advanced hydrological models. We offer a unique dataset comprising ten different ensembles at a country scale, which not only reflects a range of possible future climate conditions but also incorporates essential hydrologic variables such as evapotranspiration and groundwater. This approach enables a more detailed and nuanced understanding of hydrologic responses to climate change, highlighting the novel and comprehensive nature of our dataset. By providing this level of detail and variability, our data helps to better capture uncertainties and supports more informed decision-making for water resource management and climate adaptation strategies.

Spatial Resolution: 0.5 equal-area grid (~50 km)
Temporal Resolution: 1 day and 1 month
Time span: 1850 – 2100
Ensemble: 10
Scenarios: SSP126, SSP245, SSP370, and SSP585
File format: NetCDF

MODEL

VARIABLES

Terrestrial Water Storage (TWS) time series from various models under the SSP585 climate scenario across different river basins in Thailand, covering the years 1850 to 2100. This dataset illustrates fluctuations in TWS over time, providing valuable insights into the impact of climate change on regional water resources. It is essential for understanding hydrological dynamics, assessing future water availability, and predicting changes in drought frequency and severity.