Data Documentation

Wy-Adapt brings together 25 global climate models (GCM’s) selected to provide useful information about the Western United States current and future climate conditions. The climate models included in the platform were evaluated based on how well they represent important aspects of the climate and are suitable for examining potential changes across the country.

The 25 GCMs used are available to explore future climate projections with built-in assumptions. It is recommended to use multiple GCMs to capture the full range of possibilities.

GCMs Used:

Wy-Adapt climate data are provided at a 9 km spatial resolution, meaning the data are organized into grid cells that are approximately 9 kilometers by 9 kilometers. This resolution provides a useful balance between geographic detail and the computational resources needed to process and analyze climate projections. Data within each grid cell represents the climate conditions for that area, allowing users to examine how projected changes may vary across different areas.

The 9 km grid provides more localized information than coarser-resolution climate datasets while maintaining consistent coverage across the country. Users should keep the grid-cell size in mind when interpreting the data, particularly when comparing climate projections with information about specific communities, watersheds, or other smaller geographic areas.

Shared Socioeconomic Pathways (SSPs) are scenarios used to describe how society, the economy, technology, and population might change in the future. Climate models use these scenarios to explore how different levels of greenhouse gas emissions could affect future climate conditions. SSPs are not predictions of what will happen, rather, they represent different possible futures that help researchers and decision-makers understand a range of potential climate outcomes. Wy-Adapt uses SSP370 scenario meaning, a future with relatively high greenhouse gas emissions and limited additional climate action. The scenario, often described as a world of “regional rivalry,” assumes slower economic and technological development, higher population growth, and limited international cooperation on climate change.

The Warm Refuge scenario represents a mid-century future in which the globe has warmed approximately 3.6°F (2°C) since the late 19th century. While precipitation increases slightly, warmer temperatures cause more fall and spring precipitation to occur as rain rather than snow. This results in a greater likelihood of low-snow years, even though overall precipitation is slightly higher. The Shrinking Snowpack scenario also represents approximately 3.6°F (2°C) of global warming by mid-century, but with slightly lower precipitation. The combination of warmer and drier conditions substantially increases the likelihood of low-snow years, while rain-on-snow events may contribute to increased flooding. The Hot and Smoky scenario represents a higher-warming future, with approximately 5.4°F (3°C) of global warming by mid-century. Under this scenario, precipitation becomes more variable, while warmer temperatures contribute to earlier spring snowmelt, increased evaporation, and reduced late-summer streamflows. Rain-on-snow events and rapid spring runoff may increase flood risk, while more smoky days during the summer illustrate how multiple climate-related impacts could occur together.

Different climate scenarios use different combinations of Global Climate Models (GCMs) to represent a range of possible future climate conditions. The tables below summarize which GCMs are available for each scenario and provide information to help users understand the differences between them. These scenarios are not predictions of a single future but represent different possible climate conditions that can help illustrate how Wyoming’s climate may change and what those changes could mean for communities, ecosystems, water resources, and other areas of interest.

Wy-Adapt climate datasets use a consistent geographic grid to represent climate conditions across the Western United States. Each grid cell has an associated geographic location that allows the climate data to be aligned with maps, geographic boundaries, and other spatial datasets.

The climate datasets available through Wy-Adapt are designed to support analysis of historical and projected climate conditions across the Western United States. Each dataset represents specific climate variables, time periods, and future conditions and can be used to examine how climate may change across different locations and timeframes.

When selecting data, users should consider the purpose of their analysis and choose datasets that match the geographic area, climate variable, time period, and scenario needed for their application. Because climate projections represent a range of plausible future conditions, examining multiple models and scenarios can provide a more complete understanding of potential changes and uncertainty.

The Data Catalog provides additional information about individual datasets, including the variables, time periods, scenarios, models, and other characteristics associated with each dataset.

WY-Adapt provides many different climate variables for users to explore, including frost days, precipitation as snow, and minimum temperature. Each variable represents a different aspect of the Earth's climate and helps users understand how climate conditions may vary across locations and over time. By examining these variables, users can better assess climate trends and their potential impacts on natural and human systems.

Some climate information available through Wy-Adapt is calculated from one or more underlying climate variables. These calculations produce derived variables or indices that can provide a more useful way of describing climate conditions for a particular application.

Derived variables are created by applying a calculation to existing climate data. For example, multiple temperature measurements may be combined to describe conditions over a particular period. Climate indices take this a step further by combining climate variables into a measure that can help describe a specific impact or condition.

Because derived variables and indices depend on the underlying data and calculation method, users should review the definition, units, and methodology associated with each measure before using it in an analysis.

Climate models do not perfectly reproduce observed climate conditions, and the differences between modeled and observed data are known as bias. Bias can vary by location, season, and climate variable. For WY-Adapt researchers found that biases in the global climate model could lead to unrealistic precipitation and snowfall when the data were used in a higher-resolution regional model (WRF).

To reduce these biases, they corrected the global climate model data before using it to drive WRF. They compared the model's historical climate conditions with a more realistic observational/reanalysis dataset and adjusted the model data to better match the observed conditions. In simple terms, they removed the average difference between the model and observations before running the regional model. This helped prevent the original errors from being amplified during downscaling and produced more realistic precipitation and snow simulations.

Bias correction can therefore make climate model data more useful for certain applications, but it does not eliminate uncertainty in future climate projections. The corrected data should still be interpreted with an understanding of the limitations and uncertainties of the climate models.

• Bias correction paper:

Rahimi, S., Huang, L., Norris, J., Hall, A., Goldenson, N., Risser, M., Feldman, D. R., Lebo, Z. J., Dennis, E., & Thackeray, C. (2024). Understanding the Cascade: Removing GCM Biases Improves Dynamically Downscaled Climate Projections. Geophysical Research Letters, 51(9), e2023GL106264. https://doi.org/10.1029/2023GL106264

The climate data available through Wy-Adapt are organized around several key characteristics, including climate variable, time period, climate scenario, and geographic location. Climate variables describe the specific aspect of climate being analyzed, such as temperature or precipitation, while scenarios represent different possible future climate conditions. Data are provided on a 9 km grid, with each grid cell representing the climate conditions for a specific area of Wyoming.

This structure allows users to select the information most relevant to their needs rather than working with an entire dataset at once. For example, a user may be interested in a particular climate variable, future scenario, and time period for a specific area of Wyoming. The Wy-Adapt tools and data documentation provide guidance for identifying and working with these combinations of data.

Climate datasets may be provided in formats designed for both analysis and data sharing. Common climate data formats include NetCDF and Zarr, which are capable of storing multi-dimensional data such as climate variables across time and geographic locations.

NetCDF files store climate data in a single file and are widely used for sharing and analyzing scientific datasets. They can be useful when working with a manageable portion of a dataset or when a complete file is needed for local analysis. However, large climate datasets can require substantial computer memory and storage when opened or downloaded in their entirety.

Zarr is designed for working with large, multi-dimensional datasets and is particularly well suited for cloud-based analysis. Rather than requiring an entire dataset to be downloaded before it can be analyzed, Zarr allows users to access portions of the data as needed. This can make it more efficient to work with large climate datasets covering many years, variables, and geographic locations.

The way Wy-Adapts data is organized allows users to move from broad exploration of available climate information to more targeted analysis. Users who are working through the Wy-Adapt interface can explore climate projections without directly interacting with the underlying data structure, while more advanced users can use the documented data access methods to work directly with the datasets.

For information about the climate models, scenarios, variables, and spatial resolution represented in Wy-Adapt, see the Climate Model Simulation section. For guidance on finding and accessing specific datasets, see the Developer API and Data Brower sections.

Readability

Standard conventions organize information in a consistent format that can be understood by both people and computer software. This makes datasets easier to interpret and work with.

Interoperability

Using established standards allows Wy-Adapt data to work with common scientific, geographic, and data analysis tools. Standardized datasets can also be combined with information from other sources with less additional processing.

Data Access

Consistent formats and metadata make it easier for users to discover, download, and analyze Wy-Adapt data. This is especially important for large climate datasets that may be accessed through different software and programming environments.

Documentation

Datasets should provide enough information for users to understand what they contain without relying on separate documentation. Metadata should describe the dataset's source, variables, units, time period, spatial information, and other details needed to correctly interpret and use the data.

Climate datasets should include clear descriptions of their variables, units, geographic coordinates, and time information. Where applicable, datasets should follow established standards such as the Climate and Forecast (CF) Conventions for NetCDF data.

At a minimum, metadata should identify:

• Dataset title — A clear description of the data.

• Source — The model, observations, or other source used to produce the data.

• Variables — The climate measurements included in the dataset.

• Units — The measurement units for each variable.

• Spatial information — The coordinate system and grid used to represent locations.

• Time information — The time period and calendar used by the dataset.

• Scenario and model information — The climate scenario and GCM associated with the data, when applicable.

• Description and references — Information about how the dataset was created and where users can find additional documentation.

Following these standards helps ensure that Wy-Adapt datasets are understandable, discoverable, and usable by both technical and non-technical users.

• WUS-D3 overview paper:

Rahimi, S., Huang, L., Norris, J., Hall, A., Goldenson, N., Krantz, W., Bass, B., et al. (2024). An Overview of the Western United States Dynamically Downscaled Dataset (WUS-D3). Geoscientific Model Development, 17(6), 2265–2286. https://doi.org/10.5194/gmd-17-2265-2024

• Bias correction paper:

Rahimi, S., Huang, L., Norris, J., Hall, A., Goldenson, N., Risser, M., Feldman, D. R., Lebo, Z. J., Dennis, E., & Thackeray, C. (2024). Understanding the Cascade: Removing GCM Biases Improves Dynamically Downscaled Climate Projections. Geophysical Research Letters, 51(9), e2023GL106264. https://doi.org/10.1029/2023GL106264