PAVICS is a virtual laboratory facilitating the analysis of climate data. It provides access to several data collections ranging from observations, climate projections and reanalyses. It also provides a Python programming environment to analyze this data without the need to download it. This working environment is constantly updated with the most efficient libraries for climate data analysis, in addition to ensuring quality control on the provided data and associated metadata.

• Data and files in netCDF format
• Metadata following CF-conventions
• Parallel computing environment (xarray + dask)

Access Datasets

PAVICS provides data access via a dedicated THREDDS server providing access to a growing variety of climate and weather related datasets including

• Future climate change projections
• Observational data (station & gridded)
• Reanalysis data
• Weather forecast data

Analyse Climate Data

PAVICS provides methods for finding and analysing climate data, offering tools that span the range of common data analysis steps including

• Finding and accessing datasets
• Spatio-temporal subsetting
• Climate indicator calculations
• Ensemble statistics & metrics
• Data visualization

Run Hydrological Models

PAVICS offers a suite of tools to streamline the analysis of climate change's impacts on hydrology. It relies on Raven, a hydrological modeling framework that lets hydrologists define custom hydrological models or emulate existing ones. These models are minimally driven by daily time series of temperature and precipitation, and return series of flow and state variables such as snow pack and soil water.

• Simulate stream flow using one of four global models: HMETS, GR4J-CemaNeige, HBV-EC and MOHYSE
• Run frequency analyses on flow series
• Extract physiographic properties of watersheds
• Estimate model parameters in ungauged basins
• Make hydrological predictions from numerical weather forecasts

Services

Climate indices service: Users of climate data are interested in specific indices such as the number of freeze-thaw cycles, the number of degree-days of cooling, the duration of heatwaves, etc. This returns annual values of the most popular climate indices. - Source code

High-resolution spatial gridded data renderer: This service renders gridded data on the server and sends images to the client for display within mapping applications using Open Geospatial Consortium (OGC) Web Mappping Service (WMS) standard. - Source code - Documentation

Node: Nodes are data, compute and index endpoints accessed through the PAVICS platform or external clients. The Node service is the backend that allows: data storage, harvesting, indexation and discovery of local and federated data; authentication and authorization; server registration and management. Node service is therefore composed of several other services.

Raven: A suite of WPS processes to calibrate and run hydrological models, including geographicalinformation retrieval and processing as well as time series analysis. - Source code