Welcome to the Lagranian Reanalysis (LARA) Dataset

About the LARA Dataset

The LARA Dataset is a comprehensive collection of Lagrangian trajectory data, providing insights into atmospheric dynamics over extended periods. It includes various atmospheric variables tracked along particle trajectories, making it a valuable resource for researchers in meteorology, climate science, and related fields.

Disclaimer: This data set has been produced in framework of the project no. P 34170-N, "A demonstration of a Lagrangian re-analysis (LARA)", supported by the Dr. Gottfried and Dr. Vera Weiss Science Foundation and the Austrian Science Fund. This data is openly and freely accessible. Please use the following reference:

Dataset Structure

The LARA Dataset is organized into multiple periods, each containing data for specific years and months. Each variable is stored in its own Zarr array, allowing for efficient access and manipulation of the data.

PERIODs

• 1940-1947
• 1947-1954
• 1954-1961
• 1961-1968
• 1968-1975
• 1975-1982
• 1982-1989
• 1989-1996
• 1996-2003
• 2003-2010
• 2010-2017
• 2017-2024

VARIABLEs

• lon: Longitude of Particle
• lat: Latitude of Particle
• z: Height of Particle
• pv: Potential Vorticity at Particle location
• sh: Specific Humidity at Particle location
• rho: Density at Particle location
• T: Temperature at Particle location
• prs: Pressure at Particle location

Averaged VARIABLEs

• lon_av: Longitude
• lat_av: Latitude
• z_av: Height
• pv_av: Potential Vorticity at Particle location
• sh_av: Specific Humidity at Particle location
• rho_av: Density at Particle location
• T_av: Temperature at Particle location
• prs_av: Pressure at Particle location

Gridded VARIABLEs

• hmix: Atmospheric boundary layer height
• tro: Tropopause height
• to: Topography (fixed in time)

What is Zarr?

Zarr is a format for the storage of chunked, compressed, N-dimensional arrays. It is designed to support the storage of large datasets and provides excellent performance for both reading and writing data.

How to Access the Data

To access the LARA Dataset using Zarr, you can use the following steps:

1. Install the Zarr library in your programming environment. For Python, you can use pip install zarr<=3. Using zarr version 2.*
2. Load the dataset using the Zarr API. For example:

    import zarr
    import xarray as xr

    # Open the dataset
    #  https://data.eodc.wolke.img.univie.ac.at/[ PERIOD ]/ [ YEAR ]/[ MONTH ]/[ VARIABLE ]
    store = xr.open_zarr("https://data.eodc.wolke.img.univie.ac.at/2017-2024/2023/01/T")

    # Access data
    print(store)

Refer to the Zarr documentation and the Xarray documentation for more details on how to work with Zarr datasets.

Example Zarr Metadata File

This metadata file provides information about the dataset's structure, including the shape, chunk size, data type, and compression settings.

Example Dataset

<xarray.Dataset> Size: 17GB
Dimensions:   (particle: 5914326, time: 720)
Coordinates:
  * particle  (particle) int32 24MB 1 2 3 4 ... 5914323 5914324 5914325 5914326
  * time      (time) datetime64[ns] 6kB 2020-06-01 ... 2020-06-30T23:00:00
Data variables:
    T         (particle, time) float32 17GB dask.array<chunksize=(5914326, 24), meta=np.ndarray>