PODAAC Data Access

A Pythonic interface for accessing and downloading geographic and temporal data from NASA's Physical Oceanography Distributed Active Archive Center (PO.DAAC).

Overview

This library streamlines the process of downloading oceanographic data from NASA's PO.DAAC repository. It provides a more intuitive, Pythonic approach to interacting with PO.DAAC services.

Features

• Simple API: Clean, intuitive interface for PO.DAAC data access
• Flexible Date Ranges: Easily specify time periods for data collection
• Geographic Filtering: Define precise latitude and longitude boundaries
• Pre-configured Datasets: Common datasets available through simple imports
• Custom Dataset Support: Ability to define and download custom datasets
• Earthdata Authentication: Integrated authentication management

Installation

pip install gerg_podaac_data_access

Quick Start

Using Pre-configured Datasets

from pathlib import Path
import datetime
from gerg_podaac_data_access.models import get_common_datasets
from gerg_podaac_data_access.client import PodaacClient
from gerg_podaac_data_access.auth import cleanup_earthdata_auth

# Define output location and parameters
data_out_folder = Path("data")
date_start = "03-13-2013T00:00:00+0:00"
date_end = "03-15-2013T00:00:00+0:00"
lat_min = 19
lat_max = 31
lon_min = -98
lon_max = -83

# Initialize PodaacClient client
ssh = PodaacClient(data_out_folder=data_out_folder,
          date_start=date_start, date_end=date_end,
          lat_min=lat_min, lat_max=lat_max,
          lon_min=lon_min, lon_max=lon_max)

# Get pre-configured datasets
datasets = get_common_datasets()

# Download NASA SSH data
ssh.download_data(datasets["NASA_SSH"])

# Clean up credentials when done
cleanup_earthdata_auth()

Using Custom Datasets

from pathlib import Path
import datetime
from gerg_podaac_data_access.client import PodaacClient
from gerg_podaac_data_access.auth import cleanup_earthdata_auth
from gerg_podaac_data_access.models import Dataset

# Define output location and parameters
data_out_folder = Path("data")
date_start = "03-01-2013T00:00:00+0:00"
date_end = "04-01-2013T00:00:00+0:00"
lat_min = 19
lat_max = 31
lon_min = -98
lon_max = -83

# Initialize PodaacClient client
ssh = PodaacClient(data_out_folder=data_out_folder,
          date_start=date_start, date_end=date_end,
          lat_min=lat_min, lat_max=lat_max,
          lon_min=lon_min, lon_max=lon_max)

# Define custom dataset
dataset = Dataset(podaac_download_name="SEA_SURFACE_HEIGHT_ALT_GRIDS_L4_2SATS_5DAY_6THDEG_V_JPL2205")

# Download custom dataset
ssh.download_data(dataset=dataset)

# Clean up credentials when done
cleanup_earthdata_auth()

Authentication

This library handles NASA Earthdata Login authentication. Make sure you have valid Earthdata credentials before using the library. The cleanup_earthdata_auth() function should be called when you're done to properly manage authentication resources.

API Reference

Main Classes

• PodaacClient: Client for downloading sea surface height data

  • Parameters:
    • data_out_folder: Path to store downloaded data
    • date_start: Start date for data collection
    • date_end: End date for data collection
    • lat_min: Minimum latitude boundary
    • lat_max: Maximum latitude boundary
    • lon_min: Minimum longitude boundary
    • lon_max: Maximum longitude boundary
  • Methods:
    • download_data(dataset): Download data for the specified dataset

• Dataset: Represents a PODAAC dataset

  • Parameters:
    • podaac_download_name: The official PODAAC dataset identifier

Utility Functions

• get_common_datasets(): Returns a dictionary of pre-configured datasets
• cleanup_earthdata_auth(): Cleans up authentication resources

Examples

The library includes example scripts in the examples directory:

• simple_example.py: Demonstrates using pre-configured datasets
• custom_dataset_exmple.py: Shows how to define and use custom datasets

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgments

• NASA's PO.DAAC for providing the data services
• The oceanographic research community

Developed for the Earth science community to simplify access to valuable oceanographic data