Featured Dataverses

In order to use this feature you must have at least one published or linked dataverse.

Publish Dataverse

Are you sure you want to publish your dataverse? Once you do so it must remain published.

Publish Dataverse

This dataverse cannot be published because the dataverse it is in has not been published.

Delete Dataverse

Are you sure you want to delete your dataverse? You cannot undelete this dataverse.

Advanced Search

21 to 30 of 3,100 Results
README.txt
Oct 9, 2026 - MODIS observations of cloud responses to ship emissions in precipitating marine clouds
Plain Text - 8.0 KB - MD5: 905e6b5d2c7b73a23e75d065bf4b6364
config.py
Oct 9, 2026 - Python code for analysing the evolution of cloud properties downwind of strong aerosol point sources using MODIS satellite observations
Python Source Code - 1.5 KB - MD5: 73254f23f38c0ae94ad4549d02855eb4
data_out.tab
Oct 9, 2026 - Python code for analysing the evolution of cloud properties downwind of strong aerosol point sources using MODIS satellite observations
Tabular Data - 26.0 KB - 34 Variables, 129 Observations - UNF:6:PXwu1GWbWC5Dvh3xFGcr5A==
geom_transform.py
Oct 9, 2026 - Python code for analysing the evolution of cloud properties downwind of strong aerosol point sources using MODIS satellite observations
Python Source Code - 9.2 KB - MD5: 4daa3dfff2c64d9dff6494b73fd103e1
MOD021KM.A2015242.1500.061.2017322025327.nc4
Oct 9, 2026 - Python code for analysing the evolution of cloud properties downwind of strong aerosol point sources using MODIS satellite observations
Network Common Data Form - 264.7 MB - MD5: 8f92c190ddd279f43fdb5f883ab08f90
MOD021KM.A2023167.1905.061.2023168073950.nc4
Oct 9, 2026 - Python code for analysing the evolution of cloud properties downwind of strong aerosol point sources using MODIS satellite observations
Network Common Data Form - 267.9 MB - MD5: f5c21a7ae7bdf3e5025c55c620de2c9d
MOD03.A2015242.1500.061.2017322024356.hdf
Oct 9, 2026 - Python code for analysing the evolution of cloud properties downwind of strong aerosol point sources using MODIS satellite observations
Hierarchical Data Format - 31.2 MB - MD5: 36e90456507c968f77803af13a167e6f
MOD03.A2023167.1905.061.2023168012648.hdf
Oct 9, 2026 - Python code for analysing the evolution of cloud properties downwind of strong aerosol point sources using MODIS satellite observations
Hierarchical Data Format - 33.9 MB - MD5: a9d568476b45bdb2fb7758eb5668803d
MOD06_L2.A2015242.1500.061.2017322173229.nc4
Oct 9, 2026 - Python code for analysing the evolution of cloud properties downwind of strong aerosol point sources using MODIS satellite observations
Network Common Data Form - 213.0 MB - MD5: 1c35c12e76e53e7b6e214ca51077303b
MOD06_L2.A2023167.1905.061.2023168082635.nc4
Oct 9, 2026 - Python code for analysing the evolution of cloud properties downwind of strong aerosol point sources using MODIS satellite observations
Network Common Data Form - 306.3 MB - MD5: 5c405d382e46cfd00fde3c5dbfd7b8a7
Add Data

Sign up or log in to create a dataverse or add a dataset.

Sign Up Log In
Share Dataverse

Share this dataverse on your favorite social media networks.

Link Dataverse
Reset Modifications

Are you sure you want to reset the selected metadata fields? If you do this, any customizations (hidden, required, optional) you have done will no longer appear.