{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2021:HWVJX7YJGQNRLC5TPMQVV7DG6K","short_pith_number":"pith:HWVJX7YJ","schema_version":"1.0","canonical_sha256":"3daa9bff09341b158bb37b215afc66f2bb2c2801602a83c75e2e1031ec78a34c","source":{"kind":"arxiv","id":"2112.01221","version":1},"attestation_state":"computed","paper":{"title":"Analyzing High-Resolution Clouds and Convection using Multi-Channel VAEs","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"physics.ao-ph","authors_text":"Griffin Mooers, Harshini Mangipudi, Mike Pritchard, Stephan Mandt, Tom Beucler","submitted_at":"2021-12-01T06:23:07Z","abstract_excerpt":"Understanding the details of small-scale convection and storm formation is crucial to accurately represent the larger-scale planetary dynamics. Presently, atmospheric scientists run high-resolution, storm-resolving simulations to capture these kilometer-scale weather details. However, because they contain abundant information, these simulations can be overwhelming to analyze using conventional approaches. This paper takes a data-driven approach and jointly embeds spatial arrays of vertical wind velocities, temperatures, and water vapor information as three \"channels\" of a VAE architecture. Our"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2112.01221","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"physics.ao-ph","submitted_at":"2021-12-01T06:23:07Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"e1c978afb420319700a7389b95f967cb4b84fe3a490b03588fcef5716e86ed4f","abstract_canon_sha256":"513df00ac747397fe269fc7dd0df475ef9ce2fdff4151f39a27a7b0d4fd1a28f"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T03:37:06.561830Z","signature_b64":"QwCxuuQQOhTZgqDUhM2xtXstmGM3iY8Is6tFFycwJMOp0UUPmEAAhywAgZI6qY6cR4iWcn9csd2M4j5vige/CQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"3daa9bff09341b158bb37b215afc66f2bb2c2801602a83c75e2e1031ec78a34c","last_reissued_at":"2026-07-05T03:37:06.561425Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T03:37:06.561425Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Analyzing High-Resolution Clouds and Convection using Multi-Channel VAEs","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"physics.ao-ph","authors_text":"Griffin Mooers, Harshini Mangipudi, Mike Pritchard, Stephan Mandt, Tom Beucler","submitted_at":"2021-12-01T06:23:07Z","abstract_excerpt":"Understanding the details of small-scale convection and storm formation is crucial to accurately represent the larger-scale planetary dynamics. Presently, atmospheric scientists run high-resolution, storm-resolving simulations to capture these kilometer-scale weather details. However, because they contain abundant information, these simulations can be overwhelming to analyze using conventional approaches. This paper takes a data-driven approach and jointly embeds spatial arrays of vertical wind velocities, temperatures, and water vapor information as three \"channels\" of a VAE architecture. Our"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2112.01221","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2112.01221/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"aliases":[{"alias_kind":"arxiv","alias_value":"2112.01221","created_at":"2026-07-05T03:37:06.561482+00:00"},{"alias_kind":"arxiv_version","alias_value":"2112.01221v1","created_at":"2026-07-05T03:37:06.561482+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2112.01221","created_at":"2026-07-05T03:37:06.561482+00:00"},{"alias_kind":"pith_short_12","alias_value":"HWVJX7YJGQNR","created_at":"2026-07-05T03:37:06.561482+00:00"},{"alias_kind":"pith_short_16","alias_value":"HWVJX7YJGQNRLC5T","created_at":"2026-07-05T03:37:06.561482+00:00"},{"alias_kind":"pith_short_8","alias_value":"HWVJX7YJ","created_at":"2026-07-05T03:37:06.561482+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/HWVJX7YJGQNRLC5TPMQVV7DG6K","json":"https://pith.science/pith/HWVJX7YJGQNRLC5TPMQVV7DG6K.json","graph_json":"https://pith.science/api/pith-number/HWVJX7YJGQNRLC5TPMQVV7DG6K/graph.json","events_json":"https://pith.science/api/pith-number/HWVJX7YJGQNRLC5TPMQVV7DG6K/events.json","paper":"https://pith.science/paper/HWVJX7YJ"},"agent_actions":{"view_html":"https://pith.science/pith/HWVJX7YJGQNRLC5TPMQVV7DG6K","download_json":"https://pith.science/pith/HWVJX7YJGQNRLC5TPMQVV7DG6K.json","view_paper":"https://pith.science/paper/HWVJX7YJ","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2112.01221&json=true","fetch_graph":"https://pith.science/api/pith-number/HWVJX7YJGQNRLC5TPMQVV7DG6K/graph.json","fetch_events":"https://pith.science/api/pith-number/HWVJX7YJGQNRLC5TPMQVV7DG6K/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/HWVJX7YJGQNRLC5TPMQVV7DG6K/action/timestamp_anchor","attest_storage":"https://pith.science/pith/HWVJX7YJGQNRLC5TPMQVV7DG6K/action/storage_attestation","attest_author":"https://pith.science/pith/HWVJX7YJGQNRLC5TPMQVV7DG6K/action/author_attestation","sign_citation":"https://pith.science/pith/HWVJX7YJGQNRLC5TPMQVV7DG6K/action/citation_signature","submit_replication":"https://pith.science/pith/HWVJX7YJGQNRLC5TPMQVV7DG6K/action/replication_record"}},"created_at":"2026-07-05T03:37:06.561482+00:00","updated_at":"2026-07-05T03:37:06.561482+00:00"}