{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2020:ULME4RSMFVNORWUNDFVJGHM4F4","short_pith_number":"pith:ULME4RSM","schema_version":"1.0","canonical_sha256":"a2d84e464c2d5ae8da8d196a931d9c2f2c0a3319c73f1dc32b4fb08988e9d8d5","source":{"kind":"arxiv","id":"2007.01444","version":2},"attestation_state":"computed","paper":{"title":"Generative Modeling for Atmospheric Convection","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","physics.comp-ph"],"primary_cat":"physics.ao-ph","authors_text":"Griffin Mooers, Jens Tuyls, Michael Pritchard, Stephan Mandt, Tom Beucler","submitted_at":"2020-07-03T00:24:09Z","abstract_excerpt":"While cloud-resolving models can explicitly simulate the details of small-scale storm formation and morphology, these details are often ignored by climate models for lack of computational resources. Here, we explore the potential of generative modeling to cheaply recreate small-scale storms by designing and implementing a Variational Autoencoder (VAE) that performs structural replication, dimensionality reduction, and clustering of high-resolution vertical velocity fields. Trained on ~6*10^6 samples spanning the globe, the VAE successfully reconstructs the spatial structure of convection, perf"},"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":"2007.01444","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"physics.ao-ph","submitted_at":"2020-07-03T00:24:09Z","cross_cats_sorted":["cs.LG","physics.comp-ph"],"title_canon_sha256":"282e377061e060a164f360d888b59b9e5d1a7669b80f99cc89a42ade7924178b","abstract_canon_sha256":"5e4060ff05397c420ed7763a6cd73c469b592c5127bf802a1ed55948de903fee"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T01:45:43.931606Z","signature_b64":"cf6nHIOMU/MXkusxtj4dWKisL+DjIWd7bT33OZ7OdI4qRBUdMeJIFSWa5a6oogH4Fx9x5m7/70MmQVk8/dMcAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a2d84e464c2d5ae8da8d196a931d9c2f2c0a3319c73f1dc32b4fb08988e9d8d5","last_reissued_at":"2026-07-05T01:45:43.931199Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T01:45:43.931199Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Generative Modeling for Atmospheric Convection","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","physics.comp-ph"],"primary_cat":"physics.ao-ph","authors_text":"Griffin Mooers, Jens Tuyls, Michael Pritchard, Stephan Mandt, Tom Beucler","submitted_at":"2020-07-03T00:24:09Z","abstract_excerpt":"While cloud-resolving models can explicitly simulate the details of small-scale storm formation and morphology, these details are often ignored by climate models for lack of computational resources. Here, we explore the potential of generative modeling to cheaply recreate small-scale storms by designing and implementing a Variational Autoencoder (VAE) that performs structural replication, dimensionality reduction, and clustering of high-resolution vertical velocity fields. Trained on ~6*10^6 samples spanning the globe, the VAE successfully reconstructs the spatial structure of convection, perf"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2007.01444","kind":"arxiv","version":2},"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/2007.01444/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":"2007.01444","created_at":"2026-07-05T01:45:43.931261+00:00"},{"alias_kind":"arxiv_version","alias_value":"2007.01444v2","created_at":"2026-07-05T01:45:43.931261+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2007.01444","created_at":"2026-07-05T01:45:43.931261+00:00"},{"alias_kind":"pith_short_12","alias_value":"ULME4RSMFVNO","created_at":"2026-07-05T01:45:43.931261+00:00"},{"alias_kind":"pith_short_16","alias_value":"ULME4RSMFVNORWUN","created_at":"2026-07-05T01:45:43.931261+00:00"},{"alias_kind":"pith_short_8","alias_value":"ULME4RSM","created_at":"2026-07-05T01:45:43.931261+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/ULME4RSMFVNORWUNDFVJGHM4F4","json":"https://pith.science/pith/ULME4RSMFVNORWUNDFVJGHM4F4.json","graph_json":"https://pith.science/api/pith-number/ULME4RSMFVNORWUNDFVJGHM4F4/graph.json","events_json":"https://pith.science/api/pith-number/ULME4RSMFVNORWUNDFVJGHM4F4/events.json","paper":"https://pith.science/paper/ULME4RSM"},"agent_actions":{"view_html":"https://pith.science/pith/ULME4RSMFVNORWUNDFVJGHM4F4","download_json":"https://pith.science/pith/ULME4RSMFVNORWUNDFVJGHM4F4.json","view_paper":"https://pith.science/paper/ULME4RSM","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2007.01444&json=true","fetch_graph":"https://pith.science/api/pith-number/ULME4RSMFVNORWUNDFVJGHM4F4/graph.json","fetch_events":"https://pith.science/api/pith-number/ULME4RSMFVNORWUNDFVJGHM4F4/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/ULME4RSMFVNORWUNDFVJGHM4F4/action/timestamp_anchor","attest_storage":"https://pith.science/pith/ULME4RSMFVNORWUNDFVJGHM4F4/action/storage_attestation","attest_author":"https://pith.science/pith/ULME4RSMFVNORWUNDFVJGHM4F4/action/author_attestation","sign_citation":"https://pith.science/pith/ULME4RSMFVNORWUNDFVJGHM4F4/action/citation_signature","submit_replication":"https://pith.science/pith/ULME4RSMFVNORWUNDFVJGHM4F4/action/replication_record"}},"created_at":"2026-07-05T01:45:43.931261+00:00","updated_at":"2026-07-05T01:45:43.931261+00:00"}