Presentation of the Best Practice Protocol for the Validation of Aerosol, Cloud, and Precipitation Profiles (ACPPV) to the 2nd ESA-JAXA EarthCARE In-Orbit validation workshop
Bibliographic record
Abstract
Amiridis, V.1, Marinou, E.1, Hostetler, C.2, Koopman, R.3, Cecil, D., J.4, Moisseev, D.5, Tackett, J.2, Gross, S.6, Baars, H.7, Redemann, J.8, Marenco, F.9, Baldini, L.10, Tanelli, S.11, Fielding, M.12, Janisková, M.12, Tanaka, T.13, O’Connor, E.14, Fjæraa, A., M.15, and the ACPPV consortium 16 1Institute of Astronomy, Astrophysics, Space Applications & Remote Sensing (IAASARS), National Observatory of Athens (NOA), 15236 Athens, Greece 2NASA Langley Research Center, Hampton, United States 3European Space Research and Technology, European Space Agency (ESA/ESTEC), Keplerlaan 1, 2201 AZ Noordwijk, The Netherlands 4NASA Marshall Space Flight Center, Earth Science Branch, 320 Sparkman Dr NW, AL 35805, Huntsville, United States 5Institute for Atmospheric and Earth System Research, Faculty of Science, University of Helsinki, Helsinki, Finland 6Institut für Physik der Atmosphäre, Deutsches Zentrum für Luft- und Raumfahrt (DLR), Weßling 82234, Germany 7Leibniz Institute for Tropospheric Research (TROPOS), Permoserstraße 15, 04318 Leipzig, Germany 8School of Meteorology, University of Oklahoma, Norman, Oklahoma, United States 9The Cyprus Institute, 20 Konstantinou Kavafi Street, 2121 Nicosia, Cyprus 10National Research Council, Insitute of Atmospheric Science and Climate (CNR-ISAC), Via Fosso del Cavaliere, 100, 00133, Roma, Italy 11Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California, United States 12European Centre for Medium-Range Weather Forecasts (ECMWF), Reading, United Kingdom 13Earth Observation Research Center, Japan Aerospace Exploration Agency (JAXA), Tsukuba, Ibaraki 305-8505, Japan 14Finnish Meteorological Institute, Climate Research Programme, Erik Palménin aukio 1, FI-00560, Helsinki, Finland 15Climate and Research Institute NILU, P.O. Box 100, 2027 Kjeller, Norway 16 57 institutes, universities, and space agencies Aerosols, clouds, precipitation, and the processes governing their interactions are the grand challenges for current climate science, of the highest priority for the climate science-policy interface, and of great relevance for both Working Groups I and III of the upcoming 7th IPCC cycle. Satellite missions such as CALIPSO and CloudSat have demonstrated the value of aerosol and cloud profiling techniques in understanding the processes governing aerosol-cloud-radiation interactions. The EarthCARE mission will ensure the continuity of these efforts and further advance space-borne lidar and cloud radar profiling synergies. Following EarthCARE, the Atmosphere Observing System (AOS) of NASA will further shed light on the unknown links between aerosols, clouds, atmospheric convection, and precipitation. The geophysical validation of spaceborne high-resolution profilers for aerosols, clouds, and precipitation presents unique challenges. The need for a common practice, capturing lessons learned from earlier missions was identified, and its implementation is tracked under the CEOS Working Group Calibration and Validation action item CV-22-01. As a response, an international consortium of 86 scientists converged on the Best Practice Protocol for the Validation of Aerosol, Cloud, and Precipitation Profiles (ACPPV). The ACPPV convergence process aimed at the optimization of Calibration and Validation techniques (Cal/Val) in terms of instrumentation, sampling strategies and scenarios, and intercomparison methodologies. To this end, the scientific communities involved in past missions have reviewed lessons learned and identified areas where convergence on similar approaches is beneficial. The approaches and recommendations cover correlative site and instrument selection, data processing and quality control, campaign criteria, configurations, scenarios, collocation methods, suggestions on issues concerning scene representativeness, and intercomparison methodologies, including handling of wavelength differences. In addition, for increased statistical relevance of the intercomparison with ground sites, guidance and recommendations for inter-calibration between networks are included, to achieve a “network of networks” to compensate for the profilers' sparse overpasses per site, and avoid biases. Moreover, guidance on the statistical validation through intercomparison between satellite-based remote sensing observations, and on the near-real time validation through monitoring in an NWP data assimilation system are included. Finally, existing gaps in our Cal/Val knowledge are summarized. Given the complexity and diversity of geophysical scenarios and retrievals of aerosol, cloud, and precipitation regimes, the ACPPV document is aimed at knowledge exchange and conveying lessons learned, rather than definitions on single and strict protocols that have been agreed upon in some other domains with fewer degrees of freedom. Here the protocol will be presented and discussed. The ACPPV consortium: Lead Authors: Amiridis, V.1, Marinou, E.1, Hostetler, C.2, Koopman, R.3, Cecil, D., J.4, Moisseev, D.5, Tackett, J.2, Gross, S.6, Baars, H.7, Redemann, J.8, Marenco, F.9, Baldini, L.10, Tanelli, S.11, Fielding, M.12, Janisková, M.12, Tanaka, T.13, O’Connor, E.14, Fjæraa, A., M.15. Contributing Authors: Paschou, P.1,16, Voudouri, K., A.1,16, Ferrare, R.2, Burton, S.2, Schuster, G.2, Kato, S.2, Winker, D.2, Shook, M.2, Bley, S.7, Haarig, M.7, Floutsi, A. A.7, Wandinger, U.7, Trapon, D.7, Pfitzenmaier, L.17, Papagianopoulos, N.18, Mona, L.18, Posselt, D.11, Mason, S.12, Rennie, M.12, Benedetti, A.12, Hogan, R.12,19, Sogacheva, L.14, Balis, D.16, Michailidis, K.16, van Zadelhoff, G., J.20, Nowottnick, E.21, Yorks, J.21, Mroz, K.22, Donovan, D.20, L’Ecuyer, T.23, Okamoto, H.24, Sato, K.24, Henderson, D., S.25, Nishizawa, T.26, Barker, H.27, Cole, J.27, Qu, Z.27, Clerbaux, N.28, Nakajima, T.Y.29, Chase, R.30, Wolff, D.31, Landulfo, E.32, Kirstetter, P., E.33, Mather, J.34, Ohigashi, T.35, Ryder, C.19, Tzallas, V.36, Tsikoudi, I.1,37, Tsekeri, A.1, Tsichla, M.1,38, Koutsoupi, I.1,37, Kubota, T.13, Siomos, N.39, Takahashi, N.40, Horie, H.41, Suzuki, K.42, Mace, J.43, Prakash, G.44, McLean, W.45, Borderies, M.46, Mangla, R.47, Escribano, J.48, Moradi, I.49,50, Zhang, J.51, Rubin, J.52, Ikuta, Y.53, Marbach, T.54, Bojkov, B.54, Accadia, C.54, Fougnie, B.54, Spezzi, L.54, Bozzo, A.54, Chimot, J.54., Jafariserajehlou, J.54, Flament, T.54, Mattioli, V.54, Strandgren, J.54, Barlakas, V.55, and Kollias, P.56,57. Affiliations: 1Institute of Astronomy, Astrophysics, Space Applications & Remote Sensing (IAASARS), National Observatory of Athens (NOA), 15236 Athens, Greece 2NASA Langley Research Center, Hampton, United States 3European Space Research and Technology, European Space Agency (ESA/ESTEC), Keplerlaan 1, 2201 AZ Noordwijk, The Netherlands 4NASA Marshall Space Flight Center, Earth Science Branch, 320 Sparkman Dr NW, AL 35805, Huntsville, United States 5Institute for Atmospheric and Earth System Research, Faculty of Science, University of Helsinki, Finland 6Institut für Physik der Atmosphäre, Deutsches Zentrum für Luft- und Raumfahrt (DLR), Weßling 82234, Germany 7Leibniz Institute for Tropospheric Research (TROPOS), Permoserstraße 15, 04318 Leipzig, Germany 8School of Meteorology, University of Oklahoma, Norman, OK, United States 9The Cyprus Institute, 20 Konstantinou Kavafi Street, 2121 Nicosia, Cyprus 10National Research Council, Insitute of Atmospheric Science and Climate (CNR-ISAC), Via Fosso del Cavaliere, 100, 00133, Roma, Italy 11Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, United States 12European Centre for Medium-Range Weather Forecasts (ECMWF), Reading, United Kingdom 13Earth Observation Research Center, Japan Aerospace Exploration Agency (JAXA), Tsukuba, Ibaraki 305-8505, Japan 14Finnish Meteorological Institute, Climate Research Programme, Erik Palménin aukio 1, FI-00560, Helsinki, Finland 15Climate and Research Institute NILU, P.O. Box 100, 2027 Kjeller, Norway 16Laboratory of Atmospheric Physics, Physics Department, Aristotle University of Thessaloniki, University campus, 54124 Thessaloniki, Greece 17University of Cologne, Institute of Geophysiks and Meteorology, Pohligstraße 3, 50969 Cologne, Germany 18Istituto di Metodologie per l’Analisi Ambientale (IMAA), Consiglio Nazionale delle Ricerche (CNR), C.da S. Loja, 85050 Tito (PZ), Italy 19Department of Meteorology, University of Reading, Reading, United Kingdom 20Royal Netherlands Meteorological Institute (KNMI), De Bilt, the Netherlands 21NASA Goddard Space Flight Center, Mail Code 612, MD 20771 Greenbelt, United States 22National Centre for Earth Observation, University of Leicester, Leicester, United Kingdom 23Department of Atmospheric and Oceanic Sciences, Cooperative Institute for Meteorological Satellite Studies, University of Wisconsin-Madison, Madison, WI, United States 24Research Institute for Applied Mechanics, Kyushu University, Fukuoka, 816-8580, Japan 25Space Science and Engineering Center, University of Wisconsin-Madison, Madison, WI, United States 26Earth System Division, National Institute for Environmental Studies, Tsukuba, 305-8506, Japan 27Environment and Climate Change Canada, Toronto, ON, Canada 28Royal Meteorological Institute of Belgium, Brussels 29Tokai University, Research and Information Center (TRIC), 4-1-1 Kitakaname Hiratsuka, Kanagawa 259-1292, Japan 30Cooperative Institute for Research in Atmosphere (CIRA), Colorado State University, Fort Collins, Colorado, United States 31Mesoscale Atmospheric Processes Lab, NASA Wallops Flight Facility, 34200 Fulton Street, N159/E220, VA 23337 Wallops Island, United States 32Instituto de Pesquisas Energéticas e Nucleares, Cidade Universitária, São Paulo, Brazil 33Hydrometeorology and Remote Sensing Laboratory, University of Oklahoma, Norman, Oklahoma, United States 34Pacific Northwest National Laboratory, Richland, Washington 35National Research Institute for Earth Science and
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.143 | 0.216 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.007 | 0.004 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.012 | 0.006 |
| Open science | 0.007 | 0.014 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.100 | 0.100 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".