Matches in Nanopublications for { ?s ?p ?o <https://w3id.org/np/RA2vvz2sr2QHRDcreACSxrHccnfoySdm6iMYs-v-XfOoE/assertion>. }
- 5c135a7b-70bf-45f3-9895-3103e0e29c11 Concept "feedback" assertion.
- 5c135a7b-70bf-45f3-9895-3103e0e29c11 Concept "climate model" assertion.
- 5c135a7b-70bf-45f3-9895-3103e0e29c11 Concept "cloud" assertion.
- 5c135a7b-70bf-45f3-9895-3103e0e29c11 Concept "snow" assertion.
- 5c135a7b-70bf-45f3-9895-3103e0e29c11 Concept "water content" assertion.
- 5c135a7b-70bf-45f3-9895-3103e0e29c11 Concept "climate sensitivity" assertion.
- 5c135a7b-70bf-45f3-9895-3103e0e29c11 Concept "bias" assertion.
- 5c135a7b-70bf-45f3-9895-3103e0e29c11 FieldOfResearch "earth sciences" assertion.
- 5c135a7b-70bf-45f3-9895-3103e0e29c11 IPTC "Meteorology" assertion.
- 5c135a7b-70bf-45f3-9895-3103e0e29c11 IPTC "Weather" assertion.
- 5c135a7b-70bf-45f3-9895-3103e0e29c11 IPTC "Climate change" assertion.
- 5c135a7b-70bf-45f3-9895-3103e0e29c11 IPTC "IT-computer sciences" assertion.
- 5c135a7b-70bf-45f3-9895-3103e0e29c11 IPTC "Environment" assertion.
- 5c135a7b-70bf-45f3-9895-3103e0e29c11 Lemma "rate" assertion.
- 5c135a7b-70bf-45f3-9895-3103e0e29c11 Lemma "phase" assertion.
- 5c135a7b-70bf-45f3-9895-3103e0e29c11 Lemma "feedback" assertion.
- 5c135a7b-70bf-45f3-9895-3103e0e29c11 Lemma "climate model" assertion.
- 5c135a7b-70bf-45f3-9895-3103e0e29c11 Lemma "cloud" assertion.
- 5c135a7b-70bf-45f3-9895-3103e0e29c11 Lemma "CMIP phase 6" assertion.
- 5c135a7b-70bf-45f3-9895-3103e0e29c11 Lemma "snowfall" assertion.
- 5c135a7b-70bf-45f3-9895-3103e0e29c11 NASA "geosciences" assertion.
- 5c135a7b-70bf-45f3-9895-3103e0e29c11 Phrase "cloud phase" assertion.
- 5c135a7b-70bf-45f3-9895-3103e0e29c11 Phrase "cloud feedback" assertion.
- 5c135a7b-70bf-45f3-9895-3103e0e29c11 Phrase "global climate models" assertion.
- 5c135a7b-70bf-45f3-9895-3103e0e29c11 Phrase "phase bias" assertion.
- 5c135a7b-70bf-45f3-9895-3103e0e29c11 Phrase "snow formation" assertion.
- 5c135a7b-70bf-45f3-9895-3103e0e29c11 Phrase "surface snowfall rate" assertion.
- 5c135a7b-70bf-45f3-9895-3103e0e29c11 Sentence "Is there a correlation between the cloud phase and surface snowfall rate in GCMs?" assertion.
- 5c135a7b-70bf-45f3-9895-3103e0e29c11 Sentence "To better understand the link between biases in cloud phase and surface snowfall rate, we try to find a relationship between ice water path and surface snowfall in GCMs." assertion.
- 5c135a7b-70bf-45f3-9895-3103e0e29c11 Sentence "Cloud feedbacks are a major contributor to the spread of climate sensitivity in global climate models (GCMs) [1] Among the most poorly understood cloud feedbacks is the one associated with the cloud phase, which is expected to be modified with climate change [2] Cloud phase bias, in addition, has significant implications for the simulation of radiative properties and glacier and ice sheet mass balances in climate models." assertion.
- 5c135a7b-70bf-45f3-9895-3103e0e29c11 TimeReference "2020" assertion.
- 5c135a7b-70bf-45f3-9895-3103e0e29c11 TimeReference "from 1985 to 2014" assertion.
- 3952 description "" assertion.
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- 5c135a7b-70bf-45f3-9895-3103e0e29c11 description "Supercooled Liquid-Containing Clouds (sLCCs) play a significant role in Earth's radiative budget and the hydrological cycle, especially through surface snowfall production. Evaluating state-of-the-art climate models with respect to their ability to simulate the frequency of occurrence of sLCCs and the frequency with which they produce snow is, therefore, critically important. Here, we compare these quantities as derived from satellite observations, reanalysis datasets, and Earth System Models from Phase 6 of the Coupled Model Intercomparison Project (CMIP6) and find significant discrepancies between the data sets for mid and high latitudes in both hemispheres. Specifically, we find that the ERA5 reanalysis and ten CMIP6 models consistently overestimate the frequency of sLCCs and snowfall frequencies from sLCCs compared to CloudSat-CALIPSO satellite observations, especially over open ocean regions. The biases are very similar for ERA5 and the CMIP6 models, which indicates that the discrepancies in cloud phase and snowfall stem from differences in the representation of cloud microphysics rather than the representation of meteorological conditions. This, in turn, highlights the need for refinements in the models’ parameterizations of cloud microphysics in order for them to represent cloud phase and snowfall accurately. The thermodynamic phase of clouds and precipitation has a strong influence on simulated climate feedbacks and, thus, projections of future climate. Understanding the origin(s) of the biases identified here is, therefore, crucial for improving the overall reliability of climate models." assertion.
- 06b8228f-e7bc-48b5-9632-0500f629a2dc description "ERA5 data wrangling required to make it comparable" assertion.
- a68289fb-7a75-4ac9-a652-038e35f004e7 description "Use ReviewNB to review jupyter notebooks before merging PR." assertion.
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- e9286361-7292-48ea-a4fa-0538d4800f68 description "Data wrangling which is required to make CloudSat comparable." assertion.
- fb124247-04cb-452b-ad70-d86d7f6fd325 description "Analysis required for CMIP6 analysis" assertion.
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- 5c135a7b-70bf-45f3-9895-3103e0e29c11 contributor mailto:anne.claire.fouilloux@rohub.com assertion.
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- 5c135a7b-70bf-45f3-9895-3103e0e29c11 contributor mailto:r.o.david@geo.uio.no assertion.
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- 5c135a7b-70bf-45f3-9895-3103e0e29c11 Domain "meteorology" assertion.
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- 5c135a7b-70bf-45f3-9895-3103e0e29c11 cite-as "Hellmuth, Franziska, Anne Claire Fouilloux, Robert Oscar David, and Trude Storelvmo. "Connection of Surface Snowfall Bias to Cloud Phase Bias - Satellite Observations, ERA5, and CMIP6." ROHub. Jan 31 ,2022. https://w3id.org/ro-id/5c135a7b-70bf-45f3-9895-3103e0e29c11." assertion.
- 5c135a7b-70bf-45f3-9895-3103e0e29c11 funding 758005 assertion.
- 758005 title "MC2 Mixed Phase clouds and climate" assertion.
- 5c135a7b-70bf-45f3-9895-3103e0e29c11 about 3952 assertion.
- 5c135a7b-70bf-45f3-9895-3103e0e29c11 about 1892 assertion.
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