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Record W2460330513

Cryospheric mass variations from GRACE

2015· dissertation· en· W2460330513 on OpenAlexaboutno aff
Karoline Skår

Bibliographic record

VenueDuo Research Archive (University of Oslo) · 2015
Typedissertation
Languageen
FieldEarth and Planetary Sciences
TopicGeophysics and Gravity Measurements
Canadian institutionsnot available
Fundersnot available
KeywordsSpherical harmonicsGravitational fieldGeodesyGravity of EarthGeologyCryosphereIce sheetPost-glacial reboundClimatologyGeophysicsGeomorphologyPhysicsSea ice
DOInot available

Abstract

fetched live from OpenAlex

The Earth’s gravity field is constantly changing due to mass redistribution from\nice melting in the cryosphere and geophysical processes. With use of data from\ndedicated gravity satellite missions variations in the Earth’s gravity field over a\ntime series can be determined.\nThis thesis tries to give an explanation on how the Earth’s gravity field changes on\na global scale and regionally with the use of data from the GRACE-mission over a\ntime period. With comparison between three different GRACE-solutions and the\nuse of SLR-observations, the mass changes over Greenland has been estimated. In\naddition, a further look into the lower degree spherical harmonics has been studied,\nto explain and give a conclusion of how the lower degree spherical harmonics from\nGRACE are affecting the calculations of the gravity field.\nGRACE-data has its uncertainties in the lower degree spherical harmonics. The\nC 20 -coefficients from GRACE has large variances and therefore needs to be replaced\nby SLR-values when looking at global variations. Trend calculations shows how\npost glacial rebound(GIA) influence Canada and Fennoscandia, and ice melting\nover Greenland, Alaska and Antarctica.\nThe investigation of lower degree spherical harmonic coefficients shows that it is not\nsignificant how the C 20 -coefficients are processed when estimating mass changes\nover the area of Greenland.\nDue to restricted spatial resolution of the gravity field models and spatial averag-\ning, it is hard to get a real estimate of the mass changes over a specific area. This\nis called the leakage effect and has been studied over the area of Greenland. The\nleakage effect has been estimated and restored, and mass change over Greenland\nhas been estimated to be between -1832.76 km^3 and -2087.72 km^3 , depending on\nthe model used.\n\n\nJordas tyngdefelt er i stadig endring på grunn av masseforflytning fra isavsmelting i kryosfæren og geofysiske prosesser. Ved bruk av data fra gravimetrisatelliter kan \ndisse variasjonene i jordas tyngdefelt bestemmes over en tidsserie.\n\nDenne oppgaven prøver å gi en forklaring på hvordan jordas tyngdefelt forandres globalt og regionalt ved bruk av data fra GRACE over en tidsperiode. Ved å sammenligne tre ulike GRACE-løsninger og ved bruk av SLR-observasjoner, har masseendringer over Grønnland blitt estimert. I tillegg har det blitt sett nærmere på de laveregrads sfærisk harmoniske koeffisientene, for å gi en forklaring på hvordan disse koeffisientene fra GRACE påvirker beregninger av jordens tyngdefelt.\n\nGRACE-data har sin usikkerhet i de laveregrads sfærisk harmoniske koeffisienter. C20-koeffisientene fra GRACE har store varianser og må derfor bli byttet ut med SLR-verdier når man ser på globale variasjoner. Trendberegninger viser hvordan postglasial landheving(GIA) påvirker områdene Canada og Fennoskandia, og i tillegg issmelting over Grønnland, Alaska og Antarktis.\n\nVed å se nærmere på de laveregradskoeffisientene kan det bli observert at det ikke er av stor betydning hvordan man behandler C20-koeffisienter når masseendringer over Grønnland blir estimert.\n\nPå grunn av begrenset romlig oppløsning og romlig glatting av tyngdefeltsmodeller, er det vanskelig å gi et realistisk estimat av masseendringer over et område. Dette blir kalt "leakage"-effekt. "Leakage"-effekten har blitt estimert og gjennopprettet, og masseendringer over Grønnland har blitt beregnet til å være mellom -1832.76 km^3 og -2087.72 km^3, avhengig av hvilken modell som har blitt brukt.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.031
Threshold uncertainty score0.061

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.004

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.

Opus teacher head0.044
GPT teacher head0.264
Teacher spread0.220 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

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Citations0
Published2015
Admission routes1
Has abstractyes

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