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Record W96711839

Interaction of land surface processes and the atmosphere in the Arctic - sensitivities and extremes

2011· dissertation· en· W96711839 on OpenAlexaboutno aff
Heidrun Matthes

Bibliographic record

VenueHelmholtz-Zentrum für Polar-und Meeresforschung (Alfred-Wegener-Institut) · 2011
Typedissertation
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsnot available
Fundersnot available
KeywordsArcticClimatologyEnvironmental scienceAlbedo (alchemy)Climate changeThe arcticClimate modelClimate sensitivitySpatial variabilityOceanographyGeology
DOInot available

Abstract

fetched live from OpenAlex

For several years, the Arctic has now been in the focus of scientific debate on climate
\nchange. It is a region of high spatio-temporal climate variability and additionally a region
\nof high climate sensitivity due to strong feedback processes like the ice-albedo feedback. As
\nthere is a strong linkage to the global climate system, changes in the Arctic impact onto the
\nglobal climate. In modeling the Arctic climate, regional climate models are an important tool
\nbecause with their high resolution they provide the possibility to account for the horizontally
\nheterogeneous soil and surface characteristics. Here, the regional climate model HIRHAM is
\nused with 25km resolution for the analysis of spatial patterns, variability and trends of the
\nArctic climate and temperature-derived indices describing climate extremes.
\nInter-annual temperature variability (ITV) for present-day conditions (1958 to 2008) is
\nexamined from station data, the ERA40 re-analysis and HIRHAM results. It shows a pronounced
\ndecadal variability and specific regional and seasonal characteristics. Seasonal temperatures
\nin general show warming trends, though they are mostly not statistically significant.
\nIntra-seasonal extreme temperature range (ETR) trends were of mixed sign and only
\nsignificant from station data over the eastern Russian Arctic. In general, the spatial pattern
\nand magnitude of the Arctic temperature variability, both of seasonal temperature and
\nintra-seasonal ETR, are well reproduced by HIRHAM.
\nThe large variability of the Arctic temperature, which is inherent in the analysis period,
\ndemonstrates that natural variability is an important factor in the Arctic climate. This
\nvariability is not restricted to climate means but also appears in temperature extremes. An
\nanalysis of station-derived an re-analysis-based climate indices shows complex behavior, some
\nmeasures like frost days show consistent decrease (i.e. warming), while others like cold spell
\ndays provide a more diverse picture. As with seasonal temperatures, only few trends are found
\nstatistically significant. The indices examined exhibit strong inter-annual and decadal-scale
\nvariability and heterogeneous spatial patterns.
\nThese climate indices are then employed in the validation of the HIRHAM model. The
\nmodel well reproduces trends and variability of most indices while there is an offset in some
\nabsolute values (e.g. frost days, growing degree days). Other measures like cold and warm
\nspells are calculated with non-systematic biases; deviations in trends and variability occur in
\nsummer for cold spells and in spring and summer for warm spells due to an earlier spring
\nwarming and a too low variability of the maximum temperature over sea ice in HIRHAM.
\nHIRHAM is furthermore used as a downscaling tool for future projections (ECHAM5/MPIOM
\noutput under the IPCC scenario SRES A1B). The strong increase in mean annual air
\ntemperature (5–8 K) is expected to increase active layer thickness and permafrost boundaries
\nwill move northwards. On top of this general warming trend, the additional analysis of
\nfuture changes, using the mean conditions for the warmer climate, highlights some particularly
\nvulnerable regions (West Siberian Plain, Laptev Sea coast, Canadian Archipelago), which are
\nprojected to be warmer, to experience increased warm spells and to be wetter in summer; all
\nthis contributes to amplify the permafrost degradation initiated by the general warming.
\nDifferent realizations of HIRHAM are run for a sensitivity study looking into the importance
\nof land-surface-conditions for climate model projections. The different model setups are:
\n(1) the incorporation of freezing/thawing of soil moisture, (2) the inclusion of top organic soil
\nhorizons typical for the Arctic and (3) a vegetation shift due to a changing climate. Direct
\nthermal responses in 2m air temperature and turbulent heat fluxes over land lead to changes
\nin mean sea level pressure and geopotential height throughout the Arctic. This points to
\nthe importance of dynamical feedbacks within the atmosphere-land system. Land and soil
\nprocesses have a distinct remote influence on large scale circulation patterns in addition to
\ntheir direct, regional effects. The projected changes are clearly afflicted with uncertainties
\ndue to the different setups for land-surface-conditions; the highest temperature uncertainties
\nare found over tundra regions. This demonstrates that for an improvement of the land-surface
\nscheme of the HIRHAM model, all three representations of land-surface-processes have to be
\nincorporated.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.595
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.026
GPT teacher head0.257
Teacher spread0.230 · 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 teacher head, not a consensus.

Study designObservational
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".

Quick stats

Citations0
Published2011
Admission routes1
Has abstractyes

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