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Record W2022788656 · doi:10.1088/1748-9326/2/4/045008

Northern Hemisphere high latitude climate and environmental change

2007· article· en· W2022788656 on OpenAlexaboutno aff
Pavel Groisman, A. J. Soja

Bibliographic record

VenueEnvironmental Research Letters · 2007
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological Studies and Exploration
Canadian institutionsnot available
FundersNational Institutes of Health
KeywordsClimate changeGlobal changeEarth system scienceNorthern HemisphereClimatologyEnvironmental scienceGeographyGlobal warmingBiosphereGeologyOceanographyEcology

Abstract

fetched live from OpenAlex

High Northern Hemisphere latitudes are undergoing rapid and significant change associated with climate warming. Climatic change in this region interacts with and affects the rate of the global change through atmospheric circulation, biogeophysical, and biogeochemical feedbacks. Changes in the surface energy balance, hydrologic cycle, and carbon budget feedback to regional and global weather and climate systems. Two-thirds of the Northern Hemisphere high latitude land mass resides in Northern Eurasia (∼20% of the global land mass), and this region has undergone sweeping socio-economic change throughout the 20th century. How this carbon-rich, cold region component of the Earth system functions as a regional entity and interacts with and feeds back to the greater global system is to a large extent unknown. To mitigate the deficiencies in understanding these feedbacks, which may in turn hamper our understanding of the global change rates and patterns, an initiative was formed. Three years ago the Northern Eurasia Earth Science Partnership Initiative (NEESPI) was established to address large-scale and long-term manifestations of climate and environmental change in this region. The NEESPI Science Plan and its Executive Summary have been published at the NEESPI web site ( neespi.org ). Since 2004, NEESPI participants have been able to seed several waves of research proposals to international and national funding agencies and institutions and also contribute to the International Polar Year. Currently, NEESPI is widely recognized and endorsed by several Earth System Science Partnership (ESSP) programmes and projects: the International Geosphere and Biosphere Programme, the World Climate Research Programme through the Global Energy and Water Cycle Experiment and Climate and Cryosphere Projects, the Global Water System Project, Global Carbon Project, Global Land Project, and the Integrated Land Ecosystem—Atmosphere Processes Study. Through NEESPI, more than 100 individually funded projects (always with international participation) in the United States, Russian Federation, China, European Union, Japan, and Canada have been mutually united to explore the scientifically significant Northern Eurasian region. NEESPI scientists have been quite productive during the past two years (2005–2006) publishing more than 200 books, book chapters, and papers in refereed journals. NEESPI sessions at international conferences are open to everyone who works on environmental and climate change problems in Northern Eurasia and the circumpolar boreal zone. This thematic issue brings together articles from the authors who presented their latest results at the Annual Fall American Geophysical Union Meeting in San Francisco (December 2006). The research letters in this issue are preceded by two editorial papers (Leptoukh et al and Sherstyukov et al ) devoted to informational support of research in the NEESPI domain that is critical to the success of the Initiative. The following papers are quite diverse and are assembled into five groups devoted to studies of climate and hydrology, land cover and land use, the biogeochemical cycle and its feedbacks, the cryosphere, and human dimensions in the NEESPI domain and the circumpolar boreal zone. Focus on Northern Hemisphere High Latitude Climate and Environmental Change Contents Editorials NASA NEESPI Data and Services Center for Satellite Remote Sensing Information Gregory Leptoukh, Ivan Csiszar, Peter Romanov, Suhung Shen, Tatiana Loboda and Irina Gerasimov NEESPI Science and Data Support Center for Hydrometeorological Information in Obninsk, Russia B G Sherstyukov, V N Razuvaev, O N Bulygina and P Ya Groisman Climate and hydrology Changes in the fabric of the Arctic's greenhouse blanket Jennifer A Francis and Elias Hunter Spatial variations of summer precipitation trends in South Korea, 1973–2005 Heejun Chang and Won-Tae Kwon Climate variations and changes in extreme climate events in Russia O N Bulygina, V N Razuvaev, N N Korshunova and P Ya Groisman Land cover and land use Responses of the circumpolar boreal forest to 20th century climate variability Andrea H Lloyd and Andrew G Bunn Mapping Russian forest biomass with data from satellites and forest inventories R A Houghton, D Butman, A G Bunn, O N Krankina, P Schlesinger and T A Stone The biogeochemical cycle and its feedbacks Sphagnum peatland development at their southern climatic range inWest Siberia: trends and peat accumulation patterns Anna Peregon, Masao Uchida and Yasuyuki Shibata Methane emissions from western Siberian wetlands: heterogeneity and sensitivity to climate change T J Bohn, D P Lettenmaier, K Sathulur, L C Bowling, E Podest, K C McDonald and T Friborg Ecosystem responses to recent climate change and fire disturbance at northern high latitudes: observations and model results contrasting northern Eurasia and North America S J Goetz, M C Mack, K R Gurney, J T Randerson and R A Houghton Ecosystems and climate interactions in the boreal zone of northern Eurasia N N Vygodskaya, P Ya Groisman, N M Tchebakova, J A Kurbatova, O Panfyorov, E I Parfenova and A F Sogachev The cryosphere Potential feedback of thawing permafrost to the global climate system through methane emission O A Anisimov Glacier changes in the Siberian Altai Mountains, Ob river basin, (1952–2006) estimated with high resolution imagery A B Surazakov, V B Aizen, E M Aizen and S A Nikitin Glaciers and hydrological changes in the Tien Shan: simulation and prediction V B Aizen, E M Aizen and V A Kuzmichonok Human dimensions Food and water security in a changing arctic climate Daniel M White, S Craig Gerlach, Philip Loring, Amy C Tidwell and Molly C Chambers

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)0.001
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.062
Threshold uncertainty score0.125

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0370.006

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 head0.039
GPT teacher head0.242
Teacher spread0.203 · 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 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

Citations10
Published2007
Admission routes1
Has abstractyes

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