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Record W2783348152 · doi:10.5194/hess-2017-756

Spatiotemporal Patterns and Trends of Precipitation and Their Correlations with Related Meteorological Factors by Two Sets of Reanalysis Data in China

2018· article· en· W2783348152 on OpenAlex
Jinhui Jeanne Huang‬‬‬‬, Nan Zhang, Gye-Woon Choi, Edward A. McBean, Qian Zhang

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental and Agricultural Sciences
Canadian institutionsUniversity of Guelph
FundersGoddard Space Flight CenterNational Oceanic and Atmospheric AdministrationGuangdong Academy of SciencesMinistry of Science and Technology of the People's Republic of ChinaNational Natural Science Foundation of ChinaNational Aeronautics and Space Administration
KeywordsPrecipitationClimatologyEnvironmental scienceMonsoonPlateau (mathematics)Latent heatChinaForcing (mathematics)Atmospheric sciencesAridHumidityGeographyMeteorologyGeology

Abstract

fetched live from OpenAlex

Abstract. This paper investigates the spatial-temporal characteristics of the changes in precipitation for China and the influence of other meteorological factors on precipitation. Two reanalysis datasets at monthly scale, namely, the GLDAS2 phase 2 forcing data 0.5 × 0.5 (1948 ~ 2008) and National Centers for Environmental Prediction (NCEP) data were employed. The Mann-Kendall trend test identified the annual and seasonal changes in four meteorological factors for precipitation, air temperature, long wave radiation and surface pressure. Confidence levels of 95 % were taken as thresholds to classify the significance of positive and negative trends. The trend analysis was conducted in three storm zones (I-Eastern Monsoon Region, II-Northern Inland Region and III-Qinghai-Tibetan Plateau Region) specified by Wang (2002). The findings indicate: 1) Air temperature, specific humidity and downward long wave radiation, have strong correlation with precipitation, especially for the eastern monsoon region of China; while surface pressure has very weak correlation with precipitation. 2) Latent heat shows very strong correlation with precipitation throughout China except for a small, extremely arid area in north China where large portions of the area are deserts. 3) The correlation between the volumetric soil moisture with precipitation and latent heat are controlled by precipitation with the characteristics of high annual precipitation and high correlations. 4) For precipitation, an increasing tendency in precipitation for the southeastern monsoon region and a decreasing tendency for the northeastern monsoon region (the drier region) were observed. 5) Strong increasing tendencies for air temperature and downward long wave radiation, were observed in the northeastern monsoon region and the western area of Qinghai-Tibetan Plateau. 6) Due to changes in precipitation and air temperature and downward long wave radiation, the scarcity of water resources in northeastern monsoon region and flooding problems in southeastern monsoon region may become more severe. 7) The study shows that agricultural development in China may require a shift between northern and western areas to adapt to the shift in precipitation patterns.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.674

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.012
GPT teacher head0.227
Teacher spread0.214 · 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

Quick stats

Citations5
Published2018
Admission routes1
Has abstractyes

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