Spatio-temporal distribution and temporal periodicity of annual precipitation in Shaanxi Province
Bibliographic record
Abstract
Using precipitation data of every stations located in Shaanxi Province during 1959 to 2009,applying the statistical methods such as the Mexican hat wavelet function,linear trend analysis and Mann-Kendall method,the features and trend of the annul precipitation temporal and spatial distribution of 51 years in Shaanxi Province was analyzed.It is very important for us to strengthen the research of climate change law under the background of the global climate change,for which helps us raise the prediction ability of short-term climate,this paper took the Shaanxi Province as an example,analyzed the temporal and spatial distribution and trend of the annual precipitation in Shaanxi Province during 1959-2009,revealed the complex structure of annual precipitation in Shaanxi Province in multiple time scale,analyzed the period and mutation point of precipitation sequence in different time scale,and identified the main cycle.The result showed as follows:(1)In 1959-2009,average annual rainfall of Shaanxi Province had three periods which are 3-7 years,10-17 years,17-30 years and the 10-17 year is most obvious;(2)In the 1959-2009 time series,average annual precipitation change in Shaanxi Province was relatively stable;(3)The three regions with an average annual precipitation changes are relatively stable,from an average annual precipitation view,the northern and southern Shaanxi presented slightly down trend,the Guanzhong Plain showed a faint rising trend;(4)No significant mutations in northern Shaanxi,the significant mutations of Guanzhong Plain and southern Shaanxi respectively were in 1993 and 1991;(5)The evolution of rainfall in each area had three kinds of cycle rules.The micro scale that is 3 to 8 years behaved messy and was not significant.In medium scale,the precipitation cycle in Guanzhong Plain and southern Shaanxi was significant that is 10-17 years,precipitation cycle in northern Shaanxi showed irregularly.In macro scale,precipitation cycle of northern Shaanxi was 23-30 years,precipitation cycle of Guanzhong Plain was similar to southern Shaanxi's,18 to 25 years.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".