A 20-year satellite-reanalysis-based climatology of extreme precipitation characteristics over the Sinai Peninsula
Bibliographic record
Abstract
Abstract. Extreme precipitation events and associated flash floods caused by synoptic cyclonic systems profoundly impact society and the environment, particularly in arid regions. This study brings forward a satellite-reanalysis-based approach to quantify extreme precipitation characteristics over the Sinai Peninsula (SiP) in Egypt from a statistical–synoptic perspective for the period of 2001–2020. With a multi-statistical approach developed in this research, SiP's wet and dry periods are determined. Using satellite observations of precipitation and a set of derived precipitation indices, we characterize the spatiotemporal variations of extreme rainfall climatologies across the SiP. Then, using the reanalysis datasets, synoptic systems responsible for the occurrence of extreme precipitation events along with the major tracks of cyclones during the wet and dry periods are described. Our results indicate that trends and spatial patterns of the rainfall events across the region are inconsistent in time and space. The highest precipitation percentiles (∼20 mm per month), frequencies (∼15 d per month with rainfall ≥10 mm d−1), standard deviations (∼9 mm month per month), and monthly ratios (∼18 %) are estimated in the northern and northeastern parts of the region during the wet period, especially in early winter; also, a substantial below-average precipitation condition (drier trend) is clearly observed in most parts except for the south. Mediterranean cyclones accompanied by the Red Sea and Persian troughs are responsible for the majority of extreme rainfall events year-round. A remarkable spatial relationship is found between SiP's rainfall and the atmospheric variables of sea level pressure, wind direction, and vertical velocity. A cyclone-tracking analysis indicates that 125 cyclones (with rainfall ≥10 mm d−1) formed within, or transferred to, the Mediterranean basin and precipitated over the SiP during wet periods compared to 31 such cyclones during dry periods. It is estimated around 15 % of cyclones with sufficient rainfall >40 mm d−1 would be capable of leading to flash floods during the wet period. This study, therefore, sheds new light on the extreme precipitation characteristics over the SiP and its association with dominant synoptic-scale mechanisms over the eastern Mediterranean region.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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 source (direct Gemma or distilled Codex), 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".