Tibetan Plateau precipitation as depicted by gauge observations, reanalyses and satellite retrievals
Bibliographic record
Abstract
ABSTRACT The European Centre for Medium‐range Weather Forecasts ( ECMWF ) reanalysis ERA ‐40, ERA ‐Interim, University of Washington ( UW ) data, APHRODITE's Water Resources ( APHRODITE ), and Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis ( TMPA ) precipitation estimates are compared with each other and with the corrected gauge observations over the Tibetan Plateau ( TP ) at both basin and plateau scales. The ERA ‐40 generally can capture the broad spatial and temporal distributions in the gauge‐based precipitation estimates over the TP . However, the ERA ‐40 shows little agreement with the gauge‐based precipitation in annual variations for the years before 1979. The anticipated improvements in the ERA ‐Interim precipitation relative to ERA ‐40 have not been realized in this study. It greatly overestimates the Corrected‐China Meteorological Administration ( CMA ) (by 74–290%) and other datasets, although the ERA ‐Interim has a better correspondence than ERA ‐40 with the Corrected‐ CMA data at both annual and monthly scales among the selected basins. All the products can detect the large‐scale precipitation regime, including the monsoon‐dominated precipitation in summer and the westerly‐wind‐induced precipitation in winter. The Corrected‐ CMA and APHRODITE estimates generally show decreasing trends in summer and increasing trends in spring and winter precipitation during 1961–2007 at both basin and plateau scales. However, the Corrected‐ CMA shows larger values in trends and more cases with significance than the APHRODITE , suggesting the effects of the undercatch corrections on the precipitation trends. The use of precipitation derived from current reanalysis projects is less preferable for hydrology analysis than the TP observational data at basin scales. However, using gauge‐based precipitation datasets as hydrologic model forcings should be careful in the river basins where gauge station network is spare, such as in the Yarlung zangbo river basin. Satellite products still hold a great potential for providing high‐resolution precipitation information in remote regions such as the western TP , although more evaluations are needed on the feasibility of satellite precipitation products on the TP where the topography is complex and rainfall rate is highly variable.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".