Advancing Global-and Continental-Scale Hydrometeorology: Contributions of GEWEX Hydrometeorology Panel
Bibliographic record
Abstract
Over the past 9 years, the Global Energy and Water Cycle Experiment (GEWEX), under the auspices of the World Climate Research Programme (WCRP), has coordinated the activities of the Continental Scale Experiments (CSEs) and other related research through the GEWEX Hydrometeorology Panel (GHP). The GHP contributes to the WCRP'S objective of “developing the fundamental scientific understanding of the physical climate system and climate processes [that is] needed to determine to what extent climate can be predicted and the extent of man's influence on climate.” It also contributes to more specific GEWEX objectives, such as determining the hydrological cycle and energy fluxes, modeling the global hydrological cycle and its impacts, developing a capability to predict variations in global and regional hydrological processes, and fostering the development of observing techniques, data management and assimilation systems. GHP activities include diagnosis, simulation, and experimental prediction of regional water balances and process and modeling studies aimed at understanding and predicting the variability of the global water cycle, with an emphasis on regional coupled land–atmosphere processes. GHP efforts are central to providing a scientific basis for assessing critical science issues, such as the consequences of climate change for the intensification of the global hydrological cycle and its potential impacts on regional water resources. This article provides an overview of the role and evolution of the GHP and describes scientific issues that the GHP is seeking to address in collaboration with the international science community.
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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 | 0.011 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".