Recent Advances in Drought Monitoring
Bibliographic record
Abstract
Recent widespread, severe, and long-lasting droughts across North America have heightened awareness of and interest in how to better monitor drought and its impacts. Since its inception in 1999, the National Drought Mitigation Center (NDMC), United States Department of Agriculture (USDA) and NOAA’s Climate Prediction Center (CPC) and National Climatic Data Center (NCDC) have partnered to produce the weekly U.S. Drought Monitor (http://droug ht.unl.edu/m onitor/), a comprehensive drought assessment product based on a simple 5- category severity classification. On the heels of its widespread acceptance and usage, the NCDC, CPC, USDA, NDMC and scientists from Canada and Mexico have worked together to produce a monthly experimental North American Drought Monitor (http://www.ncdc.noaa.gov/oa/climate/monitoring/droug ht/nadm/index.html. Other projects are underway. An informal interagency push toward better water resource assessment has a goal of developing a watershed-based hydrological drought map that would complement the weekly U.S. Drought Monitor map. The Western Governor’s Association and NOAA are developing a framework for a National Integrated Drought Information System. The NDMC is also involved in projects looking to improve our spatial and temporal capabilities in monitoring drought. By tapping into the Applied Climate Information System (ACIS), the NDMC has worked with UNL’s Computer Science and Engineering department and the High Plains Regional Climate Center (HPRCC) to develop a web-interface based tool, which allows the user to analyze drought indicators like the SPI, PDSI, and Newhall Soil Moisture Model. A collaborative team of scientists from the USGS EROS Data Center, the NDMC, and the HPRCC is developing a prototype monitoring system that integrates information from climate and satellite databases using data mining techniques. The goal of this project is modeling the relationships between climate-based drought indicators and satellite-derived seasonal metrics from the NDVI (Normalized Difference Vegetation Index). This includes delivering near-real time information about drought-affected areas in the U.S. using the Internet as the primary delivery mechanism. Clearly, the products and the cooperative efforts described above have advanced our drought monitoring capabilities and have led us to a better understanding of drought as a complex hazard while also improving our capacity to assess, predict and/or provide an early warning of drought.
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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 | 0.001 |
| 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 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".