Exploring solar and wind energy resources in North Korea with COMS MI geostationary satellite data coupled with numerical weather prediction reanalysis variables
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Despite their potential as a naturally-available clean energy option, the renewable energy resources of the Democratic People's Republic of Korea (i.e., North Korea) have rarely been evaluated. Therefore, to estimate the availability of land surface solar irradiance necessary for solar applications and to model available energy potential, physically-based models drawing on Communication, Ocean and Meteorological Satellite (COMS) data and associated statistics for key atmospheric constituents, were employed. To assess wind energy resources, model output statistics (MOS) were integrated from post-processed Local Data Assimilation and Prediction System (LDAPS) variables, thereby removing any systematic bias arising from long-term regression methods. The root mean square error (RMSE) and mean bias error (MBE) served to compare pyranometer- and satellite-sourced solar radiation, under instantaneous (87.90 W m−2 and 16.84 W m−2, respectively) and daily ‘all sky conditions’ (624.98 Wh m−2 d−1 and 13.89 Wh m−2 d−1, respectively). These low values indicate that satellite-based solar irradiance is sufficiently accurate to be used to model future land surface solar energy in North Korea. In the evaluation of wind energy resources, daily wind speeds obtained from Numerical Weather Prediction (NWP) reanalysis fields showed good accuracy compared to a meteorological tower measurement (RMSE = 0.37 m s−1 and MBE = 0.24 m s−1). In the study region, mean wind energy potential (from 2013–2015) was 3.44 kWh m−2 d−1, whereas solar energy potential was slightly lower at 3.36 kWh m−2 d−1; this can be attributed to the nation's mountainous terrain and high latitude. Although the region's mountainous terrain may be an obstacle for future development of renewable energy infrastructure, these initial annual mean solar and wind power density results illustrate the significant renewable energy potential of North Korea. This situates the country in a position to promote the United Nations Sustainable Development Goal (SDG #7) of integrating cleaner and more sustainable energy resources through solar and wind power.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it