Model outputs for publication 'Thin and ephemeral snow shapes melt and runoff dynamics in the Peruvian Andes '
Bibliographic record
Abstract
These are the outputs of the TOPKAPI-ETH model associated with the publication 'Thin and ephemeral snow shapes melt and runoff dynamics in the Peruvian Andes'. The main folders are MB_26, which contains the model outputs for the majority of the analysis, and MB_27 which contains the daily snow grids for the analysis of the snow cover only. They were produced by seperate model runs with the same set-up. These files were created by running the TOPAKPI-ETH set-up which is saved at: 10.5281/zenodo.15301957. The code to analyse these data are available on Zenodo at 10.5281/zenodo.15341457. This will allow the replication of the figures presented in the paper. Details of the contents of each of these files, including the variables saved and their units, can be found in the included pdf TManual_Aug2013.pdf. Links to the relevant table in this document are given below. The files within MB_26 include: glacier_reservoirs.ts > Volumes of snow and ice melt from every simulated glacier, and the discharges from these storages, see Table 18.3 gmb_by_area.ts > Glacier mass balance for all cells per glacier (mm w.e. cumulative) qchan.cell.ts > Hourly discharge from selected stream locations in the catchment, in m^3 s^-^1 reservoirs.ts > Output of the reservoirs in the catchment, see Table 18.4 simulation.tpk > The run file for the model, containing all set-up selections and parameters. TOPKAPI-ETH.log > Log file for the model during the run. TOPKAPI-ETH.xml > Model run file. outputgcl > Timeseries outputs (hourly) from specific cells selected in the catchment, see Table 18.2. The cell number is associated with a grid cell location defined in the RS_CEL.asc file, this file is available in the analysis files at: 10.5281/zenodo.15341457 under Point_analysis>GRID_Data. xxxx.cell (175 files, xxxx = cell number) outputmaps > Gridded outputs at either a monthly or annual timestep saved for the whole model grid. Each file within a folder is a timestep. See Table 18.8. Note that annual files are saved per hydrological year (on the 31st October of each year) and monthly files are saved on the last day of the month. Glacier dynamics files don't save until the 2nd year. soil_a > yyyymmddtttt_PercolA.asc (156 files); yyyymmddtttt_QSoilAChan.asc (156 files); yyyymmddtttt_QSoilSoilA.asc (156 files) soil_b > yyyymmddtttt_PercolB.asc (156 files); yyyymmddtttt_QSoilBChan.asc (156 files); yyyymmddtttt_QSoilSoilB.asc (156 files) state@date > yyyymmddtttt_GlaThickSTT.asc (13 files); yyyymmddtttt_GMB.asc (13 files); yyyymmddtttt_SnowHSTT.asc (13 files) surface > yyyymmddtttt_Exfiltr.asc (156 files); yyyymmddtttt_Infiltr.asc (156 files); yyyymmddtttt_QSurfChan.asc (13 files); yyyymmddtttt_QSurfSurf.asc (156 files); yyyymmddtttt_VolSurf.asc (156 files) temperature > yyyymmddtttt_Temp.asc (156 files) albedo > yyyymmddtttt_Albedo.asc (156 files) channel > yyyymmddtttt_QChan.asc (156 files); yyyymmddtttt_VolChan.asc (156 files) et > yyyymmddtttt_ETAinterc.asc (156 files); yyyymmddtttt_ETArain.asc (156 files); yyyymmddtttt_ETAsoil.asc (156 files); yyyymmddtttt_ETAsurf.asc (156 files); yyyymmddtttt_ETAtot.asc (156 files); yyyymmddtttt_ETP.asc (156 files); glaciers > yyyymmddtttt_MeltG.asc (156 files); yyyymmddtttt_snow2ice.asc (12 files); glaciers_dynamics > yyyymmddtttt_gdgmb.asc (12 files); yyyymmddtttt_gdh0.asc (12 files); yyyymmddtttt_gdh1.asc (12 files); yyyymmddtttt_gdic.asc (12 files); glaciers_stt > yyyymmddtttt_GlaThickStt.asc (156 files); yyyymmddtttt_GMBStt.asc (12 files); grav_snowrd > yyyymmddtttt_SnowRD.asc (156 files); groundwater > yyyymmddtttt_QGwChan.asc (156 files); yyyymmddtttt_QGwGw.asc (156 files); precipitation > yyyymmddtttt_Prec.asc (156 files); yyyymmddtttt_Rain.asc (156 files); yyyymmddtttt_SnowP.asc (156 files); radiation > yyyymmddtttt_GICS.asc (156 files); yyyymmddtttt_GICT.asc (156 files); snow_pack > yyyymmddtttt_MeltS.asc (156 files); yyyymmddtttt_SnowH.asc (156 files); snow_pack_stt > yyyymmddtttt_SnowHStt.asc (156 files); > Outputs for selected subcatchments. Note that outputs of downstream catchments do not include the upstream components, this is corrected in the analysis code. See Table 18.1. The catchment outlines are given in Figure 1a of the main paper. 1.catchment.ts > Rio Santa catchment 2.catchment.ts > Cuchillacocha catchment 3.catchment.ts > Casa de Aqua catchment 4.catchment.ts > Pumapampa catchment 5.catchment.ts > Pachacoto catchment 6.catchment.ts > Llanganuco catchment 7.catchment.ts > Querococha catchment The files within MB_27 include: glacier_reservoirs.ts > Volumes of snow and ice melt from every simulated glacier, and the discharges from these storages, see Table 18.3 gmb_by_area.ts > Glacier mass balance for all cells per glacier (mm w.e. cumulative) qchan.cell.ts > Hourly discharge from selected stream locations in the catchment, in m^3 s^-^1 reservoirs.ts > Output of the reservoirs in the catchment, see Table 18.4 simulation.tpk > The run file for the model, containing all set-up selections and parameters. TOPKAPI-ETH.log > Log file for the model during the run. TOPKAPI-ETH.xml > Model run file. outputgcl > Timeseries outputs (hourly) from specific cells selected in the catchment, see Table 18.2. The cell number is associated with a grid cell location defined in the RS_CEL.asc file, this file is available in the analysis files at: 10.5281/zenodo.15341457 under Point_analysis>GRID_Data. xxxx.cell (175 files, xxxx = cell number) outputmaps > Gridded outputs at either a daily (SnowH) or annual timestep (others) saved for the whole model grid. Each file within a folder is a timestep. See Table 18.8. Note that annual files are saved per hydrological year (on the 31st October of each year). Glacier dynamics files don't save until the 2nd year. state@date > yyyymmddtttt_GlaThickSTT.asc (13 files); yyyymmddtttt_GMB.asc (13 files); yyyymmddtttt_SnowHSTT.asc (13 files) glaciers > yyyymmddtttt_snow2ice.asc (12 files); glaciers_dynamics > yyyymmddtttt_gdgmb.asc (12 files); yyyymmddtttt_gdh0.asc (12 files); yyyymmddtttt_gdh1.asc (12 files); yyyymmddtttt_gdic.asc (12 files); snow_pack > yyyymmddtttt_SnowH.asc (3652 files); > Outputs for selected subcatchments. Note that outputs of downstream catchments do not include the upstream components, this is corrected in the analysis code. See Table 18.1. The catchment outlines are given in Figure 1a of the main paper. 1.catchment.ts > Rio Santa catchment 2.catchment.ts > Cuchillacocha catchment 3.catchment.ts > Casa de Aqua catchment 4.catchment.ts > Pumapampa catchment 5.catchment.ts > Pachacoto catchment 6.catchment.ts > Llanganuco catchment 7.catchment.ts > Querococha catchment
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.143 | 0.046 |
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".