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                "fi": "### Käytäväharvennus – menetelmä nuorten metsien ensimmäiseen koneelliseen harvennukseen ###\n\nLuonnonvarakeskuksen, Suomen metsäkeskuksen ja UPM:n yhteistyönä hankkeessa kehitettiin työmenetelmä nuorten metsien ensimmäiseen koneelliseen harvennukseen. Menetelmästä ja kokeesta on sittemmin käytetty termiä väyläharvennus (VAYLA).\n\nKehittämistyössä selvitettiin käytäväharvennuksen vaikutukset hakkuun tehokkuuteen, kasvatettavaan puustoon ja harvennuskertymään sekä laadittiin käytäväharvennuksen koulutuspaketti hyödynnettäväksi hankkeen jälkeen. \n\nKehittämishankkeen loppuraportti on julkaistu vuonna 2019. \n\nHankkeen koemetsiköt sijaitsevat Konnevedellä, Suonelassa ja Paiholassa. Jokaisessa koemetsikössä on 9-20 kpl vierekkäin olevia koeruutuja. \n\nKoeruuduilla on sovellettu eri harvennusmenetelmiä:\n- Konnevesi 3; valikoiva harvennus, käytäväharvennus & ohjeellinen käytävän paikka merkitty, käytäväharvennus & kuljettaja valitsi käytävien paikan.\n- Suonenjoki 4; valikoiva harvennus, suora käytäväharvennus, viuhkamainen käytäväharvennus, valittu käytäväharvennus\n- Paihola 3; valikoiva harvennus ennakkoraivattu, käytäväharvennus ennakkoraivattu, käytäväharvennus ei ennakkoraivausta\n\n### Aineisto ###\n\nKokeessa on maastomittauksina tuotettu puustonmittausaineistoa. Kokeen metsät on mitattu kolmena eri ajankohtana. Lähtömittaus tehtiin ennen toimenpiteitä (2017-2018), uusi mittaus harvennuksen jälkeen (2018) ja viimeisin mittaus on tehty noin 4 vuotta harvennuksen jälkeen, vuonna 2022. \n\nEnnen testihakkuuta koealojen puusto mitattiin 100 m2 puustomittausaloilta. Kaikista puista mitattiin rinnankorkeusläpimitta ja koepuista pituus ja elinvoimaisen latvuksen pituus. \n\nTestihakkuun jälkeen 50 x 20 m koealoilta mitattiin kaikkien puiden rinnankorkeusläpimitta sekä puiden sijaintikoordinaatit.\n\nVuoden 2022 puustonmittauksessa kaikista puista on mitattu rinnankorkeusläpimitta, sekä on silmämääräisesti arvioitu, onko puu 0 = ei reunapuu, 1 = ajouran reunapuu, 2 = väylän reunapuu tai 3 = sekä ajouran että väylän reunapuu.\nReunapuu on sellainen puu, jonka latvus on vapaa muiden puiden kilpailusta (latvuksista) ajouran ja/tai väylän suuntaan.\nLisäksi koepuista on mitattu pituus ja elävän latvuksen alaraja, noin 30 kpl koepuuta harvennuskäsittelytapakohtaisesti, jokaisessa koemetsikössä."
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                "en": "# Data for the manuscript \"Cell tracking -based framework for assessing nowcasting model skill in reproducing growth and decay of convective rainfall\" by Ritvanen et al.\n\nThis repository contains the results presented in the manuscript\n\"Cell tracking -based framework for assessing nowcasting model skill in reproducing growth and decay of convective rainfall\"\nby Ritvanen, J., Pulkkinen, S., Moisseev, D., and Nerini, D.\nsubmitted to the Geoscientific Model Development journal.\n\nA description of the data files is provided below.\n\n## tracking_data.zip\n\nThis zip folder contains the cell tracking data from the study.\n\nNOTE: the unpacked size of the files is approximately 26GB.\n\nThe data is stored in a netCDF file `OBJECTS_ALL.nc` with the following coordinates:\n\n- `method`: the nowcasting model name\n- `leadtime`: index of the leadtime of the nowcast starting from 1 (e.g. 1=5min, 2=10min, 3=15min, ...)\n- `prev_time`: index of the input time step of the nowcast starting from -5 (-5=-25min, -4=-20min, -3=-15min, -2=-10min, -1=-5min, 0=nowcast creation time)\n- `sample`: the nowcast creation time\n- `cell`: cell index\n- `track`: cell track index\n\nThe following variables are stored:\n\n- `cell_match_obs_max_rr`: the maximum observed rain rates of the observed-nowcast cell pairs matched with Hungarian algorithm, mm/h\n- `cell_match_pred_max_rr`: the maximum nowcast rain rates of the observed-nowcast cell pairs matched with Hungarian algorithm, mm/h\n- `cell_match_obs_mean_rr` : the mean observed rain rates of the observed-nowcast cell pairs matched with Hungarian algorithm, mm/h\n- `cell_match_pred_mean_rr`: the mean nowcast rain rates of the observed-nowcast cell pairs matched with Hungarian algorithm, mm/h\n- `cell_match_obs_area`: the areas of the observed cell of the observed-nowcast cell pairs matched with Hungarian algorithm, km^2\n- `cell_match_pred_area`: the areas of the nowcast cell of the observed-nowcast cell pairs matched with Hungarian algorithm, km^2\n- `unmatched_obs_sum_rr`: the volume rain rates of observed cells that were unmatched with Hungarian algorithm, 1e9 m^3/h\n- `unmatched_pred_sum_rr`: the volume rain rates of nowcast cells that were unmatched with Hungarian algorithm, 1e9 m^3/h\n- `unmatched_obs_max_rr`: the maximum rain rates of observed cells that were unmatched with Hungarian algorithm, mm/h\n- `unmatched_pred_max_rr`: the maximum rain rates of nowcast cells that were unmatched with Hungarian algorithm, mm/h\n- `unmatched_obs_mean_rr`: the mean rain rates of observed cells that were unmatched with Hungarian algorithm, mm/h\n- `unmatched_pred_mean_rr`: the mean rain rates of nowcast cells that were unmatched with Hungarian algorithm, mm/h\n- `unmatched_obs_area`: the areas of observed cells that were unmatched with Hungarian algorithm, km^2\n- `unmatched_pred_area`: the areas of nowcast cells that were unmatched with Hungarian algorithm, km^2\n- `obs_lifetime`: number of time steps the cell track exists in target observations\n- `obs_area`: the area of cells in target observations, km^2\n- `obs_max_rr`: the maximum rain rate of cells in target observations, mm/h\n- `obs_mean_rr`: the mean rain rate of cells in target observations, mm/h\n- `obs_sum_rr`: the volume rain rate of cells in target observations, 1e9 m^3/h\n- `prev_area`: the area of cells in the input observations, km^2\n- `prev_max_rr`: the maximum rain rate of cells in the input observations, mm/h\n- `prev_mean_rr`: the mean rain rate of cells in the input observations, mm/h\n- `prev_sum_rr`: the volume rain rate of cells in the input observations, 1e9 m^3/h\n- `pred_lifetime`: number of time steps the cell track exists in nowcast\n- `pred_area`: the area of cells in the nowcast, km^2\n- `pred_max_rr`: the maximum rain rate of cells in the nowcast, mm/h\n- `pred_mean_rr`: the mean rain rate of cells in the nowcast, mm/h\n- `pred_sum_rr`: the volume rain rate of cells in the nowcast, 1e9 m^3/h\n- `pred_dist`: the distance between the observed and nowcast cell centroids, km\n- `prev_merged`: whether the cell in input observations is a product of merging, bool\n- `prev_from_split`: whether the cell in input observations is a product of splitting, bool\n- `prev_will_merge`: whether the cell in input observations will merge in the next time step, bool\n- `obs_merged`: whether the cell in target observations is a product of merging, bool\n- `obs_from_split`: whether the cell in target observations is a product of splitting, bool\n- `obs_will_merge`: whether the cell in target observations will merge in the next time step, bool\n- `pred_merged`: whether the cell in nowcast is a product of merging, bool\n- `pred_from_split`: whether the cell in nowcast is a product of splitting, bool\n- `pred_will_merge`: whether the cell in nowcast will merge in the next time step, bool\n\nAdditionally, configuration file used to generate the tracking data is provided in the `objects-2021-2023-20240308-less-splits_config.yaml` file, and a csv file `done_objects-2021-2023-20240308-less-splits.csv` listing the processed timesteps is provided.\n\n## results.zip\n\nThis zip folder contains the numerical versions of the result figures.\n\nThe following files are provided:\n\n- `histograms_article_lifetime_full.csv`: numerical histograms of cell track lifetimes (Figure 4)\n- `histograms_article_max_area.csv`: numerical histograms of cell track maximum areas (Figure 4)\n- `histograms_article_prev_area.csv`: numerical histograms of cell area at t_0 (Figure 4)\n- `histograms_article_prev_sum_rr.csv`: numerical histograms of cell volume rain rates at t_0 (Figure 4)\n- `pixel_CSI_POD_FAR_ETS_results.csv`: numerical values of the pixel-based CSI (Figure 5)\n- `pixel_RMSE_MSE_ME_MAE_results.csv`: numerical values of the pixel-based RMSE (Figure 5)\n- `error_sum_rr_RMSE.csv`: numerical values of volume rain rate RMSE (Figure 6)\n- `cell_existence_counts.csv`: number of cells (Figure 7)\n- `cell_existence_growth_decay.csv`: cell track existence metrics (Figure 8)\n- `growth_decay_track_classification_ab_counts.csv`: number of hits, misses, and false alarms in the cell track classification (Figure 9a-b)\n- `growth_decay_track_classification_c_scores.csv`: cell track classification metrics (Figure 9c)\n- `sum_rr_diff_article.csv`: volume rain rate differences between observed and nowcast cells (Figure 10)\n- `area_diff_article.csv`: area differences between observed and nowcast cells (Figure 11)\n- `mean_rr_diff_article.csv`: mean rain rate differences between observed and nowcast cells (Figure 12)\n- `cell_match_metrics_a_counts.csv`: number of cells in the cell occurrence analysis (Figure 13a)\n- `cell_match_metrics_bcde_metrics.csv`: cell occurrence analysis metrics (Figure 13b-e)\n- `split_merge_counts.csv`: the number of splits and merges in the cell tracks (Figure 14)\n\n## results_supplementary.zip\n\nThis zip folder contains the numerical versions of the supplementary result figures.\n\nThe following files are provided:\n\n- `histograms_article_lifetime_full.csv`: numerical histograms of cell track lifetimes (Figure S1)\n- `histograms_article_max_area.csv`: numerical histograms of cell track maximum areas (Figure S1)\n- `histograms_article_prev_area.csv`: numerical histograms of cell area at t_0 (Figure S1)\n- `histograms_article_prev_sum_rr.csv`: numerical histograms of cell volume rain rates at t_0 (Figure S1)\n- - `error_sum_rr_RMSE.csv`: numerical values of volume rain rate RMSE (Figure S2)\n- `cell_existence_counts.csv`: number of cells (Figure S3)\n- `cell_existence_growth_decay.csv`: cell track existence metrics (Figure S4)\n- `growth_decay_track_classification_ab_counts.csv`: number of hits, misses, and false alarms in the cell track classification (Figure S5a-b)\n- `growth_decay_track_classification_c_scores.csv`: cell track classification metrics (Figure S4c)\n- `sum_rr_diff_article.csv`: volume rain rate differences between observed and nowcast cells (Figure S6)\n- `area_diff_article.csv`: area differences between observed and nowcast cells (Figure S7)\n- `mean_rr_diff_article.csv`: mean rain rate differences between observed and nowcast cells (Figure S8)"
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J. Roy. Meteor. Soc., 146, 1999-2049, doi:10.1002/qj.3803, 2020.\nVitart F.: Evolution of ECMWF sub-seasonal forecast skill scores, Q. J. R. Meteorol. Soc., 140, 1889–1899, doi: 10.1002/qj.2256, 2014."
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