Supplementary data for "More frequent warm and dry spells along persistent cold and wet spells in the Baltics"
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2025
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| _version_ | 1866901795947675648 |
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| author | Kalvāns, Andis Kalvane, Gunta |
| author_facet | Kalvāns, Andis Kalvane, Gunta |
| contents | <p>Data accompanying publication “Climate warming brings rise of warm and dry spells while cold and wet spells persist in the Baltics” (DOI: 10.1007/s00704-026-06099-w):</p> <p>1. [1_cell_id.csv] Cell identification and respective coordinates WGS84 reference system:</p> <p>2. [2_daily.csv] Mean daily temperature, precipitation, reference evapotranspiration and water balance calculated from original hourly ERA5-land reanalysis (data in Fig. 2):</p> <p>3. [3_DoY_stat.csv] Long term (1961-2020) 31-day moving window day-of-the-year (DoY) average and Q10 and Q90 temperature, precipitation, reference evapotranspiration and water balance:</p> <p>4. [4_all_spells.csv] Warm/cold and dry/wet spells stratified by grid cell</p> <p>5. [5_spell_stat.csv] Summary statistics for warm/cold and dry/wet spells stratified by grid cell and climate normal period:</p> <p>6. [6_spell_trend.csv] Linear trend for warm/cold and dry/wet spells during 1961 to 2020.</p> <p><br>Explanation of abbreviations and variable names:</p> <p>1. <em>Cell_ID </em>– cell identifier</p> <p>2. <em>X, Y</em> – X and T coordinates in WGS 4 reference system</p> <p>4. <em>Par </em>– meteorological parameters</p> <p> <em>T</em> – mean daily 2m air temperature</p> <p> <em>P</em> – daily precipitation</p> <p> <em>ET0 </em>– reference evapotranspiration</p> <p> <em>CWB</em> – daily climatological water balance</p> <p>4. <em>Stat</em> – statistical parameter</p> <p> <em>Q10</em> – 10th quantile</p> <p> <em>Q90</em> – 90th quantile</p> <p> <em>Mean</em> – average </p> <p> <em><1 mm</em> – precipitation less than 1 mm</p> <p>5. <em>Season – </em>season of the year</p> <p> <em>DJF </em>– December, January, February</p> <p> <em>MAM</em> – March, April, May</p> <p> <em>JJA</em> – June, July, August</p> <p> <em>SON</em> – September, October, November </p> <p>6. <em>Npar </em>– minim spell duration criteria</p> <p> <em>N</em> – at least 1 day</p> <p> <em>N2</em> – at least 2 days</p> <p> <em>Nmax</em> – longest spell in a season</p> <p>7. <em>Period</em> – climate normal period</p> <p> <em>Reference</em> – 1961-1990</p> <p> <em>Normal-3</em> – 1991-2020</p> <p>8. <em>MeanDays </em>– mean duration of episode of unusual weather (spell)</p> <p>9. <em>MeanNumber</em> – mean number of episodes of unusual weather (spell) in a season</p> <p>10. <em>MeanLength</em> – mean length of episode of unusual weather (spell)</p> <p>11. <em>MaxDays</em> – duration of longest episode of unusual weather (spell)</p> <p> </p> <p>Data derived from ERA5-Land data set provided by the Copernicus Climate Change Service (C3S) Climate Data Store (https://cds.climate.copernicus.eu) accessed on 2024-04-26. ERA5-land data are described in Muñoz-Sabater et al. (2021).</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_17143292 |
| institution | Zenodo |
| language | |
| publishDate | 2025 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Supplementary data for "More frequent warm and dry spells along persistent cold and wet spells in the Baltics" Kalvāns, Andis Kalvane, Gunta <p>Data accompanying publication “Climate warming brings rise of warm and dry spells while cold and wet spells persist in the Baltics” (DOI: 10.1007/s00704-026-06099-w):</p> <p>1. [1_cell_id.csv] Cell identification and respective coordinates WGS84 reference system:</p> <p>2. [2_daily.csv] Mean daily temperature, precipitation, reference evapotranspiration and water balance calculated from original hourly ERA5-land reanalysis (data in Fig. 2):</p> <p>3. [3_DoY_stat.csv] Long term (1961-2020) 31-day moving window day-of-the-year (DoY) average and Q10 and Q90 temperature, precipitation, reference evapotranspiration and water balance:</p> <p>4. [4_all_spells.csv] Warm/cold and dry/wet spells stratified by grid cell</p> <p>5. [5_spell_stat.csv] Summary statistics for warm/cold and dry/wet spells stratified by grid cell and climate normal period:</p> <p>6. [6_spell_trend.csv] Linear trend for warm/cold and dry/wet spells during 1961 to 2020.</p> <p><br>Explanation of abbreviations and variable names:</p> <p>1. <em>Cell_ID </em>– cell identifier</p> <p>2. <em>X, Y</em> – X and T coordinates in WGS 4 reference system</p> <p>4. <em>Par </em>– meteorological parameters</p> <p> <em>T</em> – mean daily 2m air temperature</p> <p> <em>P</em> – daily precipitation</p> <p> <em>ET0 </em>– reference evapotranspiration</p> <p> <em>CWB</em> – daily climatological water balance</p> <p>4. <em>Stat</em> – statistical parameter</p> <p> <em>Q10</em> – 10th quantile</p> <p> <em>Q90</em> – 90th quantile</p> <p> <em>Mean</em> – average </p> <p> <em><1 mm</em> – precipitation less than 1 mm</p> <p>5. <em>Season – </em>season of the year</p> <p> <em>DJF </em>– December, January, February</p> <p> <em>MAM</em> – March, April, May</p> <p> <em>JJA</em> – June, July, August</p> <p> <em>SON</em> – September, October, November </p> <p>6. <em>Npar </em>– minim spell duration criteria</p> <p> <em>N</em> – at least 1 day</p> <p> <em>N2</em> – at least 2 days</p> <p> <em>Nmax</em> – longest spell in a season</p> <p>7. <em>Period</em> – climate normal period</p> <p> <em>Reference</em> – 1961-1990</p> <p> <em>Normal-3</em> – 1991-2020</p> <p>8. <em>MeanDays </em>– mean duration of episode of unusual weather (spell)</p> <p>9. <em>MeanNumber</em> – mean number of episodes of unusual weather (spell) in a season</p> <p>10. <em>MeanLength</em> – mean length of episode of unusual weather (spell)</p> <p>11. <em>MaxDays</em> – duration of longest episode of unusual weather (spell)</p> <p> </p> <p>Data derived from ERA5-Land data set provided by the Copernicus Climate Change Service (C3S) Climate Data Store (https://cds.climate.copernicus.eu) accessed on 2024-04-26. ERA5-land data are described in Muñoz-Sabater et al. (2021).</p> |
| title | Supplementary data for "More frequent warm and dry spells along persistent cold and wet spells in the Baltics" |
| url | https://doi.org/10.5281/zenodo.17143292 |