Monthly maps of air temperature and air humidity of the southern slopes of Kilimanjaro, Tanzania
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| Main Authors: | , , , , , |
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| Format: | Dataset Open Access |
| Language: | en |
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PANGAEA
2022
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| _version_ | 1867168215268851712 |
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| author | Appelhans, Tim Mwangomo, Ephraim Otte, Insa Detsch, Florian Nauss, Thomas Hemp, Andreas |
| author_facet | Appelhans, Tim Mwangomo, Ephraim Otte, Insa Detsch, Florian Nauss, Thomas Hemp, Andreas |
| collection | Datos científicos de ciencias marinas y ambientales |
| contents | Monthly maps of air temperature and air humidity of the southern slopes of Kilimanjaro, Tanzania. The dataset is part of our study on eco‐meteorological characteristics of the southern slopes of Kilimanjaro, Tanzania ([https://doi.org/10.1002/joc.4552]). (1) ta200_kriging.zip The dataset contains interpolate monthly air temperature maps using universal kriging with elevation, aspect, slope, sky‐view factor and mean monthly normalized difference vegetation index (NDVI) as external drift variables. This corresponds to step 5 in chapter 3.1 of [https://doi.org/10.1002/joc.4552]. (2) rh200_kriging.zip The dataset contains interpolate monthly air humidity maps using universal kriging with elevation, aspect, slope, sky‐view factor and mean monthly normalized difference vegetation index (NDVI) as external drift variables. This corresponds to step 5 in chapter 3.1 of [https://doi.org/10.1002/joc.4552]. (3) ta200_kriging_multi-year_average.zip and rh200_kriging_multi-year_average.zip The dataset contains multi-year monthly averages from (1) and (2) and a map of the multi-year annual mean air temperature and humidity. This corresponds to step 6 in chapter 3.1 of [https://doi.org/10.1002/joc.4552]. For the datasets (1) and (2), we used 5-min measurements between 2011 and 2014 of 52 climate stations that distributed across the southern slopes of Mt. Kilimanjaro. We aggregated the 5-min measurements to hourly observations and filled existing gaps of up to 1 year through multivariate regression using the five nearest stations. We aggregated the gap-filled hourly data to daily averages if at least 22 h of valid records exist for that day at a specific station. Finally, we aggregated the daily averages to monthly averages if a single month has at least 20 valid daily records. |
| format | Dataset Open Access |
| id | pangaea_https___doi_org_10_1594_PANGAEA_942820 |
| institution | PANGAEA |
| language | en |
| publishDate | 2022 |
| publisher | PANGAEA |
| record_format | pangaea |
| spellingShingle | Monthly maps of air temperature and air humidity of the southern slopes of Kilimanjaro, Tanzania Appelhans, Tim Mwangomo, Ephraim Otte, Insa Detsch, Florian Nauss, Thomas Hemp, Andreas Binary Object; Binary Object (File Size); Binary Object (Media Type); humidity; KiLi; Kilimanjaro; Kilimanjaro Research Group; Temperature Monthly maps of air temperature and air humidity of the southern slopes of Kilimanjaro, Tanzania. The dataset is part of our study on eco‐meteorological characteristics of the southern slopes of Kilimanjaro, Tanzania ([https://doi.org/10.1002/joc.4552]). (1) ta200_kriging.zip The dataset contains interpolate monthly air temperature maps using universal kriging with elevation, aspect, slope, sky‐view factor and mean monthly normalized difference vegetation index (NDVI) as external drift variables. This corresponds to step 5 in chapter 3.1 of [https://doi.org/10.1002/joc.4552]. (2) rh200_kriging.zip The dataset contains interpolate monthly air humidity maps using universal kriging with elevation, aspect, slope, sky‐view factor and mean monthly normalized difference vegetation index (NDVI) as external drift variables. This corresponds to step 5 in chapter 3.1 of [https://doi.org/10.1002/joc.4552]. (3) ta200_kriging_multi-year_average.zip and rh200_kriging_multi-year_average.zip The dataset contains multi-year monthly averages from (1) and (2) and a map of the multi-year annual mean air temperature and humidity. This corresponds to step 6 in chapter 3.1 of [https://doi.org/10.1002/joc.4552]. For the datasets (1) and (2), we used 5-min measurements between 2011 and 2014 of 52 climate stations that distributed across the southern slopes of Mt. Kilimanjaro. We aggregated the 5-min measurements to hourly observations and filled existing gaps of up to 1 year through multivariate regression using the five nearest stations. We aggregated the gap-filled hourly data to daily averages if at least 22 h of valid records exist for that day at a specific station. Finally, we aggregated the daily averages to monthly averages if a single month has at least 20 valid daily records. |
| title | Monthly maps of air temperature and air humidity of the southern slopes of Kilimanjaro, Tanzania |
| topic | Binary Object; Binary Object (File Size); Binary Object (Media Type); humidity; KiLi; Kilimanjaro; Kilimanjaro Research Group; Temperature |
| url | https://doi.org/10.1594/PANGAEA.942820 |