Environmental Data: Pfynwald VPDrought experiment atmospheric paramete...
Description
This dataset contains the main atmospheric measurements and treatment information from the VPDrought experiment conducted at the Pfynwald research platform...
Citation
Hunziker, S., Gisler, J., Trotsiuk, V., Schaub, M. (2026). Pfynwald VPDrought experiment atmospheric parameters and manipulations. EnviDat. https://www.doi.org/10.16904/envidat.798.
Resources
pfynwald_vpdrought_meteorology_oc_2025.zip
# Pfynwald VPDrought experiment atmospheric parameters over canopy **Content** The dataset contains 1-minute meteorological measurements from a meteorological station located above the canopy at the VPDrought experimental site at the Pfynwald research platform: - Precipitation - Air temperature - Relative humidity - Vapor pressure deficit (VPD) - Global radiation - Photosynthetically active radiation (PAR) - Wind speed - Wind direction **General gap-filling approach** Short gaps were filled by linear interpolation, whereas longer gaps were filled either by fitting external data or by averaging valid observations from preceding and following time steps at the same time of day. Directly measured values are labelled as observed in the *valtype* column, values to which a correction has been applied are labelled as corrected, and values used to fill gaps are labelled as estimated. The *quality_flag* provides information on the quality and origin of each value, while the *comment* column provides more specific information for values that have been corrected or estimated. **Precipitation** **Processing** - Missing values were linearly interpolated when ≤2 consecutive values were missing and the preceding and following measurement values had passed all quality checks. - 10-minute data blocks with remaining missing values were filled using MeteoSwiss precipitation data from the nearby station Sierre. The MeteoSwiss 10-minute precipitation totals were divided equally among the corresponding ten estimated 1-minute values. **Quality flags** The *quality_flag* describes the origin and quality of each precipitation value: - 1 = measured value with no identified quality issue - 2 = value estimated by linear interpolation across a gap of ≤2 minutes - 3 = value estimated using MeteoSwiss Sierre 10-minute precipitation data **Comments** The *comment* column provides additional information on estimated precipitation values: - *linear_interpolation* = missing value estimated by linear interpolation between surrounding valid measurements - *meteoswiss_sierre_10min* = missing value estimated from the corresponding MeteoSwiss Sierre 10-minute precipitation total, distributed equally across the ten 1-minute records **Air temperature and Relative humidity** **Processing** - Missing values were linearly interpolated when ≤2 consecutive values were missing and the previous and following measurement values had passed all quality checks. - Remaining missing values were estimated using aggregated ambient measurements of the corresponding variable measured in the canopy. The difference between valid above canopy and in canopy measurements was used as an additive correction to estimate above canopy values from the in canopy measurements. - For gaps of ≤3 hours, the additive correction was linearly interpolated between the correction values immediately before and after the gap. The interpolated correction was then added to the in canopy ambient measurement. - For gaps of >3 hours, the gap was divided into three sections: a first hour, a middle section, and a last hour. For the first hour, the additive correction at the last valid above canopy measurement before the gap was linearly interpolated to the correction estimated for the first timestamp of the middle section. For the last hour, the correction was linearly interpolated from the correction estimated for the last timestamp of the middle section to the correction at the first valid above canopy measurement after the gap. For the middle section, the additive correction at each timestamp was estimated as the mean of the nearest valid above canopy and in canopy differences at the same hour and minute before and after the target timestamp. The resulting correction was then added to the corresponding in canopy ambient measurement to estimate the missing above canopy value. **Quality flags** The *quality_flag* describes the origin and quality of each value: - 1 = measured value with no identified quality issue - 2 = value estimated by linear interpolation across a gap of ≤2 minutes - 3 = value estimated using fitted in canopy ambient measurements **Comments** The *comment* column provides additional information on estimated values: - *linear_interpolation* = missing value estimated by linear interpolation between surrounding valid measurements - *fitted_in_canopy_ambient* = missing value estimated from aggregated in canopy ambient measurements using an additive correction to account for the difference between in canopy and above canopy measurements **VPD** **Processing** - Missing values were linearly interpolated when ≤2 consecutive values were missing and the previous and following measurement values had passed all quality checks. - Remaining missing values were estimated using aggregated ambient VPD measured in the canopy. The relationship between valid above canopy and in canopy VPD was used as a correction to adjust the in canopy measurements to above canopy conditions. - For gaps of ≤3 hours, the correction was linearly interpolated between the correction values immediately before and after the gap. A multiplicative correction factor was used when both boundary corrections were expressed as factors (VPD ≥ 0.5 kPa). If either boundary correction was an additive offset (VPD < 0.5 kPa), both corrections were expressed as additive offsets and interpolated linearly. The interpolated correction was then applied to the in canopy VPD to estimate above canopy VPD. - For gaps of >3 hours, the gap was divided into three sections: a first hour, a middle section, and a last hour. For the first hour, the correction at the last valid above canopy measurement before the gap was linearly interpolated to the correction estimated for the first timestamp of the middle section. For the last hour, the correction was linearly interpolated from the correction estimated for the last timestamp of the middle section to the correction at the first valid above canopy measurement after the gap. For the middle section, the correction at each timestamp was estimated as the mean of the nearest valid above canopy and in canopy VPD relationships at the same hour and minute before and after the target timestamp. A multiplicative correction was used when both reference corrections were factors (i.e. all reference VPD values were ≥ 0.5 kPa). When either reference correction was an additive offset, both corrections were converted to additive offsets and applied additively. Thus, the correction method could switch between multiplicative and additive depending on the VPD level and the available reference observations. The resulting correction was then applied to the corresponding in canopy VPD to estimate the missing above canopy VPD. **Quality flags** The *quality_flag* describes the origin and quality of each VPD value: - 1 = measured value with no identified quality issue - 2 = value estimated by linear interpolation across a gap of ≤2 minutes - 3 = value estimated using in canopy ambient VPD and a fitted correction **Comments** The *comment* column provides additional information on estimated VPD values: - *linear_interpolation* = missing value estimated by linear interpolation between surrounding valid measurements - *fitted_in_canopy_ambient* = missing value estimated from aggregated in canopy ambient VPD using a fitted correction to account for the difference between in canopy and above canopy VPD **Global radiation and PAR** **Processing** - For global radiation, measured values below 4 were set to 0 to account for sensor noise around 0 under low-light conditions. These values were identified as corrected and assigned the comment *nighttime_noise_removed*. - Missing values were linearly interpolated when ≤10 consecutive values were missing and the previous and following measurement values had passed all quality checks. - For gaps of >10 consecutive values, missing values were estimated from observations at the same time of day on other days. The nearest valid observation before and after each missing timestamp was identified by stepping backward and forward in 24-hour increments. Only observations with *quality_flag* <3 were used as references. The estimated value was calculated as the mean of these two observations. **Quality flags** The *quality_flag* describes the origin and quality of each value: - 1 = measured value with no identified quality issue - 2 = value estimated by linear interpolation across a gap of ≤10 consecutive values - 3 = value estimated using valid observations at the same time of day on preceding and following days **Comments** The *comment* column provides additional information on corrected or estimated values: - *nighttime_noise_removed* = measured value below 4 set to 0 to account for low-light sensor noise (only for global radiation) - *linear_interpolation* = missing value estimated by linear interpolation between surrounding valid measurements - *mean_of_previous_and_following_valid_messval_same_time_of_day* = missing value estimated as the mean of valid observations at the same time of day before and after the gap **Wind speed** **Processing** - Missing values were linearly interpolated when ≤2 consecutive values were missing and the previous and following measurement values had passed all quality checks. - Remaining missing values were estimated using aggregated ambient in canopy wind speed. The relationship between valid above canopy and in canopy wind speed was used as a correction to adjust the in canopy measurements to above canopy conditions. - For gaps of ≤3 hours, the correction was linearly interpolated between the correction values immediately before and after the gap. A multiplicative correction factor was used when both boundary corrections were expressed as factors (wind speed in canopy ≥0.4 m s⁻¹). If either boundary correction was an additive offset (wind speed in canopy <0.4 m s⁻¹), both corrections were expressed as additive offsets and interpolated linearly. The interpolated correction was then applied to the in canopy wind speed to estimate above canopy wind speed. - For gaps of >3 hours, the gap was divided into three sections: a first hour, a middle section, and a last hour. For the first hour, the correction at the last valid above canopy measurement before the gap was linearly interpolated to the correction estimated for the first timestamp of the middle section. For the last hour, the correction was linearly interpolated from the correction estimated for the last timestamp of the middle section to the correction at the first valid above canopy measurement after the gap. For the middle section, the correction at each timestamp was estimated as the mean of the nearest valid above canopy and in canopy wind speed relationships at the same hour and minute before and after the target timestamp. A multiplicative correction was used when both reference corrections were factors (i.e. all reference in canopy wind speeds were ≥0.4 m s⁻¹). When either reference correction was an additive offset, both corrections were converted to additive offsets and applied additively. Thus, the correction method could switch between multiplicative and additive depending on the wind speed level and the available reference observations. The resulting correction was then applied to the corresponding in canopy wind speed to estimate the missing above canopy wind speed. - Negative estimated wind speed values resulting from the correction procedure were set to 0. **Quality flags** The *quality_flag* describes the origin and quality of each value: - 1 = measured value with no identified quality issue - 2 = value estimated by linear interpolation across a gap of ≤2 minutes - 3 = value estimated using in canopy ambient wind speed and a fitted correction **Comments** The *comment* column provides additional information on estimated values: - *linear_interpolation* = missing value estimated by linear interpolation between surrounding valid measurements - *fitted_in_canopy_ambient* = missing value estimated from aggregated ambient in canopy wind speed using a fitted correction to account for the difference between in canopy and above canopy wind speed **Wind direction** **Processing** - Missing wind direction values were linearly interpolated on a circular scale when ≤2 consecutive values were missing and the previous and following measurement values had passed all quality checks. - Remaining missing values were estimated using aggregated ambient in canopy wind direction. The relationship between valid above canopy and in canopy wind direction was used as an additive circular correction to adjust the in canopy measurements to above canopy conditions. - For gaps of ≤3 hours, the circular correction was linearly interpolated between the correction values immediately before and after the gap. The shortest angular difference between the two corrections was used, and the interpolated correction was applied to the in canopy wind direction. - For gaps of >3 hours, the gap was divided into three sections: a first hour, a middle section, and a last hour. For the first hour, the correction at the last valid above canopy measurement before the gap was circularly interpolated to the correction estimated for the first timestamp of the middle section. For the last hour, the correction was circularly interpolated from the correction estimated for the last timestamp of the middle section to the correction at the first valid above canopy measurement after the gap. For the middle section, the correction at each timestamp was estimated as the circular mean of the nearest valid above canopy and in canopy wind direction relationships at the same hour and minute before and after the target timestamp. The shortest angular difference was used when interpolating between corrections, and all corrections were applied additively to the corresponding in canopy wind direction. The resulting circular correction was then applied to the corresponding in canopy wind direction to estimate the missing above canopy wind direction. - If the result of a circular mean was undefined because the values were diametrically opposed (e.g., 90° and 270°), the first value was adjusted internally by +1° (circularly) and the circular mean was recalculated. - The final estimated values were circularly rounded to integer degrees from 0 to 359. **Quality flags** The *quality_flag* describes the origin and quality of each wind direction value: - 1 = measured value with no identified quality issue - 2 = value estimated by circular linear interpolation across a gap of ≤2 consecutive values - 3 = value estimated using in canopy ambient wind direction and a fitted circular correction **Comments** The *comment* column provides additional information on estimated wind direction values: - *linear_interpolation* = missing value estimated by circular linear interpolation between surrounding valid measurements - *fitted_in_canopy_ambient* = missing value estimated from aggregated ambient in canopy wind direction using a fitted circular correction to account for the difference between in canopy and above canopy wind direction
pfynwald_vpdrought_meteorology_oc_2025.zippfynwald_vpdrought_meteorology_oc_2024.zip
# Pfynwald VPDrought experiment atmospheric parameters over canopy **Content** The dataset contains 1-minute meteorological measurements from a meteorological station located above the canopy at the VPDrought experimental site at the Pfynwald research platform: - Precipitation - Air temperature - Relative humidity - Vapor pressure deficit (VPD) - Global radiation - Photosynthetically active radiation (PAR) - Wind speed - Wind direction **General gap-filling approach** Short gaps were filled by linear interpolation, whereas longer gaps were filled either by fitting external data or by averaging valid observations from preceding and following time steps at the same time of day. Directly measured values are labelled as observed in the *valtype* column, values to which a correction has been applied are labelled as corrected, and values used to fill gaps are labelled as estimated. The *quality_flag* provides information on the quality and origin of each value, while the *comment* column provides more specific information for values that have been corrected or estimated. **Precipitation** **Processing** - Missing values were linearly interpolated when ≤2 consecutive values were missing and the preceding and following measurement values had passed all quality checks. - 10-minute data blocks with remaining missing values were filled using MeteoSwiss precipitation data from the nearby station Sierre. The MeteoSwiss 10-minute precipitation totals were divided equally among the corresponding ten estimated 1-minute values. **Quality flags** The *quality_flag* describes the origin and quality of each precipitation value: - 1 = measured value with no identified quality issue - 2 = value estimated by linear interpolation across a gap of ≤2 minutes - 3 = value estimated using MeteoSwiss Sierre 10-minute precipitation data **Comments** The *comment* column provides additional information on estimated precipitation values: - *linear_interpolation* = missing value estimated by linear interpolation between surrounding valid measurements - *meteoswiss_sierre_10min* = missing value estimated from the corresponding MeteoSwiss Sierre 10-minute precipitation total, distributed equally across the ten 1-minute records **Air temperature and Relative humidity** **Processing** - Missing values were linearly interpolated when ≤2 consecutive values were missing and the previous and following measurement values had passed all quality checks. - Remaining missing values were estimated using aggregated ambient measurements of the corresponding variable measured in the canopy. The difference between valid above canopy and in canopy measurements was used as an additive correction to estimate above canopy values from the in canopy measurements. - For gaps of ≤3 hours, the additive correction was linearly interpolated between the correction values immediately before and after the gap. The interpolated correction was then added to the in canopy ambient measurement. - For gaps of >3 hours, the gap was divided into three sections: a first hour, a middle section, and a last hour. For the first hour, the additive correction at the last valid above canopy measurement before the gap was linearly interpolated to the correction estimated for the first timestamp of the middle section. For the last hour, the correction was linearly interpolated from the correction estimated for the last timestamp of the middle section to the correction at the first valid above canopy measurement after the gap. For the middle section, the additive correction at each timestamp was estimated as the mean of the nearest valid above canopy and in canopy differences at the same hour and minute before and after the target timestamp. The resulting correction was then added to the corresponding in canopy ambient measurement to estimate the missing above canopy value. **Quality flags** The *quality_flag* describes the origin and quality of each value: - 1 = measured value with no identified quality issue - 2 = value estimated by linear interpolation across a gap of ≤2 minutes - 3 = value estimated using fitted in canopy ambient measurements **Comments** The *comment* column provides additional information on estimated values: - *linear_interpolation* = missing value estimated by linear interpolation between surrounding valid measurements - *fitted_in_canopy_ambient* = missing value estimated from aggregated in canopy ambient measurements using an additive correction to account for the difference between in canopy and above canopy measurements **VPD** **Processing** - Missing values were linearly interpolated when ≤2 consecutive values were missing and the previous and following measurement values had passed all quality checks. - Remaining missing values were estimated using aggregated ambient VPD measured in the canopy. The relationship between valid above canopy and in canopy VPD was used as a correction to adjust the in canopy measurements to above canopy conditions. - For gaps of ≤3 hours, the correction was linearly interpolated between the correction values immediately before and after the gap. A multiplicative correction factor was used when both boundary corrections were expressed as factors (VPD ≥ 0.5 kPa). If either boundary correction was an additive offset (VPD < 0.5 kPa), both corrections were expressed as additive offsets and interpolated linearly. The interpolated correction was then applied to the in canopy VPD to estimate above canopy VPD. - For gaps of >3 hours, the gap was divided into three sections: a first hour, a middle section, and a last hour. For the first hour, the correction at the last valid above canopy measurement before the gap was linearly interpolated to the correction estimated for the first timestamp of the middle section. For the last hour, the correction was linearly interpolated from the correction estimated for the last timestamp of the middle section to the correction at the first valid above canopy measurement after the gap. For the middle section, the correction at each timestamp was estimated as the mean of the nearest valid above canopy and in canopy VPD relationships at the same hour and minute before and after the target timestamp. A multiplicative correction was used when both reference corrections were factors (i.e. all reference VPD values were ≥ 0.5 kPa). When either reference correction was an additive offset, both corrections were converted to additive offsets and applied additively. Thus, the correction method could switch between multiplicative and additive depending on the VPD level and the available reference observations. The resulting correction was then applied to the corresponding in canopy VPD to estimate the missing above canopy VPD. **Quality flags** The *quality_flag* describes the origin and quality of each VPD value: - 1 = measured value with no identified quality issue - 2 = value estimated by linear interpolation across a gap of ≤2 minutes - 3 = value estimated using in canopy ambient VPD and a fitted correction **Comments** The *comment* column provides additional information on estimated VPD values: - *linear_interpolation* = missing value estimated by linear interpolation between surrounding valid measurements - *fitted_in_canopy_ambient* = missing value estimated from aggregated in canopy ambient VPD using a fitted correction to account for the difference between in canopy and above canopy VPD **Global radiation and PAR** **Processing** - For global radiation, measured values below 4 were set to 0 to account for sensor noise around 0 under low-light conditions. These values were identified as corrected and assigned the comment *nighttime_noise_removed*. - Missing values were linearly interpolated when ≤10 consecutive values were missing and the previous and following measurement values had passed all quality checks. - For gaps of >10 consecutive values, missing values were estimated from observations at the same time of day on other days. The nearest valid observation before and after each missing timestamp was identified by stepping backward and forward in 24-hour increments. Only observations with *quality_flag* <3 were used as references. The estimated value was calculated as the mean of these two observations. **Quality flags** The *quality_flag* describes the origin and quality of each value: - 1 = measured value with no identified quality issue - 2 = value estimated by linear interpolation across a gap of ≤10 consecutive values - 3 = value estimated using valid observations at the same time of day on preceding and following days **Comments** The *comment* column provides additional information on corrected or estimated values: - *nighttime_noise_removed* = measured value below 4 set to 0 to account for low-light sensor noise (only for global radiation) - *linear_interpolation* = missing value estimated by linear interpolation between surrounding valid measurements - *mean_of_previous_and_following_valid_messval_same_time_of_day* = missing value estimated as the mean of valid observations at the same time of day before and after the gap **Wind speed** **Processing** - Missing values were linearly interpolated when ≤2 consecutive values were missing and the previous and following measurement values had passed all quality checks. - Remaining missing values were estimated using aggregated ambient in canopy wind speed. The relationship between valid above canopy and in canopy wind speed was used as a correction to adjust the in canopy measurements to above canopy conditions. - For gaps of ≤3 hours, the correction was linearly interpolated between the correction values immediately before and after the gap. A multiplicative correction factor was used when both boundary corrections were expressed as factors (wind speed in canopy ≥0.4 m s⁻¹). If either boundary correction was an additive offset (wind speed in canopy <0.4 m s⁻¹), both corrections were expressed as additive offsets and interpolated linearly. The interpolated correction was then applied to the in canopy wind speed to estimate above canopy wind speed. - For gaps of >3 hours, the gap was divided into three sections: a first hour, a middle section, and a last hour. For the first hour, the correction at the last valid above canopy measurement before the gap was linearly interpolated to the correction estimated for the first timestamp of the middle section. For the last hour, the correction was linearly interpolated from the correction estimated for the last timestamp of the middle section to the correction at the first valid above canopy measurement after the gap. For the middle section, the correction at each timestamp was estimated as the mean of the nearest valid above canopy and in canopy wind speed relationships at the same hour and minute before and after the target timestamp. A multiplicative correction was used when both reference corrections were factors (i.e. all reference in canopy wind speeds were ≥0.4 m s⁻¹). When either reference correction was an additive offset, both corrections were converted to additive offsets and applied additively. Thus, the correction method could switch between multiplicative and additive depending on the wind speed level and the available reference observations. The resulting correction was then applied to the corresponding in canopy wind speed to estimate the missing above canopy wind speed. - Negative estimated wind speed values resulting from the correction procedure were set to 0. **Quality flags** The *quality_flag* describes the origin and quality of each value: - 1 = measured value with no identified quality issue - 2 = value estimated by linear interpolation across a gap of ≤2 minutes - 3 = value estimated using in canopy ambient wind speed and a fitted correction **Comments** The *comment* column provides additional information on estimated values: - *linear_interpolation* = missing value estimated by linear interpolation between surrounding valid measurements - *fitted_in_canopy_ambient* = missing value estimated from aggregated ambient in canopy wind speed using a fitted correction to account for the difference between in canopy and above canopy wind speed **Wind direction** **Processing** - Missing wind direction values were linearly interpolated on a circular scale when ≤2 consecutive values were missing and the previous and following measurement values had passed all quality checks. - Remaining missing values were estimated using aggregated ambient in canopy wind direction. The relationship between valid above canopy and in canopy wind direction was used as an additive circular correction to adjust the in canopy measurements to above canopy conditions. - For gaps of ≤3 hours, the circular correction was linearly interpolated between the correction values immediately before and after the gap. The shortest angular difference between the two corrections was used, and the interpolated correction was applied to the in canopy wind direction. - For gaps of >3 hours, the gap was divided into three sections: a first hour, a middle section, and a last hour. For the first hour, the correction at the last valid above canopy measurement before the gap was circularly interpolated to the correction estimated for the first timestamp of the middle section. For the last hour, the correction was circularly interpolated from the correction estimated for the last timestamp of the middle section to the correction at the first valid above canopy measurement after the gap. For the middle section, the correction at each timestamp was estimated as the circular mean of the nearest valid above canopy and in canopy wind direction relationships at the same hour and minute before and after the target timestamp. The shortest angular difference was used when interpolating between corrections, and all corrections were applied additively to the corresponding in canopy wind direction. The resulting circular correction was then applied to the corresponding in canopy wind direction to estimate the missing above canopy wind direction. - If the result of a circular mean was undefined because the values were diametrically opposed (e.g., 90° and 270°), the first value was adjusted internally by +1° (circularly) and the circular mean was recalculated. - The final estimated values were circularly rounded to integer degrees from 0 to 359. **Quality flags** The *quality_flag* describes the origin and quality of each wind direction value: - 1 = measured value with no identified quality issue - 2 = value estimated by circular linear interpolation across a gap of ≤2 consecutive values - 3 = value estimated using in canopy ambient wind direction and a fitted circular correction **Comments** The *comment* column provides additional information on estimated wind direction values: - *linear_interpolation* = missing value estimated by circular linear interpolation between surrounding valid measurements - *fitted_in_canopy_ambient* = missing value estimated from aggregated ambient in canopy wind direction using a fitted circular correction to account for the difference between in canopy and above canopy wind direction
pfynwald_vpdrought_meteorology_oc_2024.zippfynwald_vpdrought_meteorology_irrigation_2025.zip
# Pfynwald VPDrought experiment irrigation **Content** Daily irrigation sums (mm) from the VPDrought experiment, aggregated across the four irrigated sub-plots (2, 3, 6, and 7) at the Pfynwald research platform. Scaffolds 3, 4, 10, 14, 15, and 901 are located on these irrigated sub-plots. **Processing** - Irrigation measurements ≤ 1 mm were excluded, as these small values are considered non-relevant and result from maintenance activities. - Irrigation generally occurred during the night over a period of approximately 3.5 hours. For the few irrigation events outside this period, measurements were assigned to an irrigation day as follows: - measurements up to 19:00 UTC: same day - measurements after 19:00 UTC: following day - Daily irrigation amounts were calculated separately for each sub-plot by summing up all irrigation measurements assigned to the same day. - The median of the four sub-plot amounts was used as the final daily irrigation sum. - All daily irrigation sums were assigned to the timestamp 02:00 UTC. **Quality flags** The *quality\_flag* indicates the consistency of irrigation sums among the four sub-plots for each daily timestamp. Individual sub-plot values were compared with the daily median using a 10% deviation threshold: - 1 = no quality issue identified - 2 = one or two sub-plot values deviate by more than 10% from the daily median - 3 = more than two sub-plot values deviate by more than 10% from the daily median **Comments** The *comment* column identifies the sub-plots responsible for deviations. For example, *treatment\_deviation\_pl2\_pl7* indicates that the irrigation sums on sub-plots 2 and 7 deviated by more than 10% from the daily median. If no sub-plot deviation occurred, *comment* is empty.
pfynwald_vpdrought_meteorology_irrigation_2025.zippfynwald_vpdrought_meteorology_irrigation_2024.zip
# Pfynwald VPDrought experiment irrigation **Content** Daily irrigation sums (mm) from the VPDrought experiment, aggregated across the four irrigated sub-plots (2, 3, 6, and 7) at the Pfynwald research platform. Scaffolds 3, 4, 10, 14, 15, and 901 are located on these irrigated sub-plots. **Processing** - Irrigation measurements ≤ 1 mm were excluded, as these small values are considered non-relevant and result from maintenance activities. - Irrigation generally occurred during the night over a period of approximately 3.5 hours. For the few irrigation events outside this period, measurements were assigned to an irrigation day as follows: - measurements up to 19:00 UTC: same day - measurements after 19:00 UTC: following day - Daily irrigation amounts were calculated separately for each sub-plot by summing up all irrigation measurements assigned to the same day. - The median of the four sub-plot amounts was used as the final daily irrigation sum. - All daily irrigation sums were assigned to the timestamp 02:00 UTC. **Quality flags** The *quality\_flag* indicates the consistency of irrigation sums among the four sub-plots for each daily timestamp. Individual sub-plot values were compared with the daily median using a 10% deviation threshold: - 1 = no quality issue identified - 2 = one or two sub-plot values deviate by more than 10% from the daily median - 3 = more than two sub-plot values deviate by more than 10% from the daily median **Comments** The *comment* column identifies the sub-plots responsible for deviations. For example, *treatment\_deviation\_pl2\_pl7* indicates that the irrigation sums on sub-plots 2 and 7 deviated by more than 10% from the daily median. If no sub-plot deviation occurred, *comment* is empty.
pfynwald_vpdrought_meteorology_irrigation_2024.zippfynwald_vpdrought_meteorology_ic_2025.zip
# Pfynwald VPDrought experiment atmospheric parameters in canopy and VPD manipulation **Content** The dataset contains aggregated 1-minute meteorological measurements from the VPDrought experiment at the Pfynwald research platform. It includes in canopy measurements for ambient (*\_amb*) and VPD-reduced (*\_manip*) conditions. Parameters unaffected by the VPD manipulation were not distinguished between ambient and manipulated conditions: - Air temperature (*TA\_ic\_amb* and *TA\_ic\_manip*) - Relative humidity (*RH\_ic\_amb* and *RH\_ic\_manip*) - Vapor pressure deficit (*VPD\_ic\_amb* and *VPD\_ic\_manip*) - Wind speed (*WS\_ic*) - Wind direction (*WD\_ic*) - VPD manipulation operation status (*OPERATION\_STATUS*), indicating whether the VPD reduction system was operating: - 0 = system not operating - 1 = system operating **Processing** - Measurements were aggregated to one value per parameter and timestamp using the median across available sensors. - For wind direction, a circular median was used. If no clear wind direction could be determined from the valid values (e.g., the circular median of 90° and 270° results in NA), these missing values were filled by circular interpolation between the preceding and following aggregated values. - The operation status indicates whether the VPD manipulation system was operating. A timestamp was classified as operational when water pressure was >60 bar and at least one valve was open, with an open valve defined as valve state < −0.99. **Quality flags** The *quality\_flag* describes the completeness and consistency of the underlying measurements for each parameter and timestamp: - 1 = sufficient valid measurements; no quality issue identified - 2 = less than 50% of the expected measurements were available - 3 = only one valid measurement was available - For *OPERATION\_STATUS*, quality flag 2 is assigned when an individual valve state deviates from the median valve state by more than 0.4 during periods when water pressure was >60 bar. **Comments** The *comment* column provides additional information when a quality issue was identified. For meteorological variables, comments indicate limited data availability: - *less\_than\_50%\_valid\_measurement\_values* = fewer than half of the expected measurements were valid - *only\_1\_valid\_measurement\_value* = only one valid measurement was available For *OPERATION\_STATUS*, the *comment* identifies individual scaffolds whose valve state deviated from those of the other scaffolds during system operation. For example, *treatment\_deviation\_PFY\_SC03\_PFY\_SC10* indicates that VPD reduction on scaffold 3 and 10 deviated from the median VPD reduction across scaffolds. Consequently, trees around these scaffolds were exposed to VPD conditions that deviated from the intended treatment.
pfynwald_vpdrought_meteorology_ic_2025.zippfynwald_vpdrought_meteorology_ic_2024.zip
# Pfynwald VPDrought experiment atmospheric parameters in canopy and VPD manipulation **Content** The dataset contains aggregated 1-minute meteorological measurements from the VPDrought experiment at the Pfynwald research platform. It includes in canopy measurements for ambient (*\_amb*) and VPD-reduced (*\_manip*) conditions. Parameters unaffected by the VPD manipulation were not distinguished between ambient and manipulated conditions: - Air temperature (*TA\_ic\_amb* and *TA\_ic\_manip*) - Relative humidity (*RH\_ic\_amb* and *RH\_ic\_manip*) - Vapor pressure deficit (*VPD\_ic\_amb* and *VPD\_ic\_manip*) - Wind speed (*WS\_ic*) - Wind direction (*WD\_ic*) - VPD manipulation operation status (*OPERATION\_STATUS*), indicating whether the VPD reduction system was operating: - 0 = system not operating - 1 = system operating **Processing** - Measurements were aggregated to one value per parameter and timestamp using the median across available sensors. - For wind direction, a circular median was used. If no clear wind direction could be determined from the valid values (e.g., the circular median of 90° and 270° results in NA), these missing values were filled by circular interpolation between the preceding and following aggregated values. - The operation status indicates whether the VPD manipulation system was operating. A timestamp was classified as operational when water pressure was >60 bar and at least one valve was open, with an open valve defined as valve state < −0.99. **Quality flags** The *quality\_flag* describes the completeness and consistency of the underlying measurements for each parameter and timestamp: - 1 = sufficient valid measurements; no quality issue identified - 2 = less than 50% of the expected measurements were available - 3 = only one valid measurement was available - For *OPERATION\_STATUS*, quality flag 2 is assigned when an individual valve state deviates from the median valve state by more than 0.4 during periods when water pressure was >60 bar. **Comments** The *comment* column provides additional information when a quality issue was identified. For meteorological variables, comments indicate limited data availability: - *less\_than\_50%\_valid\_measurement\_values* = fewer than half of the expected measurements were valid - *only\_1\_valid\_measurement\_value* = only one valid measurement was available For *OPERATION\_STATUS*, the *comment* identifies individual scaffolds whose valve state deviated from those of the other scaffolds during system operation. For example, *treatment\_deviation\_PFY\_SC03\_PFY\_SC10* indicates that VPD reduction on scaffold 3 and 10 deviated from the median VPD reduction across scaffolds. Consequently, trees around these scaffolds were exposed to VPD conditions that deviated from the intended treatment.
pfynwald_vpdrought_meteorology_ic_2024.zip