Wang, Di; Tian, Lide (2022): Vehicle-based in-situ observations of the water vapor isotopic composition across China during the pre-monsoon season 2019 [dataset]. PANGAEA, https://doi.org/10.1594/PANGAEA.947627
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Published: 2022-08-30 • DOI registered: 2022-10-26
Abstract:
This dataset provide large scale (order 10000 km) vehicle-based in-situ observations of near-surface water vapor isotopic composition and concurrent meteorological data across China during the pre-monsoon season (3rd to 26th March, 2019).
We used a Picarro 2130i CRDS water vapor isotope analyzer fixed on a vehicle to obtain continuous measurements of near-surface vapor isotopes (δ18O and δ2H) and vapor concentration (humidity) along the route. All measured vapor isotope values were humidity calibrated and also calibrated to the VSMOW-SLAP scale. The position data (latitude, longitude, and altitude) along the route are recorded by a portable GPS unit. Air temperature (T), relative humidity (RH), dew-point temperature (Td), and air pressure (Pres) are measured by a portable weather station on the roof of the vehicle. All sensors were located near the ambient air intake. The specific humidity (q) of the near-surface air was calculated from the measured Td and Pres. Meteorological data, GPS location data and vapor isotope data were synchronized according to their measurement times. Average precipitation during the observation period (P- temporal mean) and daily precipitation (P-daily) from the Global Precipitation Climatology Project (GPCP) are also provided. The dataset present here had been averaged to a 10-min temporal resolution, with the horizontal footprint of about 15 km.
Based on the tracking results of the HYSPLIT4 model, we classify the observations into different potential sources of water vapor based on the geographical origin of the air masses and label them with different area numbers.
During the pre-monsoon period, we categorize our domain into 3 regions.
(1) WR_1: In northern China, the air is mainly advected by the Westerlies.
(2) WR_2: In central China, the air also comes from the Westerlies but with a slower wind speed (as shown by the shorter trajectories in 10 days), suggesting potential for greater interaction with the land surface and more continental recycling as moisture source.
(3) WR_3: In southern China, trajectories come from the Southwest and South with marine moisture sources from the Bay of Bengal (BoB).
Keyword(s):
Related to:
Wang, Di; Tian, Lide; Risi, Camille; Wang, Xuejie; Cui, Jiangpeng; Bowen, Gabriel J; Yoshimura, Kei; Wei, Zhongwang; Li, Laurent Z X (2023): Vehicle-based in situ observations of the water vapor isotopic composition across China: spatial and seasonal distributions and controls. Atmospheric Chemistry and Physics, 23(6), 3409-3433, https://doi.org/10.5194/acp-23-3409-2023
Coverage:
Median Latitude: 38.440911 * Median Longitude: 110.814775 * South-bound Latitude: 24.828400 * West-bound Longitude: 93.689000 * North-bound Latitude: 49.259300 * East-bound Longitude: 126.615100
Date/Time Start: 2019-03-03T15:20:00 * Date/Time End: 2019-03-26T17:10:00
Minimum ALTITUDE: 5.888900000 m * Maximum ALTITUDE: 2739.125000000 m
Event(s):
Water_vapor_China-2019 * Latitude Start: 24.839500 * Longitude Start: 102.835500 * Latitude End: 24.828400 * Longitude End: 102.851700 * Date/Time Start: 2019-03-03T15:20:00 * Date/Time End: 2019-03-26T17:10:00 * Elevation Start: 1946.9 m * Elevation End: 2001.3 m * Location: China * Method/Device: Near-surface in-situ water vapor isotopic composition
Parameter(s):
| # | Name | Short Name | Unit | Principal Investigator | Method/Device | Comment |
|---|---|---|---|---|---|---|
| 1 | Date/time start | Date/time start | Wang, Di | Local time | ||
| 2 | Date/time end | Date/time end | Wang, Di | Local time | ||
| 3 | Water vapour content | WVC | ppmv | Wang, Di | Cavity ring-down spectroscopy (CRDS), Picarro Inc., L2130-i | 10-minute mean |
| 4 | δ18O, water vapour | δ18O H2O vapour | ‰ SMOW | Wang, Di | ||
| 5 | δ Deuterium, water vapour | δD H2O vapour | ‰ SMOW | Wang, Di | ||
| 6 | Deuterium excess | d xs | ‰ | Wang, Di | ||
| 7 | LATITUDE | Latitude | Wang, Di | Geocode | ||
| 8 | LONGITUDE | Longitude | Wang, Di | Geocode | ||
| 9 | ALTITUDE | Altitude | m | Wang, Di | Geocode | |
| 10 | Temperature, air | TTT | °C | Wang, Di | ||
| 11 | Humidity, relative | RH | % | Wang, Di | ||
| 12 | Dew/frost point | TdTdTd | K | Wang, Di | ||
| 13 | Pressure, atmospheric | PPPP | hPa | Wang, Di | ||
| 14 | Humidity, specific | Humidity spec | g/kg | Wang, Di | ||
| 15 | Precipitation, mean | Precip mean | mm | Wang, Di | during observation period | |
| 16 | Precipitation | Precip | mm/day | Wang, Di | ||
| 17 | Area/locality | Area | Wang, Di |
License:
Creative Commons Attribution 4.0 International (CC-BY-4.0)
Status:
Curation Level: Enhanced curation (CurationLevelC) * Processing Level: PANGAEA data processing level 3 (ProcLevel3)
Size:
16389 data points
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