气候变化领域集成服务门户(CCPortal): Tracking the global flows of atmospheric moisture and associated uncertainties

CCPortal

DOI	10.5194/hess-24-2419-2020
	Tracking the global flows of atmospheric moisture and associated uncertainties
	Tuinenburg O.A.; Staal A.
发表日期	2020
ISSN	1027-5606
起始页码	2419
结束页码	2435
卷号	24 期号:5
英文摘要	Many processes in hydrology and Earth system science relate to continental moisture recycling, the contribution of terrestrial evaporation to precipitation. For example, the effects of land-cover changes on regional rainfall regimes depend on this process. To study moisture recycling, a range of moisture-tracking models are in use that are forced with output from atmospheric models but differ in various ways. They can be Eulerian (grid-based) or Lagrangian (trajectory-based), have two or three spatial dimensions, and rely on a range of other assumptions. Which model is most suitable depends not only on the purpose of the study but also on the quality and resolution of the data with which it is forced. Recently, the high-resolution ERA5 reanalysis data set has become the state of the art, paving the way for a new generation of moisture-tracking models. However, it is unclear how the new data can best be used to obtain accurate estimates of atmospheric moisture flows. Here we develop a set of moisture-tracking models forced with ERA5 data and systematically test their performance regarding continental evaporation recycling ratio, distances of moisture flows, and "footprints" of evaporation from seven point sources across the globe. We report simulation times to assess possible trade-offs between accuracy and speed. Three-dimensional Lagrangian models were most accurate and ran faster than Eulerian versions for tracking water from single grid cells. The rate of vertical mixing of moisture in the atmosphere was the greatest source of uncertainty in moisture tracking. We conclude that the recently improved resolution of atmospheric reanalysis data allows for more accurate moisture tracking results in a Lagrangian setting, but that considerable uncertainty regarding turbulent mixing remains. We present an efficient Lagrangian method to track atmospheric moisture flows from any location globally using ERA5 reanalysis data and make the code for this model, which we call UTrack-atmospheric-moisture, publicly available. © Author(s)2020.
语种	英语
scopus关键词	Economic and social effects; Evaporation; Lagrange multipliers; Mixing; Recycling; Atmospheric model; Atmospheric moisture; Atmospheric reanalysis data; Earth system science; Lagrangian methods; Lagrangian models; Land-cover change; Spatial dimension; Moisture; atmospheric modeling; atmospheric moisture; precipitation (climatology); rainfall; tracking; uncertainty analysis
来源期刊	Hydrology and Earth System Sciences
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/159409
作者单位	Tuinenburg, O.A., Copernicus Institute for Sustainable Development, Utrecht University, TC Utrecht, 3508, Netherlands, Stockholm Resilience Centre, Stockholm University, Stockholm, 10691, Sweden, Bolin Centre for Climate Research, Stockholm, 10691, Sweden; Staal, A., Stockholm Resilience Centre, Stockholm University, Stockholm, 10691, Sweden, Bolin Centre for Climate Research, Stockholm, 10691, Sweden
推荐引用方式 GB/T 7714	Tuinenburg O.A.,Staal A.. Tracking the global flows of atmospheric moisture and associated uncertainties[J],2020,24(5).
APA	Tuinenburg O.A.,&Staal A..(2020).Tracking the global flows of atmospheric moisture and associated uncertainties.Hydrology and Earth System Sciences,24(5).
MLA	Tuinenburg O.A.,et al."Tracking the global flows of atmospheric moisture and associated uncertainties".Hydrology and Earth System Sciences 24.5(2020).