Quantification of Evaporative Sources of Precipitation and Its Changes in the Southeastern Tibetan Plateau and Middle Yangtze River Basin
Abstract
:1. Introduction
2. Model, Dataset, Study Regions, and Methodology
2.1. Model
2.2. Dataset Used
2.3. Study Region and Methodology
3. Results
3.1. Mean Evaporative Source in the Two Regions
3.2. Linear Trend of the Evaporative Source over the Past Three Decades
3.3. Relationship of the Seasonal and Inter-Annual Variability of Evaporative Source with the Large-Scale Climate Systems
4. Discussions and Conclusions
4.1. Discussions
4.2. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
- Zhisheng, A.; Guoxiong, W.; Jianping, L.; Youbin, S.; Yimin, L.; Weijian, Z.; Yanjun, C.; Anmin, D.; Li, L.; Jiangyu, M. Global monsoon dynamics and climate change. Annu. Rev. Earth Planet. Sci. 2015, 43, 29–77. [Google Scholar] [CrossRef]
- Gadgil, S. The Indian monsoon and its variability. Annu. Rev. Earth Planet. Sci. 2003, 31, 429–467. [Google Scholar] [CrossRef]
- Wang, B. Rainy season of the asian–pacific summer monsoon. J. Clim. 2002, 15, 386–398. [Google Scholar] [CrossRef]
- Ge, M.; Feng, Z. Classification of densities and characteristics of curve of population centers in china by GIS. J. Geogr. Sci. 2010, 20, 628–640. [Google Scholar] [CrossRef]
- Huang, X.F.; Xue, L.; Tian, X.D.; Shao, W.W.; Sun, T.L.; Gong, Z.H.; Ju, W.W.; Jiang, B.; Hu, M.; He, L.Y. Highly time-resolved carbonaceous aerosol characterization in yangtze river delta of china: Composition, mixing state and secondary formation. Atmos. Environ. 2013, 64, 200–207. [Google Scholar] [CrossRef]
- Ding, Y. The variability of the asian summer monsoon. J. Meteorol. Soc. Jpn. Ser. II 2007, 85, 21–54. [Google Scholar] [CrossRef]
- Adrien, F.; Martin, P.C.; Pauls, S.U.; JäHnig, S.C.; Dieter, U.; Ingo, M.; Muellner-Riehl, A.N. The role of the uplift of the Qinghai-Tibetan Plateau for the evolution of Tibetan biotas. Biol. Rev. Camb. Philos. Soc. 2015, 90, 236–253. [Google Scholar]
- Hou, J.; D’Andrea, W.J.; Wang, M.; He, Y.; Liang, J. Influence of the indian monsoon and the subtropical jet on climate change on the Tibetan Plateau since the late pleistocene. Quat. Sci. Rev. 2017, 163, 84–94. [Google Scholar] [CrossRef]
- Hren, M.T.; Bookhagen, B.; Blisniuk, P.M.; Booth, A.L.; Chamberlain, C.P. Δ18o and δd of streamwaters across the himalaya and Tibetan Plateau: Implications for moisture sources and paleoelevation reconstructions. Earth Planet. Sci. Lett. 2009, 288, 20–32. [Google Scholar] [CrossRef]
- Wernicke, J.; Hochreuther, P.; Grießinger, J.; Zhu, H.; Wang, L.; Bräuning, A. Multi-century humidity reconstructions from the southeastern Tibetan Plateau inferred from tree-ring δ18o. Glob. Planet. Chang. 2017, 149, 26–35. [Google Scholar] [CrossRef]
- Liu, Z.; Liu, Y.; Wang, S.; Yang, X.; Wang, Z. Evaluation of spatial and temporal performances of era-interim precipitation and temperature in mainland china. J. Clim. 2018, 31, 4347–4365. [Google Scholar] [CrossRef]
- Li, K.; Liu, X.; Wang, Y.; Herzschuh, U.; Ni, J.; Liao, M.; Xiao, X. Late holocene vegetation and climate change on the southeastern Tibetan Plateau: Implications for the indian summer monsoon and links to the indian ocean dipole. Quat. Sci. Rev. 2017, 177, 235–245. [Google Scholar] [CrossRef]
- Gao, X.; Shi, Y.; Song, R.; Giorgi, F.; Wang, Y.; Zhang, D. Reduction of future monsoon precipitation over china: Comparison between a high resolution rcm simulation and the driving gcm. Meteorol. Atmos. Phys. 2008, 100, 73–86. [Google Scholar] [CrossRef]
- Van der Ent, R.J.; Savenije, H.H.; Schaefli, B.; Steele-Dunne, S.C. Origin and fate of atmospheric moisture over continents. Water Resour. Res. 2010, 46, W09525. [Google Scholar] [CrossRef]
- Dirmeyer, P.A.; Brubaker, K.L. Characterization of the global hydrologic cycle from a back-trajectory analysis of atmospheric water vapor. J. Hydrometeorol. 2007, 8, 20–37. [Google Scholar] [CrossRef]
- Trenberth, K.E. Atmospheric moisture residence times and cycling: Implications for rainfall rates and climate change. Clim. Chang. 1998, 39, 667–694. [Google Scholar] [CrossRef]
- McDonald, J.E. The evaporation-precipitation fallacy. Weather 1962, 17, 168–177. [Google Scholar] [CrossRef]
- Budyko, M.; Drozdov, O. Characteristics of the moisture circulation in the atmosphere. Izv. Akad. Nauk SSSR Ser. Geogr. Geofiz 1953, 4, 5–14. [Google Scholar]
- Dirmeyer, P.A.; Brubaker, K.L.; DelSole, T. Import and export of atmospheric water vapor between nations. J. Hydrol. 2009, 365, 11–22. [Google Scholar] [CrossRef]
- Trenberth, K.E. Atmospheric moisture recycling: Role of advection and local evaporation. J. Clim. 1999, 12, 1368–1381. [Google Scholar] [CrossRef]
- Dominguez, F.; Kumar, P.; Liang, X.Z.; Ting, M. Impact of atmospheric moisture storage on precipitation recycling. J. Clim. 2006, 19, 1513–1530. [Google Scholar] [CrossRef]
- Zhang, C.; Tang, Q.; Chen, D. Recent changes in the moisture source of precipitation over the Tibetan Plateau. J. Clim. 2017, 30, 1807–1819. [Google Scholar] [CrossRef]
- Zhang, C.; Tang, Q.; Chen, D.; van der Ent, R.J.; Liu, X.; Li, W.; Gebremeskel Haile, G. Moisture source changes contributed to different precipitation changes over the northern and southern Tibetan Plateau. J. Hydrometeorol. 2019, 20, 217–229. [Google Scholar] [CrossRef]
- Curio, J.; Maussion, F.; Scherer, D. A 12-year high-resolution climatology of atmospheric water transport over the Tibetan Plateau. Earth Syst. Dyn. 2015, 6, 109–124. [Google Scholar] [CrossRef] [Green Version]
- Chen, B.; Xu, X.D.; Yang, S.; Zhang, W. On the origin and destination of atmospheric moisture and air mass over the Tibetan Plateau. Theor. Appl. Climatol. 2012, 110, 423–435. [Google Scholar] [CrossRef]
- Drumond, A.; Nieto, R.; Gimeno, L. Sources of moisture for china and their variations during drier and wetter conditions in 2000–2004: A lagrangian approach. Clim. Res. 2011, 50, 215–225. [Google Scholar] [CrossRef]
- Wang, N.; Zeng, X.M.; Guo, W.D.; Chen, C.; Wei, Y.; Zheng, Y.; Jian, Z. Quantitative diagnosis of moisture sources and transport pathways for summer precipitation over the mid-lower yangtze river basin. J. Hydrol. 2018, 559, 252–265. [Google Scholar] [CrossRef]
- Chen, B.; Xu, X.D.; Zhao, T. Main moisture sources affecting lower yangtze river basin in boreal summers during 2004–2009. Int. J. Climatol. 2013, 33, 1035–1046. [Google Scholar]
- Budyko, M. Climate and Life; Academic Press: New York, NY, USA, 1974; Volume 508. [Google Scholar]
- Eltahir, E.A.; Bras, R.L. Precipitation recycling. Rev. Geophys. 1996, 34, 367–378. [Google Scholar] [CrossRef]
- Brubaker, K.L.; Entekhabi, D.; Eagleson, P. Estimation of continental precipitation recycling. J. Clim. 1993, 6, 1077–1089. [Google Scholar] [CrossRef]
- Dominguez, F.; Kumar, P.; Vivoni, E.R. Precipitation recycling variability and ecoclimatological stability—A study using narr data. Part ii: North American monsoon region. J. Clim. 2008, 21, 5187–5203. [Google Scholar] [CrossRef]
- Van der Ent, R.J.; Savenije, H. Length and time scales of atmospheric moisture recycling. Atmos. Chem. Phys. 2011, 11, 1853–1863. [Google Scholar] [CrossRef] [Green Version]
- Stohl, A.; Forster, C.; Frank, A.; Seibert, P.; Wotawa, G. The lagrangian particle dispersion model flexpart version 6.2. Atmos. Chem. Phys. 2005, 5, 2461–2474. [Google Scholar] [CrossRef]
- Brioude, J.; Arnold, D.; Stohl, A. The lagrangian particle dispersion model flexpart-wrf version 3.1. Geosci. Model Dev. 2013, 6, 1889–1904. [Google Scholar] [CrossRef]
- Van der Ent, R.J.; Tuinenburg, O.; Knoche, H.R.; Kunstmann, H.; Savenije, H. Should we use a simple or complex model for moisture recycling and atmospheric moisture tracking? Hydrol. Earth Syst. Sci. 2013, 17, 4869–4884. [Google Scholar] [CrossRef] [Green Version]
- Fitzmaurice, J.A. A Critical Analysis of Bulk Precipitation Recycling Models. Ph.D. Thesis, Massachusetts Institute of Technology, Cambridge, MA, USA, 2007. [Google Scholar]
- Burde, G.I. Bulk recycling models with incomplete vertical mixing. Part i: Conceptual framework and models. J. Clim. 2006, 19, 1461–1472. [Google Scholar] [CrossRef]
- Harding, K.J.; Snyder, P.K. Modeling the atmospheric response to irrigation in the great plains. Part ii: The precipitation of irrigated water and changes in precipitation recycling. J. Hydrometeorol. 2012, 13, 1687–1703. [Google Scholar] [CrossRef]
- Tuinenburg, O.; Hutjes, R.; Kabat, P. The fate of evaporated water from the Ganges basin. J. Geophys. Res. Atmos. 2012, 117, D01107. [Google Scholar] [CrossRef]
- Wei, J.F.; Dirmeyer, P.A.; Bosilovich, M.G.; Wu, R.G. Water vapor sources for yangtze river valley rainfall: Climatology, variability, and implications for rainfall forecasting. J. Geophys. Res. Atmos. 2012, 117, D05126. [Google Scholar] [CrossRef]
- Brubaker, K.L.; Dirmeyer, P.A.; Sudradjat, A.; Levy, B.S.; Bernal, F. A 36-yr climatological description of the evaporative sources of warm-season precipitation in the mississippi river basin. J. Hydrometeorol. 2001, 2, 537–557. [Google Scholar] [CrossRef]
- Dirmeyer, P.A.; Brubaker, K.L. Contrasting evaporative moisture sources during the drought of 1988 and the flood of 1993. J. Geophys. Res. Atmos. 1999, 104, 19383–19397. [Google Scholar] [CrossRef]
- Merrill, J.T.; Bleck, R.; Boudra, D. Techniques of lagrangian trajectory analysis in isentropic coordinates. Mon. Weather Rev. 1986, 114, 571–581. [Google Scholar] [CrossRef]
- Dee, D.P.; Uppala, S. Variational bias correction of satellite radiance data in the era-interim reanalysis. Q. J. R. Meteorol. Soc. 2009, 135, 1830–1841. [Google Scholar] [CrossRef]
- Dee, D.P.; Uppala, S.; Simmons, A.; Berrisford, P.; Poli, P.; Kobayashi, S.; Andrae, U.; Balmaseda, M.; Balsamo, G.; Bauer, P. The era-interim reanalysis: Configuration and performance of the data assimilation system. Q. J. R. Meteorol. Soc. 2011, 137, 553–597. [Google Scholar] [CrossRef]
- Gao, Y.; Cuo, L.; Zhang, Y. Changes in moisture flux over the Tibetan Plateau during 1979–2011 and possible mechanisms. J. Clim. 2014, 27, 1876–1893. [Google Scholar] [CrossRef]
- Roxy, M.K.; Ritika, K.; Terray, P.; Murtugudde, R.; Ashok, K.; Goswami, B. Drying of indian subcontinent by rapid indian ocean warming and a weakening land-sea thermal gradient. Nat. Commun. 2015, 6, 7423. [Google Scholar] [CrossRef] [PubMed]
- Song, F.; Zhou, T.; Qian, Y. Responses of East Asian summer monsoon to natural and anthropogenic forcings in the 17 latest cmip5 models. Geophys. Res. Lett. 2014, 41, 596–603. [Google Scholar] [CrossRef]
- Zhu, C.; Wang, B.; Qian, W.; Zhang, B. Recent weakening of northern East Asian summer monsoon: A possible response to global warming. Geophys. Res. Lett. 2012, 39, L09701. [Google Scholar] [CrossRef]
- Martinez, J.A.; Dominguez, F. Sources of atmospheric moisture for the la plata river basin. J. Climate 2014, 27, 6737–6753. [Google Scholar] [CrossRef]
- Petterssen, S. Weather Analysis and Forecasting; McGraw-Hill Book Company: New York, NY, USA, 1940; pp. 221–223. [Google Scholar]
SETP | MYRB | |||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
April | May | June | July | August | September | Average | April | May | June | July | August | September | Average | |
ARS | 0.85 | 0.46 | 0.75 | 0.21 | 0.08 | 0.12 | 0.41 | 0.34 | 0.19 | 0.37 | 0.71 | 0.10 | 0.01 | 0.29 |
BM | 8.97 | 8.57 | 11.41 | 11.87 | 10.18 | 14.85 | 10.97 | 3.80 | 4.53 | 5.17 | 3.42 | 1.00 | 1.47 | 3.23 |
BB | 0.44 | 0.48 | 3.23 | 2.62 | 1.12 | 2.20 | 1.68 | 0.75 | 2.06 | 7.04 | 5.51 | 2.17 | 0.43 | 2.99 |
INDO | 0.06 | 0.12 | 0.35 | 0.46 | 0.50 | 1.22 | 0.45 | 6.11 | 7.37 | 7.85 | 8.26 | 4.50 | 2.91 | 6.17 |
CC | 0.74 | 0.78 | 0.63 | 0.89 | 1.02 | 0.57 | 0.77 | 10.99 | 10.92 | 8.81 | 8.33 | 10.54 | 12.61 | 10.37 |
NE | 0.01 | 0.01 | 0.01 | 0.01 | 0.02 | 0.01 | 0.01 | 0.51 | 0.34 | 0.27 | 0.29 | 0.34 | 0.76 | 0.42 |
NIN | 12.51 | 10.14 | 13.12 | 5.78 | 1.88 | 5.34 | 8.13 | 2.66 | 2.80 | 1.86 | 0.48 | 0.13 | 0.25 | 1.36 |
NW | 0.40 | 0.64 | 0.45 | 0.31 | 0.28 | 0.27 | 0.39 | 0.87 | 0.99 | 0.54 | 0.36 | 0.27 | 0.40 | 0.57 |
PAC | 0.01 | 0.01 | 0.01 | 0.06 | 0.06 | 0.16 | 0.05 | 2.40 | 1.89 | 1.76 | 3.20 | 6.06 | 8.31 | 3.94 |
SC | 7.03 | 7.38 | 6.46 | 10.69 | 16.11 | 12.51 | 10.03 | 28.10 | 26.47 | 27.90 | 30.96 | 31.16 | 31.87 | 29.41 |
SCS | 0.02 | 0.03 | 0.06 | 0.23 | 0.28 | 0.54 | 0.19 | 7.08 | 7.34 | 5.91 | 8.83 | 7.75 | 5.92 | 7.14 |
SIN | 0.17 | 0.18 | 0.56 | 0.57 | 0.24 | 0.36 | 0.35 | 0.14 | 0.20 | 0.42 | 0.58 | 0.18 | 0.03 | 0.26 |
RTP | 27.41 | 29.66 | 28.04 | 28.01 | 25.55 | 29.23 | 27.98 | 2.01 | 1.93 | 2.37 | 1.91 | 1.38 | 1.91 | 1.92 |
SETP | 33.32 | 36.66 | 30.20 | 37.23 | 41.86 | 31.85 | 35.19 | 2.57 | 2.49 | 2.52 | 2.01 | 1.33 | 2.57 | 2.25 |
WE | 7.90 | 4.76 | 4.60 | 0.84 | 0.41 | 0.53 | 3.17 | 1.34 | 1.22 | 0.65 | 0.20 | 0.13 | 0.09 | 0.62 |
MYRB | 0.16 | 0.12 | 0.12 | 0.21 | 0.42 | 0.25 | 0.21 | 30.34 | 29.25 | 26.58 | 24.97 | 32.95 | 30.44 | 29.09 |
April | May | June | July | August | September | Average | |||
---|---|---|---|---|---|---|---|---|---|
SETP | Terrestrial | 98.67 | 99.02 | 95.95 | 96.88 | 98.46 | 96.99 | 97.66 | |
Local | 33.32 | 36.66 | 30.20 | 37.23 | 41.86 | 31.85 | 35.19 | ||
Oceanic | 1.33 | 0.98 | 4.05 | 3.12 | 1.54 | 3.01 | 2.34 | ||
Indian Ocean | 1.29 | 0.95 | 3.98 | 2.83 | 1.20 | 2.31 | 2.09 | ||
Pacific Ocean | 0.04 | 0.03 | 0.07 | 0.29 | 0.34 | 0.70 | 0.24 | ||
MYRB | Terrestrial | 89.43 | 88.53 | 84.92 | 81.76 | 83.91 | 85.33 | 85.65 | |
Local | 30.34 | 29.25 | 26.58 | 24.97 | 32.95 | 30.44 | 29.09 | ||
Oceanic | 10.57 | 11.47 | 15.08 | 18.24 | 16.09 | 14.67 | 14.35 | ||
Indian Ocean | 1.08 | 2.25 | 7.41 | 6.22 | 2.28 | 0.44 | 3.28 | ||
Pacific Ocean | 9.48 | 9.22 | 7.67 | 12.02 | 13.81 | 14.23 | 11.07 |
SETP | MYRB | |||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
April | May | June | July | August | September | Average | April | May | June | July | August | September | Average | |
ARS | −0.12 | 0.00 | 0.15 | 0.08 | 0.02 | 0.01 | 0.02 | −0.07 | 0.00 | 0.04 | 0.01 | −0.02 | 0.00 | −0.01 |
BM | −0.44 | 0.41 | −0.51 | −0.60 | 0.40 | −1.24 | −0.33 | −0.23 | −0.34 | −0.67 | −0.51 | −0.17 | −0.29 | −0.37 |
BB | −0.02 | 0.07 | −1.04 | −0.24 | 0.02 | −0.61 | −0.30 | −0.11 | 0.02 | −0.64 | −0.25 | −0.25 | −0.16 | −0.23 |
INDO | 0.00 | 0.02 | −0.05 | 0.02 | 0.04 | 0.08 | 0.02 | −0.23 | −0.36 | −0.27 | −0.56 | −0.36 | −0.57 | −0.39 |
CC | 0.01 | 0.03 | −0.02 | 0.34 | 0.14 | 0.04 | 0.09 | −0.15 | −0.16 | −0.16 | 0.89 | −0.54 | 0.29 | 0.03 |
NE | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | −0.10 | −0.05 | −0.11 | 0.05 | −0.10 | 0.10 | −0.03 |
NIN | −0.33 | 0.53 | −0.15 | −1.86 | −0.21 | −1.29 | −0.55 | −0.29 | −0.18 | −0.18 | −0.11 | −0.01 | −0.06 | −0.14 |
NW | 0.02 | 0.07 | −0.04 | −0.07 | −0.09 | −0.04 | −0.02 | −0.01 | 0.08 | −0.05 | 0.01 | −0.03 | −0.03 | 0.00 |
PAC | 0.00 | 0.00 | 0.00 | −0.01 | 0.02 | −0.08 | −0.01 | −0.54 | 0.00 | −0.53 | −0.12 | 0.59 | 0.34 | −0.04 |
SC | 0.05 | 0.25 | 0.20 | 1.41 | 1.17 | 0.94 | 0.67 | −0.39 | −1.15 | −1.67 | −0.18 | −0.26 | −0.14 | −0.63 |
SCS | 0.00 | 0.00 | −0.01 | −0.01 | 0.03 | −0.06 | −0.01 | −0.51 | −0.22 | −0.77 | −1.22 | 0.31 | −0.32 | −0.46 |
SIN | 0.01 | 0.02 | −0.07 | −0.08 | 0.03 | −0.04 | −0.02 | −0.03 | −0.02 | −0.03 | −0.10 | −0.04 | 0.00 | −0.04 |
RTP | −0.62 | 0.47 | −0.29 | 0.02 | 0.58 | −1.58 | −0.24 | 0.02 | −0.03 | −0.10 | 0.25 | −0.05 | −0.14 | −0.01 |
SETP | 0.18 | −0.03 | 0.26 | 1.67 | −0.41 | 0.52 | 0.36 | 0.06 | −0.14 | −0.10 | 0.04 | −0.11 | −0.10 | −0.06 |
WE | −0.90 | 0.43 | 0.06 | 0.09 | 0.04 | −0.03 | −0.05 | −0.26 | −0.03 | −0.07 | 0.07 | 0.00 | −0.02 | −0.05 |
MYRB | 0.00 | 0.02 | 0.01 | 0.07 | 0.04 | 0.01 | 0.02 | −0.43 | −0.28 | 0.75 | 2.20 | 0.02 | 0.03 | 0.38 |
April | May | June | July | August | September | Average | |||
---|---|---|---|---|---|---|---|---|---|
SETP | Terrestrial | −2.02 | 2.23 | −0.60 | 1.01 | 1.74 | −2.63 | −0.05 | |
Local | 0.18 | −0.03 | 0.26 | 1.67 | −0.41 | 0.52 | 0.36 | ||
Oceanic | −0.14 | 0.08 | −0.91 | −0.18 | 0.09 | −0.74 | −0.30 | ||
Indian Ocean | −0.14 | 0.07 | −0.89 | −0.16 | 0.04 | −0.61 | −0.28 | ||
Pacific Ocean | 0.00 | 0.00 | −0.02 | −0.03 | 0.05 | −0.14 | −0.02 | ||
MYRB | Terrestrial | −2.03 | −2.67 | −2.66 | 2.05 | −1.64 | −0.93 | −1.31 | |
Local | −0.43 | −0.28 | 0.75 | 2.20 | 0.02 | 0.03 | 2.28 | ||
Oceanic | −1.23 | −0.21 | −1.90 | −1.58 | 0.63 | −0.15 | −0.74 | ||
Indian Ocean | −0.18 | 0.01 | −0.60 | −0.25 | −0.27 | −0.16 | −0.24 | ||
Pacific Ocean | −1.05 | −0.22 | −1.31 | −1.34 | 0.90 | 0.01 | −0.50 |
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Xu, Y.; Gao, Y. Quantification of Evaporative Sources of Precipitation and Its Changes in the Southeastern Tibetan Plateau and Middle Yangtze River Basin. Atmosphere 2019, 10, 428. https://doi.org/10.3390/atmos10080428
Xu Y, Gao Y. Quantification of Evaporative Sources of Precipitation and Its Changes in the Southeastern Tibetan Plateau and Middle Yangtze River Basin. Atmosphere. 2019; 10(8):428. https://doi.org/10.3390/atmos10080428
Chicago/Turabian StyleXu, Yu, and Yanhong Gao. 2019. "Quantification of Evaporative Sources of Precipitation and Its Changes in the Southeastern Tibetan Plateau and Middle Yangtze River Basin" Atmosphere 10, no. 8: 428. https://doi.org/10.3390/atmos10080428
APA StyleXu, Y., & Gao, Y. (2019). Quantification of Evaporative Sources of Precipitation and Its Changes in the Southeastern Tibetan Plateau and Middle Yangtze River Basin. Atmosphere, 10(8), 428. https://doi.org/10.3390/atmos10080428