Articles | Volume 26, issue 17
https://doi.org/10.5194/hess-26-4587-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/hess-26-4587-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Characterizing basin-scale precipitation gradients in the Third Pole region using a high-resolution atmospheric simulation-based dataset
Yaozhi Jiang
Department of Earth System Science, Ministry of Education Key
Laboratory for Earth System Modeling, Institute for Global Change Studies,
Tsinghua University, Beijing, China
Department of Earth System Science, Ministry of Education Key
Laboratory for Earth System Modeling, Institute for Global Change Studies,
Tsinghua University, Beijing, China
National Tibetan Plateau Data Center, State Key Laboratory of Tibetan
Plateau Earth System, Environment and Resources, Institute of Tibetan
Plateau Research, Chinese Academy of Sciences, Beijing, China
Hua Yang
National Tibetan Plateau Data Center, State Key Laboratory of Tibetan
Plateau Earth System, Environment and Resources, Institute of Tibetan
Plateau Research, Chinese Academy of Sciences, Beijing, China
Department of Earth System Science, Ministry of Education Key
Laboratory for Earth System Modeling, Institute for Global Change Studies,
Tsinghua University, Beijing, China
Yingying Chen
National Tibetan Plateau Data Center, State Key Laboratory of Tibetan
Plateau Earth System, Environment and Resources, Institute of Tibetan
Plateau Research, Chinese Academy of Sciences, Beijing, China
National Tibetan Plateau Data Center, State Key Laboratory of Tibetan
Plateau Earth System, Environment and Resources, Institute of Tibetan
Plateau Research, Chinese Academy of Sciences, Beijing, China
Jing Sun
Department of Earth System Science, Ministry of Education Key
Laboratory for Earth System Modeling, Institute for Global Change Studies,
Tsinghua University, Beijing, China
Yuan Yang
Institute of Science and Technology, China Three Gorges
Corporation, Beijing, China
Yan Wang
Key Laboratory of Land Surface Pattern and Simulation, Institute of
Geographic Science and Natural Resources Research, Chinese Academy of
Sciences, Beijing, China
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Cited articles
Andermann, C., Bonnet, S., and Gloaguen, R.: Evaluation of precipitation
data sets along the Himalayan front, Geochem. Geophy. Geosy., 12, Q07023,
https://doi.org/10.1029/2011GC003513, 2011.
Basist, A., Bell, G. D., and Meentemeyer, V.: Statistical Relationships between Topography and Precipitation Patterns, J. Climate, 7, 1305–1315, https://doi.org/10.1175/1520-0442(1994)007<1305:SRBTAP>2.0.CO;2, 1994.
Bookhagen, B. and Burbank, D. W.: Topography, relief, and TRMM-derived rainfall variations along the Himalaya, Geophys. Res. Lett., 33, L08405,
https://doi.org/10.1029/2006GL026037, 2006.
Chen, H., Yuan, W., Li, J., and Yu, R.: A possible cause for different
diurnal variations of warm season rainfall as shown in station observations
and TRMM 3B42 data over the southeastern Tibetan plateau, Adv. Atmos. Sci.,
29, 193–200, https://doi.org/10.1007/s00376-011-0218-1, 2012.
Chen, R., Han, C., Liu, J., Yang, Y., Liu, Z., Wang, L., and Kang, E.:
Maximum precipitation altitude on the northern flank of the Qilian
Mountains, northwest China, Hydrol. Res., 49, 1696–1710,
https://doi.org/10.2166/nh.2018.121, 2018.
Chen, Y., Sharma, S., Zhou, X., Yang, K., Li, X., Niu, X., Hu, X., and
Khadka, N.: Spatial performance of multiple reanalysis precipitation
datasets on the southern slope of central Himalaya, Atmos. Res., 250, 105365,
https://doi.org/10.1016/j.atmosres.2020.105365, 2020.
Collier, E. and Immerzeel, W. W.: High-resolution modeling of atmospheric
dynamics in the Nepalese Himalaya, J. Geophys. Res.-Atmos., 120, 9882–9896,
https://doi.org/10.1038/175238c0, 2015.
Cuo, L. and Zhang, Y.: Spatial patterns of wet season precipitation vertical
gradients on the Tibetan Plateau and the surroundings, Sci. Rep.-UK, 7, 1–10,
https://doi.org/10.1038/s41598-017-05345-6, 2017.
Daly, C., Taylor, G., and Gibson, W.: The Prism approach to mapping
precipitation and temperature, in: Proceedings of the 10th AMS Conf. Appl. Climatol. Amer. Meteor Soc., Reno, NV, 20–23 October, 1–4, 1997.
Daly, C., Gibson, W. P., Taylor, G. H., Johnson, G. L., and Pasteris, P.: A
knowledge-based approach to the statistical mapping of climate, Clim. Res.,
22, 99–113, https://doi.org/10.3354/cr022099, 2002.
Derin, Y. and Yilmaz, K. K.: Evaluation of multiple satellite-based
precipitation products over complex topography, J. Hydrometeorol., 15,
1498–1516, https://doi.org/10.1175/JHM-D-13-0191.1, 2014.
Diodato, N.: The influence of topographic co-variables on the spatial variability of precipitation over small regions of complex terrain, Int. J. Climatol., 25, 351–363, https://doi.org/10.1002/joc.1131, 2005.
Gao, Y., Xu, J., and Chen, D.: Evaluation of WRF mesoscale climate simulations
over the Tibetan Plateau during 1979–2011, J. Climate, 28, 2823–2841,
https://doi.org/10.1175/JCLI-D-14-00300.1, 2015.
Gao, Y., Chen, F., and Jiang, Y.: Evaluation of a convection-permitting
modeling of precipitation over the Tibetan Plateau and its influences on the
simulation of snow-cover fraction, J. Hydrometeorol., 21, 1531–1548,
https://doi.org/10.1175/JHM-D-19-0277.1, 2020.
Guo, X., Wang, L., and Tian, L.: Spatio-temporal variability of vertical
gradients of major meteorological observations around the Tibetan Plateau,
Int. J. Climatol., 36, 1901–1916, https://doi.org/10.1002/joc.4468, 2016.
Han, C., Wang, L., Chen, R., Liu, Z., Liu, J., Yang, Y., and Lv, H.:
Precipitation observation network and its data application in the alpine
region of Qilian Mountains, Resources Science, 42, 1987–1997,
https://doi.org/10.18402/resci.2020.10.15, 2020 (in Chinese).
Henn, B., Newman, A. J., Livneh, B., Daly, C., and Lundquist, J. D.: An
assessment of differences in gridded precipitation datasets in complex
terrain, J. Hydrol., 556, 1205–1219,
https://doi.org/10.1016/j.jhydrol.2017.03.008, 2018.
Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A.,
Muñoz-Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D.,
Simmons, A., Soci, C., Abdalla, S., Abellan, X., Balsamo, G., Bechtold, P.,
Biavati, G., Bidlot, J., Bonavita, M., De Chiara, G., Dahlgren, P., Dee, D.,
Diamantakis, M., Dragani, R., Flemming, J., Forbes, R., Fuentes, M., Geer,
A., Haimberger, L., Healy, S., Hogan, R.J., Hólm, E., Janisková, M.,
Keeley, S., Laloyaux, P., Lopez, P., Lupu, C., Radnoti, G., de Rosnay, P.,
Rozum, I., Vamborg, F., Villaume, S., and Thépaut, J. N.: The ERA5 global
reanalysis, Q. J. R. Meteor. Soc., 146, 1999–2049,
https://doi.org/10.1002/qj.3803, 2020.
Hill, F. F.: The use of average annual rainfall to derive estimates of
orographic enhancement of frontal rain over England and Wales for different
wind directions, J. Climatol., 3, 113–129,
https://doi.org/10.1002/joc.3370030202, 1983.
Houze, R. A.: Orographic Effects on Precipitating Clouds, Rev. Geophys., 50,
1–47, https://doi.org/10.1029/2011RG000365, 2012.
Huffman, G., Bolvin, D., Nelkin, E., and Tan, J.: Integrated Multi-satellite
Retrievals for GPM (IMERG) Technical Documentation, NASA, https://docserver.gesdisc.eosdis.nasa.gov/public/project/GPM/IMERG_doc.06.pdf (last access: 11 September 2022), 2019.
Hutchinson, M. F.: The application of thin plate smoothing splines to
continent-wide data assimilation, edited by: Jasper, J. D., BMRC Research Report
No. 27, Data Assimilation Systems, 104–113, 1991.
Immerzeel, W. W., Petersen, L., Ragettli, S., and Pellicciotti, F.: The
importance of observed gradients of air temperature and precipitation for
modeling runoff from a glacierized watershed in the Nepalese Himalayas,
Water Resour. Res., 50, 2212–2226, https://doi.org/10.1002/2013WR014506,
2014.
Jiang, Y., Yang, K., Shao, C., Zhou, X., Zhao, L., and Chen, Y.: A
downscaling approach for constructing high-resolution precipitation dataset
over the Tibetan Plateau from ERA5 reanalysis, Atmos. Res., 256, 105574,
https://doi.org/10.1016/j.atmosres.2021.105574, 2021.
Johansson, B. and Chen, D.: The influence of wind and topography on
precipitation distribution in Sweden: Statistical analysis and modelling,
Int. J. Climatol., 23, 1523–1535, https://doi.org/10.1002/joc.951, 2003.
Kan, B., Su, F., Xu, B., Xie, Y., Li, J., and Zhang, H.: Generation of High
Mountain Precipitation and Temperature Data for a Quantitative Assessment of
Flow Regime in the Upper Yarkant Basin in the Karakoram, J. Geophys. Res.-Atmos., 123, 8462–8486, https://doi.org/10.1029/2017JD028055, 2018.
Li, D., Yang, K., Tang, W., Li, X., Zhou, X., and Guo, D.: Characterizing
precipitation in high altitudes of the western Tibetan plateau with a focus
on major glacier areas, Int. J. Climatol., 40, 1–14,
https://doi.org/10.1002/joc.6509, 2020.
Li, Z. and Fu, B.: Characteristics of climate in Qinling Mountains,
Monography of Montain Climate, Meteorological Press, Beijing, 87–96, 1984 (in Chinese).
Linke, S., Lehner, B., Ouellet Dallaire, C., Ariwi, J., Grill, G., Anand,
M., Beames, P., Burchard-Levine, V., Maxwell, S., Moidu, H., Tan, F., and
Thieme, M.: Global hydro-environmental sub-basin and river reach
characteristics at high spatial resolution, Sci. Data, 6, 1–15,
https://doi.org/10.1038/s41597-019-0300-6, 2019.
Liu, J., Chen, R., Qin, W., and Yang, Y.: Study on the vertical distribution
of precipitation in mountainous regions using TRMM data, Adv. water Sci.,
22, 447–454, 2011.
Lundquist, J., Hughes, M., Gutmann, E., and Kapnick, S.: Our skill in
modeling mountain rain and snow is bypassing the skill of our observational
networks, B. Am. Meteorol. Soc., 100, 2473–2490,
https://doi.org/10.1175/BAMS-D-19-0001.1, 2019.
Maussion, F., Scherer, D., Mölg, T., Collier, E., Curio, J., and
Finkelnburg, R.: Precipitation seasonality and variability over the Tibetan
Plateau as resolved by the high Asia reanalysis, J. Climate, 27, 1910–1927,
https://doi.org/10.1175/JCLI-D-13-00282.1, 2014.
Ouyang, L., Yang, K., Lu, H., Chen, Y., Lazhu, Zhou, X., and Wang, Y.:
Ground-Based Observations Reveal Unique Valley Precipitation Patterns in the
Central Himalaya, J. Geophys. Res.-Atmos., 125, e2019JD031502,
https://doi.org/10.1029/2019JD031502, 2020.
Ouyang, L., Lu, H., Yang, K., Leung, L.R., Wang, Y., Zhao, L., Zhou, X.,
LaZhu, Chen, Y., Jiang, Y., and Yao, X.: Characterizing uncertainties in
ground “truth” of precipitation over complex terrain through
high-resolution numerical modeling, Geophys. Res. Lett., 48, e2020GL091950,
https://doi.org/10.1029/2020gl091950, 2021.
Pan, X., Li, X., Shi, X., Han, X., Luo, L., and Wang, L.: Dynamic
downscaling of near-surface air temperature at the basin scale using WRF-a
case study in the Heihe River Basin, China, Front. Earth Sci., 6, 314–323,
https://doi.org/10.1007/s11707-012-0306-2, 2012.
Pritchard, D. M. W., Forsythe, N., Fowler, H. J., O'Donnell, G. M., and Li,
X. F.: Evaluation of upper indus near-surface climate representation by WRF
in the High Asia Refined Analysis, J. Hydrometeorol., 20, 467–487,
https://doi.org/10.1175/JHM-D-18-0030.1, 2019.
Putkonen, J. K.: Continuous snow and rain data at 500 to 4400 m altitude near
Annapurna, Nepal, 1999–2001, Arct. Antarct. Alp. Res., 36, 244–248,
https://doi.org/10.1657/1523-0430(2004)036[0244:CSARDA]2.0.CO;2, 2004.
Roe, G. H.: Orographic precipitation, Annu. Rev. Earth Pl. Sc., 33,
645–671, https://doi.org/10.1146/annurev.earth.33.092203.122541, 2005.
Salerno, F., Guyennon, N., Thakuri, S., Viviano, G., Romano, E., Vuillermoz, E., Cristofanelli, P., Stocchi, P., Agrillo, G., Ma, Y., and Tartari, G.: Weak precipitation, warm winters and springs impact glaciers of south slopes of Mt. Everest (central Himalaya) in the last 2 decades (1994–2013), The Cryosphere, 9, 1229–1247, https://doi.org/10.5194/tc-9-1229-2015, 2015.
Shen, Y., Xiong, A., Hong, Y., Yu, J., Pan, Y., Chen, Z., and Saharia, M.:
Uncertainty analysis of five satellite-based precipitation products and
evaluation of three optimally merged multi-algorithm products over the
Tibetan Plateau, Int. J. Remote Sens., 35, 6843–6858,
https://doi.org/10.1080/01431161.2014.960612, 2014.
Singh, P., Ramasastri, K. S., and Kumar, N.: Topographical influence on precipitation distribution in different ranges of western Himalayas, Hydrol. Res., 26, 259–284, https://doi.org/10.2166/nh.1995.0015, 1995.
Skamarock, W. C., Klemp, J. B., Dudhia, J., Gill, D. O., Barker, D. M., Duda,
M. G., Huang, X., Wang, W., and Powers, J. G.: A Description of the Advanced
Research WRF Version 3 (No. NCAR/TN–475+STR), Technical Report, University Corporation for
Atmospheric Research, https://doi.org/10.5065/D68S4MVH, 2008.
Sun, H. and Su, F.: Precipitation correction and reconstruction for
streamflow simulation based on 262 rain gauges in the upper Brahmaputra of
southern Tibetan Plateau, J. Hydrol., 590, 125484,
https://doi.org/10.1016/j.jhydrol.2020.125484, 2020.
Sun, J., Yang, K., Guo, W., Wang, Y., He, J., and Lu, H.: Why has the inner
tibetan plateau become wetter since the Mid-1990s?, J. Climate, 33, 8507–8522,
https://doi.org/10.1175/JCLI-D-19-0471.1, 2020.
Tang, G., Long, D., Hong, Y., Gao, J., and Wan, W.: Documentation of
multifactorial relationships between precipitation and topography of the
Tibetan Plateau using spaceborne precipitation radars, Remote Sens.
Environ., 208, 82–96, https://doi.org/10.1016/j.rse.2018.02.007, 2018.
Wang, L., Chen, R., Song, Y., Yang, Y., Liu, J., Han, C., and Liu, Z.:
Precipitation–altitude relationships on different timescales and at
different precipitation magnitudes in the Qilian Mountains, Theor. Appl.
Climatol., 134, 875–884, https://doi.org/10.1007/s00704-017-2316-1, 2018a.
Wang, L., Zhang, F., Zhang, H., Scott, C. A., Zeng, C., and Shi, X.:
Intensive precipitation observation greatly improves hydrological modelling
of the poorly gauged high mountain Mabengnong catchment in the Tibetan
Plateau, J. Hydrol., 556, 500–509,
https://doi.org/10.1016/j.jhydrol.2017.11.039, 2018b.
Wang, N., He, J., Jiang, X., Song, G., Pu, J., Wu, X., and Chen, L.: Study
on the zone of maximum precipitation in the north slopes of the central
Qilian Mountains, Journal of Glaciology and Geocryology,
31, 395–403, 2009 (in Chinese).
Wang, X., Pang, G., and Yang, M.: Precipitation over the tibetan plateau
during recent decades: A review based on observations and simulations, Int.
J. Climatol., 38, 1116–1131, https://doi.org/10.1002/joc.5246, 2018.
Wang, X., Tolksdorf, V., Otto, M., and Scherer, D.: WRF-based dynamical
downscaling of ERA5 reanalysis data for High Mountain Asia: Towards a new
version of the High Asia Refined analysis, Int. J. Climatol., 41, 1–20,
https://doi.org/10.1002/joc.6686, 2020.
Wang, Y., Geerts, B., and Liu, C.: A 30-year convection-permitting regional
climate simulation over the interior western United States. Part I:
Validation, Int. J. Climatol., 38, 3684–3704,
https://doi.org/10.1002/joc.5527, 2018.
Wang, Y., Yang, K., Zhou, X., Chen, D., Lu, H., Ouyang, L., Chen, Y., Lazhu,
Wang, B.: Synergy of orographic drag parameterization and high resolution
greatly reduces biases of WRF-simulated precipitation in central Himalaya,
Clim. Dynam., 54, 1729–1740, https://doi.org/10.1007/s00382-019-05080-w,
2020.
Wulf, H., Bookhagen, B., and Scherler, D.: Seasonal precipitation gradients
and their impact on fluvial sediment flux in the Northwest Himalaya,
Geomorphology, 118, 13–21, https://doi.org/10.1016/j.geomorph.2009.12.003,
2010.
Xu, R., Tian, F., Yang, L., Hu, H., Lu, H., and Hou, A.: Ground validation of
GPM IMERG and trmm 3B42V7 rainfall products over Southern Tibetan plateau
based on a high-density rain gauge network, J. Geophys. Res., 122, 910–924,
https://doi.org/10.1002/2016JD025418, 2017.
Yang, K.: Ground observed precipitation data in Yadong River Valley
(2016–2019), National Tibetan Plateau Data Center [data set],
https://doi.org/10.11888/Meteoro.tpdc.270319, 2020.
Yang, K., Wu, H., Qin, J., Lin, C., Tang, W., Chen, Y.: Recent climate
changes over the Tibetan Plateau and their impacts on energy and water
cycle: A review, Global Planet. Change, 112, 79–91,
https://doi.org/10.1016/j.gloplacha.2013.12.001, 2014.
Yang, K., Guyennon, N., Ouyang, L., Tian, L., Tartari, G., and Salerno, F.:
Impact of summer monsoon on the elevation-dependence of meteorological
variables in the south of central Himalaya, Int. J. Climatol., 38,
1748–1759, https://doi.org/10.1002/joc.5293, 2018.
Yu, H., Wang, L., Yang, R., Yang, M., and Gao, R.: Temporal and spatial
variation of precipitation in the Hengduan Mountains region in China and its
relationship with elevation and latitude, Atmos. Res., 213, 1–16,
https://doi.org/10.1016/j.atmosres.2018.05.025, 2018.
Zeng, C., Zhang, F., Wang, L., and Chen, D.: Summer precipitation
characteristics on the southern Tibetan plateau, Int. J. Climatol., 41,
E3160–E3177, https://doi.org/10.1002/joc.6914, 2021.
Zhang, F., Zhang, H., Hagen, S.C., Ye, M., Wang, D., Gui, D., Zeng, C.,
Tian, L., and Liu, J.: Snow cover and runoff modelling in a high mountain
catchment with scarce data: effects of temperature and precipitation
parameters, Hydrol. Process., 29, 52–65, https://doi.org/10.1002/hyp.10125,
2015.
Zhang, G.: Dataset of river basins map over the TP (2016), National Tibetan Plateau Data Center [data set],
https://doi.org/10.11888/BaseGeography.tpe.249465.file,
2019.
Zhao, Y., Shi, F., Sheng, Y. Li, J., Zhao, Z., Han, M., and Yilihamu, Y.:
Regional differentiation characteristics of precipitation changing with
altitude in Xinjiang region in recent 50 years, Journal of
Glaciology and Geocryology, 33, 1203–1213, 2011 (in Chinese).
Zhou, X., Yang, K., Ouyang, L., Wang, Y., Jiang, Y., Li, X., Chen, D., and
Prein, A.: Added value of kilometer-scale modeling over the third pole
region: a CORDEX-CPTP pilot study, Clim. Dynam., 57, 1673–1687,
https://doi.org/10.1007/s00382-021-05653-8, 2021.
Short summary
Our study quantified the altitudinal precipitation gradients (PGs) over the Third Pole (TP). Most sub-basins in the TP have positive PGs, and negative PGs are found in the Himalayas, the Hengduan Mountains and the western Kunlun. PGs are positively correlated with wind speed but negatively correlated with relative humidity. In addition, PGs tend to be positive at smaller spatial scales compared to those at larger scales. The findings can assist precipitation interpolation in the data-sparse TP.
Our study quantified the altitudinal precipitation gradients (PGs) over the Third Pole (TP)....