Sciences in Cold and Arid Regions ›› 2019, Vol. 11 ›› Issue (2): 93-115.doi: 10.3724/SP.J.1226.2019.00093.

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Review on simulation of land-surface processes on the Tibetan Plateau

Rui Chen1,2,MeiXue Yang1(),XueJia Wang1,GuoNing Wan1   

  1. 1. State Key Laboratory of Cryospheric Science, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, Gansu 730000, China
    2. University of Chinese Academy of Sciences, Beijing 100049, China
  • Received:2019-01-24 Accepted:2019-04-02 Online:2019-04-01 Published:2019-04-29
  • Contact: MeiXue Yang
  • About author:MeiXue Yang, State Key Laboratory of Cryospheric Science, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences. No. 320, West Donggang Road, Lanzhou, Gansu 730000, China. Tel: +86-931-4967376; E-mail:


The Tibetan Plateau (TP) has powerful dynamics and thermal effects, which makes the interaction between its land and atmosphere significantly affect climate and environment in the regional or global area. By retrospecting the latest research progress in the simulation of land-surface processes (LSPs) over the past 20 years, this study discusses both the simulation ability of land-surface models (LSMs) and the modification of parameterization schemes from two perspectives, the models' applicability and improved parameterization schemes. Our review suggests that different LSMs can well capture the spatiotemporal variations of the physical quantities of LSPs; but none of them can be fully applied to the plateau, meaning that all need to be revised according to the characteristics specific to the TP. Avoiding the unstable iterative computation and determining the freeze?thaw critical temperature according to the thermodynamic equilibrium equation, the unreasonable freeze?thaw parameterization scheme can be improved. Due to the complex underlying surface of the TP, no parameterization scheme of roughness length can well simulate the various characteristics of the turbulent flux over the TP at different temporal scales. The uniform soil thermodynamic and hydraulic parameterization scheme is unreasonable when it is applied to the plateau, as a result of the strong soil heterogeneity. There is little research on the snow-cover process so far, and the improved scheme has no advantage over the original one due to the lack of some related physical processes. The constant interaction among subprocesses of LSPs makes the improvement of a multiparameterization scheme yield better simulation results. According to the review of existing research, adding high-quality observation stations, developing a parameterization scheme suitable for the special LSPs of the TP, and adjusting the model structures can be helpful to the simulation of LSPs on the TP.

Key words: Tibetan Plateau, land?atmosphere interaction, land-surface models, model applicability, parameterized modification

Figure 1

Location of study area"

Table 1

Major land-surface-processes experiments of the TP"

Experiments name Primary objective Dates Reference
QXPMEX To study the diurnal variation, seasonal variation, geographical distribution, and heating effect of the plateau radiation balance and heat balance on the TP; the effect on the seasonal variation of planetary-scale circulation; the occurrence, development, and structure of the summer weather system on the TP 1979.5?1979.8 Xu and Chen (2006)
TIPEX To reveal the physical processes of ground?atmosphere interaction, the plateau atmospheric boundary layer and troposphere structure, cloud-radiation processes, and the effects of plateau motions and thermal forces on the formation of atmospheric circulation, monsoons, climate change, and disastrous weather 1996?2000 Xu and Chen (2006)
GAME-Tibet To improve the quantitative understanding of the land?atmosphere interaction on the TP, develop land models and methods, and apply them to larger spatial scales. To develop and test methods for estimating land-surface parameters using satellite data 1996?2000 Ma et al. (2006)
CAMP-Tibet To improve the quantitative understanding of the land?atmosphere interaction and hydrological cycle on the TP, to develop tests of land-surface-processes models, and to calculate land-surface parameters using satellite data 2001?2006 Ma et al. (2006, 2009a)
JICA To understand the impact of the TP on the disastrous weather in East Asia, the impact of the TP on the global and regional energy and water cycle, and the impact of the TP on global climate change 2005?2009 Xu et al. (2008b);Zhang et al. (2012)
TORP To study the multilayer interaction on the TP (mainly land?atmosphere interaction) 2005 up to now Ma et al. (2008, 2009b)

Figure 2

Comparison of simulated soil moisture of four LSMs in GLDAS with the in situ soil moisture from two observation networks at different soil layers: (a) first layer and (b) second layer in the Nagqu network region; (c) first layer, (b) second layer, and (c) third layer in the Maqu network region (Bi et al., 2016)"

Figure 3

Simulated hourly near-surface soil moisture, monthly mean diurnal variations of surface-skin temperature, sensible-heat flux, and latent-heat flux at Amdo, 1998 (Yang et al., 2009)"

Table 2

Error statistic of GLDAS simulated soil moisture during the unfrozen season for the Nagqu network (Chen et al., 2013b)"

Area Depth (cm) LSMs BIAS (m3/m3) RMSE (m3/m3) R 2 No.
Coarse network 0?5 CLM ?0.08 0.09 0.473 1878
Noah ?0.06 0.08 0.483 1878
VIC ?0.02 0.05 0.358 1878
Mosaic ?0.13 0.14 0.491 1878
10?40 CLM 0.01 0.02 0.609 1878
Noah 0.00 0.02 0.585 1878
Dense network 0?5 Noah ?0.07 0.09 0.466 1878
10?40 Noah ?0.04 0.04 0.528 1878

Figure 4

Comparison of observed and simulated soil liquid-water content at six soil depths at the DY station. The black dashed line denotes observation data, the blue line denotes results from the Hydro-SiB2 model, and the red line denotes results from the revised model (Bao et al., 2016)"

Figure 5

Comparison of the diurnal variation of the (a) surface temperature (°C), (b) net radiation (W/m2), (c) sensible-heat flux (W/m2), and (d) soil-heat flux (W/m2). Circles represent the observations, the dashed line represents simulations by the original models, and the solid line represents simulations by revised roughness parameterization (Chen et al., 2010)"

Table 3

Parameterization scheme of roughness"

Formula Reference Abbreviation
Z 0 h = Z 0 m / ( P r R e * ) Sheppard, 1958 S58
Z 0 h = Z 0 m e x p [ - k α ( 8 R e * ) 0.45 P r 0.8 ] Owen and Thomson, 1963 OT63
Z 0 h = Z 0 m e x p ( 2.0 - 2.46 R e * 0.25 ) Brutsaert, 1982 B82
Z 0 h = Z 0 m e x p ( - 0.1 k R e * 0.5 ) Zilitinkevich, 1995 Z95
Z 0 h = Z 0 m e x p ( - k α R e * 0.45 ) Zeng and Dickinson, 1998 Z98
Z 0 h = Z 0 m e x p ( 2 - 1.29 R e * 0.25 ) Kanda et al., 2007 K07
Z 0 h = ( 70 v / u * ) e x p ( - β u * 0.5 T * 0.25 ) Yang et al., 2008 Y08
Z 0 h = Z 0 m e x p - 10 - 0.4 Z 0 m 0.07 k R e * 0.5 Chen and Zhang, 2009 CZ09
Z 0 h = Z 0 m e x p ( - 0.32 R e * 0.5 ) Zeng et al., 2012 Z12
Z 0 h = Z 0 m ' e x p [ - 0.8 1 - G V F 2 k R e * 0.5 ] Zheng et al., 2012 ZH12

Table 4

Parameterization scheme of soil thermal conductivity and hydraulic conductivity"

Parameterization schemes References
λ = K e λ s a t + ( 1 - K e ) λ d r y S r > 1 × 10 - 5 λ d r y S r 1 × 10 - 5 λ s a t = ( λ q q λ o 1 - q ) 1 - θ s a t λ l i q θ s a t T T f ( λ q q λ o 1 - q ) 1 - θ s a t λ l i q θ s a t λ i c e θ s a t - θ l i q T T f Johansen, 1975
λ d r y = ( 0.135 ρ d + 64.7 ) / ( 2700 - 03947 ρ d ) K e = 0.7 l o g S r + 1 T T f l o g ( S r ) T T f

λ = K e λ s a t + 1 - K e λ d r y S r > 1 × 10 - 5 λ d r y S r 1 × 10 - 5 λ s a t = 8.80 % s a n d + 2.92 % d r y % s a n d + % d r y 1 - θ s a t λ l i q θ s a t T T f 8.80 % s a n d + 2.92 % d r y % s a n d + % d r y 1 - θ s a t λ l i q θ s a t λ i c e θ s a t - θ l i q T T f

λ d r y = ( 0.135 ρ d + 64.7 ) / ( 2700 - 03947 ρ d ) K e = l o g S r + 1 T T f S r T T f

Farouki, 1986

λ = K e λ s a t + ( 1 - K e ) λ d r y S r > 1 × 10 - 5 λ d r y S r 1 × 10 - 5 λ s a t = ( λ q q λ o 1 - q ) 1 - θ s a t λ l i q θ s a t T T f ( λ q q λ o 1 - q ) 1 - θ s a t λ l i q θ s a t λ i c e θ s a t - θ l i q T T f

λ d r y = ( 0.135 ρ d + 64.7 ) / ( 2700 - 03947 ρ d ) K e = e x p [ K T 1 - 1 / w ]

Yang et al., 2005

λ = K e λ s a t + ( 1 - K e ) λ d r y S r > 1 × 10 - 5 λ d r y S r 1 × 10 - 5 λ s a t = [ j λ m j j ] 1 - θ s a t λ l i q θ s a t T T f [ j λ m j j ] 1 - θ s a t λ l i q θ s a t λ i c e θ s a t - θ l i q T T f

λ d r y = χ × 10 - η θ s a t K e = K S r / 1 + ( K - 1 ) S r

Cote and Konrad, 2005

λ = K e λ s a t + ( 1 - K e ) λ d r y S r > 1 × 10 - 5 λ d r y S r 1 × 10 - 5 λ s a t = ( λ q q λ o 1 - q ) 1 - θ s a t λ l i q θ s a t T T f ( λ q q λ o 1 - q ) 1 - θ s a t λ l i q θ s a t λ i c e θ s a t - θ l i q T T f

λ d r y = χ × 10 - η θ s a t K e = K S r / 1 + ( K - 1 ) S r

Luo et al., 2009b

λ = K e λ s a t + ( 1 - K e ) λ d r y S r > 1 × 10 - 5 λ d r y S r 1 × 10 - 5 λ s a t = ( λ q q λ S O C V S O C λ o 1 - q - V S O C ) 1 - θ s a t λ l i q θ s a t T T f ( λ q q λ S O C V S O C λ o 1 - q - V S O C ) 1 - θ s a t λ l i q θ s a t λ i c e θ s a t - θ l i q T T f

λ d r y = 1 - V S O C λ m , d r y + V S O C λ S O C , d r y K e = e x p [ K T 1 - 1 / w ]

Chen et al., 2012

λ = K e λ s a t + ( 1 - K e ) λ d r y S r > 1 × 10 - 5 λ d r y S r 1 × 10 - 5 λ s a t = ( λ q q λ S O C V S O C λ o 1 - q - V S O C ) 1 - θ s a t λ l i q θ s a t T T f ( λ q q λ S O C V S O C λ o 1 - q - V S O C ) 1 - θ s a t λ l i q θ s a t λ i c e θ s a t - θ l i q T T f

λ d r y = χ × 10 - η θ s a t K e = K S r / 1 + ( K - 1 ) S r

Pan et al., 2017
Ψ = Ψ S ( θ θ S ) - b K = K S ( θ S ) ( θ θ S ) 2 b + 3 Clapp and Hornberger, 1978
Ψ = 1 α ( S e - 1 m - 1 ) 1 - m K = K S S e 1 2 ( 1 - ( 1 - s e 1 / m ) m ) 2 Van Genuchten, 1980

Figure 6

Variations of daily mean soil temperature and moisture at 5 cm (a, e), 25 cm (b, f), 75 cm (c, g), and 150 cm (d, h). CTL denotes the original model, LAY denotes the revised model of soil vertically heterogeneous, SOM denotes the revised model of soil organic matter, and root 1?3 denotes the different saturated conductivities at the rhizosphere, respectively (Gao et al., 2015)"

Figure 7

Observed and simulated snow depth (m), soil temperature (°C), soil moisture (m3/m3), and soil-ice content at 5 cm at the DY site (Wang et al., 2017)"

Figure 8

Comparisons of monthly (a) averaged downward shortwave radiation; (b) accumulated precipitation; (c) LE, soil temperature, and moisture from depths of (d, f) 5 cm and (e, g) 25 cm; and simulated results from five Noah experiments for the period of November 2009 to November 2010 (Zheng et al., 2016a)"

Albergel C , De Rosnay P , Balsamo G , et al . , 2012. Soil moisture analyses at ECMWF: Evaluation using global ground-based in situ observations. Journal of Hydrometeorology, 13(5): 1442−1460. DOI: 10.1175/JHM-D-11-0107.1.
doi: 10.1175/JHM-D-11-0107.1
Baker IT , Sellers PJ , Denning AS , et al . , 2017. Closing the scale gap between land surface parameterizations and GCMs with a new scheme, SiB3-Bins. Journal of Advances in Modeling Earth Systems, 9(1): 691−711. DOI: 10.1002/2016MS000764.
doi: 10.1002/2016MS000764
Bao HY , Koike T , Yang K , et al . , 2016. Development of an enthalpy-based frozen soil model and its validation in a cold region in China. Journal of Geophysical Research-Atmospheres, 121(10): 5259−5280. DOI: 10.1002/2015JD02 4451.
doi: 10.1002/2015JD02 4451
Bi HY , Ma JW , Zhang WJ , et al . , 2016. Comparison of soil moisture in GLDAS model simulations and in situ observations over the Tibetan Plateau. Journal of Geophysical Research-Atmospheres, 121(6): 2658−2678. DOI: 10.1002/2015JD024131.
doi: 10.1002/2015JD024131
Boike J , Georgi C , Kirilin G , et al . , 2015. Thermal processes of thermokarst lakes in the continuous permafrost zone of northern Siberia observations and modeling (Lena River Delta, Siberia). Biogeosciences, 12(20): 5941−5965. DOI: 10.5194/bg-12-5941-2015.
doi: 10.5194/bg-12-5941-2015
Brutsaert WH, 1982. Evaporation into the Atmosphere: Theory, History, and Applications. D. Reidel Press, Dordrecht Netherlands.
Charney J , Quirk WJ , Chow SH , et al . , 1977. A Comparative study of effects of albedo change on drought in semi-arid regions. Journal of the Atmospheric Sciences, 34(9): 1366−1385. DOI: 10.1175/1520-0469(1977)034 <1366:ACSOTE>2.0.CO;2.
doi: 10.1175/1520-0469(1977)034 <1366:ACSOTE>2.0.CO;2.
Charney JG, 1975. Dynamics of deserts and drought in the Sahel. Quarterly Journal of the Royal Meteorological Society, 101(428): 193−202. DOI: 10.1002/qj.49710142802.
doi: 10.1002/qj.49710142802
Chase TN , Pielke RA , Kittel TGF , et al . , 1996. Sensitivity of a general circulation model to global changes in leaf area index. Journal of Geophysical Research-Atmospheres, 101(D3): 7393−7408. DOI: 10.1029/95JD02417.
doi: 10.1029/95JD02417
Chen BL , Luo SQ , Lv SH , et al . , 2014. Simulation and improvement of soil temperature and moisture at Zoige station in Source Region of the Yellow River during freezing and thawing. Plateau Meteorology, 33(2): 337−345. DOI: 10.7522/j.issn.1000-0534.2013.00085. (in Chinese)
doi: 10.7522/j.issn.1000-0534.2013.00085
Chen F , Zhang Y , 2009. On the coupling strength between the land surface and the atmosphere: From viewpoint of surface exchange coefficients. Geophysical Research Letters, 36: L10404. DOI: 10.1029/2009GL037980.
doi: 10.1029/2009GL037980
Chen H , Nan ZT , Zhao L , et al . , 2015. Noah Modelling of the permafrost distribution and characteristics in the West Kunlun Area, Qinghai-Tibet Plateau, China. Permafrost and Periglacial Processes, 26(2): 160−174. DOI: 10.1002/ppp. 1841.
doi: 10.1002/ppp. 1841
Chen JF , Gao XG , Zheng XQ , et al . , 2019. Simulation of soil freezing and thawing for different groundwater table depths. Vadose Zone Journal, 18(1): 180157. DOI: 10.2136/vzj2018.08.0157.
doi: 10.2136/vzj2018.08.0157
Chen XL , Su ZB , Ma YM , et al . , 2013a. An improvement of roughness height parameterization of the surface energy balance system (SEBS) over the Tibetan Plateau. Journal of Applied Meteorology and Climatology, 52(3): 607−622. DOI: 10.1175/JAMC-D-12-056.1.
doi: 10.1175/JAMC-D-12-056.1
Chen YY , Yang K , He J , et al . , 2011. Improving land surface temperature modeling for dry land of China. Journal of Geophysical Research-Atmospheres, 116: D20104. DOI: 10.1029/2011JD015921.
doi: 10.1029/2011JD015921
Chen YY , Yang K , Qin J , et al . , 2013b. Evaluation of AMSR-E retrievals and GLDAS simulations against observations of a soil moisture network on the central Tibetan Plateau. Journal of Geophysical Research-Atmospheres, 118(10): 4466−4475. DOI: 10.1002/jgrd.50301.
doi: 10.1002/jgrd.50301
Chen YY , Yang K , Tang WJ , et al . , 2012. Parameterizing soil organic carbon's impacts on soil porosity and thermal parameters for Eastern Tibet grasslands. Science China: Earth Sciences, 55(6): 1001−1011. DOI: 10.1007/s11430-012-44 33-0.
doi: 10.1007/s11430-012-44 33-0
Chen YY , Yang K , Zhou DG , et al . , 2010. Improving the Noah land surface model in arid regions with an appropriate parameterization of the thermal roughness length. Journal of Hydrometeorology, 11(4): 995−1006. DOI: 10.1175/2010 JHM1185.1.
doi: 10.1175/2010 JHM1185.1
Clapp RB , Hornberger GM , 1978. Empirical equations for some soil hydraulic properties. Water Resources Research, 14(4): 601−604. DOI: 10.1029/WR014i004p00601.
doi: 10.1029/WR014i004p00601
Collatz GJ , Bounoua L , Los SO , et al . , 2000. A mechanism for the influence of vegetation on the response of the diurnal temperature range to changing climate. Geophysical Research Letters, 27(20): 3381−3384. DOI: 10.1029/1999GL 010947.
doi: 10.1029/1999GL 010947
Cote J , Konrad JM , 2005. Thermal conductivity of base-course materials. Canadian Geotechnical Journal, 42(1): 61−78. DOI: 10.1139/T04-081.
doi: 10.1139/T04-081
D'Odorico P , Porporato A , 2004. Preferential states in soil moisture and climate dynamics. Proceedings of the National Academy of Sciences of the United States of America, 101(24): 8848−8851. DOI: 10.1073/pnas.0401428101.
doi: 10.1073/pnas.0401428101
Dai YJ , Zeng XB , Dickinson RE , et al . , 2003. The Common land model. Bulletin of the American Meteorological Society, 84(8): 1013−1023. DOI: 10.1175/BAMS-84-8-1013.
doi: 10.1175/BAMS-84-8-1013
Dickinson RE, 1995. Land atmosphere interaction. Reviews of Geophysics, 33(S2): 917−922. DOI: 10.1029/95RG00284.
doi: 10.1029/95RG00284
Dickinson RE , Henderson-Sellers A , Rosenzweig C , et al . , 1991. Evapotranspiration models with canopy resistance for use in climate models—A Review. Agricultural and Forest Meteorology, 54(2−4): 373−388. DOI: 10.1016/0168-1923(91)90014-H.
doi: 10.1016/0168-1923(91)90014-H
Entin JK , Robock A , Vinnikov KY , et al . , 2000. Temporal and spatial scales of observed soil moisture variations in the extratropics. Journal of Geophysical Research-Atmospheres, 105(D9): 11865−11877. DOI: 10.1029/2000JD900051.
doi: 10.1029/2000JD900051
Farouki OT, 1981. The thermal properties of soils in cold regions. Cold Regions Science and Technology, 5(1): 67−75. DOI: 10.1016/0165-232X(81)90041-0.
doi: 10.1016/0165-232X(81)90041-0
Franz D , Mammarella I , Boike J , et al . , 2018. Lake-atmosphere heat flux dynamics of a thermokarst lake in Arctic Siberia. Journal of Geophysical Research-Atmospheres, 123: 5222−5239. DOI: 10.1029/2017JD027751.
doi: 10.1029/2017JD027751
Gao YH , Li K , Chen F , et al . , 2015. Assessing and improving Noah-MP land model simulations for the central Tibetan Plateau. Journal of Geophysical Research-Atmospheres, 120(18): 9258−9278. DOI: 10.1002/2015JD023404.
doi: 10.1002/2015JD023404
Gao YH , Xiao LH , Chen DL , et al . , 2017. Quantification of the relative role of land-surface processes and large-scale forcing in dynamic downscaling over the Tibetan Plateau. Climate Dynamics, 48(5−6): 1705−1721. DOI: 10.1007/s00382-016-3168-6.
doi: 10.1007/s00382-016-3168-6
Gao ZQ , Chae N , Kim J , et al . , 2004. Modeling of surface energy partitioning, surface temperature, and soil wetness in the Tibetan prairie using the Simple Biosphere Model 2 (SiB2). Journal of Geophysical Research-Atmospheres, 109(D6): D06102. DOI: 10.1029/2003JD004089.
doi: 10.1029/2003JD004089
Guo DL , Yang MX , 2010. Simulation of soil temperature and moisture in seasonally frozen ground of Central Tibetan Plateau by SHAW model. Plateau Meteorology, 29(6): 1369−1377. (in Chinese)
Hong J , Kim J , 2010. Numerical study of surface energy partitioning on the Tibetan plateau: comparative analysis of two biosphere models. Biogeosciences, 7(2): 557−568. DOI: 10.5194/bg-7-557-2010.
doi: 10.5194/bg-7-557-2010
Immerzeel WW , Van Beek LPH , Bierkens MFP , 2010. Climate change will affect the Asian water towers. Science, 328(5984): 1382−1385. DOI: 10.1126/science.1183188.
doi: 10.1126/science.1183188
Ji P , Yuan X , Liang XZ , 2017. Do lateral flows matter for the hyperresolution land surface modeling? Journal of Geophysical Research- Atmospheres, 122(22): 12077−12092. DOI: 10.1002/2017JD027366.
doi: 10.1002/2017JD027366
Johansen O, 1975. Thermal conductivity of soil. PhD Thesis, University of Trondheim, Norway.
Kanda M , Kanega M , Kawai T , et al . , 2007. Roughness lengths for momentum and heat derived from outdoor urban scale models. Journal of Applied Meteorology and Climatology, 46(7): 1067−1079. DOI: 10.1175/JAM2500.1.
doi: 10.1175/JAM2500.1
Kang SC , Xu YW , You QL , et al . , 2010. Review of climate and cryospheric change in the Tibetan Plateau. Environmental Research Letters, 5(1): 015101. DOI: 10.1088/1748-9326/5/1/015101.
doi: 10.1088/1748-9326/5/1/015101
Koster RD , Dirmeyer PA , Guo ZC , et al . , 2004. Regions of strong coupling between soil moisture and precipitation. Science, 305(5687): 1138−1140. DOI: 10.1126/science. 1100217.
doi: 10.1126/science. 1100217
Krakauer NY , Puma MJ , Cook BI , 2013. Impacts of soil−aquifer heat and water fluxes on simulated global climate. Hydrology and Earth System Sciences, 17(5): 1963−1974. DOI: 10.5194/hess-17-1963-2013.
doi: 10.5194/hess-17-1963-2013
Langer M , Westermann S , Anthony KW , et al . , 2015. Frozen ponds: production and storage of methane during the Arctic winter in a lowland tundra landscape in northern Siberia, Lena River Delta. Biogeosciences, 12: 977−990.
Langer M , Westermann S , Boike J , et al . , 2016. Rapid degradation of permafrost underneath waterbodies in tundra landscapes-Towards a representation of thermokarst in land surface models. Journal of Geophysical Research-Earth Surface, 121(12): 2446−2470. DOI: 10.1002/2016JF003956.
doi: 10.1002/2016JF003956
Lawrence DM , Slater AG , 2008. Incorporating organic soil into a global climate model. Climate Dynamics, 30(2−3): 145−160. DOI: 10.1007/s00382-007-0278-1.
doi: 10.1007/s00382-007-0278-1
Li Q , Sun SF , 2006. Development of frozen soil model. Advances in Earth Science, 21(12): 1339−1349. DOI: 10. 11867/j.issn.1001-8166.2006.12.1339. (in Chinese)
doi: 10. 11867/j.issn.1001-8166.2006.12.1339
Li Q , Sun SF , 2007. Development of the university and simplified soil model coupling heat and water transport. Science China: Earth Sciences, 37(11): 1522−1535. DOI: 10.1360/zd2007-37-11-1522. (in Chinese)
doi: 10.1360/zd2007-37-11-1522
Li Q , Sun SF , Xue YK , 2010. Analyses and development of a hierarchy of frozen soil models for cold region study. Journal of Geophysical Research-Atmospheres 115: D03107. DOI: 10.1029/2009JD012530.
doi: 10.1029/2009JD012530
Li R , Zhao L , Ding YJ , et al . , 2013. Study on soil thermodynamic characteristics at different underlying surface in northern Qinghai-Tibetan Plateau. Acta Energiae Solaris Sinica, 34(6): 1076−1084. (in Chinese)
Li X , Cheng GD , Jin HJ , et al . , 2008. Cryospheric change in China. Global and Planetary Change, 62(3−4): 210−218. DOI: 10.1016/j.gloplacha.2008.02.001.
doi: 10.1016/j.gloplacha.2008.02.001
Li X , Koike T , 2003. Frozen soil parameterization in SiB2 and its validation with GAME-Tibet observations. Cold Regions Science and Technology, 36(1−3): 165−182. DOI: 10.1016/S0165-232X(03)00009-0.
doi: 10.1016/S0165-232X(03)00009-0
Li Y , Sun R , Liu SM , 2015. Vegetation physiological parameter setting in the Simple Biosphere model 2 (SiB2) for alpine meadows in the upper reaches of Heihe river. Science China-Earth Science, 58(5): 755−769. DOI: 10.1007/s11430-014-4909-1.
doi: 10.1007/s11430-014-4909-1
Liu HL , Hu ZY , Cheng S , et al . , 2016. Simulation of the land surface processes over the central Tibetan Plateau based on Noah-LSM and CoLM. Journal of Glaciology and Geocryology, 38(6): 1501−1509. DOI: 10.7522/j.issn.1000-0240.2016.0175.
doi: 10.7522/j.issn.1000-0240.2016.0175
Liu L , Ma YM , Menenti M , et al . , 2019. Evaluation of WRF modeling in relation to different land surface schemes and initial and boundary conditions: a snow event simulation over the Tibetan Plateau. Journal of Geophysical Research-Atmospheres, 124(1): 209−226. DOI: 10.1029/2018JD02 9208.
doi: 10.1029/2018JD02 9208
Luo SQ , Fang XW , Lv SH , et al . , 2017. Improving CLM4.5 simulations of land−atmosphere exchange during freeze−thaw processes on the Tibetan Plateau. Journal of Meteorological Research, 31(5): 916−930. DOI: 10.1007/s13351-017-6063-0.
doi: 10.1007/s13351-017-6063-0
Luo SQ, Lv SH, Zhang Y, 2009a. Development and validation of the frozen soil parameterization scheme in Common Land Model. Cold Regions Science and Technology, 55(1): 130−140. DOI: 10.1016/j.coldregions.2008.07.009.
doi: 10.1016/j.coldregions.2008.07.009
Luo SQ , Lv SH , Zhang Y , et al . , 2009b. Soil thermal conductivity parameterization establishment and application in numerical model of central Tibetan Plateau. Chinese Journal of Geophysics, 52(4): 919−928. DOI: 10.3969/j.issn.001-5733.2009.04.008.
doi: 10.3969/j.issn.001-5733.2009.04.008
Ma HY , Xiao H , Mechoso CR , et al . , 2013. Sensitivity of global tropical climate to land surface processes: mean state and inter annual variability. Journal of Climate, 26(5): 1818−1837. DOI: 10.1175/JCLI-D-12-00142.1.
doi: 10.1175/JCLI-D-12-00142.1
Ma Q , Liu X , Li WP , et al . , 2014. Simulation of thermal and hydraulic properties affected by organic and gravel soil over the Tibetan Plateau during summer. Chinese Journal of Atmospheric Sciences, 38(2): 337−351. DOI: 10.3878/j.issn.1006-9895.2013.13119.
doi: 10.3878/j.issn.1006-9895.2013.13119
Ma SB , Zhou LB , 2017. Characteristics of land−air exchange parameters over grassland in southeast Tibet. Journal of Hydrometeorology, 18(8): 2249−2264. DOI: 10.1175/JHM-D-16-0084.1.
doi: 10.1175/JHM-D-16-0084.1
Ma YM , Kang SC , Zhu LP , et al . , 2008. Tibetan observation and research platform atmosphere-land interaction over a heterogeneous landscape. Bulletin of the American Meteorological Society, 89(10): 1487−1492. DOI: 10.1175/2008 BAMS2545.1.
doi: 10.1175/2008 BAMS2545.1
Ma YM , Ma WQ , Zhong L , et al . , 2017. Monitoring and modeling the Tibetan Plateau's climate system and its impact on East Asia. Scientific Reports, 7: 44574. DOI: 10.1038/srep44574.
doi: 10.1038/srep44574
Ma YM , Wang Y , Wu R , et al . , 2009b. Recent advances on the study of atmosphere-land interaction observations on the Tibetan Plateau. Hydrology and Earth System Sciences, 13(7): 1103−1111. DOI: 10.5194/hess-13-1103-2009.
doi: 10.5194/hess-13-1103-2009
Ma YM , Yao TD , Hu ZY , et al . , 2009a. The cooperative study on energy and water cycle over the Tibetan Plateau. Advances in Earth Science, 24(11): 1280−1284. (in Chinese)
Ma YM , Yao TD , Wang JM , 2006. Experimental study of energy and water cycle in Tibetan Plateau-The progress introduction on the study of GAME-Tibet and CAMP-Tibet. Plateau Meteorology, 25(2): 344−351. (in Chinese)
Niu GY , Yang ZL , 2006. Effects of frozen soil on snowmelt runoff and soil water storage at a continental scale. Journal of Hydrometeorology, 7(5): 937−952. DOI: 10.1175/JHM 538.1.
doi: 10.1175/JHM 538.1
Niu GY , Yang ZL , 2007. An observation-based formulation of snow cover fraction and its evaluation over large north American river basins. Journal Geophysical Research-Atmospheres, 112(D21): D21101. DOI: 10.1029/2007JD00 8674.
doi: 10.1029/2007JD00 8674
Niu GY , Yang ZL , Mitchell KE, et al . , 2011. The community Noah land surface model with multiparameterization options (Noah-MP): 1. Model description and evaluation with local-scale measurements. Journal Geophysical Research-Atmospheres, 116: D12109. DOI: 10.1029/2010JD015139.
doi: 10.1029/2010JD015139
Owen PR , Thomson WR , 1963. Heat transfer across rough surfaces. Journal of Fluid Mechanics, 15(3): 321−334. DOI: 10.1017/S0022112063000288.
doi: 10.1017/S0022112063000288
Pan BT , Li JJ , 1996. Qinghai-Tibetan Plateau: A driver and amplifier of the global climate change III. The effects of the uplift of Qinghai-Tibetan Plateau on Climatic Changes. Journal of Lanzhou University (Natural Sciences), 32(1): 108−115. (in Chinese)
Pan YJ , Lv SH , Li SS , et al . , 2017. Simulating the role of gravel in freeze-thaw process on the Qinghai-Tibet Plateau. Theoretical and Applied Climatology, 127(3−4): 1011−1022. DOI: 10.1007/s00704-015-1684-7.
doi: 10.1007/s00704-015-1684-7
Peters-Lidard CD , Blackburn E , Liang X , et al . , 1998. The effect of soil thermal conductivity parameterization on surface energy fluxes and temperatures. Journal of the Atmospheric Sciences, 55(7): 1209−1224. DOI: 10.1175/1520-0469(1998)055<1209:TEOSTC>2.0.CO;2.
doi: 10.1175/1520-0469(1998)055<1209:TEOSTC>2.0.CO;2.
Peylin P , Polcher J , Bonan G , et al . , 1997. Comparison of two complex land surface schemes coupled to the National Center for Atmospheric Research general circulation model. Journal of Geophysical Research-Atmospheres, 102(D16): 19413−19431. DOI: 10.1029/97JD00489.
doi: 10.1029/97JD00489
Qiu J, 2008. The third pole. Nature, 454(7203): 393−396. DOI: 10.1038/454393a.
doi: 10.1038/454393a
Ren XQ , Sun SF , Chen W , et al . , 2013. A review of researches on the lake numerical modeling. Advances in Earth Science, 28(3): 347−356. DOI: 10.11867/j.issn.1001-8166. 2013.03.0347. (in Chinese)
doi: 10.11867/j.issn.1001-8166. 2013.03.0347
Sellers PJ , Dickinson RE , Randall DA , et al . , 1997. Modeling the exchanges of energy, water, and carbon between continents and the atmosphere. Science, 275(5299): 502−509. DOI: 10.1126/science.275.5299.502.
doi: 10.1126/science.275.5299.502
Seneviratne SI, Corti T , Davin EL , et al . , 2010. Investigation soil moisture-climate interactions in a changing climate: A review. Earth Science Reviews, 99(3−4): 125−161. DOI: 10. 1016/j.earscirev.2010.02.004.
doi: 10. 1016/j.earscirev.2010.02.004
Sheppard PA, 1958. Transfer across the earth's surface and through the air above. Quarterly Journal of the Royal Meteorological Society, 84(361): 205−224. DOI: 10.1002/qj.49 708436102.
doi: 10.1002/qj.49 708436102
Shukla J , Mintz Y , 1982. Influence of land surface evapotranspiration on the earth's climate. Science, 215(4539): 1498−1501. DOI: 10.1126/science.215.4539.1498.
doi: 10.1126/science.215.4539.1498
Sud YC , Shukla J , Mintz Y , 1988. Influence of land surface roughness on atmospheric circulation and precipitation- A sensitivity study with a general circulation model. Journal of Applied Meteorology, 27(9): 1036−1054. DOI: 10.1175/1520-0450(1988)027<1036:IOLSRO>2.0.C;2.
doi: 10.1175/1520-0450(1988)027<1036:IOLSRO>2.0.C;2.
Sud YC, Smith WE, 1985a. Influence of local land surface processes on the Indian monsoon-A Numerical study. Journal of Climate and Applied Meteorology, 24(10): 1015−1036. DOI: 10.1175/1520-0450(1985)024<1015:IOLLSP>2.0.CO;2.
doi: 10.1175/1520-0450(1985)024<1015:IOLLSP>2.0.CO;2.
Sud YC, Smith WE, 1985b. The Influence of surface roughness of deserts on the July circulation (A numerical study). Boundary-Layer Meteorology, 33(1): 15−49. DOI: 10.1007/BF00137034.
doi: 10.1007/BF00137034
Sun SB , Chen BZ , Chen J , et al . , 2016a. Comparison of remotely-sensed and modeled soil moisture using CLM4.0 with in situ measurements in the central Tibetan Plateau area. Cold Regions Science and Technology, 129: 31−44. DOI: 10.1016/j.coldregions.2016.06.005.
doi: 10.1016/j.coldregions.2016.06.005
Sun SB , Chen BZ , Ge MY , et al . , 2016b. Improving soil organic carbon parameterization of land surface model for cold regions in the Northeastern Tibetan Plateau, China. Ecological Modelling, 330: 1−15. DOI: 10.1016/j.ecolmodel.2016.03.014.
doi: 10.1016/j.ecolmodel.2016.03.014
Sun SF, 2005. Parameterization Study of Physical and Biochemical Mechanism in Land Surface Process. Beijing: China Meteorology Press. (in Chinese)
Swenson SC, Lawrence DM, 2012b. A new fractional snow-covered area parameterization for the community land model and its effect on the surface energy balance. Journal of Geophysical Research-Atmospheres, 117: D21107. DOI: 10.1029/2012JD018178.
doi: 10.1029/2012JD018178
Swenson SC, Lawrence DM, Lee H, 2012a. Improved simulation of the terrestrial hydrological cycle in permafrost regions by the Community Land Model. Journal of Advances in Modeling Earth Systems, 4: M08002. DOI: 10.1029/2012MS000165.
doi: 10.1029/2012MS000165
Takayabu I , Takata K , Yamazali T , et al . , 2001. Comparison of the four land surface models driven by a common forcing data prepared from GAME/Tibet POP'97 products-Snow accumulation and soil freezing processes. Journal of the Meteorological Society of Japan, 79(1B): 535−554. DOI: 10.2151/jmsj.79.535.
doi: 10.2151/jmsj.79.535
Van der Velde R , Su Z , Ek M , et al . , 2009. Influence of thermodynamic soil and vegetation parameterizations on the simulation of soil temperature states and surface fluxes by the Noah LSM over a Tibetan plateau site. Hydrology and Earth System Sciences, 13(6): 759−777. DOI: 10.5194/hess-13-759-2009.
doi: 10.5194/hess-13-759-2009
Van Genuchten MT, 1980. A closed-form equation for predicting the hydraulic conductivity of unsaturated soils. Soil Science Society of America Journal, 44(5): 892−898. DOI: 10.2136/sssaj1980.03615995004400050002x.
doi: 10.2136/sssaj1980.03615995004400050002x
Wang CH , Yang K , 2018. A new scheme for considering soil water-heat transport coupling based on community land model: model description and preliminary validation. Journal of Advances in Modeling Earth Systems, 10(4): 927−950. DOI: 10.1002/2017MS001148.
doi: 10.1002/2017MS001148
Wang L , Zhou J , Qin J , et al . , 2017. Development of a land surface model with coupled snow and frozen soil physics. Water Resources Research, 53(6): 5085−5103. DOI: 10.1002/2017WR020451.
doi: 10.1002/2017WR020451
Wang XJ , Pang GJ , Yang MX , 2018. Precipitation over the Tibetan Plateau during recent decades: a review based on observations and simulations. International Journal of Climatology, 38(3): 1116−1131. DOI: 10.1002/joc.5246.
doi: 10.1002/joc.5246
Wang XJ , Pang GJ , Yang MX , et al . , 2016. Effects of modified soil water-heat physics on RegCM4 simulations of climate over the Tibetan Plateau. Journal of Geophysical Research-Atmospheres, 121(12): 6692−6712. DOI: 10.1002/2015JD 024407.
doi: 10.1002/2015JD 024407
Wang XJ , Yang MX , Pang GJ , et al . , 2015. Simulation and improvement of land surface processes in Nameqie, Central Tibetan Plateau, using the Community Land Model (CLM3.5). Environment Earth Sciences, 73(11): 7343−7357. DOI: 10.1007/s12665-014-3911-4.
doi: 10.1007/s12665-014-3911-4
Wood EF, 1991. Land Surface−Atmosphere Interactions for Climate Modeling. Dordrecht: Kluwer Academic Publishers, pp. 85−126, 155−178.
Wu GX , Duan AM , Liu YM , et al . , 2015. Tibetan Plateau climate dynamics: recent research progress and outlook. National Science Review, 2(1): 100−116. DOI: 10.1093/nsr/nwu045.
doi: 10.1093/nsr/nwu045
Wu GX , He B , Liu YM , et al . , 2016. Recent progresses on dynamics of the Tibetan Plateau and Asian Summer Monsoon. Chinese Journal of Atmospheric Sciences, 40(1): 22−32. DOI: 10.3878/j.issn.1006-9895.1504.15129.
doi: 10.3878/j.issn.1006-9895.1504.15129
Xia K , Luo Y , Li WP , 2011. Simulation of freezing and melting of soil on the northeast Tibetan Plateau. Chinese Science Bulletin, 56(20): 2145−2155. DOI: 10.1007/s11434-011-4542-8.
doi: 10.1007/s11434-011-4542-8
Xiao Y , Zhao L , Dai YJ , et al . , 2013. Representing permafrost properties in CoLM for the Qinghai-Xizang (Tibetan) Plateau. Cold Regions Science and Technology, 87: 68−77. DOI: 10.1016/j.coldregions.2012.12.004.
doi: 10.1016/j.coldregions.2012.12.004
Xie ZP , Hu ZY , Xie ZH , et al . , 2018. Impact of the snow cover scheme on snow distribution and energy budget modeling over the Tibetan Plateau. Theoretical and Applied Climatology, 131(3−4): 951−965. DOI: 10.1007/s00704-016-2020-6.
doi: 10.1007/s00704-016-2020-6
Xu XD , Chen LS , 2006. Advances of the study on Tibetan Plateau experiment of atmospheric sciences. Journal of Applied Meteorological Science, 17(6): 756−772. (in Chinese)
Xu XD , Lu CG , Shi XH , et al . , 2008a. World water tower: An atmospheric perspective. Geophysical Research Letters, 35(20): L20815. DOI: 10.1029/2008GL035867.
doi: 10.1029/2008GL035867
Xu XD , Zhang RH , Koike T , et al . , 2008b. A new integrated observational system over the Tibetan Plateau. Bulletin of the American Meteorological Society, 89(10): 1492−1496. DOI: 10.1175/2008BAMS2557.1.
doi: 10.1175/2008BAMS2557.1
Xue YK , Shukla J , 1993. The Influence of land surface properties on Sahel Climate. Part I: Desertification. Journal of Climate, 6(12): 2232−2245. DOI: 10.1175/1520-0442(1993)006<2232:TIOLSP>2.0.CO;2.
doi: 10.1175/1520-0442(1993)006<2232:TIOLSP>2.0.CO;2.
Xue YK , Shukla J , 1996. The Influence of land surface properties on Sahel Climate. Part II: Afforestation. Journal of Climate, 9(12): 3260−3275. DOI: 10.1175/1520-0442(1996)009<3260:TIOLSP>2.0.CO;2.
doi: 10.1175/1520-0442(1996)009<3260:TIOLSP>2.0.CO;2.
Yang K , Chen YY , Qin J , 2009. Some practical notes on the land surface modeling in the Tibetan Plateau. Hydrology and Earth System Sciences, 13(5): 687−701. DOI: 10.5194/hess-13-687-2009.
doi: 10.5194/hess-13-687-2009
Yang K , Koike T , Ishikawa H , et al . , 2008. Turbulent flux transfer over bare-soil surfaces: Characteristics and parameterization. Journal of Applied Meteorology and Climatology, 47(1): 276−290. DOI: 10.1175/2007JAMC1547.1.
doi: 10.1175/2007JAMC1547.1
Yang K , Koike T , Ye BS , et al . , 2005. Inverse analysis of the role of soil vertical heterogeneity in controlling surface soil state and energy partition. Journal of Geophysical Research-Atmospheres, 110(D8): D08101. DOI: 10.1029/2004JD005500.
doi: 10.1029/2004JD005500
Yang K , Qin J , Zhao L , et al . , 2013. A multiscale soil moisture and freeze-thaw monitoring network on the third pole. Bulletin of the American Meteorological Society, 94(12): 1907−1916. DOI: 10.1175/BAMS-D-12-00203.1.
doi: 10.1175/BAMS-D-12-00203.1
Yang K , Rasmy M , Rauniyar S , et al . , 2007. Initial CEOP-based review of the prediction skill of operational general circulation models and land surface models. Journal of the Meteorological Society of Japan, 85A: 99−116. DOI: 10.2151/jmsj.85A.99.
doi: 10.2151/jmsj.85A.99
Yang K , Wang CH , Li SY , 2018. Improved simulation of frozen-thawing process in land surface model (CLM4.5). Journal of Geophysical Research-Atmospheres, 123(23): 13238−13258. DOI: 10.1029/2017JD028260.
doi: 10.1029/2017JD028260
Yang K , Wu H , Qin J , et al . , 2014. Recent climate changes over the Tibetan Plateau and their impacts on energy and water cycle: A review. Global and Planetary Change, 112: 79−91. DOI: 10.1016/j.gloplacha.2013.12.001.
doi: 10.1016/j.gloplacha.2013.12.001
Yang MX , Wang XJ , Pang GJ , et al . , 2019. The Tibetan Plateau cryosphere: Observations and model simulations for current status and recent changes. Earth-Sciences Reviews, 190: 353−369. DOI: 10.1016/j.earscirev.2018.12.018.
doi: 10.1016/j.earscirev.2018.12.018
Yang MX , Yao TD , Gou XH , et al . , 2007a. The spatially heterogeneous distribution of precipitation of the Anduo area, Tibetan Plateau, in summer 1998. Hydrological Sciences Journal-Journal Des Sciences Hydeologiques, 52(4): 645−653. DOI: 10.1623/hysj.52.4.645
doi: 10.1623/hysj.52.4.645
Yang MX , Yao TD , Gou XH , et al . , 2007b. Water recycling between the land surface and atmosphere on the northern Tibetan Plateau-A case study at flat observation sites. Arctic, Antarctic and Alpine Research, 39(4): 694−698. DOI: 10.1657/1523-0430(07-509)[YANG]2.0.CO;2.
doi: 10.1657/1523-0430(07-509)[YANG]2.0.CO;2.
Yao TD , Thompson L , Yang W , et al . , 2012. Different glacier status with atmospheric circulations in Tibetan Plateau and surroundings. Nature Climate Change, 2(9): 663−667. DOI: 10.1038/NCLIMATE1580.
doi: 10.1038/NCLIMATE1580
Yao TD , Wu FY , Ding L , et al . , 2015. Multispherical interactions and their effects on the Tibetan Plateau's earth system: a review of the recent researches. National Science Review, 2(4): 468−488. DOI: 10.1093/nsr/nwv070.
doi: 10.1093/nsr/nwv070
Ye DZ , Gao YX , 1979. The Meteorology of the Qinghai-Xizang (Tibet) Plateau. Beijing: Science Press. (in Chinese)
Ye DZ , Zeng QC , Guo YF , 1991. Current Research in Climate. Beijing: Meteorological Press. (in Chinese)
You QL , Min JZ , Zhang W , et al . , 2015. Comparison of multiple datasets with gridded precipitation observations over the Tibetan Plateau. Climate Dynamics, 45(3−4): 791−806. DOI: 10.1007/s00382-014-2310-6.
doi: 10.1007/s00382-014-2310-6
Yuan X , Ji P , Wang LY , et al . , 2018. High-resolution land surface modeling of hydrological changes over the sanjiangyuan region in the eastern Tibetan Plateau: 1. model development and evaluation. Journal of Advances in Modeling Earth Systems, 10(11): 2806−2828. DOI: 10.1029/2018MS 001412.
doi: 10.1029/2018MS 001412
Zeng XB , Dickinson RE , 1998. Effect of surface sublayer on surface skin temperature and fluxes. Journal of Climate, 11(4): 537−550. DOI: 10.1175/1520-0442(1998)011<0537:EOSSOS>2.0.CO;2.
doi: 10.1175/1520-0442(1998)011<0537:EOSSOS>2.0.CO;2.
Zeng XB , Wang Z , Wang AH , 2012. Surface skin temperature and the interplay between sensible and ground heat fluxes over arid regions. Journal of Hydrometeorology, 13(4): 1359−1370. DOI: 10.1175/JHM-D-11-0117.1.
doi: 10.1175/JHM-D-11-0117.1
Zhan CS , Ning LK , Zhou J , et al . , 2018. A review on the fully coupled atmosphere-hydrology simulations. Acta Geographica Sinica, 73(5): 893−905. DOI: 10.11821/dlxb20180 5009.
doi: 10.11821/dlxb20180 5009
Zhang G , Chen F , Gan YJ , 2016. Assessing uncertainties in the Noah-MP ensemble simulations of a cropland site during the Tibet Joint International Cooperation program field campaign. Journal of Geophysical Research-Atmospheres, 121(16): 9576−9596. DOI: 10.1002/2016JD024928.
doi: 10.1002/2016JD024928
Zhang RH , Koike T , Xu XD , et al . , 2012. A China-Japan cooperative JICA atmospheric observing network over the Tibetan Plateau (JICA/Tibet Project): An overviews. Journal of the Meteorological Society of Japan, 90C: 1−16. DOI: 10. 2151/jmsj.2012-C01.
doi: 10. 2151/jmsj.2012-C01
Zhang X , Sun SF , Xue YK , 2006. Development and testing of a frozen soil parameterization for cold region studies. Journal of Hydrometeorology, 8(4): 690−701. DOI: 10.1175/JH M605.1.
doi: 10.1175/JH M605.1
Zhao H , Zeng YJ , Lv SN , et al . , 2018. Analysis of soil hydraulic and thermal properties for land surface modeling over the Tibetan Plateau. Earth System Science Data, 10(2): 1031−1061. DOI: 10.5194/essd-10-1031-2018.
doi: 10.5194/essd-10-1031-2018
Zheng DH , van der Velde R , Su ZB , et al . , 2014. Assessment of roughness length schemes implemented within the Noah land surface model for high-altitude regions. Journal of Hydrometeorology, 15(3): 921−937. DOI: 10.1175/JHM-D-13-0102.1.
doi: 10.1175/JHM-D-13-0102.1
Zheng DH , van der Velde R , Su ZB , et al . , 2015a. Under-canopy turbulence and root water uptake of a Tibetan meadow ecosystem modeled by Noah-MP. Water Resources Research, 51(7): 5735−5755. DOI: 10.1002/2015WR017115.
doi: 10.1002/2015WR017115
Zheng DH , van der Velde R , Su ZB , et al . , 2015b. Augmentations to the Noah model physics for application to the Yellow River Source Area. Part I: soil water flow. Journal of Hydrometeorology, 16(6): 2659−2676. DOI: 10.1175/JHM-D-14-0198.1.
doi: 10.1175/JHM-D-14-0198.1
Zheng DH , van der Velde R , Su ZB , et al . , 2015c. Augmentations to the Noah model physics for application to the Yellow River Source Area. Part II: turbulent heat fluxes and soil heat transport. Journal of Hydrometeorology, 16(6): 2677−2694. DOI: 10.1175/JHM-D-14-0199.1.
doi: 10.1175/JHM-D-14-0199.1
Zheng DH , van der Velde R , Su ZB , et al . , 2016a. Impacts of Noah model physics on catchment-scale runoff simulations. Journal of Geophysical Research-Atmospheres, 121(2): 807−832. DOI: 10.1002/2015JD023695.
doi: 10.1002/2015JD023695
Zheng DH , van der Velde R , Su ZB , et al . , 2016b. Assessment of Noah land surface model with various runoff parameterizations over a Tibetan River. Journal of Geophysical Research-Atmospheres, 122(3): 1488−1504. DOI: 10.1002/2016JD025572.
doi: 10.1002/2016JD025572
Zheng DH , van der Velde R , Su ZB , et al . , 2017. Evaluation of Noah Frozen Soil Parameterization for Application to a Tibetan Meadow Ecosystem. Journal of Hydrometeorology, 18(6): 1749−1763. DOI: 10.1175/JHM-D-16-0199.1.
doi: 10.1175/JHM-D-16-0199.1
Zheng WZ , Wei HL , Wang Z , et al . , 2012. Improvement of daytime land surface skin temperature over arid regions in the NCEP GFS model and its impact on satellite data assimilation. Journal of Geophysical Research-Atmospheres, 117, D06117. DOI: 10.1029/2011JD015901.
doi: 10.1029/2011JD015901
Zhou LM , Tucker CJ , Kaufmann RK , et al . , 2001. Variations in northern vegetation activity inferred from satellite data of vegetation index during 1981 to 1999. Journal of Geophysical Research-Atmospheres, 106(D17): 20069−20083. DOI: 10.1029/2000JD000115.
doi: 10.1029/2000JD000115
Zhou YL , Sun XM , Zhu ZL , et al . , 2007. Comparative research on four typical surface roughness length calculation methods. Geographical Research, 26(5): 887−896. DOI: 10.118 21/yj2007050004.(in Chinese)
doi: 10.118 21/yj2007050004.(in Chinese)
Zhu ZC , Piao SL , Xu L , et al . , 2017. Attribution of seasonal leaf area index trends in the northern latitudes with "optimally" integrated ecosystem models. Global Change Biology, 23(11): 4798−4813. DOI: 10.1111/gcb.13723.
doi: 10.1111/gcb.13723
Zilitinkevich SS, 1995. Non-local turbulent transport: Pollution dispersion aspects of coherent structure of convective flows, Air Pollution III, Vol. I, Air Theory and Simulation. In: Power H, Moussiopoulos N, Brebbia CA (eds.). Boston: Computational Mechanics Publications, pp: 53−60.
Zou DF , Zhao L , Sheng Y , et al . , 2017. A new map of permafrost distribution on the Tibetan Plateau. The Cryosphere, 11(6): 2527−2542. DOI: 10.5194/tc-11-2527-2017.
doi: 10.5194/tc-11-2527-2017
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[2] YinHuan Ao,ShiHua Lyu,ZhaoGuo Li,LiJuan Wen,Lin Zhao. Numerical simulation of the climate effect of high-altitude lakes on the Tibetan Plateau [J]. Sciences in Cold and Arid Regions, 2018, 10(5): 379-391.
[3] HeWen Niu, XiaoFei Shi, Gang Li, JunHua Yang, ShiJin Wang. Characteristics of total suspended particulates in the atmosphere of Yulong Snow Mountain, southwestern China [J]. Sciences in Cold and Arid Regions, 2018, 10(3): 207-218.
[4] ZhenMing Wu, Lin Zhao, Lin Liu, Rui Zhu, ZeShen Gao, YongPing Qiao, LiMing Tian, HuaYun Zhou, MeiZhen Xie. Surface-deformation monitoring in the permafrost regions over the Tibetan Plateau, using Sentinel-1 data [J]. Sciences in Cold and Arid Regions, 2018, 10(2): 114-125.
[5] BenLi Liu, JianJun Qu, ShiChang Kang, Bing Liu. Climate change inferred from aeolian sediments in a lake shore environment in the central Tibetan Plateau during recent centuries [J]. Sciences in Cold and Arid Regions, 2018, 10(2): 134-144.
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[11] ZhiCai Li, Yan Song, Wei Zhang, Jing Zhang, ZiNiu Xiao. Interdecadal correlation of solar activity with Tibetan Plateau snow depth and winter atmospheric circulation in East Asia [J]. Sciences in Cold and Arid Regions, 2016, 8(6): 524-535.
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[13] MaoShan Li, ZhongBo Su, YaoMing Ma, XueLong Chen, Lang Zhang, ZeYong Hu. Characteristics of land-atmosphere energy and turbulent fluxes over the plateau steppe in central Tibetan Plateau [J]. Sciences in Cold and Arid Regions, 2016, 8(2): 103-115.
[14] JianZhong Xu, ShiChang Kang, ShuGui Hou, QiangGong Zhang, Jie Huang, CunDe Xiao, JiaWen Ren, DaHe Qin. Characterization of contemporary aeolian dust deposition on mountain glaciers of western China [J]. Sciences in Cold and Arid Regions, 2016, 8(1): 9-21.
[15] ShengJie Wang, WenYing He, HongBin Chen, JianChun Bian, ZhenHui Wang. Statistics of cloud heights over the Tibetan Plateau and its surrounding region derived from CloudSat data [J]. Sciences in Cold and Arid Regions, 2016, 8(1): 72-81.
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