Abstract
Snow is a key variable that influences hydrological and climatic cycles. Land surface models employing snow physics-modules can simulate the snow accumulation and ablation processes. However, there are still uncertainties in modeling snow resources over complex terrain such as mountains. This study employed the National Center for Atmospheric Research’s Weather Research and Forecasting (WRF) model coupled with the Noah-Multiparameterization (Noah-MP) land surface model to run one-year simulations to assess its ability to simulate snow across the Tianshan Mountains. Six tests were conducted based on different reanalysis forcing datasets and different land surface properties. The results indicated that the snow dynamics were reproduced in a snow hydrological year by the WRF/Noah-MP model for all of the tests. The model produced a low bias in snow depth and snow water equivalent (SWE) regardless of the forcing datasets. Additionally, the underestimation of snow depth and SWE could be relatively alleviated by modifying the land cover and vegetation parameters. However, no significant improvement in accuracy was found in the date of snow depth maximum and melt rate. The best performance was achieved using ERA5 with modified land cover and vegetation parameters (mean bias = -4.03 mm and -1.441 mm for snow depth and SWE, respectively). This study highlights the importance of selecting forcing data for snow simulation over the Tianshan Mountains.
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References
Aalstad K, Westermann S, Schuler TV, et al. (2018) Ensemble-based assimilation of fractional snow-covered area satellite retrievals to estimate the snow distribution at Arctic sites. The Cryosphere 12(1): 247–270. https://doi.org/10.5194/tc-12-247-2018
Aizen VB, Aizen EM, Melack JM (1995) Climate, Snow Cover, Glaciers, and Runoff in the Tien Shan, Central Asia. J Am Water Resour As 31(6): 1113–1129. https://doi.org/10.1111/j.1752-1688.1995.tb03426.x
Alves M, Nadeau DF, Music B, et al. (2020) On the performance of the Canadian Land Surface Scheme driven by the ERA5 reanalysis over the Canadian boreal forest. J Hydrometeorol 21(6): 13831404. https://doi.org/10.1175/JHM-D-19-0172.1
Anderson EA (1976) A point energy and mass balance model of a snow cover. Stanford University.
Barnett TP, Adam JC, Lettenmaier DP (2005) Potential impacts of a warming climate on water availability in snow-dominated regions. Nature 438(17): 303–309. https://doi.org/10.1038/nature04141
Cai X, Yang Z, Xia Y, et al. (2014) Assessment of simulated water balance from Noah, Noah-MP, CLM, and VIC over CONUS using the NLDAS test bed. J Geophys Res Atmos 119(13): 751–770. https://doi.org/10.1038/175238c0
Cao Q, Wu J, Yu D, et al. (2019) The biophysical effects of the vegetation restoration program on regional climate metrics in the Loess Plateau, China. Agr Forest Meteorol 268(19): 169–180. https://doi.org/10.1016/j.agrformet.2019.01.022
Carrera ML, Bélair S, Fortin V, et al. (2010) Evaluation of snowpack simulations over the canadian rockies with an experimental hydrometeorological modeling system. J Hydrometeorol 11(5): 1123–1140. https://doi.org/10.1175/2010JHM1274.1
Chen F, Barlage M, Tewari M, et al. (2014) Modeling seasonal snowpack evolution in the complex terrain and forested colorado headwaters region: A model intercomparison study. J Geophys Res 119(22): 13795–13819. https://doi.org/10.1002/2014JD022167
Chen F, Dudhia J (2001) Coupling an Advanced Land Surface-Hydrology Model with thePenn State-NCAR MM5 Modeling System. Part I: Model Implementation and Sensitivity. Mon Weather Rev 129: 569–585. https://doi.org/10.1175/1520-0493(2001)129<0587:CAALSH>2.0.CO;2
Chen L, Dirmeyer PA (2017) Impacts of land-use/land-cover change on afternoon precipitation over North America. J Climate 30(6). https://doi.org/10.1175/JCLI-D-16-0589.1
Chen S, Hamdi R, Ochege FU, et al. (2019) Added Value of a Dynamical Downscaling Approach for Simulating Precipitation and Temperature Over Tianshan Mountains Area, Central Asia. J Geophys Res Atmos 124(21): 11051–11069. https://doi.org/10.1029/2019JD031016
Dai L, Che T, Wang J, et al. (2012) ESnow depth and snow water equivalent estimation from AMSR-E data based on a priori snow characteristics in Xinjiang, China. Remote Sens Environ 127: 14–29. https://doi.org/10.1016/j.rse.2011.08.029
Dee DP, Uppala SM, Simmons AJ, et al. (2011) The ERA-Interim reanalysis: Configuration and performance of the data assimilation system. Q J Roy Meteor Soc 137(656): 553–597. https://doi.org/10.1002/qj.828
Dudhia J (1989) Numerical Study of Convection Observed during the Winter Monsoon Experiment Using a Mesoscale Two-Dimensional Model. J Atmos Sci 46(20): 3077–3107. https://doi.org/10.1175/1520-0469(1989)046<3077:NSOCOD>2.0.CO;2
Dutra E, Kotlarski S, Viterbo P, et al. (2011) Snow cover sensitivity to horizontal resolution, parameterizations, and atmospheric forcing in a land surface model. J Geophys Res Atmos 116(21): 1–16. https://doi.org/10.1029/2011JD016061
ESA (2017) ESA. Land Cover CCI Product User Guide Version 2. Report, Technical, CCI-LC-PUGV2. http://maps.elie.ucl.ac.be/CCI/viewer/ (Accessed on 16 October 2017)
Essery R, Bunting P, Hardy J, et al. (2008) Radiative transfer modeling of a coniferous canopy characterized by airborne remote sensing. J Hydrometeorol 9(2): 228–241. https://doi.org/10.1175/2007JHM870.1
Fang H, Baret F, Plummer S, et al. (2019) An Overview of Global Leaf Area Index (LAI): Methods, Products, Validation, and Applications. Rev Geophys 57(3): 739–799. https://doi.org/10.1029/2018RG000608
Farinotti D, Longuevergne L, Moholdt, et al. (2015) Substantial glacier mass loss in the Tien Shan over the past 50 years. Nat Geosci 8(9): 716–722. https://doi.org/10.1038/ngeo2513
Fernández-González S, Valero F, Sánchez JL, et al. (2015) Numerical simulations of snowfall events: Sensitivity analysis of physical parameterizations. J Geophys Res 120(19): 10130–10148. https://doi.org/10.1002/2015JD023793
GanY, Liang XZ, Duan Q, et al. (2019) Assessment and Reduction of the Physical Parameterization Uncertainty for Noah-MP Land Surface Model. Water Resour Res 55(7): 5518–5538. https://doi.org/10.1029/2019WR024814
Gao Y, Chen F, Barlage M, et al. (2008) Enhancement of land surface information and its impact on atmospheric modeling in the Heihe River Basin, northwest China. J Geophys Res Atmos 113(20): 1–19. https://doi.org/10.1029/2008JD010359
Gao Y, Xiao L, Chen D, et al. (2017) Quantification of the relative role of land-surface processes and large-scale forcing in dynamic downscaling over the Tibetan Plateau. Clim Dynam 48(5–6): 1705–1721. https://doi.org/10.1007/s00382-016-3168-6
Gelfan AN, Pomeroy JW, Kuchment LS (2004) Modeling forest cover influences on snow accumulation, sublimation, and melt. J Hydrometeorol 5(5): 785–803. https://doi.org/10.1175/1525-7541(2004)005<0785:MFCIOS>2.0.CO;2
Guo L, Li L (2015) Variation of the proportion of precipitation occurring as snow in the Tian Shan Mountains, China. Int J Climatol 35 (7): 1379–1393. https://doi.org/10.1002/joc.4063
Henderson GR, Peings Y, Furtado JC, et al. (2018) Snow-atmosphere coupling in the Northern Hemisphere. Nat Clim Change 8(November): 954–963. https://doi.org/10.1038/s41558-018-0295-6
Hersbach H, Bell B, Berrisford P, et al. (2020) The ERA5 global reanalysis. Q J Roy Meteor Soc 146(730): 1999–2049. https://doi.org/10.1002/qj.3803
Holtzman NM, Pavelsky TM, Cohen JS, et al. (2020) Tailoring WRF and Noah-MP to Improve Process Representation of Sierra Nevada Runoff: Diagnostic Evaluation and Applications.J Adv Model Earth Sy 12(3): 1–18. https://doi.org/10.1029/2019MS001832
Hong S, Lim JOJ (2006) The WRF single-moment 6-class microphysics scheme (WSM6). Journal of Korean meteorological society 42(2): 129–151.
Hong SY, Noh Y, Dudhia J (2006) A new vertical diffusion package with an explicit treatment of entrainment processes. Mon Weather Rev 134(9): 2318–2341. https://doi.org/10.1175/MWR3199.1
Huang D, Gao S (2018) Impact of different reanalysis data on WRF dynamical downscaling over China. Atmos Res 200: 25–35. https://doi.org/10.1016/j.atmosres.2017.09.017
Huning LS, Aghakouchak A (2020) Mountain snowpack response to different levels of warming. P Natl Acad Sci USA 115(43): 10932–10937. https://doi.org/10.1073/pnas.1805953115
Immerzeel WW, Lutz AF, Andrade M, et al. (2020) Importance and vulnerability of the world’s water towers. Nature 577(7790):364–369. https://doi.org/10.1038/s41586-019-1822-y
Jiménez-Esteve B, Udina M, Soler MR, et al. (2018) Land use and topography influence in a complex terrain area: A high resolution mesoscale modelling study over the Eastern Pyrenees using the WRF model. Atmos Res 202: 49–62. https://doi.org/10.1016/j.atmosres.2017.11.012
Jost G, Weiler M, Gluns DR, et al. (2007) The influence of forest and topography on snow accumulation and melt at the watershed-scale. J Hydrol 347(1–2): 101–115. https://doi.org/10.1016/j.jhydrol.2007.09.006
Jordan R (1991) A one-dimensional temperature model for a snow cover: Technicaldocumentation for SNTHERM. 89 (No. CRREL-SR-91-16). Cold Regions Research and Engineering Lab Hanover NH
Kain JS (2004) The Kain-Fritsch Convective Parameterization: An Update. J Appl Meteorol Clim 43(1): 170–181. https://doi.org/10.1175/1520-0450(2004)043<0170:TKCPAU>2.0.CO;2
Kumar SV, Mocko DM, Wang S, et al. (2019) Assimilation of remotely sensed leaf area index into the noah-mp land surface model: Impacts on water and carbon fluxes and states over the continental United States. J Hydrometeorol 20(7): 1359–1377. https://doi.org/10.1175/JHM-D-18-0237.1
Lehning M, Bartelt P, Brown B, et al. (2002) A physical SNOWPACK model for the Swiss avalanche warning Part II. Snow microstructure. Cold Reg Sci Technol 35(3): 147–167. https://doi.org/10.1016/S0165-232X(02)00073-3
Leung LR, Qian Y (2003) The sensitivity of precipitation and snowpack simulations to model resolution via nesting in regions of complex terrain. J Hydrometeorol 4(6): 1025–1043. https://doi.org/10.1175/1525-7541(2003)004<1025:TSOPAS>2.0.CO;2
Li Q, Yang T, Qi Z, et al. (2018) Spatiotemporal Variation of Snowfall to Precipitation Ratio and Its Implication on Water Resources by a Regional Climate Model over Xinjiang, China. Water 10(1463): 1–13. https://doi.org/10.3390/w10101463
Li Q, Yang T, Zhou H, et al. (2019) Patterns in snow depth maximum and snow cover days during 1961–2015 period in the Tianshan Mountains, Central Asia. Atmos Res 228(May): 14–22. https://doi.org/10.1016/j.atmosres.2019.05.004
Li Z, Chen Y, Li Y, et al. (2020) Declining snowfall fraction in the alpine regions, Central Asia. Scientific Reports 10(1): 1–12. https://doi.org/10.1038/s41598-020-60303-z
Liang X, Lettenmaier DP, Wood EF, et al. (1994) A simple hydrologically based model of land surface water and energy fluxes for general circulation models. J Geophys Res 99(D7): 415–428. https://doi.org/10.1029/94jd00483
Liu L, Ma Y, Menenti, 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. J Geophys Res Atmos 124(1): 209–226. https://doi.org/10.1029/2018JD029208
Liu Y, Chen X, Li Q, et al. (2020) Impact of different microphysics and cumulus parameterizations in WRF for heavy rainfall simulations in the central segment of the Tianshan Mountains, China. Atmos Res 244(November 2019): 105052. https://doi.org/10.1016/j.atmosres.2020.105052
Luijting H, Vikhamar-Schuler D, Aspelien T, et al. (2018) Forcing the SURFEX/Crocus snow model with combined hourly meteorological forecasts and gridded observations in southern Norway. The Cryosphere 12(6): 2123–2145. https://doi.org/10.5194/tc-12-2123-2018
Ma N, Niu GY, Xia Y, et al. (2017) A systematic evaluation of Noah-MP in simulating land-atmosphere energy, water, and carbon exchanges over the continental United States. J Geophys Res Atmos 122(22): 245–268. https://doi.org/10.1002/2017JD027597
Ma W, Ma Y (2016) Modeling the influence of land surface flux on the regional climate of the Tibetan Plateau. Theor Appl Climatol 125(1–2). https://doi.org/10.1007/s00704-015-1495-x
Ma X, Jin J, Liu J, et al. (2019) An improved vegetation emissivity scheme for land surface modeling and its impact on snow cover simulations. Clim Dynam (0123456789). https://doi.org/10.1007/s00382-019-04924-9
Magnusson J, Wever N, Essery R, et al. (2015) Evaluating snow models with varying process representations for hydrological applications. Water Resour Res 51: 2707–2723. https://doi.org/10.1002/2015WR017200.A
Maina FZ, Siirila-Woodburn ER, Vahmani P (2020) Sensitivity of meteorological-forcing resolution on hydrologic variables. Hydrol Earth Syst Sc 24(7): 3451–3474. https://doi.org/10.5194/hess-24-3451-2020
Mallard MS, Spero TL (2019) Effects of Mosaic Land Use on Dynamically Downscaled WRF Simulations of the Contiguous United States. J Geophys Res Atmos 124: 9117–9140. https://doi.org/10.1029/2018jd029755
Mankin JS, Viviroli D, Mekonnen MM, et al. (2015) The potential for snow to supply human water demand in the present and future. Environ Res Lett 10(11406). https://doi.org/10.1088/1748-9326/10/11/114016
Maussion F, Scherer D, Finkelnburg R, et al. (2011) WRF simulation of a precipitation event over the Tibetan Plateau, China — an assessment using remote sensing and ground observations. Hydrol Earth Syst Sc 15: 1795–1817. https://doi.org/10.5194/hess-15-1795-2011
Mazzotti G, Currier WR, Deems JS, et al. (2019) Revisiting Snow Cover Variability and Canopy Structure Within Forest Stands: Insights From Airborne Lidar Data. Water Resour Res 55(7): 6198–6216.https://doi.org/10.1029/2019wr024898
Mazzotti G, Essery R, Moeser CD, et al. (2020) Resolving Small-Scale Forest Snow Patterns Using an Energy Balance Snow Model With a One-Layer Canopy. Water Resour Res 56(1). https://doi.org/10.1029/2019WR026129
Mizukami N, Clark MP, Slater AG, et al. (2014) Hydrologic implications of different large-scale meteorological model forcing datasets in mountainous regions. J Hydrometeorol 15(1): 474–488. https://doi.org/10.1175/JHM-D-13-036.1
Mlawer EJ, Taubman SJ, Brown PD, et al. (1997) Radiative transfer for inhomogeneous atmospheres: RRTM, a validated correlated-k model for the longwave. J Geophys Res 102(D14): 16663. https://doi.org/10.1029/97JD00237
Moeser D, Mazzotti G, Helbig N, et al. (2016) Representing spatial variability of forest snow: Implementation of a new interception model. Water Resour Res 52: 1208–1226. https://doi.org/10.1111/j.1752-1688.1969.tb04897.x
Moriasi DN, Arnold JG, Liew MW, et al. (2007) Model evaluation guidelines for systematic quantification of accuracy in watershed simulations. Transactions of American Society of Agricultural and Biological Engineers 50(3): 885–900. https://doi.org/10.13031/2013.23153
Musselman KN, Molotch NP, Brooks PD (2008) Effects of vegetation on snow accumulation and ablation in a mid-latitude sub-alpine forest. Hydrol Process 22: 2767–2776. https://doi.org/10.1002/hyp
Niu GY, Yang ZL (2004) Effects of vegetation canopy processes on snow surface energy and mass balances. J Geophys Res Atmos 109(23): 1–15. https://doi.org/10.1029/2004JD004884
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. J Geophys Res Atmos 116(12): 1–19. https://doi.org/10.1029/2010JD015139
Norris J, Carvalho LMV, Jones, et al. (2017) The spatiotemporal variability of precipitation over the Himalaya: evaluation of one- year WRF model simulation. Clim Dynam 49(5): 2179–2204. https://doi.org/10.1007/s00382-016-3414-y
Parajuli A, Nadeau DF, Anctil F, et al. (2020) Exploring the spatiotemporal variability of the snow water equivalent in a small boreal forest catchment through observation and modelling. Hydrol Process 34(11): 2628–2644. https://doi.org/10.1002/hyp.13756
Park S, Park SK (2016) Parameterization of the snow-covered surface albedo in the Noah-MP Version 1.0 by implementing vegetation effects. Geosci Model Dev 9(3): 1073–1085. https://doi.org/10.5194/gmd-9-1073-2016
Pulliainen J, Luojus K, Derksen C, et al. (2020) Patterns and trends of Northern Hemisphere snow mass from 1980 to 2018. Nature 581(7808): 294–298. https://doi.org/10.1038/s41586-020-2258-0
Qin Y, Abatzoglou JT, Siebert S, et al. (2020) Agricultural risks from changing snowmelt. Nat Clim Change 10(5): 459–465. https://doi.org/10.1038/s41558-020-0746-8
Qiu Y, Hu Q, Zhang C (2017) WRF simulation and downscaling of local climate in Central. Int J Climatol 37(March): 513–528. https://doi.org/10.1002/joc.5018
Qu X, Hall A (2014) On the persistent spread in snow-albedo feedback. Clim Dynam 42(1–2): 69–81. https://doi.org/10.1007/s00382-013-1774-0
Rutter N, Essery R, Pomeroy J, et al. (2009) Evaluation of forest snow processes models (SnowMIP2). J Geophys Res Atmos 114(6). https://doi.org/10.1029/2008JD011063
Samuelsson P, Bringfelt B, Graham LP (2003) The role of aerodynamic roughness for runoff and snow evaporation in land-surface schemes - Comparison of uncoupled and coupled simulations. Global Planet Change 38(1–2): 93–99. https://doi.org/10.1016/S0921-8181(03)00009-2
Schmucki E, Marty C, Fierz C, et al. (2014) Evaluation of modelled snow depth and snow water equivalent at three contrasting sites in Switzerland using SNOWPACK simulations driven by different meteorological data input. Cold Reg Sci Technol 99: 27–37. https://doi.org/10.1016/j.coldregions.2013.12.004
Skamarock, C, Klemp JB (2008). A time-split nonhydrostatic atmospheric model for weather research and forecasting applications. Journal of Computational Physics 227(7): 3465–3485. https://doi.org/10.1016/j.jcp.2007.01.037
Skok G, Nedjeljka Ž, Honzak L (2016) Precipitation intercomparison of a set of satellite- and raingauge-derived datasets, ERA Interim reanalysis, and a single WRF regional climate simulation over Europe and the North Atlantic. Theor Appl Climatol 123: 217–232. https://doi.org/10.1007/s00704-014-1350-5
Smyth EJ, Raleigh MS, Small EE (2020) Improving SWE estimation with data assimilation: The influence of snow depth observation timing and uncertainty. Water Resour Res 56(5). https://doi.org/10.1029/2019WR026853
Sorg A, Bolch T, Stoffel M, et al. (2012) Climate change impacts on glaciers and runoff in Tien Shan (Central Asia). Nat Clim Change 2(10). https://doi.org/10.1038/nclimate1592
Spera SA, Winter JM, Chipman JW (2018) Evaluation of agricultural land cover representations on regional climate model simulations in the Brazilian Cerrado. J Geophys Res Atmos 123(10). https://doi.org/10.1029/2017JD027989
Stephens GL, Ecuyer TL, Forbes R, et al. (2010) Dreary state of precipitation in global models. Journal of Geophysical Research 115(D24211): 1–13. https://doi.org/10.1029/2010JD014532
Sun S, Jin J, Xue Y (1999) A simple snow-atmosphere-soil transfer model. J Geophys Res Atmos 104(D16): 19587–19597. https://doi.org/10.1029/1999JD900305
Sun Y, Solomon S, Dai A, et al. (2006) How often does it rain? J Climate 19(6): 916–934. https://doi.org/10.1175/JCLI3672.1
Tang Z, Wang X, Wang J, et al. (2017) Spatiotemporal variation of snow cover in Tianshan Mountains, Central Asia, based on cloud-free MODIS fractional snow cover product, 2001–2015. Remote Sens 9(10). https://doi.org/10.3390/rs9101045
Taylor KE (2001) Summarizing multiple aspects of model performance in a single diagram. J Geophys Res 106: 7183–7192. https://doi.org/10.1029/2000JD900719
Terzago S, Andreoli V, Arduini G, et al. (2020) Sensitivity of snow models to the accuracy of meteorological forcings in mountain environments. Hydrol Earth Syst Sc 24(8): 4061–4090. https://doi.org/10.5194/hess-24-4061-2020
Tomasi E, Giovannini L, Zardi D, et al. (2017) Optimization of Noah and Noah_MP WRF land surface schemes in snow-melting conditions over complex terrain. Mon Weather Rev 145(12): 4727–4745. https://doi.org/10.1175/MWR-D-16-0408.1
Toure AM, Rodell M, Yang ZL, et al. (2016) Evaluation of the snow simulations from the community land model, version 4 (CLM4). J Hydrometeorol 17(1): 153–170. https://doi.org/10.1175/JHM-D-14-0165.1
Toure AM, Reichle RH, Forman BA, et al. (2018) Assimilation of MODIS snow cover fraction observations into the NASA catchment land surface model. Remote Sens 10(2): 316. https://doi.org/10.3390/rs10020316
Unger-Shayesteh K, Vorogushyn S, Farinotti D, et al. (2013) What do we know about past changes in the water cycle of Central Asian headwaters? A review. Global Planet Change 110: 4–25. https://doi.org/10.1016/j.gloplacha.2013.02.004
Varhola A, Coops NC, Weiler M, et al. (2010) Forest canopy effects on snow accumulation and ablation: An integrative review of empirical results. J Hydrol 392(3–4): 219–233. https://doi.org/10.1016/j.jhydrol.2010.08.009
Verseghy DL (1991) Canadian Land Surface Scheme for GCMs. Int J Climatol 11(2): 111–133. https://doi.org/10.1002/joc.3370110202
Wang A, Zeng X, Guo D (2016) Estimates of global surface hydrology and heat fluxes from the community land model (CLM4.5) with four atmospheric forcing datasets. J Hydrometeorol 17(9): 2493–2510. https://doi.org/10.1175/JHM-D-16-0041.1
Wang X, Tolksdorf V, Otto M, et al. (2020) 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 (May): 1–20. https://doi.org/10.1002/joc.6686
Wang Y, Xie Z, Jia B, et al. (2020) Sensitivity of Snow Simulations to Different Atmospheric Forcing Data Sets in the Land Surface Model CAS - LSM. J Geophys Res Atmos 125(16): 1–24. https://doi.org/10.1029/2019jd032001
Wen X, Lu S, Jin J (2012) Integrating remote sensing data with WRF for improved simulations of oasis effects on local weather processes over an Arid Region in Northwestern China. J Hydrometeorol 13(2): 573–587. https://doi.org/10.1175/JHM-D-10-05001.1
Wrzesien ML, Durand MT, Pavelsky TM, et al. (2018) A New Estimate of North American Mountain Snow Accumulation From Regional Climate Model Simulations. Geophys Res Lett 45(3): 1423–1432. https://doi.org/10.1002/2017GL076664
Xiao Z, Liang S, Wang J, et al. (2014) Use of general regression neural networks for generating the GLASS leaf area index product from time-series MODIS surface reflectance. IEEE T Geosci Remote 52(1): 209–223. https://doi.org/10.1109/TGRS.2013.2237780
Xiao Z, Liang S, Wang J, et al. (2016) Long-Time-Series Global Land Surface Satellite Leaf Area Index Product Derived from MODIS and AVHRR Surface Reflectance. IEEE T Geosci Remote 54(9). https://doi.org/10.1109/TGRS.2016.2560522
Xu M, Kang S, Wu H, et al. (2018) Detection of spatio-temporal variability of air temperature and precipitation based on longterm meteorological station observations over Tianshan Mountains, Central Asia. Atmos Res 203(December): 141–163. https://doi.org/10.1016/j.atmosres.2017.12.007
Yang T, Li Q, Ahmad S, et al. (2019) Changes in Snow Phenology from 1979 to 2016 over the Tianshan Mountains, Central Asia. Remote Sens 11(499): 1–16. https://doi.org/10.3390/rs11050499
Yang T, Li Q, Chen X, et al. (2020a) Evaluation of spatiotemporal variability of temperature and precipitation over the Karakoram Highway region during the cold season by a Regional Climate Model. J Mt Sci 17: 1–16. https://doi.org/10.1007/s11629-019-5772-5
Yang T, Li Q, Chen X, et al. (2020b) Improving snow simulation with more realistic vegetation parameters in a regional climate model in the Tianshan Mountains, Central Asia. J Hydrol 590. https://doi.org/10.1016/j.jhydrol.2020.125525
Yang T, Li Q, Chen X, et al. (2021) Variation of snow mass in a regional climate model downscaling simulation covering the Tianshan Mountains, Central Asia. J Geophys Res Atmos 126: e2020JD034183. https://doi.org/10.1029/2020JD034183
Yang ZL, Dickinson RE, Robock A, et al. (1997) Validation of the snow submodel of the biosphere-atmosphere transfer scheme with Russian snow cover and meteorological observational data. J Climate 10(2): 353–373. https://doi.org/10.1175/1520-0442(1997)010<0353:VOTSSO>2.0.CO;2
You Y, Huang C, Yang Z, et al. (2020) Assessing Noah-MP Parameterization Sensitivity and Uncertainty Interval Across Snow Climates. J Geophys Res Atmos 125(4): 1–20. https://doi.org/10.1029/2019JD030417
Zheng Z, Ma Q, Jin S, et al. (2019) Canopy and Terrain Interactions Affecting Snowpack Spatial Patterns in the Sierra Nevada of California. Water Resour Res 55(11): 8721–8739. https://doi.org/10.1029/2018WR023758
Zhou H, Aizen E, Aizen V (2017) Seasonal snow cover regime and historical change in Central Asia from 1986 to 2008. Global Planet Change 148: 192–216. https://doi.org/10.1016/j.gloplacha.2016.11.011
Zolina O, Kapala A, Simmer C, et al. (2004) Analysis of extreme precipitation over Europe from different reanalyses: A comparative assessment. Global Planet Change 44(1–4): 129–161. https://doi.org/10.1016/j.gloplacha.2004.06.009
Acknowledgements
This study was supported by the National Natural Science Foundation of China (NSFC Grant 42001061, U1703241, and 41901087), and the Strategic Priority Research Program of the Chinese Academy of Sciences, the Pan-Third Pole Environment Study for a Green Silk Road (Pan-TPE) (No. XDA2004030202).
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Li, Q., Yang, T. & Li, Lh. Impact of forcing data and land surface properties on snow simulation in a regional climate model: a case study over the Tianshan Mountains, Central Asia. J. Mt. Sci. 18, 3147–3164 (2021). https://doi.org/10.1007/s11629-020-6621-2
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DOI: https://doi.org/10.1007/s11629-020-6621-2