Concerted Earth Observation and Prediction of Water and Energy Cycles in the Third Pole Environment (CEOP-TPE) (ID )

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1 Concerted Earth Observation and Prediction of Water and Energy Cycles in the Third Pole Environment (CEOP-TPE) (ID ) Yaoming Ma(马耀明)1, Bob Su(苏中波)2, Weiqiang Ma (马伟强) 1, Lei Zhong(仲雷) 3, Maoshan Li(李茂善) 4, Cunbo Han(韩存博) 1, Binbin Wang (王宾宾) 1,2 on behalf of the Chinese Dragon CEOP-TPE Team 1Key Laboratory of Tibetan Environment Changes and Land Surface Processes, Institute of Tibetan Plateau Research, the Chinese Academy of Sciences, Beijing Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, Enschede 7500 AA, Netherlands 3School of Earth and Space Sciences, University of Science and Technology of China, Hefei Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences, Lanzhou

2 Outline EO data acquisition and ground data collection campaigns Progresses Parameterization of soil heat flux Parameterization of effective roughness length Plateau-scale land surface parameters from satellite data and WRF model The role of young scientists Publications Plans for next years

3 TPE implementation plan

4 青藏所的 10 个多圈层综合观测研究站 9 个地气相互作用过程站点分布 塔吉克斯坦站 慕士塔格站 巴基斯坦站 阿里站 NewD66 双湖站 D110 Amdo BJ 纳木错站 D66 D105 MS3478 那曲站 MS3608 玛曲站 珠峰站 亚东 藏东南站 多圈层综合观测研究站 尼泊尔站 地气相互作用观测站点

5 Tibetan Observation and Research Platform 40m PBL tower ( radiation system and SMTMS) Turbulent system,co 2 /H 2 O flux and radiation system Wind Profiler and RASS GPS Meso-scale experimental area Five comprehensive observation and research platforms have been set up.

6 Optical and Microwave Remote Sensing Data ASTER SPOT LANDSAT MODIS AVHRR

7 Optical and Microwave Remote Sensing Data FY ENVISAT ERS TRMM

8 Results soil heat flux Comparisons between TDEC results and in-situ values measured by soil heat flux plate (a)anni,(b)bj,(c)d105 Time series of soil heat flux derived by different methods at ANNI station (a)10 cm,(b)20 cm

9 Daily variations of soil heat flux at ANNI station under different weather conditions (a)sunny,(b)cloudy,(c)rainy

10 Units:W m -2 站名 ANNI BJ D105 净辐射通量日均值 G TDEC,0 日最大值 / 日最小值 / 日均值 G TDEC,30 日最大值 / 日最小值 / 日均值 G TDEC,50 日最大值 / 日最小值 / 日均值 / / / / / -3.1 / / / / / / -1.9 / / / / -6.0 / / 7.4 / 10.4 站名 soil texture 土壤深度 /cm ANNI 砂质壤土 砂质壤土 砂质壤土 / / BJ 砂土 砂土 砂土 壤质砂土 砂土 D105 / / / / / Daily variations of soil heat flux at three stations (a)0 cm,(b)30 cm,(c)50 cm

11 Results effective roughness length 45N 40N 35N Shiquanhe N QOMS Litang N 70E 75E 80E 85E 90E 95E 100E 105E 1000 ASL(m) QOMS: GPS Radiosonde, Wind Profiler and EC Shiquanhe: GPS Radiosonde Litang: GPS Radiosonde and EC 11

12 Estimation of z 0m and d 0 from wind profiles U = u* κ z d 0 ln( ) z 0m u U U 2 0 0m * = 0.4( 2 1) / ln( ) z1 Cz 0 0m z Cz z = z[exp(0.4 U / u ) + C ] 0m 1 1 * 0 1 d = Cz 0 0 0m C0 = aλ b A h λ = = S L (Kustas and Brutsaert, 1986) 12

13 10 3 (a) Semi-log plot of near-neutral wind profiles at QOMS(a), Shiquanhe(b) and Litang station(c) R 2 = 0.95, RMSE = 0.14 R 2 = 0.99, RMSE = 0.07 R 2 = 0.99, RMSE = 0.08 R 2 = 0.97, RMSE = 0.19 R 2 = 0.93, RMSE = (a) R 2 = 0.94, RMSE = 0.33 R 2 = 0.98, RMSE = 0.11 R 2 = 0.94, RMSE = z-d 0 (m) 10 2 R 2 = 0.85, RMSE = 0.41 R 2 = 0.94, RMSE = 0.20 R 2 = 0.97, RMSE = 0.14 R 2 = 0.97, RMSE = 0.18 R 2 = 0.84, RMSE = 0.50 R 2 = 0.81, RMSE = 0.40 R 2 = 0.88, RMSE = 0.33 Height (m) N = 24 R 2 = 0.98, RMSE = 0.09 R 2 = 0.95, RMSE = 0.13 R 2 = 0.88, RMSE = 0.18 R 2 = 0.93, RMSE = 0.37 R 2 = 0.99, RMSE = 0.06 R 2 = 0.98, RMSE = 0.18 R 2 = 0.88, RMSE = z-d 0 (m) R 2 = 0.91, RMSE = 0.34 R 2 = 0.99, RMSE = Wind speed (m/s) (b) N = 12 R 2 = 0.99, RMSE = 0.13 R 2 = 0.96, RMSE = 0.23 R 2 = 0.99, RMSE = 0.05 R 2 = 0.99, RMSE = 0.06 R 2 = 1.00, RMSE = 0.03 R 2 = 0.98, RMSE = 0.06 R 2 = 0.99, RMSE = 0.05 R 2 = 0.95, RMSE = 0.28 R 2 = 0.98, RMSE = 0.08 R 2 = 0.99, RMSE = 0.07 R 2 = 0.99, RMSE = Wind speed (m/s) (c) 10 3 R 2 = 0.99, RMSE = Wind direction (Degree) (b) 300 Height (m) Wind direction (Degree) (c) The selected wind profiles coincide with the logarithmic law of neutral condition z-d 0 (m) N = 9 13 R 2 = 0.99, RMSE = 0.08 R 2 = 0.95, RMSE = 0.27 R 2 = 1.00, RMSE = 0.07 R 2 = 0.99, RMSE = 0.08 R 2 = 0.99, RMSE = 0.21 R 2 = 0.99, RMSE = 0.13 R 2 = 1.00, RMSE = 0.09 R 2 = 1.00, RMSE = 0.03 R 2 = 0.99, RMSE = Wind speed (m/s) Height (m) Wind direction (Degree)

14 Average and standard deviation of z 0m and d 0 for QOMS station, Shiquanhe station, and Litang station calculated using wind profile data. z eff 0m & d 0 Station (Samples) Average d 0 (m) Average z eff 0m (m) QOMS (24) 551.7± ±5.0 Shiquanhe (12) 81.9± ±4.3 Litang (9) 60.7± ±1.1 14

15 Relation between roughness parameter and terrain characteristics k 0.5 DA/ S + k / ln ( h / 2 z ) 2 2 eff ln ( h/ 2 z0m ) = 2 2 0m (Grant and Mason, 1990) = 2 Ff 0.5 ρdu ( h / 2) A k 2 2 Fs = ρu ( h/ 2) S 2 ln ( h/ 2 z0m) k Ft = U h S ln ( / 2 ) 2 2 ρ ( / 2) 2 eff h zom (Form drag term) (Shear stress term) (Total drag) 15

16 Comparison of different parameterization schemes L S Q D = 0.6 D = 0.5 D = 0.4 D = L S Q WO73 GM90 / h eff z 0m 10-2 K (Grant and Mason,1990) / h eff z 0m 10-2 K λ λ The curve with D=0.5 produces the best agreement. So 0.5 is a more appropriate value of form drag coefficient in mountainous areas especially in mountainous areas like the Tibetan Plateau. 16

17 Comparison of different parameterization schemes Station height h(m) density λ QOMS Shiquanhe Litang There is a systematic underestimation of ERA-Interim which also use GM 90 method but with D of

18 NOAA/AVHRR MODIS Landsat-7 ETM ASTER Satellite data SL+ABL obs. Vegetation fractional coverage MODTRAN surface and atmospheric data MSAVI ε0 r0 Tsfc K L Z 0 m kb 1, d 0, u, T a, ψ m, ψ h G0 Surface data Hf ( 加热场 ) Rn λe Parameterization Scheme (Ma et al., 2012, AAS; Ma et al., 2013, TAAC; Ma et al., 2014, ACP) H Blending height and Tile approach

19 Latent heat flux λe (Wm -2 ) R n H λe G 0 NPAM

20 Land surface heating field (net radiation) ITPCAS T & RH & P MODIS LST & Emissivity (Terra & Aqua) MODIS Albedo & ITPCAS SWD (Brutsaert 1975) LWD LWU Net Shortwave Radiation (Crawford and Duchon 1999) Net Longwave Radiation NET Radiation Parameters Source Spatial resolution Time resolution Albedo MODIS reflectance 0.01 degree 8 d SWD ITPCAS Reanalysis 0.1 degree 3 h Specific humidity ITPCAS Reanalysis 0.1 degree 3 h Air temperature ITPCAS Reanalysis 0.1 degree 3 h Air pressure ITPCAS Reanalysis 0.1 degree 3 h LST (Terra, Aqua) MODIS products 0.01 degree 1 d 4 data Emissivity (Terra, Aqua) MODIS Products 0.01 degree 1 d 4 data DEM ASTER 0.01 degree (30m) The ITPCAS reanalysis data (SWD, air temperature, air pressure) is downscaled from 0.1 degree to 0.01 degree.

21 Validation of ITPCAS forcing data The daily sum of SWD radiation is validated and show acceptable result between ITPCAS forcing data and observations in BJ, Nam Co, Qomo and Linzh station.

22 ITPCAS reanalysis data correction The corrections is performed using DEM with the following methods: ) The air temperature is corrected using the lapse rate; 0.1 2) The air pressure is corrected using the air pressure estimation equation; 3) The short wave radiation is corrected with the radiation simulation model for slope and aspect.

23 10-year averaged land surface heating field West Middle East

24 Results from WRF Hourly variations of air temperature 24

25 25 Hourly variations of sensible heat flux

26 26 Hourly variations of soil heat flux

27 y [Wm -2 ] Rn_obs Rn_default Rn_SM Rn_VER125 Rn_VER y [Wm -2 ] H_obs H_default H_SM H_VER125 H_VEG x x y [Wm -2 ] λe_obs λe_default λe_sm λe_veg125 λe_veg y [Wm -2 ] G0_obs G0_default G0_SM G0_VEG125 G0_VEG x x The modeling results and observations from 2 Aug Note: a) net radiation; b) sensible heat flux; c) latent heat flux; d) soil heat flux 27

28 Young scientists Weiqiang Ma (Prof.) (land surface processes, remote sensing and numerical model) Lei Zhong (A. Prof.) (land surface processes, monsoon climate) Maoshan Li (A. Prof.) (land surface processes, Land surface modeling) Binbin Wang (PhD student) (land surface processes, remote sensing ) Cunbo Han (PhD student) (Land-atmosphere interactions) Junping Du (PhD student) (remote sensing)

29 Academic Exchange Programmes Four PhD students have been sent to European partner for joint training Lei Zhong and Xuelong Chen have got their PhD degree from University of Twente under the supervision of Prof. Yaoming Ma and Prof. Z.(Bob) Su Several European students from our partner also come to China regularly for joint field visiting and academic exchange

30 Publications 1. Ma, Y., Z. Zhu, L. Zhong, B.Wang, C. Han, Z.Wang, Y.Wang, L. Lu, P. M. Amatya1,W. Ma, and Z. Hu, 2014, Combining MODIS, AVHRR and in situ data for evapotranspiration estimation over heterogeneous landscape of the Tibetan Plateau, Atmospheric Chemistry and Physics, 14, Ma, W., Y. Ma, H.Ishikawa, 2014, Evaluation of the SEBS for upscaling the evapotranspiration based on in-situ observations over the Tibetan Plateau, Atmospheric Research, 138, Zhong, L., Y. Ma, Y. Fu, X. Pan, W. Hu, Z. Su, M.S. Salama and L. Feng, 2014, Assessment of soil water deficit for the middle reaches of Yarlung-Zangbo River from optical and passive microwave images, Remote Sensing of Environment, 142: DOI: /j.rse Ma, Y., C. Han, L. Zhong, B. Wang, Z. Zhu, Y. Wang, L. Zhang, C. Meng, C. Xu, P. M. Amatya, 2013, Using MODIS and AVHRR data to determine regional surface heating field and heat flux distribution over heterogeneous landscape of the Tibetan Plateau, Theoretical and Applied Climatology, DOI /s Ma, Y., B. Wang, L. Zhong, W. Ma, 2012, The regional surface heating field over the heterogeneous landscape of the Tibetan Plateau using MODIS and in-situ data, Advances in Atmospheric Sciences, 29(1): Ma, Y., L. Zhong, Y.Wang, Z.Su, 2012, Using NOAA/AVHRR data to determine regional net radiation and soil heat fluxes over the heterogeneous landscape of the Tibetan Plateau, International Journal of Remote Sensing, 33(15): Zhong, L., Y. Ma, W. Ma, Y. Fu, Z. Su, Mhd. Suhyb Salama, Duo Chu, Ciren Bianba, 2012, Remote Sensing of Land Surface Parameters in the Middle Reaches of YarlungZangbo River and Its Two Tributaries from AVHRR and MODIS Data, Journal of the Meteorological Society of Japan, 90C: 75-86, doi: /jmsj.2012-c Li, M, Y. Ma, L. Zhong, 2012, The Turbulence Characteristics of the Atmospheric Surface Layer on the North Slope of Mt. Everest Region in the Spring of 2005, Journal of the Meteorological Society of Japan, 90C: ,doi: /jmsj.2012-C Xun, X., Z. YHu, and Y. Ma, 2012, The Dynamic Plateau Monsoon Index and itsassociation with general circulation anomalies. Adv. Atmos. Sci., 29(6), 1249{1263, doi: /s Chen, X., Z.Su, Y. Ma, and F.Sun, 2012, Analysis of land-atmosphere interactions over the north region of Mt. Qomolangma (Mt. Everest), Artic, Antarctic, and Alpine Research, 44(4), Duan, A., G. Wu, Y. Liu, Y. Ma, and P. Zhao, 2012, Weather and climate effects of the Tibetan Plateau. Advances in Atmospheric Sciences, 29(5), 978{992, doi: /s y. 12. Zhang, R., T. Koike, X. Xu, Y. Ma, and K. Yang, 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: /jmsj.2012-c Han, C., Y. Ma, Z. Su, X. Chen, L. Zhang, M. Li, F. Sun Estimates of effective aerodynamic roughness length over mountainous areas of the Tibetan Plateau. Quarterly Journal of the Royal Meteorological Society. 141: doi: /qj.2462.

31 What we will do in next years?? Intensive field observations for the TP Continuous cal/val of EO data products Validation & improvements of model parameterization Generation of basin scale water and energy cycle data to close water and energy balance on basin scale For Nagqu River basin, Namco Lake basin Academic exchange programmes 31

32 Thank You! 32