Annual mean land surface temperature over the Tibet plateau

The Tibetan plateau (TP), called as “the third pole of the earth” is the water tower of Asia not only feed tens of millions of people, but also maintain fragile ecosystems in arid region of northwestern China. Temporal-spatially complete representations of land surface temperature are required for many purposes in environmental science, especially in third pole where the traditional ground measurement is difficult and therefore the data is sparse.

The cloud-free datasets of daily mean land surface temperature (LST) and mean annual land surface temperature (MAST) during 2004 to 2016 were released and derived from the quartic daily MODIS (the Moderate Resolution Imaging Spectroradiometer) Terra/Aqua LST products with a resolution of 1 km using a pragmatic data processing algorithm (Ran et al., 2015; 2017a). The comparison between radiance-based LST measurement and the estimated LST shows good agreement in the daily and inter-annual variability, with a correlation of 0.95 and 0.99 and bias of -1.73℃ (±3.38℃) and -2.07℃ (±1.05℃) for daily-mean-LST and MAST, respectively (Ran et al., 2017c). The systematic error is mainly source from the defined of daily mean LST, which is represented by the arithmetic average of the daytime and nighttime LSTs. The random error is mainly source from the uncertainty of the original MODIS LST values, especially for the daytime LST products. Trend validation using air temperatures from 94 weather stations indicate that the warming trends derived from time series MAST data is comparable with that derived from CMA data. The dataset is potential useful for various studies, including climatology, hydrology, meteorology, ecology, agriculture, public health, and environmental monitoring in the third pole and around regions.

Data file naming and use method

Two types of simulations are designed (i.e., B case and H case). For each type, four simulations are performed with different heterogeneity length scales (e.g., 2000 m, 1200 m, 550 m and 240 m). Hence, the first char of the filename in our dateset refers to the simulation type and the following numbers represent the heterogeneity length scales.

Required Data Citation View Data Cite Help About Data Citation

1. Zhou, Y.Z., Li, D., Li, X. (2019). The Effects of Surface Heterogeneity Scale on the Flux Imbalance under Free Convection, Journal of Geophysical Research: Atmospheres, doi:10.1029/2018jd029550.( View Details | Download )

Cite the data

ZHOU Yanzhao. The Surface Heterogeneity patterns and the Flux Imbalance under Free Convection based on the WRF LES. Big Data System for Pan-Third Pole, 2019. doi: 10.11888/Meteoro.tpdc.270103. (Download the reference: RIS | Bibtex )

Using this data, you must reference article references listed in the Required Data Citation and reference data

References literature

1.Zhou, Y.Z., Li, D., Liu, H. and Li, X., (2018). Diurnal variations of the flux imbalance over homogeneous and heterogeneous landscapes. Boundary Layer Meteorol. 168(3), 417-442. doi:10.1007/s10546-018-0358-2. (View Details | Download )

Support Program

Pan-Third Pole Environment Study for a Green Silk Road-A CAS Strategic Priority A Program

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License: This work is licensed under a Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)

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  • Time Resolution: Hourly
  • Spatial Resolution: m
  • File size: 900.0 MB
  • View count:119 Times
  • Share type: online
  • Time Description: 3 hours
  • Updated Time:2019-08-08
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Data Resource Provider: ZHOU Yanzhao  

Distributor: Observational & Big Data Center for Three Poles


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