青藏高原非均匀地表区域能量通量的研究

卫星遥感在研究青藏高原非均匀地表区域能量通量和蒸发(蒸散)量时有其独到的作用。本文介绍了基于NOAA-14 AVHRR和Landsat TM资料推算藏北高原地区区域地表特征参数、植被参数及区域地表热通量的方案,并把其用于GAME/Tibet(全球能量水循环之亚洲季风青藏高原试验研究)和CAMP/Tibet(“全球协调加强观测计划(CEOP)亚澳季风之青藏高原试验研究”)试验区。并指出了此方法估算青藏高原非均匀地表区域地表能量通量和蒸发(蒸散)量时存在的难点问题和解决问题的可能途径。

卫星遥感藏北高原非均匀陆表地表特征参数和植被参数

卫星遥感在研究青藏高原北部地区 (藏北高原地区 )非均匀陆表地表特征参数和植被参数时有其独到的作用。作者提出了基于NOAA 1 4AVHRR资料推算藏北高原地区地表特征参数和植被参数的方案 ,并把其用于全球能量水循环之亚洲季风青藏高原试验(GAME/Tibet)试验区。同时利用 3个景的NOAA 1 4AVHRR资料进行了分析研究 ,得到了一些有关藏北地区非均匀地表的区域地表特征参数 (地表反射率、地表温度 )和植被参数(INDV、修正的土壤调整植被指数IMSAV、植被覆盖度和叶面指数ILA)。

卫星遥感结合地面观测估算非均匀地表区域能量通量

卫星遥感在研究非均匀陆面上地－气间能量和水循环过程时有其独到的作用。文中介绍了一种利用ＬＡＮＤＳＡＴＴＭ资料进行非均匀陆面上区域能量平衡研究的参数化方案。并以夏季和深秋两个景的ＴＭ资料为个例，结合“黑河实验”（ＨＥＩＦＥ）期间的地面观测资料分析了实验区非均匀陆面上地表特征参数及能量平衡各分量的区域分布及季节差异，同时将所得的结果与地面观测的“真值”作了比较，所得的这些结果是基本可信的。这种方法仍然处于发展的初始阶段，对此也进行了讨论。

Parameterization of Heat Fluxes at Heterogeneous Surfaces by Integrating Satellite Measurements with Surface Layer and Atmospheric Boundary Layer Observations

The regional heat flux exchange between heterogeneous landscapes and the nearby surface layer （SL） is a key issue in the study of land-atmosphere interactions over arid areas such as the Heihe River basin in northwestern China and in high elevation areas such as the Tibetan Plateau. Based on analysis of the land surface heterogeneity and its effects on the overlying air flow, the use of SL observations, atmospheric boundary layer （ABL） observations, and satellite remote sensing （RS） measurements along with three parameterization methodologies （here, termed as the RS, tile, and blending approaches） have been proposed to estimate the surface heat flux densities over heterogeneous landscapes. The tile and blending approaches have also been implemented during HEIhe basin Field Experiment （HEIFE）, the Coordinated Enhanced Observing Period （CEOP） Asia-Australia Monsoon Project on the Tibetan Plateau （CAMP/Tibet）, the Arid Environment Comprehensive Monitoring Plan ＇95 （AECMP＇95）, and the DunHuang Experiment （DHEX）. The results showed that these two proposed parameterization methodologies can be accurately used over heterogeneous land surfaces.

High Elevation Energy and Water Balance:the Roles of Surface Albedo and Temperature

Observation and modeling of the coupled energy and water balance is the key to understand hydrospheric and cryospheric processes at high elevation.The paper summarizes the progress to address this aspect in relation with different earth system elements,from glaciers to wetlands.The energy budget of two glaciers,i.e.Xiao Dongkemadi and Parlung No.4,was studied by means of extended field measurements and a distributed model of the coupled energy and mass balance was developed and evaluated.The need for accurate characterization of surface albedo was further documented for the entire Qinghai Tibet Plateau by numerical experiments with Weather Research and Forecast(WRF)on the sensitivity of the atmospheric boundary layer to the parameterization of land surface processes.A new approach to the calibration of a coupled distributed watershed model of the energy and water balance was demonstrated by a case study on the Heihe River Basin in northwestern China.The assimilation of land surface temperature did lead to the retrieval of critical soil and vegetation properties as the soil permeability and the canopy resistance to the exchange of vapour and carbon dioxide.The retrievals of actual Evapo-Transpiration(ET)were generated by the ETMonitor system and evaluated against eddy covariance measurements at sites spread throughout Asia.As regards glacier response to climate variability,the combined findings based on satellite data and model experiments showed that the spatial variability of surface albedo and temperature is significant and controls both glacier mass balance and flow.Experiments with both atmospheric and hydrosphere-cryosphere models documented the need and advantages of using accurate retrievals of land surface albedo to capture lan-atmosphere interactions at high elevation.

Improved Parameterization of Snow Albedo in WRF+Noah:Methodology Based on a Severe Snow Event on the Tibetan Plateau

Snowfall and the subsequent evolution of the snowpack have a large effect on the surface energy balance and water cycle of the Tibetan Plateau(TP).The effects of snow cover can be represented by the WRF coupled with a land surface scheme.The widely used Noah scheme is computationally efficient,but its poor representation of albedo needs considerable improvement.In this study,an improved albedo scheme is developed using a satellite-retrieved albedo that takes snow depth and age into account.Numerical experiments were then conducted to simulate a severe snow event in March 2017.The performance of the coupled WRF/Noah model,which implemented the improved albedo scheme,is compared against the model’s performance using the default Noah albedo scheme and against the coupled WRF/CLM that applied CLM albedo scheme.When the improved albedo scheme is implemented,the albedo overestimation in the southeastern TP is reduced,reducing the RMSE of the air temperature by 0.7°C.The improved albedo scheme also attains the highest correlation between the satellite-derived and the model-estimated albedo,which provides for a realistic representation of both the snow water equivalent(SWE)spatial distribution in the heavy snowbelt(SWE>6 mm)and the maximum SWE in the eastern TP.The underestimated albedo in the coupled WRF/CLM leads to underestimating the regional maximum SWE and a consequent failure to estimate SWE in the heavy snowbelt accurately.Our study demonstrates the feasibility of improving the Noah albedo scheme and provides a theoretical reference for researchers aiming to improve albedo schemes further.

A scalable software package for time series reconstruction of remote sensing datasets on the Google Earth Engine platform

Spatiotemporal residual noise in terrestrial earth observation products,often caused by unfavorable atmospheric conditions,impedes their broad applications.Most users prefer to use gap-filled remote sensing products with time series reconstruction(TSR)algorithms.Applying currently available implementations of TSR to large-volume datasets is time-consuming and challenging for non-professional users with limited computation or storage resources.This study introduces a new open-source software package entitled‘HANTS-GEE’that implements a well-known and robust TSR algorithm,i.e.Harmonic ANalysis of Time Series(HANTS),on the Google Earth Engine(GEE)platform for scalable reconstruction of terrestrial earth observation data.Reconstruction tasks can be conducted on user-defined spatiotemporal extents when raw datasets are available on GEE.According to site-based and regional-based case evaluation,the new tool can effectively eliminate cloud contamination in the time series of earth observation data.Compared with traditional PC-based HANTS implementation,the HANTS-GEE provides quite consistent reconstruction results for most terrestrial vegetated sites.The HANTS-GEE can provide scalable reconstruction services with accelerated processing speed and reduced internet data transmission volume,promoting algorithm usage by much broader user communities.To our knowledge,the software package is thefirst tool to support full-stack TSR processing for popular open-access satellite sensors on cloud platforms.

Understanding spatial patterns in the drivers of greenness trends in the Sahel-Sudano-Guinean region

The region-wide spatial pattern of the drivers of vegetation trends in the African Sahel-Sudano-Guinean region, one of the main drylands of the world, has not been fully investigated. Time-series satellite earth observation datasets were used to investigate spatiotemporal patterns of the vegetation greenness changes in the region and then a principal component regression method was applied to identify the region-wide spatial pattern of driving factors. Results find that vegetation greening is widespread in the region, while vegetation browning is more clustered in central West Africa. The dominant drivers of vegetation greenness have a distinct spatial pattern. Climatic factors are the primary drivers, but the impacts of precipitation decrease from north to south, while the impacts of temperature are contrariwise. Coupled with climatic drivers, land cover changes lead to greening trends in the arid zone, especially in the western Sahelian belt. However, the cluster of browning trends in central West Africa can primarily be attributed to the human-induced land cover changes, including an increasing fractional abundance of agriculture. The results highlight the spatial pattern of climatic and anthropic factors driving vegetation greenness changes, which helps natural resources sustainable use and mitigation of climate change and human activities in global dryland ecosystems.

A prototype web-based analysis platform for drought monitoring and early warning

It has long been recognized that an effective drought monitoring and early warning system,which provides functions for real-time condition monitoring and prediction,risk assessment,information dissemination and response recommendation,is very important for the preparedness for and mitigation of drought impacts.In this article,we review the currently existing drought monitor and early warning systems,discuss applicable remote sensing datasets and drought indicators and present the development of a web-based quasi-real-time Global Drought Monitoring&Analysis Platform(Web-GDMAP).The Web-GDMAP is built upon a series of indicators derived from multi-source satellite remote sensing data and various other sources of data.From a technical perspective,the Web-GDMAP system includes a series of components from data storage,model implementation and distribution,to client-side visualization and user intuitive interaction.From a theoretical perspective,the Web-GDMAP system integrates multi-indicators on different aspects of drought,including anomalies in precipitation,anomalies in land surface thermal and vegetation conditions,water deficit of soil and plants,etc.Several case studies on applying the developed Web-GDMAP in the Asian region are demonstrated.Further improvements and perspectives are discussed.

Constructing dataset of classified drainage areas based on surface water-supply patterns in High Mountain Asia

The High Mountain Asia(HMA)region,ranging from the Hindu Kush and Tien Shan in thewest totheHimalaya inthe southwith an altitude between 2000 and 8844 m,holds the largest reservoir of glaciers and snow outside Earth Polar Regions.In the last decades,numerous glaciers and lake areas there have undergone tremendous changes with water redistribution.In order to increase understanding of the pattern of distribution of water resources,and their dynamic changes at the basin scale,a watershed classification based on the water replenishment patterns dataset was constructed.The input dataset are from the Randolph Glacier Inventory V.6.0 and the vector data of rivers and streams.Four datasets were thus obtained:Glacier-fed and Runoff-fed Drainage Area(GRDA),Glacier-fed and Runoff-free Drainage Area(GDA),Glacier-free and Runoff-fed Drainage Area(RDA),and the Glacier-free and Runoff-free Drainage Area(NGRDA),and the numbers of these four types of basins are 87,107,32,and 448 separately.The statistical results show GRDA has the largest surface area,accounting for 82.2%of the total basin area in HMA,mainly in the region of the basin with outflow rivers or streams.Dominated by small basins,the GDA area accounts for the smallest area,only 3.86%and the RDA accounts for 5.62%.For NGRDA,most are with small areas,accounting for 8.32%,and mainly distributes in the closed basin of the Qiangtang Plateau.This dataset provides a fundamental classified data source for research on water resources,climate,ecology,and environment in HMA.The published data are available at https://data.4tu.nl/download/uuid:d07d748f-d10b-4308-9626-199ef05cc9af/and http://www.dx.doi.org/10.11922/sciencedb.923.

Consistent nighttime light time series in 1992–2020 in Northern Africa by combining DMSP-OLS and NPP-VIIRS data

Human activities modulate the impact of environmental forcing in general and of climate in particular.Information on the spatial and temporal patterns of human activities is in high demand,but scarce in sparsely populated and data-poor regions such as Northern Africa.The intensity and spatial distribution of nighttime lights provide useful information on human activities and can be observed by space-borne imaging radiometers.Our study helps to bridge the gap between the DMSP-OLS data available until 2013 and the NPP-VIIRS data available since 2013.The approach to calibrate the OLS data includes three steps:a)inter-calibrate the OLS DN data acquired by different sensors in 1992-2013;b)cali-brate the OLS DN data using VIIRS data in 2013;c)generate syn-thetic OLS radiance data by degrading the VIIRS data in 2013-2020.We generated a)a time series of calibrated OLS nighttime light radiance data(1992-2013);b)mean annual VIIRS radiance on stable lights at the OLS spatial resolution for 2013-2020;c)synthetic OLS radiance data generated using VIIRS radiance data degraded to match the radiometric specifications of OLS for 2013-2020.The evaluation of these data products in 2013 documented their accu-racy and consistency.

The Digital Belt and Road program in support of regional sustainability

The Belt and Road initiative has a significant focus on infrastructure,trade,and economic development across a vast region,and it also provides significant opportunities for sustainable development.The combined pressure of climate variability,intensified use of resources,and the fragility of ecosystems make it very challenging,however,to achieve future sustainability.To develop the path in a sustainable way,it is important to have a comprehensive understanding of these issues across nations and evaluate them in a scientific and well-informed approach.In this context,the Digital Belt and Road(DBAR)program was initiated as an international venture to share expertise,knowledge,technologies,and data to demonstrate the role of Earth observation science and technology and big Earth data applications to support large-scale development.In this paper,we identify pressing challenges,present the research priorities and foci of the DBAR program,and propose solutions where big Earth data can make significant contributions.This paper calls for further joint actions and collaboration to build a digital silk road in support of sustainable development at national,regional and global levels.