scholarly journals Evaluation of Parameterizations of Incoming Longwave Radiation in the High-Mountain Region of the Tibetan Plateau

2017 ◽  
Vol 56 (4) ◽  
pp. 833-848 ◽  
Author(s):  
Meilin Zhu ◽  
Tandong Yao ◽  
Wei Yang ◽  
Baiqing Xu ◽  
Xiaojun Wang
Keyword(s):  
Tibetan Plateau ◽  
Longwave Radiation ◽  
Cloud Base ◽  
High Mountain ◽  
The Tibetan Plateau ◽  
Mountain Regions ◽  
Local Conditions ◽  
Clear Sky ◽  
The Difference ◽  
Study Sites

AbstractAccurate evaluations of incoming longwave radiation (Lin) parameterization have practical implications for glacier and river runoff changes in high-mountain regions of the Tibetan Plateau (TP). To identify potential means of accurately predicting spatiotemporal variations in Lin, 13 clear-sky parameterizations combined with 10 cloud corrections for all-sky atmospheric emissivity were evaluated at five sites in high-mountain regions of the TP through temporal and spatial parameter transfer tests. Most locally calibrated parameterizations for clear-sky and all-sky conditions performed well when applied to the calibration site. The best parameterization at five sites is Dilley and O’Brien’s A model combined with Sicart et al.’s A for cloud-correction-incorporated relative humidity. The performance of parameter transferability in time is better than that in space for the same all-sky parameterizations. The performance of parameter transferability in space presents spatial discrepancies. In addition, all all-sky parameterizations show a decrease in performance with increasing altitude regardless of whether the parameters of all-sky parameterizations were recalibrated by local conditions or transferred from other study sites. This may be attributable to the difference between screen-level air temperature and the effective atmospheric boundary layer temperature and to different cloud-base heights. Nevertheless, such worse performance at higher altitudes is likely to change because of terrain, underlying surfaces, and wind systems, among other factors. The study also describes possible spatial characteristics of Lin and its driving factors by reviewing the few studies about Lin for the mountain regions of the TP.

scholarly journals A revisit of parametrization of summer downward longwave radiation over the Tibetan Plateau from high temporal resolution measurements

2019 ◽  
Author(s):  
Mengqi Liu ◽  
Xiangdong Zheng ◽  
Jinqiang Zhang ◽  
Xiangao Xia
Keyword(s):  
Tibetan Plateau ◽  
Temporal Resolution ◽  
Longwave Radiation ◽  
Surface Energy Budget ◽  
Coefficient Of Determination ◽  
Cloud Base ◽  
High Temporal Resolution ◽  
The Tibetan Plateau ◽  
Clear Sky ◽  
Downward Longwave Radiation

Abstract. The Tibetan Plateau (TP) is one of hot spots in the climate research due to its unique geographical location, high altitude, highly sensitive to climate change as well potential effects on climate in East Asia. Downward longwave radiation (DLR), as a key component in the surface energy budget, is of practical implications for many research fields. Several attempts have been made to measure hourly or daily DLR and then model it over the TP. This study uses 1-minute radiation and meteorological measurements at three stations over the TP to parameterize DLR during summer months. Three independent methods are used to discriminate clear-sky observations by making maximal use of collocated measurements of downward shortwave and longwave radiation as well as Lidar backscatter measurements with high temporal resolution. This guarantees a reliable separation of clear-sky and cloudy samples that favors for proper parameterizations of DLR under these two contrast conditions. Clear-sky and cloudy DLR models with original parameters are firstly assessed. These models are then locally calibrated based on 1-minute observations. DLR estimation is notably improved since specific conditions over the TP are accounted for by local calibration, which is indicated by smaller root mean square error (RMSE) and larger coefficient of determination (R2). The best local parametrization can estimate clear-sky DLR with RMSE of 3.8 W⸱m-2. Overestimation of clear-sky DLR by previous study is evident, likely due to potential residue cloud contamination on the clear-sky samples. Cloud base height under overcast conditions is shown to be intimately related to cloudy DLR parameterization, which is considered by this study in the locally calibrated parameterization over the TP for the first time.

scholarly journals A revisiting of the parametrization of downward longwave radiation in summer over the Tibetan Plateau based on high-temporal-resolution measurements

2020 ◽  
Vol 20 (7) ◽  
pp. 4415-4426 ◽  
Author(s):  
Mengqi Liu ◽  
Xiangdong Zheng ◽  
Jinqiang Zhang ◽  
Xiangao Xia
Keyword(s):  
Climate Change ◽  
Tibetan Plateau ◽  
Longwave Radiation ◽  
Radiation Budget ◽  
Cloud Base ◽  
The Tibetan Plateau ◽  
Climate Change Research ◽  
Clear Sky ◽  
Downward Longwave Radiation ◽  
Mean Square Errors

Abstract. The Tibetan Plateau (TP) is one of the research hot spots in the climate change research due to its unique geographical location and high altitude. Downward longwave radiation (DLR), as a key component in the surface energy budget, has practical implications for radiation budget and climate change. A couple of attempts have been made to parametrize DLR over the TP based on hourly or daily measurements and crude clear-sky discrimination methods. This study uses 1 min shortwave and longwave radiation measurements at three stations over the TP to parametrize DLR during summer months. Three independent methods are used to discriminate clear sky from clouds based on 1 min radiation and lidar measurements. This guarantees the strict selection of clear-sky samples that is fundamental for the parametrization of clear-sky DLR. A total of 11 clear-sky and 4 cloudy DLR parametrizations are examined and locally calibrated. Compared to previous studies, DLR parametrizations here are shown to be characterized by smaller root-mean-square errors (RMSEs) and higher coefficients of determination (R2). Clear-sky DLR can be estimated from the best parametrization with a RMSE of 3.8 W m−2 and R2>0.98. Systematic overestimation of clear-sky DLR by the locally calibrated parametrization in one previous study is found to be approximately 25 W m−2 (10 %), which is very likely due to potential residual cloud contamination on previous clear-sky DLR parametrization. The cloud base height under overcast conditions is shown to play an important role in cloudy DLR parametrization, which is considered in the locally calibrated parametrization over the TP for the first time. Further studies on DLR parametrization during nighttime and in seasons except summer are required for our better understanding of the role of DLR in climate change.

Estimation of All-weather Downward Longwave Radiation over the Tibetan Plateau

2021 ◽  
Author(s):  
Lirong Ding ◽  
Zhiyong Long ◽  
Ji Zhou ◽  
Shaofei Wang ◽  
Xiaodong Zhang
Keyword(s):  
Climate Change ◽  
Tibetan Plateau ◽  
Energy Budget ◽  
Water Cycle ◽  
Longwave Radiation ◽  
Radiation Balance ◽  
The Tibetan Plateau ◽  
Clear Sky ◽  
Downward Longwave Radiation ◽  
Sky Conditions

<p>The downward longwave radiation (DLR) is a critical parameter for radiation balance, energy budget, and water cycle studies at regional and global scales. The accurate estimation of the all-weather DLR with a high temporal resolution is important for the estimation of the surface net radiation and evapotranspiration. However, the most DLR products involve instantaneous DLR estimates based on polar orbiting satellite data under clear-sky conditions. To obtain an in-depth understanding of the performances of different models in the estimation of the DLR over the Tibetan Plateau, which is a focus area of climate change study, this study tested eight methods under clear-sky conditions and six methods under cloudy conditions based on ground-measured data. The results show that the Dilley and O’Brien model and the Lhomme model are most suitable under clear-sky conditions and cloudy conditions, respectively. For the Dilley and O’Brien model, the average root mean square error (RMSE) of the DLR under clear-sky conditions is approximately 22.5 W/m<sup>2</sup> at nine ground sites; for the Lhomme model, the average RMSE is approximately 23.2 W/m<sup>2</sup>. Based on the estimated cloud fraction and meteorological data provided by the China land surface data assimilation system (CLDAS), the hourly all-weather daytime DLR with 0.0625° over the Tibetan Plateau was estimated. The results show that the average RMSE of the estimated hourly all-weather DLR was approximately 26.4 W/m<sup>2</sup>. With the combined all-weather DLR model, the hourly all-weather daytime DLR dataset with a 0.0625° resolution from 2008 to 2016 over the Tibetan Plateau was generated. This dataset can better contribute to studies associated with the radiation balance and energy budget, water cycle, and climate change over the Tibetan Plateau.</p>

Estimation of surface upward longwave radiation from MODIS and VIIRS clear-sky data in the Tibetan Plateau

2015 ◽  
Vol 162 ◽  
pp. 221-237 ◽  
Author(s):  
Zhonghu Jiao ◽  
Guangjian Yan ◽  
Jing Zhao ◽  
Tianxing Wang ◽  
Ling Chen
Keyword(s):  
Tibetan Plateau ◽  
Longwave Radiation ◽  
The Tibetan Plateau ◽  
Clear Sky

scholarly journals Glacier changes on the Tibetan Plateau derived from Landsat imagery: mid-1970s – 2000–13

2017 ◽  
Vol 63 (238) ◽  
pp. 273-287 ◽  
Author(s):  
QINGHUA YE ◽  
JIBIAO ZONG ◽  
LIDE TIAN ◽  
J. GRAHAM COGLEY ◽  
CHUNQIAO SONG ◽  
...  
Keyword(s):  
Tibetan Plateau ◽  
Landsat Imagery ◽  
Google Earth ◽  
The Tibetan Plateau ◽  
Glacier Area ◽  
Drainage Basins ◽  
Glacier Inventory ◽  
The Difference ◽  
Study Sites ◽  
Landsat Satellite

ABSTRACTGlacier area changes on the Tibetan Plateau were studied in different drainage basins based on Landsat satellite images from three epochs: 263 in the mid-1970s, 150 in 1999–2002 and 148 in 2013/14. Three mosaics (M1976, M2001 and M2013) with minimal cloud and snow cover were constructed, and the uncertainty due to each epoch having a finite span was accounted for. Glacier outlines (TPG1976, TPG2001 and TPG2013) were digitized manually with guidance from the SRTM DEM v4.1 and Google Earth imagery. To achieve complete multi-temporal coverage in a reasonable time, only debris-free ice was delineated. Area mapping uncertainty was evaluated at three study sites, Mount Qomolangma (Everest), Mount Naimona'Nyi, Mount Geladandong, where the largest differences between present and earlier measurements were within ~±4%. Area differences with previous inventories ranged from −19.6% (TPG1976 minus the first Chinese Glacier Inventory) to −3.6% and −1.1% (TPG2013 and TPG2001, respectively minus the second Chinese Glacier Inventory), while the difference TPG2001 minus the GAMDAM Glacier Inventory was +10.4%. Glacier area on the plateau decreased from 44 366 ± 2827 km2 (1.7% of the study area) in the 1970s to 42 210 ± 1621 km2 in 2001 and 41 137 ± 1616 km2 in 2013. Shrinkage was faster in external drainage basins of the southeast than in the interior basins of the northwest, from a maximum of −0.43% a−1 (−1.60% a−1 during 1994–2013) in the Mekong catchment down to a minimum of −0.12% a−1 in the Tarim interior drainage.

Remote sensing-based river discharge estimation for a small river flowing over the high mountain regions of the Tibetan Plateau

2020 ◽  
Author(s):  
Mulugeta Genanu Kebede ◽  
Lei Wang ◽  
Xiuping Li ◽  
Zhidan Hu
Keyword(s):  
Remote Sensing ◽  
Tibetan Plateau ◽  
River Discharge ◽  
Equation Model ◽  
High Mountain ◽  
The Tibetan Plateau ◽  
Mountain Regions ◽  
Discharge Estimation ◽  
Academy Of Sciences ◽  
Beijing China

<p><strong>Remote sensing-based river discharge estimation for a small river flowing over the high mountain regions of the Tibetan Plateau </strong></p><p>Mulugeta Genanu Kebede <sup>1, 2, 3</sup>, Lei Wang<sup>1, 2*</sup>, Xiuping Li<sup>1</sup> and Zhidan Hu<sup>4</sup></p><p><sup>1 </sup>Key Laboratory of Tibetan Environment Changes and Land Surface Processes, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, and CAS Center for Excellence in Tibetan Plateau Earth Sciences, Beijing, China</p><p><sup>2 </sup>University of Chinese Academy of Sciences, Beijing, China</p><p><sup>3 </sup>Arba Minch University, Water Technology Institute, Faculty of Meteorology and Hydrology, Arba Minch, Ethiopia</p><p><sup>4 </sup>Information Center, Ministry of Water Resources, Beijing 100053, China</p><p><strong>* </strong>Correspondence to: Dr. Lei Wang, Professor</p><p>Email: [email protected];     Tel.: +86-10-8409-7107; Fax: +86-10-8409-7079</p><p><strong>ABSTRACT</strong></p><p>River discharge, as one of the most essential climate variables, plays a vital role in the water cycle. Small-scale headwater catchments including high-mountain regions of Tibetan Plateau (TP) Rivers are mostly ungauged. Satellite technology shows its potential to fill this gap with high correlation of satellite-derived effective river width and corresponding in-situ gauged discharge. This study is innovative in estimating daily river discharge using modified Manning equation (Model 1), Bjerklie equation (Model 2), and Rating curve approach (Model 3) by combining river surface hydraulic variables directly derived from remote sensing datasets with other variables indirectly derived from empirical equations, which greatly contributes to the improvement of river flow measurement information especially over small rivers of TP. We extracted the effective width from Landsat image and flow depth via hydraulic geometry approach. All the input parameters directly or indirectly derived from remote sensing were combined and substituted into the fundamental flow equations/models to estimate discharges of Lhasa River. The validation of all three models’ results against the in-situ discharge measurements shows a strong correlation (the Nash–Sutcliffe efficiency coefficient (NSE) and the coefficient of determination (R<sup>2</sup>) values ≥ 0.993), indicating the potentiality of the models in accurately estimating daily river discharges. Trends of an overestimation of discharge by Model 1 and underestimation by Model 2 are observed. The discharge estimation by using Model 3 outperforms Model 1 and Model 2 due to the uncertainties associated with estimation of input parameters in the other two models. Generally, our discharge estimation methodology performs well and shows a superior result as compared with previously developed multivariate empirical equations and its application for other places globally can be the focus of upcoming studies.    </p><p><strong>Keywords:</strong> River discharge estimation, remote sensing, effective width, hydraulic relationship, Tibetan Plateau</p>

scholarly journals Toward the Estimation of All-Weather Daytime Downward Longwave Radiation over the Tibetan Plateau

Atmosphere ◽  
2021 ◽  
Vol 12 (12) ◽  
pp. 1692
Author(s):  
Zhiyong Long ◽  
Lirong Ding ◽  
Ji Zhou ◽  
Tianhao Zhou
Keyword(s):  
Climate Change ◽  
Tibetan Plateau ◽  
Energy Budget ◽  
Water Cycle ◽  
Longwave Radiation ◽  
Radiation Balance ◽  
The Tibetan Plateau ◽  
Clear Sky ◽  
Downward Longwave Radiation ◽  
Sky Conditions

Downward longwave radiation (DLR) is a critical parameter for radiation balance, energy budget, and water cycle studies at regional and global scales. Accurate estimation of the all-weather DLR with a high temporal resolution is important for the estimation of the surface net radiation and evapotranspiration. However, most DLR products involve instantaneous DLR estimates based on polar orbiting satellite data under clear-sky conditions. To obtain an in-depth understanding of the performances of different models in the estimation of DLR over the Tibetan Plateau, which is a focus area of climate change study, this study tests eight methods for clear-sky conditions and six methods for cloudy conditions based on ground-measured data. It is found that the Dilley and O’Brien model and the Lhomme model are most suitable for clear-sky conditions and cloudy conditions, respectively. For the Dilley and O’Brien model, the average root mean square error (RMSE) of DLR under clear-sky conditions is approximately 22.5 W/m2 for nine ground sites; for the Lhomme model, the average RMSE is approximately 23.2 W/m2. Based on the estimated cloud fraction and meteorological data provided by the China Land Surface Data Assimilation System (CLDAS), hourly all-weather daytime DLR with a 0.0625° resolution over the Tibetan Plateau is estimated. Results demonstrate that the average RMSE of the estimated hourly all-weather DLR is approximately 26.4 W/m2. With the combined all-weather DLR model, the hourly all-weather daytime DLR dataset with a 0.0625° resolution from 2008 to 2016 over the Tibetan Plateau is generated. This dataset can contribute to studies associated with the radiation balance and energy budget, water cycle, and climate change over the Tibetan Plateau.

scholarly journals Spatiotemporal patterns of High Mountain Asia's snowmelt season identified with an automated snowmelt detection algorithm, 1987–2016

2017 ◽  
Vol 11 (5) ◽  
pp. 2329-2343 ◽  
Author(s):  
Taylor Smith ◽  
Bodo Bookhagen ◽  
Aljoscha Rheinwalt
Keyword(s):  
Time Series ◽  
Tibetan Plateau ◽  
Climate Model ◽  
Single Point ◽  
Passive Microwave ◽  
Spatiotemporal Patterns ◽  
Signal Separation ◽  
High Mountain ◽  
The Tibetan Plateau ◽  
Microwave Data

Abstract. High Mountain Asia (HMA) – encompassing the Tibetan Plateau and surrounding mountain ranges – is the primary water source for much of Asia, serving more than a billion downstream users. Many catchments receive the majority of their yearly water budget in the form of snow, which is poorly monitored by sparse in situ weather networks. Both the timing and volume of snowmelt play critical roles in downstream water provision, as many applications – such as agriculture, drinking-water generation, and hydropower – rely on consistent and predictable snowmelt runoff. Here, we examine passive microwave data across HMA with five sensors (SSMI, SSMIS, AMSR-E, AMSR2, and GPM) from 1987 to 2016 to track the timing of the snowmelt season – defined here as the time between maximum passive microwave signal separation and snow clearance. We validated our method against climate model surface temperatures, optical remote-sensing snow-cover data, and a manual control dataset (n = 2100, 3 variables at 25 locations over 28 years); our algorithm is generally accurate within 3–5 days. Using the algorithm-generated snowmelt dates, we examine the spatiotemporal patterns of the snowmelt season across HMA. The climatically short (29-year) time series, along with complex interannual snowfall variations, makes determining trends in snowmelt dates at a single point difficult. We instead identify trends in snowmelt timing by using hierarchical clustering of the passive microwave data to determine trends in self-similar regions. We make the following four key observations. (1) The end of the snowmelt season is trending almost universally earlier in HMA (negative trends). Changes in the end of the snowmelt season are generally between 2 and 8 days decade−1 over the 29-year study period (5–25 days total). The length of the snowmelt season is thus shrinking in many, though not all, regions of HMA. Some areas exhibit later peak signal separation (positive trends), but with generally smaller magnitudes than trends in snowmelt end. (2) Areas with long snowmelt periods, such as the Tibetan Plateau, show the strongest compression of the snowmelt season (negative trends). These trends are apparent regardless of the time period over which the regression is performed. (3) While trends averaged over 3 decades indicate generally earlier snowmelt seasons, data from the last 14 years (2002–2016) exhibit positive trends in many regions, such as parts of the Pamir and Kunlun Shan. Due to the short nature of the time series, it is not clear whether this change is a reversal of a long-term trend or simply interannual variability. (4) Some regions with stable or growing glaciers – such as the Karakoram and Kunlun Shan – see slightly later snowmelt seasons and longer snowmelt periods. It is likely that changes in the snowmelt regime of HMA account for some of the observed heterogeneity in glacier response to climate change. While the decadal increases in regional temperature have in general led to earlier and shortened melt seasons, changes in HMA's cryosphere have been spatially and temporally heterogeneous.

scholarly journals Understanding precipitation recycling over the Tibetan Plateau using tracer analysis with WRF

2020 ◽  
Vol 55 (9-10) ◽  
pp. 2921-2937
Author(s):  
Yanhong Gao ◽  
Fei Chen ◽  
Gonzalo Miguez-Macho ◽  
Xia Li
Keyword(s):  
Tibetan Plateau ◽  
Land Surface ◽  
Precipitation Amount ◽  
Interaction Strength ◽  
Convective Precipitation ◽  
High Mountain ◽  
The Tibetan Plateau ◽  
Important Indicator ◽  
Precipitation Recycling ◽  
Atmosphere Interaction

Abstract The precipitation recycling (PR) ratio is an important indicator that quantifies the land-atmosphere interaction strength in the Earth system’s water cycle. To better understand how the heterogeneous land surface in the Tibetan Plateau (TP) contributes to precipitation, we used the water-vapor tracer (WVT) method coupled with the Weather Research and Forecasting (WRF) regional climate model. The goals were to quantify the PR ratio, in terms of annual mean, seasonal variability and diurnal cycle, and to address the relationships of the PR ratio with lake treatments and precipitation amount. Simulations showed that the PR ratio increases from 0.1 in winter to 0.4 in summer when averaged over the TP with the maxima centered at the headwaters of three major rivers (Yangtze, Yellow and Mekong). For the central TP, the highest PR ratio rose to over 0.8 in August, indicating that most of the precipitation was recycled via local evapotranspiration in summer. The larger daily mean and standard deviation of the PR ratio in summer suggested a stronger effect of land-atmosphere interactions on precipitation in summer than in winter. Despite the relatively small spatial extent of inland lakes, the treatment of lakes in WRF significantly impacted the calculation of the PR ratio over the TP, and correcting lake temperature substantially improved both precipitation and PR ratio simulations. There was no clear relationship between PR ratio and precipitation amount; however, a significant positive correlation between PR and convective precipitation was revealed. This study is beneficial for the understanding of land-atmosphere interaction over high mountain regions.

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