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.

scholarly journals Land-surface processes and summer-cloud-precipitation characteristics in the Tibetan Plateau and their effects on downstream weather: a review and perspective

2020 ◽  
Vol 7 (3) ◽  
pp. 500-515 ◽  
Author(s):  
Yunfei Fu ◽  
Yaoming Ma ◽  
Lei Zhong ◽  
Yuanjian Yang ◽  
Xueliang Guo ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Tibetan Plateau ◽  
Land Surface ◽  
Sensible Heat Flux ◽  
Vertical Direction ◽  
Heat Fluxes ◽  
Surface Processes ◽  
Convective Precipitation ◽  
The Tibetan Plateau ◽  
Land Surface Processes

Abstract Correct understanding of the land-surface processes and cloud-precipitation processes in the Tibetan Plateau (TP) is an important prerequisite for the study and forecast of the downstream activities of weather systems and one of the key points for understanding the global atmospheric movement. In order to show the achievements that have been made, this paper reviews the progress on the observations for the atmospheric boundary layer, land-surface heat fluxes, cloud-precipitation distributions and vertical structures by using ground- and space-based multiplatform, multisensor instruments and the effect of the cloud system in the TP on the downstream weather. The results show that the form drag related to the topography, land–atmosphere momentum and scalar fluxes is an important part of the parameterization process. The sensible heat flux decreased especially in the central and northern TP caused by the decrease in wind speeds and the differences in the ground-air temperatures. Observations show that the cloud and precipitation over the TP have a strong diurnal variation. Studies also show the compressed-air column in the troposphere by the higher-altitude terrain of the TP makes particles inside clouds vary at a shorter distance in the vertical direction than those in the non-plateau area so that precipitation intensity over the TP is usually small with short duration, and the vertical structure of the convective precipitation over the TP is obviously different from that in other regions. In addition, the influence of the TP on severe weather downstream is preliminarily understood from the mechanism. It is necessary to use model simulations and observation techniques to reveal the difference between cloud precipitation in the TP and non-plateau areas in order to understand the cloud microphysical parameters over the TP and the processes of the land boundary layer affecting cloud, precipitation and weather in the downstream regions.

Recent Trends in Land Surface Temperature on the Tibetan Plateau

2006 ◽  
Vol 19 (12) ◽  
pp. 2995-3003 ◽  
Author(s):  
Yuichiro Oku ◽  
Hirohiko Ishikawa ◽  
Shigenori Haginoya ◽  
Yaoming Ma
Keyword(s):  
Tibetan Plateau ◽  
Surface Temperature ◽  
Air Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Precipitation Amount ◽  
Surface Air Temperature ◽  
The Tibetan Plateau ◽  
Near Surface ◽  
Diurnal Range

Abstract The diurnal, seasonal, and interannual variations in land surface temperature (LST) on the Tibetan Plateau from 1996 to 2002 are analyzed using the hourly LST dataset obtained by Japanese Geostationary Meteorological Satellite 5 (GMS-5) observations. Comparing LST retrieved from GMS-5 with independent precipitation amount data demonstrates the consistent and complementary relationship between them. The results indicate an increase in the LST over this period. The daily minimum has risen faster than the daily maximum, resulting in a narrowing of the diurnal range of LST. This is in agreement with the observed trends in both global and plateau near-surface air temperature. Since the near-surface air temperature is mainly controlled by LST, this result ensures a warming trend in near-surface air temperature.

scholarly journals Impact of Initialized Land Surface Temperature and Snowpack on Subseasonal to Seasonal Prediction Project, Phase I (LS4P-I): Organization and Experimental design

2021 ◽  
Author(s):  
Yongkang Xue ◽  
Tandong Yao ◽  
Aaron A. Boone ◽  
Ismaila Diallo ◽  
Ye Liu ◽  
...  
Keyword(s):  
Tibetan Plateau ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Large Scale ◽  
Initial Conditions ◽  
Yangtze River Basin ◽  
Seasonal Prediction ◽  
High Mountain ◽  
The Tibetan Plateau

Abstract. Sub-seasonal to seasonal (S2S) prediction, especially the prediction of extreme hydroclimate events such as droughts and floods, is not only scientifically challenging but has substantial societal impacts. Motivated by preliminary studies, the Global Energy and Water Exchanges (GEWEX)/Global Atmospheric System Study (GASS) has launched a new initiative called Impact of initialized Land Surface temperature and Snowpack on Sub-seasonal to Seasonal Prediction (LS4P), as the first international grass-root effort to introduce spring land surface temperature (LST)/subsurface temperature (SUBT) anomalies over high mountain areas as a crucial factor that can lead to significant improvement in precipitation prediction through the remote effects of land/atmosphere interactions. LS4P focuses on process understanding and predictability, hence it is different from, and complements, other international projects that focus on the operational S2S prediction. More than forty groups worldwide have participated in this effort, including 21 Earth System Models, 9 regional climate models, and 7 data groups. This paper overviews the history and objectives of LS4P, provides the first phase experimental protocol (LS4P-I) which focuses on the remote effect of the Tibetan Plateau, discusses the LST/SUBT initialization, and presents the preliminary results. Multi-model ensemble experiments and analyses of observational data have revealed that the hydroclimatic effect of the spring LST in the Tibetan Plateau is not limited to the Yangtze River basin but may have a significant large-scale impact on summer precipitation and its S2S prediction. LS4P models are unable to preserve the initialized LST anomalies in producing the observed anomalies largely for two main reasons: i) inadequacies in the land models arising from total soil depths which are too shallow and the use of simplified parameterizations which both tend to limit the soil memory; and ii) reanalysis data, that are used for initial conditions, have large discrepancies from the observed mean state and anomalies of LST over the Tibetan Plateau. Innovative approaches have been developed to largely overcome these problems.

scholarly journals Impact of Initialized Land Surface Temperature and Snowpack on Subseasonal to Seasonal Prediction Project, Phase I (LS4P-I): organization and experimental design

2021 ◽  
Vol 14 (7) ◽  
pp. 4465-4494
Author(s):  
Yongkang Xue ◽  
Tandong Yao ◽  
Aaron A. Boone ◽  
Ismaila Diallo ◽  
Ye Liu ◽  
...  
Keyword(s):  
Tibetan Plateau ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Large Scale ◽  
Initial Conditions ◽  
Yangtze River Basin ◽  
Seasonal Prediction ◽  
High Mountain ◽  
The Tibetan Plateau

Abstract. Subseasonal-to-seasonal (S2S) prediction, especially the prediction of extreme hydroclimate events such as droughts and floods, is not only scientifically challenging, but also has substantial societal impacts. Motivated by preliminary studies, the Global Energy and Water Exchanges (GEWEX)/Global Atmospheric System Study (GASS) has launched a new initiative called “Impact of Initialized Land Surface Temperature and Snowpack on Subseasonal to Seasonal Prediction” (LS4P) as the first international grass-roots effort to introduce spring land surface temperature (LST)/subsurface temperature (SUBT) anomalies over high mountain areas as a crucial factor that can lead to significant improvement in precipitation prediction through the remote effects of land–atmosphere interactions. LS4P focuses on process understanding and predictability, and hence it is different from, and complements, other international projects that focus on the operational S2S prediction. More than 40 groups worldwide have participated in this effort, including 21 Earth system models, 9 regional climate models, and 7 data groups. This paper provides an overview of the history and objectives of LS4P, provides the first-phase experimental protocol (LS4P-I) which focuses on the remote effect of the Tibetan Plateau, discusses the LST/SUBT initialization, and presents the preliminary results. Multi-model ensemble experiments and analyses of observational data have revealed that the hydroclimatic effect of the spring LST on the Tibetan Plateau is not limited to the Yangtze River basin but may have a significant large-scale impact on summer precipitation beyond East Asia and its S2S prediction. Preliminary studies and analysis have also shown that LS4P models are unable to preserve the initialized LST anomalies in producing the observed anomalies largely for two main reasons: (i) inadequacies in the land models arising from total soil depths which are too shallow and the use of simplified parameterizations, which both tend to limit the soil memory; (ii) reanalysis data, which are used for initial conditions, have large discrepancies from the observed mean state and anomalies of LST over the Tibetan Plateau. Innovative approaches have been developed to largely overcome these problems.

Trends of land surface heat fluxes on the Tibetan Plateau from 2001 to 2012

2017 ◽  
Vol 37 (14) ◽  
pp. 4757-4767 ◽  
Author(s):  
Cunbo Han ◽  
Yaoming Ma ◽  
Xuelong Chen ◽  
Zhongbo Su
Keyword(s):  
Tibetan Plateau ◽  
Land Surface ◽  
Surface Heat ◽  
Heat Fluxes ◽  
The Tibetan Plateau ◽  
Surface Heat Fluxes ◽  
Land Surface Heat Fluxes

scholarly journals Atmospheric Thermal and Dynamic Vertical Structures of Summer Hourly Precipitation in Jiulong of the Tibetan Plateau

Atmosphere ◽  
2021 ◽  
Vol 12 (4) ◽  
pp. 505
Author(s):  
Yonglan Tang ◽  
Guirong Xu ◽  
Rong Wan ◽  
Xiaofang Wang ◽  
Junchao Wang ◽  
...  
Keyword(s):  
Wind Speed ◽  
Tibetan Plateau ◽  
Precipitation Amount ◽  
Summer Precipitation ◽  
The Tibetan Plateau ◽  
Hourly Precipitation ◽  
Air Convection ◽  
Precipitation Variation ◽  
Long Term Observation

It is an important to study atmospheric thermal and dynamic vertical structures over the Tibetan Plateau (TP) and their impact on precipitation by using long-term observation at representative stations. This study exhibits the observational facts of summer precipitation variation on subdiurnal scale and its atmospheric thermal and dynamic vertical structures over the TP with hourly precipitation and intensive soundings in Jiulong during 2013–2020. It is found that precipitation amount and frequency are low in the daytime and high in the nighttime, and hourly precipitation greater than 1 mm mostly occurs at nighttime. Weak precipitation during the daytime may be caused by air advection, and strong precipitation at nighttime may be closely related with air convection. Both humidity and wind speed profiles show obvious fluctuation when precipitation occurs, and the greater the precipitation intensity, the larger the fluctuation. Moreover, the fluctuation of wind speed is small in the morning, large at noon and largest at night, presenting a similar diurnal cycle to that of convective activity over the TP, which is conductive to nighttime precipitation. Additionally, the inverse layer is accompanied by the inverse humidity layer, and wind speed presents multi-peaks distribution in its vertical structure. Both of these are closely related with the underlying surface and topography of Jiulong. More studies on physical mechanism and numerical simulation are necessary for better understanding the atmospheric phenomenon over the TP.

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 Uncertainty and Variation of Remotely Sensed Lake Ice Phenology across the Tibetan Plateau

2018 ◽  
Vol 10 (10) ◽  
pp. 1534 ◽  
Author(s):  
Linan Guo ◽  
Yanhong Wu ◽  
Hongxing Zheng ◽  
Bing Zhang ◽  
Junsheng Li ◽  
...  
Keyword(s):  
Tibetan Plateau ◽  
Land Surface ◽  
Regional Climate ◽  
Local Environment ◽  
Remotely Sensed ◽  
The Tibetan Plateau ◽  
Remotely Sensed Data ◽  
Lake Ice ◽  
Reflectance Data ◽  
Ice Phenology

In the Tibetan Plateau (TP), the changes of lake ice phenology not only reflect regional climate change, but also impose substantial ecohydrological impacts on the local environment. Due to the limitation of ground observation, remote sensing has been used as an alternative tool to investigate recent changes of lake ice phenology. However, uncertainties exist in the remotely sensed lake ice phenology owing to both the data and methods used. In this paper, three different remotely sensed datasets are used to investigate the lake ice phenology variation in the past decade across the Tibetan Plateau, with the consideration of the underlying uncertainties. The remotely sensed data used include reflectance data, snow product, and land surface temperature (LST) data of moderate resolution imaging spectroradiometer (MODIS). The uncertainties of the three methods based on the corresponding data are assessed using the triple collocation approach. Comparatively, it is found that the method based on reflectance data outperforms the other two methods. The three methods are more consistent in determining the thawing dates rather than the freezing dates of lake ice. It is consistently shown by the three methods that the ice-covering duration in the northern part of the TP lasts longer than that in the south. Though there is no general trend of lake ice phenology across the TP for the period of 2000–2015, the warmer climate and stronger wind have led to the earlier break-up of lake ice.

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