Abstract:Turbulence measurements at 3 m performed at the base camp of Mt. Everest during the spring of 2005 were used to study the atmospheric turbulent characteristics under conditions of down-slope ambient wind (katabatic wind). The cases where large-scale forcing resulted in a down-slope ambient wind were considered. Firstly, the normalized standard deviations of wind speed (u and v components) were larger than those reported in the literature. Then the (co)spectral characteristics of turbulence under near neutral s… Show more
“…Everest. Southwesterly winds near the surface prevail during the monsoon season, while in other seasons northeasterly winds prevail (Ma et al, 2011;Li et al, 2012). EVK2-CNR station in Nepal (Table 1, Fig.…”
Abstract. The Himalaya mountains along the southern edge of the Tibetan Plateau act as a natural barrier for the transport of atmospheric aerosols from the polluted regions of South Asia to the main body of the Tibetan Plateau. In this study, we investigate the seasonal and diurnal variations of aerosol optical properties measured at two Aerosol Robotic Network (AERONET) sites on the southern side of the Himalaya (Pokhara, 812 m above sea level (a.s.l.) and EVK2-CNR, 5079 m a.s.l. in Nepal) and one on the northern side (Qomolangma (Mt. Everest) station for Atmospheric and Environmental Observation and Research, Chinese Academy of Sciences (QOMS_CAS) in Tibet, 4076 m a.s.l. in China). While observations at QOMS_CAS and EVK2-CNR can generally be representative of a remote background atmosphere, Pokhara is a lower-elevation suburban site with much higher aerosol load due to both the influence of local anthropogenic activities and to its proximity to the Indo-Gangetic Plains. The annual mean aerosol optical depth (AOD) during the investigated period was 0.05 at QOMS_CAS, 0.04 at EVK2-CNR and 0.51 at Pokhara, respectively. Seasonal variations of aerosols are profoundly affected by large-scale atmospheric circulation. Vegetation fires, peaking during April in the Himalayan region and northern India, contribute to a growing fine mode AOD at the three stations. Dust transported to these sites, wind erosion and hydrated/cloudprocessed aerosols lead to an increase in coarse mode AOD during the monsoon season at QOMS_CAS and EVK2-CNR. Meanwhile, coarse mode AOD at EVK2-CNR is higher than at QOMS_CAS in August and September, indicating that the transport of coarse mode aerosols from the southern to the northern side may be effectively reduced. The effect of precipitation scavenging is clearly seen at Pokhara, which sees significantly reduced aerosol loads during the monsoon season. Unlike the seasonal variations, diurnal variations are mainly influenced by meso-scale systems and local topography. The diurnal pattern in precipitation appears to contribute to diurnal changes in AOD through the effect of precipitation scavenging. AOD exhibits diurnal patterns related to emissions in Pokhara, while it does not at the other two high-altitude sites. At EVK2-CNR, the daytime airflow carries aerosols up from lower-altitude polluted regions, leading to increasing AOD, while the other two stations are less influenced by valley winds. Surface heating influences the local convection, which further controls the vertical aerosol exchange and the diffusion rate of pollution to the surrounding areas. Fine and coarse mode particles Published by Copernicus Publications on behalf of the European Geosciences Union.
C. Xu et al.: Similarities and differences of aerosol optical propertiesare mixed together on the southern side of the Himalaya in spring, which may lead to the greater inter-annual difference in diurnal cycles of Ångström exponent (AE) at EVK2-CNR than that at QOMS_CAS.
“…Everest. Southwesterly winds near the surface prevail during the monsoon season, while in other seasons northeasterly winds prevail (Ma et al, 2011;Li et al, 2012). EVK2-CNR station in Nepal (Table 1, Fig.…”
Abstract. The Himalaya mountains along the southern edge of the Tibetan Plateau act as a natural barrier for the transport of atmospheric aerosols from the polluted regions of South Asia to the main body of the Tibetan Plateau. In this study, we investigate the seasonal and diurnal variations of aerosol optical properties measured at two Aerosol Robotic Network (AERONET) sites on the southern side of the Himalaya (Pokhara, 812 m above sea level (a.s.l.) and EVK2-CNR, 5079 m a.s.l. in Nepal) and one on the northern side (Qomolangma (Mt. Everest) station for Atmospheric and Environmental Observation and Research, Chinese Academy of Sciences (QOMS_CAS) in Tibet, 4076 m a.s.l. in China). While observations at QOMS_CAS and EVK2-CNR can generally be representative of a remote background atmosphere, Pokhara is a lower-elevation suburban site with much higher aerosol load due to both the influence of local anthropogenic activities and to its proximity to the Indo-Gangetic Plains. The annual mean aerosol optical depth (AOD) during the investigated period was 0.05 at QOMS_CAS, 0.04 at EVK2-CNR and 0.51 at Pokhara, respectively. Seasonal variations of aerosols are profoundly affected by large-scale atmospheric circulation. Vegetation fires, peaking during April in the Himalayan region and northern India, contribute to a growing fine mode AOD at the three stations. Dust transported to these sites, wind erosion and hydrated/cloudprocessed aerosols lead to an increase in coarse mode AOD during the monsoon season at QOMS_CAS and EVK2-CNR. Meanwhile, coarse mode AOD at EVK2-CNR is higher than at QOMS_CAS in August and September, indicating that the transport of coarse mode aerosols from the southern to the northern side may be effectively reduced. The effect of precipitation scavenging is clearly seen at Pokhara, which sees significantly reduced aerosol loads during the monsoon season. Unlike the seasonal variations, diurnal variations are mainly influenced by meso-scale systems and local topography. The diurnal pattern in precipitation appears to contribute to diurnal changes in AOD through the effect of precipitation scavenging. AOD exhibits diurnal patterns related to emissions in Pokhara, while it does not at the other two high-altitude sites. At EVK2-CNR, the daytime airflow carries aerosols up from lower-altitude polluted regions, leading to increasing AOD, while the other two stations are less influenced by valley winds. Surface heating influences the local convection, which further controls the vertical aerosol exchange and the diffusion rate of pollution to the surrounding areas. Fine and coarse mode particles Published by Copernicus Publications on behalf of the European Geosciences Union.
C. Xu et al.: Similarities and differences of aerosol optical propertiesare mixed together on the southern side of the Himalaya in spring, which may lead to the greater inter-annual difference in diurnal cycles of Ångström exponent (AE) at EVK2-CNR than that at QOMS_CAS.
“…It is complicated and problematic using variance (σ 2 ) to explain C EB . Furthermore, the glacial wind and mountain-valley wind effect (Sun et al 2007;Li et al 2012) at Qomolangma have important consequences for the non-closure of the surface energy balance during the daytime. The advection produced by glacial and mountain-valley winds leads to a large residuum at the Qomolangma site.…”
The Tibetan Plateau (TP) has become a focus of strong scientific interest due to its role in the global water cycle and its reaction to climate change. Regional flux estimates of sensible and latent heat are important variables for linking the energy and hydrological cycles at the TP's surface. Within this framework, a 3-year dataset (2008)(2009)(2010) of eddy covariance measured turbulent fluxes was compiled from four stations on the TP into a standardised workflow: corrections and quality tests were applied using an internationally comparable software package. Second, the energy balance closure (C EB ) was determined and two different closure corrections applied. The four stations (Qomolangma, Linzhi, NamCo and Nagqu) represent different locations and typical land surface types on the TP (high altitude alpine steppe with sparse vegetation, a densely vegetated alpine meadow, and bare soil/gravel, respectively). We show that the C EB differs between each surface and undergoes seasonal changes. Typical differences in the turbulent energy fluxes occur between the stations at Qomolangma, Linzhi and NamCo, while Nagqu is quite similar to NamCo. Specific investigation of the pre-monsoon, the Tibetan Plateau summer monsoon, postmonsoon and winter periods within the annual cycle reinforces these findings. The energy flux of the four sites is clearly influenced by the Tibetan Plateau monsoon. In the pre-monsoon period, sensible heat flux is the major energy source delivering heat to the atmosphere, whereas latent heat flux is greater than sensible heat flux during the monsoon season. Other factors affecting surface energy flux are topography and location. Land cover type also affects surface energy flux. The energy balance residuum indicates a typically observed overall non-closure in winter, while closure (or 'turbulent over-closure') is achieved during the Tibetan Plateau summer monsoon at the Nagqu site. The latter seems to depend on ground heat flux, which is higher in the wet season, related not only to a larger radiation input but also to a thermal decoupling of dry soils. Heterogeneous landscape modelling using a MODIS product is introduced to explain energy non-closure.
“…Furthermore, AVHRR band 1 and band 2 are broad bands which contain several strong water vapour absorption zones and this will reduce AVHRR retrieval accuracy. In comparison with estimate results from AVHRR and MODIS data, it can be seen their spatial patterns are consistent on the same day but the MODIS results are greater than the AVHRR results (3)(4)(5). The reason is that the shortwave solar radiation or the net radiation flux at 13:00 is greater than those at 15:00 which is validated by the in-situ measurements (for instance, Lhasa station).…”
Section: Spatiotemporal Variations Of Land Surface Parameters In the supporting
confidence: 59%
“…Accordingly, surface albedo declines together with atmospheric water vapour content increasing from spring to autumn. The surface flux estimation results show that the spatial distribution of net radiation flux, sensible heat flux, latent heat flux and soil heat flux in the study area corresponds well with that of the surface parameters (NDVI, Pv and surface albedo) (3)(4)(5). In the eastern part with relatively higher vegetation cover, the net radiation flux and the latent heat flux are much higher while the sensible heat flux is much lower.…”
Section: Spatiotemporal Variations Of Land Surface Parameters In the supporting
confidence: 56%
“…This method will be investigated to derive LST from AVHRR data. (3)(4)(5)(6)(7)(8)(9) Where 4 T and 5 T are brightness temperature of band 4 and band 5 for AVHRR; W is water vapour content and ε is average emissivity of band 4 and band 5.…”
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