Glacial melting in the Tibetan Plateau affects the water resources of millions of people. This study finds that—partly owing to changes in atmospheric circulations and precipitation patterns—the most intensive glacier shrinkage is in the Himalayan region, whereas glacial retreat in the Pamir Plateau region is less apparent.

Different glacier status with atmospheric circulations in Tibetan Plateau and surroundings

Abstract. The Tibetan Plateau (TP) has long been identified to be critical in regulating the Asian monsoon climate and hydrological cycle. In this modeling study a series of numerical experiments with a global climate model are designed to simulate radiative effect of black carbon (BC) and dust in snow, and to assess the relative impacts of anthropogenic CO2 and carbonaceous particles in the atmosphere and snow on the snowpack over the TP and subsequent impacts on the Asian monsoon climate and hydrological cycle. Simulations results show a large BC content in snow over the TP, especially the southern slope. Because of the high aerosol content in snow and large incident solar radiation in the low latitude and high elevation, the TP exhibits the largest surface radiative flux changes induced by aerosols (e.g. BC, Dust) in snow compared to any other snow-covered regions in the world. Simulation results show that the aerosol-induced snow albedo perturbations generate surface radiative flux changes of 5–25 W m−2 during spring, with a maximum in April or May. BC-in-snow increases the surface air temperature by around 1.0 °C averaged over the TP and reduces spring snowpack over the TP more than pre-industrial to present CO2 increase and carbonaceous particles in the atmosphere. As a result, runoff increases during late winter and early spring but decreases during late spring and early summer (i.e. a trend toward earlier melt dates). The snowmelt efficacy, defined as the snowpack reduction per unit degree of warming induced by the forcing agent, is 1–4 times larger for BC-in-snow than CO2 increase during April–July, indicating that BC-in-snow more efficiently accelerates snowmelt because the increased net solar radiation induced by reduced albedo melts the snow more efficiently than snow melt due to warming in the air. The TP also influences the South (SAM) and East (EAM) Asian monsoon through its dynamical and thermal forcing. Simulation results show that during boreal spring aerosols are transported by southwesterly, causing some particles to reach higher altitude and deposit to the snowpack over the TP. While BC and Organic Matter (OM) in the atmosphere directly absorb sunlight and warm the air, the darkened snow surface polluted by BC absorbs more solar radiation and increases the skin temperature, which warms the air above through sensible heat flux. Both effects enhance the upward motion of air and spur deep convection along the TP during the pre-monsoon season, resulting in earlier onset of the SAM and increase of moisture, cloudiness and convective precipitation over northern India. BC-in-snow has a more significant impact on the EAM in July than CO2 increase and carbonaceous particles in the atmosphere. Contributed by the significant increase of both sensible heat flux associated with the warm skin temperature and latent heat flux associated with increased soil moisture with long memory, the role of the TP as a heat pump is elevated from spring through summer as the land-sea thermal contrast increases to strengthen the EAM. As a result, both southern China and northern China become wetter, but central China (i.e. Yangtze River Basin) becomes drier – a near-zonal anomaly pattern that is consistent with the dominant mode of precipitation variability in East Asia. The snow impurity effects reported in this study likely represent some upper limits as snowpack is remarkably overestimated over the TP due to excessive precipitation. Improving the simulation of precipitation and snowpack will be important for improved estimates of the effects of snowpack pollution in future work.

Impacts of Tibetan Plateau snowpack pollution on the Asian hydrological cycle and monsoon climate

 Snow cover plays a key role for sustaining ecology and society in mountainous regions Light-absorbing particulates (including black carbon, organic carbon, and mineral dust) deposited on snow can reduce surface albedo and contribute to the near-worldwide melting of snow and ice This study focused on understanding the role of black carbon and other water-insoluble light-absorbing particulates in the snow cover of the Tibetan Plateau (TP) The results found that the black carbon, organic carbon, and dust concentrations in snow cover generally ranged from 202 to 17 468 ng g−1, 491 to 13 880 ng g−1, and 22 to 846 µg g−1, respectively, with higher concentrations in the central to northern areas of the TP Back trajectory analysis suggested that the northern TP was influenced mainly by air masses from Central Asia with some Eurasian influence, and air masses in the central and Himalayan region originated mainly from Central and South Asia The relative biomass-burning-sourced black carbon contributions decreased from ∼ 50 % in the southern TP to ∼ 30 % in the northern TP The relative contribution of black carbon and dust to snow albedo reduction reached approximately 37 and 15 %, respectively The effect of black carbon and dust reduced the snow cover duration by 31 ± 01 to 44 ± 02 days Meanwhile, the black carbon and dust had important implications for snowmelt water loss over the TP The findings indicate that the impacts of black carbon and mineral dust need to be properly accounted for in future regional climate projections, particularly in the high-altitude cryosphere

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Black carbon and mineral dust in snow cover on the Tibetan Plateau

Random forests (RFs), an advanced machine learning (ML) method, was used here to develop a robust and rapid quantitative precipitation estimates (QPEs) algorithm for the new-generation geostationary satellite of Himawari-8. In this algorithm, the global precipitation measurement (GPM) product has been employed to train QPE prediction model. The real-time multiband infrared brightness temperature from Himawari-8, combined with the spatiotemporally matched numerical weather prediction (NWP) data from the global forecast system, have been used as predictor variables for QPE. Among the variables used in RF learning model, total precipitable water and $K$ -index from NWP data have the highest rankings, indicating the importance of atmospheric environment for QPE. To enhance the accuracy of RF models or to optimize model training, a sample-balance technique has been utilized to adjust the ratios of samples in nonprecipitation/precipitation classification and quantitative precipitation regression data sets. Further sensitivity and validation analyses help determine the optimal RF classification and regression models for predicting nonprecipitation/precipitation pixel and rain rate. The selected RF classification model is found to predict precipitation area with an accuracy of 0.87. For predicted QPE product, the mean-absolute-error and root-mean-square error of RF regression model are 0.51 and 2.0 mm/h, respectively. Overall, the RF ML algorithm has a higher detection rate over homogenous ocean surface as compared with over land. Meanwhile, this RF algorithm tends to underestimate rain rate, especially in the presence of heavy rainfall. Despite this, it still produces a reasonable pattern of rainfall area and intensity, which are highly consistent with GPM observations.

Estimating Summertime Precipitation from Himawari-8 and Global Forecast System Based on Machine Learning

Aerosol-cloud interactions (ACI) represent a significant source of forcing uncertainty in global climate models (GCMs). Estimates of radiative forcing due to ACI in Fifth Assessment Report range fr ...

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The global aerosol-cloud first indirect effect estimated using MODIS, MERRA and AeroCom

. Using 2B-CLDCLASS-LIDAR (radar–lidar) cloud classification and 2B-FLXHR-LIDAR radiation products from CloudSat over 4 years, this study evaluates the co-occurrence frequencies of different cloud types, analyzes their along-track horizontal scales and cloud radiative effects (CREs), and utilizes the vertical distributions of cloud types to evaluate cloud-overlap assumptions. The statistical results show that high clouds, altostratus (As), altocumulus (Ac) and cumulus (Cu) tend to coexist with other cloud types. However, stratus (St) (or stratocumulus, Sc), nimbostratus (Ns) and convective clouds are much more likely to exhibit individual features than other cloud types. On average, altostratus-over-stratus/stratocumulus cloud systems have a maximum horizontal scale of 17.4 km, with a standard deviation of 23.5 km. Altocumulus-over-cumulus cloud types have a minimum scale of 2.8 km, with a standard deviation of 3.1 km. By considering the weight of each multilayered cloud type, we find that the global mean instantaneous net CREs of multilayered cloud systems during the daytime are approximately −41.3 and −50.2 W m−2, which account for 40.1 and 42.3% of the global mean total net CREs at the top of the atmosphere (TOA) and at the surface, respectively. The radiative contributions of high-over-altocumulus and high-over-stratus/stratocumulus (or cumulus) in the all multilayered cloud systems are dominant due to their frequency. Considering the overlap of cloud types, the cloud fraction based on the random overlap assumption is underestimated over vast oceans, except in the west-central Pacific Ocean warm pool. Obvious overestimations mainly occur over tropical and subtropical land masses. In view of a lower degree of overlap than that predicted by the random overlap assumption to occur over the vast ocean, particularly poleward of 40° S, the study therefore suggests that a linear combination of minimum and random overlap assumptions may further improve the predictions of actual cloud fractions for multilayered cloud types (e.g., As + St/Sc and Ac + St/Sc) over the Southern Ocean. The establishment of a statistical relationship between multilayered cloud types and the environmental conditions (e.g., atmospheric vertical motion, convective stability and wind shear) would be useful for parameterization design of cloud overlap in numerical models.

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A global survey of cloud overlap based on CALIPSO and CloudSat measurements

. A large field campaign was conducted and 284 snow samples were collected at 38 sites in Xinjiang Province and 6 sites in Qinghai Province across northwestern China from January to February 2012. A spectrophotometer combined with chemical analysis was used to measure the insoluble light-absorbing particles (ILAPs) and chemical components in seasonal snow. The results indicate that the cleanest snow was found in northeastern Xinjiang along the border of China, and it presented an estimated black carbon (CBCest) of approximately 5 ng g−1. The dirtiest snow presented a CBCest of approximately 450 ng g−1 near industrial cities in Xinjiang. Overall, the CBCest of most of the snow samples collected in this campaign was in the range of 10–150 ng g−1. Vertical variations in the snowpack ILAPs indicated a probable shift in emission sources with the progression of winter. An analysis of the fractional contributions to absorption implied that organic carbon (OC) dominated the 450 nm absorption in Qinghai, while the contributions from BC and OC were comparable in Xinjiang. Finally, a positive matrix factorization (PMF) model was run to explore the sources of particulate light absorption, and the results indicated an optimal three-factor/source solution that included industrial pollution, biomass burning, and soil dust.

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Properties of black carbon and other insoluble light-absorbing particles in seasonal snow of northwestern China

. The deposition of
insoluble light-absorbing particles (ILAPs) on snow and ice surfaces can
significantly reduce albedo, thereby accelerating the melting process. In
this study, 67 ice samples were collected from seven glaciers located on the
Tibetan Plateau (TP) between May 2013 and October 2015. The mixing ratios of
black carbon (BC), organic carbon (OC), and mineral dust (MD) were measured
with an integrating sphere/integrating sandwich spectrophotometer (ISSW) system,
which assumes that the light absorption of MD is due to iron oxide (Fe). Our
results indicate that the mass-mixing ratios of BC, OC, and Fe exhibit
considerable variability (BC: 10–3100 ng g −1 ; OC:
10–17 000 ng g −1 ; Fe: 10–3500 ng g −1 ) with respective mean
values of 220±400  ng g −1 , 1360±2420  ng g −1 , and
 240±450  ng g −1 over the course of the field campaign. We
observed that for wavelengths of 450–600 nm, the measured light absorption
can be largely attributed to the average light absorption of BC (50.7 %)
and OC (33.2 %). Chemical elements and selected carbonaceous particles
were also analyzed for source attributions of particulate light absorption
based on a positive matrix factorization (PMF) receptor model. Our findings
indicate that on average, industrial pollution (33.1 %), biomass or
biofuel burning (29.4 %), and MD (37.5 %) constitute the principal
sources of ILAPs deposited on TP glaciers.

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Quantifying the light absorption and source attribution of insoluble light-absorbing particles on Tibetan Plateau glaciers between 2013 and 2015

1 Key Laboratory for Semi-Arid Climate Change of the Ministry of Education, College of Atmospheric Sciences, Lanzhou University, Lanzhou, 730000, China 2 Key Laboratory of Wetland Ecology and Environment, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102, China 3 College of Atmospheric Science, Chengdu University of Information Technology, and Plateau Atmospheric and Environment Laboratory of Sichuan Province, Chengdu 610225, China

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Snow albedo reduction in seasonal snow due to anthropogenic dust and carbonaceous aerosols across northern China

/pdf/distributions-and-radiative-forcings-of-various-cloud-types-1e4risr6np.pdf

Distributions and radiative forcings of various cloud types based on active and passive satellite datasets - Part 1: Geographical distributions and overlap of cloud types

Hongchun Jin

Papers

A global survey of cloud overlap based on CALIPSO and CloudSat measurements

Properties of black carbon and other insoluble light-absorbing particles in seasonal snow of northwestern China

Quantifying the light absorption and source attribution of insoluble light-absorbing particles on Tibetan Plateau glaciers between 2013 and 2015

Snow albedo reduction in seasonal snow due to anthropogenic dust and carbonaceous aerosols across northern China

Distributions and radiative forcings of various cloud types based on active and passive satellite datasets - Part 1: Geographical distributions and overlap of cloud types