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

Aerosol indirect effects continue to constitute one of the most important uncertainties for anthropogenic climate perturbations. Within the international AEROCOM initiative, the representation of aerosol-cloud-radiation interactions in ten different general circulation models (GCMs) is evaluated using three satellite datasets. The focus is on stratiform liquid water clouds since most GCMs do not include ice nucleation effects, and none of the model explicitly parameterizes aerosol effects on convective clouds. We compute statistical relationships between aerosol optical depth (Ta) and various cloud and radiation quantities in a manner that is consistent between the models and the satellite data. It is found that the model-simulated influence of aerosols on cloud droplet number concentration (Nd) compares relatively well to the satellite data at least over the ocean. The relationship between Ta and liquid water path is simulated much too strongly by the models. It is shown that this is partly related to the representation of the second aerosol indirect effect in terms of autoconversion. A positive relationship between total cloud fraction (fcld) and Ta as found in the satellite data is simulated by the majority of the models, albeit less strongly than that in the satellite data in most of them. In a discussion of the hypotheses proposed in the literature to explain the satellite-derived strong fcld - Ta relationship, our results indicate that none can be identified as unique explanation. Relationships similar to the ones found in satellite data between Ta and cloud top temperature or outgoing long-wave radiation (OLR) are simulated by only a few GCMs. The GCMs that simulate a negative OLR - Ta relationship show a strong positive correlation between Ta and fcld The short-wave total aerosol radiative forcing as simulated by the GCMs is strongly influenced by the simulated anthropogenic fraction of Ta, and parameterisation assumptions such as a lower bound on Nd. Nevertheless, the strengths of the statistical relationships are good predictors for the aerosol forcings in the models. An estimate of the total short-wave aerosol forcing inferred from the combination of these predictors for the modelled forcings with the satellite-derived statistical relationships yields a global annual mean value of -1.5+-0.5 Wm-2. An alternative estimate obtained by scaling the simulated clear- and cloudy-sky forcings with estimates of anthropogenic Ta and satellite-retrieved Nd - Ta regression slopes, respectively, yields a global annual mean clear-sky (aerosol direct effect) estimate of -0.4+-0.2 Wm-2 and a cloudy-sky (aerosol indirect effect) estimate of -0.7+-0.5 Wm-2, with a total estimate of -1.2+-0.4 Wm-2.

Aerosol indirect effects -- general circulation model intercomparison and evaluation with satellite data

Fusing satellite observations and station measurements to estimate ground-level PM2.5 is promising for monitoring PM2.5 pollution. A geo-intelligent approach, which incorporates geographical correlation into an intelligent deep learning architecture, is developed to estimate PM2.5. Specifically, it considers geographical distance and spatiotemporally correlated PM2.5 in a deep belief network (denoted as Geoi-DBN). Geoi-DBN can capture the essential features associated with PM2.5 from latent factors. It was trained and tested with data from China in 2015. The results show that Geoi-DBN performs significantly better than the traditional neural network. The out-of-sample cross-validation R2 increases from 0.42 to 0.88, and RMSE decreases from 29.96 to 13.03 μg/m3. On the basis of the derived PM2.5 distribution, it is predicted that over 80% of the Chinese population live in areas with an annual mean PM2.5 of greater than 35 μg/m3. This study provides a new perspective for air pollution monitoring in large geographic regions.

https://agupubs.onlinelibrary.wiley.com/doi/epdf/10.1002/2017GL075710

Estimating Ground-Level PM2.5 by Fusing Satellite and Station Observations: A Geo-Intelligent Deep Learning Approach

Influence of meteorological conditions on PM2.5 concentrations across China: A review of methodology and mechanism.

Clouds are a critical component of the Earth's coupled water and energy cycles. Poor understanding of cloud–radiation–dynamics feedbacks results in large uncertainties in forecasting human-induced climate changes. Better understanding of cloud microphysical and dynamical processes is critical to improving cloud parameterizations in climate models as well as in cloud-resolving models. Airborne in situ and remote sensing can make critical contributions to progress. Here, a new integrated cloud observation capability developed for the University of Wyoming King Air is described. The suite of instruments includes the Wyoming Cloud Lidar, a 183- GHz microwave radiometer, the Wyoming Cloud Radar, and in situ probes. Combined use of these remote sensor measurements yields more complete descriptions of the vertical structure of cloud microphysical properties and of cloud-scale dynamics than that attainable through ground-based remote sensing or in situ sampling alone. Together with detailed in situ data on aeroso...

Single Aircraft Integration of Remote Sensing and In Situ Sampling for the Study of Cloud Microphysics and Dynamics

. The relationship between aerosol optical depth (AOD) and PM2.5 is often investigated in order to obtain surface PM2.5 from satellite observation of AOD with a broad area coverage. However, various factors could affect the AOD–PM2.5 regressions. Using both ground and satellite observations in Beijing from 2011 to 2015, this study analyzes the influential factors including the aerosol type, relative humidity (RH), planetary boundary layer height (PBLH), wind speed and direction, and the vertical structure of aerosol distribution. The ratio of PM2.5 to AOD, which is defined as η, and the square of their correlation coefficient (R2) have been examined. It shows that η varies from 54.32 to 183.14, 87.32 to 104.79, 95.13 to 163.52, and 1.23 to 235.08 µg m−3 with aerosol type in spring, summer, fall, and winter, respectively. η is smaller for scattering-dominant aerosols than for absorbing-dominant aerosols, and smaller for coarse-mode aerosols than for fine-mode aerosols. Both RH and PBLH affect the η value significantly. The higher the RH, the smaller the η, and the higher the PBLH, the smaller the η. For AOD and PM2.5 data with the correction of RH and PBLH compared to those without, R2 of monthly averaged PM2.5 and AOD at 14:00 LT increases from 0.63 to 0.76, and R2 of multi-year averaged PM2.5 and AOD by time of day increases from 0.01 to 0.93, 0.24 to 0.84, 0.85 to 0.91, and 0.84 to 0.93 in four seasons respectively. Wind direction is a key factor for the transport and spatial–temporal distribution of aerosols originated from different sources with distinctive physicochemical characteristics. Similar to the variation in AOD and PM2.5, η also decreases with the increasing surface wind speed, indicating that the contribution of surface PM2.5 concentrations to AOD decreases with surface wind speed. The vertical structure of aerosol exhibits a remarkable change with seasons, with most particles concentrated within about 500 m in summer and within 150 m in winter. Compared to the AOD of the whole atmosphere, AOD below 500 m has a better correlation with PM2.5, for which R2 is 0.77. This study suggests that all the above influential factors should be considered when we investigate the AOD–PM2.5 relationships.

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Analysis of influential factors for the relationship between PM 2.5 and AOD in Beijing

https://agupubs.onlinelibrary.wiley.com/doi/epdf/10.1002/2017EA000346

Negative Aerosol‐Cloud re Relationship From Aircraft Observations Over Hebei, China

8-Year ground-based observational analysis about the seasonal variation of the aerosol-cloud droplet effective radius relationship at SGP site

MMCR-based characteristic properties of non-precipitating cloud liquid droplets at Naqu site over Tibetan Plateau in July 2014

This study describes the microphysical properties of high ice clouds (with bases above 5 km) using ground-based millimeter cloud radar cirrus-mode observations over the Naqu site of the Tibetan Plateau (TP) during a short period from 6 to 31 July 2014. Empirical regression equations are applied for the cloud retrievals in which the parameters are given on the basis of a review of existing literature. The results show a unimodal distribution for the cloud ice effective radius re and ice water content with maximum frequencies around 36 μm and 0.001 g m−3, respectively. Analysis shows that clouds with high ice re are more likely to occur at times from late afternoon until nighttime. The clouds with large (small) re mainly occur at low (high) heights and are likely orographic cumulus or stratocumulus (thin cirrus). Further analysis indicates that ice re decreases with increasing height and shows strong positive relationships between ice re (μm) and depth h (m), with a regression equation of re = 35.45...

Toward Understanding the Properties of High Ice Clouds at the Naqu Site on the Tibetan Plateau Using Ground-Based Active Remote Sensing Measurements Obtained during a Short Period in July 2014

Yanmei Qiu

Papers

Analysis of influential factors for the relationship between PM 2.5 and AOD in Beijing

Negative Aerosol‐Cloud re Relationship From Aircraft Observations Over Hebei, China

8-Year ground-based observational analysis about the seasonal variation of the aerosol-cloud droplet effective radius relationship at SGP site

MMCR-based characteristic properties of non-precipitating cloud liquid droplets at Naqu site over Tibetan Plateau in July 2014

Toward Understanding the Properties of High Ice Clouds at the Naqu Site on the Tibetan Plateau Using Ground-Based Active Remote Sensing Measurements Obtained during a Short Period in July 2014