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Dust aerosols play key roles in affecting regional and global climate through their direct, indirect, and semi-direct effects. Dust events have decreased rapidly since the 1980s in East Asia, particularly over northern China, primarily because of changes in meteorological parameters (e.g. surface wind speed and precipitation). In this study, we found that winter (December–January–February) Arctic amplification associated with weakened temperature gradients along with decreased zonal winds is primarily responsible for the large decline in following spring (March–April–May) dust event occurrences over northern China since the mid-1980s. A dust index was developed for northern China by combining the daily frequency of three types of dust event (dust storm, blowing dust, and floating dust). Using the empirical orthogonal function (EOF) analysis, the first pattern of dust events was obtained for spring dust index anomalies, which accounts for 56.2% of the variability during 1961–2014. Moreover, the enhanced Arctic amplification and stronger Northern Hemisphere annular mode (NAM) in winter can result in the anticyclonic anomalies over Siberia and Mongolia, while cyclonic anomalies over East Europe in spring. These results are significantly correlated with the weakened temperature gradients, increased precipitation and soil moisture, and decreased snow cover extent in the mid-latitude over Northern Hemisphere. Based on the future predictions obtained from the Fifth Climate Models Intercomparison Project (CMIP5), we found that the dust event occurrences may continually decrease over northern China due to the enhanced Arctic amplification in future climate.

Enhanced near-surface atmospheric warming has occurred over East Asia in recent decades, especially in drylands. Although local factors have been confirmed to provide considerable contributions to this warming, such factors have not been sufficiently analyzed. In this study, we extracted the radiatively-forced temperature (RFT) associated with the built-up greenhouse gases (GHGs), aerosol emission and various other radiative forcing over East Asia, and found a close relationship between RFT and CO2. In addition, using climate model experiments, we explored the responses of temperature changes to black carbon (BC), CO2 and SO4, and found that the enhanced dryland warming induced by CO2 had the largest magnitude and was strengthened by the warming effect of BC. Moreover, the sensitivity of daily maximum and minimum temperature changes to BC, CO2 and SO4 was examined. It showed asymmetric responses of daily maximum and minimum temperature to radiative factors, which led to an obvious change of diurnal temperature range (DTR), especially in drylands. The DTR's response to CO2 is the most significant. Therefore, CO2 not only plays a dominant role in enhanced warming, but also greatly affects the decrease of DTR in drylands. However, the mechanisms of these radiative factors’ effects in the process of DTR change are not clear and require more investigation.

Enhanced warming in semi-arid regions has received much attention since it was first proposed, but the primary driver of this phenomenon remains unknown. This study applied dynamical adjustment to surface air temperature and partitioned the warming into two separate components: a thermodynamically forced component and a dynamically induced component. The results show that the mean amount of thermodynamic warming in the Northern Hemisphere in the study period 1902–2011 was 1.36 °C/109 years and that the amount of dynamic warming was 0.14 °C/109 years. In the mid-latitude zones of Asia, Europe, and North America, the thermodynamic warming was 1.60, 1.19, and 1.32 °C/109 years, respectively, and the corresponding dynamic warming was 0.26, 0.14, and 0.09 °C/109 years. Obviously, higher thermodynamic temperature warming was observed in semi-arid regions, suggesting that the enhanced semi-arid warming (ESAW) is the result of local thermodynamic effects. Thus, different local thermodynamic effects are responsible for the warming discrepancies in the semi-arid regions of Asia, Europe, and North America. Moreover, the considerable bias of Coupled Model Intercomparison Project Phase 5 (CMIP5) ensemble mean temperature trend appeared in semi-arid regions rather than other regions indicate that the simulation of semi-arid regions is particularly complex and difficult.

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.

A snow survey was carried out to collect 13 surface snow samples (10 for fresh snow, and 3 for aged snow) and 79 subsurface snow samples in seasonal snow at 13 sites across northeastern China in January 2014. A spectrophotometer combined with chemical analysis was used to quantify snow particulate absorption by insoluble light-absorbing particles (ILAPs, e.g., black carbon, BC; mineral dust, MD; and organic carbon, OC) in snow. Snow albedo was measured using a field spectroradiometer. A new radiative transfer model (Spectral Albedo Model for Dirty Snow, or SAMDS) was then developed to simulate the spectral albedo of snow based on the asymptotic radiative transfer theory. A comparison between SAMDS and an existing model – the Snow, Ice, and Aerosol Radiation (SNICAR) – indicates good agreements in the model-simulated spectral albedos of pure snow. However, the SNICAR model values tended to be slightly lower than those of SAMDS when BC and MD were considered. Given the measured BC, MD, and OC mixing ratios of 100–5000, 2000–6000, and 1000–30 000 ng g−1, respectively, in surface snow across northeastern China, the SAMDS model produced a snow albedo in the range of 0.95–0.75 for fresh snow at 550 nm, with a snow grain optical effective radius (Reff) of 100 µm. The snow albedo reduction due to spherical snow grains assumed to be aged snow is larger than fresh snow such as fractal snow grains and hexagonal plate or column snow grains associated with the increased BC in snow. For typical BC mixing ratios of 100 ng g−1 in remote areas and 3000 ng g−1 in heavy industrial areas across northern China, the snow albedo for internal mixing of BC and snow is lower by 0.005 and 0.036 than that of external mixing for hexagonal plate or column snow grains with Reff of 100 µm. These results also show that the simulated snow albedos by both SAMDS and SNICAR agree well with the observed values at low ILAP mixing ratios but tend to be higher than surface observations at high ILAP mixing ratios.

Dust aerosol effect on the retrievals of dusty cloud top height (DCTH) are analyzed over Northwest China using cloud products from MODerate Resolution Imaging Spectroradiometer (MODIS) on Aqua, Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO), and CloudSat for the Spring season of March–May over the years 2007–2011. An excellent agreement is found between CloudSat and CALIPSO derived DCTHs for all cloud types, suggesting that the effect of dust aerosols plays a small role in DCTHs determination for lidar and radar measurements. However, the presence of dust aerosols greatly affects the retrievals of DCTHs for MODIS compared with pure clouds and the active sensors derived results. The differences of DCTHs retrieving from CloudSat and MODIS range from −2.30 to 6.8 km. Likewise, the differences of DCTHs retrieving from CALIPSO and MODIS range from −2.66 to 6.78 km. In addition, the results show that the differences in DCTHs for active and passive sensors are dependent on cloud type. On the whole, dust aerosols have the largest effect on cloud top heights (CTH) retrieved of nimbostratus (Ns), followed by altocumulus (Ac) and altostratus (As), the last is cirrus (Ci) over Northwest China. Our results also indicate that the accuracy of MODIS-derived retrievals reduces accompanied with a decrease of height.

Dust aerosols have significant impact on the environment and climate through long-range transport. We report, in this paper, a case of dust–cloud interaction process using combined measurements of a ground-based polarization and Raman (PR) lidar systems, and implemented by the spaceborne Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) lidar observations. The dust event occurred on 14 March 2009 over East Asia. During the two hours of observing time, the ground-based lidar observed an ongoing process of decreasing of the depolarization ratio (DR) accompanied by the increase of the water vapor simultaneously, indicating a dust–cloud interaction and particle transformation. CALIPSO measurements also found similar layers of dusts and clouds over lands and oceans with properties similar to the ground based lidar measurements. Our observation was a real-time dust–cloud process with the observation of occurrence of particle transformation. The depolarization reduced from 0.2 to 0.1 corresponding to a change of aspect ratio from 1.2 to 1.1. A discussion of a dust–cloud interaction in terms of three-stage cloud processes is made based on back-trajectory analyses and lidar observations. The result shows that dust aerosols decrease the cloud extinction coefficient by 41% but increase the cloud optical depth (COD) of water cloud by 12.79%, compared with that of pure water clouds. Furthermore, if dust aerosols participate as cloud condensation nuclei (CCN) in cloud physical processes, then they significantly reduce the size of the cloud droplet by 44–79%. Finally, based on three-year collocated CALIPSO and CloudSat measurements from 2007 to 2010, we found approximately one-third of clouds are originally dusty in the spring over the Pacific Coast areas.

Dust aerosol effects on the properties of cirrus and altocumulus cloud in Northwest China were studied for the period March–May 2007 by using the satellite data of Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO), Aqua, and CloudSat. Dusty clouds were defined as those mixed with dust aerosols or existing in dust aerosol conditions, while pure clouds were those in a dust-free environment. For dusty altocumulus clouds, the mean values of cloud optical depth (OPD), cloud liquid water path (LWP), cloud ice water path (IWP), cloud effective particle radius (Re), and cloud effective particle diameter (D e) were 6.40, 40.23 g m-2, 100.70 g m-2, 8.76 μm, and 40.72 μm, respectively. For pure altocumulus clouds, the corresponding mean values were 9.28, 76.70 g m-2, 128.75 g m-2, 14.03 μm, and 48.92 μm, respectively. These results show a significant decrease of OPD, LWP, IWP, R e, and D e of approximately 31%, 48%, 22%, 38%, and 17% because of the effects of dust aerosols. Moreover, the effects of dust aerosols on liquid-phase altocumulus clouds were greater than on ice-phase altocumulus clouds. Regarding dusty cirrus clouds, the mean values of OPD, IWP, and D e were 5.11, 137.53 g m-2, and 60.44 μm, respectively. In contrast, the mean values were 6.69, 156.17 g m-2, and 66.63 μm, respectively, for pure cirrus clouds, with a 24% decrease in OPD, a 12% decrease in IWP, and a 9% decrease in D e. These results indicate that dust aerosols can significantly change cloud properties, leading to a reduction of OPD, LWP, and effective particle size for both altocumulus and cirrus clouds in Northwest China.

Black carbon (BC), normally existing as aggregates, significantly affects the Earth radiative forcing, energy balance, and climate by scattering and absorbing both solar radiation and terrestrial emission. The BC particles are usually treated as fractal aggregates with same-sized monomers. However, experimental studies show that monomer diameters of BC normally obey a lognormal distribution ranging from 10 nm to over 100 nm. This study investigates the effects of monomer size distribution on the radiative properties of BC particles. The fractal aggregates are generated by a cluster–cluster aggregation (CCA) algorithm, and the Multiple Sphere T-Matrix (MSTM) method is used to simulate the radiative properties of randomly oriented aggregates. The integral radiative properties of aggregates with different-sized monomers have normal distributions with large standard deviations, and it requires to average radiative properties of over 60 aggregate realizations to represent their ensemble-averaged properties. Th...

Planetary boundary layer (PBL) height was estimated using the maximum standard deviation method for Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) attenuated backscatter observations. It was only retrieved under conditions where the clouds accounted for less than 5% in a profile, where it could be compared with ground lidar results at SACOL. The correlation between CALIPSO and the ground lidar was 0.73. We present the seasonal mean patterns of 4-year mid-day PBL heights over China and use them to evaluate the European Centre for Medium-Range Weather Forecasts (ECMWF) PBL depth retrievals, inform boundary layer studies, and improve our understanding of how PBL height mediates exchanges of energy and pollutants between the surface and the atmosphere. We found that the largest PBL heights occurred over the Tibetan Plateau and coastal areas. The smallest PBL heights appeared in the Tarim Basin and northeast of China during local winter. A comparison of CALIPSO and ECMWF PBL under different land-cover conditions showed that the PBL depth estimated by the CALIPSO backscatter climatology is larger over ocean and forest surface than that estimated from ECMWF data. However, the PBL heights of ECMWF that were larger than those of CALIPSO were mainly concentrated over grassland and bare land surface in spring and summer.

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.

We conducted a comprehensive field campaign on exploring the optical characteristics of mineral dust in Dunhuang farmland nearby the Gobi deserts of northwest China during spring of 2012. The day-to-day and diurnal variations of dust aerosol showed prominent features throughout the experiment, primarily attributable to frequent dust events and local anthropogenic emissions. The overall average mass concentration of the particulate matter with an aerodynamic diameter less than 10 μm (PM10), light scattering coefficient (σsp,670), absorption coefficient (σap,670), and single-scattering albedo (SSA670) were 113±169 μgm-3, 53.3 ± 74.8 Mm-1, 3.2± 2.4 Mm-1, and 0.913 ± 0.05, which were comparable to the background levels in southern United States, but smaller than that in the eastern and other northwestern China. The anthropogenic dust produced by agricultural cultivations (e.g., land planning, plowing, and disking) exerted a significant superimposed effect on high dust concentrations in Dunhuang farmland prior to the growing season (i.e., from 1 April to 10 May). Strong south valley wind and vertical mixing in daytime scavenged the pollution and weak northeast mountain wind and stable inversion layer at night favorably accumulated the air pollutants near the surface. In the afternoon (13:00–18:00 LT), mean SSA670 was 0.945 ± 0.04 that was predominant by dust particles, whereas finer particles and lower SSA670 values (~ 0.90–0.92) were measured at night, suggesting the potential influence by the mixed dust-pollutants. During a typical biomass burning event on 4 April 2012, σap,670 changed from ~ 2.0 Mm-1 to 4.75 Mm-1 and SSA670 changed from ~ 0.90 to ~ 0.83, implying remarkable modification of aerosol absorptive properties induced by human activities. The findings of this study would help to advance an in-depth understanding of the interaction among dust aerosol, atmospheric chemistry, and climate change in desert source region.

Atmospheric Infrared Sounder (AIRS) infrared-based cloud-thermodynamic-phase retrievals are evaluated using the Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) cloud thermodynamic phase. The AIRS cloud phase is derived from spectral information contained within the 8–12-μm window, and CALIPSO provides coincident pixel-scale observations of cloud phase using the depolarization capability of the 532-nm channel. Comparisons are performed between the AIRS and CALIPSO cloud-phase observations for single-layer (48.5% of all clouds), heterogeneous-layer (45.9%), and multilayered (5.6%) clouds. The AIRS ice phase is in agreement with CALIPSO for more than 90% of coincident observations globally, with the largest discrepancies found in high latitudes and multilayered clouds. AIRS water phase generally follows CALIPSO spatial patterns, but the frequency is lower by about a factor of 2. The ice and water phases of AIRS both show misclassifications about 1% of the time when compared with CALIPSO. Not all clouds demonstrate strong phase signatures in the AIRS spectrum, which leads AIRS to classify unknown phase to around 10% of CALIPSO’s ice clouds and 60% of CALIPSO’s water clouds. This study shows that the algorithm is capable of detecting ice clouds within the AIRS field of view and can be used as the first step in further retrievals of ice-cloud optical thickness and effective particle size.

Abstract. A large field campaign was conducted in northwestern China from January to February 2012 to measure the insoluble light-absorbing particles (ILAPs) and chemical species in the snow, and two hundred eighty-four snow samples were collected at 38 sites in Xinjiang Province and 6 sites in Qinghai Province. The cleanest snow was found in northeastern Xinjiang along the border of China, and it presented an estimated black carbon (BC) (CBCest) of approximately 5 ng g−1. The dirtiest snow was found near industrial cities, and it presented a CBCest of approximately 450 ng g−1. Overall, the CBCest of most of the snow samples collected in this campaign was 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, whereas the contributions from BC and OC were comparable in Xinjiang. A Positive Matrix Factorization (PMF) model was run to explore the sources of particulate light absorption, and the results indicated an optimal 3-factor/source solution that included industrial pollution, biomass burning, and soil dust. In addition, the chemical components were evaluated to examine the mass contributions. In Qinghai, biomass burning was the dominant absorption factor despite the high mass contribution from soil dust. In Xinjiang, the primary absorption source was industrial pollution at sites near cities and biomass burning at most sites in other regions. A negative correlation was observed between the BC mixing ratio and altitude in Xinjiang. An analysis based on the PMF 3-factor solution showed that this relationship likely resulted from gradient variations in the contributions of industrial pollution sources.

A survey was performed to collect 92 seasonal snow samples across northern China in January 2014. The results show that mixing ratios of black carbon (BC), organic carbon (OC), and anthropogenic dust (AD) range from 60 to 4200 ng g−1, 280 to 32 000 ng g−1, and 1300 to 5800 ng g−1 in surface snow, respectively. A relatively high correlation (R2 = 0.87, n = 13) between OC and BC in surface snow is observed, indicating similar emission sources, and high OC/BC ratios suggest that biomass burning may be a major contributor at most snow sampling sites. In addition to the BC and AD parameters in the Snow, Ice, and Aerosol Radiation (SNICAR) model, the OC content in snow is considered an initial parameter for calculating snow albedo through a new radiative transfer model (Spectral Albedo Model for Dirty Snow, or SAMDS). The spectral albedo of snow reduction caused by OC (20 μg g−1) is up to a factor of 3 for a snow grain size of 800 μm compared to 100 μm. We find a larger difference in snow albedo levels between the model simulations and surface measurements for higher insoluble light-absorbing impurities (ILAPs) using the measured snow grain radii. However, using the optical effective radii (Reff), snow albedos modeled through both the SNICAR and SAMDS models are consistent with surface measurements, especially in the case of near-infrared wavelengths.

The soil state (e.g. temperature and moisture) in a mesoscale numerical prediction model is typically initialized by reanalysis or analysis data that may be subject to large bias. Such bias may lead to unrealistic land–atmosphere interactions. This study shows that the Climate Forecast System Reanalysis (CFSR) dramatically underestimates soil temperature and overestimates soil moisture over most parts of China in the first (0-10cm) and second (10-25cm) soil layers compared to in situ observations in July, 2013. A correction based on the global optimal dual kriging is employed to correct CFSR bias in soil temperature and moisture using in situ observations. To investigate the impacts of the corrected soil state on model forecasts, two numerical model simulations—a control run with CFSR soil state and a disturbed run with the corrected soil state—were conducted using the Weather Research and Forecasting model. All the simulations are initiated four times per day and run 48 hours. Model results show that the corrected soil state, i.e. warmer and drier surface over the most parts of China, can enhance evaporation over wet regions, which changes the overlying atmospheric temperature and moisture. The changes of the lifting condensation level, level of free convection, and water transport due to corrected soil state favor precipitation over wet regions, while prohibiting precipitation over dry regions. Moreover, diagnoses indicate that the remote moisture flux convergence plays a dominant role in the precipitation changes over the wet regions.

The data from CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations) satellite was used to analyze the aerosol micro-physical properties over Beijing and surrounding area during haze periods from 2007 to 2008 in this paper. The results showed as follows. The values of TABC (total attenuated backscatter coefficient) for aerosols accounted for about 25% with varying altitudes. The aerosol scattering ability little changed from 0-4 km, showing that the aerosol layer evenly distribute. At different altitude ranges (0-1, 1-2, 2-3 and 3-4 km above ground level), values of TABC almost concentrate in the range of 2.5×10-3 -4.5×10-3 km-1.sr-1. In spring, summer and winter, aerosol scattering has the similar variation, with the maximum of TABC ranging from 3.5×10-3 km-1.sr-1 to 4.5×10-3 km-1.sr-1, while the maximum of TABC in autumn is from 1.5×10-3 km-1.sr-1 to 2.5×10-3 km-1.sr-1. Aerosol shape and size are characterized by VDR (volume depolarization ratio) and TACR (total attenuated color ratio). Aerosols with VDR greater than 10% were more than the ones with VDR less than 10% at the same altitude range. Notably, aerosols with smaller VDR (0-10%) appeared more frequently in autumn than those in the other three seasons. For each altitude range, aerosols with TACR ranging from 0-0.2 contributed much more than those with TACR ranging from 1.8-2.0. The size of aerosols in summer was the largest and that in autumn was the smallest in middle and lower troposphere.

Based on four year' 2B-CLDCLASS-Lidar (Radar-Lidar) cloud classification product from CloudSat, we analyze the geographical distributions of different cloud types and their co-occurrence frequency across different seasons, moreover, utilize the vertical distributions of cloud type to further evaluate the cloud overlap assumptions. The statistical results show that more high clouds, altocumulus, stratocumulus or stratus and cumulus are identified in the Radar-Lidar cloud classification product compared to previous results from Radar-only cloud classification (2B-CLDCLASS product from CloudSat). In particularly, high clouds and cumulus cloud fractions increased by factors 2.5 and 4–7, respectively. The new results are in more reasonable agreement with other datasets (typically the International Satellite Cloud Climatology Project (ISCCP) and surface observer reports). Among the cloud types, altostratus and altocumulus are more popular over the arid/semi-arid land areas of the Northern and Southern Hemispheres, respectively. These features weren't observed by using the ISCCP D1 dataset. For co-occurrence of cloud types, high cloud, altostratus, altocumulus and cumulus are much more likely to co-exist with other cloud types. However, stratus/stratocumulus, nimbostratus and convective clouds are much more likely to exhibit individual features. After considering the co-occurrence of cloud types, the cloud fraction based on the random overlap assumption is underestimated over the vast ocean except in the west-central Pacific Ocean warm pool. Obvious overestimations are mainly occurring over land areas in the tropics and subtropics. The investigation therefore indicates that incorporate co-occurrence information of cloud types based on Radar-Lidar cloud classification into the overlap assumption schemes used in the current GCMs possible be able to provide an better predictions for vertically projected total cloud fraction.

Hyperspectral infrared observations from AIRS are used to determine cloud thermodynamic phase. These phase retrievals are compared with co-located CALIPSO lidar products to investigate relationships between cloud phase, height, and temperature.

Recent progress in the determination of cloud phase using infrared AIRS hyperspectral observations is presented. CALIPSO lidar products are used to create a database of manually classified AIRS pixels for algorithm development.

Asian dust can be transported long distances from the Taklimakan or Gobi desert to North America across the Pacific Ocean, and it has been found to have a significant impact on ecosystems, climate, and human health. Although it is well known that Asian dust is transported all over the globe, there are limited observations reporting Asian dust transported to the Arctic. We report a case study of a large-scale heavy dust storm over East Asia on 19 March 2010, as shown by ground-based and space-borne multi-sensor observations, as well as NCEP/NCAR reanalysis data and HYSPLIT trajectories. Our analysis suggests that Asian dust aerosols were transported from northwest China to the Arctic within 5 days, crossing eastern China, Japan and Siberia before reaching the Arctic. The results indicate that Asian dust can be transported for long distances along a previously unreported transport path. Evidence from other dust events over the past decade (2001-2010) also supports our results, indicating that dust from 25.2% of Asian dust events has potentially been transported directly to the Arctic. The transport of Asian dust to the Arctic is due to cyclones and the enhanced East Asia Trough (EAT), which are very common synoptic systems over East Asia. This suggests that many other large dust events would have generated long-range transport of dust to the Arctic along this path in the past. Thus, Asian dust potentially affects the Arctic climate and ecosystem, making climate change in the Arctic much more complex to be fully understood.

The impact of Asian dust on the determination of cloud phase is analyzed over dust sources and downwind using cloud phase products from cloud-aerosol lidar and infrared pathfinder satellite observations (CALIPSO), atmospheric infrared sounder (AIRS), moderate resolution imaging spectroradiometer (MODIS), and polarization and anisotropy of reflectances for atmospheric sciences coupled with observations from a lidar (PARASOL). The results show that the presence of dust greatly affects determination of cloud phase in both source and downwind regions. CALIPSO products demonstrate better ice cloud discrimination of about 70% and 60% over source and downwind regions, respectively, compared to passive sensors. These results suggest that semi-direct effects of dust, which act to warm clouds and evaporate large cloud particles, may play a role in cloud phase determination. This study suggests that the presence of dust tends to increase misclassification of ice clouds as water or uncertain phase by AIRS, MODIS, and PARASOL.