This study focuses on the analysis of aerosol hygroscopic growth during the
Sierra Nevada Lidar AerOsol Profiling Experiment (SLOPE I) campaign by using
the synergy of active and passive remote ...sensors at the ACTRIS Granada
station and in situ instrumentation at a mountain station (Sierra Nevada,
SNS). To this end, a methodology based on simultaneous measurements of
aerosol profiles from an EARLINET multi-wavelength Raman lidar (RL) and
relative humidity (RH) profiles obtained from a multi-instrumental approach
is used. This approach is based on the combination of calibrated water vapor
mixing ratio (r) profiles from RL and continuous temperature profiles from
a microwave radiometer (MWR) for obtaining RH profiles with a reasonable
vertical and temporal resolution. This methodology is validated against the
traditional one that uses RH from co-located radiosounding (RS) measurements,
obtaining differences in the hygroscopic growth parameter (γ) lower
than 5 % between the methodology based on RS and the one presented here.
Additionally, during the SLOPE I campaign the remote sensing methodology used
for aerosol hygroscopic growth studies has been checked against Mie
calculations of aerosol hygroscopic growth using in situ measurements of
particle number size distribution and submicron chemical composition measured
at SNS. The hygroscopic case observed during SLOPE I showed an increase in
the particle backscatter coefficient at 355 and 532 nm with relative
humidity (RH ranged between 78 and 98 %), but also a decrease in the
backscatter-related Ångström exponent (AE) and particle linear
depolarization ratio (PLDR), indicating that the particles became larger and
more spherical due to hygroscopic processes. Vertical and horizontal wind
analysis is performed by means of a co-located Doppler lidar system, in order
to evaluate the horizontal and vertical dynamics of the air masses. Finally,
the Hänel parameterization is applied to experimental data for both
stations, and we found good agreement on γ measured with remote
sensing (γ532=0.48±0.01 and γ355=0.40±0.01) with respect to the values calculated using Mie theory
(γ532=0.53±0.02 and γ355=0.45±0.02),
with relative differences between measurements and simulations lower than
9 % at 532 nm and 11 % at 355 nm.
Bismuth sodium titanate (BNT)‐derived materials have seen a flurry of research interest in recent years because of the existence of extended strain under applied electric fields, surpassing that of ...lead zirconate titanate (PZT), the most commonly used piezoelectric. The underlying physical and chemical mechanisms responsible for such extraordinary strain levels in BNT are still poorly understood, as is the nature of the successive phase transitions. A comprehensive explanation is proposed here, combining the short‐range chemical and structural sensitivity of in situ Raman spectroscopy (under an applied electric field and temperature) with macroscopic electrical measurements. The results presented clarify the causes for the extended strain, as well as the peculiar temperature‐dependent properties encountered in this system. The underlying cause is determined to be mediated by the complex‐like bonding of the octahedra at the center of the perovskite: a loss of hybridization of the 6s2 bismuth lone pair interacting with the oxygen p‐orbitals occurs, which triggers both the field‐induced phase transition and the loss of macroscopic ferroelectric order at the depolarization temperature.
Bismuth sodium titanate (BNT)‐derived materials show extended strain under applied electric fields, surpassing that of lead zirconate titanate (PZT), which is the most commonly used piezoelectric. The mechanism of the extended strain is, however, poorly understood, in particular its structural and chemical origins. The results presented clarify the causes of the extended strain and the peculiar temperature‐dependent properties encountered in this system.
Soil moisture, especially surface soil moisture (SSM), plays an important role in the development of various natural hazards that result from extreme weather events such as drought, flooding, and ...landslides. There have been many remote sensing methods for soil moisture retrieval based on microwave or optical thermal infrared (TIR) measurements. TIR remote sensing has been popular for SSM retrieval due to its fine spatial and temporal resolutions. However, because of limitations in the penetration of optical TIR radiation and cloud cover, TIR methods can only be used under clear sky conditions. Microwave SSM retrieval is based on solid physical principles, and has advantages in cases of cloud cover, but it has low spatial resolution. For applications at the local scale, SSM data at high spatial and temporal resolutions are important, especially for agricultural management and decision support systems. Current remote sensing measurements usually have either a high spatial resolution or a high temporal resolution, but not both. This study aims to retrieve SSM at both high spatial and temporal resolutions through the fusion of Moderate Resolution Imaging Spectroradiometer (MODIS) and Land Remote Sensing Satellite (Landsat) data. Based on the universal triangle trapezoid, this study investigated the relationship between land surface temperature (LST) and the normalized difference vegetation index (NDVI) under different soil moisture conditions to construct an improved nonlinear model for SSM retrieval with LST and NDVI. A case study was conducted in Iowa, in the United States (USA) (Lat: 42.2°~42.7°, Lon: −93.6°~−93.2°), from 1 May 2016 to 31 August 2016. Daily SSM in an agricultural area during the crop-growing season was downscaled to 120-m spatial resolution by fusing Landsat 8 with MODIS, with an R2 of 0.5766, and RMSE from 0.0302 to 0.1124 m3/m3.
Surface soil moisture (SSM) is an important parameter at the land-atmosphere interface. In past decades, passive microwave remote sensing offers a good opportunity for obtaining SSM on a global ...scale, and many downscaling methods have been proposed using the triangle-based empirical soil moisture relationship models to overcome the limitation of coarse spatial resolution of its SSM products for regional applications. This paper aimed to examine and compare the effectiveness of five typical triangle-based empirical soil moisture relationship models for estimating SSM with Landsat-5 data and in situ measurements from the Maqu network on the northeastern part of the Tibetan Plateau for nine cloud-free days. The results showed that the model that treats the SSM as a second-order polynomial with land surface temperature, vegetation indices (VIs), and surface albedo as inputs exhibited the best performance compared with the results of other models. The VI comparison indicated that the use of the normalized difference VI or the fractional vegetation cover in this model outperformed other VIs, with the root-mean-square deviation of approximately 0.055 m 3 /m 3 and the coefficient of determination (\text{R}^{2} ) above 0.78 at the nine-day average level. In addition, a significant spatial scale effect of the model was also found through analyzing the model fitting results at different window sizes. The study provides important insight into the best empirical relationship models for capturing soil moisture dynamics. These models can support the passive microwave soil moisture data spatial downscaling and validation applications in future studies.
Cloud droplet number concentration (Nd) is an important parameter of liquid clouds and is crucial to understanding aerosol-cloud interactions. It couples boundary layer aerosol composition, size and ...concentration with cloud reflectivity. It affects cloud evolution, precipitation, radiative forcing, global climate and, through observation, can be used to partially monitor the first indirect effect.
With its unique combination of multi-wavelength, multi-angle, total and polarized reflectance measurements, the Research Scanning Polarimeter (RSP) retrieves Nd with relatively few assumptions. The approach involves measuring cloud optical thickness, mean droplet extinction cross-section and cloud physical thickness. Polarimetric observations are capable of measuring the effective variance, or width, of the droplet size distribution. Estimating cloud geometrical thickness is also an important component of the polarimetric Nd retrieval, which is accomplished using polarimetric measurements in a water vapor absorption band to retrieve the amount of in-cloud water vapor and relating this to physical thickness. We highlight the unique abilities and quantify uncertainties of the polarimetric approach.
We validate the approach using observational data from the North Atlantic and Marine Ecosystems Study (NAAMES). NAAMES targets specific phases in the seasonal phytoplankton lifecycle and ocean-atmosphere linkages. This study provides an excellent opportunity for the RSP to evaluate its approach of sensing Nd over a range of concentrations and cloud types with in situ measurements from a Cloud Droplet Probe (CDP). The RSP and CDP, along with an array of other instruments, are flown on the NASA C-130 aircraft, which flies in situ and remote sensing legs in sequence.
Cloud base heights retrieved by the RSP compare well with those derived in situ (R = 0.83) and by a ceilometer aboard the R.V. Atlantis (R = 0.79). Comparing geometric mean values from 12 science flights throughout the NAAMES-1 and NAAMES-2 campaigns, we find a strong correlation between Nd retrieved by the RSP and CDP (R = 0.96). A linear least squares fit has a slope of 0.92 and an intercept of 0.3 cm−3. Uncertainty in this comparison can be attributed to cloud 3D effects, nonlinear liquid water profiles, multilayered clouds, measurement uncertainty, variation in spatial and temporal sampling, and assumptions used within the method. Radiometric uncertainties of the RSP measurements lead to biases on derived optical thickness and cloud physical thickness, but these biases largely cancel out when deriving Nd for most conditions and geometries. We find that a polarimetric approach to sensing Nd is viable and the RSP is capable of accurately retrieving Nd for a variety of cloud types and meteorological conditions.
•We present a new method for sensing cloud droplet concentration using polarimetry.•We find a strong correlation between remotely sensed and in situ measurements.•The method requires relatively few assumptions of cloud vertical structure.•The method offers unique advantages over traditional techniques.•We validate the approach using observational data from NASA NAAMES air campaign.
Improvements in air quality and Earth’s climate predictions require improvements of the aerosol speciation in chemical transport models, using observational constraints. Aerosol speciation (e.g., ...organic aerosols, black carbon, sulfate, nitrate, ammonium, dust or sea salt) is typically determined using in situ instrumentation. Continuous, routine surface network aerosol composition measurements are not uniformly widespread over the globe. Satellites, on the other hand, can provide a maximum coverage of the horizontal and vertical atmosphere but observe aerosol optical properties (and not aerosol speciation) based on remote sensing instrumentation. Combinations of satellite-derived aerosol optical properties can inform on air mass aerosol types (AMTs e.g., clean marine, dust, polluted continental). However, these AMTs are subjectively defined, might often be misclassified and are hard to relate to the critical parameters that need to be refined in models.
In this paper, we derive AMTs that are more directly related to sources and hence to speciation. They are defined, characterized, and derived using simultaneous in situ gas-phase, chemical and optical instruments on the same aircraft during the Study of Emissions and Atmospheric Composition, Clouds, and Climate Coupling by Regional Surveys (SEAC4RS, US, summer of 2013). First, we prescribe well-informed AMTs that display distinct aerosol chemical and optical signatures to act as a training AMT dataset. These in situ observations reduce the errors and ambiguities in the selection of the AMT training dataset. We also investigate the relative skill of various combinations of aerosol optical properties to define AMTs and how much these optical properties can capture dominant aerosol speciation.
We find distinct optical signatures for biomass burning (from agricultural or wildfires), biogenic and dust-influence AMTs. Useful aerosol optical properties to characterize these signatures are the extinction angstrom exponent (EAE), the single scattering albedo, the difference of single scattering albedo in two wavelengths, the absorption coefficient, the absorption angstrom exponent (AAE), and the real part of the refractive index (RRI). We find that all four AMTs studied when prescribed using mostly airborne in situ gas measurements, can be successfully extracted from at least three combinations of airborne in situ aerosol optical properties (e.g., EAE, AAE and RRI) over the US during SEAC4RS. However, we find that the optically based classifications for BB from agricultural fires and polluted dust include a large percentage of misclassifications that limit the usefulness of results relating to those classes. The technique and results presented in this study are suitable to develop a representative, robust and diverse source-based AMT database. This database could then be used for widespread retrievals of AMTs using existing and future remote sensing suborbital instruments/networks. Ultimately, it has the potential to provide a much broader observational aerosol data set to evaluate chemical transport and air quality models than is currently available by direct in situ measurements.
This study illustrates how essential it is to explore existing airborne datasets to bridge chemical and optical signatures of different AMTs, before the implementation of future spaceborne missions (e.g., the next generation of Earth Observing System (EOS) satellites addressing Aerosol, Cloud, Convection and Precipitation (ACCP) designated observables).
An aerosol layer in the upper troposphere and lower stratosphere over the Asian summer monsoon (ASM) regions, namely, the Asian tropopause aerosol layer (ATAL), has been observed based on satellite ...remote sensing and in situ measurements; however, its source is still under debate. In August 2018, an experimental campaign over the Tibetan Plateau at Golmud (GLM, 36.48 °N, 94.93 °E) was performed, during which a balloon-borne Portable Optical Particle Counter was used to measure the aerosol particle profile. Backward-trajectory simulations were conducted with the Massive-Parallel Trajectory Calculations model to investigate the possible sources and transport pathways of the observed particles. The in situ measurements showed a robust ATAL around the tropopause, 16 km above sea level, with a maximum aerosol number density of 35 cm−3 and a maximum aerosol mass concentration of 0.15 g m−3 for particles with diameters between 0.14 and 3 m. The aerosol particles in the ATAL are mostly smaller than 0.25 m in diameter, accounting for 98% of all aerosol particles detected. The backward-trajectory analysis revealed that the air parcels arrived at the altitude of the ATAL through two separate pathways: (1) the uplift below the 360 K isentropic surface, where air parcels were first elevated to the upper troposphere and then joined the ASM anticyclonic circulation; and (2) the quasi-horizontal transport along the anticyclonic circulation, located approximately between the 360 and 420 K isentropic surfaces. The complex transport pathways may aggravate the challenge of analyzing the composition of the ATAL, and further observation campaigns are required to extend our knowledge.
In addition to the duration and intensity of rainfall, infiltration processes are strongly affected by the hydraulic properties of the soil. In the case of heterogeneous and stratified soil profiles, ...the analysis of the infiltration process becomes more complex, since conflicting hydraulic properties of adjacent layers can induce locally diverted flow. Soils of volcanic origin present these characteristics, because during the various eruptive phases, layers with very different textures are deposited. In this article, data are analysed which have been recorded by a monitoring station installed on a slope made up of volcanic deposits. The station consists of a rain gauge to measure rainfall and seven tensiometers and eight TDR probes installed at different depths to measure suction and volumetric water content, respectively. The slope is made up of alternating volcanic ash (silt‐sandy‐clay paleosoils) interspersed with pumice (sandy‐gravel), due to the different eruptive phases of the volcanic complexes in the area. The analysis of the data established that the layers of coarser material (pumices), depending on the initial moisture conditions, may hinder or even favour the infiltration of water into the deeper layers. In particular, when water content is low, the pumices presented a low unsaturated conductivity which hindered infiltration. By contrast, in wetter conditions, they favoured the flow of water. Therefore, the initial moisture conditions of the soil layers must be taken into account for a correct prediction of the infiltration phenomena. Dry conditions of the pumice layers can hinder drainage into the lower layers, thus favouring the rapid accumulation of soil water during rainfall events, which could eventually lead to slope failure.
The results obtained indicate that coarse pumice layers, when they have a low water content, delay the advancement of the wet front, inducing the accumulation of water in the overlying ashes. Conversely, when they are wet, they can even promote the passage of water into the underlying ash layer. In addition to the duration and intensity of rainfall, infiltration is therefore strongly influenced by the initial conditions of water content of the pumice layers.
In-situ snow measurements conducted by European institutions for operational, research, and energy business applications were surveyed in the framework of the European Cooperation in Science and ...Technology (COST) Action ES1404, called "A European network for a harmonised monitoring of snow for the benefit of climate change scenarios, hydrology, and numerical weather prediction". Here we present the results of this survey, which was answered by 125 participants from 99 operational and research institutions, belonging to 38 European countries. The typologies of environments where the snow measurements are performed range from mountain to low elevated plains, including forests, bogs, tundra, urban areas, glaciers, lake ice, and sea ice. Of the respondents, 93% measure snow macrophysical parameters, such as snow presence, snow depth (HS), snow water equivalent (SWE), and snow density. These describe the bulk characteristics of the whole snowpack or of a snow layer, and they are the primary snow properties that are needed for most operational applications (such as hydrological monitoring, avalanche forecast, and weather forecast). In most cases, these measurements are done with manual methods, although for snow presence, HS, and SWE, automatized methods are also applied by some respondents. Parameters characterizing precipitating and suspended snow (such as the height of new snow, precipitation intensity, flux of drifting/blowing snow, and particle size distribution), some of which are crucial for the operational services, are measured by 74% of the respondents. Parameters characterizing the snow microstructural properties (such as the snow grain size and shape, and specific surface area), the snow electromagnetic properties (such as albedo, brightness temperature, and backscatter), and the snow composition (such as impurities and isotopes) are measured by 41%, 26%, and 13% of the respondents, respectively, mostly for research applications. The results of this survey are discussed from the perspective of the need of enhancing the efficiency and coverage of the in-situ observational network applying automatic and cheap measurement methods. Moreover, recommendations for the enhancement and harmonization of the observational network and measurement practices are provided.
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