This PDF file contains the front matter associated with SPIE Proceedings Volume 12265, including the Title Page, Copyright information, Table of Contents, and Conference Committee listings.

The paper uses Level 2 IASI (Infrared Atmospheric Sounder Interferometer) products to analyse long-standing heatwaves and related droughts. The paper is mostly interested in studying and assessing the effect of drought on vegetation. To this end, we have devised a series of indices sensitive to the water deficit. IASI retrievals are used to derive indices from the surface temperature, emissivity, and temperature/humidity atmospheric profiles. We define the emissivity contrast index, which is sensitive to the land cover and type, and the water deficit index, which combines the surface and air dew point temperatures. These two indices are assessed by considering the heatwave, which hit most of Europe and the Mediterranean basin in 2017. The application of the methodology will be shown by considering a target area in Southern Italy, where woodlands are suffering from climate change. It will be shown that the two indices are sensitive to the water deficit caused by long-lasting droughts.

Long-term exposure to airborne fine particulate matter or PM2.5 is associated with an increase in the long-term risk of premature death that creates critical concerns for public health. This study uses twenty years (2002-2021) of daily remotely sensed data with multi-spatial resolution of 1 km to 3 km to examine the long-term spatiotemporal distribution of PM2.5 across Thailand. Good agreement is found between the in-situ measurements of PM2.5 and instantaneous estimates made from the satellite data with correlation coefficients of 0.51. Based on data analysis during the year 2002- 2021, the region with the highest yearly averaged concentration level of PM2.5 was a central region of Thailand (19.91 μg.m^-3) followed by northern (19.11 μg.m^-3), northeastern (18.92 μg.m^-3), eastern (18.76 μg.m^-3) and southern (16.16 μg.m^-3) region, respectively. The period with the highest PM2.5 levels were during March and April with monthly averages 23.74 to 26.72 μg.m^-3. For the 20-year record, monthly-mean PM2.5 concentration in northern Thailand showed statistically significant increase at the rate of 0.14 μg.m-3 month-1 in dry season, the same as in the northeastern (0.126 μg.m-3month-1), eastern (0.12 μg.m-3 month-1) and Central region (0.083 μg.m^-3 month-1). While the southern region has a negative trend (-0.018 μg.m^-3 month-1) which is different from other regions. The spatiotemporal variation and changing of PM2.5 concentrations were a result of both changing in meteorological factors and anthropogenic activities. Here, we discuss and present possible explanations for long-term spatiotemporal variation of PM2.5.

The economy of the Indian subcontinent primarily depends on the two monsoons - the southwest and the northeast. The southeast monsoon occurs in June-September bringing rainfall throughout India. The northeast monsoon brings rainfall to the southern peninsula, from October-December. The two monsoons, especially the northeast one,demand very careful study due to devastating impacts of cyclones causing loss of life and property. The authors wish to investigate the two monsoons over a few locations in India, namely Bangalore, Bhubaneswar, Kolkata, Gadanki, Chennai, Machilipatnam, Kakdwip, Karaikal, Mangalore, Mumbai, Panjim, Puri, Trivandrum, and Vishakhapatnam, in the context of the dominance of convective and stratiform rain over surface rainfall. They have analyzed the frequency of occurrence of convective/stratiform rain, and the percentage contribution of these categories to surface rainfall. The authors use the cloud liquid water (CLW) and latent heat (LH) from the surface up to 18 km to investigate the occurrence of the peak cloud liquid water level (HPCL) and the levels of the multiple evolution latent heat (MLHevol). TheCLW and LH are obtained from the data product 2A12 of the Tropical Microwave Imager (TMI) aboard the Tropical Rainfall Measuring Mission (TRMM) satellite. The selected parameters (CLW and LH) are used to estimate contributions of convective and stratiform clouds to surface rainfall. The study analyzes the above-mentioned data during 1999-2008. The paper describes the salient features of the southwest and northeast monsoon in the light of convective/stratiform dominance of surface rainfall and the occurrence of HPCL at different levels in the atmosphere. The paper also reviews a few observable climatological aspects, viz. occurrence of cyclones and floods in the two monsoons.

In this work, a nonlinear statistical regressor method based on deep learning feed-forward neural network (NN) for the retrieval of atmospheric CH₄ is proposed. The methodology has been trained and validated on a simulated dataset of observations by the processing of the Monitoring Atmospheric Composition and Climate (MACC) Reanalysis dataset with the state-of-the-art transfer model (RTM) σ-IASI-as. Global data related to one day of the 12 months of 2012 and four synoptic hours (00-06-12-18 UTC) have been processed to catch typical seasonal and diurnal cycles, corresponding to a fairly large number (168.000) of simulated IASI-L1 spectral radiances. CH₄ profiles have been predicted on 60 pressure layers. A regression framework based on the principal components analysis (PCA) of the IASI radiances and CH₄ profiles has been implemented. The choice of the number of principal components has been addressed by the study of their eigenvalues, to filter redundant information from IASI channels and extract the most significant information from the CH₄ profiles. The analysis of the NN retrieval, shows agreement with the reference MACC CH4 contents, allowing to obtain unbiased profile estimates, with accuracy on the total content of about 1.55%. The same accuracy has been obtained for the tropospheric column while for the stratosphere atmospheric column the accuracy is about 3%. Finally, an additional analysis of the CH₄ total content shows a correlation between the reference and predicted values of about 0.97.

The focus of this paper is to report results of comparison of unfiltered shortwave radiances measured by CERES scanners while implementing a strategy, referred to as “matched sites targeting”, in which CERES instruments scan at nadir along their respective collocated ground-tracks. This strategy is enabled by similarities in the Suomi-NPP (FM5)/NOAA20 (FM6) and Aqua (FM3) satellite orbits, and a special scan profile available for the CERES scanners. Comparison of collected data in this strategy is done at a footprint level between the instruments(FM5 and FM3 or FM6 and FM3) for specific scene types, determined by their “almost” coincidental ground-tracks. A far more stringent test of the measurement consistency is achieved as averages of 330 collocated nadir samples are compared. Results of the unfiltered shortwave radiance comparison with the focus on clear-sky cases over ocean or snow are based on ES8 or ERBE-like data product using Edition2 for FM5, Edition1 for FM6 and Edition4 for FM3; cloud coverage is verified using MODIS data for FM3 and VIIRS data for FM5/FM6, which are available in SSF products.

Advances in interference filter technology permit currently using selected parts of the N₂ and O₂ pure rotational Raman spectra with very low temperature sensitivity, while rejecting sufficiently the elastic return. The Raman technique to retrieve the aerosol extinction coefficient can then be used with higher signal-to-noise ratios, because of a higher (about 8 times) effective differential backscatter cross-section as compared to the cross-section of the N2 vibro-rotational spectra. The design and results of pure rotational Raman channels at 354 nm and 530 nm allowing daytime aerosol extinction measurements implemented at the EARLINET/ACTRIS Barcelona lidar station are presented and discussed.

We show the field-deployable prototype which can demonstrate this concept in the field testing. The prototype has the newly developed optical transceiver and optics. The transceiver integrates all functions of (i) pulse modulation of the transmitted light, (ii) heterodyne detection of the received light, (iii) digital signal processing, and (iv) system operation control. The optics is also unique and capable of multi-directional transmitting and receiving with one telescope. The above-mentioned technologies contribute to the compactness and portability. The optical circuit is the fiber-based. The size of the prototype is 1100 mm * 900 mm * 800 mm. The vertical profiling of the wind direction can be realized simultaneously owing to this multi-directional optics, in addition to the profiling of the water vapor density and wind speed. Some results of the initial observation test with the prototype are shown in addition to the preliminary test with the bench-top system. It was confirmed that the water vapor density and wind speed are measured simultaneously with the measurable range of more than 500 m, range resolution of 100 m, and measurement interval of 10 minutes. The correlation between the DIAL-measured water vapor density and the one measured by an in-situ sensor is also shown.

This paper describes a ground-based pulsed Cloud-Aerosol Lidar system for providing a backscatter laser signal at both wavelengths 532 and 1064 nm, from which aerosol and cloud profiles are derived. The Lidar system is installed on the roof of a building in a monostatic biaxial configuration. Test measurements show that the Lidar system is capable of resolving cloud structure and identifying the presence of aerosols from the ground up to a distance of 15 km. The performance of the Lidar system is considered adequate for routine measurements. This paper provides information on the basic features and performance of the Lidar system. The measurements confirm the excellent sensitivity of the detection chain. Recent improvements in the Lidar detection chain with improved dynamic range are also discussed.

The area around the Japanese Alps, which is the focus of this study, is located at the center of Japan's main island and surrounded by mountains with multiple basins. Here, we investigated the effect of mountains on aerosol blocking with respect to transboundary pollution and estimated the effect of the mountain source with respect to local pollution using observations and simulations. A regional chemical transport model was employed for the study. To investigate the effect of mountains, simulations were conducted with and without mountains. From the results of these simulations, we estimated the mountain effects. The presence of mountains was found to increase or decrease aerosol concentration in some cases. However, when averaged over the simulation period, the results showed that mountains effectively reduce aerosol concentrations. On the days when aerosol concentrations increased due to the mountain effect, meteorological conditions with high local emissions and the basin effect acted synergistically to accelerate the increase in aerosol concentrations.

The number of severe wildfires has increased globally since 2019, occurring every day worldwide. Therefore, our previous studies have focused on the characterization of biomass burning aerosols derived from heavy wildfires. Serious aerosol events include not only biomass burning plumes, but also many other kinds of aerosol events such as desert dust storms and those derived from the combination of natural factors and human activities. This work proposes the use of polarization information for detecting severe aerosol events, using wildfire as an example. The Japanese mission JAXA/GCOM (Global Change Observation Mission-Climate)-C (SHIKISAI in Japanese), launched in 2017, carried a second-generation global imager (SGLI). The SGLI contains 19 channels from near-ultraviolet to thermal infrared (IR), including red (674 nm designated as the PL1 band) and near-IR (869 nm; PL2 band) polarization channels. This work intends to demonstrate the advantages of the SGLI, especially polarization information, in detecting and characterizing severe biomass burning aerosols.

Doppler lidars with daylight capability are challenging systems because of the small field of view (FOV), spectral filtering, and other additional subsystems required compared to observations at night. A universal Doppler Lidar platform with all the required technologies for automatic operation is assembled. By combining a novel narrow-bandwidth pulsed laser (FWHM ~3 MHz) and a matched interferometer (FWHM ~7.5 MHz) the backscattered signals from molecules and aerosols are separated into two channels within the receiver. By tuning the frequency of the pulsed laser from pulse to pulse with sub-MHz accuracy relative to the interferometer, Doppler-aerosol measurements with largely reduced Rayleigh-signal allow aerosol measurements from ground to ~25 km altitude, including Doppler-wind measurements from the Doppler-shift. The compact lidar (1m^3) is built for automatic 24/7 operation and comprises a novel diode-pumped alexandrite ring-laser, a 50cm-telescope and a receiver for solar background free aerosol measurements. The combination of cost-efficient design and fast assembling of such a system allows the construction of a Doppler Lidar network with identical units. Such a network can address a wide range of horizontal and vertical scales.

Scattering of light by ice crystals of cirrus clouds is an important problem for remote sensing of clouds and the atmosphere. Such a solution is necessary for the interpretation of data obtained be the active and passive remote sensing instruments, such as lidars and photometers. Ice crystals in cirrus clouds are large non-spherical particles. To solve the problem of light scattering by large non-spherical particles, it is not possible to apply rigorous numerical methods such as FDTD, DDA, PSDT, due to their high computational complexity for large particles. This problem also cannot be solved within the framework of the classical geometric optics approximation, since this method does not take into account such phenomena as diffraction and interference, which have a significant effect in the vicinity of the backscattering direction. This report presents the solution for the problem of light scattering by non-spherical particles with sizes from 10 to 1000 μm. The results were obtained within the framework of the physical optics approximation. The obtained database of light scattering matrices allows one to improve the accuracy of interpretation of laser sounding data of atmospheric aerosol and crystal clouds for lidars and remote sensing applications.

The paper presents a solution to the problem of light scattering by small randomly oriented ice crystals of arbitrary shape. The solution was obtained within the discrete dipole approximation. The particle sizes ranged from 0.02 up to 4 μm. The wavelength of the incident radiation is 0.532 μm, the refractive index is 1.3116. The influence of the number of dipoles per lambda and number of orientations on the convergence of the solution is shown. It is shown that the computation time has an exponential law dependence on particle size.

The paper presents peculiarities of polarization at vicinity of near backscattering direction for large randomly oriented irregular particles. We used our physical optics approximation where the light scattered inside the particle consists of many plane-parallel beams. It is shown that the backscattering peak is caused by of interference between the light beams with any number of refraction/reflection events; however, only pair of conjugate beams with four events (two internal reflections and two refractions at the exit faces of the particle) lead to local minimum in polarization element in scattering (Mueller) matrixes and create negative polarization.

The elements of light backscattering matrix for atmospheric ice hexagonal particles with distorted shapes with random spatial orientation were calculated within the physical optics approximation. Three different set of particle geometry shapes was created by distortion of a solid hexagonal column for calculation. The distortion angle for each method is 0- 50 degrees. The wavelength of the incident radiation was 1.064 μm. The backscattering cross section, the linear depolarization ratio, and the lidar ratio are presented.

Observations from spaceborne microwave (MW) and infrared (IR) passive sensors are the backbone of current satellite meteorology, essential for data assimilation into modern numerical weather prediction and climate benchmarking. In this context, over the last decades, the study and the analysis of cloud microphysics have received increasing attention to better understand cloud feedbacks on climate. MW and IR observations from space offer complementary features concerning cloud microphysics, and various tools have been developed to retrieve cloud parameters such as the effective radius of water and ice clouds. However, MW-IR synergy for cloud investigation is currently under-explored. In this framework, innovative processing methods, such as those based on the use of Artificial Intelligence (AI), which can run on large databases and can handle hundreds of input variables from different sensors, such as those operating in hyperspectral and multispectral channels of the infrared and the microwave bands, such as the New Generation Atmospheric Sounding Interferometer (IASI-NG) and the Microwave Sounder (MWS) of the EPS second generation (EPSSG) platforms whose forthcoming launch is scheduled from 2024 onwards. A regression framework has been implemented based on the combined use of Random Forest (RF) regression and the principal components analysis (PCA) of IASI-NG and MWS observations to input the RF regressors. The supervised learning of liquid and ice water clouds' effective radii was carried out based on this framework. In conclusion, the regression analysis shows good agreement between reference and retrieved effective radius, with 80% correlation and root-mean-square error (RMSE) of 0.68 μm for liquid and 11.6 μm for ice cloud effective radius.