The Japanese space mission JAXA/GCOM (Global Change Observation Mission-Climate)-C launched in 2017 carries a second-generation global imager (SGLI). The SGLI contains 19 channels from near-UV to thermal infrared (IR), including red (674 nm named PL1 band) and near-IR (869 nm; PL2 band) polarization channels. SGLI’s spatial resolution is fine as the instantaneous field-of-view (IFOV) is 250 m from the near-UV to short-IR wavelength range for radiometry and 1 km for the polarization measurements. This work presents retrieval algorithms for BBA (biomass burning aerosol) using the advantages of SGLI features. The BBA generated by wildfires causes long-range advection migration. Severe wildfires, which now frequently occur around the world, have become a major environmental problem. As an example of large scale wildfires in September of 2020 around western North America, we show that SGLI’s simultaneous observation of radiance and polarization is useful for characterization of BBA. Further, a regional numerical model SCALE (Scalable Computing for Advanced Library and Environment) is used to consider meteorological conditions and/or topography. The objective of this study is to better understand the BBA events through the integration of space-borne and ground-based measurements as well as the regional meteorological model.

This study shows a method for the direct detection of severe biomass burning aerosols (SBBAs) from SGLI data. Polarization data derived from polarization remote sensing was incorporated to improve the detection accuracy. This is possible because the SGLI is a multi-wavelength sensor consisting of 19 channels from 380 nm in the near-UV to thermal infrared, including red (674 nm) and near-infrared (869 nm) polarization channels. In order to examine the difference between radiance and polarized radiance distributions, BC aerosol distributions by altitude obtained from chemical transport model simulations were used. The radiance distribution corresponds well to the aerosol distribution in the vertical integration, and the polarized radiance corresponds well to the aerosol distribution in the upper layers. That is, polarization information is useful for understanding aerosols in the upper layer of the atmosphere at the time of observation.

This study presents aerosol retrieval from space over extreme biomass burning events. The Japanese mission GCOM-C launched in 2017 loads only SGLI imager. The SGLI contains 19 channels from near-UV to thermal-infrared, including red (0.674 µm) and near-infrared (0.869 µm) polarization channels. This work enhances the advantages of SGLI feature in aerosol remote sensing. It has been shown in the previous work that the near-UV data not only detected absorbing aerosols such as biomass burning aerosols (BBA) or mineral dust (DUST), but is also used to distinguish between BBA and DUST with short wave-IR data. Using a large forest fire in western Canada in 2018 as an example, we show that mutual use of radiance and polarization measurements by SGLI is useful for radiation simulations to characterize heavy biomass burning aerosols.

We observed PM2.5 concentration levels in a mountainous area at the center of the main island of Japan in March 2020. The factors causing a change in the PM2.5 concentration are investigated by comparing the concentration levels on two days. One of the factors is the contribution of local sources. The day when the concentration was low was a holiday and visual observation confirmed very low near the observation site. Comparison of the meteorological conditions indicated that on the high concentration day, when the boundary layer was low, the atmosphere became stable, which increased the concentration of PM2.5. Chemical transport model simulations showed that PM2.5 advection from the urban area was seen through the valley on the high concentration day. In contrast, PM2.5 advection was blocked by the high mountains in the north on the low concentration day.

The Japanese mission GCOM-C launched in 2017 loads only SGLI imager. SGLI is multi-spectral sensor including near-UV and two polarization channels. This work enhanced the advantages of SGLI feature in aerosol remote sensing. It was shown that the near-UV data not only detected absorbing aerosols such as biomass burning aerosols (BBA) or mineral dust (DUST), but was also used to distinguish between BBA and DUST with short-IR data. For leading issues such as aerosols above clouds, the detection of optically thick clouds was challenged in a similar manner to aerosol classification as well as utilization of polarization measurements. As a result, some scenes concerned with DUST or BBA above water clouds were practically detected.

The second generation global imager (SGLI) is onboard the Japanese Global Change Observation Mission-Climate (GCOM-C) (SHIKISAI in Japanese) satellite launched on December 23rd in 2017. The SGLI has multiple channels (19) including near-UV and polarization channels in the red and near-IR wavelengths. It is shown in this work that the advantages of SGLI near-UV measurements are effective for aerosol classification.

It is known that the biomass burning aerosols (BBA) generated by the large-scale forest fires and burn agriculture have influenced the severity of air pollution. Nevertheless the biomass burning plumes increase due to global warming and climate change and vice versa. It is worth noting that the near ultra violet (NUV) measurements are helpful for the detection of carbonaceous particles, which are the main component of aerosols from biomass burning. In this work, improved retrieval algorithms for BBA are interpreted by using the measurements observed by GLI and POLDER-2 on Japanese short term mission ADEOS-2 from December 2002 to October 2003. The GLI sensor has 380nm channel. Finally the obtained optical properties of BBA are investigated from the standpoint of spatial and temporal variations in comparison with the numerical model simulations.

In general, aerosols influence the climate directly by scattering and absorbing the solar radiation and indirectly by acting as cloud condensation nuclei and ice nuclei, which modify the radiative properties of clouds. To estimate the effects of anthropogenic aerosols on the climate in future, we used earth system model simulations. The emission of anthropogenic aerosols can be decreased by controlling air pollution. If the emission of anthropogenic aerosol drops to zero abruptly, the surface temperature will rise in a short span of time. However, the surface temperature will decrease if the emission of anthropogenic aerosols is doubled suddenly. These results indicate that aerosols have immediate effects on climate change.

The concentration of air pollutants has become severe, and influence of biomass burning aerosols (BBA) generated by agricultural biomass burning (ABB) has been noted upon the severe haze episodes. This work intends to show the retrieval algorithm as far as heavy air pollution caused by ABB is concerned. Aerosol retrieval in the hazy atmosphere is achieved based on radiation simulation method of successive order of scattering (MSOS) for the moderate resolution imaging spectroradiometer (MODIS) on AQUA data. Multi-angle observations with the polarization and directionality of the Earth's reflectances (POLDER) on the polarization & anisotropy of reflectances for atmospheric sciences coupled with observations from a lidar (PARASOL) are available for aerosol retrieval from a mixture of cloud and haze.

Aerosol impacts on Earth's system are not negligible. The change of concentration of aerosols causes various effects on the climate by directly and indirectly modifying the optical properties and lifetimes of cloud. In addition to radiation budget change, aerosol has a significant potential to change cloud and precipitation. East Asia is the area with high concentration of aerosols in the world. This work intends to investigate distribution of aerosols over East Asia and estimate impacts of aerosol on regional climate change using by satellite data and GCM simulations. Aerosol impacts on climate over East Asia is larger than global mean. The simulated results show that surface cooling and weaken monsoon circulation by aerosol effects.

Concentration of particulate matter (PM2.5) is a good indicator of air pollution by anthropogenic aerosols in particular near surface. However instrumentation of PM2.5is still on going in East Asia even in Japan. This work intends to develop an algorithm for estimating PM2.5distribution based on the satellite measurements. Combined use of satellite derived columnar aerosol optical thickness (AOT) and vertical distribution of aerosol extinction by ground-based LIDAR measurements is available for estimation of near surface AOT. Thus the derived correlation between AOT and PM2.5is utilized to retrieve satellite based PM2.5.

Air pollution in East Asia has become severe in recent years, with heavy air pollutants and Asian dust being transported from China to neighboring countries throughout the year. In this study, we focus on heavy haze event occurring around Beijing in June, when a serious aerosol episode was detected by both satellite and ground measurements. Retrieval of atmospheric aerosol characteristics from satellite is achieved by radiative transfer simulation in the Earth atmosphere model. The aerosol model is compiled from the worldwide aerosol monitoring network (NASA/AERONET). It is shown here that the radiative transfer problem in the case of aerosol episode is solved by a method of successive order of scattering. In addition we conclude that air pollution around Beijing in June is mainly due to increasing emissions of the anthropogenic aerosols, furthermore carbonaceous aerosols from agriculture biomass burning in Southeast Asia also contribute to the pollution.

The aerosol properties are estimated by comparing satellite measurements with the numerical values of radiation simulations in the Earth-atmosphere-surface model. This work is aimed at developing the practical and efficient algorithms for retrieving aerosol characteristics. The standard radiative transfer problem in a case of finite optical thickness is treated first, and then the problem in aerosol events such as dust storms or biomass burning plumes that are associated with excessive loading of aerosols in the atmosphere is considered. Finally our algorithms are practically applied for space-based measurements by MODIS.

Higashi-Osaka is urban area located on the east of Osaka city in Japan. In this work, we intend to demonstrate the spatial and temporal variation of atmospheric particles around this area. We equip various ground measurement devices and obtain data of AERONET, PM2.5and LIDAR measurements in Higashi-Osaka campus of Kinki University. In addition to the simultaneous measurements, we make observation of the air quality at several locations in the neighborhood using portable sun-photometer. In order to investigate change of aerosol properties before and after dust event, we analyze atmospheric particles with scanning electron microscope coupled with energy dispersive X-ray analyzer.

The aerosol distribution in Asia is complicated due to the increasing emissions of sulfuric, nitric, carbonaceous and other aerosols in association with economic growth. Anthropogenic small aerosols dominate the air over urban areas because of local emissions by diesel vehicles and industries, and in addition, behavior of natural dusts significantly varies with the seasons. Thus, studying various properties of aerosols in Asian urban areas is an important subject. In this work, we classify aerosol properties with a clustering method, by utilizing the ground observations provided by multi-spectral photometers which are installed in Kinki University Campus, Higashi-Osaka, Japan. Cluster information can be used to improve estimation of relations between spectral and particle observations.

Carbonaceous aerosol plays an important role not only in climate but also in aerosol study. It is, however, difficult to make models of biomass burning aerosols because their properties are changable due to strongly dependce on the biomaterial itself, and on the stage of burning, and/or transportation process. This work intends to estimate the optical properties of biomass burning aerosols based on the combined use of the satellite data by CAI (Cloud Aerosol Imager) on GOSAT and by POLDER (POLarization and Directionality of Earth's Reflectances) on PARASOL. As a result, aerosol optical thickness (AOT), Angstrom exponent, and single scattering albedo (SSA) are retrieved. The retrieved values of AOT and Angstrom exponent are partially validated with the ground-based measurements of AERONET.

It is shown that column number density of aerosols has a negative correlation with the effective radius of cloud particles and proportionally correlates with the optical thickness and the column number density of cloud particles. These results confirm the indirect effect of aerosols, namely aerosols play sufficient role as cloud condensation nuclei (CCN).

Retrieval of aerosol parameters over turbid coastal waters depends on how accurate the contribution of waters (water-leaving radiance) is estimated. In order to retrieve parameters of the atmospheric aerosols, water-leaving radiance with various concentrations of water substances should be considered at the wavelength. In this study, water-leaving radiance of turbid water with moderate to high amount of suspended sediments is considered based on the component model of the water substances.

The ADEOS/POLDER sensor provides the first opportunity to measure the atmospheric water vapor content on a global scale. A POLDER sensor, mounted on the Earth observation satellite ADEOS in 1996, is a unique sensor which can gather multi-(up to 14) directional polarization measurements of one target. Two channels of POLDER in the near infrared wavelengths are examined in this study. The first channel is in the water vapor absorption band of 0.910 /spl mu/m and the second is in the gas absorption-free band of 0.865 /spl mu/m. In practice, a ratio of each reflectance for these two channels is used to estimate the total column water vapor content. This algorithm is referred to as the two-channel ratio method. It is shown that the global distribution of water vapor content from the POLDER data present the typical characteristics of spatial and temporal changes. The water vapor content has high values over the tropical zone and decreases with latitude. Furthermore, the Indian monsoon is clearly demonstrated in the water vapor map. It should be noted that the water vapor content retrieved from the POLDER data has been validated with AERONET measurements.

Aerosol retrieval over coastal regions suffers from the noisy contribution of various substances from the land. A new aerosol retrieval algorithm is proposed for the regions where the soil particles are spreading. The proposed algorithm is applicable for ocean color sensor data, e.g. ADEOS/OCTS, SeaStar/SeaWiFS, etc., observed over the Gulf of Cambay region (located on the western coast of India) in order to retrieve aerosol optical thickness. As a result, a natural pattern of aerosol optical thickness is obtained with our algorithm.

This work shows the global map of atmospheric aerosols retrieved from ADEOS/POLDER's radiance and polarization data over the entire functioning period of the satellite ADEOS from November, 1996 to June, 1997. In practice, the radiance and the polarization degree are used in the case of aerosol estimation over the ocean, and polarized radiance is applied to aerosols over the land. The retrieved results of the optical thickness, Angstrom exponent and refractive indices of aerosols are compared with AGCM/SPRINTARS simulations.

This communication describes a procedure to estimate the vertical profiles of stratospheric aerosols based on the visible data to be obtained by ADEOS/ILAS. The authors' algorithms mainly consist of two parts: the first process is baseline estimation for the observed transmittance spectrum, followed by the inversion process that derives vertical profiles of atmospheric extinction from ILAS transmittance data. Model calculations with an ILAS simulator show that the authors' treatment provides quick and accurate results within the expected domain of validity.>

A procedure for an accurate atmospheric correction for ocean color remote sensing is described. It is shown that an appropriate aerosol model is the key factor for pursuing the atmospheric correction, including multiple scattering light in the atmosphere-ocean system. An algorithm for estimating the aerosol models suitable for the Nimbus-7 CZCS image of interest is proposed. As a result, phytoplankton pigment concentration near the sea surface is derived through the atmospheric correction and biooptical algorithms. The treatment is found to provide an improved pigment map of the sea surface near Japan.>