Methane is a major greenhouse gas besides carbon dioxide. It is important to monitor methane emission from natural and anthropogenic sources. In this study, we tested an inverse modeling algorithm for retrieving methane column density of a near-ground methane cloud. A synthetic dataset of top-of-atmosphere reflectance is generated using a radiative-transfer based forward model. In the retrieval procedure, the linearized reflectance model is solved by inverting the linear matrix equation with the pseudo-inverse technique. The logarithm of the surface reflectance is modeled by a third order polynomial within a narrow spectral window. For the test data set with column density up to 5000 ppmm, the retrieved column density correlates highly with the true values with R2=0.9834, average bias –290 ppmm and rms error 551 ppmm. The relative error is below 20% for column density above 1400 ppmm. Considering the sensor’s SNR and the detection model, the detection limit is about 1300 ppmm for a sensor with SNR 100, spectral bandwidth 10 nm and a spectral window for detection spanning from 2310 nm to 2380 nm.

Satellite and ground level observations during the period of August to October 2023 captured an elevated number of fire hot spots and biomass burning (smoke) activity over the South-East Asia landmasses of Sumatra and Borneo. Over this region, fire activity can be a yearly occurrence due to prevalent regional dryness and low rainfall, such activity can also be enhanced by other tropical phenomena like El Nino Southern Oscillation. In this paper, we present a multi—site photometric analysis of smoke emissions during this period with emphasis on aerosol physical and optical characteristics that would allow us to differentiate the source levels of emissions, aerosol composition and possibly transport pathways to downwind receptor sites.

In a previous work we presented a methodology for forecasting the future cloud distribution in the atmosphere by using the capabilities of the Advanced Himawari Imager (AHI) which provides high frequency imagery (every 10min) of the Asian hemisphere. This capability is used to detect and characterize cloud physical and optical characteristics over a fixed geographical location centered over Singapore. In this present work, we report on the forecast (1-3Hrs) of short-wave solar radiation by using a radiative transfer model, that includes aerosols and clouds, and applied to future cloud distribution scenarios resulting from the cloud motion scheme reported in our earlier work.

Advanced imagery from instruments onboard geostationary and/or polar orbit satellites provide measurements of electromagnetic radiation emitted from the earth's atmosphere at visible, near-infrared, and infrared channels. In Asia, the Advanced Himawari Imager (AHI) onboard the Himawari-8 satellite provides a unique opportunity to exploit its high frequency imagery capabilities (every 10 min) that can be used to detect and characterize cloud physical and optical characteristics as well as to enhance cloud motion/transport algorithms with possible applications to short and medium term solar radiation forecasting.

On 23rdJuly 2018 during an intense heat wave, two large fires broke out in Attika, a region in the central-southern part of Greece. Attika Regional Authorities declared a state of emergency and the European Union Civil Protection Mechanism was activated to oversee and manage the effects of this event. Subsequently, burn area delineation maps were produced as a way to evaluate the damage caused by these fires. For example, for July 26thmaps, which is near the fire episode's end, approximately 41 Km2were burned during this event. A side effect of these fires are the large emission of aerosol pollutants (smoke) and other gases generated during the burning process much of which can be very detrimental to human health. In this work and as part of an international collaborative validation effort on air quality methodologies; a WRF-Chem and source generation model was tasked to model the amount of gases and particles emitted during this event. Here in, we present a model perspective of the evolution and transport characteristics of aerosols particles and other gases (CO, NOx) generated during this intensive period of burning over Attika Greece.

A large-scale episode of biomass burning was observed during the months of August to October 2019. Satellite and in-situ observations reported scores of fires over the regions of central Sumatra and southern Kalimantan of Indonesia. Prevailing meteorological conditions contributed to long range transport of these aerosol particles and they were observed over several cities in Malaysia, Indonesia and Singapore. In this work, we report in-situ observations at two AERONET sites located in Singapore and Kuching (Sarawak, East Malaysia) complemented by satellite imagery (MODIS) over the above mentioned regions.

The recently developed Bruhn optical flow method has been found to improve imagery analysis results but has yet to be tested for cloud tracking purposes. We propose a cloud tracking model that is based on the Bruhn method and compare its performance with models based on more conventional optical flow methods. For lead-times spanning from 5s to 600s, the Bruhn based model has a comparable tracking accuracy when contrasted with current methods yet achieves a better than 30% improvement in computing processing time. We conclude that the Bruhn method represents a promising method for use in cloud tracking models.

Regional trans-boundary biomass burning activity in South-East Asia is routinely monitored via ground PM2.5 sampling devices. In Singapore for example, the National Environment Agency host an array of tens of PM2.5 samplers distributed island wide, such array provides hourly and daily averages of PM10/2.5 concentrations at near real time and at a good spatial resolution. However, in other neighboring countries, such an array of samplers are impossible to deploy due to its vast geographical landscape and prohibitive economic cost. Hence, a satellite based monitoring of PM2.5 can be of great help as it has the capability to cover the entire region. Unfortunately satellite products do not include a PM2.5 product as such but its close proxy, the so called aerosol optical depth (AOD). Unfortunately the spatial and temporal dependency of PM2.5/AOD makes it challenging to find optimal correlations for these two parameters specially over the tropics. In this work, we present an initial 2year analysis of measured PM2.5, photometric AOD (AERONET), and PBL height (MPLNET) as well as meteorological % RH collected at Singapore. Our analysis is based on the assumption that a linear relationship between measured PM2.5 and photometric AOD can be found. To increase co-relation accuracy, appropriate corrections are made for atmospheric %RH and variability of the PBL height.

Hygroscopic growth of sub-micrometer aerosol particles were measured in Singapore during a first phase of a local experimental campaign. Such a measurement campaign was conducted in order to understand the impact that humidity has on the local aerosol sources. Total scattering and backseattering experiments were carried out by using two-collocated 3-wavelength integrating nephelometers. Results show a consistent particle growth via the retrieved scattering Angstrom number. A local particle growth factor was constructed from these scattering measurements.

In the present study, the surface meteorological parameters over Singapore are simulated using WRF-ARW mesoscale model by varying the planetary boundary layer (PBL) parameterization schemes, horizontal resolutions and two land cover data sets (USGS and MODIS). Simulations are conducted with four nested domains having horizontal resolution of 27, 9, 3 and 1 km; 51 vertical levels by using the 1° × 1° NCEP final analysis meteorological fields for initial and boundary conditions. Eight days (20-28 January 2015) are selected for simulating various surface meteorological parameters. The model-simulated parameters of surface temperature, relative humidity, wind speed and wind direction are validated with the available observations over Singapore. It has been found that, improvements in predicting surface meteorological parameters with the increase in model resolution up to 3 km. The experiment with the 3 km grid resolution showed better simulated surface meteorological variables than that of 1 km resolution grid. Further, MODIS land cover data considerably improved the prediction of surface meteorological variables compare to the USGS. The surface meteorological variables simulated using the ACM2 PBL scheme with MODIS data are in better agreement with the observations showing least error statistics than the other PBL schemes used in the study. The better performance by ACM2 could be due to the non-local turbulence closure during unstable conditions and local-closure during stable conditions formulated in this scheme.

Over the last two decades and due to rapid economic growth, the South-East Asia region experiences mild to severe smoke episodes generated from annual biomass burning events, usually occurring during the regions's dry season that can last several months (June to October). Such a events poses a hazard to the region itself and specially to Singapore due to close proximity to the land masses of Sumatra and Borneo. In-situ aerosol measurements are now performed by our AERONET link photometer (Singapore and Kuching) sites. Such measurements readily provide optical characterization of atmospheric aerosols when biomass burning events occur. In this work, we present an analysis of three months of AERONET level 1.5 data recorded during August-October 2015 period. Besides the classical aerosol optical depth and Angstrom exponent number classifications, a special emphasis is paid to separate the fine/coarse mode part of the particle size distribution and by applying strict constrains to avoid cloud contamination and other artifacts.

Over the last two decades and due to rapid economic growth, South-East Asia experiences mild to severe smoke episodes generated from annual biomass burning, usually occurring during the dry season period (from June to October). In Singapore, in-situ aerosol measurements are now performed by our AERONET sun photometer site since 2006. Such measurements readily provide optical characterization of atmospheric aerosols, such as optical depth and Angstrom number, as well as other physical properties such as refractive index, single scattering albedo, particle size distribution and scattering phase function when available. However, realistic aerosol phase functions can be quite complex and sometimes prohibitive to use in full radiative transfer calculations. This is due to the fact that many radiative transfer codes use Legendre polynomials and/or generalized spherical functions to represent the aerosol phase function. In such a cases, the number of expansion terms, for realistic aerosol particles, could be very large. In this work, a double Henyey-Greenstein function approximation is adopted to generate aerosol phase functions from level 1.5 AERONET measurements during smoke/smoke-free periods.

We report our first photometric measurements of aerosol optical depth from AERONET's mini-DRAGON sites at Singapore performed over the months of August and September 2012. Multi-spectral measurements of aerosol optical depth provide essential spectral information to obtain and/or retrieve the so-called Angstrom exponent number which is an essential parameter for inferring aerosol particle size regime. Based on the range of variability of Angstrom exponent number and aerosol optical depth, various aerosol types present in the local environment, can be identified. Special emphasis is placed on detecting the possible presence of external sources of aerosols such as from trans-boundary smoke originating from regional biomass burning episodes which is prevalent during this time of the year.

Over the past two decades, the Asia and South-Asia region has experienced a dramatic economic, industrial and population grow. Big cities are becoming large emission sources of anthropogenic aerosols resulting from the incessant industrial activity. In rural areas, clearance of large forested areas, via the method of burning, has resulted in severe smoke emission episodes during the 1996-2006 decade and has become an annual phenomenon specially in the South-East-Asia region. Large emission episodes can occur during periods of severe draught and exacerbated by the inter- annual El Ninõ events. Depending on weather patterns, smoke events can evolve into a persistent trans-boundary smoke with aerosol concentrations high enough to significantly reduce visibility and become a health hazard for local populations. During the month of October 2010, elevated levels of fire activity was detected by remote sensing satellites as well as by local in-situ measurements of fine particulate matter. In this work, we investigate the radiative impact of this smoke episode by firstly, analyzing the physical and optical properties of smoke particles with the aid of passive (Sun-photometer, AERONET), active and in-situ sampling of fine particulate (PM2.5) at our Singapore receptor site. Secondly, inversions of particle size distribution as well as single scattering albedo were used to evaluate the radiative impact of this biomass burning episode.

Since October 2006, the Center for Remote Imaging, Sensing and Processing (CRISP) of the National University of Singapore has joined the Aerosol Robotic Network, AERONET, to monitoring aerosol optical properties in this region. This initiative complements the already existing activities on satellite remote sensing performed at CRISP. In Singapore, the sources of aerosols are mostly from fossil fuel burning (energy stations, incinerators, cars etc.) and from the industrial and urban areas. The proximity to the sea adds a possible oceanic source and depending on the time of the year, there can be a strong bio-mass component coming from forest fires from various regions of the neighboring countries. In this work, we present a survey of aerosol optical depth (AOD) and Angstrom exponent retrievals at several regions of Singapore. AOD measurements were performed with the help of AERONET's CIMEL Sun-photometer (located at CRISP) and a versatile hand held Microtops II Sun-photometer. In order to identify the degree of geographical variability of aerosol optical properties, we collected data samples over selected sites across the island. Furthermore, we extracted concurrent data points from our own AERONET site in order to check for consistency and validation of our results. This study has enabled us to identify possible aerosol sources and understand the nature and physical characteristics of atmospheric aerosols across Singapore.

Satellite remote measurements taken over the ocean surface, often contain information of near-surface or sub-surface processes, which occur on, or over the ocean. These remote measurements, can enable as to retrieve important parameters such as near surface wind, sea surface temperature and salinity and underwater bathymetry, which, all, in one way or another, depend on how well we understand sea surface reflection and roughness. However, the quality of these retrievals are often limited by the amount of scattering, emission and absorption of electromagnetic radiation caused by atmospheric aerosols which often shows dependency on polarization. From a remote sensing perspective, it is very well known that at off-nadir incidence angles and wavelenghts longer than 3.6 mum, the radiance originated from the sea surface becomes partially vertically polarized. Similarly, at shorter wavelenghts (shorter than 3.6 mum), the total radiance at off-nadir angles can become strongly horizontally polarized , . Since at shorter wavelengths, the reflected skylight becomes more significant; it is important to quantify the contribution that atmospheric polarization has on the top of the atmosphere remotely observed sea surface reflection, specially near areas of enhanced surface reflection such as from the Sun glitter. Furthermore, surface phenomena, such as wind-generated waves, gravity and capillary waves, internal waves, surface currents, density fluctuations etc., modulate the ocean's surface roughness which has a direct effect on sea surface reflection. This modulating effect is represented by the so called the mean square slope (MSS) of ocean surface waves. In general, the MSS is mainly related to short wind waves which are strongly dependent on wind speed, wind direction, surface waves and air sea temperature. To understand these wind and wave related effects on the Sun glint pattern, Salinas [3] have developed an atmospheric radiative transfer model that incorporates a new wind-wave description for the mean square slope of the sea surface. This model solves the scalar radiative transfer equation and includes wind interaction and wave states, such as wave age, as the main factors contributing to surface roughness. In this paper, we extend the above mentioned work and include light polarization effects originating from aerosol and molecular scattering and from the roughness of the surface. Polarization is considered by using the 4-Stokes vector formalism and the 4x4 scattering phase matrix for aerosols and molecules. Simulation results showing polarization effects on the simulated, top of the atmosphere, Sun glint pattern are presented. Initial simulations performed at low wind speed show increasing levels of linear polarization with increasing values for the wave age parameter. However, at higher wind speed, lower levels of linear polarization is obtained for similar values of the wave age parameter. On the other hand, calculations performed at near surface levels, show low linear polarization and a gradual shift of the Brewster angle with increasing wind speed and wave age. These results, although initial, will be carefully analyzed and compared with limiting cases where available. Finally, the present model can have possible applications to the retrieval of wind and wave states, such as wave age, near a Sun glint region and for the study of of ocean surface roughness characteristics arising from air-sea interaction.

In this paper, we present a method for atmospheric correction that uses the cloud and shadow image features. An iterative scheme is formulated to computes the ratio of diffuse to direct irradiance as well as the path radiance using the radiance detected over the open water and shadow pixels. These parameters are then used to compute the cloud and water reflectance. We implemented this method on IKONOS images which are known to have inferior signal to noise ratio compared to sensors specially designed for ocean color measurements. The corrected image reflectance over water pixels are compared to field measurements.

Since the pioneering work of Cox & Munk , who first investigated the probability distribution of liquid surface facets using the analysis of aerial photographs of the Sun glitter, it has been widely recognized that the dominant parameter that determines the sea surface roughness is the mean square slope (MSS) of the sea surface which is mainly related to short wind waves and other surface effects in a lesser degree. Liquid surface reflection has been studied experimentally over the years and several empirical algorithms have been formulated relating wind speed directly to the MSS. Using these empirical formulations, the reflectivity of the liquid surface can be computed using a normal probability distribution of water surface facets and applying Fresnel relations to each surface facet. However, these approaches do not include the influence of wave states or the physical properties of the sea surface on the computation of the MSS. In a recent work, Salinas, et al (2007) has developed a radiative transfer model that incorporates a new windwave description for the MSS of the sea surface in Zhao, D. and Toba, Y. (2003) . This model includes wind interaction and windwave states, such as wave age, as the main factors contributing to surface roughness. In this work, we apply the above mentioned radiative transfer model to the analysis of remote sensing data obtained from TERRA-MODIS satellite imagery taken near Sun glint regions. As as ancillary step, wind speed data, corresponding to TERRA-MODIS date of measurements and obtained from the SeaWinds instrument on the QuikScat satellite, are used to constrain the range of wind speed in our calculations.

10.1109/IGARSS.2005.1526635