Tang-Huang Lin

Applying SPOT data to estimate the aerosol optical depth and air quality

Abstract The improvement in the structure function method for retrieving aerosol optical depth (AOD) with SPOT HRV data and its application in air quality monitoring are highlighted in this paper. Generally speaking, estimation of the aerosol optical depth will be affected by the temporal change of surface canopy, observation geometry and terrain effect when applying the contrast reduction method to the multi-temporal satellite image set. In order to reduce the errors induced by such effects, the single-directional structure function is replaced by the multi-directional mode, which can describe the real characteristics of the surface structure more completely. Comparison of the results with in-site observations show a significant improvement in the accuracy of the retrieved AOD. Furthermore, due to the linear relationship between aerosol optical depth and turbidity coefficient, satellite images can be employed for monitoring air quality. Application of the method is demonstrated with a case study situated around the northern Taiwan area.

Asian dust weather categorization with satellite and surface observations

This study categorizes various dust weather types by means of satellite remote sensing over central Asia. Airborne dust particles can be identified by satellite remote sensing because of the different optical properties exhibited by coarse and fine particles (i.e. varying particle sizes). If a correlation can be established between the retrieved aerosol optical properties and surface visibility, the intensity of dust weather can be more effectively and consistently discerned using satellite rather than surface observations. In this article, datasets consisting of collocated products from Moderate Resolution Imaging Spectroradiometer Aqua and surface measurements are analysed. The results indicate an exponential relationship between the surface visibility and the satellite-retrieved aerosol optical depth, which is subsequently used to categorize the dust weather. The satellite-derived spatial frequency distributions in the dust weather types are consistent with Chinas weather station reports during 2003, indicating that dust weather classification using satellite data is highly feasible. Although the period during the springtime from 2004 to 2007 may be not sufficient for statistical significance, our results reveal an increasing tendency in both intensity and frequency of dust weather over central Asia during this time period.

Effect of black carbon on dust property retrievals from satellite observations

Abstract The effect of black carbon on the optical properties of polluted mineral dust is studied from a satellite remote-sensing perspective. By including the auxiliary data of surface reflectivity and aerosol mixing weight, the optical properties of mineral dust, or more specifically, the aerosol optical depth (AOD) and single-scattering albedo (SSA), can be retrieved with improved accuracy. Precomputed look-up tables based on the principle of the Deep Blue algorithm are utilized in the retrieval. The mean differences between the retrieved results and the corresponding ground-based measurements are smaller than 1% for both AOD and SSA in the case of pure dust. However, the retrievals can be underestimated by as much as 11.9% for AOD and overestimated by up to 4.1% for SSA in the case of polluted dust with an estimated 10% (in terms of the number-density mixing ratio) of soot aggregates if the black carbon effect on dust aerosols is neglected.

Using Surface Stations to Improve Sounding Retrievals from Hyperspectral Infrared Instruments

Having an accurate atmospheric thermodynamic state is critical for environmental research, particularly the vertical temperature and moisture profiles within the atmospheric boundary layer. This paper investigates the synergistic use of spaceborne hyperspectral infrared radiance measurement and traditional surface observation to conduct the best estimation of atmospheric temperature and water vapor profiles. Comparing the retrieval results from the original spaceborne observation stand-alone algorithm, atmospheric boundary layer temperature and moisture retrievals appear to be improved through the inclusion of the surface observation in the new developed algorithm. The statistics of retrieval performance by comparing with radiosonde observation suggest that the improvement is not only at the lowest surface level but also within the planetary boundary layer. This implies the benefit of surface observation in the atmospheric sounding retrieval algorithm, and the boundary layer thermodynamic structure could be retrieved optimally from the use of both spaceborne and ground-based observations.

Retrieval of Atmospheric Thermodynamic State From Synergistic Use of Radio Occultation and Hyperspectral Infrared Radiances Observations

Atmospheric temperature soundings derived from satellite-based advanced infrared (IR) sounder radiance measurements tend to have higher uncertainty in the upper troposphere. In contrast, radio occultation (RO) measurements have high accuracy and high vertical-resolution for atmospheric sounding in the upper troposphere and lower stratosphere (UTLS). It is anticipated that the best estimation of atmospheric thermodynamic state can be obtained by the synergistic use of RO and IR radiance measurements. A physical-based algorithm accounting for the significant geometric difference between the two observing systems has been developed to combine RO refractivity and Atmospheric InfraRed Sounder (AIRS) radiances for atmospheric temperature and humidity vertical profiles. Comparisons between RO/AIRS and AIRS-alone derived profiles showed that the impact of RO observations to be most apparent in the upper troposphere between 100 and 300 hPa, where the root-mean-square difference (RMSD) of estimated temperature is reduced by 24% (0.36 K) to 35% (0.66 K). In addition to having improved temperature profile retrievals in the upper troposphere, the humidity retrievals are also improved; the RMSD below 100 hPa was reduced by 22.4% (0.298 g/kg) when compared with radiosondes observations. Results indicated that the humidity profiles retrieved using this method were overall better than the IR-only retrievals in all of the comparisons, and the temperature profiles improved upon the IR-only retrievals, most notably in the upper troposphere. These improvements are more significant using a three-dimensional (3-D) slant-path collocation procedure.

A satellite-derived typhoon intensity index using a deviation angle technique

An objective index was proposed to determine the intensity of typhoons in this study. This was achieved using an image edge processing technique to examine meaningful discontinuity characteristics and thereby calculate the gradient of brightness temperature in satellite infrared images. By taking the typhoon centre as a reference point, the angle between the position vector and the gradient vector was defined as the deviation angle. Following this definition, the probability density and standard deviation of the deviation angle may be derived. After creating a scale from 1 to 0 (0–1) to, respectively, represent the maximum and minimum values of the probability density (standard deviation), this research proposed a non-dimensional typhoon intensity (TI) index. Analysis results reveal a high accuracy when the TI index was used to objectively measure TI. The bias, average error, root mean square error, and R2 value reached 0.6, 3.5, 4.8 m s–1, and 0.89, respectively. Meanwhile, various evaluation parameters in assessing the forecasting skill were also employed, where a specific ‘yes’ and ‘no’ threshold for each typhoon stage was established. The ratio of the number of correct determination to the number of events for a specific typhoon stage was 0.74 (mild), 0.76 (moderate), and 0.89 (severe), respectively, for 557 infrared images of five validation typhoon cases in 2011. The results demonstrated that the TI index technique had good performance in assessing the TI even during typhoon stage changes.

The atmospheric correction algorithm of ROCSAT-1/OCI data

Abstract In this study, the Normalized Difference Vegetation Index (NDVI) and the band ratio of the total radiance at channels 670nm and 865nm were used to determine the sea surface albedo. The air mass character parameter and aerosol optical depth were then assessed by a simulated process. The pixel-by-pixel aerosol scattering radiance and water-leaving radiance are the main goals to retrieve in this study. As the Ocean Color Imager (OCI) is similar to the Sea-viewing Wide Field-of-view Sensor (Sea WiFS), a set of images were acquired both by Sea WiFS and OCI at the same temporal and spatial parameters. Their respective models-SeaWiFS Data Analysis System (SeaDAS) and Ocean Color Imager TRANsmittance / radiance computation code (OCITRAN) were employed to retrieve the water-leaving radiance so we could compare and evaluate the accuracy of OCITRAN. The results showed a high correlation (R>0.76) between the two models, proving that the OCITRAN algorithm established by this study is adaptable.

Satellite-derived normalized difference convection index for typhoon observations

Abstract. This study used the spectral features of the geostationary satellite infrared window channel and the water vapor channel data to calculate a new parameter, normalized difference convection index (NDCI), to help determine the overshooting areas in typhoon cloud systems and the centers and intensity of typhoons. The results showed that the two-dimensional NDCI analysis helped to identify typhoon convective cloud systems and the positions of overshooting areas. In addition, because the NDCI values near a typhoon eye were rather significant, if a typhoon eye was formed, the NDCI cross-section analysis could help to confirm its position. When the center of a typhoon was covered by the high anvils and cirrus layers, it could still be qualitatively found through two-dimensional analysis. As for determining the intensity of typhoons, this study also tried to perform correlation analyses with NDCI and maximum sustained wind speed. The result showed that in the ranges within circles of 200 to 250 km radii with a typhoon eye as the center, the correlation between the area with the NDCI values <0 and the maximum sustained wind speed is high with a coefficient 0.7. Thus, the NDCI value could be a referential index to determine the intensity of a typhoon.

To analyze the effects of mixing with soot aggregates on retrieving dust properties for satellite observations in Asia

Long range transport leads mineral dusts to internally/externally mix with the ambient aerosols, such as soot particles, naturally. The physicochemical characteristics of dust particles thus are dramatically altered after mixing with soot aggregates. Therefore, the investigation on the optical properties of mineral dust along with their pathway causes a significant topic for understanding the impacts of Asian dust storm on regional air quality, environment and climate. Unfortunately, the previous researches regarding to the optical properties of dust/soot mixture for satellite remote sensing are scarce. Consequently, the objective of this study is to simulate the effects of mixing with soot aggregates on the optical properties of dust particles for satellite observations based on the well developed models. A tri-axial ellipsoidal model for dust particles by introducing the third morphological freedom to improve the symmetry of spheroids has been developed and showed in good agreement for the retrievals of dust optical properties from remote sensing measurements and ground based observations. For the model of soot aggregation, the scattering properties of fractal aggregates can be obtained with the Rayleigh-Debye-Gans (RDG), superposition T-matrix and Generalized Multiple Mie (GMM) methods. The results show that the AOD (aerosol optical depth) retrievals of dust particle will be underestimated while the SSA (single scattering albedo) will be overestimated when neglecting the combination of soot aggregates. The simulations also suggest that simultaneously retrieve AOD and SSA based on the apparent reflectance may induce large uncertainty for the dust/soot mixtures.

Improved tropical rainfall potential forecasting for mountainous regions

In many geographic regions like Taiwan, people suffer from the disastrous effects of tropical cyclones year after year. For instance, the heavy rainfall from these events often triggers mudslides and other associated problems. Furthermore, there appears to be an increasing trend for stronger tropical cyclones.1 Indeed, typhoon Morakot (in 2009) brought record-breaking rainfall floods, the likes of which had not been witnessed in Taiwan for more than 50 years. This typhoon caused the death of more than 680 people (about 500 were killed in a single mudslide). There is thus a great need to develop a method that can be used to forecast the potential of tropical rainfall in both a quick and accurate manner (especially over mountainous regions as these are associated with the highest flood and mudslide risks). Assessing a tropical cyclone’s rainfall potential, however, can be very difficult because the interaction between the cyclone and inland rugged terrains is very complex. This is unfortunately the case for Taiwan because more than two-thirds of its area is covered by mountainous terrain (up to 3000m in altitude). For potential rainfall forecasting methods, the use of satellite data is the optimal choice, and the possibility of estimating tropical cyclone intensity was first demonstrated in the 1980s.2 In addition, continued satellite channel and resolution improvements have dramatically enhanced the application potential of such satellite data. The tropical rainfall potential (TRaP) technique3, 4 is one of the most practical methods for tropical cyclone potential rainfall operations that has so far been proposed. With this technique it is assumed that the tropical cyclone rainfall potential can be calculated by summing together all the rainfall rates derived from microwave satellite data (shifted with respect to Figure 1. Comparison of (a) the observed rainfall rate (Obs. RR) over Taiwan’s Central Mountain Range during the 2009 Morakot typhoon and the rainfall potential obtained from the (b) improved tropical rainfall potential (I-TRaP) model and (c) original TRaP methodology. These results (in mm) are for the period between 00:00UTC (coordinated universal time) on 7 August 2009 and 00:00UTC on 9 August 2009. Black triangles denote the peak rainfall locations. (d) The relationship between the gauge-measured rainfall and the I-TRaP results. r: Correlation coefficient. MB: Mean bias. RMSE: Root mean square error.