Chian-Yi Liu

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.

Image-based derivation of aerosol optical depth to correct the atmospheric effect for satellite image

An image-based atmospheric correction model for a satellite image is proposed. By assuming Junge size distributed aerosol in the atmosphere and feeding back the new Junge parameter, not only the aerosol optical depth but also the Junge parameter, single scattering albedo and phase function can be iteratively derived and converged from digital counts of dense-dark vegetation (DDV) in the green and red bands of the SPOT satellite image. Multiple scattering of path radiance for aerosol is taken into consideration. The accuracy of derived reflectance is assessed with field measurements.

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.

Variability of the bare soil albedo due to different solar zenith angles and atmospheric haziness

Abstract Owing to the non-Lambertian reflection properties of natural surfaces, the bidirectional reflectance factor (BRF) and hence the albedo depend on solar zenith angle (SZ) as well as the haziness of the atmosphere. By using the results of Pinty, Verstraetc and Dickinson to describe the BRFs of bare soil in NOAA-7, -8 satellite AVHRR band 1 and 2, and the results of LOWTRAN-7 as the description of hemispherical irradiation, the variation of bare soil albedo and errors inferred from all viewing directions of BRF under changing SZs and aerosol optical depths is discussed. This paper also shows that the optimal view angle of bare soil used to infer the albedo from a single observation under SZ from 25° to 45°, and atmospheric conditions from clear sky to hazy sky, for both AVHRR bands is about 50° off-nadir and about 80° relative azimuthal angle. Their errors are no more than 1 per cent. The sensitivity of optimal view angle with aerosol optical depth is also discussed. This leads to the evaluation of t...

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.

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.

Applying satellite remote sensing technique in disastrous rainfall systems around Taiwan

Many people in Asia regions have been suffering from disastrous rainfalls year by year. The rainfall from typhoons or tropical cyclones (TCs) is one of their key water supply sources, but from another perspective such TCs may also bring forth unexpected heavy rainfall, thereby causing flash floods, mudslides or other disasters. So far we cannot stop or change a TC route or intensity via present techniques. Instead, however we could significantly mitigate the possible heavy casualties and economic losses if we can earlier know a TC’s formation and can estimate its rainfall amount and distribution more accurate before its landfalling. In light of these problems, this short article presents methods to detect a TC’s formation as earlier and to delineate its rainfall potential pattern more accurate in advance. For this first part, the satellite-retrieved air-sea parameters are obtained and used to estimate the thermal and dynamic energy fields and variation over open oceans to delineate the high-possibility typhoon occurring ocean areas and cloud clusters. For the second part, an improved tropical rainfall potential (TRaP) model is proposed with better assumptions then the original TRaP for TC rainfall band rotations, rainfall amount estimation, and topographic effect correction, to obtain more accurate TC rainfall distributions, especially for hilly and mountainous areas, such as Taiwan.

Mixing weight determination for retrieving optical properties of polluted dust with MODIS and AERONET data

In this study, an approach in determining effective mixing weight of soot aggregates from dust–soot aerosols is proposed to improve the accuracy of retrieving properties of polluted dusts by means of satellite remote sensing. Based on a pre-computed database containing several variables (such as wavelength, refractive index, soot mixing weight, surface reflectivity, observation geometries and aerosol optical depth (AOD)), the fan-shaped look-up tables can be drawn out accordingly for determining the mixing weights, AOD and single scattering albedo (SSA) of polluted dusts simultaneously with auxiliary regional dust properties and surface reflectivity. To validate the performance of the approach in this study, 6 cases study of polluted dusts (dust–soot aerosols) in Lower Egypt and Israel were examined with the ground-based measurements through AErosol RObotic NETwork (AERONET). The results show that the mean absolute differences could be reduced from 32.95% to 6.56% in AOD and from 2.67% to 0.83% in SSA retrievals for MODIS aerosol products when referenced to AERONET measurements, demonstrating the soundness of the proposed approach under different levels of dust loading, mixing weight and surface reflectivity. Furthermore, the developed algorithm is capable of providing the spatial distribution of the mixing weights and removing the requirement to assume that the dust plume properties are uniform. The case study further shows the spatially variant dust–soot mixing weight would improve the retrieval accuracy in AODmixture and SSAmixture about 10.0% and 1.4% respectively.

An improved spectral knowledge for multi-temporal images classification-a case study of urban area

The authors demonstrate that the normalized reflectance is much more suitable than bidirectional reflectance factor (BRF) as the scene-independent spectral knowledge as Wharton (1987) suggested. Normalized reflectance can be obtained from normalization of BRF by its intrinsic BRDF. Transformed divergences of apparent reflectance, BRF and normalized reflectance of the urban target in the multi-temporal dataset are compared.