Multi-functional Transport Satellite Research Articles

SST diurnal warming in the China seas and northwestern Pacific Ocean using MTSAT satellite observations

Hourly sea surface temperature (SST) observations from the geostationary satellite are increasingly used in studies of the diurnal warming of the surface oceans. The aim of this study is to derive the spatial and temporal distribution of diurnal warming in the China seas and northwestern Pacific Ocean from Multi-functional Transport Satellite (MTSAT) SST. The MTSAT SST is validated against drifting buoy measurements firstly. It shows mean biases is about–0.2°C and standard deviation is about 0.6°C comparable to other satellite SST accuracy. The results show that the tropics, mid-latitudes controlled by subtropical high and marginal seas are frequently affected by large diurnal warming. The Kuroshio and its extension regions are smaller compared with the surrounding regions. A clear seasonal signal, peaking at spring and summer can be seen from the long time series of diurnal warming in the domain in average. It may due to large insolation and low wind speed in spring and summer, while the winter being the opposite. Surface wind speed modulates the amplitude of the diurnal cycle by influencing the surface heat flux and by determining the momentum flux. For the shallow marginal seas, such as the East China Sea, turbidity would be another important factor promoting diurnal warming. It suggests the need for the diurnal variation to be considered in SST measurement, air-sea flux estimation and multiple sensors SST blending.

First retrieval of fire radiative power from COMS data using the mid-infrared radiance method

ABSTRACTFire radiative power (FRP), which is the power radiated by fire within a unit area, is a fundamental component for estimation of fire emissions. Successive information of FRP is provided by instruments on geostationary satellites, such as the Spinning Enhanced Visible and Infrared Imager (SEVIRI) on board Meteosat, and the Imager on board Geostationary Operational Environmental Satellite (GOES) for Europe, Africa and America. In East Asia, however, the geostationary satellites such as Multifunctional Transport Satellite, Himawari, Fengyun, and Communication, Ocean and Meteorological Satellite (COMS) do not provide official FRP products yet. This article describes the first retrieval of COMS FRP using the mid-infrared radiance method with an optimal sensor coefficient derived from our experimental simulations. The COMS FRP retrievals were compared with Moderate Resolution Imaging Spectroradiometer (MODIS) FRP products in East Asia for each April during 2011–2014. The mean absolute percentage difference was approximately 17%, which is comparable with the results of SEVIRI (30%) and GOES (17%) against MODIS FRP even if their experiment conditions were slightly different. The retrieval accuracies of the COMS FRP had almost no dependence on land-cover types and the size of fire, which can be interpreted a stable outcome covering most wildfire situations, although parts of the pixels showed somewhat low accuracies according to viewing and solar zenith angles. The results of our study can be useful to understand spatiotemporal variations of wildfire emissions. Furthermore, it can be a reference for FRP retrievals of the next-generation geostationary satellites such as the latest Himawari-8 and the forthcoming Geostationary Korean Multipurpose Satellite 2A.

Estimation of Hong Kong’s solar energy potential using GIS and remote sensing technologies

This paper studies the use of Remote Sensing (RS) technologies and Geographic Information Systems (GIS) for estimation of city-wide photovoltaic (PV) potential in Hong Kong. It investigates the spatial distribution of cloud coverage through geostationary satellites from the Multi-functional Transport Satellite (MTSAT). The results indicate that a non-prominent spatial variation of cloud cover presides over a majority of Hong Kong territories. Appropriate locations for deploying solar PV panels, such as rooftops, were delineated using RS, GIS, and existing ancillary data. Extraction and filtering of pixels based on a set of criterions were used to identify optimal PV rooftops. This study shows that the summarization of PV potentials in Hong Kong is 2.66 TWh on building rooftops. The methodologies and findings from this study permits detailed spatial estimation of city-wide solar energy potential, and assists the policy-decision process on the use of renewable energy in Hong Kong.

Monitoring and tracking the trans-Pacific transport of aerosols using multi-satellite aerosol optical depth composites

Abstract. The primary goal of this study was to generate a near-real time (NRT) aerosol optical depth (AOD) product capable of providing a comprehensive understanding of the aerosol spatial distribution over the Pacific Ocean, in order to better monitor and track the trans-Pacific transport of aerosols. Therefore, we developed a NRT product that takes advantage of observations from both low-earth orbiting and geostationary satellites. In particular, we utilize AOD products from the Moderate Resolution Imaging Spectroradiometer (MODIS) and Suomi National Polar-orbiting Partnership (NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) satellites. Then, we combine these AOD products with our own retrieval algorithms developed for the NOAA Geostationary Operational Environmental Satellite (GOES-15) and Japan Meteorological Agency (JMA) Multi-functional Transport Satellite (MTSAT-2) to generate a NRT daily AOD composite product. We present examples of the daily AOD composite product for a case study of trans-Pacific transport of Asian pollution and dust aerosols in mid-March 2014. Overall, the new product successfully tracks this aerosol plume during its trans-Pacific transport to the west coast of North America as the frequent geostationary observations lead to a greater coverage of cloud-free AOD retrievals equatorward of about 35° N, while the polar-orbiting satellites provide a greater coverage of AOD poleward of 35° N. However, we note several areas across the domain of interest from Asia to North America where the GOES-15 and MTSAT-2 retrieval algorithms can introduce significant uncertainties into the new product.

Retrieving high-resolution surface solar radiation with cloud parameters derived by combining MODIS and MTSAT data

Abstract. Cloud parameters (cloud mask, effective particle radius, and liquid/ice water path) are the important inputs in estimating surface solar radiation (SSR). These parameters can be derived from MODIS with high accuracy, but their temporal resolution is too low to obtain high-temporal-resolution SSR retrievals. In order to obtain hourly cloud parameters, an artificial neural network (ANN) is applied in this study to directly construct a functional relationship between MODIS cloud products and Multifunctional Transport Satellite (MTSAT) geostationary satellite signals. In addition, an efficient parameterization model for SSR retrieval is introduced and, when driven with MODIS atmospheric and land products, its root mean square error (RMSE) is about 100 W m−2 for 44 Baseline Surface Radiation Network (BSRN) stations. Once the estimated cloud parameters and other information (such as aerosol, precipitable water, ozone) are input to the model, we can derive SSR at high spatiotemporal resolution. The retrieved SSR is first evaluated against hourly radiation data at three experimental stations in the Haihe River basin of China. The mean bias error (MBE) and RMSE in hourly SSR estimate are 12.0 W m−2 (or 3.5 %) and 98.5 W m−2 (or 28.9 %), respectively. The retrieved SSR is also evaluated against daily radiation data at 90 China Meteorological Administration (CMA) stations. The MBEs are 9.8 W m−2 (or 5.4 %); the RMSEs in daily and monthly mean SSR estimates are 34.2 W m−2 (or 19.1 %) and 22.1 W m−2 (or 12.3 %), respectively. The accuracy is comparable to or even higher than two other radiation products (GLASS and ISCCP-FD), and the present method is more computationally efficient and can produce hourly SSR data at a spatial resolution of 5 km.

Optical Thickness and Effective Radius Retrievals of Low Stratus and Fog from MTSAT Daytime Data as a Prerequisite for Yellow Sea Fog Detection

Operational nowcasting techniques for sea fog over the Yellow Sea rely on data from weather satellites because ground-based observations are hardly available. While there are several algorithms for detecting low stratus (LST) that are applicable to geostationary weather satellite data, sea fog retrieval is more complicated. These schemes mostly need ancillary data such as Cloud Optical Thickness (COT) and Droplet Effective Radius (DER). To retrieve the necessary parameters for sea fog detection over the Yellow Sea, the Comprehensive Analysis Program for Cloud Optical Measurement (CAPCOM) scheme developed by Kawamoto et al. (2001) was adapted to the Japanese Multifunctional Transport Satellites (MTSAT) system-Japanese Advanced Meteorological Imager (JAMI). COT and DER values were then retrieved for 64 cases over the Yellow Sea (= 85,000 LST pixels) and compared with the COT and DER products from the MYD06/MOD06, CAPCOM-MODIS (Moderate Resolution Imaging Spectroradiometer) and CloudSat (cloud radar). Results showed that the COT and DER values retrieved from JAMI were satisfactory. The MTSAT-2 JAMI data delivered better COT values than the MTSAT-1R JAMI data, due to the re-calibration of MTSAT-2 JAMI’s visible (VIS) band in 2011. Similarly, improvements were seen in DER retrieval, even though the VIS re-calibration primarily affects COT retrieval. By comparing the difference in stratus thickness calculated by MTSAT-1R and MTSAT-2, the COT and DER retrieved from MTSAT-2 JAMI can be used in ground fog retrieval schemes. These values exhibit less bias, especially in cases involving high cloud top and thin cloud thickness. Both the COT and DER retrievals from MTSAT-2 JAMI offer potential as reliable parameters for Yellow Sea fog detection.

Mass Deposition Fluxes of Asian Dust to the Bohai Sea and Yellow Sea from Geostationary Satellite MTSAT: A Case Study

Windblown dust aerosol plays an important role in marine ecosystems once they are deposited and dissolved. At present, methods for estimating the deposition flux are mainly limited to direct measurements or model outputs. Additionally, satellite remote sensing was often used to estimate the integral dust column concentration (DCC). In this paper, an algorithm is developed to estimate the mass deposition fluxes of Asian dust by satellite. The dust aerosol is identified firstly and then the DCC is derived based on the relationships between the pre-calculated lookup table (LUT) and observations from Japanese geostationary Multi-functional Transport Satellites (MTSAT). The LUT is built on the dust cloud and surface parameters by a radiation transfer model Streamer. The average change rate of deposition is derived, which shows an exponential decay dependence on transport time along the pathway. Thus, the deposition flux is acquired via integrating the hourly deposition. This simple algorithm is applied to a dust storm that occurred in the Bohai Sea and Yellow Sea from 1 to 3 March 2008. Results indicate that the properties of the dust cloud over the study area changed rapidly and the mass deposition flux is estimated to be 2.59 Mt.

Coordinated airglow observations between IMAP/VISI and a ground‐based all‐sky imager on concentric gravity wave in the mesopause

AbstractWe present a study of concentric gravity waves (CGWs) event from the coordinated observation between Ionosphere, Mesosphere, upper Atmosphere, and Plasmasphere mapping (IMAP)/Visible and near‐Infrared Spectral Imager (VISI), all‐sky camera at Rikubetsu, Multi‐functional Transport Satellite (MTSAT), Tropical Rainfall Measuring Mission, and MF radar at Wakkanai combined with Modern‐Era Retrospective Analysis for Research and Application data. IMAP/VISI is the first space‐based imager that capable of imaging the airglow in the mesosphere and lower thermosphere region in the nadir‐looking direction. Therefore, it has a unique ability to observe a great extend of CGWs propagation. Arc‐like shaped, part of CGWs pattern was observed around the mesopause (~95 km) in the O2 762 nm airglow emission obtained by IMAP/VISI at 1204 UT on 18 October 2012. Similar patterns were also observed by the all‐sky imager at Rikubetsu (43.5°N, 143.8°E) in OI 557.7 nm and OH band airglow emissions from ~1100 to 1200 UT. Horizontal wavelengths of the observed small‐scale gravity waves are ~50 km (OH band and OI 557.7 nm) and ~67 km (O2 762 nm). The source is suggested to be a deep convective activity over Honshu Island which likely was an enhanced convective activity related to a typhoon in the south of Japan. The data showed that the CGWs could propagate up to ~1400–1500 km horizontally from the source to the mesopause but not farther away. Using atmospheric temperature profiles obtained by Thermospheric Ionosphere Mesosphere Energetics Dynamics/Sounding of the Atmosphere using Broadband Emission Radiometry, we conclude that this long‐distance propagation of the waves could be caused by thermal duct in the middle atmosphere. The arc‐like shaped instead of full circle pattern points out that the wind filtering effect is significant for the particular direction of wave propagation.

A method for estimating hourly photosynthetically active radiation (PAR) in China by combining geostationary and polar-orbiting satellite data

Photosynthetically active radiation (PAR) is an important parameter in ecosystem and land surface models. PAR represents the amount of solar radiation in the spectral range of 400–700nm that travels through the atmosphere to the top of the vegetation canopy. In recent years, various methods using different input data to estimate PAR and produce different PAR products have been developed. However, most of the algorithms used in these state-of-the-art studies have not fully compensated for the low spatial and temporal resolution of the data, which affects the accuracy of the PAR estimates. In this study, we have developed a method for estimating hourly PAR based on a combination of geostationary and polar-orbiting satellite data. The Multifunctional Transport Satellite (MTSAT) was selected to retrieve cloud optical depth (COD) with a higher spatial resolution, and the polar orbit satellite data of the Moderate Resolution Imaging Spectroradiometer (MODIS) products were used to derive surface parameters based on multispectral characteristics. A look-up table was established by the Second Simulation of a Satellite Signal in the Solar Spectrum-Vector (6SV) model and the Santa Barbara DISORT Atmospheric Radiative Transfer (SBDART) model consisting the following parameters: solar zenith angle, total water vapor, total ozone column, aerosol optical depth (AOD), COD, surface elevation, surface albedo and PAR. The instantaneous PAR was linearly interpolated from the input data for the selected parameters and the look-up table. The root mean square error (RMSE) between the estimated and observed instantaneous PAR at the Huailai station was 45.72W/m2 for all sky conditions. The RMSE between the estimated and observed daily PAR at the meteorological stations was 17% in the eastern regions of China. The mean bias error (MBE) was between −2.83 and 32.43W/m2 for the Tibetan Plateau. These results indicated that the proposed method can significantly improve the accuracy of PAR estimates and can be used to produce PAR products with high spatial and temporal resolution. However, the method requires further improvement, especially with respect to cloudy conditions.

Geostationary Satellite Observation of Precipitable Water Vapor Using an Empirical Orthogonal Function (EOF) based Reconstruction Technique over Eastern China

Water vapor, as one of the most important greenhouse gases, is crucial for both climate and atmospheric studies. Considering the high spatial and temporal variations of water vapor, a timely and accurate retrieval of precipitable water vapor (PWV) is urgently needed, but has long been constrained by data availability. Our study derived the vertically integrated precipitable water vapor over eastern China using Multi-functional Transport Satellite (MTSAT) data, which is in geostationary orbit with high temporal resolution. The missing pixels caused by cloud contamination were reconstructed using an Empirical Orthogonal Function (EOF) decomposition method over both spatial and temporal dimensions. GPS meteorology data were used to validate the retrieval and the reconstructed results. The diurnal variation of PWV over eastern China was analyzed using harmonic analysis, which indicates that the reconstructed PWV data can depict the diurnal cycle of PWV caused by evapotranspiration and local thermal circulation.

Spatial-Response Matched Filter and Its Application in Radiometric Accuracy Improvement of FY-2 Satellite Thermal Infrared Band

The adjacent effect caused by a nonideal system point spread function (PSF) is an important source generating additional errors in radiometric measurements. Traditional recovery methods, i.e., inverse and Wiener filters, are attempted to restore the scene without the influence of RSF, which is inexistent in real observations and usually leads to the ringing artifact as well as uncertainties in noise amplification (NA). In this paper, a novel spatial-response matched filter (SRMF) and its processing method are established, where the aimed scene is supposed to be observed by instruments with higher PSF performance. Also, NA effects triggered by SRMF are precisely modeled and used for the further evaluation of radiometric accuracy (RA) variation after SRMF processing. Simulation results indicate that the SRMF method is more suitable for images with lower noise level and greater variation in the targets' radiation, where RA performance could be improved in a certain extent. Meanwhile, when the imager in a Multifunctional Transport Satellite is selected as the reference one with high-performance PSF, the SRMF for Fengyun-2 satellite is set up and applied for observations in thermal infrared band during April and May 2013. After SRMF processing, the recovered images show significant improvements in both visual effects and RA, where the increase of RA is expected to be 2-6 K at 190 K in statistics. Such a progress is believed to be beneficial to tropical cyclone intensity estimation as well as for other relevant products, i.e., cloud classification generation.

Analysis of Interactions Among Two Tropical Depressions and Typhoons Tembin and Bolaven (2012) in Pacific Ocean by Using Satellite Cloud Images

This paper presents a framework for using remote sensing imagery and image processing techniques to analyze the interactions among tropical depressions (TDs) and typhoons. The purpose is to properly understand and predict this phenomenon, in order to reduce their influence on the regions where they pass by. Improvements on the understanding of the interactions among TDs and typhoons are obtained and presented. They carry the potential to improve forecast of severe weather system. In this paper, we analyzed the physical responses of TDs on two typhoons Tembin and Bolaven (2012), including TD's appearance, development, interaction, and mergence. According to the Central Weather Bureau of Taiwan, Tembin and Bolaven were formed about 1550 km apart. In general, the Fujiwhara effect happens when two storms are within a distance of 1400 km. Does the TD have impacts on the typhoons, and could we also call this impact as Fujiwhara effect? The 3-D profiles of the weather systems are reconstructed using the multifunctional transport satellite (MTSAT) infrared cloud images by the image reconstruction technique (IRT). The 3-D profiles of typhoons were implemented for investigating the in-depth distribution of the cloud top from a surface cloud image. The main parameters, which have been analyzed in this paper, are distance, height difference, rotation, and sizes of the two TDs and the two typhoons. The results showed that two TDs occurred between typhoons Tembin and Bolaven, which interacted with each other through upward convection and attraction between two typhoons and the TDs, respectively. The mergence of the two TDs caused the typhoons to start rotating and generate strengthened power. The findings of the TD effects on two typhoons represent a new aspect of the interaction between TD and typhoon.

MTSAT-1R Visible Imager Point Spread Function Correction, Part II: Theory

An image processing methodology is presented to recover the quality of the Multifunctional Transport Satellite (MTSAT)-1R visible channel data affected by spatial crosstalk. The slight blurring of the visible optical path is attributed to an imperfection in the mirror surface caused either by flawed polishing or a dust contaminant. The methodology assumes that the dispersed portion of the signal is small and distributed randomly around the optical axis, which allows the image to be deconvolved using an inverted point spread function (PSF). The PSF is described by four parameters, which are solved using a maximum-likelihood estimator using coincident collocated MTSAT-2 images as truth. A subpixel image matching technique is used to align the MTSAT-2 pixels into the MTSAT-1R projection and to correct for navigation errors and cloud displacement due to the time and viewing geometry differences between the two satellite observations. An optimal set of the PSF parameters is derived by an iterative routine based on the 4-D Powell's conjugate direction method that minimizes the difference between the PSF-corrected MTSAT-1R and the collocated MTSAT-2 images. The PSF parameters were found to be consistent over the 5 days of available daytime coincident and MTSAT-1R and MTSAT-2 images. After applying the PSF parameters, the visible sensor response is nearly linear, and the space count is close to zero. The overall linear regression standard error was reduced by 52%. Users can easily apply the PSF parameter coefficients to the MTSAT-1R imager pixel level counts to restore the original quality of the entire MTSAT-1R record.

MTSAT-1R Visible Imager Point Spread Correction Function, Part I: The Need for, Validation of, and Calibration With

The multifunctional transport satellite (MTSAT)-1R imager was launched in 2005 and is operated by the Japan Meteorological Agency (JMA). A nonlinear behavior in the MTSAT-1R visible sensor response is observed when the instrument is intercalibrated with coincident moderate resolution imaging spectroradiometer (MODIS) ray-matched radiances. Analysis reveals that the nonlinear behavior is not a result of imager navigation, sensor spectral response difference, nor scan pattern. Examination of coincident MTSAT-1R and MTSAT-2 images reveals that MTSAT-1R dark ocean radiances are affected by neighboring bright clouds, whereas large regions of dark ocean radiances are not impacted. Although the IR and visible optical paths are shared, the MTSAT-1R brightness temperatures are not affected. A dust contaminant coating the mirror, which only affects certain wavelengths, may be one explanation. To address the nonlinearity, a pixel point spread function (PSF) correction algorithm is implemented, wherein most of the radiance contribution is from the pixel field of view itself, as well as including a small contribution from all pixels within a radii of several hundred kilometers. The application of the PSF-corrected ~80% of the affected pixel radiances. After application, a near linear response is observed between the coincident MTSAT-1R and Aqua-MODIS ray-matched radiances, and the intercept is now near the predicted space count of zero. The monthly calibration gain noise is reduced by one-third when compared with the non-PSF-corrected gains. The monthly gains are the most erratic during the first two years of operation, and the MTSAT-1R visible sensor is degrading at ~1.9 % decade.

Investigation of Low-Cloud Characteristics Using Mesoscale Numerical Model Data for Improvement of Fog-Detection Performance by Satellite Remote Sensing

AbstractThe comprehensive relationship between meteorological conditions and whether low water cloud touches the surface, particularly at sea, is examined with the goal of improving low-cloud detection by satellite. Gridpoint-value data provided by an operational mesoscale model with integration of Multifunction Transport Satellite-2 data can provide sufficient data for statistical analyses to find general parameters that can discern whether low clouds touch the surface, compensating for uncertainty due to the scarcity of observation sites at sea and the infrequent incidence of fog. The analyses reveal that surface-touching low clouds tend to have lower cloud-top heights than those not touching the surface, although the frequency distribution of cloud-top height differs by season. The bottom of the Γ > Γm layer (where Γ and Γm are the vertical gradient and the moist-adiabatic lapse rate of the potential temperature, respectively) with surface-touching low-cloud layers tends to be very low or almost attached to the surface. In contrast, the tops of low-cloud layers not touching the surface tend to occur near the bottom of the Γ > Γm layer. Mechanisms to correlate these meteorological conditions with whether low clouds touch the surface are inferred from investigations into the vertical structure of equivalent potential temperature. These results indicate that the temperature difference between cloud-top height and the surface can be an appropriate parameter to infer whether low clouds touch the surface. It is also suggested that only a little addition of meteorological ancillary data, such as the forecast sea surface temperature, to satellite data allows successful performance of the discrimination.

Generating Global LAnd Surface Satellite incident shortwave radiation and photosynthetically active radiation products from multiple satellite data

Incident shortwave radiation (ISR) at the surface is an essential parameter in the land surface radiation budget and in many land surface process models. Incident photosynthetically active radiation (PAR) is required by nearly all terrestrial ecosystem models. Although several global radiation products from numeric models and satellite observations have been released, their coarse spatial resolutions and low accuracy, especially at high altitude regions, limit their applications in land community. In this study, the Global LAnd Surface Satellite (GLASS) ISR and PAR products are developed based on an improved look-up table method from 2008 to 2010 at a 5km spatial resolution and a 3hour temporal resolution, the first global radiation products at such high resolutions, from multiple polar-orbiting and geostationary satellite data, including the Moderate Resolution Imaging Spectroradiometer (MODIS), the Meteosat Second Generation (MSG2) SEVIRI, the Multi-functional Transport Satellite (MTSAT)-1R, and the Geostationary Operational Environmental Satellite (GOES) Imager. The look-up table algorithm primarily considers the influences of surface elevation, atmospheric water vapor because sensitivity experiments indicate that ISR and PAR are more sensitive to surface elevation, and less sensitive to atmospheric profiles and ozone amount. The water vapor absorption has strong impact on ISR but weak on PAR. Moreover, the surface bi-directional reflectance distribution function (BRDF) is taken into account to retrieve spatially and temporally continuous surface reflectances from the geostationary satellite observations, which is an input parameter in the revised look-up table method. Ground-based measurement data from 34 sites are used to validate the improved algorithm and the GLASS products. The validation results of the instantaneous ISR and PAR products at all validation sites are notably good with coefficient of determination values of 0.83 and 0.84, respectively, and root mean square error values of 115.0Wm−2 and 49.0Wm−2, respectively. We also aggregate the GLASS ISR product for comparing with the corresponding ISCCP and CERES data at 7 SURFRAD sites and demonstrate that the GLASS ISR product is more accurate. The GLASS ISR and PAR products have been made publicly available.

Satellite-Derived Tropical Cyclone Intensity in the North Pacific Ocean Using the Deviation-Angle Variance Technique

Abstract The deviation-angle variance technique (DAV-T), which was introduced in the North Atlantic basin for tropical cyclone (TC) intensity estimation, is adapted for use in the North Pacific Ocean using the “best-track center” application of the DAV. The adaptations include changes in preprocessing for different data sources [Geostationary Operational Environmental Satellite-East (GOES-E) in the Atlantic, stitched GOES-E–Geostationary Operational Environmental Satellite-West (GOES-W) in the eastern North Pacific, and the Multifunctional Transport Satellite (MTSAT) in the western North Pacific], and retraining the algorithm parameters for different basins. Over the 2007–11 period, DAV-T intensity estimation in the western North Pacific results in a root-mean-square intensity error (RMSE, as measured by the maximum sustained surface winds) of 14.3 kt (1 kt ≈ 0.51 m s−1) when compared to the Joint Typhoon Warning Center best track, utilizing all TCs to train and test the algorithm. The RMSE obtained when testing on an individual year and training with the remaining set lies between 12.9 and 15.1 kt. In the eastern North Pacific the DAV-T produces an RMSE of 13.4 kt utilizing all TCs in 2005–11 when compared with the National Hurricane Center best track. The RMSE for individual years lies between 9.4 and 16.9 kt. The complex environment in the western North Pacific led to an extension to the DAV-T that includes two different radii of computation, producing a parametric surface that relates TC axisymmetry to intensity. The overall RMSE is reduced by an average of 1.3 kt in the western North Pacific and 0.8 kt in the eastern North Pacific. These results for the North Pacific are comparable with previously reported results using the DAV for the North Atlantic basin.

Synoptic features and environmental conditions of the tornado outbreak on March 22, 2013 at Brahmanbaria in the east-central region of Bangladesh

This study evaluates the synoptic features and environmental conditions of Brahmanbaria tornado event that caused 36 fatalities, 388 injuries and huge damages of properties on 22 March, 2013. Various factors for initiation of that terrific event are investigated through analysis JRA-55 reanalysis (50 km horizontal resolution) data and Multi-functional Transport Satellite images by Japan Meteorological Agency. In addition, radar images, radiosonde data and three hourly synoptic data of Bangladesh Meteorological Department are used to verify the reanalysis data. The genesis of the tornadic storm is identifiable in the most unstable part of the study region. The satellite observations are found to useful to identify the location of convection occurrence region. The half hourly satellite images identify that the convection initiation started at the convergence area and the systems intensify and organize by the continuous moisture supply from the Bay of Bengal. Lower-level convergence coupled with strong wind shear and humidity gradient lift moist air aloft to trigger deep convection and the severe storm occurred. Energy Helicity Index seems a good predictor parameter for this specific case study.

Observations of typhoon eye using SAR and IR sensors

In this review, recent studies on the observations of typhoon eyes by images acquired by multiple sensors, including synthetic aperture radar (SAR), and infrared (IR) radiometer, are first summarized. Large horizontal distances between typhoon eyes on the ocean surface by SAR and those on the cloud top by IR sensors have been demonstrated; these have previously been ignored but should not be ignored in typhoon forecasts and numerical simulations. Then, based on nine published typhoon cases, the horizontal shifts and vertical tilt angles from the cloud-top typhoon eye locations by IR sensors on board the Feng-Yun 2 (FY-2) and Multi Functional Transport Satellite (MTSAT) to those at sea surface by SAR are further estimated. This shift difference between different sensors raises an issue on project distortion and navigation system errors for FY-2 and MTSAT satellites, which are of concern to both space agencies and data users. Finally, issues for current ongoing study and future research related to typhoon eyes are discussed, including rainband tracking between sensors for local wind speeds.

Assimilating MTSAT-Derived Humidity in Nowcasting Sea Fog over the Yellow Sea

Abstract An extended three-dimensional variational data assimilation (3DVAR) method based on the Weather Research and Forecasting Model (WRF) is developed to assimilate satellite-derived humidity from sea fog at its initial stage over the Yellow Sea. The sea fog properties, including its horizontal distribution and thickness, are retrieved empirically from the infrared and visible cloud imageries of the Multifunctional Transport Satellite (MTSAT). Assuming a relative humidity of 100% in fog, the MTSAT-derived humidity is assimilated by the extended 3DVAR assimilation method. Two sea fog cases, one spread widely over the Yellow Sea and the other spread narrowly along the coast, are first studied in detail with a suite of experiments. For the widespread-fog case, the assimilation of MTSAT-derived information significantly improves the forecast of the sea fog area, increasing the probability of detection and equitable threat scores by about 20% and 15%, respectively. The improvement is attributed to a more realistic representation of the marine boundary layer (MBL) and better descriptions of moisture and temperature profiles. For the narrowly spread coastal case, the model completely fails to reproduce the sea fog event without the assimilation of MTSAT-derived humidity. The extended 3DVAR assimilation method is then applied to 10 more sea fog cases to further evaluate its effect on the model simulations. The results reveal that the assimilation of MTSAT-derived humidity not only improves sea fog forecasts but also provides better moisture and temperature structure information in the MBL.