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The systematic difference between observations and simulation from weather forecast model hampers effective data assimilation and model improvement. The purpose of this study is to identify the characteristics and cause of the systematic difference or observation‐minus‐background (O − B) bias for all‐sky infrared radiances of the Himawari‐8 satellite, and propose data assimilation preprocessings and model verification. The O − B bias in cloudy scenes showed substantial negative values because of the shortage of high‐altitude clouds generated in the forecast model. Additionally, a positive bias appeared for thin ice clouds because of the excessive absorption of radiative transfer models (RTMs). These biases were traced based on a bottom‐up approach investigating individual uncertainty of RTMs, observation calibration, and the forecast model using two RTMs, reference hyperspectral sounders and synergetic measurements of CloudSat and CALIPSO. Based on these findings, data assimilation preprocessing such as quality‐control procedures excluding samples that models poorly reproduced was developed. Although the quality controls reduced the number of biased samples, non‐negligible O − B biases remained. Possible problems and treatments for the biases were discussed, including bias correction, observation error inflation, and correction of the cloud effect parameter. The O–B statistics also suggested insufficient representation of the diurnal variation in the cloud fraction in the tropics. Modified physical processes in the forecast model to increase ice clouds were tested to help improve the model bias and develop data assimilation. This trial indicated the difficulty in improving both O − B bias and variance and the necessity of adjusting the cloud effect parameters in data assimilation. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM PUBLISHER]

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. [ABSTRACT FROM PUBLISHER]

A Sierpinski gasket with continuous trajectories is presented as an example of the fractal transition that characterizes the behavior of dissipative dynamical systems excited by external temporal inputs. Using this example, we investigate the fractal transition from two points of views, i.e. a hierarchical structure and a noise effect. Depending on internal and external parameters, the structure can be geometrically classified as one of three types, i.e. totally disconnected, just-touching, and overlapping. For the totally disconnected structure, continuous trajectories and their starting points can be characterized by a definite hierarchical tree structure. Even for the just-touching and overlapping structure, a similar hierarchy exists. White noise contaminating the external inputs breaks the hierarchy. In particular, small clustered structures are sensitive to the noise. In such a case, the difference between trajectories and starting points is remarkable in the hierarchy. [ABSTRACT FROM AUTHOR]

This paper presents a framework for dissipative dynamical systems excited by external temporal inputs. We introduce a set {I[sub l]} of temporal inputs with finite intervals. The set {I[sub l]} defines two other sets of dynamical systems. The first is the set of continuous dynamical systems that are defined by a set {f[sub l]} of vector fields on the hyper-cylindrical phase space M. The second is the set of discrete dynamical systems that are defined by a set {g[sub l]} of iterated functions on the global Poincaré section Σ. When the inputs are switched stochastically, a trajectory in the space M converges to an attractive invariant set with fractal-like structure. We can analytically prove this result when all of the iterated functions satisfy a contraction property. Even without this property, we can numerically show that an attractive invariant set with fractal-like structure exists. [ABSTRACT FROM AUTHOR]