## 1 Introduction  
The international ocean satellite family will soon have two new members, HY-1C in 2018 and HY-1D in 2019, which will constitute China's optical satellite constellation for global ocean monitoring (one in the morning and the other in the afternoon). The two satellites are equipped with the same optical instruments. Except the Chinese Ocean Color and Temperature Scanner (COCTS) for the ocean color and sea surface temperature monitoring of the global ocean, another key payload is the Coastal Zone Imager (CZI), which can provide four broad band (i.e., blue, green, red, and near infrared) optical images with a wide swath of 950 km and moderate spatial resolution (50 m), for the coastal environment and resources monitoring from space. The wide swath is achieved by mosaicking the images acquired by the two identical cameras, each having a 32\({}^{\circ}\) field of view, with 1\({}^{\circ}\) overlapping. Through qualitative image interpretation, CZI will aid coastal zone management by providing key information on reclamation [1], wetlands [2], land cover/use [3], mangroves [4], coral reef [5], and sea ice [6] in the coastal zone and islands, where significant changes are usually expected due to intense human activity. At the same time, the quantitative information inversion from CZI images may also be expected to retrieve key parameters of aquatic environments (including turbidity, suspended sediment concentration, transparency, and water depth) [7; 8; 9], natural resources (such as wetland biomass) [10], and abnormal ecological phenomena [11; 12]. In order to achieve this goal, the comprehensive optical characterization of CZI is of high importance, including the radiometric accuracy, signal-to-noise ratio, out-of-band (OOB) response, etc. For the multi-spectral sensor, especially those with wide band width, the sensor-observed signal includes not only the contribution from sensor's in-band response, but also that from the unexpected OOB response [13]. Typically, the in-band radiometric contribution is defined as the integration of the input signal over the spectral domain within 1% peak response, whereas the OOB radiometric contribution is the difference between the in-band contribution and the total radiometric contribution, defined as the input signal integrated over the whole spectral domain [14]. Significant OOB response can lead to the shifting of the actual center wavelength relative to the nominal one (defined as the center of the 50% peak response), and the OOB-induced radiometric bias will have negative impact on the satellite-derived product [14]. Thus, the comprehensive prelaunch OOB assessment (and correction) is of vital importance for high-accuracy satellite data processing and high-quality products [13]. As the OOB radiometric contribution is determined not only by the sensor's spectral response, but also by the observed target radiance, a systematic OOB effect evaluation and correction should be performed for different types of waters [14]. Besides, as the top-of-the atmosphere (TOA) radiance (or reflectance) measured by the satellite sensor is dominated by the atmosphere radiometric contribution, the result of OOB evaluation based on this signal will mainly reflect the OOB modulation on the atmosphere signal, whereas the OOB influence on the ocean radiometric observation is less effectively characterized. In this background, the CZI OOB characteristics will be evaluated for turbid (Case 2) and clear (Case 1) waters [15], both of which will be covered in the CZI global observation of the world's coastal zones and islands. In order to effectively characterize the sensor's OOB effect on the in-water ocean color retrieval, the OOB analysis is based on the sensor-observed signal just above the sea surface (i.e., the spectral remote sensing reflectance \(\mathrm{R_{rs}}(\lambda)\)), rather than the TOA radiance, due to the fact that all the ocean biological and biogeochemical parameters are derived from \(\mathrm{R_{rs}}(\lambda)\).