SMOS instrument performance and calibration after 6 years in orbit

Manuel Martin-Neira, Roger Oliva, Ignasi Corbella, Francesc Torres, Nuria Duffo, Israel Duran, Juha Kainulainen, Josep Closa, Alberto Zurita, Francois Cabot, Ali Khazaal, Eric Anterrieu (+10 others)
2016 2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)  
1 Abstract 40 41 ESA's Soil Moisture and Ocean Salinity (SMOS) mission, launched 2-Nov-2009, has been in orbit for over 5 42 years, and its Microwave Imaging Radiometer with Aperture Synthesis (MIRAS) in two dimensions keeps 43 working well. The calibration strategy remains overall as established after the commissioning phase, with a few 44 improvements. The data for this whole period has been reprocessed with a new fully polarimetric version of the 45 Level-1 processor which includes a refined
more » ... calibration schema for the antenna losses. This reprocessing has 46 allowed the assessment of an improved performance benchmark. An overview of the results and the progress 47 achieved in both calibration and image reconstruction is presented in this contribution. 48 2 INTRODUCTION 49 50 With an experience of over 5 years of in-orbit operation, much has been learnt on how MIRAS works 51 and how its observations can be improved through better calibration and image reconstruction 52 techniques. The purpose of this paper is to update the reader with the latest results on the payload 53 performance and data processing of the SMOS mission (Mecklenburg et al., 2012) . SMOS is currently 54 delivering several products, some of them used by operational systems, others only for scientific 55 research (Mecklenburg et al., in press). MIRAS is a Microwave Imaging Radiometer with two-56 dimensional Aperture Synthesis, which remains being the first and so far, the only one of its kind, in 57 space. The main feature of MIRAS is that it obtains two-dimensional images at every snapshot without 58 needing any mechanical scanning of its antenna, a very distinct capability when compared with 59 traditional scanners or push-broom radiometers. A detailed description of the instrumental aspects of 60 MIRAS can be found in (McMullan et al., 2008) while the on-board Calibration System and respective 61 in-flight calibration strategy are described in (Brown et al., 2008) and (Martín-Neira et al., 2008). One 62 year after launch the calibration approach was slightly modified with the initial flight experience, and 63 the first SMOS instrument in-orbit performance was assessed in (Oliva et al., 2013), including the 64 effect of the unexpectedly severe Radio Frequency Interference from ground transmitters (Oliva et al., 65 2012). The present paper will then follow the same structure as (Oliva et al., 2013), with important 66 REPLACE THIS LINE WITH YOUR PAPER IDENTIFICATION NUMBER (DOUBLE-CLICK HERE TO EDIT) < 3 additions brought by the accumulated experience of over 5 years: Section 3 provides an overview of the 67 main sources of error and the current mitigation strategies used to overcome them; Section 4 68 summarizes the current status of calibration activities, including all latest modifications to the initial 69 calibration plan; Section 5 presents the in-orbit behaviour of the most critical instrument parameters; 70 Section 6 gives the performance obtained with the latest version of the Level-1 processor, through the 71 spatial and temporal analysis of brightness temperature images, and finally, Section 7 includes a view 72 on the current investigations that should lead to the next version of the Level-1 processor with a hint on 73 the expected improvements. 74 It is worth mentioning that, at the time of the writing of this paper, the running version of the 75 operational SMOS Level-1 data processor is V620, that a new version, V700, has been delivered and is 76 under assessment, and that the entire data record of the SMOS mission (from January 2010 onwards) 77 has been reprocessed with V620 and is available to the whole SMOS user community. 78 79 ERROR SOURCES AND MITIGATION TECHNIQUES 80 Error Sources 81 Different error sources cause different effects on the SMOS brightness temperature images. Therefore 82 in this section the error sources will be presented according to the effect they produce in the images. 83 3.1.1 Systematic Spatial Ripple 84 85 Figure 1 presents the deviation, with respect to a forward model, of an image of the brightness 86 temperature measured by SMOS over a portion of the South-Eastern Pacific Ocean in X-polarization 87 (X-polarization refers to the image formed with the signal collected by the horizontal probe of MIRAS 88 antenna elements). The comparison is performed after averaging many snapshots so that random errors 89 induced by the radiometric resolution can be neglected, and only systematic errors remain. The most 90 prominent features of such deviation image are a +0.96 K bias and a 1.5 K rms spatial ripple, both 91 statistics evaluated within the dashed circle shown in Figure 1. Similar statistics can be computed for 92 REPLACE THIS LINE WITH YOUR PAPER IDENTIFICATION NUMBER (DOUBLE-CLICK HERE TO EDIT) < 4 the Y-polarization as well as for the Stokes-3 and Stokes-4 parameters, obtaining, in general, different 93 values for the different parameters, values which, in turn, depend on the particular image reconstruction 94 approach being applied, that is, on the Level-1 processor version. Furthermore, and although it is not as 95 easy to show as with measurements of the relatively uniform ocean, bias and ripples also appear in 96 images acquired over any region of the Earth, be it land, ice or coastlines, and over the Cold Sky, 97
doi:10.1109/igarss.2016.7729526 dblp:conf/igarss/Martin-NeiraOCT16 fatcat:knhb6vbj2ncoraimyrshugpshe