Quantifying and Characterizing Striping of Microwave Humidity Sounder With Observation and Simulation

Striping has been observed in the MetOp-A microwave humidity sounder (MHS) data since its degradation in November 2018. However, accurate striping quantification and characterization remain challenging due to the large scene dynamics observed at W-/G-bands of MHS. Here, we have developed a set of novel algorithms for striping quantification, decomposition, characterization, and simulation. Our algorithm extracts striping from the warm-load and cold-space scenes that are relatively stable. We break down the striping into two parts of thermal and noises, and quantify their absolute magnitude and relative ratio. We found a significant increase in striping at 157 GHz, which has more than quadrupled by October 2019 relative to its normal level. Regardless of the degradation, the ratio of thermal and noises remains the same. Our simulation reproduces all the characteristics of striping against observation. It is shown that noise generates sharp, nonperiodic stripes, while thermal noise also generates stripes but with smoother band features. The latter is due to the periodic calibration that has a chopping effect. The striping percentage, defined as the ratio of to total noise, shows no dependence on the scene temperature. Striping is pronounced not only in 157 GHz but also in 89 and 190 GHz with the striping percentage over 50 & x0025; while lower in 183 GHz of 20 & x0025;. The results provide insights for quantifying and understanding striping. Our algorithm can be applied to other radiometers and to simulate striping for evaluating its impact on data assimilation and science products.