{"title":"Single-Point Calibration for Microwave Sounders: Application to TEMPEST-D","authors":"S. Brown, A. Tanner, S. Reising, W. Berg","doi":"10.1175/jtech-d-22-0063.1","DOIUrl":null,"url":null,"abstract":"\nPassive microwave sounders are critical for accurate forecasts from numerical weather prediction models. These sensors are calibrated using a traditional two-point approach, with one source typically a free-space blackbody target and the second a clear view to the cosmic microwave background, commonly referred to as “cold space.” Occasionally, one or both of these calibration sources can become corrupted, either by solar/lunar intrusion in the cold space view or by thermal instability of the blackbody calibration source. A Temporal Experiment for Storms and Tropical Systems (TEMPEST) microwave sounder instrument is currently deployed on the International Space Station (ISS) for a 3-year mission. TEMPEST is also calibrated using a blackbody target and cold space view; however, the cold space view will be routinely obstructed by objects present on the ISS. Here we test an alternative single point calibration methodology that uses only the blackbody calibration target. We find the brightness temperature difference between this new approach and the traditional two-point calibration approach to be < 0.1 K when applied to 3 years of the TEMPEST CubeSat Demonstration (TEMPEST-D) mission data from 2018-2020. This approach is applicable to other microwave radiometers that experience occasional degradation of calibration sources, such as thermal effects, intrusions or instability of noise diodes.","PeriodicalId":15074,"journal":{"name":"Journal of Atmospheric and Oceanic Technology","volume":" ","pages":""},"PeriodicalIF":1.9000,"publicationDate":"2023-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Atmospheric and Oceanic Technology","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.1175/jtech-d-22-0063.1","RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, OCEAN","Score":null,"Total":0}
引用次数: 0
Abstract
Passive microwave sounders are critical for accurate forecasts from numerical weather prediction models. These sensors are calibrated using a traditional two-point approach, with one source typically a free-space blackbody target and the second a clear view to the cosmic microwave background, commonly referred to as “cold space.” Occasionally, one or both of these calibration sources can become corrupted, either by solar/lunar intrusion in the cold space view or by thermal instability of the blackbody calibration source. A Temporal Experiment for Storms and Tropical Systems (TEMPEST) microwave sounder instrument is currently deployed on the International Space Station (ISS) for a 3-year mission. TEMPEST is also calibrated using a blackbody target and cold space view; however, the cold space view will be routinely obstructed by objects present on the ISS. Here we test an alternative single point calibration methodology that uses only the blackbody calibration target. We find the brightness temperature difference between this new approach and the traditional two-point calibration approach to be < 0.1 K when applied to 3 years of the TEMPEST CubeSat Demonstration (TEMPEST-D) mission data from 2018-2020. This approach is applicable to other microwave radiometers that experience occasional degradation of calibration sources, such as thermal effects, intrusions or instability of noise diodes.
期刊介绍:
The Journal of Atmospheric and Oceanic Technology (JTECH) publishes research describing instrumentation and methods used in atmospheric and oceanic research, including remote sensing instruments; measurements, validation, and data analysis techniques from satellites, aircraft, balloons, and surface-based platforms; in situ instruments, measurements, and methods for data acquisition, analysis, and interpretation and assimilation in numerical models; and information systems and algorithms.