TY - JOUR
T1 - Community Global Observing System Simulation Experiment (OSSE) Package (CGOP)
T2 - Perfect observations simulation validation
AU - Boukabara, Sid Ahmed
AU - Ide, Kayo
AU - Shahroudi, Narges
AU - Zhou, Yan
AU - Zhu, Tong
AU - Li, Ruifang
AU - Cucurull, Lidia
AU - Atlas, Robert
AU - Casey, Sean P.F.
AU - Hoffman, Ross N.
N1 - Publisher Copyright:
© 2018 American Meteorological Society.
PY - 2018/1/1
Y1 - 2018/1/1
N2 - The simulation of observations-a critical Community Global Observing System Simulation Experiment (OSSE) Package (CGOP) component-is validated first by a comparison of error-free simulated observations for the first 24 h at the start of the nature run (NR) to the real observations for those sensors that operated during that period. Sample results of this validation are presented here for existing low-Earth-orbiting (LEO) infrared (IR) and microwave (MW) brightness temperature (BT) observations, for radio occultation (RO) bending angle observations, and for various types of conventional observations. For sensors not operating at the start of the NR, a qualitative validation is obtained by comparing geographic and statistical characteristics of observations over the initial day for such a sensor and an existing similar sensor. The comparisons agree, with no significant unexplained bias, and to within the uncertainties caused by real observation errors, time and space collocation differences, radiative transfer uncertainties, and differences between the NR and reality. To validate channels of a proposed future MW sensor with no equivalent existing spaceborne sensor channel, multiple linear regression is used to relate these channels to existing similar channels. The validation then compares observations simulated from the NR to observations predicted by the regression relationship applied to actual real observations of the existing channels. Overall, the CGOP simulations of error-free observations from conventional and satellite platforms that make up the global observing system are found to be reasonably accurate and suitable as a starting point for creating realistic simulated observations for OSSEs. These findings complete a critical step in the CGOP validation, thereby reducing the caveats required when interpreting the OSSE results.
AB - The simulation of observations-a critical Community Global Observing System Simulation Experiment (OSSE) Package (CGOP) component-is validated first by a comparison of error-free simulated observations for the first 24 h at the start of the nature run (NR) to the real observations for those sensors that operated during that period. Sample results of this validation are presented here for existing low-Earth-orbiting (LEO) infrared (IR) and microwave (MW) brightness temperature (BT) observations, for radio occultation (RO) bending angle observations, and for various types of conventional observations. For sensors not operating at the start of the NR, a qualitative validation is obtained by comparing geographic and statistical characteristics of observations over the initial day for such a sensor and an existing similar sensor. The comparisons agree, with no significant unexplained bias, and to within the uncertainties caused by real observation errors, time and space collocation differences, radiative transfer uncertainties, and differences between the NR and reality. To validate channels of a proposed future MW sensor with no equivalent existing spaceborne sensor channel, multiple linear regression is used to relate these channels to existing similar channels. The validation then compares observations simulated from the NR to observations predicted by the regression relationship applied to actual real observations of the existing channels. Overall, the CGOP simulations of error-free observations from conventional and satellite platforms that make up the global observing system are found to be reasonably accurate and suitable as a starting point for creating realistic simulated observations for OSSEs. These findings complete a critical step in the CGOP validation, thereby reducing the caveats required when interpreting the OSSE results.
KW - Algorithms
KW - Data assimilation
KW - Regression analysis
KW - Satellite observations
UR - https://www.scopus.com/pages/publications/85041661573
U2 - 10.1175/JTECH-D-17-0077.1
DO - 10.1175/JTECH-D-17-0077.1
M3 - Article
AN - SCOPUS:85041661573
SN - 0739-0572
VL - 35
SP - 207
EP - 226
JO - Journal of Atmospheric and Oceanic Technology
JF - Journal of Atmospheric and Oceanic Technology
IS - 1
ER -