Initial Error Dispersion and Midcourse Correction Maneuver Analysis of the Lunar Orbiter

2018 ◽  
Vol 19 (4) ◽  
pp. 1041-1051
Author(s):  
Jonghee Bae ◽  
Young-Joo Song ◽  
Young-Rok Kim ◽  
Bangyeop Kim
2021 ◽  
Author(s):  
Hui Xu ◽  
Lei Chen ◽  
Wansuo Duan

AbstractThe optimally growing initial errors (OGEs) of El Niño events are found in the Community Earth System Model (CESM) by the conditional nonlinear optimal perturbation (CNOP) method. Based on the characteristics of low-dimensional attractors for ENSO (El Niño Southern Oscillation) systems, we apply singular vector decomposition (SVD) to reduce the dimensions of optimization problems and calculate the CNOP in a truncated phase space by the differential evolution (DE) algorithm. In the CESM, we obtain three types of OGEs of El Niño events with different intensities and diversities and call them type-1, type-2 and type-3 initial errors. Among them, the type-1 initial error is characterized by negative SSTA errors in the equatorial Pacific accompanied by a negative west–east slope of subsurface temperature from the subsurface to the surface in the equatorial central-eastern Pacific. The type-2 initial error is similar to the type-1 initial error but with the opposite sign. The type-3 initial error behaves as a basin-wide dipolar pattern of tropical sea temperature errors from the sea surface to the subsurface, with positive errors in the upper layers of the equatorial eastern Pacific and negative errors in the lower layers of the equatorial western Pacific. For the type-1 (type-2) initial error, the negative (positive) temperature errors in the eastern equatorial Pacific develop locally into a mature La Niña (El Niño)-like mode. For the type-3 initial error, the negative errors in the lower layers of the western equatorial Pacific propagate eastward with Kelvin waves and are intensified in the eastern equatorial Pacific. Although the type-1 and type-3 initial errors have different spatial patterns and dynamic growing mechanisms, both cause El Niño events to be underpredicted as neutral states or La Niña events. However, the type-2 initial error makes a moderate El Niño event to be predicted as an extremely strong event.


1969 ◽  
Vol 6 (7) ◽  
pp. 849-850
Author(s):  
PAUL M. MULLER ◽  
WILLIAM L. SJOGREN

Icarus ◽  
2013 ◽  
Vol 226 (1) ◽  
pp. 52-66 ◽  
Author(s):  
Mikhail A. Kreslavsky ◽  
James W. Head ◽  
Gregory A. Neumann ◽  
Margaret A. Rosenburg ◽  
Oded Aharonson ◽  
...  

2005 ◽  
Vol 14 (10) ◽  
pp. 1657-1666 ◽  
Author(s):  
GUANGYU LI ◽  
HAIBIN ZHAO

In the experimental tests of gravity, there have been considerable interests in the possibility of intermediate-range gravity. In this paper, we use the earth–satellite measurement of earth gravity, the lunar orbiter measurement of lunar gravity, and lunar laser ranging measurement to constrain the intermediate-range gravity from λ = 1.2 × 107 m –3.8 × 108 m . The limits for this range are α = 10-8–5 × 10-8, which improve previous limits by about one order of magnitude in the range λ = 1.2 × 107 m –3.8 × 108 m .


2014 ◽  
Vol 71 (7) ◽  
pp. 2476-2488 ◽  
Author(s):  
Dale R. Durran ◽  
Mark Gingrich

Abstract The spectral turbulence model of Lorenz, as modified for surface quasigeostrophic dynamics by Rotunno and Snyder, is further modified to more smoothly approach nonlinear saturation. This model is used to investigate error growth starting from different distributions of the initial error. Consistent with an often overlooked finding by Lorenz, the loss of predictability generated by initial errors of small but fixed absolute magnitude is essentially independent of their spatial scale when the background saturation kinetic energy spectrum is proportional to the −5/3 power of the wavenumber. Thus, because the background kinetic energy increases with scale, very small relative errors at long wavelengths have similar impacts on perturbation error growth as large relative errors at short wavelengths. To the extent that this model applies to practical meteorological forecasts, the influence of initial perturbations generated by butterflies would be swamped by unavoidable tiny relative errors in the large scales. The rough applicability of the authors’ modified spectral turbulence model to the atmosphere over scales ranging between 10 and 1000 km is supported by the good estimate that it provides for the ensemble error growth in state-of-the-art ensemble mesoscale model simulations of two winter storms. The initial-error spectrum for the ensemble perturbations in these cases has maximum power at the longest wavelengths. The dominance of large-scale errors in the ensemble suggests that mesoscale weather forecasts may often be limited by errors arising from the large scales instead of being produced solely through an upscale cascade from the smallest scales.


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