Engineering topics

Kouvaris, L.

Publications and source records attributed to Kouvaris, L..

5 records

NASA NTRS2018

A GEOS-Based OSSE for the "MISTiC Winds" Concept

The Goddard Earth Observing System (GEOS) atmospheric model and data assimilation system are used to perform an Observing System Simulation Experiment (OSSE) for the proposed MISTiC Wind mission. The GEOS OSSE includes a reference simulation (the Nature Run), from which the pseudo-observations are generated. These pseuo-observations span the entire suite of in-situ and space space-based observations presently used in operational weather prediction, with the addition of the MISTiC-Wind dataset. New observation operators have been constructed for the MISTiC Wind data, including both the radiances measured in the 4-micron part of the solar spectrum and the winds derived from these radiances. The OSSE examines the impacts on global forecast skill of adding these observations to the current operational suite, showing substantial improvements in forecasts when the wind information are added. It is shown that a constellation of four MISTiC Wind satellites provides more benefit than a single platform, largely because of the increased accuracy of the feature-derived wind measurements when more platforms are used.

McCarty, W.↗

NASA NTRS2018

An OSSE Investigating a Constellation of 4-5 Micrometer Infrared Sounders

NASA is investigating the utility of a strategically-constructed constellation of infrared sounders on board small satellites to be able to ultimately provide spaceborne measurements of wind. The method proposed by instrument teams is to fly multiple instruments in complementary orbits so that atmospheric motion vector measurements can be made. As part of the investigation of this measurement approach, the Global Modeling and Assimilation Office (GMAO) at NASA Goddard Space Flight Center performed a set of Observing System Simulation Experiments (OSSEs) to demonstrate the value of the wind measurements as well as the corresponding infrared radiance observations that will come from the constellation. This work was an extension of the GMAO OSSE infrastructure and is in the context of the MISTIC Winds concept. It is noted, though, that this provided insight to the overall measurement strategy. This talk addresses the simulation of the atmospheric motion vectors retrieved via the constellation, the simulation and validation of the radiance observations measured via the constellation, the specification of observations errors for both winds and radiances, and the extension of the data assimilation system to utilize these additional observations on top of a full global observation system. Finally, the results from a set of OSSE experiments is presented.

McCarty, Will↗

NASA NTRS2000

Morphology of Mars North Polar Ice Cap

The northern ice cap of Mars consists of a parabolic dome centered within 13 km of the pole, plus an arm-like ridge extending from the dome between about 135 and 225 east. Chasma Boreale lies between the dome and the extended ridge. The base of the dome is approximately elliptical with a major axis of 1100 km along the 90 east to 270 east direction and minor axis of 700 km along zero east to 180 deg. The heights of the dome and the extended ridge are respectively 2900 inches and 1700 inches above the surrounding basin. Least-squares fitting of a parabola through height profiles of the dome along longitudes 90 deg to 270 deg and zero deg to 180 deg gives an elliptic-paraboloid equation for the dome: Z(m) = 2800 - [(X-x)(exp 2)/113.6] - [(Y-y)(exp 2)/50.3], where X is the 90 deg to 270 deg axis, x = 9.90 km, y = 13.32 km, and the slightly-different fitted heights for the two axes are averaged. The center of the dome is shifted 13.32 km from the pole along zero deg longitude and 9.90 km along 90 deg longitude. Typical mean surface slopes on the ice cap are the order of 1/100 (0.6 deg), A small central portion of the cap, about 100 km by 200 km, extends in elevation about 200 inches above the parabolic shape of the cap. Additional information is contained in the original extended abstract.

Zwally, H. J.↗

NASA NTRS1986

Monochromatic calculations of atmospheric radiative transfer due to molecular line absorption

Sensitivity studies related to the effects of line cutoff, spectral resolution, and temperature and pressure interpolations in radiative transfer have been performed so that a data set of absorption coefficients for water vapor, CO2, and O3 may be created efficiently. Results show that computations of absorption coefficients are affected only slightly by cutting a line off at a wave number 190 times the Lorentz half width from the center, or equivalently, cutting off 0.33 percent of the line intensity from the wings. To achieve a relative cooling rate error smaller than 2 percent, it is sufficient to precompute the absorption coefficient at three temperatures (210, 250, and 290 K) and 19 pressures with Delta (log 10 p) = 0.2. The absorption coefficient at other conditions can be interpolated linearly with pressure and exponentially with a quadratic in temperature. For the spectral resolution the absorption coefficients can be adequately computed at 0.01, 0.002, 0.005, and 0.025/cm intervals in the thermal water vapor, the CO2 and O3 bands, and the solar water vapor bands, respectively, which limits the error to only a few percent in the cooling and heating rates. Using the precomputed absorption coefficients, repeated monochromatic calculations of atmospheric heating/cooling rates for radiation model developments and for comparison with less detailed calculations are no longer difficult.

Chou, M.-D.↗

NASA NTRS1981

An efficient routine for infrared radiative transfer in a cloudy atmosphere

A FORTRAN program that calculates the atmospheric cooling rate and infrared fluxes for partly cloudy atmospheres is documented. The IR fluxes in the water bands and the 9.6 and 15 micron bands are calculated at 15 levels ranging from 1.39 mb to the surface. The program is generalized to accept any arbitrary atmospheric temperature and humidity profiles and clouds as input and return the cooling rate and fluxes as output. Sample calculations for various atmospheric profiles and cloud situations are demonstrated.

Chou, M. D.↗