Global modelling of the early Martian climate under a denser CO2 atmosphere: Water cycle and ice evolution

We discuss 3D global simulations of the early Martian climate that we have performed assuming a faint young Sun and denser CO2 atmosphere. We include a self-consistent representation of the water cycle, with atmosphere-surface interactions, atmospheric transport, and the radiative effects of CO2 and H2O gas and clouds taken into account. We find that for atmospheric pressures greater than a fraction of a bar, the adiabatic cooling effect causes temperatures in the southern highland valley network regions to fall significantly below the global average. Long-term climate evolution simulations indicate that in these circumstances, water ice is transported to the highlands from low-lying regions for a wide range of orbital obliquities, regardless of the extent of the Tharsis bulge. In addition, an extended water ice cap forms on the southern pole, approximately corresponding to the location of the Noachian/Hesperian era Dorsa Argentea Formation. Even for a multiple-bar CO2 atmosphere, conditions are too cold to allow long-term surface liquid water. Limited melting occurs on warm summer days in some locations, but only for surface albedo and thermal inertia conditions that may be unrealistic for water ice. Nonetheless, meteorite impacts and volcanism could potentially cause intense episodic melting under such conditions. Because ice migration to higher altitudes is a robust mechanism for recharging highland water sources after such events, we suggest that this globally sub-zero, `icy highlands' scenario for the late Noachian climate may be sufficient to explain most of the fluvial geology without the need to invoke additional long-term warming mechanisms or an early warm, wet Mars.Comment: Minor revisions to text, one new table, figs. 1,3 11 and 18 redon

Comparison of Solar and Other Influences on Long-term Climate

Examples are shown of climate variability, and unforced climate fluctuations are discussed, as evidenced in both model simulations and observations. Then the author compares different global climate forcings, a comparison which by itself has significant implications. Finally, the author discusses a new climate simulation for the 1980s and 1990s which incorporates the principal known global climate forcings. The results indicate a likelihood of rapid global warming in the early 1990s

Understanding climate: A strategy for climate modeling and predictability research, 1985-1995

The emphasis of the NASA strategy for climate modeling and predictability research is on the utilization of space technology to understand the processes which control the Earth's climate system and it's sensitivity to natural and man-induced changes and to assess the possibilities for climate prediction on time scales of from about two weeks to several decades. Because the climate is a complex multi-phenomena system, which interacts on a wide range of space and time scales, the diversity of scientific problems addressed requires a hierarchy of models along with the application of modern empirical and statistical techniques which exploit the extensive current and potential future global data sets afforded by space observations. Observing system simulation experiments, exploiting these models and data, will also provide the foundation for the future climate space observing system, e.g., Earth observing system (EOS), 1985; Tropical Rainfall Measuring Mission (TRMM) North, et al. NASA, 1984

Extension of four-dimensional atmospheric models

The cloud data bank, the 4-D atmospheric model, and a set of computer programs designed to simulate meteorological conditions for any location above the earth are described in turns of space vehicle design and simulation of vehicle reentry trajectories. Topics discussed include: the relationship between satellite and surface observed cloud cover using LANDSAT 1 photographs and including the effects of cloud shadows; extension of the 4-D model to the altitude of 52 km; and addition of the u and v wind components to the 4-D model of means and variances at 1 km levels from the surface to 25 km. Results of the cloud cover analysis are presented along with the stratospheric model and the tropospheric wind profiles

Efficient dynamical downscaling of general circulation models using continuous data assimilation

Continuous data assimilation (CDA) is successfully implemented for the first time for efficient dynamical downscaling of a global atmospheric reanalysis. A comparison of the performance of CDA with the standard grid and spectral nudging techniques for representing long- and short-scale features in the downscaled fields using the Weather Research and Forecast (WRF) model is further presented and analyzed. The WRF model is configured at 25km horizontal resolution and is driven by 250km initial and boundary conditions from NCEP/NCAR reanalysis fields. Downscaling experiments are performed over a one-month period in January, 2016. The similarity metric is used to evaluate the performance of the downscaling methods for large and small scales. Similarity results are compared for the outputs of the WRF model with different downscaling techniques, NCEP reanalysis, and Final Analysis. Both spectral nudging and CDA describe better the small-scale features compared to grid nudging. The choice of the wave number is critical in spectral nudging; increasing the number of retained frequencies generally produced better small-scale features, but only up to a certain threshold after which its solution gradually became closer to grid nudging. CDA maintains the balance of the large- and small-scale features similar to that of the best simulation achieved by the best spectral nudging configuration, without the need of a spectral decomposition. The different downscaled atmospheric variables, including rainfall distribution, with CDA is most consistent with the observations. The Brier skill score values further indicate that the added value of CDA is distributed over the entire model domain. The overall results clearly suggest that CDA provides an efficient new approach for dynamical downscaling by maintaining better balance between the global model and the downscaled fields

Earthshine as an Illumination Source at the Moon

Earthshine is the dominant source of natural illumination on the surface of the Moon during lunar night, and at locations within permanently shadowed regions that never receive direct sunlight. As such, earthshine may enable the exploration of areas of the Moon that are hidden from solar illumination. The heat flux from earthshine may also influence the transport and cold trapping of volatiles present in the very coldest areas. In this study, Earth's spectral radiance at the Moon is examined using a suite of Earth spectral models created using the Virtual Planetary Laboratory (VPL) three dimensional modeling capability. At the Moon, the broadband, hemispherical irradiance from Earth near 0 phase is approximately 0.15 watts per square meter, with comparable contributions from solar reflectance and thermal emission. Over the simulation timeframe, spanning two lunations, Earth's thermal irradiance changes less than a few mW per square meter as a result of cloud variability and the south-to-north motion of sub-observer position. In solar band, Earth's diurnally averaged light curve at phase angles < 60 degrees is well fit using a Henyey Greenstein integral phase function. At wavelengths > 0.7 microns, near the well known vegetation "red edge", Earth's reflected solar radiance shows significant diurnal modulation as a result of the longitudinal asymmetry in projected landmass, as well as from the distribution of clouds. A simple formulation with adjustable coefficients is presented for estimating Earth's hemispherical irradiance at the Moon as a function of wavelength, phase angle and sub-observer coordinates. It is demonstrated that earthshine is sufficiently bright to serve as a natural illumination source for optical measurements from the lunar surface.Comment: 27 pages, 15 figures, 1 tabl