Evaluation of remotely sensed indices for assessing burn severity in interior Alaska using Landsat TM and ETM

[1] We define the radiative forcings used in climate simulations with the SI2000 version of the Goddard Institute for Space Studies (GISS) global climate model. These include temporal variations of well-mixed greenhouse gases, stratospheric aerosols, solar irradiance, ozone, stratospheric water vapor, and tropospheric aerosols. Our illustrations focus on the period 1951–2050, but we make the full data sets available for those forcings for which we have earlier data. We illustrate the global response to these forcings for the SI2000 model with specified sea surface temperature and with a simple Q-flux ocean, thus helping to characterize the efficacy of each forcing. The model yields good agreement with observed global temperature change and heat storage in the ocean. This agreement does not yield an improved assessment of climate sensitivity or a confirmation of the net climate forcing because of possible compensations with opposite changes of these quantities. Nevertheless, the results imply that observed global temperature change during the past 50 years is primarily a response to radiative forcings. It is also inferred that the planet is now out of radiation balance by 0.5 to 1 W/m 2 and that additional global warming of about 0.5� C is already ‘‘in the pipeline.’’ INDEX TERMS: 1620 Global Change: Climate dynamics (3309); 1635 Global Change: Oceans (4203); 1650 Global Change: Solar variability;

/pdf/climate-forcings-in-goddard-institute-for-space-studies-dj8hzgc5ro.pdf

Climate forcings in Goddard Institute for Space Studies SI2000 simulations

Apparent thermal inertia and the surface heterogeneity of Mars

Time-dependent models of the thermal and diffusive behavior of the Martian regolith are developed to investigate the stability of ground ice within the top several meters of the regolith. The geographic distribution of thermal inertia and albedo as well as the latitudinal variation in insolation are included in calculations of surface and subsurface temperatures between +/- 60 deg latitude. Ground ice is found to be stable where the annual mean surface and subsurface temperatures were below the atmospheric frost point. Calculations of temperatures at high and low obliquity suggest that ground ice would be stable globally at high obliquity and would not be stable between +/- 60 deg latitude at low obliquity. The time scales for condensation of ground ice are found to be comparable to that of orbital oscillations, suggesting that the present geographic distribution of ground ice may depend on the orbital history of Mars.

Geographic variations in the thermal and diffusive stability of ground ice on Mars

Gaussian processes (GPs) have experienced tremendous success in biogeophysical parameter retrieval in the last few years. GPs constitute a solid Bayesian framework to consistently formulate many function approximation problems. This article reviews the main theoretical GP developments in the field, considering new algorithms that respect signal and noise characteristics, extract knowledge via automatic relevance kernels to yield feature rankings automatically, and allow applicability of associated uncertainty intervals to transport GP models in space and time that can be used to uncover causal relations between variables and can encode physically meaningful prior knowledge via radiative transfer model (RTM) emulation. The important issue of computational efficiency will also be addressed. These developments are illustrated in the field of geosciences and remote sensing at local and global scales through a set of illustrative examples. In particular, important problems for land, ocean, and atmosphere monitoring are considered, from accurately estimating oceanic chlorophyll content and pigments to retrieving vegetation properties from multi- and hyperspectral sensors as well as estimating atmospheric parameters (e.g., temperature, moisture, and ozone) from infrared sounders.

/pdf/a-survey-on-gaussian-processes-for-earth-observation-data-57o1q6kh7k.pdf

A Survey on Gaussian Processes for Earth-Observation Data Analysis: A Comprehensive Investigation

A model originally developed to explain the spectral albedo and emissivity of terrestrial snow is extended to the case of carbon dioxide snow on Mars. The variation of albedo and emissivity with wavelength is caused by the spectral variation of the absorption coefficient of solid CO2. The most important variables controlling the radiative properties are grain size and contamination by dust or water. Solar zenith angle and snowpack thickness are of less importance. The observation that red albedo is higher than blue albedo in the Martian south polar cap indicates that the snow is contaminated with red dust. The interband absorption coefficient of CO2 ice in the thermal infrared is 2-3 orders of magnitude smaller than that of H20 ice, due to the absence of hydrogen bonding in CO2. This allows CO2 snow emissivity to be sensitive to grain size, emission angle, and impurities, in contrast to water snow which is nearly a blackbody under all conditions. The emissivity of CO2 snow varies substantially with wavelength, so energy budget modeling should be done in spectral detail. The addition of a thin layer of water frost over CO2 snow dramaticaliy raises the thermal emissivity but causes little change to the spectrally averaged albedo unless the underlying CO2 snow is dirty. Remote sensing of CO2 grain size, H20 content, and dust content may be possible. However, the design of a remote-sensing strategy awaits more accurate laboratory determination of the optical constants of CO2 ice.

NASA Goddard Space Flight Center, Greenbelt, Maryland

In this paper, a snow albedo model previously developed for terrestrial snow is extended to the case of CO2 snow on Mars. Pure CO2 snow is calculated to have high albedo at visible wavelengths but not as high as that of water snow. At any given wavelength, the primary variable controlling albedo and emissivity is the snow grain size, with albedo decreasing and emissivity increasing as grain size increases. Observations that red albedo is much higher than blue albedo in the Martian south polar cap indicates that the snow or the atmosphere is contaminated with red dust. The absorption coefficient of CO2 ice in the thermal infrared is two to three orders of magnitude smaller than that measured for H2O ice. CO2 snow emissivity is therefore much lower than H2O snow, varying substantially with wavelength and quite sensitive to grain size and emission angle. Factors tending to increase emissivity are large grain size, small emission angle, and large concentrations of dust or water.

/pdf/spectral-albedo-and-emissivity-of-co2-in-martian-polar-caps-4fxj0zu5d6.pdf

Spectral albedo and emissivity of CO2 in Martian polar caps - Model results

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NASA Goddard Space Flight Center, Greenbelt, Maryland

Spectral albedo and emissivity of CO2 in Martian polar caps - Model results