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NASA NTRSDate not supplied

The Land Surface in Current and Planned MERRA Reanalysis Products

Current global atmospheric reanalysis products such as the European Centre for Medium-Range Weather Forecasts Reanalysis version 5 (ERA5), the NASA Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA-2), and the Japanese Reanalysis for Three Quarters of a Century (JRA-3Q) provide estimates of land surface states and fluxes, including soil moisture, soil temperature, snow mass, latent and sensible heat fluxes, and runoff, that are widely used in research and applications. These land surface estimates are based on land surface process models and, depending on the reanalysis product, on precipitation observations or the assimilation of land surface observations of soil moisture, soil temperature, snow conditions, and screen-level air temperature and humidity from satellite observations and in situ measurements. In this presentation, we review the land surface modeling and data assimilation components of the suite of current and planned MERRA reanalysis products. In addition to MERRA-2, we will discuss the latest NASA reanalysis, MERRA for the 21st century (M21C), which is currently under production, as well as the development and planning of the next version of the MERRA reanalysis, tentatively labeled MERRA-3. In MERRA-2, observations-based precipitation data products are used to correct the precipitation falling on the land surface. Outside of the high-latitudes and Africa, the daily, 0.5-degree, gauge-based Climate Prediction Center (CPC) Unified (CPCU) product is used. In Africa, the pentad, 2.5-degree, satellite- and gauge-based CPC Merged Analysis of Precipitation (CMAP) product is used. Poleward of 62.5 degrees latitude, the land surface sees the precipitation generated by the atmospheric model in the cycling data assimilation system. This configuration provides improved soil moisture estimates compared to those of the original (version 1) MERRA estimates, which did not benefit from the use of precipitation observations. Moreover, the use of precipitation observations facilitates a seamless spin-up of the land surface initial conditions across the MERRA-2 production streams. The use of a gauge-only precipitation product in MERRA-2 across much of the globe, however, adversely impacts the quality of the MERRA-2 land surface estimates in regions with poor gauge coverage, including most of South America and Australia. Therefore, the forthcoming M21C reanalysis uses satellite- and gauge-based precipitation from the Integrated Multi-satellitE Retrievals for the Global Precipitation Measurement Mission (IMERG). This change results in significant improvements in the quality of the M21C soil moisture estimates in the Southern Hemisphere compared to those from MERRA-2. Planning for MERRA-3 focuses on the assimilation of soil moisture observations from the Soil Moisture Active Passive (SMAP) mission and the Advanced Scatterometer (ASCAT), along with snow cover area fraction observations from the Moderate Resolution Imaging Spectroradiometer (MODIS) to further improve the quality of the land surface estimates from the reanalysis. As a first step towards the assimilation of land surface observations in MERRA-3, the offline (land-only) M21C-Land reanalysis is currently under development as a supplemental M21C product that includes the assimilation of SMAP, ASCAT, and MODIS observations. Preliminary results from M21C and M21C-Land will be discussed in the context of MERRA-2 and plans for MERRA-3.

Rolf Reichle↗
NASA NTRS2008

Microwave Extraction of Lunar Water for Rocket Fuel

Nearly 50% of the lunar surface is oxygen, present as oxides in silicate rocks and soil. Methods for reduction of these oxides could liberate the oxygen. Remote sensing has provided evidence of significant quantities of hydrogen possibly indicating hundreds of millions of metric tons, MT, of water at the lunar poles. If the presence of lunar water is verified, water is likely to be the first in situ resource exploited for human exploration and for LOX-H2 rocket fuel. In-Situ lunar resources offer unique advantages for space operations. Each unit of product produced on the lunar surface represents 6 units that need not to be launched into LEO. Previous studies have indicated the economic advantage of LOX for space tugs from LEO to GEO. Use of lunar derived LOX in a reusable lunar lander would greatly reduce the LEO mass required for a given payload to the moon. And Lunar LOX transported to L2 has unique advantages for a Mars mission. Several methods exist for extraction of oxygen from the soil. But, extraction of lunar water has several significant advantages. Microwave heating of lunar permafrost has additional important advantages for water extraction. Microwaves penetrate and heat from within not just at the surface and excavation is not required. Proof of concept experiments using a moon in a bottle concept have demonstrated that microwave processing of cryogenic lunar permafrost simulant in a vacuum rapidly and efficiently extracts water by sublimation. A prototype lunar water extraction rover was built and tested for heating of simulant. Microwave power was very efficiently delivered into a simulated lunar soil. Microwave dielectric properties (complex electric permittivity and magnetic permeability) of lunar regolith simulant, JSC-1A, were measured down to cryogenic temperatures and above room temperature. The microwave penetration has been correlated with the measured dielectric properties. Since the microwave penetration depth is a function of temperature and frequency, an extraction system can be designed for water removal from different depths.

Ethridge, Edwin C.↗
NASA NTRS2017

The Role of Local Heating in the 2015 Indian Heat Wave

India faced a major heat wave during the summer of 2015. Temperature anomalies peaked in the dry period before the onset of the summer monsoon, suggesting that local land-atmosphere feedbacks involving desiccated soils and vegetation might have played a role in driving the heat extreme. Upon examination of in situ data, reanalysis, satellite observations, and land surface models, we find that the heat wave included two distinct peaks: one in late May, and a second in early June. During the first peak we find that clear skies led to a positive net radiation anomaly at the surface, but there is no significant sensible heat flux anomaly within the core of the heat wave affected region. By the time of the second peak, however, soil moisture had dropped to anomalously low levels in the core heat wave region, net surface radiation was anomalously high, and a significant positive sensible heat flux anomaly developed. This led to a substantial local forcing on air temperature that contributed to the intensity of the event. The analysis indicates that the highly agricultural landscape of North and Central India can reinforce heat extremes under dry conditions.

Debjani Ghatak↗
NASA NTRS1974

Creation of an artificial lunar atmosphere

It is pointed out that the tenuous nature of the lunar atmosphere is maintained by rapid loss of gases released at the lunar surface. The loss of gases from the lunar atmosphere in the case of a greatly increased atmospheric density is investigated. It is found that in the case of such an increase in the density of the lunar atmosphere, a point can be reached where loss occurs so slowly that it is negligible over human time scales. In the event an artificial lunar atmosphere were to be created, gases can be obtained by heating or vaporization of the lunar soil. This could be done with the aid of nuclear devices.

Vondrak, R. R.↗
NASA NTRS1973

Environmental microbiology as related to planetary quarantine

The mechanistic basis of the synergetic effect of combined heat and radiation on microbial destruction was analyzed and results show that radiation intensity, temperature, and relative humidity are the determining factors. Dry heat resistance evaluation for selected bacterial spore crops indicates that different strains of Bacillus stearothermophilus demonstrate marked differences in resistance. Preliminary work to determine the effects of storage time, suspending medium, storage temperature and spore crop cleaning procedures on dry heat survival characteristics of Bacillus subtilis var. Niger, and dry heat resistance of natural microflora in soil particles is also reported.

Pflug, I. J.↗
NASA NTRS1974

Automated microbial metabolism laboratory

The labeled release concept was advanced to accommodate a post- Viking mission designed to extend the search, to confirm the presence of, and to characterize any Martian life found, and to obtain preliminary information on control of the life detected. The advanced labeled release concept utilizes four test chambers, each of which contains either an active or heat sterilized sample of the Martian soil. A variety of C-14 labeled organic substrates can be added sequentially to each soil sample and the resulting evolved radioactive gas monitored. The concept can also test effects of various inhibitors and environmental parameters on the experimental response. The current Viking '75 labeled release hardware is readily adaptable to the advanced labeled release concept.

Source record↗
NASA NTRS1984

Land-surface influences on weather and climate

Land-surface influences on weather and climate are reviewed. The interrelationship of vegetation, evapotranspiration, atmospheric circulation, and climate is discussed. Global precipitation, soil moisture, the seasonal water cycle, heat transfer, and atmospheric temperature are among the parameters considered in the context of a general biosphere model.

Baer, F.↗
NASA NTRS1985

The evolution of CO2 on Mars

At the surface, the atmosphere of Mars contains approximately 95.3 percent CO2 by volume. At the Viking Lander 1 (VL1) site, the total surface pressure varied with the season between about 6.89 and 8.94 mbar. Questions related to the observed CO2 pressure on Mars are explored. Several published estimates of the total amount of CO2 outgassed over the history of Mars, varying between 140 and 3000 mbar, are shown in a table. It is pointed out that the study of likely reservoirs for outgassed CO2 has focused mainly on the polar caps and regolith. Constraints on the formation of transitory pockets of moist soil are discussed, taking into account heat requirements, supply of water, and constraints related to pressure. Attention is also given to chemical considerations, implications for the current status of CO2 reservoirs, and scenarios for the evolution of CO2 pressure.

Kahn, R.↗
NASA NTRS1986

Release of noble gases and nitrogen from grain-surface sites in lunar ilmenite by closed-system oxidation

Noble gases and nitrogen were extracted from a 100 to 150 microns ilmenite separate from lunar soil 71501 by closed system stepped heating in approx. 10 torr O2 at 300 C, 400 C, 500 C, 600 C and 630 C, followed by stepped pyrolysis at ten temperatures between 680 C and approx. 1500 C. The five oxidation steps together liberated approx. 65% of the total He-4, 45% of the Ne-20, 23% of the N-14 and Ar-36, 12% of the Kr-84 and 8% of the Xe-132 in the sample; Ne-20/Ar-36 and Ne-20/Ne-22 ratios agree with the solar wind composition experiment, and Kr-84/Ar-36 and Xe-132/Ar-36 are within approx. 10% of Cameron's estimates for the sun and solar wind. The remaining gases, released above 630 C by pyrolysis, are strongly fractionated with respect to the SWC-Cameron solar wind elemental composition. Large concentrations of fractionated noble gases in grain interiors, their virtual absence in the relatively unfractionated surface gas reservoir, and the high N/noble gas ratio all imply that most of the solar wind noble gases initially implanted in grain surfaces are eventually lost by diffusion. Loss limits can be estimated by considering two given scenarios. It is concluded tat approx. 70 to 97% or more of the Ar implanted in 71501 ilmenite grains has diffusively escaped.

Frick, U.↗
NASA NTRS1992

A model of the CO2 exchanges between biosphere and atmosphere in the tundra

A physical model of the soil thermal regime in a permafrost terrain has been developed and validated with soil temperature measurements at Barrow, Alaska. The model calculates daily soil temperatures as a function of depth and average moisture contents of the organic and mineral layers using a set of five climatic variables, i.e., air temperature, precipitation, cloudiness, wind speed, and relative humidity. The model is not only designed to study the impact of climate change on the soil temperature and moisture regime, but also to provide the input to a decomposition and net primary production model. In this context, it is well known that CO2 exchanges between the terrestrial biosphere and the atmosphere are driven by soil temperature through decomposition of soil organic matter and root respiration. However, in tundra ecosystems, net CO2 exchange is extremely sensitive to soil moisture content; therefore it is necessary to predict variations in soil moisture in order to assess the impact of climate change on carbon fluxes. To this end, the present model includes the representation of the soil moisture response to changes in climatic conditions. The results presented in the foregoing demonstrate that large errors in soil temperature and permafrost depth estimates arise from neglecting the dependence of the soil thermal regime on soil moisture contents. Permafrost terrain is an example of a situation where soil moisture and temperature are particularly interrelated: drainage conditions improve when the depth of the permafrost increases; a decrease in soil moisture content leads to a decrease in the latent heat required for the phase transition so that the heat penetrates faster and deeper, and the maximum depth of thaw increases; and as excepted, soil thermal coefficients increase with moisture.

Labgaa, Rachid R.↗
NASA NTRS1998

Surface Emissivity Derived From Multispectral Satellite Data

Surface emissivity is critical for remote sensing of surface skin temperature and infrared cloud properties when the observed radiance is influenced by the surface radiation. It is also necessary to correctly compute the longwave flux from a surface at a given skin temperature. Surface emissivity is difficult to determine because skin temperature is an ill-defined parameter. The surface-emitted radiation may arise from a range of surface depths depending on many factors including soil moisture, vegetation, surface porosity, and heat capacity. Emissivity can be measured in the laboratory for pure surfaces. Transfer of laboratory measurements to actual Earth surfaces, however, is fraught with uncertainties because of their complex nature. This paper describes a new empirical approach for estimating surface skin temperature from a combination of brightness temperatures measured at different infrared wavelengths with satellite imagers. The method uses data from the new Geostationary Operational Environmental Satellite (GOES) imager to determine multispectral emissivities from the skin temperatures derived over the ARM Southern Great Plains domain.

Minnis, P.↗
NASA NTRSDate not supplied

Communicating Metrics of Land Surface Temperature Variability Using Multi-sensor Machine Learning

Land surface temperature (LST) is a key climate observable used to detect changes in the Earth’s surface energy budget that influence carbon and water cycles. Land surface temperature exhibits strong diurnal variability, which geostationary satellites can observe at scale thanks to their temporal resolution. Due to anthropogenic climate and land use changes, the surface energy balance has been considerably modified and may be described by changes in diurnal temperature range and extremes. Using high performance computing and datasets from the NASA Earth Exchange, we exploit co-located, co-temporal observations from low-earth orbit (LEO) and geostationary (GEO) sensors to develop a deep learning-based method for LEO-to-GEO algorithm emulation. Our model is trained to predict MODIS Terra LST from GOES-16 thermal bands and achieves validation error <2K. Application of the model to unseen times of day (observed by MODIS Aqua) and a new GEO sensor (Himawari-8) observing an unseen spatial domain, demonstrate the generalization of the deep learning model across space, time and spectra. Further, time series clustering approaches are examined with the objective of identifying key indicators of change in diurnal cycling and extremes on a continental scale. Communicating LST variability observed by geostationary satellites can have impacts in multiple disciplines, from understanding of snow, vegetation and soil dynamics, to recognizing trends in heat events relevant to human health.

Kate Duffy↗
NASA NTRSDate not supplied

LEO Sensor to GEO Sensor Algorithm Transfer Models for Land Surface Temperature

Land surface temperature (LST) is a key climate observable used to detect changes in the Earth’s surface energy budget that influence carbon and water cycles. Land surface temperature exhibits strong diurnal variability, which geostationary satellites can observe at scale thanks to their temporal resolution. Due to anthropogenic climate and land use changes, the surface energy balance has been considerably modified and may be described by changes in diurnal temperature range and extremes. Using high performance computing and datasets from the NASA Earth Exchange, we exploit co-located, co-temporal observations from low-earth orbit (LEO) and geostationary (GEO) sensors to develop a deep learning-based method for LEO-to-GEO algorithm emulation. Our model is trained to predict MODIS Terra LST from GOES-16 thermal bands and achieves validation error <2K. Application of the model to unseen times of day (observed by MODIS Aqua) and a new GEO sensor (Himawari-8) observing an unseen spatial domain, demonstrate the generalization of the deep learning model across space, time and spectra. Communicating diurnal LST variability observed by geostationary satellites can have impacts in multiple disciplines, from understanding of snow, vegetation and soil dynamics, to recognizing trends in heat events relevant to human health.

Kate Marie Duffy↗
NASA NTRS2005

A comparison of soil moisture sensors for space flight applications

Plants will be an important part of future long-term space missions. Automated plant growth systems require accurate and reliable methods of monitoring soil moisture levels. There are a number of different methods to accomplish this task. This study evaluated sensors using the capacitance method (ECH2O), the heat-pulse method (TMAS), and tensiometers, compared to soil water loss measured gravimetrically in a side-by-side test. The experiment monitored evaporative losses from substrate compartments filled with 1- to 2-mm baked calcinated clay media. The ECH2O data correlated well with the gravimetric measurements, but over a limited range of soil moisture. The averaged TMAS sensor data overstated soil moisture content levels. The tensiometer data appeared to track evaporative losses in the 0.5- to 2.5-kPa range of matric potential that corresponds to the water content needed to grow plants. This small range is characteristic of large particle media, and thus high-resolution tensiometers are required to distinguish changing moisture contents in this range.

NASA Center KSC↗
NASA NTRS1984

Soil temperature extrema recovery rates after precipitation cooling

From a one dimensional view of temperature alone variations at the Earth's surface manifest themselves in two cyclic patterns of diurnal and annual periods, due principally to the effects of diurnal and seasonal changes in solar heating as well as gains and losses of available moisture. Beside these two well known cyclic patterns, a third cycle has been identified which occurs in values of diurnal maxima and minima soil temperature extrema at 10 cm depth usually over a mesoscale period of roughly 3 to 14 days. This mesoscale period cycle starts with precipitation cooling of soil and is followed by a power curve temperature recovery. The temperature recovery clearly depends on solar heating of the soil with an increased soil moisture content from precipitation combined with evaporation cooling at soil temperatures lowered by precipitation cooling, but is quite regular and universal for vastly different geographical locations, and soil types and structures. The regularity of the power curve recovery allows a predictive model approach over the recovery period. Multivariable linear regression models alloy predictions of both the power of the temperature recovery curve as well as the total temperature recovery amplitude of the mesoscale temperature recovery, from data available one day after the temperature recovery begins.

Welker, J. E.↗
NASA NTRS2003

Reconciling the MOLA, TES, and Neutron Observations of the North Polar CO2 Mass Budget on Mars

There are now three independent observations of the CO2 polar cap mass budget of Mars' north polar cap. The first is based elevation changes detected by the Mars Orbiter Laser Altimeter (MOLA) on the Mars Global Surveyor (MGS). The second is based on MGS Thermal Emission Spectrometer (TES) broadband observations of the solar and infrared radiation fields at the top of the atmosphere. The third is based on neutron counts measured by the neutron spectrometer (NS) on Odyssey. The TES data are based on an energy balance. The net radiative loss (gain) in a column is balanced by latent heating due condensation (sublimation) of CO2. In calculating the mass budget, the other main energy sources, atmospheric heat transport and subsurface conduction, were neglected. At the pole, atmospheric heat transport is indeed a small term. However, subsurface heat conduction can be significant because at the North Pole water ice, which has a high thermal conductivity compared to bare soil, is a dominant component of the subsurface. Thus, heat conducted down into the ice during summer will slowly bleed back out during fall and winter reducing the amount of CO2 that condenses on the pole. We have taken a first cut at quantifying this effect by fitting a curve to Paige's estimates of the conducted energy flux in his analysis of Viking IRTM data.

Haberle, R. M.↗
NASA NTRS1993

Comparison between the land surface response of the ECMWF model and the FIFE-1987 data

An averaged time series for the surface data for the 15 x 15 km FIFE site was prepared for the summer of 1987. Comparisons with 48-hr forecasts from the ECMWF model for extended periods in July, August, and October 1987 identified model errors in the incoming SW radiation in clear skies, the ground heat flux, the formulation of surface evaporation, the soil-moisture model, and the entrainment at boundary-layer top. The model clear-sky SW flux is too high at the surface by 5-10 percent. The ground heat flux is too large by a factor of 2 to 3 because of the large thermal capacity of the first soil layer (which is 7 cm thick), and a time truncation error. The surface evaporation was near zero in October 1987, rather than of order 70 W/sq m at noon. The surface evaporation falls too rapidly after rainfall, with a time-scale of a few days rather than the 7-10 d (or more) of the observations. On time-scales of more than a few days the specified 'climate layer' soil moisture, rather than the storage of precipitation, has a large control on the evapotranspiration. The boundary-layer-top entrainment is too low. This results in a moist bias in the boundary-layer mixing ratio of order 2 g/Kg in forecasts from an experimental analysis with nearly realistic surface fluxes; this because there is insufficient downward mixing of dry air.

Betts, Alan K.↗
NASA NTRS2011

Simulated Seasonal Spatio-Temporal Patterns of Soil Moisture, Temperature, and Net Radiation in a Deciduous Forest

The temperature and moisture regimes in a forest are key components in the forest ecosystem dynamics. Observations and studies indicate that the internal temperature distribution and moisture content of the tree influence not only growth and development, but onset and cessation of cambial activity [1], resistance to insect predation[2], and even affect the population dynamics of the insects [3]. Moreover, temperature directly affects the uptake and metabolism of population from the soil into the tree tissue [4]. Additional studies show that soil and atmospheric temperatures are significant parameters that limit the growth of trees and impose treeline elevation limitation [5]. Directional thermal infrared radiance effects have long been observed in natural backgrounds [6]. In earlier work, we illustrated the use of physically-based models to simulate directional effects in thermal imaging [7-8]. In this paper, we illustrated the use of physically-based models to simulate directional effects in thermal, and net radiation in a adeciduous forest using our recently developed three-dimensional, macro-scale computational tool that simulates the heat and mass transfer interaction in a soil-root-stem systems (SRSS). The SRSS model includes the coupling of existing heat and mass transport tools to stimulate the diurnal internal and external temperatures, internal fluid flow and moisture distribution, and heat flow in the system.

Ballard, Jerrell R., Jr.↗