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NASA NTRS1981

Reports of Planetary Geology Program, 1981

Abstracts of 205 reports from Principal investigators of NASA's Planetary Geology Program succinctly summarize work conducted and reflect the significant accomplishments. The entries are arranged under the following topics: (1) Saturnian satellites; (2) asteroids, comets and Galilean satellites; (3) cratering processes and landform development; (4) volcanic processes and landforms; (5) Aerolian processes and landforms; (6) fluvial, preglacial, and other processes of landform development; (7) Mars polar deposits, volatiles, and climate; (8) structure, tectonics, and stratigraphy; (9) remote sensing and regolith chemistry; (10) cartography and geologic mapping; and (11) special programs.

Holt, H. E.↗

NASA NTRS1991

NSSDC data listing

The purpose here is to identify, in a highly summarized way, data available from the National Space Science Data Center (NSSDC). Most data are maintained as offline data sets gathered from individual instruments carried on spacecraft; these comprise the Satellite Data Listing. Descriptive names, time spans, data form, and quality of these data sets are identified in the listing, which is sorted alphabetically, first by spacecraft name and then by the principal investigator's or team leader's last name. Several data sets not associated with individual spaceflight instruments are identified in separate listings following the Satellite Data Listing. These include composite spacecraft data sets, ground based data, models, and computer routines. NSSDC also offers data via special services and systems in a number of areas, including the Astronomical Data Center, Coordinated Data Analysis Workshops, NASA Climate Data System, Pilot Land Data System, and Crustal Dynamics Data Information System.

Horowitz, Richard↗

NASA NTRS1998

The Origin of Antarctic Precipitation: A Modeling Approach

Isotope concentrations in polar ice cores have long been used to estimate paleotemperatures. Underlying the use of this "isotope paleothermometer" is the assumption that the relationship between surface temperature and isotope concentration over time at a single geographical point is the same as that observed over space during the present-day climate. The validity of this assumption may in fact be compromised by several factors related to climate change. The specific factor studied in this paper involves the evaporative sources for polar precipitation. Climatic changes in the relative strengths of these sources would imply a need for a recalibration of the paleothermometer. To quantify such changes, we performed two GCM simulations, one of present-day climate and the other of the climate during the Last Glacial Maximum (LGM), roughly 18000 years ago. Evaporative sources of Antarctic precipitation were established using special tracer diagnostics. Results suggest that polar precipitation during the LGM does indeed consist of (relatively) more water from tropical oceans, a direct reflection of the LGM's increased equator-to-pole temperature gradient and its increased sea ice extent, which reduces high latitude evaporation. This result implies that an uncalibrated ice core paleothermometer would produce LGM temperatures that are biased slightly low. Because LGM boundary conditions are still under debate, we performed a third GCM simulation using a modified set of LGM boundary conditions. Using this simulation gives some qualitatively similar results, though the tropical contribution is not quite as high. Uncertainties in the LGM boundary conditions does hamper success in calibrating the paleothermometer.

Delaygue, Gilles↗

NASA NTRSDate not supplied

Studying Microbial Adaptation in the Laboratory: Sensor & Control Upgrades for an Experimental Evolution Biofluidics System

Experimental evolution (EE) involves iteratively exposing a microbial community to specific stressors to study its response to changes in environment over time. EE work is commonly done manually in the laboratory, but, when there are many environmental variables to measure and adjust, it is highly labor intensive, prone to human error, and challenging to scale. Single-purpose automated continuous culturing chambers exist, but implement only limited stressor types. A more general-purpose design is desirable. The BeING Lab at Ames Research Center created the prototype Automated Adaptive Directed Evolution Chamber (AADEC) to address these problems, beginning with Escherichia coli tolerance of short-wave ultraviolet (UV-C) radiation and of temperature. In newer versions, AADEC monitors microbial activity and can adjust the UV-C and temperature levels automatically. An optical density measurement is used to determine how many cells are present in the growth medium—over time, this corresponds to how many survive and reproduce. Oxidation-reduction potential provides information on consumed metabolic energy, and pH and electrical conductivity on metabolic products. Dissolved oxygen content is used to determine aerobic vs anaerobic growth. A Raspberry Pi computer processes all this data to set the UV-C stressor level. AADEC’s auxiliary systems include peristaltic pumps to change media and agitation to counteract cell settling. These actuators can also act as additional stressors. With the Raspberry Pi monitoring sensors and adjusting actuators in real time, AADEC takes measurements and controls the environment much more accurately than can be done with a manual EE implementation. The third and latest AADEC iteration is the first to simplify design and usage with circuits on PCBs and the ability to pre-program experimental protocols. Still planned is expansion to a multi-well design for the study of varying cell cultures in parallel, which will enable researchers to retain and re-inoculate cultures exhibiting the desired trait most strongly while flushing out others. AADEC’s special capabilities make it a valuable tool for studying life under multiple stressors, enabling scientists to replicate changes in climate on microbes for study in a lab setting.

Microbial Adaptation↗

NASA NTRS2000

Snow Physics and Meltwater Hydrology of the SSiB Model Employed for Climate Simulation Studies with GEOS 2 GCM

Present-day climate models produce large climate drifts that interfere with the climate signals simulated in modelling studies. The simplifying assumptions of the physical parameterization of snow and ice processes lead to large biases in the annual cycles of surface temperature, evapotranspiration, and the water budget, which in turn causes erroneous land-atmosphere interactions. Since land processes are vital for climate prediction, and snow and snowmelt processes have been shown to affect Indian monsoons and North American rainfall and hydrology, special attention is now being given to cold land processes and their influence on the simulated annual cycle in GCMs. The snow model of the SSiB land-surface model being used at Goddard has evolved from a unified single snow-soil layer interacting with a deep soil layer through a force-restore procedure to a two-layer snow model atop a ground layer separated by a snow-ground interface. When the snow cover is deep, force-restore occurs within the snow layers. However, several other simplifying assumptions such as homogeneous snow cover, an empirical depth related surface albedo, snowmelt and melt-freeze in the diurnal cycles, and neglect of latent heat of soil freezing and thawing still remain as nagging problems. Several important influences of these assumptions will be discussed with the goal of improving them to better simulate the snowmelt and meltwater hydrology. Nevertheless, the current snow model (Mocko and Sud, 2000, submitted) better simulates cold land processes as compared to the original SSiB. This was confirmed against observations of soil moisture, runoff, and snow cover in global GSWP (Sud and Mocko, 1999) and point-scale Valdai simulations over seasonal snow regions. New results from the current snow model SSiB from the 10-year PILPS 2e intercomparison in northern Scandinavia will be presented.

Mocko, David M.↗

NASA NTRS2002

Role of Satellite Rainfall Information in Improving Understanding of the Dynamical Link Between the Tropics and Extratropics Prospects of Improved Forecasts of Weather and Short-Term Climate Variability on Sub-Seasonal Time Scales

The tropics and extratropics are two dynamically distinct regimes. The coupling between these two regimes often defies simple analytical treatment. Progress in understanding of the dynamical interaction between the tropics and extratropics relies on better observational descriptions to guide theoretical development. However, global analyses currently contain significant errors in primary hydrological variables such as precipitation, evaporation, moisture, and clouds, especially in the tropics. Tropical analyses have been shown to be sensitive to parameterized precipitation processes, which are less than perfect, leading to order-one discrepancies between estimates produced by different data assimilation systems. One strategy for improvement is to assimilate rainfall observations to constrain the analysis and reduce uncertainties in variables physically linked to precipitation. At the Data Assimilation Office at the NASA Goddard Space Flight Center, we have been exploring the use of tropical rain rates derived from the TRMM Microwave Imager (TMI) and the Special Sensor Microwave/ Imager (SSM/I) instruments in global data assimilation. Results show that assimilating these data improves not only rainfall and moisture fields but also related climate parameters such as clouds and radiation, as well as the large-scale circulation and short-range forecasts. These studies suggest that assimilation of microwave rainfall observations from space has the potential to significantly improve the quality of 4-D assimilated datasets for climate investigations (Hou et al. 2001). In the next few years, there will be a gradual increase in microwave rain products available from operational and research satellites, culminating to a target constellation of 9 satellites to provide global rain measurements every 3 hours with the proposed Global Precipitation Measurement (GPM) mission in 2007. Continued improvements in assimilation methodology, rainfall error estimates, and model parameterizations are needed to ensure that we derive maximum benefits from these observations.

Hou, Arthur Y.↗

NASA NTRS1998

Developing Information Power Grid Based Algorithms and Software

This was an exploratory study to enhance our understanding of problems involved in developing large scale applications in a heterogeneous distributed environment. It is likely that the large scale applications of the future will be built by coupling specialized computational modules together. For example, efforts now exist to couple ocean and atmospheric prediction codes to simulate a more complete climate system. These two applications differ in many respects. They have different grids, the data is in different unit systems and the algorithms for inte,-rating in time are different. In addition the code for each application is likely to have been developed on different architectures and tend to have poor performance when run on an architecture for which the code was not designed, if it runs at all. Architectural differences may also induce differences in data representation which effect precision and convergence criteria as well as data transfer issues. In order to couple such dissimilar codes some form of translation must be present. This translation should be able to handle interpolation from one grid to another as well as construction of the correct data field in the correct units from available data. Even if a code is to be developed from scratch, a modular approach will likely be followed in that standard scientific packages will be used to do the more mundane tasks such as linear algebra or Fourier transform operations. This approach allows the developers to concentrate on their science rather than becoming experts in linear algebra or signal processing. Problems associated with this development approach include difficulties associated with data extraction and translation from one module to another, module performance on different nodal architectures, and others. In addition to these data and software issues there exists operational issues such as platform stability and resource management.

Dongarra, Jack↗

NASA NTRS2015

Future Changes in Major Stratospheric Warmings in CCMI Models

Major stratospheric warmings (MSWs) are one of the most important phenomena of wintertime Arctic stratospheric variability. They consist of a warming of the Arctic stratosphere and a deceleration of the polar night jet, triggered by an anomalously high injection of tropospheric wave activity into the stratosphere. Due to the relevance and the impact of MSWs on the tropospheric circulation, several model studies have investigated their potential responses to climate change. However, a wide range of results has been obtained, extending from a future increase in the frequency of MSWs to a decrease. These discrepancies might be explained by different factors such as a competition of radiative and dynamical contributors with opposite effects on the Arctic polar vortex, biases of models to reproduce the related processes, or the metric chosen for the identification of MSWs. In this study, future changes in wintertime Arctic stratospheric variability are examined in order to obtaina more precise picture of future changes in the occurrence of MSWs. In particular, transient REFC2 simulations of different CCMs involved in the Chemistry Climate Model Initiative (CCMI) are used. These simulations extend from 1960 to 2100 and include forcings by halogens and greenhouse gases following the specifications of the CCMI-REF-C2 scenario. Sea surface temperatures (SSTs) and sea-ice distributions are either prescribed from coupled climate model integrations or calculated internally in the case of fully coupled atmosphere-ocean CCMs. Potential changes in the frequency and main characteristics of MSWs in the future are investigated with special focus on the dependence of the results on the criterion for the identification of MSWs and the tropospheric forcing of these phenomena.

Chemistry-Climate Modeling↗

NASA NTRS1981

Weather and climate needs for lidar observations from space and concepts for their realization

The spectrum of weather and climate needs for lidar observations from space is discussed. This paper focuses mainly on the requirements for winds, temperature, moisture, and pressure. Special emphasis is given to the need for wind observations, and it is shown that winds are required to depict realistically all atmospheric scales in the tropics and the smaller scales at higher latitudes, where both temperature and wind profiles are necessary. The need for means to estimate air-sea exchanges of sensible and latent heat also is noted. Lidar can aid here by measurement of the slope of the boundary layer. Recent theoretical feasibility studies concerning the profiling of temperature, pressure, and humidity by differential absorption lidar (DIAL) from space and expected accuracies are reviewed. Initial ground-based trials provide support for these approaches and also indicate their direct applicability to path-average temperature measurements near the surface. An alternative approach to Doppler lidar wind measurements also is presented. The concept involves the measurement of the displacement of the aerosol backscatter pattern, at constant height, between two successive scans of the same area, one ahead of the spacecraft and the other behind it, a few minutes later. Finally, an integrated space lidar system capable of measuring temperature, pressure, humidity, and winds which combines the DIAL methods with the aerosol pattern displacement concept is described briefly.

Atlas, D.↗

NASA NTRS2002

Version 2 Goddard Satellite-Based Surface Turbulent Fluxes (GSSTF2)

Information on the turbulent fluxes of momentum, moisture, and heat at the air-sea interface is essential in improving model simulations of climate variations and in climate studies. We have derived a 13.5-year (July 1987-December 2000) dataset of daily surface turbulent fluxes over global oceans from the Special Sensor Mcrowave/Imager (SSM/I) radiance measurements. This dataset, version 2 Goddard Satellite-based Surface Turbulent Fluxes (GSSTF2), has a spatial resolution of 1 degree x 1 degree latitude-longitude and a temporal resolution of 1 day. Turbulent fluxes are derived from the SSM/I surface winds and surface air humidity, as well as the 2-m air and sea surface temperatures (SST) of the NCEP/NCAR reanalysis, using a bulk aerodynamic algorithm based on the surface layer similarity theory.

Chou, Shu-Hsien↗

NASA NTRS1999

Impact of TRMM and SSM/I-derived Precipitation and Moisture Data on the GEOS Global Analysis

Current global analyses contain significant errors in primary hydrological fields such as precipitation, evaporation, and related cloud and moisture in the tropics. The Data Assimilation Office at NASA's Goddard Space Flight Center has been exploring the use of space-based rainfall and total precipitable water (TPW) estimates to constrain these hydrological parameters in the Goddard Earth Observing System (GEOS) global data assimilation system. We present results showing that assimilating the 6-hour averaged rain rates and TPW estimates from the Tropical Rainfall Measuring Mission (TRMM) and Special Sensor Microwave/Imager (SSM/I) instruments improves not only the precipitation and moisture estimates but also reduce state-dependent systematic errors in key climate parameters directly linked to convection such as the outgoing longwave radiation, clouds, and the large-scale circulation. The improved analysis also improves short-range forecasts beyond 1 day, but the impact is relatively modest compared with improvements in the time-averaged analysis. The study shows that, in the presence of biases and other errors of the forecast model, improving the short-range forecast is not necessarily prerequisite for improving the assimilation as a climate data set. The full impact of a given type of observation on the assimilated data set should not be measured solely in terms of forecast skills.

Hou, Arthur Y.↗

NASA NTRS2015

Introduction The Role of the Agricultural Model Intercomparison and Improvement Project

Climate impacts on agriculture are of increasing concern in both the scientific and policy communities because of the need to ensure food security for a growing population. A special challenge is posed by the changes in the frequency and intensity of heat-waves, droughts, and episodic rainstorms already underway in many parts of the world. Changes in production are directly linked to such variations in temperature and precipitation during the growing season, and often to offseason changes in weather affecting soil-water storage and availability to crops. This is not an isolated problem but one of both global and regional importance, because of impacts on the livelihoods of smallholder farmers as well as consequences for the world food trade system. This two-part set the Agricultural Model Intercomparison and Improvement Project (AgMIP): Integrated Crop and Economic Assessments is the first to be entirely devoted to AgMIP (www.agmip.org). AgMIP is a major international research program focused on climate change and agriculture. The goal of the two parts is to advance the field by providing detailed information on new simulation techniques and assessments being conducted by this program. It presents information about new methods of global and regional integrated assessment, results from agricultural regions, and adaptation strategies for maintaining food security under changing climate conditions.

security↗

NASA NTRS1978

Early climate on earth-reduced gas models and early climate on Mars-reduced gas and obliquity models

At high obliquity, Martian polar ground temperatures could exceed the melting point of ice for considerable periods of time (approximately 90 Earth days). Under special conditions ice itself might melt. Carbon dioxide adsorbed on the Martian regolith is not expected to buffer the seasonal pressure wave except in the unlikely event that the soil pore size is very large (50 micron). For a basaltic soil composition the maximum CO2 that could be desorbed over obliquity time scales due to thermal forces is a few millibars. At low obliquities the atmospheric pressures may drop, desorbing the soil. The only means to achieve higher CO2 pressures is to have much higher planet-wide temperatures due to some greenhouse effect, or to be at an epoch before the regolith or carbonates formed. The water ice budget between north and south polar caps was considered and summer sublimation rates imply that the ice could be exchanged between the poles during obliquity cycles. A critical factor in the polar cap water budget is the interaction of water and dust. The origin of the Martian polar laminae is probably due to variations in this interaction.

Toon, O. B.↗

NASA NTRS2011

Investigation of Seasonal Landscape Freeze/Thaw Cycles in Relation to Cloud Structure in the High Northern Latitudes

The seasonal freezing and thawing of Earth's cryosphere (the portion of Earth's surface permanently or seasonally frozen) has an immense impact on Earth's climate as well as on its water, carbon and energy cycles. During the spring, snowmelt and the transition between frozen and non-frozen states lowers Earth's surface albedo. This change in albedo causes more solar radiation to be absorbed by the land surface, raising surface soil and air temperatures as much as 5 C within a few days. The transition of ice into liquid water not only raises the surface humidity, but also greatly affects the energy exchange between the land surface and the atmosphere as the phase change creates a latent energy dominated system. There is strong evidence to suggest that the thawing of the cryosphere during spring and refreezing during autumn is correlated to local atmospheric conditions such as cloud structure and frequency. Understanding the influence of land surface freeze/thaw cycles on atmospheric structure can help improve our understanding of links between seasonal land surface state and weather and climate, providing insight into associated changes in Earth's water, carbon, and energy cycles that are driven by climate change.Information on both the freeze/thaw states of Earth's land surface and cloud characteristics is derived from data sets collected by NOAA's Special Sensor Microwave/Imager (SSM/I), the Advanced Microwave Scanning Radiometer on NASA's Earth Observing System(AMSR-E), NASA's CloudSat, and NASA's SeaWinds-on-QuickSCAT Earth remote sensing satellite instruments. These instruments take advantage of the microwave spectrum to collect an ensemble of atmospheric and land surface data. Our analysis uses data from radars (active instruments which transmit a microwave signal toward Earth and measure the resultant backscatter) and radiometers (passive devices which measure Earth's natural microwave emission) to accurately characterize salient details on Earth's surface and atmospheric states. By comparing the cloud measurements and the surface freeze-thaw data sets, a correlation between the two phenomena can be developed.

clouds↗

NASA NTRS2016

The Impact of ARM on Climate Modeling

Climate models are among humanity's most ambitious and elaborate creations. They are designed to simulate the interactions of the atmosphere, ocean, land surface, and cryosphere on time scales far beyond the limits of deterministic predictability, and including the effects of time-dependent external forcings. The processes involved include radiative transfer, fluid dynamics, microphysics, and some aspects of geochemistry, biology, and ecology. The models explicitly simulate processes on spatial scales ranging from the circumference of the Earth down to one hundred kilometers or smaller, and implicitly include the effects of processes on even smaller scales down to a micron or so. The atmospheric component of a climate model can be called an atmospheric global circulation model (AGCM). In an AGCM, calculations are done on a three-dimensional grid, which in some of today's climate models consists of several million grid cells. For each grid cell, about a dozen variables are time-stepped as the model integrates forward from its initial conditions. These so-called prognostic variables have special importance because they are the only things that a model remembers from one time step to the next; everything else is recreated on each time step by starting from the prognostic variables and the boundary conditions. The prognostic variables typically include information about the mass of dry air, the temperature, the wind components, water vapor, various condensed-water species, and at least a few chemical species such as ozone. A good way to understand how climate models work is to consider the lengthy and complex process used to develop one. Lets imagine that a new AGCM is to be created, starting from a blank piece of paper. The model may be intended for a particular class of applications, e.g., high-resolution simulations on time scales of a few decades. Before a single line of code is written, the conceptual foundation of the model must be designed through a creative envisioning that starts from the intended application and is based on current understanding of how the atmosphere works and the inventory of mathematical methods available.

atmospheric circulation↗

NASA NTRS2014

MERRA Analytic Services: Meeting the Big Data Challenges of Climate Science Through Cloud-enabled Climate Analytics-as-a-service

Climate science is a Big Data domain that is experiencing unprecedented growth. In our efforts to address the Big Data challenges of climate science, we are moving toward a notion of Climate Analytics-as-a-Service (CAaaS). We focus on analytics, because it is the knowledge gained from our interactions with Big Data that ultimately produce societal benefits. We focus on CAaaS because we believe it provides a useful way of thinking about the problem: a specialization of the concept of business process-as-a-service, which is an evolving extension of IaaS, PaaS, and SaaS enabled by Cloud Computing. Within this framework, Cloud Computing plays an important role; however, we it see it as only one element in a constellation of capabilities that are essential to delivering climate analytics as a service. These elements are essential because in the aggregate they lead to generativity, a capacity for self-assembly that we feel is the key to solving many of the Big Data challenges in this domain. MERRA Analytic Services (MERRAAS) is an example of cloud-enabled CAaaS built on this principle. MERRAAS enables MapReduce analytics over NASAs Modern-Era Retrospective Analysis for Research and Applications (MERRA) data collection. The MERRA reanalysis integrates observational data with numerical models to produce a global temporally and spatially consistent synthesis of 26 key climate variables. It represents a type of data product that is of growing importance to scientists doing climate change research and a wide range of decision support applications. MERRAAS brings together the following generative elements in a full, end-to-end demonstration of CAaaS capabilities: (1) high-performance, data proximal analytics, (2) scalable data management, (3) software appliance virtualization, (4) adaptive analytics, and (5) a domain-harmonized API. The effectiveness of MERRAAS has been demonstrated in several applications. In our experience, Cloud Computing lowers the barriers and risk to organizational change, fosters innovation and experimentation, facilitates technology transfer, and provides the agility required to meet our customers' increasing and changing needs. Cloud Computing is providing a new tier in the data services stack that helps connect earthbound, enterprise-level data and computational resources to new customers and new mobility-driven applications and modes of work. For climate science, Cloud Computing's capacity to engage communities in the construction of new capabilies is perhaps the most important link between Cloud Computing and Big Data.

Data Analytics↗

NASA NTRS1993

New parameterizations and sensitivities for simple climate models

This paper presents a reexamination of the earth radiation budget parameterization of energy balance climate models in light of data collected over the last 12 years. The study consists of three parts: (1) an examination of the infrared terrestrial radiation to space and its relationship to the surface temperature field on time scales from 1 month to 10 years; (2) an examination of the albedo of the earth with special attention to the seasonal cycle of snow and clouds; (3) solutions for the seasonal cycle using the new parameterizations with special attention to changes in sensitivity. While the infrared parameterization is not dramatically different from that used in the past, the albedo in the new data suggest that a stronger latitude dependence be employed. After retuning the diffusion coefficient the simulation results for the present climate generally show only a slight dependence on the new parameters. Also, the sensitivity parameter for the model is still about the same (1.25 C for a 1 percent increase of solar constant) for the linear models and for the nonlinear models that include a seasonal snow line albedo feedback (1.34 C). One interesting feature is that a clear-sky planet with a snow line albedo feedback has a significantly higher sensitivity (2.57 C) due to the absence of smoothing normally occurring in the presence of average cloud cover.

Graves, Charles E.↗

NASA NTRS1984

The Corfu Landslide: Analog to Giant Landslides on Mars

In an analog to the great landslides of the Vales Marineris, Mars, a detailed study was made of the Corfu Landslide in south-central Washington. This prehistoric slide is located on the northern flank of the Saddle Mountains, southwest of Othello, Washington. The slide covers a 13 square km area centered on section 11 of T.15N., R.27E., Willamette Meridian, adjacent to the Corfu townsite. Approximately 1 cubic km of material is involved in sliding that was probably initiated by Missoula flooding through the Channeled Scabland. It is concluded that there were four primary factors involved in the initiation of the Corfu landsliding: (1) A slip surface was present at the right orientation; (2) Glacial flooding undercut the slope; (3) Wetter climatic conditions prevailed during that time period; and (4) Some seismic vibrations, known to occur locally, probably acted as a trigger. These factors show that special conditions were required in conjunction to produce landsliding. Studies in progress of the Vales Marieneris suggest that the same factors probably contributed to landsliding there.

Scott W. Lewis↗