SEARCH · Engineering Papers

Results for “droughts”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,711 records · Page 95

All sources NASA NTRS DOE OSTI

NASA NTRS2014

Assimilation of SMOS Soil Moisture Retrievals in the Land Information System

Soil moisture is a crucial variable for weather prediction because of its influence on evaporation. It is of critical importance for drought and flood monitoring and prediction and for public health applications. The NASA Short-term Prediction Research and Transition Center (SPoRT) has implemented a new module in the NASA Land Information System (LIS) to assimilate observations from the ESA's Soil Moisture and Ocean Salinity (SMOS) satellite. SMOS Level 2 retrievals from the Microwave Imaging Radiometer using Aperture Synthesis (MIRAS) instrument are assimilated into the Noah LSM within LIS via an Ensemble Kalman Filter. The retrievals have a target volumetric accuracy of 4% at a resolution of 35-50 km. Parallel runs with and without SMOS assimilation are performed with precipitation forcing from intentionally degraded observations, and then validated against a model run using the best available precipitation data, as well as against selected station observations. The goal is to demonstrate how SMOS data assimilation can improve modeled soil states in the absence of dense rain gauge and radar networks.

Blakenship, Clay↗

NASA NTRS2012

Interpretation of Variations in Modis-Measured Greenness Levels of Amazon Forests During 2000 to 2009

This work investigates variations in satellite-measured greenness of Amazon forests using ten years of NASA Moderate Resolution Imaging Spectroradiometer (MODIS) enhanced vegetation index (EVI) data. Corruption of optical remote sensing data with clouds and aerosols is prevalent in this region; filtering corrupted data causes spatial sampling constraints, as well as reducing the record length, which introduces large biases in estimates of greenness anomalies. The EVI data, analyzed in multiple ways and taking into account EVI accuracy, consistently show a pattern of negligible changes in the greenness levels of forests both in the area affected by drought in 2005 and outside it. Small random patches of anomalous greening and browning-especially prominent in 2009-appear in all ten years, irrespective of contemporaneous variations in precipitation, but with no persistence over time. The fact that over 90% of the EVI anomalies are insignificantly small-within the envelope of error (95% confidence interval) in EVI-warrants cautious interpretation of these results: there were no changes in the greenness of these forests, or if there were changes, the EVI data failed to capture these either because the constituent reflectances were saturated or the moderate resolution precluded viewing small-scale variations. This suggests a need for more accurate and spatially resolved synoptic views from satellite data and corroborating comprehensive ground sampling to understand the greenness dynamics of these forests.

MODIS↗

NASA NTRS2014

Recent Weather Extremes and Impacts on Agricultural Production and Vector-Borne Disease Outbreak Patterns

We document significant worldwide weather anomalies that affected agriculture and vector-borne disease outbreaks during the 2010-2012 period. We utilized 2000-2012 vegetation index and land surface temperature data from NASA's satellite-based Moderate Resolution Imaging Spectroradiometer (MODIS) to map the magnitude and extent of these anomalies for diverse regions including the continental United States, Russia, East Africa, Southern Africa, and Australia. We demonstrate that shifts in temperature and/or precipitation have significant impacts on vegetation patterns with attendant consequences for agriculture and public health. Weather extremes resulted in excessive rainfall and flooding as well as severe drought, which caused,10 to 80% variation in major agricultural commodity production (including wheat, corn, cotton, sorghum) and created exceptional conditions for extensive mosquito-borne disease outbreaks of dengue, Rift Valley fever, Murray Valley encephalitis, and West Nile virus disease. Analysis of MODIS data provided a standardized method for quantifying the extreme weather anomalies observed during this period. Assessments of land surface conditions from satellite-based systems such as MODIS can be a valuable tool in national, regional, and global weather impact determinations.

Weather↗

NASA NTRS2012

Evaluating the Use of Remote Sensing Data in the U.S. Agency for International Development Famine Early Warning Systems Network

The U.S. Agency for International Development (USAID)'s Famine Early Warning System Network (FEWS NET) provides monitoring and early warning support to decision makers responsible for responding to food insecurity emergencies on three continents. FEWS NET uses satellite remote sensing and ground observations of rainfall and vegetation in order to provide information on drought, floods, and other extreme weather events to decision makers. Previous research has presented results from a professional review questionnaire with FEWS NET expert end-users whose focus was to elicit Earth observation requirements. The review provided FEWS NET operational requirements and assessed the usefulness of additional remote sensing data. We analyzed 1342 food security update reports from FEWS NET. The reports consider the biophysical, socioeconomic, and contextual influences on the food security in 17 countries in Africa from 2000 to 2009. The objective was to evaluate the use of remote sensing information in comparison with other important factors in the evaluation of food security crises. The results show that all 17 countries use rainfall information, agricultural production statistics, food prices, and food access parameters in their analysis of food security problems. The reports display large-scale patterns that are strongly related to history of the FEWS NET program in each country. We found that rainfall data were used 84% of the time, remote sensing of vegetation 28% of the time, and gridded crop models 10% of the time, reflecting the length of use of each product in the regions. More investment is needed in training personnel on remote sensing products to improve use of data products throughout the FEWS NET system.

USAID↗

NASA NTRS2013

State of the Art in Large-Scale Soil Moisture Monitoring

Soil moisture is an essential climate variable influencing land atmosphere interactions, an essential hydrologic variable impacting rainfall runoff processes, an essential ecological variable regulating net ecosystem exchange, and an essential agricultural variable constraining food security. Large-scale soil moisture monitoring has advanced in recent years creating opportunities to transform scientific understanding of soil moisture and related processes. These advances are being driven by researchers from a broad range of disciplines, but this complicates collaboration and communication. For some applications, the science required to utilize large-scale soil moisture data is poorly developed. In this review, we describe the state of the art in large-scale soil moisture monitoring and identify some critical needs for research to optimize the use of increasingly available soil moisture data. We review representative examples of 1) emerging in situ and proximal sensing techniques, 2) dedicated soil moisture remote sensing missions, 3) soil moisture monitoring networks, and 4) applications of large-scale soil moisture measurements. Significant near-term progress seems possible in the use of large-scale soil moisture data for drought monitoring. Assimilation of soil moisture data for meteorological or hydrologic forecasting also shows promise, but significant challenges related to model structures and model errors remain. Little progress has been made yet in the use of large-scale soil moisture observations within the context of ecological or agricultural modeling. Opportunities abound to advance the science and practice of large-scale soil moisture monitoring for the sake of improved Earth system monitoring, modeling, and forecasting.

Review↗

NASA NTRS2013

NASAs Soil Moisture Active Passive (SMAP) Mission and Opportunities For Applications Users

Water in the soil, both its amount (soil moisture) and its state (freeze/thaw), plays a key role in water and energy cycles, in weather and climate, and in the carbon cycle. Additionally, soil moisture touches upon human lives in a number of ways from the ravages of flooding to the needs for monitoring agricultural and hydrologic droughts. Because of their relevance to weather, climate, science, and society, accurate and timely measurements of soil moisture and freeze/thaw state with global coverage are critically important.

Mission↗

NASA NTRS2013

El Nino and Health Risks from Landscape Fire Emissions in Southeast Asia

Emissions from landscape fires affect both climate and air quality. Here, we combine satellite-derived fire estimates and atmospheric modelling to quantify health effects from fire emissions in southeast Asia from 1997 to 2006. This region has large interannual variability in fire activity owing to coupling between El Nino-induced droughts and anthropogenic land-use change. We show that during strong El Nino years, fires contribute up to 200 micrograms per cubic meter and 50 ppb in annual average fine particulate matter (PM2.5) and ozone surface concentrations near fire sources, respectively. This corresponds to a fire contribution of 200 additional days per year that exceed the World Health Organization 50 micrograms per cubic metre 24-hr PM(sub 2.5) interim target and an estimated 10,800 (6,800-14,300)-person (approximately 2 percent) annual increase in regional adult cardiovascular mortality. Our results indicate that reducing regional deforestation and degradation fires would improve public health along with widely established benefits from reducing carbon emissions, preserving biodiversity and maintaining ecosystem services.

fires↗

NASA NTRS2014

Assimilation of SMOS Retrieved Soil Moisture into the Land Information System

Soil moisture is a crucial variable for weather prediction because of its influence on evaporation and surface heat fluxes. It is also of critical importance for drought and flood monitoring and prediction and for public health applications such as monitoring vector-borne diseases. Land surface modeling benefits greatly from regular updates with soil moisture observations via data assimilation. Satellite remote sensing is the only practical observation type for this purpose in most areas due to its worldwide coverage. The newest operational satellite sensor for soil moisture is the Microwave Imaging Radiometer using Aperture Synthesis (MIRAS) instrument aboard the Soil Moisture and Ocean Salinity (SMOS) satellite. The NASA Short-term Prediction Research and Transition Center (SPoRT) has implemented the assimilation of SMOS soil moisture observations into the NASA Land Information System (LIS), an integrated modeling and data assimilation software platform. We present results from assimilating SMOS observations into the Noah 3.2 land surface model within LIS. The SMOS MIRAS is an L-band radiometer launched by the European Space Agency in 2009, from which we assimilate Level 2 retrievals [1] into LIS-Noah. The measurements are sensitive to soil moisture concentration in roughly the top 2.5 cm of soil. The retrievals have a target volumetric accuracy of 4% at a resolution of 35-50 km. Sensitivity is reduced where precipitation, snowcover, frozen soil, or dense vegetation is present. Due to the satellite's polar orbit, the instrument achieves global coverage twice daily at most mid- and low-latitude locations, with only small gaps between swaths.

Blankenship, Clay B.↗

NASA NTRS2013

Estimating Global Precipitation for Science and Application

Over the past two decades there has been vigorous development in the satellite assets and the algorithms necessary to estimate precipitation around the globe. In particular the highly successful joint NASAJAXA Tropical Rainfall Measuring Mission (TRMM) and the upcoming Global Precipitation Measurement (GPM) mission, also joint between NASA and JAXA, have driven these issues. At the same time, the long-running Global Precipitation Climatology Project (GPCP) continues to extend a stable, climate-oriented view of global precipitation. This talk will provide an overview of these projects and the wider international community of precipitation datasets, sketch plans for next-generation products, and provide some examples of the best use for the different products. One key lesson learned is that different data sets are needed to address the variety of issues that need precipitation data, including detailed 3-D views of hurricanes, flash flood forecasting, drought analysis, and global change.

global precipitation↗

NASA NTRS2012

Fire-induced Carbon Emissions and Regrowth Uptake in Western U.S. Forests: Documenting Variation Across Forest Types, Fire Severity, and Climate Regions

The forest area in the western United States that burns annually is increasing with warmer temperatures, more frequent droughts, and higher fuel densities. Studies that examine fire effects for regional carbon balances have tended to either focus on individual fires as examples or adopt generalizations without considering how forest type, fire severity, and regional climate influence carbon legacies. This study provides a more detailed characterization of fire effects and quantifies the full carbon impacts in relation to direct emissions, slow release of fire-killed biomass, and net carbon uptake from forest regrowth. We find important variations in fire-induced mortality and combustion across carbon pools (leaf, live wood, dead wood, litter, and duff) and across low- to high-severity classes. This corresponds to fire-induced direct emissions from 1984 to 2008 averaging 4 TgC/yr and biomass killed averaging 10.5 TgC/yr, with average burn area of 2723 sq km/yr across the western United States. These direct emission and biomass killed rates were 1.4 and 3.7 times higher, respectively, for high-severity fires than those for low-severity fires. The results show that forest regrowth varies greatly by forest type and with severity and that these factors impose a sustained carbon uptake legacy. The western U.S. fires between 1984 and 2008 imposed a net source of 12.3 TgC/yr in 2008, accounting for both direct fire emissions (9.5 TgC/yr) and heterotrophic decomposition of fire-killed biomass (6.1 TgC yr1) as well as contemporary regrowth sinks (3.3 TgC/yr). A sizeable trend exists toward increasing emissions as a larger area burns annually.

Forest↗

NASA NTRS2013

Surface Freshwater Storage and Variability in the Amazon Basin from Multi-Satellite Observations, 1993-2007

The amount of water stored and moving through the surface water bodies of large river basins (river, floodplains, wetlands) plays a major role in the global water and biochemical cycles and is a critical parameter for water resources management. However, the spatio-temporal variations of these freshwater reservoirs are still widely unknown at the global scale. Here, we propose a hypsographic curve approach to estimate surface freshwater storage variations over the Amazon basin combining surface water extent from a multi-satellite-technique with topographic data from the Global Digital Elevation Model (GDEM) from Advance Spaceborne Thermal Emission and Reflection Radiometer (ASTER). Monthly surface water storage variations for 1993-2007 are presented, showing a strong seasonal and interannual variability, and are evaluated against in situ river discharge and precipitation. The basin-scale mean annual amplitude of approx. 1200 cu km is in the range of previous estimates and contributes to about half of the Gravity Recovery And Climate Experiment (GRACE) total water storage variations. For the first time, we map the surface water volume anomaly during the extreme droughts of 1997 (October-November) and 2005 (September-October) and found that during these dry events the water stored in the river and flood-plains of the Amazon basin was, respectively, approx. 230 (approx. 40%) and 210 (approx. 50%) cu km below the 1993-2007 average. This new 15year data set of surface water volume represents an unprecedented source of information for future hydrological or climate modeling of the Amazon. It is also a first step toward the development of such database at the global scale.

Storage↗

NASA NTRS2014

Amazon Forests Maintain Consistent Canopy Structure and Greenness During the Dry Season

The seasonality of sunlight and rainfall regulates net primary production in tropical forests. Previous studies have suggested that light is more limiting than water for tropical forest productivity, consistent with greening of Amazon forests during the dry season in satellite data.We evaluated four potential mechanisms for the seasonal green-up phenomenon, including increases in leaf area or leaf reflectance, using a sophisticated radiative transfer model and independent satellite observations from lidar and optical sensors. Here we show that the apparent green up of Amazon forests in optical remote sensing data resulted from seasonal changes in near-infrared reflectance, an artefact of variations in sun-sensor geometry. Correcting this bidirectional reflectance effect eliminated seasonal changes in surface reflectance, consistent with independent lidar observations and model simulations with unchanging canopy properties. The stability of Amazon forest structure and reflectance over seasonal timescales challenges the paradigm of light-limited net primary production in Amazon forests and enhanced forest growth during drought conditions. Correcting optical remote sensing data for artefacts of sun-sensor geometry is essential to isolate the response of global vegetation to seasonal and interannual climate variability.

dry season↗

NASA NTRS2011

Snow Cover, Snowmelt Timing and Stream Power in the Wind River Range, Wyoming

Earlier onset of springtime weather, including earlier snowmelt, has been documented in the western United States over at least the last 50 years. Because the majority (is greater than 70%) of the water supply in the western U.S. comes from snowmelt, analysis of the declining spring snowpack (and shrinking glaciers) has important implications for the management of streamflow. The amount of water in a snowpack influences stream discharge which can also influence erosion and sediment transport by changing stream power, or the rate at which a stream can do work, such as move sediment and erode the stream bed. The focus of this work is the Wind River Range (WRR) in west-central Wyoming. Ten years of Moderate-Resolution Imaging Spectroradiometer (MODIS) snow-cover, cloud-gap-filled (CGF) map products and 30 years of discharge and meteorological station data are studied. Streamflow data from streams in WRR drainage basins show lower annual discharge and earlier snowmelt in the decade of the 2000s than in the previous three decades, though no trend of either lower streamflow or earlier snowmelt was observed within the decade of the 2000s. Results show a statistically-significant trend at the 95% confidence level (or higher) of increasing weekly maximum air temperature (for three out of the five meteorological stations studied) in the decade of the 1970s, and also for the 40-year study period as a whole. The extent of snow-cover (percent of basin covered) derived from the lowest elevation zone (2500-3000 m) of the WRR, using MODIS CGF snow-cover maps, is strongly correlated with maximum monthly discharge on 30 April, where Spearman's Rank correlation, rs,=0.89 for the decade of the 2000s. We also investigated stream power for Bull Lake Creek above Bull Lake; and found a trend (significant at the 90% confidence level) toward reduced stream power from 1970 to 2009. Observed changes in streamflow and stream power may be related to increasing weekly maximum air temperature measured during the 40-year study period, possibly contributing to a reduction in snow cover. In addition, the strong relationship between percent of basin that was snow covered, and maximum monthly streamflow indicates that MODIS snow-cover maps are useful for predicting streamflow, and can be used to improve management of water resources in the drought-prone western United States.

MODIS↗

NASA NTRS2014

Application of Suomi-NPP Green Vegetation Fraction and NUCAPS for Improving Regional Numerical Weather Prediction

The NASA SPoRT Center is working to incorporate Suomi‐NPP products into its research and transition activities to improve regional numerical weather prediction (NWP). Specifically, SPoRT seeks to utilize two data products from NOAA/NESDIS: (1) daily global VIIRS green vegetation fraction (GVF), and (2) NOAA Unique CrIS and ATMS Processing System (NUCAPS) temperature and moisture retrieved profiles. The goal of (1) is to improve the representation of vegetation in the Noah land surface model (LSM) over existing climatological GVF datasets in order to improve the land‐atmosphere energy exchanges in NWP models and produce better temperature, moisture, and precipitation forecasts. The goal of (2) is to assimilate NUCAPS retrieved profiles into the Gridpoint Statistical Interpolation (GSI) data assimilation system to assess the impact on a summer pre‐frontal convection case. Most regional NWP applications make use of a monthly GVF climatology for use in the Noah LSM within the Weather Research and Forecasting (WRF) model. The GVF partitions incoming energy into direct surface heating/evaporation over bare soil versus evapotranspiration processes over vegetated surfaces. Misrepresentations of the fractional coverage of vegetation during anomalous weather/climate regimes (e.g., early/late bloom or freeze; drought) can lead to poor NWP model results when land‐atmosphere feedback is important. SPoRT has been producing a daily MODIS GVF product based on the University of Wisconsin Direct Broadcast swaths of Normalized Difference Vegetation Index (NDVI). While positive impacts have been demonstrated in the WRF model for some cases, the reflectances composing these NDVI do not correct for atmospheric aerosols nor satellite view angle, resulting in temporal noisiness at certain locations (especially heavy vegetation). The method behind the NESDIS VIIRS GVF is expected to alleviate the issues seen in the MODIS GVF real‐time product, thereby offering a higher‐quality dataset for modeling applications. SPoRT is evaluating the VIIRS GVF data against the MODIS real‐time and climatology GVF in both WRF and the NASA Land Information System. SPoRT has a history of assimilating hyperspectral infrared retrieved profiles

Numerical Weather Prediction↗

NASA NTRS2015

Spinoff 2015

Topics covered include: 3D Endoscope to Boost Safety, Cut Cost of Surgery; Audio App Brings a Better Night's Sleep Liquid Cooling Technology Increases Exercise Efficiency; Algae-Derived Dietary Ingredients Nourish Animals; Space Grant Research Launches Rehabilitation Chair; Vision Trainer Teaches Focusing Techniques at Home; Aircraft Geared Architecture Reduces Fuel Cost and Noise; Ubiquitous Supercritical Wing Design Cuts Billions in Fuel Costs; Flight Controller Software Protects Lightweight Flexible Aircraft; Cabin Pressure Monitors Notify Pilots to Save Lives; Ionospheric Mapping Software Ensures Accuracy of Pilots' GPS; Water Mapping Technology Rebuilds Lives in Arid Regions; Shock Absorbers Save Structures and Lives during Earthquakes; Software Facilitates Sharing of Water Quality Data Worldwide; Underwater Adhesives Retrofit Pipelines with Advanced Sensors; Laser Imaging Video Camera Sees through Fire, Fog, Smoke; 3D Lasers Increase Efficiency, Safety of Moving Machines; Air Revitalization System Enables Excursions to the Stratosphere; Magnetic Fluids Deliver Better Speaker Sound Quality; Bioreactor Yields Extracts for Skin Cream; Private Astronaut Training Prepares Commercial Crews of Tomorrow; Activity Monitors Help Users Get Optimum Sun Exposure; LEDs Illuminate Bulbs for Better Sleep, Wake Cycles; Charged Particles Kill Pathogens and Round Up Dust; Balance Devices Train Golfers for a Consistent Swing; Landsat Imagery Enables Global Studies of Surface Trends; Ruggedized Spectrometers Are Built for Tough Jobs; Gas Conversion Systems Reclaim Fuel for Industry; Remote Sensing Technologies Mitigate Drought; Satellite Data Inform Forecasts of Crop Growth; Probes Measure Gases for Environmental Research; Cloud Computing Technologies Facilitate Earth Research; Software Cuts Homebuilding Costs, Increases Energy Efficiency; Portable Planetariums Teach Science; Schedule Analysis Software Saves Time for Project Planners; Sound Modeling Simplifies Vehicle Noise Management; Custom 3D Printers Revolutionize Space Supply Chain; Improved Calibration Shows Images' True Colors; Micromachined Parts Advance Medicine, Astrophysics, and More; Metalworking Techniques Unlock a Unique Alloy; Low-Cost Sensors Deliver Nanometer-Accurate Measurements; Electrical Monitoring Devices Save on Time and Cost; Dry Lubricant Smooths the Way for Space Travel, Industry; and Compact Vapor Chamber Cools Critical Components.

Source record↗

NASA NTRS2015

Water Mapping Technology Rebuilds Lives in Arid Regions

Using NASA Landsat satellite and other remote sensing topographical data, Radar Technologies International developed an algorithm-based software program that can locate underground water sources. Working with international organizations and governments, the firm, which maintains an office in New Braunfels, Texas, is helping to provide water for refugees and other people in drought-stricken regions such as Kenya, Sudan, and Afghanistan.

Source record↗

NASA NTRS2014

In-Orbit Performance of the MWRI Scanning Mechanisms

Scanning Equipment supporting the Millimeter Wave Radiometer Instrument (MWRI) are flying in a sunsynchronized orbit of 850-km altitude with an inclination of 98.8 deg on the FY-3 meteorological satellite (FY = Feng Yun, Wind and Cloud). MWRI is a linearly polarized, ten-channel passive Radiometer; it measures precipitation and water clouds, sea ice, snow/water equivalent, drought and flood index, land temperature and soil moisture. Following the FY3-A, the FY3-B Satellite was launched in autumn 2010. Since that time, the Scanning Equipment was continuously operated. During the last three and a half years in orbit, the Scanning Mechanism has executed about 65 million revolutions, while the Scan Compensation Mechanism (SCM) - used for momentum compensation - has already successfully executed more than one billion revolutions. During the commissioning phase of the instrument and during the first operation phase, random torque spikes, which manifested themselves as a motor current increase, were observed in the Scan Drive Mechanism, whereas the Scan Compensation drive operated nominally from the beginning. The result of the root cause investigations performed in order to isolate the issue, and the consequences for the follow-on MWRI equipment which was successfully launched by end of September 2013 (now flying on the FY 3-C Spacecraft), are discussed.

Schmid, Manfred↗

NASA NTRS2011

Utilization of Ancillary Data Sets for Conceptual SMAP Mission Algorithm Development and Product Generation

The planned Soil Moisture Active Passive (SMAP) mission is one of the first Earth observation satellites being developed by NASA in response to the National Research Council's Decadal Survey, Earth Science and Applications from Space: National Imperatives for the Next Decade and Beyond [1]. Scheduled to launch late in 2014, the proposed SMAP mission would provide high resolution and frequent revisit global mapping of soil moisture and freeze/thaw state, utilizing enhanced Radio Frequency Interference (RFI) mitigation approaches to collect new measurements of the hydrological condition of the Earth's surface. The SMAP instrument design incorporates an L-band radar (3 km) and an L band radiometer (40 km) sharing a single 6-meter rotating mesh antenna to provide measurements of soil moisture and landscape freeze/thaw state [2]. These observations would (1) improve our understanding of linkages between the Earth's water, energy, and carbon cycles, (2) benefit many application areas including numerical weather and climate prediction, flood and drought monitoring, agricultural productivity, human health, and national security, (3) help to address priority questions on climate change, and (4) potentially provide continuity with brightness temperature and soil moisture measurements from ESA's SMOS (Soil Moisture Ocean Salinity) and NASA's Aquarius missions. In the planned SMAP mission prelaunch time frame, baseline algorithms are being developed for generating (1) soil moisture products both from radiometer measurements on a 36 km grid and from combined radar/radiometer measurements on a 9 km grid, and (2) freeze/thaw products from radar measurements on a 3 km grid. These retrieval algorithms need a variety of global ancillary data, both static and dynamic, to run the retrieval models, constrain the retrievals, and provide flags for indicating retrieval quality. The choice of which ancillary dataset to use for a particular SMAP product would be based on a number of factors, including its availability and ease of use, its inherent error and resulting impact on the overall soil moisture or freeze/thaw retrieval accuracy, and its compatibility with similar choices made by the SMOS mission. All decisions regarding SMAP ancillary data sources would be fully documented by the SMAP Project and made available to the user community.

freeze/thaw↗