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NASA NTRS1997

An Ecosystem Simulation Model for Methane Production and Emission from Wetlands

Previous experimental studies suggest that methane emission from wetland is influenced by multiple interactive pathways of gas production and transport through soil and sediment layers to the atmosphere. The objective of this study is to evaluate a new simulation model of methane production and emission in wetland soils that was developed initially to help identify key processes that regulate methanogenesis and net flux of CH4 to the air, but which is designed ultimately for regional simulation using remotely sensed inputs for land cover characteristics. The foundation for these computer simulations is based on a well-documented model (CASA) of ecosystem production and carbon cycling in the terrestrial blaspheme. Modifications to represent flooded wetland soils and anaerobic decomposition include three new sub-models for: (1) layered soil temperature and water table depth (WTD) as a function of daily climate drivers, (2) CH4 production within the anoxic soil layer as a function of WTD and CO2 production under poorly drained conditions, and (3) CH4 gaseous transport pathways (molecular diffusion, ebullition, and plant vascular transport) as a function of WTD and ecosystem type. The model was applied and tested using climate and ecological data to characterize tundra wetland sites near Fairbanks, Alaska studied previously by Whalen and Reeburgh. Comparison of model predictions to measurements of soil temperature and thaw depth, water-table depth, and CH4 emissions over a two year period suggest that inter-site differences in soil physical conditions and methane fluxes could be reproduced accurately for selected periods. Day-to-day comparison of predicted emissions to measured CH4 flux rates reveals good agreement during the early part of the thaw season, but the model tends to underestimate production of CH4 during the months of July and August in both test years. Important seasonal effects, including that of falling WTD during these periods, are apparently overlooked in the model formulation. Nevertheless, reasonably close agreement was achieved between the model's mean daily and seasonal estimates of CH4 flux and observed emission rates for northern wetland ecosystems. Several features of the model are identified as crucial to more accurate prediction of wetland methane emission, including the capacity to incorporate influences of localized topographic and hydrologic features on site-specific soil temperature and WTD dynamics, and mechanistic simulation of methane emission transport pathways from within the soil profile.

Potter, C. S.↗

NASA NTRS2023

Northeast Alaska Climate: Using Earth Observations to Evaluate Snow Variability through a Climatological Analysis to Support Ecological Monitoring in Northeast Alaska

Alaska is experiencing climate change at an unprecedented rate, with temperatures increasing twice as fast as the national average. The resulting changes to the landscape and ecosystems are significant, including shorter winters, declining snow depth, thawing permafrost, and rapidly receding glaciers. These changes are not only exacerbating the negative impacts of oil exploration but also affecting the food security of indigenous communities that rely on hunting as a subsistence food source. With the US Fish and Wildlife Service managing a potential tundra travel season for the first time in its history, adequate data on historic snow variables is essential to protect the unique habitat of the area. This project used NASA satellite and assimilation system data to inform and improve the current understanding of snow patterns in the Arctic National Wildlife Refuge and the National Petroleum Reserve – Alaska. The DEVELOP team used MODIS Normalized Difference Snow Index data to determine snow season duration, snow change frequency, and the first and last days of snow. The team also utilized the 2.1 Global Land Data Assimilation System and Daymet V4 products to study climatological trends in snow depth and snow water equivalent, respectively, across the study areas. The results of this study give users the capacity to visualize maps of multiple snow variables to monitor changes in snow conditions and proactively prepare for the ecological, cultural, and landscape impacts that changes in snow variability will cause in the future.

Remote Sensing↗

NASA NTRS1999

A Process-based, Climate-Sensitive Model to Derive Methane Emissions from Natural Wetlands: Application to 5 Wetland Sites, Sensitivity to Model Parameters and Climate

Methane emissions from natural wetlands constitutes the largest methane source at present and depends highly on the climate. In order to investigate the response of methane emissions from natural wetlands to climate variations, a 1-dimensional process-based climate-sensitive model to derive methane emissions from natural wetlands is developed. In the model the processes leading to methane emission are simulated within a 1-dimensional soil column and the three different transport mechanisms diffusion, plant-mediated transport and ebullition are modeled explicitly. The model forcing consists of daily values of soil temperature, water table and Net Primary Productivity, and at permafrost sites the thaw depth is included. The methane model is tested using observational data obtained at 5 wetland sites located in North America, Europe and Central America, representing a large variety of environmental conditions. It can be shown that in most cases seasonal variations in methane emissions can be explained by the combined effect of changes in soil temperature and the position of the water table. Our results also show that a process-based approach is needed, because there is no simple relationship between these controlling factors and methane emissions that applies to a variety of wetland sites. The sensitivity of the model to the choice of key model parameters is tested and further sensitivity tests are performed to demonstrate how methane emissions from wetlands respond to climate variations.

Walter, Bernadette P.↗

NASA NTRS2011

Wildfires in Northern Siberian Larch Dominated Communities

The fire history of the northern larch forests within the permafrost zone in a portion of northern Siberia (approx 66 deg N, 100 deg E) was studied. Since there is little to no human activities in this area fires within the study area were mostly caused by lightning. Fire return intervals (FRI) were estimated based on burn marks on tree stems and dates of tree natality. FRI values varied from 130 yr to 350 yr with 200 +/- 50 yr mean. In southerly larch dominated communities FRI was found to be shorter (77 +/- 20 yr at approx 61 deg. N, and 82 +/- 7 at 64 deg N), and longer at the northern boundary (approx 71 deg) of larch stands (320 +/- 50 yr). During the Little Ice Age period in the 16th to 18th centuries FRI was approximately twice as long as recorded in this study. Fire caused changes in the soil including increases in soil drainage and permafrost thawing depth and a radial growth increase of about 2 times (with more than 6 times observed). This effect may simulate the predicted warming impact on the larch growth in the permafrost zone.

Khaurk, Viacheslav I.↗

NASA NTRS2020

Joint retrieval of soil moisture and permafrost active layer thickness using L-band InSAR and P-band PolSAR

Seasonal subsidence measured by repeat-pass interferometric synthetic aperture radar (InSAR) can be used to infer the active layer thickness (ALT) in permafrost regions. The differential volume of soil water undergoing the phase change over the thaw season is one of the factors impacting the seasonal subsidence and is a function of both soil moisture profile and thaw depth. Without the information about soil moisture, this InSAR approach can have large biases in the ALT estimates when soil moisture profile is below saturation. Soil moisture and ALT can also be estimated from polarimetric synthetic aperture radar (PolSAR) backscatter observations but the sensing depth of the PolSAR approach is limited when deep ALT is present. In this paper, we integrated these two approaches and applied a joint retrieval method to estimate the soil moisture profiles and ALT from the L-band InSAR and P-band PolSAR data acquired over the Arctic-boreal region during the 2017 Arctic-Boreal Vulnerability Experiment (ABoVE) airborne campaign.

Schaefer, Kevin M.↗

NASA NTRS2018

Ecosystem Carbon Emissions from 2015 Forest Fires in Interior Alaska

In the summer of 2015, hundreds of wildfires burned across the state of Alaska, and consumed more than 1.6 million ha of boreal forest and wetlands in the Yukon-Koyukuk region. Mapping of 113 large wildfires using Landsat satellite images from before and after 2015 indicated that nearly 60% of this area was burned at moderate-to-high severity levels. Field measurements near the town of Tanana on the Yukon River were carried out in July of 2017 in both unburned and 2015 burned forested areas (nearly adjacent to one-another) to visually verify locations of different Landsat burn severity classes (low, moderate, or high). Results: Field measurements indicated that the loss of surface organic layers in boreal ecosystem fires is a major factor determining post-fire soil temperature changes, depth of thawing, and carbon losses from the mineral topsoil layer. Measurements in forest sites showed that soil temperature profiles to 30 cm depth at burned forest sites increased by an average of 8o - 10o C compared to unburned forest sites. Sampling and laboratory analysis indicated a 65% reduction in soil carbon content and a 58% reduction in soil nitrogen content in severely burned sample sites compared to soil mineral samples from nearby unburned spruce forests. Conclusions: Combined with nearly unprecedented forest areas severely burned in the Interior region of Alaska in 2015, total ecosystem fire emission of carbon to the atmosphere exceeded most previous estimates for the state.

Ecosystem↗

NASA NTRS1998

Seasonally Frozen Soil Monitoring Using Passive Microwave Satellite Data and Simulation Modeling

Satellite data and simulation modeling were used to assess seasonally frozen soils in the central US - Canada borders area (46-53 degrees N and 96-108 degrees). We used Scanning Multichannel Microwave Radiometer (SMMR) satellite data to delineate the top layer of frozen soils. SMMR is a passive microwave sensor having five channels (6.6, 10, 18, 21 and 37 GHz) with a horizontal and vertical polarization. SMRR data are available between 1978-1987 with noon and midnight overpass and footprint sizes between 25 km and 150 km. SMMR data were processed from resampled 1/4 degree grid cells during fall freeze-up and spring thaw (fall 1985 - spring 1987). The dielectric properties of a target may directly affect the satellite signal. The dielectric value is an order of magnitude smaller for frozen soil water. There are other significant changes to the emitted microwave signal from changes to the surface physical temperature, attenuation of the soil signal from plant water and soil moisture. We further characterized the temporal and spatial dynamic of frozen soils using the FroST (Frozen Soil Temperature) simulation model. The FroST model was used to further predict soil water and ice content, and soil temperature. SMMR results were compared versus 5-cm soil temperature data from available weather stations (14 in Canada and 11 for available months in the US). SMMR data were analyzed as a function of frequency, polarization, polarization difference, and "frequency gradient". In addition, vegetation density, physical temperature and snow depth were also considered. Preliminary analysis of SMMR derived frozen soil/thaw classification using a simple threshold classification indicates a mean overall classification accuracy by season of 85 percent. A sensitivity analysis for different soils with varying amounts of snow was conducted with FroST, which showed that the amount of snow, and the time of snow fall and melt affected the ice and water content, and depth of thaw. These results indicate a potential source of flooding and erosion under conditions when melting snow and spring rains provide a source of infiltrating water.

Toll, D. L.↗

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 NTRS1981

Utilization of remote sensing in Alaska permafrost studies

Permafrost related features such as: aufeis, tundra, thaw lakes and subsurface ice features were studied. LANDSAT imagery was used to measure the extent and distribution of aufeis in Arctic Slope rivers over a period of 7 years. Interannual extent of large aufeis fields was found to vary significantly. Digital LANDSAT data were used to study the short term effects of a tundra fire which burned a 48 sq km area in northwestern Alaska. Vegetation regrowth was inferred from Landsat spectral reflectance increases and compared to in-situ measurements. Aircraft SAR (Synethic Aperture Radar) imagery was used in conjunction with LANDSAT imagery used in conjunction with LANDSAT imagery to qualitatively determine depth categories for thaw lakes in northern Alaska.

Hall, D. K.↗

NASA NTRS2003

Prospecting for Martian Ice from Orbit

Recent data from the Gamma-Ray Spectrometer (GRS) on Mars Odyssey indicate the presence of a hydrogen-rich layer tens of centimeters thick in high latitudes on Mars. This hydrogen-rich layer correlates to previously determined regions of ice stability. It has been suggested that the subsurface hydrogen is ice and constitutes 35 plus or minus 15% by weight near the north and south polar regions. This study constrains the location of subsurface ice deposits on the scale of kilometers or smaller by combining GRS data with surface features indicative of subsurface ice. The most recognizable terrestrial geomorphic indicators of subsurface ice, formed in permafrost and periglacial environments, include thermokarst pits, pingos, pseudocraters and patterned ground. Patterned ground features have geometric forms such as circles, polygons, stripes and nets. This study focuses on the polygonal form of patterned ground, selected for its discernable shape and subsurface implications. Polygonal features are typically demarcated by troughs, beneath which grow vertical ice-wedges. Ice-wedges form in thermal contraction cracks in ice-rich soil and grow with annual freezing and thawing events repeated over tens of years. Ice wedges exist below the depth of seasonal freeze-thaw. Terrestrial ice wedges can be several meters deep and polygons can be tens of meters apart, and, on rare occasions, up to 1 km. The crack spacing of terrestrial polygons is typically 3 to 10 times the crack depth.

Kanner, L. C.↗

NASA NTRS1995

Ice Processes and Growth History on Arctic and Sub-Arctic Lakes Using ERS-1 SAR Data

A survey of ice growth and decay processes on a selection of shallow and deep sub-Arctic and Arctic lakes was conducted using radiometrically calibrated ERS-1 SAR images. Time series of radar backscatter data were compiled for selected sites on the lakes during the period ot ice cover (September to June) for the years 1991-1992 and 1992-1993. A variety of lake-ice processes could be observed, and significant changes in backscatter occurred from the time of initial ice formation in autumn until the onset of the spring thaw. Backscatter also varied according to the location and depth of the lakes. The spatial and temporal changes in backscatter were most constant and predictable at the shallow lakes on the North Slope of Alaska. As a consequence, they represent the most promising sites for long-term monitoring and the detection of changes related to global warming and its effects on the polar regions.

Morris, K.↗

NASA NTRS2014

Lunar Polar Environmental Testing: Regolith Simulant Conditioning

As ISRU system development approaches flight fidelity, there is a need to test hardware in relevant environments. Extensive laboratory and field testing have involved relevant soil (lunar regolith simulants), but the current design iterations necessitate relevant pressure and temperature conditions. Including significant quantities of lunar regolith simulant in a thermal vacuum chamber poses unique challenges. These include facility operational challenges (dust tolerant hardware) and difficulty maintaining a pre-prepared soil state during pump down (consolidation state, moisture retention).For ISRU purposes, the regolith at the lunar poles will be of most interest due to the elevated water content. To test at polar conditions, the regolith simulant must be doped with water to an appropriate percentage and then chilled to cryogenic temperatures while exposed to vacuum conditions. A 1m tall, 28cm diameter bin of simulant was developed for testing these simulant preparation and drilling operations. The bin itself was wrapped with liquid nitrogen cooling loops (100K) so that the simulant bed reached an average temperature of 140K at vacuum. Post-test sampling was used to determine desiccation of the bed due to vacuum exposure. Depth dependent moisture data is presented from frozen and thawed soil samples.Following simulant only evacuation tests, drill hardware was incorporated into the vacuum chamber to test auguring techniques in the frozen soil at thermal vacuum conditions. The focus of this testing was to produce cuttings piles for a newly developed spectrometer to evaluate. This instrument, which is part of the RESOLVE program science hardware, detects water signatures from surface regolith. The drill performance, behavior of simulant during drilling, and characteristics of the cuttings piles will be offered.

lunar regolith↗

NASA NTRS2014

Lunar Polar Environmental Testing: Regolith Simulant Conditioning

in situ resource utilization↗

NASA NTRS1990

Possible Martian brines - Radar observations and models

The 1971 and 1973 Goldstone 12.6-cm radar observations of Mars are separate data sets which include reflectivity as a function of latitude, longitude, and season. It has been argued that secular reflectivity variations of Mars' surface are indicated by the data and that shallow subsurface melting is the causal mechanism most compatible with the observations; however, the melting hypothesis conflicts with accepted notions of the state and distribution of water on Mars. The data are examined to identify temporal and spatial domains within which statistically significant changes in measured reflectivity are clustered. Brines which might satisfy the best supported reflectivity variations are out of equilibrium with the chemical megaenvironment. It is unclear whether such a brine, if emplaced in the Martian regolith at a depth shallow enough to affect the radar reflectivity, could survive even a single freeze-thaw cycle. Some combination of unique scattering properties or some as yet unidentified process other than melting is responsible for any genuine reflectivity variations.

Zent, Aaron P.↗

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 NTRSDate not supplied

Examining Soil Freeze/Thaw Remote Sensing Using NASA’s SLAPex Freeze/Thaw Airborne Campaign

Around half the exposed land of the Northern Hemisphere experiences seasonal freezing and thawing. The changes to the soil thermal, hydraulic, and mechanical properties are large and these, in turn, exert significant controls on the water, energy, and carbon cycles of the affected regions. Wide-area freeze/thaw discrimination via microwave remote sensing is possible using both passive and active techniques. We explore freeze/thaw remote sensing using observations from NASA’s Scanning L-band Active Passive (SLAP) airborne sensor during the SLAPex Freeze/Thaw campaign near Winnipeg, Canada in November, 2015. SLAP is an airborne simulator of the Soil Moisture Active Passive (SMAP) satellite mission. The SLAPex Freeze/Thaw dataset is a unique dataset that allows comparison of airborne-derived freeze/thaw state (plus soil moisture for thawed areas) against in-situ ground truth, satellite-derived freeze/thaw from SMAP, as well as tower-based passive microwave freeze/thaw observations. The sensitivity of passive and active microwave sensing to different depths of freezing and different dielectric models (when soil moisture is retrieved) is examined, and the spatial scaling of heterogeneous frozen/thawed pixels is also explored. Implications for the accuracy of satellite-based freeze/thaw discrimination are discussed.

Edward Kim↗

NASA NTRS2018

Portable, Low-Cost, Column Carbon Dioxide and Methane Measurements for Validating Satellite Observations in Remote Locations

We present a low-cost (~$10K per instrument), portable solution to ground-based validation of satellite observations for difficult to reach locations with precisions of 1 ppm XCO2 and 10 ppb XCH4 for hourly data products. While Total Carbon Column Observing Network (TCCON) is the gold-standard for ground validation, there are locations where a ground column validation data point would be useful but conditions are not conducive to a permanent station. Examples include wetlands, thawing permafrost, the tropics, the Amazon, sub-Saharan Africa, as well as locations without a power grid or with geopolitical conflict. In addition, the low-cost and portability mean a geographical region can be studied in depth with multiple instruments. This passive, sun-pointing instrument is a miniaturized, laser heterodyne radiometer (mini-LHR) that has been under development by our team since 2009. It can be operated either in tandem with AERONET (a global network of 500 instruments that measure aerosol optical depth), or as a stand-alone instrument with a low-cost (~$3K), light-weight sun tracker. One of the main benefits of the mini-LHR is that it can quickly reach remote locations and provide a validation measurement even if there is limited or no infrastructure at the site. The instrument weighs ~10 lbs, fits into a backpack, and is powered by two folding solar panels and a battery pack. In clear conditions, the instrument can be set-up in under an hour. Portability means that mini-LHRs can be easily moved for side-by-side comparisons with other mini-LHRs and with TCCON which simplifies assessing instrument bias as well as accuracy. Like TCCON, the mini-LHR points directly at the sun with a narrow field-of-view and is its insensitivity to cloud and aerosol scattering that is common to nadir-pointing passive satellite approaches. Here we present a collection of sample data sets to demonstrate performance from locations that vary in climate, altitude, solar zenith angle, hours of sun per day, etc., as well as data from side-by-side TCCON comparisons. Retrievals of CO2 and CH4 were completed using the NASA/Goddard's Planetary Spectrum Generator (PSG) that incorporates meteorological inputs from Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) data set.

Wilson, Emily W.↗

NASA NTRS2009

Preliminary Evaluation of the AFWA-NASA (ANSA) Blended Snow-Cover Product over the Lower Great Lakes Region

The Air Force Weather Agency (AFWA) - NASA (ANSA) blended-snow product utilizes EOS standard snow products from the Moderate-Resolution Imaging Spectroradiometer (MODIS) and the Advanced Microwave Scanning Radiometer for EOS (AMSR-E) to map daily snow cover and snow-water equivalent (SWE) globally. We have compared ANSA-derived SWE. with SWE values calculated from snow depths reported at approx.1500 National Climatic Data Center (NCDC) coop stations in the Lower Great Lakes basin. Our preliminary results show that conversion of snow depth to SWE is very sensitive to the choice of snow density (we used either 0.2 or 03 as conversion factors). We found overall better agreement between the ANSA-derived SWE and the co-op station data when we use a snow density of 0.3 to convert the snow depths to SWE. In addition, we show that the ANSA underestimates SWE in densely-forested areas, using January and February 2008 ANSA and co-op data. Furthermore, apparent large SWE changes from one day to the next may be caused by thaw-re-freeze events, and do not always represent a real change in SWE. In the near future we will continue the analysis in the 2006-07 and 2007-08 snow seasons.

Hall, Dorothy K.↗