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NASA NTRS2013

Consistency of Estimated Global Water Cycle Variations Over the Satellite Era

Motivated by the question of whether recent indications of decadal climate variability and a possible "climate shift" may have affected the global water balance, we examine evaporation minus precipitation (E-P) variability integrated over the global oceans and global land from three points of view-remotely sensed retrievals / objective analyses over the oceans, reanalysis vertically-integrated moisture convergence (MFC) over land, and land surface models forced with observations-based precipitation, radiation and near-surface meteorology. Because monthly variations in area-averaged atmospheric moisture storage are small and the global integral of moisture convergence must approach zero, area-integrated E-P over ocean should essentially equal precipitation minus evapotranspiration (P-ET) over land (after adjusting for ocean and land areas). Our analysis reveals considerable uncertainty in the decadal variations of ocean evaporation when integrated to global scales. This is due to differences among datasets in 10m wind speed and near-surface atmospheric specific humidity (2m qa) used in bulk aerodynamic retrievals. Precipitation variations, all relying substantially on passive microwave retrievals over ocean, still have uncertainties in decadal variability, but not to the degree present with ocean evaporation estimates. Reanalysis MFC and P-ET over land from several observationally forced diagnostic and land surface models agree best on interannual variations. However, upward MFC (i.e. P-ET) reanalysis trends are likely related in part to observing system changes affecting atmospheric assimilation models. While some evidence for a low-frequency E-P maximum near 2000 is found, consistent with a recent apparent pause in sea-surface temperature (SST) rise, uncertainties in the datasets used here remain significant. Prospects for further reducing uncertainties are discussed. The results are interpreted in the context of recent climate variability (Pacific Decadal Oscillation, Atlantic Meridional Overturning), and efforts to distinguish these modes from longer-term trends.

Robertson, F. R.↗

NASA NTRS2013

Consistency of Estimated Global Water Cycle Variations Over the Satellite Era

Robertson, F. R.↗

NASA NTRSDate not supplied

Improving the Use of Surface-Sensitive Radiances in the GMAO Hybrid-4DEnVar System

The planetary boundary layer (PBL) was designated as an incubation-class targeted observable (TO) in the 2018 Decadal Survey. As no single instrument source will provide enough information to constrain the global PBL, the assimilation of a wide range of observations in data assimilation (DA) systems will play a critical role, and GMAO has put in efforts to enhance surface-sensitive radiance assimilation. Although a vast number of microwave radiance observations are used in the GEOS global DA system, very few surface-sensitive radiances are currently used over land due to large uncertainty of land surface emissivity in the CRTM as well as cloud detection issue. Dynamically varying emissivity is retrieved from observations of window channels in the GEOS system for non-scattering FOVs and applied to sounding channel assimilation. Moreover, the original radiance bias correction is found not to work well over land, and shows drifting bias when the original emissivity sensitivity bias predictor with a dynamically varying emissivity retrieval is used. Hence, the radiance bias correction has been modified, and the quality control procedure has been adapted accordingly. Cycled experiment results show improvement in the temperature forecast at lower model levels; further refinement of this system continues.

Yanqiu Zhu↗

NASA NTRSDate not supplied

Remote Sensing of Lineage Functional Types for Modeling and Monitoring Biodiversity

Hyperspectral remote sensing has the potential to continuously scale plant function and plant diversity information from landscape to global extents. Numerous studies have indicated that VSWIR (400-2500 nm) reflectance properties of vegetation capture evolutionarily conserved biochemical, structural, and other functional attributes of plant species. Spectral properties conserved in plants provide the opportunity to both 1) aggregate species into lineages with improved classification accuracy and 2) link those lineages directly to plant traits. Full realization of this goal will enable parameterization of Land Surface Models (LSMs) with remotely sensed information, e.g., canopy nitrogen, and better representations of biodiversity and functional diversity in biogeographic studies. In this study, we use hyperspectral AVIRIS data from the 2013 HyspIRI campaign over the Southern Sierra Nevada, California flight box to investigate the potential for incorporating evolutionary thinking into landcover classification. We link the airborne hyperspectral data with vegetation plot data from roughly 1372 surveys and a phylogeny representing 1361 species. We aggregate species into lineages ranging from species level groups down to similar number of Plant Functional Types as often used in LSMs. We assessed the ability of Random Forest and Partial Least Squares Discriminant Analysis to discriminate across these different phylogenetic scales and determine the optimal number of lineages to classify. Although there are some temporal and spatial differences in our training data, our best approaches achieved moderate classification accuracy (Kappa > 0.65). Given an optimal number of lineages, we explored approaches to improve classifications including machine learning and unmixing approaches. This work suggests that lineage-based methods may be a promising way to leverage the huge amounts of data that will come from high resolution and high return interval hyperspectral data planned for the Surface Biology and Geology mission with sparsely sampled existing ground-based ecological data.

Hyperspectral↗

NASA NTRS2013

The Response of the South Asian Summer Monsoon Circulation to Intensified Irrigation in Global Climate Model Simulations

Agricultural intensification in South Asia has resulted in the expansion and intensification of surface irrigation over the twentieth century. The resulting changes to the surface energy balance could affect the temperature contrasts between the South Asian land surface and the equatorial Indian Ocean, potentially altering the South Asian Summer Monsoon (SASM) circulation. Prior studies have noted apparent declines in the monsoon intensity over the twentieth century and have focused on how altered surface energy balances impact the SASM rainfall distribution. Here, we use the coupled Goddard Institute for Space Studies ModelE-R general circulation model to investigate the impact of intensifying irrigation on the large-scale SASM circulation over the twentieth century, including how the effect of irrigation compares to the impact of increasing greenhouse gas (GHG) forcing. We force our simulations with time-varying, historical estimates of irrigation, both alone and with twentieth century GHGs and other forcings. In the irrigation only experiment, irrigation rates correlate strongly with lower and upper level temperature contrasts between the Indian sub-continent and the Indian Ocean (Pearson's r = -0.66 and r = -0.46, respectively), important quantities that control the strength of the SASM circulation. When GHG forcing is included, these correlations strengthen: r = -0.72 and r = -0.47 for lower and upper level temperature contrasts, respectively. Under irrigated conditions, the mean SASM intensity in the model decreases only slightly and insignificantly. However, in the simulation with irrigation and GHG forcing, inter-annual variability of the SASM circulation decreases by *40 %, consistent with trends in the reanalysis products. This suggests that the inclusion of irrigation may be necessary to accurately simulate the historical trends and variability of the SASM system over the last 50 years. These findings suggest that intensifying irrigation, in concert with increased GHG forcing, is capable of reducing the variability of the simulated SASM circulation and altering the regional moisture transport by limiting the surface warming and reducing land-sea temperature gradients.

amplification↗

NASA NTRS2013

Enhanced Deep Blue Aerosol Retrieval Algorithm: The Second Generation

The aerosol products retrieved using the MODIS collection 5.1 Deep Blue algorithm have provided useful information about aerosol properties over bright-reflecting land surfaces, such as desert, semi-arid, and urban regions. However, many components of the C5.1 retrieval algorithm needed to be improved; for example, the use of a static surface database to estimate surface reflectances. This is particularly important over regions of mixed vegetated and non- vegetated surfaces, which may undergo strong seasonal changes in land cover. In order to address this issue, we develop a hybrid approach, which takes advantage of the combination of pre-calculated surface reflectance database and normalized difference vegetation index in determining the surface reflectance for aerosol retrievals. As a result, the spatial coverage of aerosol data generated by the enhanced Deep Blue algorithm has been extended from the arid and semi-arid regions to the entire land areas.

Deep Blue↗

NASA NTRS1970

Anisotropic reflectance characteristics of natural earth surfaces

Reflection patterns of solar radiation from cloud, water and land surfaces measured by airbone radiometer, observing anisotropy

Bandeen, W. R.↗

NASA NTRS1988

Plant microfossil record of the terminal Cretaceous event in the western United States and Canada

Plant microfossils, principally pollen grains and spores produced by land plants, provide an excellent record of the terminal Cretaceous event in nonmarine environments. The record indicates regional devastation of the latest Cretaceous vegetation with the extinction of many groups, followed by a recolonization of the earliest Tertiary land surface, and development of a permanently changed land flora. The regional variations in depositional environments, plant communities, and paleoclimates provide insight into the nature and effects of the event, which were short-lived but profound. The plant microfossil data support the hypothesis that an abruptly initiated, major ecological crisis occurred at the end of the Cretaceous. Disruption of the Late Cretaceous flora ultimately contributred to the rise of modern vegetation. The plant microfossils together with geochemical and mineralogical data are consistent with an extraterrestrial impact having been the cause of the terminal Cretaceous event.

Nichols, D. J.↗

NASA NTRS1990

EOS Multi-angle Imaging SpectroRadiometer (MISR)

The Multi-angle Imaging SpectroRadiometer (MISR) experiment is an Instrument Investigation in the planning stages for the first NASA Earth Observing System polar platform, EOS-A. MISR will routinely acquire multispectral images of the angular reflectance signatures of terrestrial scenes. Scientific objectives include study of the climatic and environmental impacts of atmospheric aerosols, characterization of heterogeneous cloud fields and their impact on the shortwave radiation budget, development of surface bidirectional reflectance and albedo models for land surface climatology studies, and investigation of biosphere-atmosphere interactions and ecosystem change. This paper describes the MISR investigation, instrument, and data products.

Diner, David J.↗

NASA NTRS1992

Application of self-preservation in the diurnal evolution of the surface energy budget to determine daily evaporation

Evaporation from natural land surfaces often exhibits a strong variation during the course of a day, mostly in response to the daily variation of radiative energy input at the surface. This makes it difficult to derive the total daily evaporation, when only one or a few instantaneous estimates of evaporation are available. It is often possible to resolve this difficulty by assuming self-preservation in the diurnal evolution of the surface energy budget. Thus if the relative partition of total incoming energy flux among the different components remains the same, the ratio of latent heat flux and any other flux component can be taken as constant through the day. This concept of constant flux ratios is tested by means of data obtained during the First ISLSCP Field Experiment; the instantaneous evaporation values were calculated by means of the atmospheric boundary layer bulk similarity approach with radiosonde profiles and radiative surface temperatures. Good results were obtained for evaporative flux ratios with available energy flux, with net radiation, and with incoming shortwave radiation.

Brutsaert, Wilfried↗

NASA NTRS2007

Influence of World and Gravity Model Selection on Surface Interacting Vehicle Simulations

A vehicle simulation is surface-interacting if the state of the vehicle (position, velocity, and acceleration) relative to the surface is important. Surface-interacting simulations perform ascent, entry, descent, landing, surface travel, or atmospheric flight. Modeling of gravity is an influential environmental factor for surface-interacting simulations. Gravity is the free-fall acceleration observed from a world-fixed frame that rotates with the world. Thus, gravity is the sum of gravitation and the centrifugal acceleration due to the world s rotation. In surface-interacting simulations, the fidelity of gravity at heights above the surface is more significant than gravity fidelity at locations in inertial space. A surface-interacting simulation cannot treat the gravity model separately from the world model, which simulates the motion and shape of the world. The world model's simulation of the world's rotation, or lack thereof, produces the centrifugal acceleration component of gravity. The world model s reproduction of the world's shape will produce different positions relative to the world center for a given height above the surface. These differences produce variations in the gravitation component of gravity. This paper examines the actual performance of world and gravity/gravitation pairs in a simulation using the Earth.

Madden, Michael M.↗

NASA NTRS2009

Further Investigations of Gravity Modeling on Surface-Interacting Vehicle Simulations

A vehicle simulation is "surface-interacting" if the state of the vehicle (position, velocity, and acceleration) relative to the surface is important. Surface-interacting simulations perform ascent, entry, descent, landing, surface travel, or atmospheric flight. The dynamics of surface-interacting simulations are influenced by the modeling of gravity. Gravity is the sum of gravitation and the centrifugal acceleration due to the world s rotation. Both components are functions of position relative to the world s center and that position for a given set of geodetic coordinates (latitude, longitude, and altitude) depends on the world model (world shape and dynamics). Thus, gravity fidelity depends on the fidelities of the gravitation model and the world model and on the interaction of the gravitation and world model. A surface-interacting simulation cannot treat the gravitation separately from the world model. This paper examines the actual performance of different pairs of world and gravitation models (or direct gravity models) on the travel of a subsonic civil transport in level flight under various starting conditions.

Madden, Michael M.↗

NASA NTRS2011

Evaluation of the Event Driven Phenology Model Coupled with the VegET Evapotranspiration Model Through Comparisons with Reference Datasets in a Spatially Explicit Manner

A new model coupling scheme with remote sensing data assimilation was developed for estimation of daily actual evapotranspiration (ET). The scheme represents a mix of the VegET, a physically based model to estimate ET from a water balance, and an event driven phenology model (EDPM), where the EDPM is an empirically derived crop specific model capable of producing seasonal trajectories of canopy attributes. In this experiment, the scheme was deployed in a spatially explicit manner within the croplands of the Northern Great Plains. The evaluation was carried out using 2007-2009 land surface forcing data from the North American Land Data Assimilation System (NLDAS) and crop maps derived from remotely sensed data of NASA's Moderate Resolution Imaging Spectroradiometer (MODIS). We compared the canopy parameters produced by the phenology model with normalized difference vegetation index (NDVI) data derived from the MODIS nadir bi-directional reflectance distribution function (BRDF) adjusted reflectance (NBAR) product. The expectations of the EDPM performance in prognostic mode were met, producing determination coefficient (r2) of 0.8 +/-.0.15. Model estimates of NDVI yielded root mean square error (RMSE) of 0.1 +/-.0.035 for the entire study area. Retrospective correction of canopy dynamics with MODIS NDVI brought the errors down to just below 10% of observed data range. The ET estimates produced by the coupled scheme were compared with ones from the MODIS land product suite. The expected r2=0.7 +/-.15 and RMSE = 11.2 +/-.4 mm per 8 days were met and even exceeded by the coupling scheme0 functioning in both prognostic and retrospective modes. Minor setbacks of the EDPM and VegET performance (r2 about 0.5 and additional 30 % of RMSR) were found on the peripheries of the study area and attributed to the insufficient EDPM training and to spatially varying accuracy of crop maps. Overall the experiment provided sufficient evidence of soundness and robustness of the EDPM and VegET coupling scheme, assuring its potential for spatially explicit applications.

Kovalskyy, V.↗

NASA NTRS2011

The Impact of Devegetated Dune Fields on North American Climate During the Late Medieval Climate Anomaly

During the Medieval Climate Anomaly, North America experienced severe droughts and widespread mobilization of dune fields that persisted for decades. We use an atmosphere general circulation model, forced by a tropical Pacific sea surface temperature reconstruction and changes in the land surface consistent with estimates of dune mobilization (conceptualized as partial devegetation), to investigate whether the devegetation could have exacerbated the medieval droughts. Presence of devegetated dunes in the model significantly increases surface temperatures, but has little impact on precipitation or drought severity, as defined by either the Palmer Drought Severity Index or the ratio of precipitation to potential evapotranspiration. Results are similar to recent studies of the 1930s Dust Bowl drought, suggesting bare soil associated with the dunes, in and of itself, is not sufficient to amplify droughts over North America.

Cook, B. I.↗

NASA NTRS2019

Multi-Channel Correlator Array-Fed Microwave Radiometer

Multiband passive microwave imagery in X to W Bands has a nearly 40-year history of utilization for measurement of multiple geophysical parameters (e.g., precipitation rate, ocean surface wind speed, sea ice concentration, and land surface temperature). Spatial resolution is limited by aperture size, and although aperture sizes have grown to 1-2 meters, current capability will not meet future spatial resolution needs. As aperture size increases, new antenna feed techniques are needed to maintain contiguous coverage and obtain Nyquist sampling. Here we apply the correlator array fed radiometer architecture adapted from radio astronomy and show how it can meet emerging needs. Simulation results of a 0.8-m, 36.5-GHz, array-fed reflector (equivalent to 20 meters at 1.41 GHz) show the feasibility of creating multiple over-lapping beams.

Microwave radiometer↗

NASA NTRS2021

Maximum entropy modeling to identify physical drivers of shallow snowpack heterogeneity using unpiloted aerial system (UAS) lidar

Understanding the spatial variability of the snowpack is valuable for hydrologists and ecologists seeking to predict hydrological processes in a cold region. Snow distribution is a function of interactions among static variables, such as terrain, vegetation, and soil properties, and dynamic meteorological variables, such as solar radiation, wind speed and direction, and soil moisture. However, identifying the dominant physical drivers responsible for spatial patterns of the snowpack, particularly for ephemeral, shallow snowpacks, has been challenging due to the lack of the high-resolution snowpack and physical variables with high vertical accuracy as well as inherent limitations in traditional approaches. This study uses an Unpiloted Aerial System (UAS) lidar-based snow depth and static variables (1-m spatial resolution) to analyze field-scale spatial structures of snow depth and apply the Maximum Entropy (MaxEnt) model to identify primary controls over open terrain and forests at the University of New Hampshire Thompson Farm Research Observatory, New Hampshire, United States. We found that, among nine topographic and soil variables, plant functional type and terrain roughness contribute up to 80% and 76% of relative importance in the MaxEnt framework to predict locations of deeper or shallower snowpacks, respectively, across a mixed temperate forested and field landscape. Soil variables, such as organic matter and saturated hydraulic conductivity, were also important controls (up to 70% and 81%) on snow depth spatial variations for both open and forested landscapes suggesting spatial variations in soil variables under snow can control thermal transfer among soil, snowpack, and surface-atmosphere. This work contributes to improving land surface and snow models by informing parameterization of the sub-grid scale snow depths, down-scaling remotely sensed snow products, and understanding field scale snow states.

Eunsang Cho↗

NASA NTRS2022

Phoenix Climate: Employing NASA Earth Observations to Conduct Site Suitability Analyses on Residential Tree Planting Initiatives in Phoenix, AZ

Phoenix, Arizona is the hottest city in the United States, with daytime summer temperatures consistently reaching upwards of 100°F. As these daytime temperatures continue to climb, heat-related illnesses and morbidity also increase. The City of Phoenix hopes to secure funding to implement the American Rescue Plan Act (ARPA) residential tree equity accelerator program. This funding will be used for targeted investments in underserved neighborhoods to increase tree canopy cover, engaging 5,000 households across selected neighborhoods. By partnering with the City of Phoenix, the Arizona Office of Heat Mitigation, and Arizona State University’s Urban Climate Research Center, our team identified residential neighborhoods, block groups within qualified census tracts, and parcels to be prioritized in the ARPA program. We conducted an analysis using NASA Earth observations, movement and heat exposure data, sociodemographic data, and tree canopy data. For Earth observations, we acquired daytime land surface temperature from the Landsat 8 Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS) and land cover classification from the United States Geological Survey (USGS) National Land Cover Database (NLCD). The project will support the prioritization of city resources and tree plantings based on community vulnerability, as well as help initiate public engagement efforts and literacy with an interactive dashboard and GIS layers that contribute to the city’s property information portal.

Alison Bautista↗

NASA NTRS2022

Editorial: DSCOVR EPIC/NISTAR: 5Years of Observing Earth From the First Lagrangian Point

The Deep Space Climate Observatory (DSCOVR) was launched in February 2015 to a Sun-Earth Lagrange-1 (L1) orbit, approximately 1.5 million kilometers from the sunlit side of the Earth. In many regards, the DSCOVR is a unique mission: for the first time, it delivers well-calibrated and multi-spectral measurements of Earth from the L1 point. This unique location allows near-hourly views of the entire illuminated disk of the Earth, multiple times a day. The moderately high observational cadence results in cloud-free views of nearly the entire Earth land surface and global ocean with significantly higher frequency than is available to the operational polar orbiters, and at a near-global scale inaccessible to geostationary sensors.

EPIC↗