Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Land surface”

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.

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

At least 163 records · Page 9

Land surface temperature measurements from EOS MODIS data

A generalized split-window method for retrieving land-surface temperature (LST) from AVHRR and MODIS data has been developed. Accurate radiative transfer simulations show that the coefficients in the split-window algorithm for LST must depend on the viewing angle, if we are to achieve a LST accuracy of about 1 K for the whole scan swath range (+/-55.4 deg and +/-55 deg from nadir for AVHRR and MODIS, respectively) and for the ranges of surface temperature and atmospheric conditions over land, which are much wider than those over oceans. We obtain these coefficients from regression analysis of radiative transfer simulations, and we analyze sensitivity and error by using results from systematic radiative transfer simulations over wide ranges of surface temperatures and emissivities, and atmospheric water vapor abundance and temperatures. Simulations indicated that as atmospheric column water vapor increases and viewing angle is larger than 45 deg it is necessary to optimize the split-window method by separating the ranges of the atmospheric column water vapor and lower boundary temperature, and the surface temperature into tractable sub-ranges. The atmospheric lower boundary temperature and (vertical) column water vapor values retrieved from HIRS/2 or MODIS atmospheric sounding channels can be used to determine the range where the optimum coefficients of the split-window method are given. This new LST algorithm not only retrieves LST more accurately but also is less sensitive than viewing-angle independent LST algorithms to the uncertainty in the band emissivities of the land-surface in the split-window and to the instrument noise.

Wan, Zhengming↗

Forward-looking Assimilation of MODIS-derived Snow Covered Area into a Land Surface Model

Snow cover over land has a significant impact on the surface radiation budget, turbulent energy fluxes to the atmosphere, and local hydrological fluxes. For this reason, inaccuracies in the representation of snow covered area (SCA) within a land surface model (LSM) can lead to substantial errors in both offline and coupled simulations. Data assimilation algorithms have the potential to address this problem. However, the assimilation of SCA observations is complicated by an information deficit in the observation SCA indicates only the presence or absence of snow, and not snow volume and by the fact that assimilated SCA observations can introduce inconsistencies with atmospheric forcing data, leading to non-physical artifacts in the local water balance. In this paper we present a novel assimilation algorithm that introduces MODIS SCA observations to the Noah LSM in global, uncoupled simulations. The algorithm utilizes observations from up to 72 hours ahead of the model simulation in order to correct against emerging errors in the simulation of snow cover while preserving the local hydrologic balance. This is accomplished by using future snow observations to adjust air temperature and, when necessary, precipitation within the LSM. In global, offline integrations, this new assimilation algorithm provided improved simulation of SCA and snow water equivalent relative to open loop integrations and integrations that used an earlier SCA assimilation algorithm. These improvements, in turn, influenced the simulation of surface water and energy fluxes both during the snow season and, in some regions, on into the following spring.

Zaitchik, Benjamin F.↗

Interannual Variability of the Mosaic Land-Surface Model

Recently, NASA Goddard Earth Observing System (GEOS-1) reanalysis data has been used to provide forcing for the Koster and Suarez Mosaic Land-surface Model (LSM). The LSM was integrated off-line at all global land points for the period of 1983 - 1995 by the Off-line Land- surface GEOS Assimilation system (OLGA). Here, we compare the interannual variability of OLGA, GEOS-1 and surface observing stations temperature and moisture. Particular attention is given to the United States because of the extreme seasons of 1988 and 1993. Furthermore, the comparison of OLGA is extended to include the analysis of data on the'tiles' (different surface types) in the Mosaic LSM. Results indicate that the GEOS-1 near-surface temperature and moisture reasonably represents the interannual variability in more normal years. However, OLGA also simulates the extreme drought and floods years well. The analysis of the tile information shows that the "Bare soil" surface type is most sensitive to the climate extremes. Off-line testing has provided valuable information on the performance of the Mosaic LSM prior to its incorporation into the new version of the GEOS Data Assimilation System and the integration of a new long reanalysis.

Bosilovich, Michael G.↗

High-Resolution Mesoscale Simulations of the 6-7 May 2000 Missouri Flash Flood: Impact of Model Initialization and Land Surface Treatment

High-resolution mesoscale model simulations of the 6-7 May 2000 Missouri flash flood event were performed to test the impact of model initialization and land surface treatment on timing, intensity, and location of extreme precipitation. In this flash flood event, a mesoscale convective system (MCS) produced over 340 mm of rain in roughly 9 hours in some locations. Two different types of model initialization were employed: 1) NCEP global reanalysis with 2.5-degree grid spacing and 12-hour temporal resolution, and 2) Eta reanalysis with 40- km grid spacing and $hour temporal resolution. In addition, two different land surface treatments were considered. A simple land scheme. (SLAB) keeps soil moisture fixed at initial values throughout the simulation, while a more sophisticated land model (PLACE) allows for r interactive feedback. Simulations with high-resolution Eta model initialization show considerable improvement in the intensity of precipitation due to the presence in the initialization of a residual mesoscale convective vortex (hlCV) from a previous MCS. Simulations with the PLACE land model show improved location of heavy precipitation. Since soil moisture can vary over time in the PLACE model, surface energy fluxes exhibit strong spatial gradients. These surface energy flux gradients help produce a strong low-level jet (LLJ) in the correct location. The LLJ then interacts with the cold outflow boundary of the MCS to produce new convective cells. The simulation with both high-resolution model initialization and time-varying soil moisture test reproduces the intensity and location of observed rainfall.

Baker, R. David↗

Towards Global Simulation of Irrigation in a Land Surface Model: Multiple Cropping and Rice Paddy in Southeast Asia

Agricultural land use significantly influences the surface water and energy balances. Effects of irrigation on land surface states and fluxes include repartitioning of latent and sensible heat fluxes, an increase in net radiation, and an increase in soil moisture and runoff. We are working on representing irrigation practices in continental- to global-scale land surface simulation in NASA's Global Land Data Assimilation System (GLDAS). Because agricultural practices across the nations are diverse, and complex, we are attempting to capture the first-order reality of the regional practices before achieving a global implementation. This study focuses on two issues in Southeast Asia: multiple cropping and rice paddy irrigation systems. We first characterize agricultural practices in the region (i.e., crop types, growing seasons, and irrigation) using the Global data set of monthly irrigated and rainfed crop areas around the year 2000 (MIRCA2000) dataset. Rice paddy extent is identified using remote sensing products. Whether irrigated or rainfed, flooded fields need to be represented and treated explicitly. By incorporating these properties and processes into a physically based land surface model, we are able to quantify the impacts on the simulated states and fluxes.

Beaudoing, Hiroko Kato↗

Tropical peatland hydrology simulated with a global land surface model

Tropical peatlands are among the most carbon-dense ecosystems on Earth, and their water storage dynamics strongly control these carbon stocks. The hydrological functioning of tropical peatlands differs from that of northern peatlands, which has not yet been accounted for in global land surface models (LSMs). Here, we integrated tropical peat-specific hydrology modules into a global LSM for the first time, by utilizing the peatland-specific model structure adaptation (PEATCLSM) of the NASA Catchment Land Surface Model (CLSM). We developed literature-based parameter sets for natural (PEATCLSM(Trop,Nat)) and drained (PEATCLSM(Trop,Drain)) tropical peatlands. Simulations with PEATCLSM(Trop,Nat) were compared against those with the default CLSM version and the northern version of PEATCLSM (PEATCLSM(North,Nat)) with tropical vegetation input. All simulations were forced with global meteorological reanalysis input data for the major tropical peatland regions in Central and South America, the Congo Basin, and Southeast Asia. The evaluation against a unique and extensive data set of in situ water level and eddy covariance-derived evapotranspiration showed an overall improvement in bias and correlation compared to the default CLSM version. Over Southeast Asia, an additional simulation with PEATCLSM(Trop,Drain) was run to address the large fraction of drained tropical peatlands in this region. PEATCLSM(Trop,Drain) outperformed CLSM, PEATCLSM(North,Nat) and PEATCLSM(Trop,Nat) over drained sites. Despite the overall improvements of PEATCLSM(Trop,Nat) over CLSM, there are strong differences in performance between the three study regions. We attribute these performance differences to regional differences in accuracy of meteorological forcing data, and differences in peatland hydrologic response that are not yet captured by our model.

Peatland↗

Land-surface temperature measurement from space - Physical principles and inverse modeling

To apply the multiple-wavelength (split-window) method used for satellite measurement of sea-surface temperature from thermal-infrared data to land-surface temperatures, the authors statistically analyze simulations using an atmospheric radiative transfer model. The range of atmospheric conditions and surface temperatures simulated is wide enough to cover variations in clear atmospheric properties and surface temperatures, both of which are larger over land than over sea. Surface elevation is also included in the simulation as the most important topographic effect. Land covers characterized by measured or modeled spectral emissivities include snow, clay, sands, and tree leaf samples. The empirical inverse model can estimate the surface temperature with a standard deviation less than 0.3 K and a maximum error less than 1 K, for viewing angles up to 40 degrees from nadir under cloud-free conditions, given satellite measurements in three infrared channels. A band in the region from 10.2 to 11.0 microns will usually give the most reliable single-band estimate of surface temperature. In addition, a band in either the 3.5-4.0-micron region or in the 11.5-12.6-micron region must be included for accurate atmospheric correction, and a band below the ozone absorption feature at 9.6 microns (e.g., 8.2-8.8 microns) will increase the accuracy of the estimate of surface temperature.

Wan, Zhengming↗

Influence of land-surface evapotranspiration on the earth's climate

Land-surface evapotranspiration is shown to strongly influence global fields of rainfall, temperature and motion by calculations using a numerical model of the atmosphere, confirming the general belief in the importance of evapotranspiration-producing surface vegetation for the earth's climate. The current version of the Goddard Laboratory atmospheric general circulation model is used in the present experiment, in which conservation equations for mass, momentum, moisture and energy are expressed in finite-difference form for a spherical grid to calculate (1) surface pressure field evolution, and (2) the wind, temperature, and water vapor fields at nine levels between the surface and a 20 km height.

Shukla, J.↗

The Vertical Extent of the Influence of the Land Surface Boundary on the Atmosphere Above

Heterogeneities in the land surface type on scales smaller than the typical General Circulation Model (GMC) grid size have long presented a challenge to properly modelling the impact of the subgrid scale variability on the grid scale. In particular, at some height above the heterogeneous vegetated surface the atmospheric properties (temperature, humidity, for example) become homogenized. This is an issue with implications for climate modelling as well as for the optimal use of field data for climate studies. There is evidence that the influence of the soil and/or vegetation properties extends well beyond the atmospheric surface layer. The present study is aimed at understanding the implications of this influence for a GCM's description of the coupling at the earth-atmosphere interface.

Molod, Andrea↗

Global Assessment of Land Surface Temperature From Geostationary Satellites and Model Estimates

Land surface (or 'skin') temperature (LST) lies at the heart of the surface energy balance and is a key variable in weather and climate models. In this research we compare two global and independent data sets: (i) LST retrievals from five geostationary satellites generated at the NASA Langley Research Center (LaRC) and (ii) LST estimates from the quasi-operational NASA GEOS-5 global modeling and assimilation system. The objective is to thoroughly understand both data sets and their systematic differences in preparation for the assimilation of the LaRC LST retrievals into GEOS-5. As expected, mean differences (MD) and root-mean-square differences (RMSD) between modeled and retrieved LST vary tremendously by region and time of day. Typical (absolute) MD values range from 1-3 K in Northern Hemisphere mid-latitude regions to near 10 K in regions where modeled clouds are unrealistic, for example in north-eastern Argentina, Uruguay, Paraguay, and southern Brazil. Typically, model estimates of LST are higher than satellite retrievals during the night and lower during the day. RMSD values range from 1-3 K during the night to 2-5 K during the day, but are larger over the 50-120 W longitude band where the LST retrievals are derived from the FY2E platform

Reichle, Rolf H.↗

Influence of Land Surface Processes on the Indian Monsoon: A Numerical Study

Twelve July integrations are made with the Goddard Laboratory for Atmospheres' Global Circulation Model GLAS GCM to investigate the influence of local changes in the land surface fluxes, that may be produced by changes in the land surface vegetation, on the monsoon circulation and rainfall over the Indian subcontinent. The study consists of an ensemble mean of three integrations each for four separate cases: (1) control integrations with normaly prescribed boundary conditions, called C; (2) three other integrations with the surface albedo increased (from 0.14 to 0.20) on the Indian subcontinent, called E sub 1; (3) another set of three integrations with the surface albedo increased as above together with a decrease of surface roughness (from 45 cm to 0.02 cm), called E sub 2; and (4) a last set of three integrations with higher surface albedo and low surface roughness as above, but with no evapotranspiration, called E sub 3. Except for these changes in the anomaly region (delimited by solid line) all other boundary conditions were prescribed. Consequently, their time evaluation is unaffected by the Earth-atmosphere interactions.

Sud, Y. C.↗

Downscaling Soil Moisture in the Southern Great Plains Through a Calibrated Multifractal Model for Land Surface Modeling Applications

Accounting for small-scale spatial heterogeneity of soil moisture (theta) is required to enhance the predictive skill of land surface models. In this paper, we present the results of the development, calibration, and performance evaluation of a downscaling model based on multifractal theory using aircraft!based (800 m) theta estimates collected during the southern Great Plains experiment in 1997 (SGP97).We first demonstrate the presence of scale invariance and multifractality in theta fields of nine square domains of size 25.6 x 25.6 sq km, approximately a satellite footprint. Then, we estimate the downscaling model parameters and evaluate the model performance using a set of different calibration approaches. Results reveal that small-scale theta distributions are adequately reproduced across the entire region when coarse predictors include a dynamic component (i.e., the spatial mean soil moisture ) and a stationary contribution accounting for static features (i.e., topography, soil texture, vegetation). For wet conditions, we found similar multifractal properties of soil moisture across all domains, which we ascribe to the signature of rainfall spatial variability. For drier states, the theta fields in the northern domains are more intermittent than in southern domains, likely because of differences in the distribution of vegetation coverage. Through our analyses, we propose a regional downscaling relation for coarse, satellite-based soil moisture estimates, based on ancillary information (static and dynamic landscape features), which can be used in the study area to characterize statistical properties of small-scale theta distribution required by land surface models and data assimilation systems.

Mascaro, Giuseppe↗

Prescription of land-surface boundary conditions in GISS GCM 2: A simple method based on high-resolution vegetation data bases

A simple method was developed for improved prescription of seasonal surface characteristics and parameterization of land-surface processes in climate models. This method, developed for the Goddard Institute for Space Studies General Circulation Model II (GISS GCM II), maintains the spatial variability of fine-resolution land-cover data while restricting to 8 the number of vegetation types handled in the model. This was achieved by: redefining the large number of vegetation classes in the 1 deg x 1 deg resolution Matthews (1983) vegetation data base as percentages of 8 simple types; deriving roughness length, field capacity, masking depth and seasonal, spectral reflectivity for the 8 types; and aggregating these surface features from the 1 deg x 1 deg resolution to coarser model resolutions, e.g., 8 deg latitude x 10 deg longitude or 4 deg latitude x 5 deg longitude.

Matthews, E.↗

An Analysis of Spatio-Temporal Relationship between Satellite-Based Land Surface Temperature and Station-Based Near-Surface Air Temperature over Brazil

A better understanding of the relationship between land surface temperature (Ts) and near-surface air temperature (Ta) is crucial for improving the simulation accuracy of climate models, developing retrieval schemes for soil and vegetation moisture, and estimating large-scale Ta from satellite-based Ts observations. In this study, we investigated the relationship between multiple satellite-based Ts products, derived from the Atmospheric Infrared Sounder (AIRS) and the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard Aqua satellite, and Ta from 204 meteorological stations over Brazil during 2003–2016. Monthly satellite-based Ts products used in this study include: (1) AIRS Version 6 with 1° spatial resolution, (2) AIRS Version 7 with 1° spatial resolution, (3) MODIS Collection 6 with 0.05° spatial resolution, and (4) MODIS Collection 6 with 1° spatial resolution re-sampled from (3) for a direct comparison with AIRS products. We found that satellite-based Ts is lower than Ta over the forest area, but higher than Ta over the non-forest area. Nevertheless, the correlation coefficients (R) between monthly Ta and four Ts products during 2003–2016 are greater than 0.8 over most stations. The long-term trend analysis shows a general warming trend in temperatures, particularly over the central and eastern parts of Brazil. The satellite products could also observe the increasing Ts over the deforestation region. Furthermore, we examined the temperature anomalies during three drought events in the dry season of 2005, 2010, and 2015. All products show similar spatio-temporal patterns, with positive temperature anomalies expanding in areal coverage and magnitude from the 2005 to 2015 event. The above results show that satellite-based Ts is sensitive in reflecting environmental changes such as deforestation and extreme climatic events, and can be used as an alternative to Ta for climatological studies. Moreover, the observed differences between Ts and Ta may inform how thermal assumptions can be improved in satellite-based retrievals of soil and vegetation moisture or evapotranspiration.

land surface temperature↗

Geometric-Optical Modeling of Directional Thermal Radiance for Improvement of Land Surface Temperature Retrievals from MODIS, ASTER, and Landsat-7 Instruments

The general objectives of this project were to improve understanding of the directional emittance properties of land surfaces in the thermal infrared (TIR) region of the electro-magnetic spectrum. To accomplish these objectives our research emphasized a combination of theoretical model development and empirical studies designed to improve land surface temperature (LST) retrievals from space-borne remote sensing instruments. Following the proposal, the main tasks for this project were to: (1) Participate in field campaigns; (2) Acquire and process field, aircraft, and ancillary data; (3) Develop and refine models of LST emission; (4) Develop algorithms for LST retrieval; and (5) Explore LST retrieval methods for use in energy balance models. In general all of these objectives were addressed, and for the most part achieved. The main results from this project are described in the publications arising from this effort. We summarize our efforts related to each of the objectives.

Li, Xiaowen↗

Assimilation of GRACE Terrestrial Water Storage Data into a Land Surface Model

The NASA Gravity Recovery and Climate Experiment (GRACE) system of satellites provides observations of large-scale, monthly terrestrial water storage (TWS) changes. In. this presentation we describe a land data assimilation system that ingests GRACE observations and show that the assimilation improves estimates of water storage and fluxes, as evaluated against independent measurements. The ensemble-based land data assimilation system uses a Kalman smoother approach along with the NASA Catchment Land Surface Model (CLSM). We assimilated GRACE-derived TWS anomalies for each of the four major sub-basins of the Mississippi into the Catchment Land Surface Model (CLSM). Compared with the open-loop (no assimilation) CLSM simulation, assimilation estimates of groundwater variability exhibited enhanced skill with respect to measured groundwater. Assimilation also significantly increased the correlation between simulated TWS and gauged river flow for all four sub-basins and for the Mississippi River basin itself. In addition, model performance was evaluated for watersheds smaller than the scale of GRACE observations, in the majority of cases, GRACE assimilation led to increased correlation between TWS estimates and gauged river flow, indicating that data assimilation has considerable potential to downscale GRACE data for hydrological applications. We will also describe how the output from the GRACE land data assimilation system is now being prepared for use in the North American Drought Monitor.

Reichle, Rolf H.↗

Large Vehicle Lunar Landing Surface Interaction and In-Situ Resource Based Risk Mitigation: Landing & Launch Pads

A key capability required for the exploration of planetary bodies is the ability to land on the surface. Previous work performed by NASA and other institutions has primarily focused on landing small spacecraft on planetary surfaces and the associated small-to-medium thrusters required for the soft landing. In the case of human exploration—particularly the establishment of long duration exploration and habitation outposts—the ability to land large landers, such as the SpaceX Starship, is necessary. These larger landing systems require the use of more powerful engines, with higher engine exhaust temperatures and higher landing loads. Understanding the excavation of material by the engines, as well as the potential for the landing legs to sink into the subsurface, is key in ensuring reliable and safe landings. A further improvement in landing reliability can be achieved by constructing landing / launch pads, especially with in-situ resources. Some material excavation by the plume is inevitable, leaving at least a portion of the surface scoured and uneven under the lander and ejecting regolith particles and rocks at very high velocities. One possible solution would be to robotically build landing / launch pads (ideally autonomously) at the destination using in-situ materials. In this case, the first one or few landers will need to land on unimproved surfaces at higher risk; however, they would bring the required equipment to build the landing pads with mostly local resources, thus increasing the reliability of safe landing for subsequent larger landers. A number of methods to build in-situ landing and launch pads have already been developed. These methods include no or some addition of required binder additives to the local regolith material, different processing approaches and result in varying landing pad strengths. A sub-scale rocket engine plume, was used to simulate some of the conditions of a landing on the Moon to assess the effectiveness of various materials for an in-situ built landing pad, The GO2/GCH4 rocket engine fired on 1m2 area coupons of representative pad materials. The results will allow continued development towards materials that satisfy the landing pad properties required for the effective risk reduction and increased reliability for landing people and equipment on the lunar surface. This work contained two parts: (1) computer modeling of a large rocket engine plume interacting with regolith on the Moon, using the Granular Gas Flow Solver (GGFS) provided by CFD Research Corporation as well as other computational fluid dynamics codes (CFD) such as Loci/CHEM. (2) Developing landing/launch pad materials that could be used for in-situ construction on the lunar surface in the future, to mitigate the calculated effects of a large vehicle rocket engine landing and launching on the Moon. The resulting computed values of plume impingement surface temperature, stagnation pressure, gas velocity, shear stress and heat flux were then matched as closely as possible in the Earth’s atmosphere in a sub-scale rocket engine GO2/CH4 test which was provided by Masten Space Systems in Mojave, California. The rocket engine was mounted on a test stand with vertical translation capabilities so that the landing operations of a lander could be simulated (Figure 1).The pad materials test coupons were placed at the surface of a large bin containing simulated lunar basalt regolith and subjected to a test firing as shown in Figure 2. The results of this testing will be presented with related findings, analysis and discussion.

Plume Surface Interaction↗

Land Surface Microwave Emissivities Derived from AMSR-E and MODIS Measurements with Advanced Quality Control

A microwave emissivity database has been developed with data from the Advanced Microwave Scanning Radiometer-EOS (AMSR-E) and with ancillary land surface temperature (LST) data from the Moderate Resolution Imaging Spectroradiometer (MODIS) on the same Aqua spacecraft. The primary intended application of the database is to provide surface emissivity constraints in atmospheric and surface property retrieval or assimilation. An additional application is to serve as a dynamic indicator of land surface properties relevant to climate change monitoring. The precision of the emissivity data is estimated to be significantly better than in prior databases from other sensors due to the precise collocation with high-quality MODIS LST data and due to the quality control features of our data analysis system. The accuracy of the emissivities in deserts and semi-arid regions is enhanced by applying, in those regions, a version of the emissivity retrieval algorithm that accounts for the penetration of microwave radiation through dry soil with diurnally varying vertical temperature gradients. These results suggest that this penetration effect is more widespread and more significant to interpretation of passive microwave measurements than had been previously established. Emissivity coverage in areas where persistent cloudiness interferes with the availability of MODIS LST data is achieved using a classification-based method to spread emissivity data from less-cloudy areas that have similar microwave surface properties. Evaluations and analyses of the emissivity products over homogeneous snow-free areas are presented, including application to retrieval of soil temperature profiles. Spatial inhomogeneities are the largest in the vicinity of large water bodies due to the large water/land emissivity contrast and give rise to large apparent temporal variability in the retrieved emissivities when satellite footprint locations vary over time. This issue will be dealt with in the future by including a water fraction correction. Also note that current reliance on the MODIS day-night algorithm as a source of LST limits the coverage of the database in the Polar Regions. We will consider relaxing the current restriction as part of future development.

Moncet, Jean-Luc↗