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At least 343 records · Page 19

LOFTID Surface Heating Reconstruction

On November 10, 2022, the Low-Earth Orbit Flight Test of an Inflatable Decelerator (LOFTID) reentry vehicle launched to low-Earth orbit aboard a United Launch Alliance Atlas V rocket out of Vandenberg Air Force Base. The aeroshell, the largest Hypersonic Inflatable Aerodynamic Decelerator (HIAD) ever flown, was inflated to its full 6-meter diameter before successful re-entry into the atmosphere. The aeroshell was heavily instrumented in order to understand its behavior during entry. There were 82 thermocouples (TCs) distributed across the aeroshell, with 22 integrated into the flexible thermal protection system (FTPS) on the rigid nose, 36 in the FTPS on the deployable structure, and 24 on the inflatable structure. TCs were placed at different depths throughout the FTPS. Those nearest to the surface were located just beneath the two SiC outer fabric layers. The near-surface TCs on the rigid nose were Type R with flame spray alumina insulation, while those on the flank were Type N with mica/ceramic insulation. Additionally, a radiometer was placed at the center of the nose surrounded by four total heat flux gauges in a cruciform configuration at a radius of 0.41 m. The nose instrumentation is shown in Fig. 1 and a cross-section of the aeroshell with all TC locations is shown in Fig. 2. The objective of this work was to use the temperatures measured by the TCs during flight to estimate the surface heat rate across the aeroshell throughout the period of re-entry by inverse analysis methodology. The results were used to evaluate the fidelity of measurements from the total heat flux gauges on the nose, determine the surface heat flux at aeroshell locations where gauges were not present, and compare to pre-flight CFD-based heating predictions. Inversely estimated surface heat flux continues to be used to correlate FTPS thermal models to reconstruct in-flight thermal response.

H S Alpert↗

LOFTID Surface Heating Reconstruction

On November 10, 2022, the Low-Earth Orbit Flight Test of an Inflatable Decelerator (LOFTID) reentry vehicle launched to low-Earth orbit aboard a United Launch Alliance Atlas V rocket out of Vandenberg Air Force Base. The aeroshell, the largest Hypersonic Inflatable Aerodynamic Decelerator (HIAD) ever flown, was inflated to its full 6-meter diameter before successful re-entry into the atmosphere. The aeroshell was heavily instrumented in order to understand its behavior during entry. There were 82 thermocouples (TCs) distributed across the aeroshell, with 22 integrated into the flexible thermal protection system (FTPS) on the rigid nose, 36 in the FTPS on the deployable structure, and 24 on the inflatable structure. TCs were placed at different depths throughout the FTPS. Those nearest to the surface were located just beneath the two SiC outer fabric layers. The near-surface TCs on the rigid nose were Type R with flame spray alumina insulation, while those on the flank were Type N with mica/ceramic insulation. Additionally, a radiometer was placed at the center of the nose surrounded by four total heat flux gauges in a cruciform configuration at a radius of 0.41 m. The nose instrumentation is shown in Fig. 1 and a cross-section of the aeroshell with all TC locations is shown in Fig. 2. The objective of this work was to use the temperatures measured by the TCs during flight to estimate the surface heat rate across the aeroshell throughout the period of re-entry by inverse analysis methodology. The results were used to evaluate the fidelity of measurements from the total heat flux gauges on the nose, determine the surface heat flux at aeroshell locations where gauges were not present, and compare to pre-flight CFD-based heating predictions. Inversely estimated surface heat flux continues to be used to correlate FTPS thermal models to reconstruct in-flight thermal response.

LOFTID↗

The Land Surface in Earth System Reanalysis

Current global atmospheric reanalysis products such as ERA-5, MERRA-2, and JRA-55 provide estimates of land surface states and fluxes, including soil moisture, soil temperature, snow mass, latent and sensible heat fluxes, and runoff. These land surface estimates are based on land surface process models and, depending on the reanalysis product, on precipitation observations or the assimilation of land surface observations of soil moisture and snow conditions from satellites and in situ networks. The land models used in the current global atmospheric reanalysis systems are generally focused on water and energy balance processes, with prescribed static land cover and prescribed climatological vegetation conditions. That is, current global atmospheric reanalysis products do not reflect changes in land use or land cover, nor do they provide dynamic estimates of the land carbon cycle. These and other gaps, including the omission of anthropogenic processes such as irrigation in the land model, need to be addressed in the development of the next generation Earth system reanalysis systems. This presentation provides an overview of the state-of-the-art and future developments of land surface estimates in global reanalysis systems.

Rolf Reichle↗

Estimating the urban bias of surface shelter temperatures using upper-air and satellite data. Part 2: Estimation of the urban bias

A methodology is presented for estimating the urban bias of surface shelter temperatures due to the effect of the urban heat island. Multiple regression techniques were used to predict surface shelter temperatures based on the time period 1986-89 using upper-air data from the European Centre for Medium-Range Weather Forecasts (ECMWF) to represent the background climate, site-specific data to represent the local landscape, and satellite-derived data -- the normalized difference vegetation index (NDVI) and the Defense Meteorological Satellite Program (DMSP) nighttime brightness data -- to represent the urban and rural landscape. Local NDVI and DMSP values were calculated for each station using the mean NDVI and DMSP values from a 3 km x 3 km area centered over the given station. Regional NDVI and DMSP values were calculated to represent a typical rural value for each station using the mean NDVI and DMSP values from a 1 deg x 1 deg latitude-longitude area in which the given station was located. Models for the United States were then developed for monthly maximum, mean, and minimum temperatures using data from over 1000 stations in the U.S. Cooperative (COOP) Network and for monthly mean temperatures with data from over 1150 stations in the Global Historical Climate Network (GHCN). Local biases, or the differences between the model predictions using the observed NDVI and DMSP values, and the predictions using the background regional values were calculated and compared with the results of other research. The local or urban bias of U.S. temperatures, as derived from all U.S. stations (urban and rural) used in the models, averaged near 0.40 C for monthly minimum temperatures, near 0.25 C for monthly mean temperatures, and near 0.10 C for monthly maximum temperatures. The biases of monthly minimum temperatures for individual stations ranged from near -1.1 C for rural stations to 2.4 C for stations from the largest urban areas. The results of this study indicate minimal problems for global application once global NDVI and DMSP data become available.

Epperson, David L.↗

Estimates of the Lunar Surface Composition with Clementine Images and LSCC Data

There have been several approaches to develop remote sensing technique to estimate composition of the lunar surface using multispectral observations. We present a new approach based on statistical analysis of spectral and compositional data for lunar samples by the Lunar Soil Characterization Consortium (LSCC) and using the UVVIS Clementine data with 1 km resolution. This technique allows us to estimate and map the abundance of TiO2, SiO2, and FeO, pyroxene and plagioclase content, and maturity degree (Is/FeO).

Shkuratov, Yu.↗

Variation of the low level winds during the passage of a thunderstorm gust front

Three time histories of wind profiles in thunderstorm gust fronts at Cape Kennedy and three at Oklahoma City are analyzed. Wind profiles at maximum wind strength below 100 m follow logarithmic laws, so that winds above the surface layer can be estimated from surface winds once the roughness length is known. A statistical analysis of 81 cases of surface winds during thunderstorms at Tampa revealed no predictor with skill to predict the time of maximum gust. Some 34% of the variance of the strength of the gust is accounted for by a stability index and surface wind prior to the gust; the regression equations for these variables are given. The coherence between microscale wind speed variations at the different levels has the same proportions as in non-thunderstorm cases.

Sinclair, R. W.↗

Comparison between photogrammetric and bistatic-radar slope frequency distributions

A comparison was made of the results for lunar surface roughness estimates and slope frequency distributions obtained by using photogrammetric techniques with those obtained by using bistatic radar. Three topics were discussed: (1) the form of the slope frequency distributions, (2) the change of roughness estimates of the lunar surface with scale, and (3) the magnitude of surface roughness.

Moore, H. J.↗

On the temperature of surfaces

The concept of the temperature of a surface is introduced from the viewpoint of the physical chemistry of surfaces. The surface, near surface and microlayer regions of the interface are defined. Most methods measure the temperature of the microlayer or at best the near surface region and may err in representing the surface temperature. Methods based on capillary ripples actually measure the surface temperature since surface tension (or surface tension tensor when a monolayer has been spread or absorbed at the interface) is the main restoring force that controls their propagation. Light scattering methods are described for determining the elevation of very small amplitude capillary waves through the computation of various correlation functions from which the surface tension can be estimated. Procedures for estimating the surface temperature are described.

Mann, J. Adin, Jr.↗

Results of a study on polarization mix selection for the NSCAT scatterometer

The NASA scatterometer (NSCAT) is an instrument designed to measure the radar backscatter of the ocean's surface for estimating the near-surface wind velocity. A given resolution element is observed from several different azimuth angles. From these measurements the near-surface vector wind over the ocean may be inferred using a geophysical model function relating the normalized radar backscatter coefficient (sigma0) to the near-surface wind. The results of a study to select a polarization mix for NSCAT using an end-to-end simulation of the NSCAT scatterometer and ground processing of the sigma0 measurements into unambiguous wind fields using a median-filter-based ambiguity-removal algorithm are presented. The system simulation was used to compare the wind measurement accuracy and ambiguity removal skill over a set of realistic mesoscale wind fields for various polarization mixes. Considerations in the analysis and simulation are discussed, and a recommended polarization mix is given.

Long, David G.↗

Earth-atmosphere system and surface reflectivities in arid regions from LANDSAT multispectral scanner measurements

Programs for computing atmospheric transmission and scattering solar radiation were used to compute the ratios of the Earth-atmosphere system (space) directional reflectivities in the vertical direction to the surface reflectivity, for the four bands of the LANDSAT multispectral scanner (MSS). These ratios are presented as graphs for two water vapor levels, as a function of the surface reflectivity, for various sun elevation angles. Space directional reflectivities in the vertical direction are reported for selected arid regions in Asia, Africa and Central America from the spectral radiance levels measured by the LANDSAT MSS. From these space reflectivities, surface vertical reflectivities were computed applying the pertinent graphs. These surface reflectivities were used to estimate the surface albedo for the entire solar spectrum. The estimated albedos are in the range 0.34-0.52, higher than the values reported by most previous researchers from space measurements, but are consistent with laboratory measurements.

Otterman, J.↗

Earth-atmosphere system and surface reflectivities in arid regions from Landsat MSS data

Previously developed programs for computing atmospheric transmission and scattering of the solar radiation are used to compute the ratios of the earth-atmosphere system (space) directional reflectivities in the nadir direction to the surface Lambertian reflectivity, for the four bands of the Landsat multispectral scanner (MSS). These ratios are presented as graphs for two water vapor levels, as a function of the surface reflectivity, for various sun elevation angles. Space directional reflectivities in the vertical direction are reported for selected arid regions in Asia, Africa, and Central America from the spectral radiance levels measured by the Landsat MSS. From these space reflectivities, surface reflectivities are computed applying the pertinent graphs. These surface reflectivities are used to estimate the surface albedo for the entire solar spectrum. The estimated albedos are in the range 0.34-0.52, higher than the values reported by most previous researchers from space measurements, but are consistent with laboratory and in situ measurements.

Otterman, J.↗

Comparing Potential Recharge Estimates From Three Land Surface Models Across the Western US

Groundwater is a major source of water in the western US. However, there are limited recharge estimates available in this region due to the complexity of recharge processes and the challenge of direct observations. Land surface Models (LSMs) could be a valuable tool for estimating current recharge and projecting changes due to future climate change. In this study, simulations of three LSMs (Noah, Mosaic and VIC) obtained from the North American Land Data Assimilation System (NLDAS-2) are used to estimate potential recharge in the western US Modeled recharge was compared with published recharge estimates for several aquifers in the region. Annual recharge to precipitation ratios across the study basins varied from 0.01-15% for Mosaic, 3.2-42% for Noah, and 6.7-31.8% for VIC simulations. Mosaic consistently underestimates recharge across all basins. Noah captures recharge reasonably well in wetter basins, but overestimates it in drier basins. VIC slightly overestimates recharge in drier basins and slightly underestimates it for wetter basins. While the average annual recharge values vary among the models, the models were consistent in identifying high and low recharge areas in the region. Models agree in seasonality of recharge occurring dominantly during the spring across the region. Overall, our results highlight that LSMs have the potential to capture the spatial and temporal patterns as well as seasonality of recharge at large scales. Therefore, LSMs (specifically VIC and Noah) can be used as a tool for estimating future recharge rates in data limited regions.

groundwater↗

FIFE, First ISLSCP Field Experiment - Results overview

Results of the analyses of the First International Satellite Land-Surface Climatology Project Field Experiment (FIFE) are described which relate to the mass and energy flux of a particular area. The extensive satellite and ground data are used to analyze the energy balance over the FIFE site, monitor the energy-budget components, study atmospheric effects on remote sensing, examine cloud cover, and investigate fluxes in the atmospheric boundary layer. The results verify existing theories relating energy-balance components with surface biology and remote sensing, and satellites can be used to estimate surface-energy budgets. Some analyses provide data that contradict present theories regarding thermodynamic and biophysical methodologies for estimating surface-heat fluxes.

Hall, F. G.↗

Estimates of Long Term Surface Soil Moisture in the Midwestern U.S. Derived from Satellite Microwave Observations

Soil moisture is a key component of the water and energy balances of the Earth's surface, and has been identified as a parameter of significant potential for improving the accuracy of large-scale land surface-atmosphere interaction models. However, soil moisture is often somewhat difficult to measure accurately in both space and time, especially at large spatial scales. Soil moisture is highly variable, and while point measurements are typically quite accurate, subsequent areal averaging of these measurements often leads to large errors. Since remotely sensed land surface observations are already a spatially averaged or areally integrated value, they are a logical input parameter to regional or larger scale land process models. A database of long-term soil moisture was compared to satellite microwave observations over test sites in the Midwestern United States. Ground measurements of average volumetric surface soil moisture in the top ten cm were made bimonthly at 19 locations throughout the state of Illinois. Nighttime microwave brightness temperatures were observed at a frequency of 6.6 GHz, by the Scanning Multichannel Microwave Radiometer (SMMR), onboard the Nimbus 7 satellite. The life of the SMMR instrument spanned from Nov. 1978 to Aug. 1987. At 6.6 GHz, the instrument provided a spatial resolution of approximately 150 km, and a temporal frequency over the test area of about 3 nighttime orbits per week. Vegetation radiative transfer characteristics, such as the canopy transmissivity, were estimated from vegetation indices such as the Normalized Difference Vegetation Index (NDVI) and the 37 GHz Microwave Polarization Difference Index (MPDI). Because the time of satellite coverage does not always coincide with the ground measurements of soil moisture, the existing ground data were used to calibrate a water balance for the top IO cm surface layer in order to interpolate daily surface moisture values. Such a climate-based approach is often more appropriate for estimating large-area average soil moisture because meteorological data are generally more spatially representative than isolated point measurements of soil moisture, Passive microwave remote sensing presents the greatest potential for providing regular spatially representative estimates of surface soil moisture at global scales. Real time estimates should improve weather and climate modelling efforts, while the development of historical data sets will provide necessary information for simulation and validation of long-term climate and global change studies.

Owe, M.↗

Application of Low-Cost Fine Particulate Mass Monitors to Convert Satellite Aerosol Optical Depth Measurements to Surface Concentrations in North America and Africa

Low-cost particulate mass sensors provide opportunities to assess air quality at unprecedented spatial and temporal resolutions. Established traditional monitoring networks have limited spatial resolution and are simply absent in many major cities across sub-Saharan Africa (SSA). Satellites provide snapshots of regional air pollution but require ground-truthing. Low-cost monitors can supplement and extend data coverage from these sources worldwide, providing a better overall air quality picture. We investigate the utility of such a multi-source data integration approach using two case studies. First, in Pittsburgh, Pennsylvania, both traditional monitoring and dense low-cost sensor networks are compared with satellite aerosol optical depth (AOD) data from NASA's MODIS system, and a linear conversion factor is developed to convert AOD to surface fine particulate matter mass concentration (as PM2.5). With 10 or more ground monitors in Pittsburgh, there is a 2-fold reduction in surface PM2.5 estimation mean absolute error compared to using only a single ground monitor. Second, we assess the ability of combined regional-scale satellite retrievals and local-scale low-cost sensor measurements to improve surface PM2.5 estimation at several urban sites in SSA. In Rwanda, we find that combining local ground monitoring information with satellite data provides a 40 % improvement in surface PM2.5 estimation accuracy with respect to using low-cost ground monitoring data alone. A linear AOD-to-surface-PM2.5 conversion factor developed in Kigali, Rwanda, did not generalize well to other parts of SSA and varied seasonally for the same location, emphasizing the need for ongoing and localized ground-based monitoring, which can be facilitated by low-cost sensors. Overall, we find that combining ground-based low-cost sensor and satellite data, even without including additional meteorological or land use information, can improve and expand spatiotemporal air quality data coverage, especially in data-sparse regions.

AOD↗

Exchange of adsorbed H2O and CO2 between the regolith and atmosphere of Mars caused by changes in surface insolation

Estimates have been made of the capacity of the Martian regolith to exchange adsorbed H2O and CO2 with the atmosphere-plus-cap system (APCS). These estimates are based upon measured isotherms for H2O and CO2 adsorption on pulverized basalt at low temperatures and on theoretical considerations. A unit column (1 sq cm) of regolith with a deep subsurface temperature of -77 C, considered average for the disk, will contain about 0.4 g of adsorbed CO2 and about 1 g of adsorbed H2O per meter of depth. Under favorable circumstances the top 3 cm can exchange much more H2O with the lower atmosphere each day than is necessary to produce the diurnal brightening. The process appears to be seasonally reversible. The total regolith may contain, in the adsorbed phase alone, as much as 1% of the H2O and 5% of the CO2 surface inventories expected for a hypothetical Mars that has experienced degassing as intensive as that of earth.

Fanale, F. P.↗