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At least 721 records · Page 40

Including a Cold Pool Representation in a Convection Parameterization and Simulating Its Impacts on the Spatial and Temporal Variability of the Precipitation in the NASA GEOS GCM

We developed and implemented a simple representation of a cold pool in the Grell-Freitas (GF) convection parameterization. The cold pool parameterization is based on the observation that convective-scale downdrafts produce a local ‘deficit’ of the moist static energy (MSE). This information is advected and becoming downwind available to trigger and intensify new convection. The cold pool is dissipated by a simple exponential decay using a lifetime of a few hours, or by interacting with the underneath surface by exchanging latent and sensible heat fluxes. Preliminary results show some improvement of the simulation of the diurnal cycle of the precipitation over the land, mainly during the nighttime.

Cold pools↗

The High-resolution Urban Meteorology for Impacts Dataset (HUMID) daily for the Conterminous United States

Many current gridded surface meteorological datasets are inadequate for quantifying near surface spatiotemporal variability because they do not fully represent the impacts of land surface heterogeneity. Of note, explicit representation of the spatial structure and magnitude of local urban warming are usually lacking. Here we enhance the representation of spatial meteorological variability over urban areas in the conterminous United States (CONUS) by employing the High-Resolution Land Data Assimilation System (HRLDAS), which accounts for the fine-scale impacts of spatiotemporally varying land surfaces on weather. We also synthesize in situ meteorological data including local mesonets to create a 1 km grid spacing model-observation fusion product spanning 1981-2018 over the CONUS. Daily maximum, minimum, and mean values for a variety of temperature estimates, humidity, and surface energy budget terms, among others, are included. This High-resolution Urban Meteorology for Impacts Dataset (HUMID) will be useful for studies examining spatial variability of near surface meteorology and the impacts of urban heat islands across many disciplines including epidemiology, ecology, and climatology.

54 ENVIRONMENTAL SCIENCES↗

Long-term spatial and temporal solar resource variability over America using the NSRDB version 3 (1998–2017)

The study assesses the long-term spatial and temporal solar resource variability in America using the 20-year National Renewable Energy Laboratory's (NREL's) National Solar Radiation Database (NSRDB). Specifically, the coefficient of variation (COV) is used to analyze the spatial and temporal (interannual and seasonal) variability. Further, both spatial and temporal long-term variability are analyzed using the Köppen-Geiger climate classification. The temporal variability is found that, on average, the continental United States (CONUS) COV reaches up to 5% for global horizontal irradiance (GHI) and 10% for direct normal irradiance (DNI), and that the NSRDB domain's COV is roughly twice that of CONUS. For the seasonal variability analysis, the winter months are found to exhibit higher COV than the other seasons. In particular, December exhibits the highest variability, reaching on average 30% for DNI and 20% for GHI over various areas. On the other hand, the summer months demonstrate significantly lower variability, reaching only less than 20% for DNI and 10% for GHI, on average. Similarly, the spatial variability is analyzed by comparing each pixel to its neighbors. The long-term spatial variability is found to increase with the number of neighboring pixels being considered, which is equivalent to an increase in distance (within a 100-km x 100-km square grid). As expected, the DNI spatial variability is higher than that of GHI. Moreover, the annual solar irradiance anomalies are found to reach ±25% for both GHI and DNI (and even exceed those value in some instances) during each year of the 20-year period.

14 SOLAR ENERGY↗

Leveraging observed soil heterotrophic respiration fluxes as a novel constraint on global-scale models

Microbially-explicit models may improve understanding and projections of carbon dynamics in response to future climate change, but their fidelity in simulating global-scale soil heterotrophic respiration (RH), a stringent test for soil biogeochemical models, has never been evaluated. We used statistical global RH products, as well as 7,821 daily site-scale RH measurements, to evaluate the spatio-temporal performance of one first-order decay model (CASA-CNP) and two microbially-explicit biogeochemical models (CORPSE and MIMICS) that were forced by two different climate datasets. CORPSE and MIMICS did not provide any measurable performance improvement; instead, the models were highly sensitive to the meteorological input data used to drive them. Spatial RH variability was generally well simulated except in the northern middle latitudes (~50°N) and arid regions; models captured the seasonal variability of RH well, but showed more divergence in tropic and arctic regions. Our results demonstrate that the next generation of biogeochemical models shows promise, but also needs to be improved for realistic spatio-temporal variability of RH. Finally, we emphasize the importance of net primary production, soil moisture, and soil temperature inputs, and that jointly evaluating soil models for their spatial (global scale) and temporal (site scale) performance provides crucial benchmarks for improving biogeochemical models.

Jian, Jinshi↗

Theorizing Land Cover and Land Use Change: The Peasant Economy of Colonization in the Amazon Basin

This paper addresses deforestation processes in the Amazon basin. It deploys a methodology combining remote sensing and survey-based fieldwork to examine, with regression analysis, the impact household structure and economic circumstances on deforestation decisions made by colonist farmers in the forest frontiers of Brazil. Unlike most previous regression-based studies, the methodology implemented analyzes behavior at the level of the individual property. The regressions correct for endogenous relationships between key variables, and spatial autocorrelation, as necessary. Variables used in the analysis are specified, in part, by a theoretical development integrating the Chayanovian concept of the peasant household with spatial considerations stemming from von Thuenen. The results from the empirical model indicate that demographic characteristics of households, as well as market factors, affect deforestation in the Amazon. Thus, statistical results from studies that do not include household-scale information may be subject to error. From a policy perspective, the results suggest that environmental policies in the Amazon based on market incentives to small farmers may not be as effective as hoped, given the importance of household factors in catalyzing the demand for land. The paper concludes by noting that household decisions regarding land use and deforestation are not independent of broader social circumstances, and that a full understanding of Amazonian deforestation will require insight into why poor families find it necessary to settle the frontier in the first place.

Caldas, Marcellus↗

High-Altitude MMIC Sounding Radiometer for the Global Hawk Unmanned Aerial Vehicle

Microwave imaging radiometers operating in the 50-183 GHz range for retrieving atmospheric temperature and water vapor profiles from airborne platforms have been limited in the spatial scales of atmospheric structures that are resolved not because of antenna aperture size, but because of high receiver noise masking the small variations that occur on small spatial scales. Atmospheric variability on short spatial and temporal scales (second/ km scale) is completely unresolved by existing microwave profilers. The solution was to integrate JPL-designed, high-frequency, low-noise-amplifier (LNA) technology into the High-Altitude MMIC Sounding Radiometer (HAMSR), which is an airborne microwave sounding radiometer, to lower the system noise by an order of magnitude to enable the instrument to resolve atmospheric variability on small spatial and temporal scales. HAMSR has eight sounding channels near the 60-GHz oxygen line complex, ten channels near the 118.75-GHz oxygen line, and seven channels near the 183.31-GHz water vapor line. The HAMSR receiver system consists of three heterodyne spectrometers covering the three bands. The antenna system consists of two back-to-back reflectors that rotate together at a programmable scan rate via a stepper motor. A single full rotation includes the swath below the aircraft followed by observations of ambient (roughly 0 C in flight) and heated (70 C) blackbody calibration targets located at the top of the rotation. A field-programmable gate array (FPGA) is used to read the digitized radiometer counts and receive the reflector position from the scan motor encoder, which are then sent to a microprocessor and packed into data files. The microprocessor additionally reads telemetry data from 40 onboard housekeeping channels (containing instrument temperatures), and receives packets from an onboard navigation unit, which provides GPS time and position as well as independent attitude information (e.g., heading, roll, pitch, and yaw). The raw data files are accessed through an Ethernet port. The HAMSR data rate is relatively low at 75 kbps, allowing for real-time access over the Global Hawk high-data-rate downlink. Once on the ground, the raw data are unpacked and processed through two levels of processing. The Level 1 product contains geo-located, time-stamped, calibrated brightness temperatures for the Earth scan. These data are then input to a lD variational retrieval algorithm to produce temperature, water vapor, and cloud liquid water profiles, as well as several derived products such as potential temperature and relative humidity.

Brown, Shannon T.↗

Within‐field soil moisture variability and time‐invariant spatial structures of agricultural fields in the US Midwest

Abstract Understanding soil moisture variability and estimating high‐resolution soil moisture at subfield to field scales is critical for agricultural research and applications. However, systematic investigation of subfield scale soil moisture variability over cropland is still lacking from both measurement and satellite remote sensing. In this study, we aim to investigate (1) the characteristics of within‐field soil moisture distribution over typical cropland in the US Midwest and (2) the capabilities of satellite remote sensing in capturing the spatiotemporal variabilities of soil moisture at subfield scale. Specifically, we conducted soil moisture field experiments in three typical commercial agricultural fields (∼85 acres per field) in central Illinois, representing typical commercial farmlands in the US Midwest, and compared the soil moisture measurements with satellite remote sensing data from optical and active microwave sensors. In each field, dense soil moisture samples (spaced at 50–60 m) were obtained for two dry down events in May and July 2021, and multiple long‐term soil moisture stations were installed. We found prominent time‐invariant spatial structures of soil moisture at within‐field scales both during the dry down period and over longer time scales, and the stability is minimally affected by plant water use during the growing season. Comparing the field campaign measurements with satellite remote sensing data, we found that surface reflectance of shortwave infrared bands, such as SWIR1 (1610 nm) from Sentinel‐2, can capture relative surface soil moisture patterns at within‐field scales, but their relationships with soil moisture are field specific. These findings and the improved understanding of within‐field soil moisture dynamics could potentially help future research on high‐resolution soil moisture estimation with multi‐source remote sensing data.

Yang, Yi↗

Local-scale heterogeneity of soil thermal dynamics and controlling factors in a discontinuous permafrost region

In permafrost regions, the strong spatial and temporal variability in soil temperature cannot be explained by the weather forcing only. Understanding the local heterogeneity of soil thermal dynamics and their controls is essential to understand how permafrost systems respond to climate change and to develop process-based models or remote sensing products for predicting soil temperature. In this study, we analyzed soil temperature dynamics and their controls in a discontinuous permafrost region on the Seward Peninsula, Alaska. We acquired one-year temperature time series at multiple depths (at 5 or 10 cm intervals up to 85 cm depth) at 45 discrete locations across a 2.3 km 2 watershed. We observed a larger spatial variability in winter temperatures than that in summer temperatures at all depths, with the former controlling most of the spatial variability in mean annual temperatures. We also observed a strong correlation between mean annual ground temperature at a depth of 85 cm and mean annual or winter season ground surface temperature across the 45 locations. We demonstrate that soils classified as cold, intermediate, or warm using hierarchical clustering of full-year temperature data closely match their co-located vegetation (graminoid tundra, dwarf shrub tundra, and tall shrub tundra, respectively). We show that the spatial heterogeneity in soil temperature is primarily driven by spatial heterogeneity in snow cover, which induces variable winter insulation and soil thermal diffusivity. These effects further extend to the subsequent summer by causing variable latent heat exchanges. Finally, we discuss the challenges of predicting soil temperatures from snow depth and vegetation height alone by considering the complexity observed in the field data and reproduced in a model sensitivity analysis.

54 ENVIRONMENTAL SCIENCES↗

Composite laminates with spatially varying fiber orientations - 'Variable stiffness panel concept'

A solution has been obtained to the plane elasticity problem for a symmetrically laminated composite panel with spatially varying fiber orientations. Since variation of the fiber angles along the length of a composite laminate results in stiffness properties that change as a function of location, the laminates are called variable stiffness panels. An analysis of the stiffness variation and its effect on the elastic response of the panel is presented here. A numerical solution has been obtained using an iterative collocation technique. Corresponding closed-form solutions are given for three different sets of boundary conditions. Two of the cases considered have exact solutions and thus serve to validate the numerical model.

Guerdal, Zafer↗

Hyperspectral Imager for the Coastal Ocean (HICO): Overview, Operational Updates, and Coastal Ocean Applications

The Hyperspectral Imager for the Coastal Ocean (HICO) was built to measure in‐water properties of complex coastal regions. HICO enables synoptic coverage; 100‐meter spatial resolution for sampling the variability and spatial irregularity of coastal waters; and high spectral resolution to untangle the signals from chlorophyll, colored dissolved organic matter, suspended sediments and varying bottom types. HICO was built by the Naval Research Laboratory, installed on the International Space Station (ISS) in September 2009, and operated for ONR for the first three years. In 2013, NASA assumed sponsorship of operations in order to leverage HICO's ability to address their Earth monitoring mission. This has opened up access of HICO data to the broad research community. Over 8000 images are now available on NASA's Ocean Color Website (http://oceancolor.gsfc.nasa.gov/cgi/browse.pl?sen=hi). Oregon State University's HICO website (http://hico.coas.oregonstate.edu) remains the portal for researchers to request new collections and access their requested data. We will present updates on HICO's calibration and improvements in geolocation and show examples of the use of HICO data to address issues in the coastal ocean and Great Lakes.

Davis, Curtiss O.↗

Understanding Stellar Light Spatial Inhomogeneities and Time Variability

We would like the opportunity to thank NASA for supporting our efforts to construct tools to analyze the spectra of spatially inhomogeneous and temporally varying stellar atmospheres. This financial support has allowed us to a versatile radiative transfer code that can be used for many different applications. With this numerical code we have written a point-and-click analysis package written in IDL that can be used to look extensively at the generated output data. Below we describe the most recent results obtained with our transfer code and list papers that have appeared with these results. Although we have not been able to produce as many time-dependent calculations as we had hoped (mainly because of programmatic reasons; Sasselov took another position halfway through the grant), we believe we have

Uitenbroek, Han↗

Variability in Comet P/Swift-Tuttle

Spatial profiles of the coma of Comet P/Swift-Tuttle perpendicular to the projected Sun-comet line were obtained for the emission bands of CN, C2, and C3 as well as for two continuum bands from spectrophotometric observations taken from Oct. 5 to 8, 1992. The intensities were converted into emissivities per sq km in the cases of the continua and into column densities for the emission band profiles. Spatial and temporal variabilities have been found in all five investigated components, which are consistent with the rotational period of the nucleus determined from the observations of the comet during its last perihelion passage in 1862. The emission band profiles were fitted with the vectorial model and the production rates of CN, C2, and C3 were determined. One half of the profiles was fitted adequately under steady state conditions for the production rate in a first approximation, whereas the other half showed prominent bumps, which could only be explained by introducing a time-dependent production rate. Further investigations showed evidence for the presence of gaseous as well as dust jets in the coma, which indicated the presence of at least two active areas on the surface of the nucleus. The projected radial expansion velocities of two different features were determined to be (430 +/- 100) and (460 +/- 100) m/sec, respectively.

Schulz, Rita↗