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At least 433 records · Page 24

Spatial and Temporal Uncertainty of Crop Yield Aggregations

The aggregation of simulated gridded crop yields to national or regional scale requires information on temporal and spatial patterns of crop-specific harvested areas. This analysis estimates the uncertainty of simulated gridded yield time series related to the aggregation with four different harvested area data sets. We compare aggregated yield time series from the Global Gridded Crop Model Inter-comparison project for four crop types from 14 models at global, national, and regional scale to determine aggregation-driven differences in mean yields and temporal patterns as measures of uncertainty. The quantity and spatial patterns of harvested areas differ for individual crops among the four datasets applied for the aggregation. Also simulated spatial yield patterns differ among the 14 models. These differences in harvested areas and simulated yield patterns lead to differences in aggregated productivity estimates, both in mean yield and in the temporal dynamics. Among the four investigated crops, wheat yield (17% relative difference) is most affected by the uncertainty introduced by the aggregation at the global scale. The correlation of temporal patterns of global aggregated yield time series can be as low as for soybean (r = 0.28).For the majority of countries, mean relative differences of nationally aggregated yields account for10% or less. The spatial and temporal difference can be substantial higher for individual countries. Of the top-10 crop producers, aggregated national multi-annual mean relative difference of yields can be up to 67% (maize, South Africa), 43% (wheat, Pakistan), 51% (rice, Japan), and 427% (soybean, Bolivia).Correlations of differently aggregated yield time series can be as low as r = 0.56 (maize, India), r = 0.05∗Corresponding (wheat, Russia), r = 0.13 (rice, Vietnam), and r = −0.01 (soybean, Uruguay). The aggregation to sub-national scale in comparison to country scale shows that spatial uncertainties can cancel out in countries with large harvested areas per crop type. We conclude that the aggregation uncertainty can be substantial for crop productivity and production estimations in the context of food security, impact assessment, and model evaluation exercises.

Aggregation uncertainty↗

Use of In Situ and Airborne Multiangle Data to Assess MODIS and Landsat-Based Estimates of Directional Reflectance and Albedo

The quantification of uncertainty in satellite-derived global surface albedo products is a critical aspect in producing complete, physically consistent, and decadal land property data records for studying ecosystem change. A challenge in validating albedo measurements acquired from space is the ability to overcome the spatial scaling errors that can produce disagreements between satellite and field-measured values. Here, we present the results from an accuracy assessment of MODIS and Landsat-TM albedo retrievals, based on collocated comparisons with tower and airborne Cloud Absorption Radiometer (CAR) measurements collected during the 2007 Cloud and Land Surface Interaction Campaign (CLASIC). The initial focus was on evaluating intersensor consistency through comparisons of intrinsic bidirectional reflectance estimates. Local and regional assessments were then performed to obtain estimates of the resulting scaling uncertainties, and to establish the accuracy of albedo reconstructions during extended periods of precipitation. In general, the satellite derived estimates met the accuracy requirements established for the high-quality MODIS operational albedos at 500 m (the greater of 0.02 units or +/-10% of surface measured values). However, results reveal a high degree of variability in the root-mean-square error (RMSE) and bias of MODIS visible (0.3-0.7 μm) and Landsat-TM shortwave (0.3-5.0 μm) albedos; where, in some cases, retrieval uncertainties were found to be in excess of 15%. Results suggest that an overall improvement in MODIS shortwave albedo retrieval accuracy of 7.8%, based on comparisons between MODIS and CAR albedos, resulted from the removal of sub-grid scale mismatch errors when directly scaling-up the tower measurements to the MODIS satellite footprint.

biosphere↗

New numerical solutions of three-dimensional compressible hydrodynamic convection

Numerical solutions of three-dimensional compressible hydrodynamics (including sound waves) in a stratified medium with open boundaries are presented. Convergent/divergent points play a controlling role in the flows, which are dominated by a single frequency related to the mean sound crossing time. Superposed on these rapid compressive flows, slower eddy-like flows eventually create convective transport. The solutions contain small structures stacked on top of larger ones, with vertical scales equal to the local pressure scale heights, H sub p. Although convective transport starts later in the evolution, vertical scales of H sub p are apparently selected at much earlier times by nonlinear compressive effects.

Hossain, Murshed↗

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's High-Resolution GEOS Forecasting and Reanalysis Products: A Unified Tool from Local to Global Scales

NASA's GMAO produces high-resolution global forecasts for weather, aerosols, and air quality. The NASA Global Earth Observing System (GEOS) model has been expanded to provide global near-real-time 5-day forecasts of atmospheric chemical composition at unprecedented horizontal resolution of 0.25 degrees (~25 km), freely available to the public. This composition forecast system (GEOS-CF) combines the operational GEOS weather forecasting model with the state-of-the-science GEOS-Chem chemistry module to provide detailed analysis of a wide range of air pollutants such as ozone, carbon monoxide, nitrogen oxides, and fine particulate matter (PM2.5). GEOS-CF also assimilated satellite observations into the system for improved representation of weather and smoke. The assimilation system is currently being expanded to include chemically reactive trace gases. While the main focus of this new product is on tropospheric air quality information, the GEOS-Chem chemistry model used in this system includes the unified tropospheric stratospheric chemistry mechanism for improved forecasts of total column ozone during anomalous dynamical and chemical events. I will discuss current capabilities of the GEOS Constituent Data Assimilation System (CoDAS) to improve atmospheric composition modeling and possible future directions for GEOS-CF and reanalysis products. In addition, I will show how machine learning techniques can be used to correct for sub-grid-scale variability, which further improves model estimates at a given observation site.

Co-DAS↗

Improved Understanding of the Modeled QBO Using MLS Observations and MERRA Reanalysis

The Quasi-Biennial Oscillation (QBO) dominates the variability of the tropical stratosphere on interannual time scales. The QBO has been shown to extend its influence into the chemical composition of this region through dynamical mechanisms. We have started our analysis using the realistic QBO internally generated by the Goddard Earth Observing System Version 5 (GEOS-5) general circulation model coupled to a comprehensive stratospheric and tropospheric chemical mechanism forced with observed sea surface temperatures over the past 33 years. We will show targeted comparisons with observations from NASAs Aura satellite Microwave Limb Sounder (MLS) and the Modern Era Retrospective-Analysis for Research and Applications (MERRA) reanalysis to provide insight into the simulation of the primary and secondary circulations associated with the QBO. Using frequency spectrum analysis and multiple linear regression we can illuminate the resulting circulations and deduce the strengths and weaknesses in their modeled representation. Inclusion of the QBO in our simulation improves the representation of the subtropical barriers and overall tropical variability. The QBO impact on tropical upwelling is important to quantify when calculating trends in sub-decadal scale datasets.

MERRA↗

A proposed experimental test to distinguish waves from 2-D turbulence

A theory of buoyancy range turbulence that leads to a unique scale, K sub B, that allows one to differentiate between waves and turbulence for the special case of theta = 0 (i.e., horizontally propagating waves) is discussed. The theory does not seem to lead to a practical empirical distinction for the general situation. This is due to the fact that, as theta is increased, one has the ever-increasing presence of BRT for longer wavelengths. The fact that the numerical values of epsilon prime are not yet available compounds the difficulty. In addition, it does not appear possible to encompass true 2-D turbulence in the theory. We are thus driven to a test which circumvents all these difficulties. A proposed test is based on the idea that waves are coherent and propagate, while in turbulence we have the opposite situation. In particular, the test is suggested by the following quotation from MULLER (1984), on the nature of such turbulence: The turbulence in each horizontal plane is independent from the turbulence in the other planes. If this statement were to be taken literally, it would imply that the temporal coherence between horizontal speeds, separated only in altitude, would be zero. Any vertical separation would be forced to take into account the effects of viscosity: that is to say, a specific finite vertical separation would be needed to destroy coherence. In order to estimate this distance, L, one can use L = C(v/S) (1/2) were v is the kinematic viscosity, S is the shear scale, and C is a constant of order unity.

Dewan, E. M.↗

New Measurements of the Cosmic Infrared Background Fluctuations in Deep SpitzerllRAC Survey Data and their Cosmological Implications

We extend the previous measurements of CIB fluctuations to angular scales of less than or equal to 1 degree new data obtained in the course of the 2,000+ hour Spitzer Extended Deep Survey. Two fields with completed observations of approximately equal to 12 hr/pixel are analyzed for source-subtracted CIB fluctuations at 3.6 and 4.5 micrometers. The fields, EGS and UDS, cover a total area of approximately 0.25 deg and lie at high Galactic and Ecliptic latitudes, thus minimizing cirrus and zodiacal light contributions to the fluctuations. The observations have been conducted at 3 distinct epochs separated by about 6 months. As in our previous studies, the fields were assembled using the self-calibration method which is uniquely suitable for probing faint diffuse backgrounds. The assembled fields were cleaned off the bright sources down to the low shot noise levels corresponding to AB mag approximately equal to 25, Fourier-transformed and their power spectra evaluated. The noise was estimated from the time-differenced data and subtracted from the signal isolating the fluctuations remaining above the noise levels. The power spectra of the source-subtracted fields remain identical (within the observational uncertainties) for the three epochs of observations indicating that zodiacal light contributes negligibly to the fluctuations. By comparing to the measurements for the same regions at 8 micrometers we demonstrate that Galactic cirrus cannot account for the levels of the fluctuations either. The signal appears isotropically distributed on the sky as required by its origin in the CIB fluctuations. This measurement thus extends our earlier results to the important range of sub-degree scales. We find that the CIB fluctuations continue to diverge to more than 10 times those of known galaxy populations on angular scales out to less than or equal to 1 degree. The low shot noise levels remaining in the diffuse maps indicate that the large scale fluctuations arise from spatial clustering of faint sources well within the confusion noise. The spatial spectrum of these fluctuations is in reasonable agreement with simple fitting assuming that they originate in early populations spatially distributed according to the standard cosmological model (ACDM) at epochs coinciding with the first stars era. The alternative to this identification would require a new population never observed before, nor expected on theoretical grounds, but if true this would represent an important discovery in its own right.

Kashlinsky, A.↗

Explicit 3D continuum fracture modeling with smooth particle hydrodynamics

Impact phenomena shaped our solar system. As usual for most solar system processes, the scales are far different than we can address directly in the laboratory. Impact velocities are often much higher than we can achieve, sizes are often vastly larger, and most impacts take place in an environment where the only gravitational force is the mutual pull of the impactors. The Smooth Particle Hydrodynamics (SPH) technique has been applied in the past to the simulations of giant impacts. In these simulations, the colliding objects were so massive (at least a sizeable fraction of the Earth's mass) that material strength was negligible compared to gravity. This assumption can no longer be made when the bodies are much smaller. To this end, we have developed a 3D SPH code that includes a strength model to which we have added a von Mises yielding relation for stresses beyond the Hugoniot Elastic Limit. At the lower stresses associated with brittle failure, we use a rate-dependent strength based on the nucleation of incipient flaws whose number density is given by a Weibull distribution. Following Grady and Kipp and Melosh et al., we introduce a state variable D ('damage'), 0 less than D less than 1, which expresses the local reduction in strength due to crack growth under tensile loading. Unfortunately for the hydrodynamics, Grady and Kipp's model predicts which fragments are the most probable ones and not the ones that are really formed. This means, for example, that if a given laboratory experiment is modeled, the fragment distribution obtained from the Grady-Kipp theory would be equivalent to a ensemble average over many realizations of the experiment. On the other hand, the hydrodynamics itself is explicit and evolves not an ensemble average but very specific fragments. Hence, there is a clear incompatibility with the deterministic nature of the hydrodynamics equations and the statistical approach of the Grady-Kipp dynamical fracture model. We remedy these shortcomings by making the incipient flaw distribution explicit, i.e., particles carry activation strains which are distributed at random with a probability of occurrence given by the Weibull distribution. If the local principal axis strain exceeds this limit, damage starts to grow. By growing explicit cracks together with statistical cracks (damage) at the sub-particle scale, we ensure that material strength and fragmentation is independent of model resolution. We tested our scheme by simulating laboratory impact experiments on basalt spheres.

Benz, W.↗

Nonlinear Dynamics and Nucleation Kinetics in Near-Critical Liquids

The objective of our study is to model the nonlinear behavior of a near-critical liquid following a rapid change of the temperature and/or other thermodynamic parameters (pressure, external electric or gravitational field). The thermodynamic critical point is manifested by large, strongly correlated fluctuations of the order parameter (particle density in liquid-gas systems, concentration in binary solutions) in the critical range of scales. The largest critical length scale is the correlation radius r(sub c). According to the scaling theory, r(sub c) increases as r(sub c) = r(sub 0)epsilon(exp -alpha) when the nondimensional distance epsilon = (T - T(sub c))/T(sub c) to the critical point decreases. The normal gravity alters the nature of correlated long-range fluctuations when one reaches epsilon approximately equal to 10(exp -5), and correspondingly the relaxation time, tau(r(sub c)), is approximately equal to 10(exp -3) seconds; this time is short when compared to the typical experimental time. Close to the critical point, a rapid, relatively small temperature change may perturb the thermodynamic equilibrium on many scales. The critical fluctuations have a hierarchical structure, and the relaxation involves many length and time scales. Above the critical point, in the one-phase region, we consider the relaxation of the liquid following a sudden temperature change that simultaneously violates the equilibrium on many scales. Below T(sub c), a non-equilibrium state may include a distribution of small scale phase droplets; we consider the relaxation of such a droplet following a temperature change that has made the phase of the matrix stable.

Patashinski, Alexander Z.↗

Gravity-wave spectra in the atmosphere observed by MST radar, part 4.2B

A universal spectrum of atmospheric buoyancy waves is proposed based on data from radiosonde, Doppler navigation, not-wire anemometer and Jimsphere balloon. The possible existence of such a universal spectrum clearly will have significant impact on several areas in the study of the middle atmosphere dynamics such as the parameterization of sub-grid scale gravity waves in global circulation models; the transport of trace constituents and heat in the middle atmosphere, etc. Therefore, it is important to examine more global wind data with temporal and spatial resolutions suitable for the investigation of the wave spectra. Mesosphere-stratosphere-troposphere (MST) radar observations offer an excellent opportunity for such studies. It is important to realize that radar measures the line-of-sight velocity which, in general, contains the combination of the vertical and horizontal components of the wave-associated particle velocity. Starting from a general oblique radar observation configuration, applying the dispersion relation for the gravity waves, the spectrum for the observed fluctuations in the line-of-sight gravity-wave spectrum is investigated through a filter function. The consequence of the filter function on data analysis is discussed.

Scheffler, A. O.↗

Atmospheric waves and the nature of buoyancy turbulence in the context of the waves VS 2D-turbulence debate

The problem of how to empirically distinguish between velocity fluctuations due to turbulence and those due to atmospheric waves is addressed. The physical differences between waves and turbulence are reviewed. New theoretical ideas on the subject of bouyancy range turbulence are presented. A unique scale K sub B is given that allows one to differentiate between waves and turbulence for the special case of theta = 0 (i.e., horizontal propagating waves).

Dewan, E. M.↗

Deep convection in mesoscale convective systems

A study was undertaken to examine the evolution of radar echoes and lightning attending the convective storms in mesoscale convective systems (MCS) and the relationships between the spatial and temporal evolution of deep convection and the storm environment, precipitation, severe weather, and lightning. The total number of ground discharges ranges from 10,000 to 30,000 over the life cycle of the MCS with peak sustained rates (for up to 10 consecutive hours) in excess of 2000 per hour. The peak lightning activity occurs from 5 to 20 hours after the first storms and anywhere from 7 hours prior to 7 hours after the time of the maximum areal extent of the MCS for very similar synoptic environments. Thus, it appears that mesoscale and sub-synoptic scale mechanisms are responsible for these large temporal variation in lightning activity. In addition, we have found that the lightning rates in MCS's are not related to either the size or the duration of the MCS. Preliminary results suggest that the MCA's with embedded squall lines produce the greatest flash rates.

Goodman, S. J.↗

Cooperative VAS program with NASA Marshall Space Flight Center

The importance of mesoscale moisture information in the forecasting of weather events is discussed. A test is being prepared with the March 6, 1982 Vertical Atmospheric Sounder/Atmospheric Variability Experiment (VAS/AVE) case study to be run on the sub-synoptic scale model (SSM). Model intracomparison of three carefully designed simulations should isolate the role of mesoscale information in the initial conditions for both mositure and vertical motion. Three simulations will be made for the period 1200Z 6 March to 0000Z 7 March starting with the regular synoptic time data of 1200Z. The distinction between the three cases arises from data manipulation at 1800Z midway through the forecast period: (1) Control Case: no alterations at 1800Z. (2) Moisture Information Suppression: at 1800Z the model simulation field for water vapor, which by this time contains considerable mesoscale structure, is replaced by a smoothed version from which the mesoscale structure has been eliminated. No other variables are structure altered. (3) Vertical Motion Information Suppression: at 1800Z the model is subjected to a dead start procedure which primarily imposes a nondivergent constraint of the horizontal motion field field suppressing vertical motion. The main effect is to eliminate the mesoscale component. Comparison of results for the 1800Z to 0000Z time period will give the information desired.

Houghton, D. D.↗

Cascade model of coronal heating

It is suggested that the quasi-static evolution of coronal magnetic structures is characterized by a cascade of magnetic energy to smaller length scales. This cascade process takes place on a time scale t sub b determined entirely by the photospheric motions. The Ohmic heating rate E sub H in the statistically stationary state was estimated using observational data on the diffusivity of photospheric motions; E sub H turned out to be too small by a factor of 40 when compared with observed coronal energy losses. However, given the fact that the theoretical estimate is based on a rather uncertain extrapolation to the diffusive regime, current heating cannot be ruled out as a viable mechanism of coronal heating.

Vanballegooijen, A. A.↗

Systematic estimation of forecast and observation error covariances in four-dimensional data assimilation

A two-part algorithm is presented for reliably computing weather forecast model and observational error covariances during data assimilation. Data errors arise from instrumental inaccuracies and sub-grid scale variability, whereas forecast errors occur because of modeling errors and the propagation of previous analysis errors. A Kalman filter is defined as the primary algorithm for estimating the forecast and analysis error convariance matrices. A second algorithm is described for quantifying the noise covariance matrices of any degree to obtain accurate values for the observational error covariances. Numerical results are provided from a linearized one-dimensional shallow-water model. The results cover observational noise covariances, initial instrumental errors and erroneous model values.

Dee, D. P.↗

Distribution of tessera terrain on Venus - Prediction for Magellan

Tessera terrain is the dominant tectonic unit in the northern hemisphere of Venus and is characterized by complex sets of intersecting structural trends and distinctive radar properties due to a high degree of meter and sub-meter scale (5 cm to 10 m) roughness. Based on these distinctive radar properties, a prediction of the global distribution of tessera can be made using Pioneer Venus (PV) reflectivity and roughness data. Where available, Benera 15/16 and Arecibo images and PV diffuse scattering data were used to evaluate the prediction. From this assessment, it is concluded that most of the regions with prediction values greater than 0.6 (out of 1) are likely to be tessera, and are almost certain to be techonically deformed.

Bindschadler, D. L.↗

Turbulent thermal convection in a differentially rotating channel

Differentially rotating disks of gases and solids occur in several astrophysical systems, in particular in the inner parts of protostellar nebulae, of which our own solar system is thought to be a relic. The objectives of this paper are to: (1) study localized turbulence in circumstances approximating those found in accretion disks using previously existing expertise in performing direct numerical simulation of turbulent, incompressible channel flows with low Reynolds numbers; (2) determine the limitations of such calculations; and (3) extend the type of numerical simulation (e.g., to include density and stratification and compressibility effects and to accommodate higher Reynolds numbers with sub-grid scale modeling) so that the relevant physical effects are realistically captured.

Cabot, W.↗