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At least 163 records · Page 9

Total ozone trend significance from space time variability of daily Dobson data

Estimates of standard errors of total ozone time and area means, as derived from ozone's natural temporal and spatial variability and autocorrelation in middle latitudes determined from daily Dobson data are presented. Assessing the significance of apparent total ozone trends is equivalent to assessing the standard error of the means. Standard errors of time averages depend on the temporal variability and correlation of the averaged parameter. Trend detectability is discussed, both for the present network and for satellite measurements.

Wilcox, R. W.↗

Cloud cover archiving on a global scale - A discussion of principles

Monitoring of climatic variability and climate modeling both require a reliable global cloud data set. Examination is made of the temporal and spatial variability of cloudiness in light of recommendations made by GARP in 1975 (and updated by JOC in 1978 and 1980) for cloud data archiving. An examination of the methods of comparing cloud cover frequency curves suggests that the use of the beta distribution not only facilitates objective comparison, but also reduces overall storage requirements. A specific study of the only current global cloud climatology (the U.S. Air Force's 3-dimensional nephanalysis) over the United Kingdom indicates that discussion of methods of validating satellite-based data sets is urgently required.

Henderson-Sellers, A.↗

Automated Identification and Differentiation of Spectrally Similar Hydrothermal Minerals on Mars

Early telescopic observations corroborated hydration related absorptions on Mars in the infrared. Images from the Viking missions led to speculation of hydrothermal alteration and were followed by two missions which mapped the spatial variability of the ~ 3 μm hydration feature. Since then, the Compact Reconnaissance Imager for Mars (CRISM) has provided high spatial resolution (up to 18m) spectral identification of a suite of hydrothermal and diagenetic minerals which have illuminated a range of formation mechanisms. Presence/absence and spatial segregation or mixing of minerals like prehnite, epidote, chlorite amphiboles, and mixed-layer Fe/Mg smectite-chlorite provide valuable evidence for the geologic setting of deposits on Earth, and these phases are often used as temperature and aqueous chemistry indicators in terrestrial systems. Mapping the distribution of these phases will help to answer whether Mars had widespread conditions favorable for low-grade metamorphism and diagenesis, or only focused hydrothermal systems in areas of high heat flow. Further characterizing the chemistry and structure of these phases will then help to answer how most of the widespread Fe/Mg phyllosilicates formed, further defining early geochemical cycling and climate. A fully automated approach for accurate mapping of important hydrothermal mineral phases on Mars has been a challenge. Due to overlapping features in the M-OH region (~2.2-2.4 μm), the strongest absorption features of chlorite, prehnite, and epidote in the short-wave infrared are difficult to distinguish from one another and from the most commonly occurring hydrated silicates on Mars, Fe/Mg smectites. Weaker absorptions are present in both prehnite and epidote which help to distinguish them from chlorite and smectites, but their relative strength in the presence of noise and spatial mixing is often too low to confidently identify them without the noise suppression and feature enhancement methods described here. The spectral signatures of mixed-layer Fe/Mg smectite-chlorite and partially chloritized Fe/Mg smectites have not yet been adequately assessed. Here we evaluate the effectiveness of two empirical and statistical methods for identifying and differentiating these phases using CRISM data.

Rasmussen, B. P.↗

Potential of GPM IMERG Precipitation Estimates to Monitor Natural Disaster Triggers in Urban Areas: the Case of Rio deJaneiro, Brazil

Extreme rainfall can be a catastrophic trigger for natural disaster events at urban scales. However, there remains large uncertainties as to how satellite precipitation can identify these triggers at a city scale. The objective of this study is to evaluate the potential of satellite-based rainfall estimates to monitor natural disaster triggers in urban areas. Rainfall estimates from the Global Precipitation Measurement (GPM) mission are evaluated over the city of Rio de Janeiro, Brazil, where urban floods and landslides occur periodically as a result of extreme rainfall events. Two rainfall products derived from the Integrated Multi-satellite Retrievals for GPM (IMERG), the IMERG Early and IMERG Final products, are integrated into the Noah Multi-Parameterization (Noah-MP) land surface model in order to simulate the spatial and temporal dynamics of two key hydrometeorological disaster triggers across the city over the wet seasons during 2001-2019. Here, total runoff (TR) and rootzone soil moisture (RZSM) are considered as flood and landslide triggers, respectively. Ground-based observations at 33 pluviometric stations are interpolated, and the resulting rainfall fields are used in an in-situ precipitation-based simulation, considered as the reference for evaluating the IMERG-driven simulations. The evaluation is performed during the wet seasons (November-April), when average rainfall over the city is 4.4mm/day. Results show that IMERG products show low spatial variability at the city scale, generally overestimate rainfall rates by 12-35%, and impacts on TR and RZSM vary spatially mostly as a function of land cover and soil types. Results based on statistical and categorical metrics show that IMERG skill in detecting extreme events is moderate, with IMERG Final performing slightly better for most metrics. By analyzing two recent storms, we observe that IMERG detects mostly hourly extreme events, but underestimates rainfall rates, resulting in underestimated TR and RZSM. An evaluation of normalized time series using percentiles shows that both satellite products have significantly improved skill in detecting extreme events when compared to the evaluation using absolute values, indicating that IMERG precipitation could be potentially used as a predictor for natural disasters in urban areas.

IMERG↗

A 3D High-Order Unstructured Finite-Volume Algorithm for Solving Maxwell's Equations

A three-dimensional finite-volume algorithm based on arbitrary basis functions for time-dependent problems on general unstructured grids is developed. The method is applied to the time-domain Maxwell equations. Discrete unknowns are volume integrals or cell averages of the electric and magnetic field variables. Spatial terms are converted to surface integrals using the Gauss curl theorem. Polynomial basis functions are introduced in constructing local representations of the fields and evaluating the volume and surface integrals. Electric and magnetic fields are approximated by linear combinations of these basis functions. Unlike other unstructured formulations used in Computational Fluid Dynamics, the new formulation actually does not reconstruct the field variables at each time step. Instead, the spatial terms are calculated in terms of unknowns by precomputing weights at the beginning of the computation as functions of cell geometry and basis functions to retain efficiency. Since no assumption is made for cell geometry, this new formulation is suitable for arbitrarily defined grids, either smooth or unsmooth. However, to facilitate the volume and surface integrations, arbitrary polyhedral cells with polygonal faces are used in constructing grids. Both centered and upwind schemes are formulated. It is shown that conventional schemes (second order in Cartesian grids) are equivalent to the new schemes using first degree polynomials as the basis functions and the midpoint quadrature for the integrations. In the new formulation, higher orders of accuracy are achieved by using higher degree polynomial basis functions. Furthermore, all the surface and volume integrations are carried out exactly. Several model electromagnetic scattering problems are calculated and compared with analytical solutions. Examples are given for cases based on 0th to 3rd degree polynomial basis functions. In all calculations, a centered scheme is applied in the interior, while an upwind matching scheme is employed at material interfaces and the Engquist-Majda non-reflecting boundary condition is implemented at the numerical outer boundaries. The staggered leapfrog scheme and the Runge-Kutta methods are utilized for the time integration. Excellent agreements are found between the numerical and analytical solutions.

Liu, Yen↗

Statistical and Scaling Properties of Remotely-Sensed Soil Moisture in Two Contrasting Domains in the North American Monsoon Region

Characterizing soil moisture (theta) variability is important for inferring high-resolution information from coarse estimates provided by remote sensors. In this study, we analyze the spatial variability and scale invariance of high-resolution theta estimates collected in two contrasting semiarid areas, Arizona (AZ) and Sonora (SON), during the Soil Moisture Experiment - North American Monsoon in 2004 (SMEX04- NAME). Results reveal that as the mean theta condition ( ) becomes drier, the spatial standard deviation becomes smaller in both domains. The coefficient of variation of theta decreases with in SON, but does not display a clear tendency with in AZ. We also found the presence of scale invariance and multifractality in the range of support scales from 51.2 km to 0.8 km for all soil moisture fields in the two regions. The multifractal properties of theta are clearly linked to in SON, while the relation is affected by more dispersion in AZ. We argue this is due to differences in the dynamic (rainfall) and static (vegetation) controls on theta in the two domains.

Mascaro, Giuseppe↗

The two-dimensional diagnostic model for tropospheric OH - An uncertainty analysis

Tropospheric OH is believed to play a major role in atmospheric photochemistry, and, via its chemical interactions OH ultimately may affect the climate, stratospheric ozone levels, and the pH of rain. A valuable tool for predicting the global OH abundance as a function of latitude and altitude is the two-dimensional diagnostic model for tropospheric OH. This model can also be applied to budget studies of species which interact with OH, such as CH4, CO, and O3. In addition to laboratory-obtained kinetic data, important variables include the rate constants for several reactions, the rate of heterogeneous removal of soluble species, and the global abundance and spatial variability in H2O, O3, CO, and NOx. The uncertainties in these parameters imply over a factor of 3 variability in the calculated global OH concentration as well as significant uncertainties in the latitudinal and vertical OH distribution.

Chameides, W. L.↗

Prediction and experimental observation of damage dependent damping in laminated composite beams

The equations of motion are developed for laminated composite beams with load-induced matrix cracking. The damage is accounted for by utilizing internal state variables. The net result of these variables on the field equations is the introduction of both enhanced damping, and degraded stiffness. Both quantities are history dependent and spatially variable, thus resulting in nonlinear equations of motion. It is explained briefly how these equations may be quasi-linearized for laminated polymeric composites under certain types of structural loading. The coupled heat conduction equation is developed, and it is shown that an enhanced Zener damping effect is produced by the introduction of microstructural damage. The resulting equations are utilized to demonstrate how damage dependent material properties may be obtained from dynamic experiments. Finaly, experimental results are compared to model predictions for several composite layups.

Allen, D. H.↗

Modeling and parameterization of horizontally inhomogeneous cloud radiative properties

One of the fundamental difficulties in modeling cloud fields is the large variability of cloud optical properties (liquid water content, reflectance, emissivity). The stratocumulus and cirrus clouds, under special consideration for FIRE, exhibit spatial variability on scales of 1 km or less. While it is impractical to model individual cloud elements, the research direction is to model a statistical ensembles of cloud elements with mean-cloud properties specified. The major areas of this investigation are: (1) analysis of cloud field properties; (2) intercomparison of cloud radiative model results with satellite observations; (3) radiative parameterization of cloud fields; and (4) development of improved cloud classification algorithms.

Welch, R. M.↗

Spatial and Temporal Variability of Satellite-Derived Cloud and Surface Characteristics During FIRE-ACE

Advanced very high resolution radiometer (AVHRR) products calculated for the western Arctic for April-July 1998 are used to investigate spatial, temporal, and regional patterns and variability in energy budget parameters associated with ocean- ice-atmosphere interactions over the Arctic Ocean during the Surface Heat Budget of the Arctic Ocean (SHEBA) project and the First ISCCP (International Satellite Cloud Climatology Project) Regional Experiment - Arctic Cloud Experiment (FIRE-ACE). The AVHRR-derived parameters include cloud fraction, clear-sky and all-sky skin temperature and broadband albedo, upwelling and downwelling shortwave and longwave radiation, cloud top pressure and temperature, and cloud optical depth. The remotely sensed products generally agree well with field observations at the SHEBA site, which in turn is shown to be representative of a surrounding region comparable in size to a climate-model grid cell. Time series of products for other locations in the western Arctic illustrate the magnitude of spatial variability during the study period and provide spatial and temporal detail useful for studying regional processes. The data illustrate the progression of reduction in cloud cover, albedo decrease, and the considerable heating of the open ocean associated with the anomalous decrease in sea ice cover in the eastern Beaufort Sea that began in late spring. Above-freezing temperatures are also recorded within the ice pack, suggesting warming of the open water areas within the ice cover.

Maslanik, J. A.↗

The global structure of the annual and semiannual sea surface height variability from Geosat altimeter data

Two years of data from the Geosat Exact Repeat Mission are employed to study the annual and semiannual variability of sea-surface height on a global basis. The data are treated with atmospheric corrections and interpolations, and the orbit error of about 40 cm RMS is purged. The spatial variability of the Geosat data is constructed for particular frequencies, and the estimate of the M2 tidal error indicates that the error is aliased to 1.15 cycles/yr and has an unusual spatial pattern. Sine and cosine coefficients are derived for the annual and semiannual frequencies by means of a least squares fit yielding the amplitude and phase of the changes in sea-surface height. A 180-deg phase difference is noted between the Northern and Southern Hemispheres for the annual variability, and large-scale westward propagating waves are identified. The Geosat data also indicate the phase relationships between major current systems and the systems of variations at work in the Intertropical Convergence Zone.

Jacobs, Gregg A.↗

Aerosol in the Pacific troposphere

The use of near real-time optical techniques is emphasized for the measurement of mid-tropospheric aerosol over the Central Pacific. The primary focus is on measurement of the aerosol size distribution over the range of particle diameters from 0.15 to 5.0 microns that are essential for modeling CO2 backscatter values in support of the laser atmospheric wind sounder (LAWS) program. The measurement system employs a LAS-X (Laser Aerosol Spectrometer-PMS, Boulder, CO) with a custom 256 channel pulse height analyzer and software for detailed measurement and analysis of aerosol size distributions. A thermal preheater system (Thermo Optic Aerosol Descriminator (TOAD) conditions the aerosol in a manner that allows the discrimination of the size distribution of individual aerosol components such as sulfuric acid, sulfates and refractory species. This allows assessment of the relative contribution of each component to the BCO2 signal. This is necessary since the different components have different sources, exhibit independent variability and provide different BCO2 signals for a given mass and particle size. Field activities involve experiments designed to examine both temporal and spatial variability of these aerosol components from ground based and aircraft platforms.

Clarke, Antony D.↗

Ocean time-series near Bermuda: Hydrostation S and the US JGOFS Bermuda Atlantic time-series study

Bermuda is the site of two ocean time-series programs. At Hydrostation S, the ongoing biweekly profiles of temperature, salinity and oxygen now span 37 years. This is one of the longest open-ocean time-series data sets and provides a view of decadal scale variability in ocean processes. In 1988, the U.S. JGOFS Bermuda Atlantic Time-series Study began a wide range of measurements at a frequency of 14-18 cruises each year to understand temporal variability in ocean biogeochemistry. On each cruise, the data range from chemical analyses of discrete water samples to data from electronic packages of hydrographic and optics sensors. In addition, a range of biological and geochemical rate measurements are conducted that integrate over time-periods of minutes to days. This sampling strategy yields a reasonable resolution of the major seasonal patterns and of decadal scale variability. The Sargasso Sea also has a variety of episodic production events on scales of days to weeks and these are only poorly resolved. In addition, there is a substantial amount of mesoscale variability in this region and some of the perceived temporal patterns are caused by the intersection of the biweekly sampling with the natural spatial variability. In the Bermuda time-series programs, we have added a series of additional cruises to begin to assess these other sources of variation and their impacts on the interpretation of the main time-series record. However, the adequate resolution of higher frequency temporal patterns will probably require the introduction of new sampling strategies and some emerging technologies such as biogeochemical moorings and autonomous underwater vehicles.

Michaels, Anthony F.↗

Municipality Level Simulations of Dengue Fever Incidence in Puerto Rico Using Ground Based and Remotely Sensed Climate Data

Dengue fever (DF) is caused by a virus transmitted between humans and Aedes genus mosquitoes through blood feeding. In recent decades incidence of the disease has drastically increased in the tropical Americas, culminating with the Pan American outbreak in 2010 which resulted in 1.7 million reported cases. In Puerto Rico dengue is endemic, however, there is significant inter‐annual, intraannual, and spatial variability in case loads. Variability in climate and the environment, herd immunity and virus genetics, and demographic characteristics may all contribute to differing patterns of transmission both spatially and temporally. Knowledge of climate influences on dengue incidence could facilitate development of early warning systems allowing public health workers to implement appropriate transmission intervention strategies. In this study, we simulate dengue incidence in several municipalities in Puerto Rico using population and meteorological data derived from ground based stations and remote sensing instruments. This data was used to drive a process based model of vector population development and virus transmission. Model parameter values for container composition, vector characteristics, and incubation period were chosen by employing a Monte Carlo approach. Multiple simulations were performed for each municipality and the results were compared with reported dengue cases. The best performing simulations were retained and their parameter values and meteorological input were compared between years and municipalities. Parameter values varied by municipality and year illustrating the complexity and sensitivity of the disease system. Local characteristics including the natural and built environment impact transmission dynamics and produce varying responses to meteorological conditions.

Remote Sensing↗

A preliminary study of the variability and magnitude of the flux of biogenic sulfur gases from a New Hampshire salt marsh

Salt marshes have highly variable spatial and temporal fluxes of hydrogen sulfide, carbonyl sulfide, methane thiol, dimethyl sulfide, and carbon disulfide (H2S, COS, MeSH, DMS, and CS2, respectively). This variability was tested at nine emission sites in a New Hampshire, USA salt marsh: three replicates in each of three vegetation zones, Spartina alterniflora, S. patens, and a transition zone. Three sites were sampled simultaneously, either within or across vegetation zones, using a dynamic flux chamber technique. Difficulties with calibration and field equipment resulted in fluxes with maximum absolute uncertainties of greater than plus or minus 200 percent. However, the relative uncertainty between subsequent samples was closer to plus or minus 20 percent. Chambers are expected to affect the natural flux of gases by altering the humidity, temperature, and composition of the gas inside the chamber. Summertime fluxes are highest for all gases except COS which demonstrated evidence of a springtime peak. A summertime background flux of 5 to 100 x 10(exp -9) g S/m(sup -2) min was observed for all gases, while S alternifora fluxes of MeSH and DMS were approximately 8 fold and approximately 100 fold higher than S. patens, respectively. DMS and MeSH fluxes were higher during the day than at night. Evidence of COS uptake by plants was observed. CS2 appeared to be the quantitatively least important sulfur gas emitted. Improved laboratory and sample collection techniques and further data collection in the field will yield information on the details of salt marsh variability, will improve estimates of the error associated with single flux measurements, and will allow a more accurate estimation of sulfur fluxes from salt marshes based on vegetation and area coverage data. Inability to control the temperature and humidity inside of the chamber remain significant problems with the chamber design.

Morrison, Michael Cope↗

CHAMP - Camera, Handlens, and Microscope Probe

CHAMP (Camera, Handlens And Microscope Probe) is a novel field microscope capable of color imaging with continuously variable spatial resolution from infinity imaging down to diffraction-limited microscopy (3 micron/pixel). As an arm-mounted imager, CHAMP supports stereo-imaging with variable baselines, can continuously image targets at an increasing magnification during an arm approach, can provide precision range-finding estimates to targets, and can accommodate microscopic imaging of rough surfaces through a image filtering process called z-stacking. Currently designed with a filter wheel with 4 different filters, so that color and black and white images can be obtained over the entire Field-of-View, future designs will increase the number of filter positions to include 8 different filters. Finally, CHAMP incorporates controlled white and UV illumination so that images can be obtained regardless of sun position, and any potential fluorescent species can be identified so the most astrobiologically interesting samples can be identified.

Mungas, G. S.↗

CHAMP (Camera, Handlens, and Microscope Probe)

CHAMP (Camera, Handlens And Microscope Probe)is a novel field microscope capable of color imaging with continuously variable spatial resolution from infinity imaging down to diffraction-limited microscopy (3 micron/pixel). As a robotic arm-mounted imager, CHAMP supports stereo imaging with variable baselines, can continuously image targets at an increasing magnification during an arm approach, can provide precision rangefinding estimates to targets, and can accommodate microscopic imaging of rough surfaces through a image filtering process called z-stacking. CHAMP was originally developed through the Mars Instrument Development Program (MIDP) in support of robotic field investigations, but may also find application in new areas such as robotic in-orbit servicing and maintenance operations associated with spacecraft and human operations. We overview CHAMP'S instrument performance and basic design considerations below.

robotic field investigations↗

Compensatory Water Effects Link Yearly Global Land CO2 Sink Changes to Temperature

Large interannual variations in the measured growth rate of atmospheric carbon dioxide (CO2) originate primarily from fluctuations in carbon uptake by land ecosystems13. It remains uncertain, however, to what extent temperature and water availability control the carbon balance of land ecosystems across spatial and temporal scales314. Here we use empirical models based on eddy covariance data15 and process-based models16,17 to investigate the effect of changes in temperature and water availability on gross primary productivity (GPP), terrestrial ecosystem respiration (TER) and net ecosystem exchange (NEE) at local and global scales. We find that water availability is the dominant driver of the local interannual variability in GPP and TER. To a lesser extent this is true also for NEE at the local scale, but when integrated globally, temporal NEE variability is mostly driven by temperature fluctuations. We suggest that this apparent paradox can be explained by two compensatory water effects. Temporal water-driven GPP and TER variations compensate locally, dampening water-driven NEE variability. Spatial water availability anomalies also compensate, leaving a dominant temperature signal in the year-to-year fluctuations of the land carbon sink. These findings help to reconcile seemingly contradictory reports regarding the importance of temperature and water in controlling the interannual variability of the terrestrial carbon balance36,9,11,12,14. Our study indicates that spatial climate covariation drives the global carbon cycle response.

Jung, Martin↗