Calibration of colour gradient bias in shear measurement using HST/CANDELS data
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Eight Year Climatologies from Observational (AIRS) and Model (MERRA) Data
We examine climatologies derived from eight years of temperature, water vapor, cloud, and trace gas observations made by the Atmospheric Infrared Sounder (AIRS) instrument flying on the Aqua satellite and compare them to similar climatologies constructed with data from a global assimilation model, the Modern Era Retrospective-Analysis for Research and Applications (MERRA). We use the AIRS climatologies to examine anomalies and trends in the AIRS data record. Since sampling can be an issue for infrared satellites in low earth orbit, we also use the MERRA data to examine the AIRS sampling biases. By sampling the MERRA data at the AIRS space-time locations both with and without the AIRS quality control we estimate the sampling bias of the AIRS climatology and the atmospheric conditions where AIRS has a lower sampling rate. While the AIRS temperature and water vapor sampling biases are small at low latitudes, they can be more than a few degrees in temperature or 10 percent in water vapor at higher latitudes. The largest sampling biases are over desert. The AIRS and MERRA data are available from the Goddard Earth Sciences Data and Information Services Center (GES DISC). The AIRS climatologies we used are available for analysis with the GIOVANNI data exploration tool. (see, http://disc.gsfc.nasa.gov).
Hearty, Thomas↗
Completeness of the geological record
The completeness of a sedimentary section of known timespan may be assessed qualitatively by comparing its thickness with the average accumulation for that timespan. Average accumulations may be estimated from sediment volume and continental area data. Quantitative completeness estimation methods based on data compiled from the geological literature have been proposed, but we argue that the literature data are significantly biased and cannot support such methods. Interestingly, however, a comparison of the literature data and accumulation averages computed from sediment volume data suggests that the thickest known sections may be extremely complete.
NASA Discipline Exobiology↗
First Observations of SO2 from the Satellite Suomi NPP OMPS: Widespread Air Pollution Events Over China
Severe smog episodes over China in January 2013 received worldwide attention. This air pollution was distinguished by heavy loadings of fine particulate matter and SO2. To characterize these episodes, we employed the Ozone Mapping and Profiler Suite, Nadir Mapper (OMPS NM), an ultraviolet (UV) spectrometer flying on the Suomi National Polar-orbiting Partnership (SNPP) spacecraft since October 2011. We developed an advanced algorithm to quantify SO2 in the lower troposphere and achieved high-quality retrievals from OMPS NM, which are characterized by high precision, approx. 0.2 Dobson Units (DU; 1 DU = 2.69 x 10(exp 16) molecules/sq cm) for instantaneous field of view SO2 data and low biases (within +/-0.2 DU). Here we report SO2 retrievals and UV aerosol index data for these pollution events. The SO2 columns and the areas covered by high pollutant concentrations are quantified; the results reveal for the first time the full extent (an area of approx. 10(exp 6) sq km containing up to 60 kt of SO2) of these episodes.
Sulfur Dioxide↗
Validation of the Aura Microwave Limb Sounder Temperature and Geopotential Height Measurements
This paper describes the retrievals algorithm used to determine temperature and height from radiance measurements by the Microwave Limb Sounder on EOS Aura. MLS is a "limbscanning" instrument, meaning that it views the atmosphere along paths that do not intersect the surface - it actually looks forwards from the Aura satellite. This means that the temperature retrievals are for a "profile" of the atmosphere somewhat ahead of the satellite. Because of the need to view a finite sample of the atmosphere, the sample spans a box about 1.5km deep and several tens of kilometers in width; the optical characteristics of the atmosphere mean that the sample is representative of a tube about 200-300km long in the direction of view. The retrievals use temperature analyses from NASA's Goddard Earth Observing System, Version 5 (GEOS-5) data assimilation system as a priori states. The temperature retrievals are somewhat deperrde~zt on these a priori states, especially in the lower stratosphere. An important part of the validation of any new dataset involves comparison with other, independent datasets. A large part of this study is concerned with such comparisons, using a number of independent space-based measurements obtained using different techniques, and with meteorological analyses. The MLS temperature data are shown to have biases that vary with height, but also depend on the validation dataset. MLS data are apparently biased slightly cold relative to correlative data in the upper troposphere and slightly warm in the middle stratosphere. A warm MLS bias in the upper stratosphere may be due to a cold bias in GEOS-5 temperatures.
Schwartz, M. J.↗
Very High Resolution, Altitude-Corrected, TMPA-Based Monthly Satellite Precipitation Product Over the CONUS
The Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) product provided over 17 years of gridded precipitation datasets. However, the accuracy and spatial resolution of TMPA limits the applicability in hydrometeorological applications. We present a dataset that enhances the accuracy and spatial resolution of the TMPA monthly product (3B43). We resample the TMPA data to a 1 km grid and apply a correction function derived from the Parameter-elevation Regressions on Independent Slopes Model (PRISM) to reduce bias in the data. We confirm a linear relationship between bias and elevation above 1,500 meters where TMPA underestimates measured precipitation, providing a proof-of-concept of how simple linear scaling can be used to augment existing satellite datasets. The result of the correction is the High-Resolution Altitude-Corrected Precipitation product (HRAC-Precip) for the CONUS. Using 9,200 precipitation stations from the Global Historical Climatology Network (GHCN), we compare the accuracy of TMPA 3B43 versus the new HRAC-Precip product. The results show an improvement of the mean absolute error of 12.98% on average.
Hossein Hashemi↗
Astrometric observations of the satellites of the outer planets. I - The Galilean satellites in 1977
Astrometric observations of the Galilean satellites of Jupiter performed around the opposition of 1977 with a 67-cm photovisual refractor are reported. The measurements are reduced to absolute and intersatellite positions by two different methods: a linear least-squares plate-constant solution to the AGK3 reference-star frame and the trail-scale method of Pascu (1977). Results of a plate-constant reduction are also presented for two observations of JV (Amalthea). Comparison of the data with Liske's (1978) theoretical predictions for the intersatellite positions indicates no systematic bias in the data; a probable scatter of about 15 arcsec in both right ascension and declination is estimated.
Ianna, P. A.↗
Foreground Bias from Parametric Models of Far-IR Dust Emission
We use simple toy models of far-IR dust emission to estimate the accuracy to which the polarization of the cosmic microwave background can be recovered using multi-frequency fits, if the parametric form chosen for the fitted dust model differs from the actual dust emission. Commonly used approximations to the far-IR dust spectrum yield CMB residuals comparable to or larger than the sensitivities expected for the next generation of CMB missions, despite fitting the combined CMB plus foreground emission to precision 0.1 percent or better. The Rayleigh-Jeans approximation to the dust spectrum biases the fitted dust spectral index by (Delta)(Beta)(sub d) = 0.2 and the inflationary B-mode amplitude by (Delta)(r) = 0.03. Fitting the dust to a modified blackbody at a single temperature biases the best-fit CMB by (Delta)(r) greater than 0.003 if the true dust spectrum contains multiple temperature components. A 13-parameter model fitting two temperature components reduces this bias by an order of magnitude if the true dust spectrum is in fact a simple superposition of emission at different temperatures, but fails at the level (Delta)(r) = 0.006 for dust whose spectral index varies with frequency. Restricting the observing frequencies to a narrow region near the foreground minimum reduces these biases for some dust spectra but can increase the bias for others. Data at THz frequencies surrounding the peak of the dust emission can mitigate these biases while providing a direct determination of the dust temperature profile.
cosmic microwave background↗
GSFC optical ozonesonde results during the Gap, France, intercomparisons, June 1981
O3 soundings made with balloon-borne optical sensors during the French Intercomparison Ozone Campaign in June, 1981, are reported. The GSFC four-channel UV-filter-photometer ozonesonde designed for the Super Loki rocket was attached to the gondola roof for redundant O3-density measurements at altitudes of 22-32 km, using the 300 and 303-nm filters. Sensor calibration, data processing, input constants, and vertical O3-distribution calculations are discussed. The density profiles for three legs of the flight, calculated using Bass or Vigroux cross sections, agreed within a standard error of 1.4 percent for each channel, but showed a consistent 4-5 percent (significant) difference between channels. Total average O3-column amounts determined by combining the GSFC data with ECC measurements for altitudes below 21 km were in good agreement with bias-corrected TOMS data from Nimbus-VII and with ground-based data from the Observatoire de Haute-Provence at Mt. Chiran, when the latter were computed using the pre-campaign calibration. A 9-percent discrepancy arose when the Chiran data were corrected for a post-campaign recalibration of the Dobson spectrophotometer.
Krueger, A. J.↗
Timebias corrections to predictions
The importance of an accurate knowledge of the time bias corrections to predicted orbits to a satellite laser ranging (SLR) observer, especially for low satellites, is highlighted. Sources of time bias values and the optimum strategy for extrapolation are discussed from the viewpoint of the observer wishing to maximize the chances of getting returns from the next pass. What is said may be seen as a commercial encouraging wider and speedier use of existing data centers for mutually beneficial exchange of time bias data.
Wood, Roger↗
Moisture Forecast Bias Correction in GEOS DAS
Data assimilation methods rely on numerous assumptions about the errors involved in measuring and forecasting atmospheric fields. One of the more disturbing of these is that short-term model forecasts are assumed to be unbiased. In case of atmospheric moisture, for example, observational evidence shows that the systematic component of errors in forecasts and analyses is often of the same order of magnitude as the random component. we have implemented a sequential algorithm for estimating forecast moisture bias from rawinsonde data in the Goddard Earth Observing System Data Assimilation System (GEOS DAS). The algorithm is designed to remove the systematic component of analysis errors and can be easily incorporated in an existing statistical data assimilation system. We will present results of initial experiments that show a significant reduction of bias in the GEOS DAS moisture analyses.
Dee, D.↗
The muon content of EAS as a function of primary energy
The muon content of extensive air showers (EAS) was measured over the wide primary energy range 10 to the 16th power to 10 to the 20th power eV. It is reported that the relative muon content of EAS decreases smoothly over the energy range 10 to the 17th power to 10 to the 19th power eV and concluded that the primary cosmic ray flux has a constant mass composition over this range. It is also reported that an apparent significant change in the power index occurs below 10 to the 17th power eV rho sub c (250 m) sup 0.78. Such a change indicates a significant change in primary mass composition in this range. The earlier conclusions concerning EAS of energy 10 to the 17th power eV are confirmed. Analysis of data in the 10 to the 16th power - 10 to the 17th power eV range revealed a previously overlooked selection bias in the data set. The full analysis of the complete data set in the energy range 10 to the 16th power - 10 to the 17th power ev with the selection bias eliminated is presented.
Blake, P. R.↗
A comparison of turbulence intensity measurements using a laser velocimeter and a hot wire in a low speed jet flow
The study involves a simultaneous measurement with both instruments along radial scans at two axial locations in the jet exiting from the turbulent pipe and an axial scan at the 75-percent radial location in the jet from the convergent nozzle. The results suggest that, within the limits of flow stationarity, both instruments yield measurements in good agreement, + or - 0.8-percent in turbulence intensity, below a turbulence intensity (the ensemble standard deviation divided by the local mean velocity) of 20 percent. From turbulence intensities of 20 percent to a maximum of 75 percent, the measurements exhibit the same trends; for reasons discussed here, however, the comparisons are not of the quality as those below 20 percent. It is found that correcting the turbulence intensity data for velocity bias errors increases the results by an average of 2 percent in turbulence intensity above the hot wire results and the uncorrected laser velocimeter data. The results are seen as calling into question the validity of using the velocity bias correction and time average techniques for turbulence intensity measurements.
Meyers, J. F.↗
Effects on Spacecraft Radiometric Data at Superior Solar Conjunction
During 2006, three ESA interplanetary spacecraft, Rosetta, Mars Express (MEX) and Venus Express (VEX), passed through superior solar conjunction. For all three spacecraft, the noise in the post-fit range-rate residuals from the orbit determination was analysed. At small Sun-Earth-Probe (SEP) angles the level was almost two orders of magnitude higher than normal. The main objective was to characterize the Doppler (rangerate) noise as a function of SEP angle. At least then the range-rate data can be appropriately weighted within the orbit determination so that the solution uncertainties are realistic. For VEX, some intervals of particularly noisy Doppler data could be correlated with unusual solar activity. For Rosetta, the biases in the range data residuals were analysed with the aim of improving the model used for calibrating the signal delay due to the solar plasma. The model, which originally had fixed coefficients, was adjusted to achieve better fits to the data. Even the relatively small Doppler biases were well represented. Using the improved model, the electron density at 20 solar radii was compared with earlier results obtained by radio science studies using Voyager 2 and Ulysses radiometric data. There is some evidence for a dependency of the density on the phase within the 11 years solar cycle.
Morley, Trevor↗
The effects of missing data on global ozone estimates
The effects of missing data and model truncation on estimates of the global mean, zonal distribution, and global distribution of ozone are considered. It is shown that missing data can introduce biased estimates with errors that are not accounted for in the accuracy calculations of empirical modeling techniques. Data-fill techniques are introduced and used for evaluating error bounds and constraining the estimate in areas of sparse and missing data. It is found that the accuracy of the global mean estimate is more dependent on data distribution than model size. Zonal features can be accurately described by 7th order models over regions of adequate data distribution. Data variance accounted for by higher order models appears to represent climatological features of columnar ozone rather than pure error. Data-fill techniques can prevent artificial feature generation in regions of sparse or missing data without degrading high order estimates over dense data regions.
Drewry, J. W.↗
On the error in crop acreage estimation using satellite (LANDSAT) data
The problem of crop acreage estimation using satellite data is discussed. Bias and variance of a crop proportion estimate in an area segment obtained from the classification of its multispectral sensor data are derived as functions of the means, variances, and covariance of error rates. The linear discriminant analysis and the class proportion estimation for the two class case are extended to include a third class of measurement units, where these units are mixed on ground. Special attention is given to the investigation of mislabeling in training samples and its effect on crop proportion estimation. It is shown that the bias and variance of the estimate of a specific crop acreage proportion increase as the disparity in mislabeling rates between two classes increases. Some interaction is shown to take place, causing the bias and the variance to decrease at first and then to increase, as the mixed unit class varies in size from 0 to 50 percent of the total area segment.
Chhikara, R.↗
Differences Between OCO‐2 and GOME‐2 SIF Products From a Model‐Data Fusion Perspective
Space-borne retrievals of solar-induced chlorophyll fluorescence (SIF) over land surfaces have recently become a resource for studying and quantifying the broad scale dynamics of gross carbon uptake (gross primary productivity—GPP) across ecosystems. To prepare for the assimilation of SIF data in terrestrial biosphere models, we examine how differences between SIF products (due to differences in acquisition characteristics and processing chain) may affect the optimization of model parameters and the resultant GPP estimate. We compare recent daily mean SIF products (one from the Orbiting Carbon Observatory-2 [OCO-2] and two from the Global Ozone Monitoring Experiment–2 [GOME-2], GlobFluo [GF] and NASA-v28 [N28], missions), averaged at 0.5° × 0.5° spatial resolution and 16-day temporal resolution, at the biome level. Phase differences between these products are relatively small. A first-order correction of the difference in spectral sampling between the two instruments shows that OCO-2 and N28 are consistent in terms of magnitude and amplitude, while GF is twice as large as the others. Using a bias-blind toy data assimilation framework, we analyze how biases between SIF products, and between model and products, can be partially alleviated by optimizing the slope and intercept parameters of a linear GPP-SIF operator. As observation biases can transfer to biases in other optimized process-based parameters and to modeled carbon fluxes— thereby resulting in unidentified inaccurate parameter values—we argue that potential SIF biases should be treated cautiously in real-world experiments in order to achieve realistic and reliable future simulations.
Gross primary production↗
Constructing a coherent long-term global total ozone climatology from the BUV, MFR, and SBUV/TOMS data sets
Multichannel Filter Radiometer (MFR) data are intercompared with Solar Backscattered Ultraviolet (SBUV) and Total Ozone Mapping Spectrometer (TOMS) data during a five-month period of their data overlap in order to determine the usefulness of MFR data to represent the SBUV/TOMS and backscatter ultraviolet spectrometer data during their data gap period. Total ozone differences found were latitudinally and monthly dependent. Average differences between the TOMS and the MFR ozone data vary from -12.4 to +13.3 percent, with differences in the tropical to middle latitudes generally between + or - 4 percent. Biases between the data sets can be removed for certain latitude zones by applying an appropriate algorithm to the MFR ozone data.
Ellis, J. S.↗