NuSTAR measurement of the cosmic X-ray background in the 3–20 keV energy band

ABSTRACT We present measurements of the intensity of the cosmic X-ray background (CXB) with the Nuclear Spectroscopic Telescope Array (NuSTAR) telescope in the 3–20 keV energy range. Our method uses spatial modulation of the CXB signal on the NuSTAR detectors through the telescope’s side aperture. Based on the NuSTAR observations of selected extragalactic fields with a total exposure of 7 Ms, we have estimated the CXB 3–20 keV flux to be 2.8 × 10−11 erg s−1 cm−2 deg−2, which is $\sim \! 8{{\ \rm per\ cent}}$ higher than that measured with HEAO-1 and consistent with the INTEGRAL measurement. The inferred CXB spectral shape in the 3–20 keV energy band is consistent with the canonical model of Gruber et al. We demonstrate that the spatially modulated CXB signal measured by NuSTAR is not contaminated by systematic noise and is limited by photon statistics. The measured relative scatter of the CXB intensity between different sky directions is compatible with cosmic variance, which opens new possibilities for studying CXB anisotropy over the whole sky with NuSTAR.

Validation of TANSO-FTS/GOSAT XCO₂ and XCH₄ glint mode retrievals using TCCON data from near-ocean sites

The thermal And near infrared sensor for carbon observations Fourier transform spectrometer (TANSO-FTS) on board the Greenhouse Gases Observing Satellite (GOSAT) applies the normal nadir mode above the land (“land data”) and sun glint mode over the ocean (“ocean data”) to provide global distributions of column-averaged dry-air mole fractions of CO2 and CH4, or XCO2 and XCH4. Several algorithms have been developed to obtain highly accurate greenhouse gas concentrations from TANSO-FTS/GOSAT spectra. So far, all the retrieval algorithms have been validated with the measurements from ground-based Fourier transform spectrometers from the Total Carbon Column Observing Network (TCCON), but limited to the land data. In this paper, the ocean data of the SRPR, SRFP (the proxy and full-physics versions 2.3.5 of SRON/KIT's RemoTeC algorithm), NIES (National Institute for Environmental Studies operational algorithm version 02.21) and ACOS (NASA's Atmospheric CO2 Observations from Space version 3.5) are compared with FTIR measurements from five TCCON sites and nearby GOSAT land data.For XCO2, both land and ocean data of NIES, SRFP and ACOS show good agreement with TCCON measurements. Averaged over all TCCON sites, the relative biases of ocean data and land data are −0.33 and −0.13 % for NIES, 0.03 and 0.04 % for SRFP, 0.06 and −0.03 % for ACOS, respectively. The relative scatter ranges between 0.31 and 0.49 %. For XCH4, the relative bias of ocean data is even less than that of the land data for the NIES (0.02 vs. −0.35 %), SRFP (0.04 vs. 0.20 %) and SRPR (−0.02 vs. 0.06 %) algorithms. Compared to the results for XCO2, the XCH4 retrievals show larger relative scatter (0.65–0.81 %).

Validation of TANSO-FTS/GOSAT XCO₂ and XCH₄ glint mode retrievals using TCCON data from near-ocean sites

Thermal And Near infrared Sensor for carbon Observations Fourier Transform Spectrometer (TANSO-FTS) on board The Greenhouse gases Observing SATellite (GOSAT) applies the normal nadir mode above the land ("land data") and sun glint mode over the ocean ("ocean data") to provide global distributions of column-averaged dry-air mole fractions of CO2 and CH4, or XCO2 and XCH4. Several algorithms have been developed to obtain highly accurate greenhouse gas concentrations from TANSO-FTS/GOSAT spectra. So far, all the retrieval algorithms have been validated with the measurements from ground-based Fourier transform spectrometers from the Total Carbon Column Observing Network (TCCON), but limited to the land data. In this paper, the ocean data of the SRPR, SRFP (the proxy and full-physics versions 2.3.5 of SRON/KIT's RemoTeC algorithm), NIES (National Institute for Environmental Studies operational algorithm version 02.21) and ACOS (NASA's Atmospheric CO2 Observations from Space version 3.5) are compared with FTIR measurements from five TCCON sites and near-by GOSAT land data. For XCO2, both land and ocean data of NIES, SRFP and ACOS show good agreement with TCCON measurements. Averaged over all TCCON sites, the relative biases of ocean data and land data are 0.33 and 0.13 % for NIES, −0.03 and −0.04 % for SRFP, −0.06 and 0.03 % for ACOS, respectively. The relative scatter ranges between 0.31 and 0.49 %. For XCH4, the relative bias of ocean data is even less than that of the land data for the NIES (−0.02 vs. 0.35 %), SRFP (&minus,0.04 vs. −0.20 %) and SRPR (0.02 vs. −0.06 %) algorithms. Compared to the results for XCO2, the XCH4 retrievals show larger relative scatter (0.65–0.81 %).

Comparisons between SCIAMACHY atmospheric CO₂ retrieved using (FSI) WFM-DOAS to ground based FTIR data and the TM3 chemistry transport model

Atmospheric CO2 concentrations, retrieved from spectral measurements made in the near infrared (NIR) by the SCIAMACHY instrument, using Full Spectral Initiation Weighting Function Modified Differential Optical Absorption Spectroscopy (FSI WFM-DOAS), are compared to ground based Fourier Transform Infrared (FTIR) data and to the output from a global chemistry-transport model. Analysis of the FSI WFM-DOAS retrievals with respect to the ground based FTIR instrument, located at Egbert, Canada, show good agreement with an average negative bias of approximately −4.0% with a standard deviation of 3.0%. This bias which exhibits an apparent seasonal trend, is of unknown origin, though slight differences between the averaging kernels of the instruments and the limited temporal coverage of the FTIR data may be the cause. The relative scatter of the retrieved vertical column densities is larger than the spread of the FTIR measurements. Normalizing the CO2 columns using the surface pressure does not affect the magnitude of this bias although it slightly decreases the scatter of the FSI data. Comparisons of the FSI retrievals to the TM3 global chemistry-transport model, performed over four selected Northern Hemisphere scenes show reasonable agreement. The correlation, between the time series of the SCIAMACHY and model monthly scene averages, are 0.7 or greater, demonstrating the ability of SCIAMACHY to detect seasonal changes in the CO2 distribution. The amplitude of the seasonal cycle, peak to peak, observed by SCIAMACHY however, is larger by a factor of 2–3 with respect to the model, which cannot be explained. The yearly means detected by SCIAMACHY are within 2% of those of the model with the mean difference between the CO2 distributions also approximately 2.0%. Additionally, analysis of the retrieved CO2 distributions reveals structure not evident in the model fields which correlates well with land classification type. From these comparisons, it is estimated that the overall bias of the CO2 columns retrieved by the FSI algorithm is <4.0% with the precision of monthly 1°×1° gridded data close to 1.0%.

Comparisons between SCIAMACHY atmospheric CO₂ retrieved using (FSI) WFM-DOAS to ground based FTIR data and the TM3 chemistry transport model

Atmospheric CO2 concentrations, retrieved from spectral measurements made in the near infrared (NIR) by the SCIAMACHY instrument, using Full Spectral Initiation Weighting Function Modified Differential Optical Absorption Spectroscopy (FSI WFM-DOAS), are compared to ground based Fourier Transform Infrared (FTIR) data and to the output from a global chemistry-transport model. Analysis of the FSI WFM-DOAS retrievals with respect to the ground based FTIR instrument, located at Egbert, Canada, show good agreement with an average negative bias of approximately −4.0% with a standard deviation of ~3.0%. This bias which exhibits an apparent seasonal trend, is of unknown origin, though slight differences between the averaging kernels of the instruments and the limited temporal coverage of the FTIR data may be the cause. The relative scatter of the retrieved vertical column densities is comparable to the spread of the FTIR measurements themselves. Normalizing the CO2 columns using the surface pressure does not affect the magnitude of this bias although it slightly increases the scatter of the FSI data. Comparisons of the FSI retrievals to the TM3 global chemistry-transport model, performed over four selected Northern Hemisphere scenes show good agreement. The correlation, between the time series of the SCIAMACHY and model monthly scene averages, are ~0.7 or greater, demonstrating the ability of SCIAMACHY to detect seasonal changes in the CO2 distribution. The amplitude of the seasonal cycle, peak to peak, observed by SCIAMACHY however, is overestimated by a factor of 2–3, which cannot be explained. The yearly means detected by SCIAMACHY are within 2% of those of the model with the mean difference between the CO2 distributions also approximately 2.0%. Additionally, analysis of the retrieved CO2 distributions reveals structure not evident in the model fields which correlates well with land classification type. From these comparisons, the overall precision and bias of the CO2 columns retrieved by the FSI algorithm are estimated to be close to 1.0% and <4.0% respectively.

THEORY AND MEASUREMENT OF VISUAL MECHANISMS

Comparison of monocular and binocular critical flash intensities for recognition of flicker, using a centrally fixated square image subtending ca. 6.13° on a side (white light), shows that for the cone segment of the response contour the inflection point of the probability integral correlating flash frequency F (for symmetrical flicker) and log mean critical flash intensity Im is with the binocular measurements exactly intermediate between those for each eye separately. This does not mean that in general the data are intermediate; they are not; the binocular asymptotic Fmax. agrees with or lies above the greater one of the two uniocular curves. The entire contour must be considered for valid intercomparisons, as is also true if homologous curves for different observers are to be compared. For the measurements in the predominantly rod region the binocular data are more or less intermediate. The rod curves result, however, from the integrative interplay of rod and cone effects for which the intrinsic curves overlap. The resultant rod curve as measured is determined by the partial inhibition of rod effects by cone effects, and by the summation of the remaining rod contributions with those labelled cone in origin. It is pointed out that in this respect, as in others, it is desirable to consider the rôles of retinal area, and location, from the standpoint of integration of neural effects. These phenomena are essentially independent of the light-time fraction and of the spectral (λ) quality of the light used. For binocular, as for uniocular excitation, the normal probability summation provides an efficient general description, under diverse conditions of size and location of retinal image, wave-length composition of light, light-time cycle-fraction, and kind of animal. It is pointed out that this is the only function abstractly likely to exhibit this kind of efficiency. That a summation of veritable effects independently generated by simultaneous, symmetrical uniocular excitation does occur in the recognition of flicker is specifically demonstrated by the fact that for a given mean critical flash intensity the associated variation is lower for binocular than for either or the average of the single-eyed presentations,—and in the ratio not statistically different from 1:1.41; the relative scatter of the binocular indices of dispersion is also reduced below the uniocular. Since the mean variation of the critical intensity is statistically in a constant ratio to Im, in appropriately homogeneous series, independent for example of the brightness level and of the light-time fraction, this signifies an essential doubling of the effectiveness (potential) of each of the elements concerned in the discrimination of flicker when binocular excitation is concerned, although the total number of these elements is only slightly or not at all affected. The potential in question is not exclusively correlated with subjective brightness-at-fusion, which is, however, increased with binocular regard.