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At least 253 records · Page 14

From the Upper Troposphere Through the Stratosphere: How Satellite Measurements Help Us Decode the Past to Better Project the Future

Decades of observations of key chemical species are allowing us to more fully understand processes important to transport and composition from the upper troposphere through the stratosphere. This talk will focus on a few examples and how they are informing our understanding of variability, trends, and future projections. The growth of the Antarctic ozone hole (late 1970s – mid 1990s) caused a dynamical perturbation to the Southern Hemisphere stratospheric circulation visible in ozone, one of our longest and best observed chemical constituents, and illustrates the connection between chemical change and the coupled radiative and dynamical response that challenges chemistry-climate models (CCMs). The quasi-biennial oscillation (QBO) is the dominant mode of interannual variability in the tropical stratosphere, however its impacts on stratospheric circulation and composition can be traced globally. The QBOs timing with respect to the seasonal cycle in each hemisphere is significant in understanding its impact on up to decadal scale variability. The El Nino Southern Oscillation (ENSO), which dominates tropical tropospheric interannual variability, also affects the stratosphere and its influence is visible in our growing record of tropospheric and stratospheric composition measurements. I will discuss how our knowledge of response has grown and how representation of these observed responses in CCMs is key both to understanding recent trends and to reducing uncertainty in future changes of composition.

Luke David Oman↗

Magnetic space-based field measurements

Satellite measurements of the geomagnetic field began with the launch of Sputnik 3 in May 1958 and have continued sporadically in the intervening years. A list of spacecraft that have made significant contributions to an understanding of the near-earth geomagnetic field is presented. A new era in near-earth magnetic field measurements began with NASA's launch of Magsat in October 1979. Attention is given to geomagnetic field modeling, crustal magnetic anomaly studies, and investigations of the inner earth. It is concluded that satellite-based magnetic field measurements make global surveys practical for both field modeling and for the mapping of large-scale crustal anomalies. They are the only practical method of accurately modeling the global secular variation. Magsat is providing a significant contribution, both because of the timeliness of the survey and because its vector measurement capability represents an advance in the technology of such measurements.

Langel, R. A.↗

Determination of the heat balance of the earth: Interpretation of radiation measurements from satellites

A method is developed for estimating the mean and mean-square variation of the flux at an altitude arbitrarily chosen to represent the top of the atmosphere. When applied to practical satellite measurements, the method is shown to be optimum in that the estimated mean is unbiased and the mean square variation of the estimates converges to that of the true flux. Data from the Meteor-1 and -2 satellites support the essential assumptions and provide a quantitative indication of the performance that can be expected.

Laughlin, C. R.↗

Dust Optical Properties derived from Sun/Sky Measurements and Satellite Data

We derive the optical properties of dust originating from the Sahara and nearby regions using a combination of ground based and satellite measurements. The AErosol ROBotic NETwork (AERONET) sun/sky radiances from Cap Verde and Sede Boker are used together with Landsat TM data over Senegal and the Atlantic Ocean. The data introduce a cascade of increasing complexity of dust optical properties: The sky aureole radiance is sensitive mainly to the dust size distribution; the TM data over the ocean at 150 deg scattering angle are also sensitive to the spectral refractive index from 470 to 2,210 nm. The TM data over the land measure the balance between the dust scattering and absorption of light reflected by the bright surface, thus very sensitive to dust spectral absorption. Sky radiance at scattering angle of 120 deg, add sensitivity to the dust nonsphericity. Preliminary results, indicative of the ambient dust in the entire atmospheric column, show that dust is less absorbing and with smaller nonspherical properties than anticipated from in situ measurements. Dust is dominated by particles with effective radius of 2 to 2.5 micron, refractive index for wavelengths less then 1 micron of 1.53-0.001i and nonsphericity that increases the phase function at 120 deg above that of spheres by 1.8 and 1.7 at 673 nm down to 1.2 and 1.3 for 1020 nm for Cap Verde and Sede Boker respectively. No significant nonsphericity effect is noticed for scattering angle of 150 deg. This agrees with a mixture of 30% and 45% respectively of Mishchenko et al (JGR, 102, 1997: plate 5 on page 16,841) "polydisperse equiprobable shape mixture of prolate and oblate spheroids with aspect ratios ranging from 1.4 to 2.21, with the rest being spherical particles.

Kaufman, Yoram J.↗

Atmospheric measurements from satellites.

Atmospheric measurements from satellites, discussing ATS-1 cloud images for definition of wind and use of WEFAX through ATS 2 satellites for data transmission

Rados, R. M.↗

Estimating surface soil moisture from satellite microwave measurements and a satellite derived vegetation index

Normalized 18-GHz microwave brightness temperatures, T(B), and a vegetation index determined from satellite radiometer data are combined with climatically modeled surface moisture estimates to constrain a simple physically based soil moisture model. It is found that the normalized T(B) values correlated well with soil moisture when the data were segregated by vegetation index range, but less so when all the data were combined. By using the vegetation index parameter, the model is shown to account for about 70 percent of the variability in modeled surface soil moisture.

Owe, Manfred↗

Multi-Sensor Cloud and Aerosol Retrieval Simulator and Remote Sensing from Model Parameters : Aerosols - Part 2

The Multi-sensor Cloud Retrieval Simulator (MCRS) produces a simulated radiance product from any high-resolution general circulation model with interactive aerosol as if a specific sensor such as the Moderate Resolution Imaging Spectroradiometer (MODIS) were viewing a combination of the atmospheric column and land ocean surface at a specific location. Previously the MCRS code only included contributions from atmosphere and clouds in its radiance calculations and did not incorporate properties of aerosols. In this paper we added a new aerosol properties module to the MCRS code that allows users to insert a mixture of up to 15 different aerosol species in any of 36 vertical layers. This new MCRS code is now known as MCARS (Multi-sensor Cloud and Aerosol Retrieval Simulator). Inclusion of an aerosol module into MCARS not only allows for extensive, tightly controlled testing of various aspects of satellite operational cloud and aerosol properties retrieval algorithms, but also provides a platform for comparing cloud and aerosol models against satellite measurements. This kind of two-way platform can improve the efficacy of model parameterizations of measured satellite radiances, allowing the assessment of model skill consistently with the retrieval algorithm. The MCARS code provides dynamic controls for appearance of cloud and aerosol layers. Thereby detailed quantitative studies of the impacts of various atmospheric components can be controlled. In this paper we illustrate the operation of MCARS by deriving simulated radiances from various data field output by the Goddard Earth Observing System version 5 (GEOS-5) model. The model aerosol fields are prepared for translation to simulated radiance using the same model sub grid variability parameterizations as are used for cloud and atmospheric properties profiles, namely the ICA technique. After MCARS computes modeled sensor radiances equivalent to their observed counterparts, these radiances are presented as input to operational remote-sensing algorithms. Specifically, the MCARS-computed radiances are input into the processing chain used to produce the MODIS Data Collection 6 aerosol product (MOYD04). TheMOYD04 product is of course normally produced from MOYD021KM MODIS Level-1B radiance product directly acquired by the MODIS instrument. MCARS matches the format and metadata of a MOYD021KM product. The resulting MCARS output can be directly provided to MODAPS (MODIS Adaptive Processing System) as input to various operational atmospheric retrieval algorithms. Thus the operational algorithms can be tested directly without needing to make any software changes to accommodate an alternative input source. We show direct application of this synthetic product in analysis of the performance of the MOD04 operational algorithm. We use biomass-burning case studies over Amazonia employed in a recent Working Group on Numerical Experimentation (WGNE)-sponsored study of aerosol impacts on numerical weather prediction (Freitas et al., 2015). We demonstrate that a known low bias in retrieved MODIS aerosol optical depth appears to be due to a disconnect between actual column relative humidity and the value assumed by the MODIS aerosol product.

aerosol retrieval↗

Radiation measurements from polar and geosynchronous satellites

Measurements of the earth's radiation budget, its climatology and its interannual variation, are described briefly. In addition, preliminary results are given on ocean energy transports, specific large scale and local radiation budget anamolies, and studies of the separate radiation budgets of the atmosphere and ocean. Initial work in preparation for additional radiation budget measurements from EOS and ATS satellites is described. A radiation budget system simulation program and several smaller projects (including a radiance normalization technique) are also mentioned. First annual global maps of the earth's radiation budget as measured from Nimbus 3 are included.

Vonderhaar, T. H.↗