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Hampton, VA, United States

Loeb N.G.,NASA | Su W.,SSAI
Journal of Climate | Year: 2010

To provide a lower bound for the uncertainty inmeasurement-based clear-and all-sky direct aerosol radiative forcing (DARF), a radiative perturbation analysis is performed for the ideal case in which the perturbations in global mean aerosol properties are given by published values of systematic uncertainty in Aerosol Robotic Network (AERONET) aerosol measurements. DARF calculations for base-state climatological cloud and aerosol properties over ocean and land are performed, and then repeated after perturbing individual aerosol optical properties (aerosol optical depth, single-scattering albedo, asymmetry parameter, scale height, and anthropogenic fraction) from their base values, keeping all other parameters fixed. The total DARF uncertainty from all aerosol parameters combined is 0.5-1.0 W m -2, a factor of 2-4 greater than the value cited in the Intergovernmental Panel on Climate Change's (IPCC's) Fourth Assessment Report. Most of the total DARF uncertainty in this analysis is associatedwith single-scattering albedo uncertainty. Owing to the greater sensitivity to single-scattering albedo in cloudy columns, DARF uncertainty in all-sky conditions is greater than in clear-sky conditions, even though the global mean clear-sky DARF is more than twice as large as the all-sky DARF. © 2010 American Meteorological Society. Source

Thompson A.M.,Pennsylvania State University | Allen A.L.,Pennsylvania State University | Lee S.,Pennsylvania State University | Miller S.K.,Pennsylvania State University | And 2 more authors.
Journal of Geophysical Research: Atmospheres | Year: 2011

Prior investigations attempted to determine the relative influence of advection and convective processes on ozone and water vapor distributions in the tropical tropopause layer (TTL) through analyses of tracers, related physical parameters (e.g., outgoing long-wave radiation, precipitable water, and temperature), or with models. In this study, stable laminae in Southern Hemisphere Additional Ozonesonde Network (SHADOZ) ozone profiles from 1998 to 2007 are interpreted in terms of gravity waves (GW) or Rossby waves (RW) that are identified with vertical and quasi-horizontal displacements, respectively. Using the method of Pierce and Grant (1998) as applied by Thompson et al. (2007a, 2007b, 2010, 2011), amplitudes and frequencies in ozone laminae are compared among representative SHADOZ sites over Africa and the Pacific, Indian, and Atlantic oceans. GW signals maximize in the TTL and lower stratosphere. Depending on site and season, GW are identified in up to 90% of the soundings. GW are most prevalent over the Pacific and eastern Indian oceans, a distribution consistent with vertically propagating equatorial Kelvin waves. Ozone laminae from RW occur more often below the tropical tropopause and with lower frequency (<20%). Gravity wave and Rossby wave indices (GWI, RWI) are formulated to facilitate analysis of interannual variability of wave signatures among sites. GWI is positively correlated with a standard ENSO (El Nio-Southern Oscillation) index over American Samoa (14S, 171W) and negatively correlated at Watukosek, Java (7.5S, 114E), Kuala Lumpur (3N, 102E), and Ascension Island (8S, 15W). Generally, the responses of GW and RW to ENSO are consistent with prior studies. Copyright 2011 by the American Geophysical Union. Source

Crow W.T.,U.S. Department of Agriculture | Van Den Berg M.J.,Ghent University | Huffman G.J.,SSAI | Huffman G.J.,NASA | Pellarin T.,Grenoble Institute of Technology
Water Resources Research | Year: 2011

Recently, Crow et al. (2009) developed an algorithm for enhancing satellite-based land rainfall products via the assimilation of remotely sensed surface soil moisture retrievals into a water balance model. As a follow-up, this paper describes the benefits of modifying their approach to incorporate more complex data assimilation and land surface modeling methodologies. Specific modifications improving rainfall estimates are assembled into the Soil Moisture Analysis Rainfall Tool (SMART), and the resulting algorithm is applied outside the contiguous United States for the first time, with an emphasis on West African sites instrumented as part of the African Monsoon Multidisciplinary Analysis experiment. Results demonstrate that the SMART algorithm is superior to the Crow et al. baseline approach and is capable of broadly improving coarse-scale rainfall accumulations measurements with low risk of degradation. Comparisons with existing multisensor, satellite-based precipitation data products suggest that the introduction of soil moisture information from the Advanced Microwave Scanning Radiometer via SMART provides as much coarse-scale (3 day, 1) rainfall accumulation information as thermal infrared satellite observations and more information than monthly rain gauge observations in poorly instrumented regions. Copyright 2011 by the American Geophysical Union. Source

Teng H.,U.S. National Center for Atmospheric Research | Branstator G.,U.S. National Center for Atmospheric Research | Wang H.,SSAI | Meehl G.A.,U.S. National Center for Atmospheric Research | Washington W.M.,U.S. National Center for Atmospheric Research
Nature Geoscience | Year: 2013

Heat waves are thought to result from subseasonal atmospheric variability. Atmospheric phenomena driven by tropical convection, such as the Asian monsoon, have been considered potential sources of predictability on subseasonal timescales. Mid-latitude atmospheric dynamics have been considered too chaotic to allow significant prediction skill of lead times beyond the typical 10-day range of weather forecasts. Here we use a 12,000-year integration of an atmospheric general circulation model to identify a pattern of subseasonal atmospheric variability that can help improve forecast skill for heat waves in the United States. We find that heat waves tend to be preceded by 15-20 days by a pattern of anomalous atmospheric planetary waves with a wavenumber of 5. This circulation pattern can arise as a result of internal atmospheric dynamics and is not necessarily linked to tropical heating. We conclude that some mid-latitude circulation anomalies that increase the probability of heat waves are predictable beyond the typical weather forecast range. © 2013 Macmillan Publishers Limited. Source

Kashlinsky A.,SSAI | Kashlinsky A.,NASA | Arendt R.G.,NASA | Arendt R.G.,University of Maryland, Baltimore | And 4 more authors.
Astrophysical Journal | Year: 2012

We extend previous measurements of cosmic infrared background (CIB) fluctuations to ≲ 1° using new data from the Spitzer Extended Deep Survey. Two fields with depths of ≃ 12 hrpixel-1 over three epochs are analyzed at 3.6 and 4.5 μm. Maps of the fields were assembled using a self-calibration method uniquely suitable for probing faint diffuse backgrounds. Resolved sources were removed from the maps to a magnitude limit of magAB ≃ 25, as indicated by the level of the remaining shot noise. The maps were then Fourier transformed and their power spectra were evaluated. Instrumental noise was estimated from the time-differenced data, and subtracting this isolates the spatial fluctuations of the actual sky. The power spectra of the source-subtracted fields remain identical (within the observational uncertainties) for the three epochs indicating that zodiacal light contributes negligibly to the fluctuations. Comparing to 8 μm power spectra shows that Galactic cirrus cannot account for the fluctuations. The signal appears isotropically distributed on the sky as required for an extragalactic origin. The CIB fluctuations continue to diverge to >10 times those of known galaxy populations on angular scales out to ≲ 1°. The low shot-noise levels remaining in the diffuse maps indicate that the large-scale fluctuations arise from the spatial clustering of faint sources well below the confusion noise. The spatial spectrum of these fluctuations is in reasonable agreement with an origin in populations clustered according to the standard cosmological model (ΛCDM) at epochs coinciding with the first stars era. © 2012. The American Astronomical Society. All rights reserved. Source

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