Search Results

You are looking at 1 - 10 of 11 items for

  • Author or Editor: E. BAUER x
  • All content x
Clear All Modify Search
E. BAUER, A. DANJON, and JEAN LANGEVIN

Abstract

No Abstract Available.

Full access
S. J. Bauer and R. E. Bourdeau

Abstract

Charged Particle temperature results obtained by three different methods (rocket and satellite-borne Langmuir probes, rocket measurements of the altitude dependence of charged particle densities above the F2 peak, and radar incoherent backscatter) are compared with recent models of kinetic gas temperature. From the few sets of charged particle data available for conditions of a quiet sun at temperate latitudes, the comparison favors the concept of temperature equilibrium between electrons and heavy constituents in all but the lower F region of the ionosphere. Additional departures from equilibrium are indicated for disturbed ionospheric conditions and possibly for a quiet sun at auroral latitudes.

Full access
Kenneth G. Bauer and John E. Kutzbach

Abstract

Full access
A. Benedetti, P. Lopez, E. Moreau, P. Bauer, and V. Venugopal

Abstract

A validation of passive microwave–adjusted rainfall analyses of tropical cyclones using spaceborne radar data is presented. This effort is part of the one-dimensional plus four-dimensional variational (1D+4D-Var) rain assimilation project that is being carried out at the European Centre for Medium-Range Weather Forecasts (ECMWF). Brightness temperatures or surface rain rates from the Tropical Rainfall Measuring Mission (TRMM) satellite are processed through a 1D-Var retrieval to derive values of total column water vapor that can be ingested into the operational ECMWF 4D-Var. As an indirect validation, the precipitation fields produced at the end of the 1D-Var minimization process are converted into equivalent radar reflectivity at the frequency of the TRMM precipitation radar (13.8 GHz) and are compared with the observations averaged at model resolution. The averaging process is validated using a sophisticated downscaling/upscaling approach that is based on wavelet decomposition. The precipitation radar measurements are ideal for this validation exercise, being approximately collocated with but completely independent of the TRMM Microwave Imager (TMI) radiometer measurements. Qualitative and statistical comparisons between radar observations and retrievals from the TMI-derived surface rain rates and from TMI radiances are made using 17 well-documented tropical cyclone occurrences between January and April of 2003. Several statistical measures, such as bias, root-mean-square error, and Heidke skill score, are introduced to assess the 1D-Var skill as well as the model background skill in producing a realistic rain distribution. Results show a good degree of skill in the retrievals, especially near the surface and for medium–heavy rain. The model background produces precipitation in the domain that is sometimes in excess with respect to the observations, and it often shows an error in the location of precipitation maxima. Differences between the two 1D-Var approaches are not large enough to make final conclusions regarding the advantages of one method over the other. Both methods are capable of redistributing the rain patterns according to the observations. It appears, however, that the brightness temperature approach is in general more effective in increasing precipitation amounts at moderate-to-high rainfall rates.

Full access
John E. Janowiak, Peter Bauer, Wanqiu Wang, Phillip A. Arkin, and Jon Gottschalck

Abstract

In this paper, the results of an examination of precipitation forecasts for 1–30-day leads from global models run at the European Centre for Medium-Range Weather Forecasts (ECMWF) and the National Centers for Environmental Prediction (NCEP) during November 2007–February 2008 are presented. The performance of the model precipitation forecasts are examined in global and regional contexts, and results of a case study of precipitation variations that are associated with a moderate to strong Madden–Julian oscillation (MJO) event are presented.

The precipitation forecasts from the ECMWF and NCEP operational prediction models have nearly identical temporal correlation with observed precipitation at forecast leads from 2 to 9 days over the Northern Hemisphere during the cool season, despite the higher resolution of the ECMWF operational model, while the ECMWF operational model forecasts are slightly better in the tropics and the Southern Hemisphere during the warm season. The ECMWF Re-Analysis Interim (ERA-Interim) precipitation forecasts perform only slightly worse than the NCEP operational model, while NCEP’s Climate Forecast System low-resolution coupled model forecasts perform the worst among the four models. In terms of bias, the ECMWF operational model performs the best among the four model forecasts that were examined, particularly with respect to the ITCZ regions in both the Atlantic and Pacific. Local temporal correlations that were computed on daily precipitation totals for day-2 forecasts against observations indicate that the operational models at ECMWF and NCEP perform the best during the 4-month study period, and that all of the models have low to insignificant correlations over land and over much of the tropics. They perform the best in subtropical and extratropical oceanic regions.

Also presented are results that show that striking improvements have been made over the past two decades in the ability of the models to represent precipitation variations that are associated with MJO. The model precipitation forecasts exhibit the ability to characterize the evolution of precipitation variations during a moderate–strong period of MJO conditions for forecast leads as long as 10 days.

Full access
William S. Olson, Peter Bauer, Nicolas F. Viltard, Daniel E. Johnson, Wei-Kuo Tao, Robert Meneghini, and Liang Liao

Abstract

In this study, a 1D steady-state microphysical model that describes the vertical distribution of melting precipitation particles is developed. The model is driven by the ice-phase precipitation distributions just above the freezing level at applicable grid points of “parent” 3D cloud-resolving model (CRM) simulations. It extends these simulations by providing the number density and meltwater fraction of each particle in finely separated size categories through the melting layer. The depth of the modeled melting layer is primarily determined by the initial material density of the ice-phase precipitation. The radiative properties of melting precipitation at microwave frequencies are calculated based upon different methods for describing the dielectric properties of mixed-phase particles. Particle absorption and scattering efficiencies at the Tropical Rainfall Measuring Mission Microwave Imager frequencies (10.65–85.5 GHz) are enhanced greatly for relatively small (∼0.1) meltwater fractions. The relatively large number of partially melted particles just below the freezing level in stratiform regions leads to significant microwave absorption, well exceeding the absorption by rain at the base of the melting layer. Calculated precipitation backscatter efficiencies at the precipitation radar frequency (13.8 GHz) increase with particle meltwater fraction, leading to a “bright band” of enhanced radar reflectivities in agreement with previous studies. The radiative properties of the melting layer are determined by the choice of dielectric models and the initial water contents and material densities of the “seeding” ice-phase precipitation particles. Simulated melting-layer profiles based upon snow described by the Fabry–Szyrmer core-shell dielectric model and graupel described by the Maxwell-Garnett water matrix dielectric model lead to reasonable agreement with radar-derived melting-layer optical depth distributions. Moreover, control profiles that do not contain mixed-phase precipitation particles yield optical depths that are systematically lower than those observed. Therefore, the use of the melting-layer model to extend 3D CRM simulations is likely justified, at least until more-realistic spectral methods for describing melting precipitation in high-resolution, 3D CRMs are implemented.

Full access
Dorothy Koch, Susanne E. Bauer, Anthony Del Genio, Greg Faluvegi, Joseph R. McConnell, Surabi Menon, Ronald L. Miller, David Rind, Reto Ruedy, Gavin A. Schmidt, and Drew Shindell

Abstract

The authors simulate transient twentieth-century climate in the Goddard Institute for Space Studies (GISS) GCM, with aerosol and ozone chemistry fully coupled to one another and to climate including a full dynamic ocean. Aerosols include sulfate, black carbon (BC), organic carbon, nitrate, sea salt, and dust. Direct and BC-snow-albedo radiative effects are included. Model BC and sulfur trends agree fairly well with records from Greenland and European ice cores and with sulfur deposition in North America; however, the model underestimates the sulfur decline at the end of the century in Greenland. Global BC effects peak early in the century (1940s); afterward the BC effects decrease at high latitudes of the Northern Hemisphere but continue to increase at lower latitudes. The largest increase in aerosol optical depth occurs in the middle of the century (1940s–80s) when sulfate forcing peaks and causes global dimming. After this, aerosols decrease in eastern North America and northern Eurasia leading to regional positive forcing changes and brightening. These surface forcing changes have the correct trend but are too weak. Over the century, the net aerosol direct effect is −0.41 W m−2, the BC-albedo effect is −0.02 W m−2, and the net ozone forcing is +0.24 W m−2. The model polar stratospheric ozone depletion develops, beginning in the 1970s. Concurrently, the sea salt load and negative radiative flux increase over the oceans around Antarctica. Net warming over the century is modeled fairly well; however, the model fails to capture the dynamics of the observed midcentury cooling followed by the late century warming. Over the century, 20% of Arctic warming and snow–ice cover loss is attributed to the BC-albedo effect. However, the decrease in this effect at the end of the century contributes to Arctic cooling.

To test the climate responses to sulfate and BC pollution, two experiments were branched from 1970 that removed all pollution sulfate or BC. Averaged over 1970–2000, the respective radiative forcings relative to the full experiment were +0.3 and −0.3 W m−2; the average surface air temperature changes were +0.2° and −0.03°C. The small impact of BC reduction on surface temperature resulted from reduced stability and loss of low-level clouds.

Full access
E. A. Smith, J. E. Lamm, R. Adler, J. Alishouse, K. Aonashi, E. Barrett, P. Bauer, W. Berg, A. Chang, R. Ferraro, J. Ferriday, S. Goodman, N. Grody, C. Kidd, D. Kniveton, C. Kummerow, G. Liu, F. Marzano, A. Mugnai, W. Olson, G. Petty, A. Shibata, R. Spencer, F. Wentz, T. Wilheit, and E. Zipser

Abstract

The second WetNet Precipitation Intercomparison Project (PIP-2) evaluates the performance of 20 satellite precipitation retrieval algorithms, implemented for application with Special Sensor Microwave/Imager (SSM/I) passive microwave (PMW) measurements and run for a set of rainfall case studies at full resolution–instantaneous space–timescales. The cases are drawn from over the globe during all seasons, for a period of 7 yr, over a 60°N–17°S latitude range. Ground-based data were used for the intercomparisons, principally based on radar measurements but also including rain gauge measurements. The goals of PIP-2 are 1) to improve performance and accuracy of different SSM/I algorithms at full resolution–instantaneous scales by seeking a better understanding of the relationship between microphysical signatures in the PMW measurements and physical laws employed in the algorithms; 2) to evaluate the pros and cons of individual algorithms and their subsystems in order to seek optimal “front-end” combined algorithms; and 3) to demonstrate that PMW algorithms generate acceptable instantaneous rain estimates.

It is found that the bias uncertainty of many current PMW algorithms is on the order of ±30%. This level is below that of the radar and rain gauge data specially collected for the study, so that it is not possible to objectively select a best algorithm based on the ground data validation approach. By decomposing the intercomparisons into effects due to rain detection (screening) and effects due to brightness temperature–rain rate conversion, differences among the algorithms are partitioned by rain area and rain intensity. For ocean, the screening differences mainly affect the light rain rates, which do not contribute significantly to area-averaged rain rates. The major sources of differences in mean rain rates between individual algorithms stem from differences in how intense rain rates are calculated and the maximum rain rate allowed by a given algorithm. The general method of solution is not necessarily the determining factor in creating systematic rain-rate differences among groups of algorithms, as we find that the severity of the screen is the dominant factor in producing systematic group differences among land algorithms, while the input channel selection is the dominant factor in producing systematic group differences among ocean algorithms. The significance of these issues are examined through what is called “fan map” analysis.

The paper concludes with a discussion on the role of intercomparison projects in seeking improvements to algorithms, and a suggestion on why moving beyond the “ground truth” validation approach by use of a calibration-quality forward model would be a step forward in seeking objective evaluation of individual algorithm performance and optimal algorithm design.

Full access
Gavin A. Schmidt, Reto Ruedy, James E. Hansen, Igor Aleinov, Nadine Bell, Mike Bauer, Susanne Bauer, Brian Cairns, Vittorio Canuto, Ye Cheng, Anthony Del Genio, Greg Faluvegi, Andrew D. Friend, Tim M. Hall, Yongyun Hu, Max Kelley, Nancy Y. Kiang, Dorothy Koch, Andy A. Lacis, Jean Lerner, Ken K. Lo, Ron L. Miller, Larissa Nazarenko, Valdar Oinas, Jan Perlwitz, Judith Perlwitz, David Rind, Anastasia Romanou, Gary L. Russell, Makiko Sato, Drew T. Shindell, Peter H. Stone, Shan Sun, Nick Tausnev, Duane Thresher, and Mao-Sung Yao

Abstract

A full description of the ModelE version of the Goddard Institute for Space Studies (GISS) atmospheric general circulation model (GCM) and results are presented for present-day climate simulations (ca. 1979). This version is a complete rewrite of previous models incorporating numerous improvements in basic physics, the stratospheric circulation, and forcing fields. Notable changes include the following: the model top is now above the stratopause, the number of vertical layers has increased, a new cloud microphysical scheme is used, vegetation biophysics now incorporates a sensitivity to humidity, atmospheric turbulence is calculated over the whole column, and new land snow and lake schemes are introduced. The performance of the model using three configurations with different horizontal and vertical resolutions is compared to quality-controlled in situ data, remotely sensed and reanalysis products. Overall, significant improvements over previous models are seen, particularly in upper-atmosphere temperatures and winds, cloud heights, precipitation, and sea level pressure. Data–model comparisons continue, however, to highlight persistent problems in the marine stratocumulus regions.

Full access
Armin Sorooshian, Bruce Anderson, Susanne E. Bauer, Rachel A. Braun, Brian Cairns, Ewan Crosbie, Hossein Dadashazar, Glenn Diskin, Richard Ferrare, Richard C. Flagan, Johnathan Hair, Chris Hostetler, Haflidi H. Jonsson, Mary M. Kleb, Hongyu Liu, Alexander B. MacDonald, Allison McComiskey, Richard Moore, David Painemal, Lynn M. Russell, John H. Seinfeld, Michael Shook, William L. Smith Jr, Kenneth Thornhill, George Tselioudis, Hailong Wang, Xubin Zeng, Bo Zhang, Luke Ziemba, and Paquita Zuidema

Abstract

We report on a multiyear set of airborne field campaigns (2005–16) off the California coast to examine aerosols, clouds, and meteorology, and how lessons learned tie into the upcoming NASA Earth Venture Suborbital (EVS-3) campaign: Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment (ACTIVATE; 2019–23). The largest uncertainty in estimating global anthropogenic radiative forcing is associated with the interactions of aerosol particles with clouds, which stems from the variability of cloud systems and the multiple feedbacks that affect and hamper efforts to ascribe changes in cloud properties to aerosol perturbations. While past campaigns have been limited in flight hours and the ability to fly in and around clouds, efforts sponsored by the Office of Naval Research have resulted in 113 single aircraft flights (>500 flight hours) in a fixed region with warm marine boundary layer clouds. All flights used nearly the same payload of instruments on a Twin Otter to fly below, in, and above clouds, producing an unprecedented dataset. We provide here i) an overview of statistics of aerosol, cloud, and meteorological conditions encountered in those campaigns and ii) quantification of model-relevant metrics associated with aerosol–cloud interactions leveraging the high data volume and statistics. Based on lessons learned from those flights, we describe the pragmatic innovation in sampling strategy (dual-aircraft approach with combined in situ and remote sensing) that will be used in ACTIVATE to generate a dataset that can advance scientific understanding and improve physical parameterizations for Earth system and weather forecasting models, and for assessing next-generation remote sensing retrieval algorithms.

Open access