Search Results

You are looking at 21 - 29 of 29 items for

  • Author or Editor: P. Minnis x
  • Refine by Access: All Content x
Clear All Modify Search
Stanley G. Benjamin
,
Eric P. James
,
Ming Hu
,
Curtis R. Alexander
,
Therese T. Ladwig
,
John M. Brown
,
Stephen S. Weygandt
,
David D. Turner
,
Patrick Minnis
,
William L. Smith Jr.
, and
Andrew K. Heidinger

Abstract

Accurate cloud and precipitation forecasts are a fundamental component of short-range data assimilation/model prediction systems such as the NOAA 3-km High-Resolution Rapid Refresh (HRRR) or the 13-km Rapid Refresh (RAP). To reduce cloud and precipitation spinup problems, a nonvariational assimilation technique for stratiform clouds was developed within the Gridpoint Statistical Interpolation (GSI) data assimilation system. One goal of this technique is retention of observed stratiform cloudy and clear 3D volumes into the subsequent model forecast. The cloud observations used include cloud-top data from satellite brightness temperatures, surface-based ceilometer data, and surface visibility. Quality control, expansion into spatial information content, and forward operators are described for each observation type. The projection of data from these observation types into an observation-based cloud-information 3D gridded field is accomplished via identification of cloudy, clear, and cloud-unknown 3D volumes. Updating of forecast background fields is accomplished through clearing and building of cloud water and cloud ice with associated modifications to water vapor and temperature. Impact of the cloud assimilation on short-range forecasts is assessed with a set of retrospective experiments in warm and cold seasons using the RAPv5 model. Short-range (1–9 h) forecast skill is improved in both seasons for cloud ceiling and visibility and for 2-m temperature in daytime and with mixed results for other measures. Two modifications were introduced and tested with success: use of prognostic subgrid-scale cloud fraction to condition cloud building (in response to a high bias) and removal of a WRF-based rebalancing.

Open access
M. Goldberg
,
G. Ohring
,
J. Butler
,
C. Cao
,
R. Datla
,
D. Doelling
,
V. Gärtner
,
T. Hewison
,
B. Iacovazzi
,
D. Kim
,
T. Kurino
,
J. Lafeuille
,
P. Minnis
,
D. Renaut
,
J. Schmetz
,
D. Tobin
,
L. Wang
,
F. Weng
,
X. Wu
,
F. Yu
,
P. Zhang
, and
T. Zhu

The Global Space-based Inter-Calibration System (GSICS) is a new international program to assure the comparability of satellite measurements taken at different times and locations by different instruments operated by different satellite agencies. Sponsored by the World Meteorological Organization and the Coordination Group for Meteorological Satellites, GSICS will intercalibrate the instruments of the international constellation of operational low-earth-orbiting (LEO) and geostationary earth-orbiting (GEO) environmental satellites and tie these to common reference standards. The intercomparability of the observations will result in more accurate measurements for assimilation in numerical weather prediction models, construction of more reliable climate data records, and progress toward achieving the societal goals of the Global Earth Observation System of Systems. GSICS includes globally coordinated activities for prelaunch instrument characterization, onboard routine calibration, sensor intercomparison of near-simultaneous observations of individual scenes or overlapping time series, vicarious calibration using Earth-based or celestial references, and field campaigns. An initial strategy uses high-accuracy satellite instruments, such as the NASA Moderate Resolution Imaging Spectroradiometer (MODIS) and Atmospheric Infrared Sounder (AIRS) and the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT)'s Centre National d'Études Spatiales (CNES) Infrared Atmospheric Sounding Interferometer (IASI), as space-based reference standards for intercalibrating the operational satellite sensors. Examples of initial intercalibration results and future plans are presented. Agencies participating in the program include the Centre National d'Études Spatiales, China Meteorological Administration, EUMETSAT, Japan Meteorological Agency, Korea Meteorological Administration, NASA, National Institute of Standards and Technology, and NOAA.

Full access
T. J. Garrett
,
B. C. Navarro
,
C. H. Twohy
,
E. J. Jensen
,
D. G. Baumgardner
,
P. T. Bui
,
H. Gerber
,
R. L. Herman
,
A. J. Heymsfield
,
P. Lawson
,
P. Minnis
,
L. Nguyen
,
M. Poellot
,
S. K. Pope
,
F. P. J. Valero
, and
E. M. Weinstock

Abstract

This paper presents a detailed study of a single thunderstorm anvil cirrus cloud measured on 21 July 2002 near southern Florida during the Cirrus Regional Study of Tropical Anvils and Cirrus Layers–Florida Area Cirrus Experiment (CRYSTAL-FACE). NASA WB-57F and University of North Dakota Citation aircraft tracked the microphysical and radiative development of the anvil for 3 h. Measurements showed that the cloud mass that was advected downwind from the thunderstorm was separated vertically into two layers: a cirrus anvil with cloud-top temperatures of −45°C lay below a second, thin tropopause cirrus (TTC) layer with the same horizontal dimensions as the anvil and temperatures near −70°C. In both cloud layers, ice crystals smaller than 50 μm across dominated the size distributions and cloud radiative properties. In the anvil, ice crystals larger than 50 μm aggregated and precipitated while small ice crystals increasingly dominated the size distributions; as a consequence, measured ice water contents and ice crystal effective radii decreased with time. Meanwhile, the anvil thinned vertically and maintained a stratification similar to its environment. Because effective radii were small, radiative heating and cooling were concentrated in layers approximately 100 m thick at the anvil top and base. A simple analysis suggests that the anvil cirrus spread laterally because mixing in these radiatively driven layers created horizontal pressure gradients between the cloud and its stratified environment. The TTC layer also spread but, unlike the anvil, did not dissipate—perhaps because the anvil shielded the TTC from terrestrial infrared heating. Calculations of top-of-troposphere radiative forcing above the anvil and TTC showed strong cooling that tapered as the anvil evolved.

Full access
G. L. Stephens
,
R. G. Ellingson
,
J. Vitko Jr.
,
W. Bolton
,
T. P. Tooman
,
F. P. J. Valero
,
P. Minnis
,
P. Pilewskie
,
G. S. Phipps
,
S. Sekelsky
,
J. R. Carswell
,
S. D. Miller
,
A. Benedetti
,
R. B. McCoy
,
R. F. McCoy Jr.
,
A. Lederbuhr
, and
R. Bambha

The U.S. Department of Energy has established an unmanned aerospace vehicle (UAV) measurement program. The purpose of this paper is to describe the evolution of the program since its inception, review the progress of the program, summarize the measurement capabilities developed under the program, illustrate key results from the various UAV campaigns carried out to date, and provide a sense of the future direction of the program. The Atmospheric Radiation Measurement (ARM)–UAV program has demonstrated how measurements from unmanned aircraft platforms operating under the various constraints imposed by different science experiments can contribute to our understanding of cloud and radiative processes. The program was first introduced in 1991 and has evolved in the form of four phases of activity each culminating in one or more flight campaigns. A total of 8 flight campaigns produced over 140 h of science flights using three different UAV platforms. The UAV platforms and their capabilities are described as are the various phases of the program development. Examples of data collected from various campaigns highlight the powerful nature of the observing system developed under the auspices of the ARM–UAV program and confirm the viability of the UAV platform for the kinds of research of interest to ARM and the clouds and radiation community as a whole. The specific examples include applications of the data in the study of radiative transfer through clouds, the evaluation of cloud parameterizations, and the development and evaluation of cloud remote sensing methods. A number of notable and novel achievements of the program are also highlighted.

Full access
J. A. Curry
,
P. V. Hobbs
,
M. D. King
,
D. A. Randall
,
P. Minnis
,
G. A. Isaac
,
J. O. Pinto
,
T. Uttal
,
A. Bucholtz
,
D. G. Cripe
,
H. Gerber
,
C. W. Fairall
,
T. J. Garrett
,
J. Hudson
,
J. M. Intrieri
,
C. Jakob
,
T. Jensen
,
P. Lawson
,
D. Marcotte
,
L. Nguyen
,
P. Pilewskie
,
A. Rangno
,
D. C. Rogers
,
K. B. Strawbridge
,
F. P. J. Valero
,
A. G. Williams
, and
D. Wylie

An overview is given of the First ISCCP Regional Experiment Arctic Clouds Experiment that was conducted during April–July 1998. The principal goal of the field experiment was to gather the data needed to examine the impact of arctic clouds on the radiation exchange between the surface, atmosphere, and space, and to study how the surface influences the evolution of boundary layer clouds. The observations will be used to evaluate and improve climate model parameterizations of cloud and radiation processes, satellite remote sensing of cloud and surface characteristics, and understanding of cloud–radiation feedbacks in the Arctic. The experiment utilized four research aircraft that flew over surface-based observational sites in the Arctic Ocean and at Barrow, Alaska. This paper describes the programmatic and scientific objectives of the project, the experimental design (including research platforms and instrumentation), the conditions that were encountered during the field experiment, and some highlights of preliminary observations, modeling, and satellite remote sensing studies.

Full access
D.L. Westphal
,
S. Kinne
,
P. Pilewskie
,
J.M. Alvarez
,
P. Minnis
,
D.F. Young
,
S.G. Benjamin
,
W.L. Eberhard
,
R.A. Kropfli
,
S.Y. Matrosov
,
J.B. Snider
,
T.A. Uttal
,
A.J. Heymsfield
,
G.G. Mace
,
S.H. Melfi
,
D.O'C. Starr
, and
J.J. Soden

Abstract

Observations from a wide variety of instruments and platforms are used to validate many different aspects of a three-dimensional mesoscale simulation of the dynamics, cloud microphysics, and radiative transfer of a cirrus cloud system observed on 26 November 1991 during the second cirrus field program of the First International Satellite Cloud Climatology Program (ISCCP) Regional Experiment (FIRE-II) located in southeastern Kansas. The simulation was made with a mesoscale dynamical model utilizing a simplified bulk water cloud scheme and a spectral model of radiative transfer. Expressions for cirrus optical properties for solar and infrared wavelength intervals as functions of ice water content and effective particle radius are modified for the midlatitude cirrus observed during FIRE-II and are shown to compare favorably with explicit size-resolving calculations of the optical properties. Rawinsonde, Raman lidar, and satellite data are evaluated and combined to produce a time–height cross section of humidity at the central FIRE-II site for model verification. Due to the wide spacing of rawinsondes and their infrequent release, important moisture features go undetected and are absent in the conventional analyses. The upper-tropospheric humidities used for the initial conditions were generally less than 50% of those inferred from satellite data, yet over the course of a 24-h simulation the model produced a distribution that closely resembles the large-scale features of the satellite analysis. The simulated distribution and concentration of ice compares favorably with data from radar, lidar, satellite, and aircraft. Direct comparison is made between the radiative transfer simulation and data from broadband and spectral sensors and inferred quantities such as cloud albedo, optical depth, and top-of-the-atmosphere 11-µm brightness temperature, and the 6.7-µm brightness temperature. Comparison is also made with theoretical heating rates calculated using the rawinsonde data and measured ice water size distributions near the central site. For this case study, and perhaps for most other mesoscale applications, the differences between the observed and simulated radiative quantities are due more to errors in the prediction of ice water content, than to errors in the optical properties or the radiative transfer solution technique.

Full access
C. J. Stubenrauch
,
W. B. Rossow
,
S. Kinne
,
S. Ackerman
,
G. Cesana
,
H. Chepfer
,
L. Di Girolamo
,
B. Getzewich
,
A. Guignard
,
A. Heidinger
,
B. C. Maddux
,
W. P. Menzel
,
P. Minnis
,
C. Pearl
,
S. Platnick
,
C. Poulsen
,
J. Riedi
,
S. Sun-Mack
,
A. Walther
,
D. Winker
,
S. Zeng
, and
G. Zhao

Clouds cover about 70% of Earth's surface and play a dominant role in the energy and water cycle of our planet. Only satellite observations provide a continuous survey of the state of the atmosphere over the entire globe and across the wide range of spatial and temporal scales that compose weather and climate variability. Satellite cloud data records now exceed more than 25 years; however, climate data records must be compiled from different satellite datasets and can exhibit systematic biases. Questions therefore arise as to the accuracy and limitations of the various sensors and retrieval methods. The Global Energy and Water Cycle Experiment (GEWEX) Cloud Assessment, initiated in 2005 by the GEWEX Radiation Panel (GEWEX Data and Assessment Panel since 2011), provides the first coordinated intercomparison of publicly available, standard global cloud products (gridded monthly statistics) retrieved from measurements of multispectral imagers (some with multiangle view and polarization capabilities), IR sounders, and lidar. Cloud properties under study include cloud amount, cloud height (in terms of pressure, temperature, or altitude), cloud thermodynamic phase, and cloud radiative and bulk microphysical properties (optical depth or emissivity, effective particle radius, and water path). Differences in average cloud properties, especially in the amount of high-level clouds, are mostly explained by the inherent instrument measurement capability for detecting and/or identifying optically thin cirrus, especially when overlying low-level clouds. The study of long-term variations with these datasets requires consideration of many factors. The monthly gridded database presented here facilitates further assessments, climate studies, and the evaluation of climate models.

Full access
J. Verlinde
,
J. Y. Harrington
,
G. M. McFarquhar
,
V. T. Yannuzzi
,
A. Avramov
,
S. Greenberg
,
N. Johnson
,
G. Zhang
,
M. R. Poellot
,
J. H. Mather
,
D. D. Turner
,
E. W. Eloranta
,
B. D. Zak
,
A. J. Prenni
,
J. S. Daniel
,
G. L. Kok
,
D. C. Tobin
,
R. Holz
,
K. Sassen
,
D. Spangenberg
,
P. Minnis
,
T. P. Tooman
,
M. D. Ivey
,
S. J. Richardson
,
C. P. Bahrmann
,
M. Shupe
,
P. J. DeMott
,
A. J. Heymsfield
, and
R. Schofield

The Mixed-Phase Arctic Cloud Experiment (M-PACE) was conducted from 27 September through 22 October 2004 over the Department of Energy's Atmospheric Radiation Measurement (ARM) Climate Research Facility (ACRF) on the North Slope of Alaska. The primary objectives were to collect a dataset suitable to study interactions between microphysics, dynamics, and radiative transfer in mixed-phase Arctic clouds, and to develop/evaluate cloud property retrievals from surface-and satellite-based remote sensing instruments. Observations taken during the 1977/98 Surface Heat and Energy Budget of the Arctic (SHEBA) experiment revealed that Arctic clouds frequently consist of one (or more) liquid layers precipitating ice. M-PACE sought to investigate the physical processes of these clouds by utilizing two aircraft (an in situ aircraft to characterize the microphysical properties of the clouds and a remote sensing aircraft to constraint the upwelling radiation) over the ACRF site on the North Slope of Alaska. The measurements successfully documented the microphysical structure of Arctic mixed-phase clouds, with multiple in situ profiles collected in both single- and multilayer clouds over two ground-based remote sensing sites. Liquid was found in clouds with cloud-top temperatures as cold as −30°C, with the coldest cloud-top temperature warmer than −40°C sampled by the aircraft. Remote sensing instruments suggest that ice was present in low concentrations, mostly concentrated in precipitation shafts, although there are indications of light ice precipitation present below the optically thick single-layer clouds. The prevalence of liquid down to these low temperatures potentially could be explained by the relatively low measured ice nuclei concentrations.

Full access
Guy P. Brasseur
,
Mohan Gupta
,
Bruce E. Anderson
,
Sathya Balasubramanian
,
Steven Barrett
,
David Duda
,
Gregg Fleming
,
Piers M. Forster
,
Jan Fuglestvedt
,
Andrew Gettelman
,
Rangasayi N. Halthore
,
S. Daniel Jacob
,
Mark Z. Jacobson
,
Arezoo Khodayari
,
Kuo-Nan Liou
,
Marianne T. Lund
,
Richard C. Miake-Lye
,
Patrick Minnis
,
Seth Olsen
,
Joyce E. Penner
,
Ronald Prinn
,
Ulrich Schumann
,
Henry B. Selkirk
,
Andrei Sokolov
,
Nadine Unger
,
Philip Wolfe
,
Hsi-Wu Wong
,
Donald W. Wuebbles
,
Bingqi Yi
,
Ping Yang
, and
Cheng Zhou

Abstract

Under the Federal Aviation Administration’s (FAA) Aviation Climate Change Research Initiative (ACCRI), non-CO2 climatic impacts of commercial aviation are assessed for current (2006) and for future (2050) baseline and mitigation scenarios. The effects of the non-CO2 aircraft emissions are examined using a number of advanced climate and atmospheric chemistry transport models. Radiative forcing (RF) estimates for individual forcing effects are provided as a range for comparison against those published in the literature. Preliminary results for selected RF components for 2050 scenarios indicate that a 2% increase in fuel efficiency and a decrease in NOx emissions due to advanced aircraft technologies and operational procedures, as well as the introduction of renewable alternative fuels, will significantly decrease future aviation climate impacts. In particular, the use of renewable fuels will further decrease RF associated with sulfate aerosol and black carbon. While this focused ACCRI program effort has yielded significant new knowledge, fundamental uncertainties remain in our understanding of aviation climate impacts. These include several chemical and physical processes associated with NOx–O3–CH4 interactions and the formation of aviation-produced contrails and the effects of aviation soot aerosols on cirrus clouds as well as on deriving a measure of change in temperature from RF for aviation non-CO2 climate impacts—an important metric that informs decision-making.

Full access