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  • Author or Editor: E. V. Browell x
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D. N. Whiteman
,
B. Demoz
,
G. Schwemmer
,
B. Gentry
,
P. Di Girolamo
,
D. Sabatino
,
J. Comer
,
I. Veselovskii
,
K. Evans
,
R-F. Lin
,
Z. Wang
,
A. Behrendt
,
V. Wulfmeyer
,
E. Browell
,
R. Ferrare
,
S. Ismail
, and
J. Wang

Abstract

The NASA GSFC Scanning Raman Lidar (SRL) participated in the International H2O Project (IHOP) that occurred in May and June 2002 in the midwestern part of the United States. The SRL system configuration and methods of data analysis were described in Part I of this paper. In this second part, comparisons of SRL water vapor measurements and those of Lidar Atmospheric Sensing Experiment (LASE) airborne water vapor lidar and chilled-mirror radiosonde are performed. Two case studies are then presented: one for daytime and one for nighttime. The daytime case study is of a convectively driven boundary layer event and is used to characterize the daytime SRL water vapor random error characteristics. The nighttime case study is of a thunderstorm-generated cirrus cloud case that is studied in its meteorological context. Upper-tropospheric humidification due to precipitation from the cirrus cloud is quantified as is the cirrus cloud optical depth, extinction-to-backscatter ratio, ice water content, cirrus particle size, and both particle and volume depolarization ratios. A stability and back-trajectory analysis is performed to study the origin of wave activity in one of the cloud layers. These unprecedented cirrus cloud measurements are being used in a cirrus cloud modeling study.

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R. A. Ferrare
,
E. V. Browell
,
S. Ismail
,
S. A. Kooi
,
L. H. Brasseur
,
V. G. Brackett
,
M. B. Clayton
,
J. D. W. Barrick
,
G. S. Diskin
,
J. E. M. Goldsmith
,
B. M. Lesht
,
J. R. Podolske
,
G. W. Sachse
,
F. J. Schmidlin
,
D. D. Turner
,
D. N. Whiteman
,
D. Tobin
,
L. M. Miloshevich
,
H. E. Revercomb
,
B. B. Demoz
, and
P. Di Girolamo

Abstract

Water vapor mass mixing ratio profiles from NASA's Lidar Atmospheric Sensing Experiment (LASE) system acquired during the Atmospheric Radiation Measurement (ARM)–First International Satellite Cloud Climatology Project (ISCCP) Regional Experiment (FIRE) Water Vapor Experiment (AFWEX) are used as a reference to characterize upper-troposphere water vapor (UTWV) measured by ground-based Raman lidars, radiosondes, and in situ aircraft sensors over the Department of Energy (DOE) ARM Southern Great Plains (SGP) site in northern Oklahoma. LASE was deployed from the NASA DC-8 aircraft and measured water vapor over the ARM SGP Central Facility (CF) site during seven flights between 27 November and 10 December 2000. Initially, the DOE ARM SGP Cloud and Radiation Testbed (CART) Raman lidar (CARL) UTWV profiles were about 5%–7% wetter than LASE in the upper troposphere, and the Vaisala RS80-H radiosonde profiles were about 10% drier than LASE between 8 and 12 km. Scaling the Vaisala water vapor profiles to match the precipitable water vapor (PWV) measured by the ARM SGP microwave radiometer (MWR) did not change these results significantly. By accounting for an overlap correction of the CARL water vapor profiles and by employing schemes designed to correct the Vaisala RS80-H calibration method and account for the time response of the Vaisala RS80-H water vapor sensor, the average differences between the CARL and Vaisala radiosonde upper-troposphere water vapor profiles are reduced to about 5%, which is within the ARM goal of mean differences of less than 10%. The LASE and DC-8 in situ diode laser hygrometer (DLH) UTWV measurements generally agreed to within about 3%–4%. The DC-8 in situ frost point cryogenic hygrometer and Snow White chilled-mirror measurements were drier than the LASE, Raman lidars, and corrected Vaisala RS80H measurements by about 10%–25% and 10%–15%, respectively. Sippican (formerly VIZ Manufacturing) carbon hygristor radiosondes exhibited large variabilities and poor agreement with the other measurements. PWV derived from the LASE profiles agreed to within about 3% on average with PWV derived from the ARM SGP microwave radiometer. The agreement between the LASE and MWR PWV and the LASE and CARL UTWV measurements supports the hypotheses that MWR measurements of the 22-GHz water vapor line can accurately constrain the total water vapor amount and that the CART Raman lidar, when calibrated using the MWR PWV, can provide an accurate, stable reference for characterizing upper-troposphere water vapor.

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M. P. McCormick
,
D. M. Winker
,
E. V. Browell
,
J. A. Coakley
,
C. S. Gardner
,
R. M. Hoff
,
G. S. Kent
,
S. H. Melfi
,
R. T. Menzies
,
C. M. R. Piatt
,
D. A. Randall
, and
J. A. Reagan

The Lidar In-Space Technology Experiment (LITE) is being developed by NASA/Langley Research Center for a series of flights on the space shuttle beginning in 1994. Employing a three-wavelength Nd:YAG laser and a 1-m-diameter telescope, the system is a test-bed for the development of technology required for future operational spaceborne lidars. The system has been designed to observe clouds, tropospheric and stratospheric aerosols, characteristics of the planetary boundary layer, and stratospheric density and temperature perturbations with much greater resolution than is available from current orbiting sensors. In addition to providing unique datasets on these phenomena, the data obtained will be useful in improving retrieval algorithms currently in use. Observations of clouds and the planetary boundary layer will aid in the development of global climate model (GCM) parameterizations. This article briefly describes the LITE program and discusses the types of scientific investigations planned for the first flight.

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Kenneth J. Davis
,
Edward V. Browell
,
Sha Feng
,
Thomas Lauvaux
,
Michael D. Obland
,
Sandip Pal
,
Bianca C. Baier
,
David F. Baker
,
Ian T. Baker
,
Zachary R. Barkley
,
Kevin W. Bowman
,
Yu Yan Cui
,
A. Scott Denning
,
Joshua P. DiGangi
,
Jeremy T. Dobler
,
Alan Fried
,
Tobias Gerken
,
Klaus Keller
,
Bing Lin
,
Amin R. Nehrir
,
Caroline P. Normile
,
Christopher W. O’Dell
,
Lesley E. Ott
,
Anke Roiger
,
Andrew E. Schuh
,
Colm Sweeney
,
Yaxing Wei
,
Brad Weir
,
Ming Xue
, and
Christopher A. Williams

Abstract

The Atmospheric Carbon and Transport (ACT)-America NASA Earth Venture Suborbital Mission set out to improve regional atmospheric greenhouse gas (GHG) inversions by exploring the intersection of the strong GHG fluxes and vigorous atmospheric transport that occurs within the midlatitudes. Two research aircraft instrumented with remote and in situ sensors to measure GHG mole fractions, associated trace gases, and atmospheric state variables collected 1,140.7 flight hours of research data, distributed across 305 individual aircraft sorties, coordinated within 121 research flight days, and spanning five 6-week seasonal flight campaigns in the central and eastern United States. Flights sampled 31 synoptic sequences, including fair-weather and frontal conditions, at altitudes ranging from the atmospheric boundary layer to the upper free troposphere. The observations were complemented with global and regional GHG flux and transport model ensembles. We found that midlatitude weather systems contain large spatial gradients in GHG mole fractions, in patterns that were consistent as a function of season and altitude. We attribute these patterns to a combination of regional terrestrial fluxes and inflow from the continental boundaries. These observations, when segregated according to altitude and air mass, provide a variety of quantitative insights into the realism of regional CO2 and CH4 fluxes and atmospheric GHG transport realizations. The ACT-America dataset and ensemble modeling methods provide benchmarks for the development of atmospheric inversion systems. As global and regional atmospheric inversions incorporate ACT-America’s findings and methods, we anticipate these systems will produce increasingly accurate and precise subcontinental GHG flux estimates.

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Christopher J. White
,
Daniela I. V. Domeisen
,
Nachiketa Acharya
,
Elijah A. Adefisan
,
Michael L. Anderson
,
Stella Aura
,
Ahmed A. Balogun
,
Douglas Bertram
,
Sonia Bluhm
,
David J. Brayshaw
,
Jethro Browell
,
Dominik Büeler
,
Andrew Charlton-Perez
,
Xandre Chourio
,
Isadora Christel
,
Caio A. S. Coelho
,
Michael J. DeFlorio
,
Luca Delle Monache
,
Francesca Di Giuseppe
,
Ana María García-Solórzano
,
Peter B. Gibson
,
Lisa Goddard
,
Carmen González Romero
,
Richard J. Graham
,
Robert M. Graham
,
Christian M. Grams
,
Alan Halford
,
W. T. Katty Huang
,
Kjeld Jensen
,
Mary Kilavi
,
Kamoru A. Lawal
,
Robert W. Lee
,
David MacLeod
,
Andrea Manrique-Suñén
,
Eduardo S. P. R. Martins
,
Carolyn J. Maxwell
,
William J. Merryfield
,
Ángel G. Muñoz
,
Eniola Olaniyan
,
George Otieno
,
John A. Oyedepo
,
Lluís Palma
,
Ilias G. Pechlivanidis
,
Diego Pons
,
F. Martin Ralph
,
Dirceu S. Reis Jr.
,
Tomas A. Remenyi
,
James S. Risbey
,
Donald J. C. Robertson
,
Andrew W. Robertson
,
Stefan Smith
,
Albert Soret
,
Ting Sun
,
Martin C. Todd
,
Carly R. Tozer
,
Francisco C. Vasconcelos Jr.
,
Ilaria Vigo
,
Duane E. Waliser
,
Fredrik Wetterhall
, and
Robert G. Wilson

Abstract

The subseasonal-to-seasonal (S2S) predictive time scale, encompassing lead times ranging from 2 weeks to a season, is at the frontier of forecasting science. Forecasts on this time scale provide opportunities for enhanced application-focused capabilities to complement existing weather and climate services and products. There is, however, a “knowledge–value” gap, where a lack of evidence and awareness of the potential socioeconomic benefits of S2S forecasts limits their wider uptake. To address this gap, here we present the first global community effort at summarizing relevant applications of S2S forecasts to guide further decision-making and support the continued development of S2S forecasts and related services. Focusing on 12 sectoral case studies spanning public health, agriculture, water resource management, renewable energy and utilities, and emergency management and response, we draw on recent advancements to explore their application and utility. These case studies mark a significant step forward in moving from potential to actual S2S forecasting applications. We show that by placing user needs at the forefront of S2S forecast development—demonstrating both skill and utility across sectors—this dialogue can be used to help promote and accelerate the awareness, value, and cogeneration of S2S forecasts. We also highlight that while S2S forecasts are increasingly gaining interest among users, incorporating probabilistic S2S forecasts into existing decision-making operations is not trivial. Nevertheless, S2S forecasting represents a significant opportunity to generate useful, usable, and actionable forecast applications for and with users that will increasingly unlock the potential of this forecasting time scale.

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