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A. C. Best

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R. L. H. Essery
,
M. J. Best
,
R. A. Betts
,
P. M. Cox
, and
C. M. Taylor

Abstract

A land surface scheme that may be run with or without a tiled representation of subgrid heterogeneity and includes an implicit atmospheric coupling scheme is described. Simulated average surface air temperatures and diurnal temperature ranges in a GCM using this surface model are compared with climatology. Surface tiling is not found to give a clear improvement in the simulated climate but offers more flexibility in the representation of heterogeneous land surface processes. Using the same meteorological forcing in offline simulations using versions of the surface model with and without tiling, the tiled model gives slightly lower winter temperatures at high latitudes and higher summer temperatures at midlatitudes. When the surface model is coupled to a GCM, reduced evaporation in the tiled version leads to changes in cloud cover and radiation at the surface that enhance these differences.

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L. A. Sromovsky
,
J. R. Anderson
,
F. A. Best
,
J. P. Boyle
,
C. A. Sisko
, and
V. E. Suomi

Abstract

An untended instrument to measure ocean surface heat flux has been developed for use in support of field experiments and the investigation of heat flux parameterization techniques. The sensing component of the Skin-Layer Ocean Heat Flux Instrument (SOHFI) consists of two simple thermopile heat flux sensors suspended by a fiberglass mesh mounted inside a ring-shaped surface float. These sensors make direct measurements within the conduction layer, where they are held in place by a balance between surface tension and float buoyancy. The two sensors are designed with differing solar absorption properties so that surface heat flux can be distinguished from direct solar irradiance. Under laboratory conditions, the SOHFI measurements agree well with calorimetric measurements (generally to within 10%). Performance in freshwater and ocean environments is discussed in a companion paper.

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L. A. Sromovsky
,
J. R. Anderson
,
F. A. Best
,
J. P. Boyle
,
C. A. Sisko
, and
V. E. Suomi

Abstract

The Skin-Layer Ocean Heat Flux Instrument (SOHFI) described by Sromovsky et al. (Part I, this issue) was field-tested in a combination of freshwater and ocean deployments. Solar irradiance monitoring and field calibration techniques were demonstrated by comparison with independent measurements. Tracking of solar irradiance diurnal variations appears to be accurate to within about 5% of full scale. Preliminary field tests of the SOHFI have shown reasonably close agreement with bulk aerodynamic heat flux estimates in freshwater and ocean environments (generally within about 20%) under low to moderate wind conditions. Performance under heavy weather suggests a need to develop better methods of submergence filtering. Ocean deployments and recoveries of drifting SOHFI-equipped buoys were made during May and June 1995, during the Combined Sensor Program of 1996 in the western tropical Pacific region, and in the Greenland Sea in May 1997. The Gulf Stream and Greenland Sea deployments pointed out the need for design modifications to improve resistance to seabird attacks. Better estimates of performance and limitations of this device require extended intercomparison tests under field conditions.

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Executive Committee
,
E. Bollay
,
A. K. Blackadar
,
G. S. Benton
,
D. S. Johnson
,
W. H. Best Jr.
,
W. V. Burt
,
K. C. Spengler
, and
D. F. Landrigan
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R. O. Knuteson
,
H. E. Revercomb
,
F. A. Best
,
N. C. Ciganovich
,
R. G. Dedecker
,
T. P. Dirkx
,
S. C. Ellington
,
W. F. Feltz
,
R. K. Garcia
,
H. B. Howell
,
W. L. Smith
,
J. F. Short
, and
D. C. Tobin

Abstract

The Atmospheric Emitted Radiance Interferometer (AERI) instrument was developed for the Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Program by the University of Wisconsin Space Science and Engineering Center (UW-SSEC). The infrared emission spectra measured by the instrument have the sensitivity and absolute accuracy needed for atmospheric remote sensing and climate studies. The instrument design is described in a companion paper. This paper describes in detail the measured performance characteristics of the AERI instruments built for the ARM Program. In particular, the AERI systems achieve an absolute radiometric calibration of better than 1% (3σ) of ambient radiance, with a reproducibility of better than 0.2%. The knowledge of the AERI spectral calibration is better than 1.5 ppm (1σ) in the wavenumber range 400– 3000 cm−1.

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R. O. Knuteson
,
H. E. Revercomb
,
F. A. Best
,
N. C. Ciganovich
,
R. G. Dedecker
,
T. P. Dirkx
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S. C. Ellington
,
W. F. Feltz
,
R. K. Garcia
,
H. B. Howell
,
W. L. Smith
,
J. F. Short
, and
D. C. Tobin

Abstract

A ground-based Fourier transform spectrometer has been developed to measure the atmospheric downwelling infrared radiance spectrum at the earth's surface with high absolute accuracy. The Atmospheric Emitted Radiance Interferometer (AERI) instrument was designed and fabricated by the University of Wisconsin Space Science and Engineering Center (UW-SSEC) for the Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Program. This paper emphasizes the key features of the UW-SSEC instrument design that contribute to meeting the AERI instrument requirements for the ARM Program. These features include a highly accurate radiometric calibration system, an instrument controller that provides continuous and autonomous operation, an extensive data acquisition system for monitoring calibration temperatures and instrument health, and a real-time data processing system. In particular, focus is placed on design issues crucial to meeting the ARM requirements for radiometric calibration, spectral calibration, noise performance, and operational reliability. The detailed performance characteristics of the AERI instruments built for the ARM Program are described in a companion paper.

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M. J. Best
,
G. Abramowitz
,
H. R. Johnson
,
A. J. Pitman
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G. Balsamo
,
A. Boone
,
M. Cuntz
,
B. Decharme
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P. A. Dirmeyer
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J. Dong
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M. Ek
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Z. Guo
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V. Haverd
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B. J. J. van den Hurk
,
G. S. Nearing
,
B. Pak
,
C. Peters-Lidard
,
J. A. Santanello Jr.
,
L. Stevens
, and
N. Vuichard

Abstract

The Protocol for the Analysis of Land Surface Models (PALS) Land Surface Model Benchmarking Evaluation Project (PLUMBER) was designed to be a land surface model (LSM) benchmarking intercomparison. Unlike the traditional methods of LSM evaluation or comparison, benchmarking uses a fundamentally different approach in that it sets expectations of performance in a range of metrics a priori—before model simulations are performed. This can lead to very different conclusions about LSM performance. For this study, both simple physically based models and empirical relationships were used as the benchmarks. Simulations were performed with 13 LSMs using atmospheric forcing for 20 sites, and then model performance relative to these benchmarks was examined. Results show that even for commonly used statistical metrics, the LSMs’ performance varies considerably when compared to the different benchmarks. All models outperform the simple physically based benchmarks, but for sensible heat flux the LSMs are themselves outperformed by an out-of-sample linear regression against downward shortwave radiation. While moisture information is clearly central to latent heat flux prediction, the LSMs are still outperformed by a three-variable nonlinear regression that uses instantaneous atmospheric humidity and temperature in addition to downward shortwave radiation. These results highlight the limitations of the prevailing paradigm of LSM evaluation that simply compares an LSM to observations and to other LSMs without a mechanism to objectively quantify the expectations of performance. The authors conclude that their results challenge the conceptual view of energy partitioning at the land surface.

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C. S. B. Grimmond
,
M. Blackett
,
M. J. Best
,
J. Barlow
,
J-J. Baik
,
S. E. Belcher
,
S. I. Bohnenstengel
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I. Calmet
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F. Chen
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A. Dandou
,
K. Fortuniak
,
M. L. Gouvea
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R. Hamdi
,
M. Hendry
,
T. Kawai
,
Y. Kawamoto
,
H. Kondo
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E. S. Krayenhoff
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S-H. Lee
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T. Loridan
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A. Martilli
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V. Masson
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S. Miao
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K. Oleson
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G. Pigeon
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A. Porson
,
Y-H. Ryu
,
F. Salamanca
,
L. Shashua-Bar
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G-J. Steeneveld
,
M. Tombrou
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J. Voogt
,
D. Young
, and
N. Zhang

Abstract

A large number of urban surface energy balance models now exist with different assumptions about the important features of the surface and exchange processes that need to be incorporated. To date, no comparison of these models has been conducted; in contrast, models for natural surfaces have been compared extensively as part of the Project for Intercomparison of Land-surface Parameterization Schemes. Here, the methods and first results from an extensive international comparison of 33 models are presented. The aim of the comparison overall is to understand the complexity required to model energy and water exchanges in urban areas. The degree of complexity included in the models is outlined and impacts on model performance are discussed. During the comparison there have been significant developments in the models with resulting improvements in performance (root-mean-square error falling by up to two-thirds). Evaluation is based on a dataset containing net all-wave radiation, sensible heat, and latent heat flux observations for an industrial area in Vancouver, British Columbia, Canada. The aim of the comparison is twofold: to identify those modeling approaches that minimize the errors in the simulated fluxes of the urban energy balance and to determine the degree of model complexity required for accurate simulations. There is evidence that some classes of models perform better for individual fluxes but no model performs best or worst for all fluxes. In general, the simpler models perform as well as the more complex models based on all statistical measures. Generally the schemes have best overall capability to model net all-wave radiation and least capability to model latent heat flux.

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Bruce A. Wielicki
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D. F. Young
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M. G. Mlynczak
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K. J. Thome
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S. Leroy
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J. Corliss
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J. G. Anderson
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C. O. Ao
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R. Bantges
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F. Best
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K. Bowman
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H. Brindley
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J. J. Butler
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W. Collins
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J. A. Dykema
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D. R. Doelling
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D. R. Feldman
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N. Fox
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X. Huang
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R. Holz
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Y. Huang
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Z. Jin
,
D. Jennings
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D. G. Johnson
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K. Jucks
,
S. Kato
,
D. B. Kirk-Davidoff
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R. Knuteson
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G. Kopp
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D. P. Kratz
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X. Liu
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C. Lukashin
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A. J. Mannucci
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N. Phojanamongkolkij
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P. Pilewskie
,
V. Ramaswamy
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H. Revercomb
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J. Rice
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Y. Roberts
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C. M. Roithmayr
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F. Rose
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S. Sandford
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E. L. Shirley
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Sr. W. L. Smith
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B. Soden
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P. W. Speth
,
W. Sun
,
P. C. Taylor
,
D. Tobin
, and
X. Xiong

The Climate Absolute Radiance and Refractivity Observatory (CLARREO) mission will provide a calibration laboratory in orbit for the purpose of accurately measuring and attributing climate change. CLARREO measurements establish new climate change benchmarks with high absolute radiometric accuracy and high statistical confidence across a wide range of essential climate variables. CLARREO's inherently high absolute accuracy will be verified and traceable on orbit to Système Internationale (SI) units. The benchmarks established by CLARREO will be critical for assessing changes in the Earth system and climate model predictive capabilities for decades into the future as society works to meet the challenge of optimizing strategies for mitigating and adapting to climate change. The CLARREO benchmarks are derived from measurements of the Earth's thermal infrared spectrum (5–50 μm), the spectrum of solar radiation reflected by the Earth and its atmosphere (320–2300 nm), and radio occultation refractivity from which accurate temperature profiles are derived. The mission has the ability to provide new spectral fingerprints of climate change, as well as to provide the first orbiting radiometer with accuracy sufficient to serve as the reference transfer standard for other space sensors, in essence serving as a “NIST [National Institute of Standards and Technology] in orbit.” CLARREO will greatly improve the accuracy and relevance of a wide range of space-borne instruments for decadal climate change. Finally, CLARREO has developed new metrics and methods for determining the accuracy requirements of climate observations for a wide range of climate variables and uncertainty sources. These methods should be useful for improving our understanding of observing requirements for most climate change observations.

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