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J. P. Boyle

Abstract

This paper describes results from two field programs that support development of a wave-following surface contact multisensor float (MSF) designed to simultaneously measure net surface heat flux, net solar irradiance, and water temperature. The results reported herein compare measurements from a second-generation design (circa 1998) against directly measured radiative fluxes as well as turbulent fluxes derived using both eddy correlation and bulk aerodynamic methods. The reference flux data are collected using instrumented towers, buoys, and research vessels. Comparisons show that MSF net surface fluxes and net solar irradiance are in generally good agreement with values that are measured or derived using standard instruments and methods, having root-mean-square differences less than approximately 15%. MSF near-surface bulk water temperature measurement shows good agreement with similar measurements from a drifting buoy. MSF measurement of water surface temperature is not definitively determined, although results suggest it may be a good measure of skin temperature at night.

MSF flux measurement occurs from within the aqueous conductive sublayer and so does not use turbulence models or parameterizations. At this time, results are most reliable in low wind conditions (2 m s−1U 10 ≤ 7 m s−1) and relatively calm seas. In higher winds and more active seas, the imperfect surface drifting and wave-following characteristics of the second-generation system limit its performance. More fundamentally, perturbation to the aqueous conductive sublayer and modification of near-surface turbulence structure by the MSF may also limit flux measurement accuracy under certain conditions.

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Weinan Pan
,
R. P. Boyles
,
J. G. White
, and
J. L. Heitman

Abstract

Soil moisture has important implications for meteorology, climatology, hydrology, and agriculture. This has led to growing interest in development of in situ soil moisture monitoring networks. Measurement interpretation is severely limited without soil property data. In North Carolina, soil moisture has been monitored since 1999 as a routine parameter in the statewide Environment and Climate Observing Network (ECONet), but with little soils information available for ECONet sites. The objective of this paper is to provide soils data for ECONet development. The authors studied soil physical properties at 27 ECONet sites and generated a database with 13 soil physical parameters, including sand, silt, and clay contents; bulk density; total porosity; saturated hydraulic conductivity; air-dried water content; and water retention at six pressures. Soil properties were highly variable among individual ECONet sites [coefficients of variation (CVs) ranging from 12% to 80%]. This wide range of properties suggests very different behavior among sites with respect to soil moisture. A principal component analysis indicated parameter groupings associated primarily with soil texture, bulk density, and air-dried water content accounted for 80% of the total variance in the dataset. These results suggested that a few specific soil properties could be measured to provide an understanding of differences in sites with respect to major soil properties. The authors also illustrate how the measured soil properties have been used to develop new soil moisture products and data screening for the North Carolina ECONet. The methods, analysis, and results presented here have applications to North Carolina and for other regions with heterogeneous soils where soil moisture monitoring is valuable.

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A. Wootten
,
A. Terando
,
B. J. Reich
,
R. P. Boyles
, and
F. Semazzi

Abstract

In recent years, climate model experiments have been increasingly oriented toward providing information that can support local and regional adaptation to the expected impacts of anthropogenic climate change. This shift has magnified the importance of downscaling as a means to translate coarse-scale global climate model (GCM) output to a finer scale that more closely matches the scale of interest. Applying this technique, however, introduces a new source of uncertainty into any resulting climate model ensemble. Here a method is presented, on the basis of a previously established variance decomposition method, to partition and quantify the uncertainty in climate model ensembles that is attributable to downscaling. The method is applied to the southeastern United States using five downscaled datasets that represent both statistical and dynamical downscaling techniques. The combined ensemble is highly fragmented, in that only a small portion of the complete set of downscaled GCMs and emission scenarios is typically available. The results indicate that the uncertainty attributable to downscaling approaches ~20% for large areas of the Southeast for precipitation and ~30% for extreme heat days (>35°C) in the Appalachian Mountains. However, attributable quantities are significantly lower for time periods when the full ensemble is considered but only a subsample of all models is available, suggesting that overconfidence could be a serious problem in studies that employ a single set of downscaled GCMs. This article concludes with recommendations to advance the design of climate model experiments so that the uncertainty that accrues when downscaling is employed is more fully and systematically considered.

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V. Misra
,
J.-P. Michael
,
R. Boyles
,
E. P. Chassignet
,
M. Griffin
, and
J. J. O’Brien

Abstract

This study attempts to explain the considerable spatial heterogeneity in the observed linear trends of monthly mean maximum and minimum temperatures (T max and T min) from station observations in the southeastern (SE) United States (specifically Florida, Alabama, Georgia, South Carolina, and North Carolina). In a majority of these station sites, the warming trends in T min are stronger in urban areas relative to rural areas. The linear trends of T min in urban areas of the SE United States are approximately 7°F century−1 compared to about 5.5°F century−1 in rural areas. The trends in T max show weaker warming (or stronger cooling) trends with irrigation, while trends in T min show stronger warming trends. This functionality of the temperature trends with land features also shows seasonality, with the boreal summer season showing the most consistent relationship in the trends of both T max and T min. This study reveals that linear trends in T max in the boreal summer season show a cooling trend of about 0.5°F century−1 with irrigation, while the same observing stations on an average display warming trends in T min of about 3.5°F century−1. The seasonality and the physical consistency of these relationships with existing theories may suggest that urbanization and irrigation have a nonnegligible influence on the spatial heterogeneity of the surface temperature trends over the SE United States. The study also delineates the caveats and limitations of the conclusions reached herein due to the potential influence of perceived nonclimatic discontinuities (which incidentally could also have a seasonal cycle) that have not been taken into account.

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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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J. E. Kay
,
B. R. Hillman
,
S. A. Klein
,
Y. Zhang
,
B. Medeiros
,
R. Pincus
,
A. Gettelman
,
B. Eaton
,
J. Boyle
,
R. Marchand
, and
T. P. Ackerman

Abstract

Satellite observations and their corresponding instrument simulators are used to document global cloud biases in the Community Atmosphere Model (CAM) versions 4 and 5. The model–observation comparisons show that, despite having nearly identical cloud radiative forcing, CAM5 has a much more realistic representation of cloud properties than CAM4. In particular, CAM5 exhibits substantial improvement in three long-standing climate model cloud biases: 1) the underestimation of total cloud, 2) the overestimation of optically thick cloud, and 3) the underestimation of midlevel cloud. While the increased total cloud and decreased optically thick cloud in CAM5 result from improved physical process representation, the increased midlevel cloud in CAM5 results from the addition of radiatively active snow. Despite these improvements, both CAM versions have cloud deficiencies. Of particular concern, both models exhibit large but differing biases in the subtropical marine boundary layer cloud regimes that are known to explain intermodel differences in cloud feedbacks and climate sensitivity. More generally, this study demonstrates that simulator-facilitated evaluation of cloud properties, such as amount by vertical level and optical depth, can robustly expose large and at times radiatively compensating climate model cloud biases.

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J. W. Waters
,
W. G. Read
,
L. Froidevaux
,
R. F. Jarnot
,
R. E. Cofield
,
D. A. Flower
,
G. K. Lau
,
H. M. Pickett
,
M. L. Santee
,
D. L. Wu
,
M. A. Boyles
,
J. R. Burke
,
R. R. Lay
,
M. S. Loo
,
N. J. Livesey
,
T. A. Lungu
,
G. L. Manney
,
L. L. Nakamura
,
V. S. Perun
,
B. P. Ridenoure
,
Z. Shippony
,
P. H. Siegel
,
R. P. Thurstans
,
R. S. Harwood
,
H. C. Pumphrey
, and
M. J. Filipiak

Abstract

The Microwave Limb Sounder (MLS) experiments obtain measurements of atmospheric composition, temperature, and pressure by observations of millimeter- and submillimeter-wavelength thermal emission as the instrument field of view is scanned through the atmospheric limb. Features of the measurement technique include the ability to measure many atmospheric gases as well as temperature and pressure, to obtain measurements even in the presence of dense aerosol and cirrus, and to provide near-global coverage on a daily basis at all times of day and night from an orbiting platform. The composition measurements are relatively insensitive to uncertainties in atmospheric temperature. An accurate spectroscopic database is available, and the instrument calibration is also very accurate and stable. The first MLS experiment in space, launched on the (NASA) Upper Atmosphere Research Satellite (UARS) in September 1991, was designed primarily to measure stratospheric profiles of ClO, O3, H2O, and atmospheric pressure as a vertical reference. Global measurement of ClO, the predominant radical in chlorine destruction of ozone, was an especially important objective of UARS MLS. All objectives of UARS MLS have been accomplished and additional geophysical products beyond those for which the experiment was designed have been obtained, including measurement of upper-tropospheric water vapor, which is important for climate change studies. A follow-on MLS experiment is being developed for NASA’s Earth Observing System (EOS) and is scheduled to be launched on the EOS CHEMISTRY platform in late 2002. EOS MLS is designed for many stratospheric measurements, including HO x radicals, which could not be measured by UARS because adequate technology was not available, and better and more extensive upper-tropospheric and lower-stratospheric measurements.

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