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Kenneth L. Davidson, Patricia J. Boyle, and Peter S. Guest

Abstract

Atmospheric boundary-layer properties and processes in gulf and coastal regions have special characteristics that are important in forecasting winds and ocean forcing. Accurate coastal-wind predictions require knowledge of local responses to a given synoptic-forcing scenario. The overwater surface roughness effect on wind stress, specified by a neutral drag coefficient, for a 15 m s−1 surface wind averages 25% higher in coastal regions than in open-ocean regions. The change in sea state associated with a sharp sea surface temperature gradient (front) caused a 10%–20% increase in neutral drag coefficient. Sea-state and wind-wave orientation changes associated with an atmospheric cold front increased the neutral drag coefficient by a factor of 2 for a 3–4-h period following the frontal passage. The effect of increased drag coefficient on surface wind speed is to slow it down by an amount that depends on the height of the inversion base and other processes within the boundary layer. An example of a coastal jet shows complications in the wind field associated with horizontal air temperature changes in the atmospheric boundary layer.

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Edgar L. Andreas, Christopher W. Fairall, P. Ola G. Persson, and Peter S. Guest

Abstract

Defining the averaging time required for measuring meaningful turbulence statistics is a central problem in boundary layer meteorology. Path-averaging scintillation instruments are presumed to confer some time-averaging benefits when the objective is to measure surface fluxes, but that hypothesis has not been tested definitively. This study uses scintillometer measurements of the inner scale (l 0) and the refractive index structure parameter (C2n) to investigate this question of required averaging time. The first conclusion is that the beta probability distribution is useful for representing C2n and l 0 measurements. Consequently, beta distributions are used to set confidence limits on C2n and l 0 values obtained over various averaging periods. When the C2n and l 0 time series are stationary, a short-term average of C2n or l 0 can be as accurate as a long-term average. However, as with point measurements, when time series of path averaged C2n or l 0 values are nonstationary, turbulent surface fluxes inferred from these C2n and l 0 values can be variable and uncertain—problems that path averaging was presumed to mitigate. Because nonstationarity is a limiting condition, the last topic is quantifying the nonstationarity with a published nonstationarity ratio and also by simply counting zero crossings in the time series.

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Ian A. Renfrew, G. W. K. Moore, Teddy R. Holt, Simon W. Chang, and Peter Guest

This report discusses the design and implementation of a specialized forecasting system that was set up to support the observational component of the Labrador Sea Deep Convection Experiment. This ongoing experiment is a multidisciplinary program of observations, theory, and modeling aimed at improving our knowledge of the deep convection process in the ocean, and the air–sea interaction that forces it. The observational part of the program was centered around a cruise of the R/V Knorr during winter 1997, as well as several complementary meteorological research flights. To aid the planning of ship and aircraft operations a specially tailored mesoscale model was run over the Labrador Sea, with the model output postprocessed and transferred to a remote field base. The benefits of using a warm-start analysis cycle in the model are discussed. The utility of the forecasting system is illustrated through a description of the flight planning process for several cases. The forecasts proved to be invaluable both in ship operations and in putting the aircraft in the right place at the right time. In writing this narrative the authors hope to encourage the use of similar forecasting systems in the support of future field programs, something that is becoming increasingly possible with the rise in real-time numerical weather prediction.

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Ian A. Renfrew, G. W. K. Moore, Peter S. Guest, and Karl Bumke

Abstract

Comparisons are made between a time series of meteorological surface layer observational data taken on board the R/V Knorr, and model analysis data from the European Centre for Medium-Range Weather Forecasting (ECMWF) and the National Centers for Environmental Prediction (NCEP). The observational data were gathered during a winter cruise of the R/V Knorr, from 6 February to 13 March 1997, as part of the Labrador Sea Deep Convection Experiment. The surface layer observations generally compare well with both model representations of the wintertime atmosphere. The biases that exist are mainly related to discrepancies in the sea surface temperature or the relative humidity of the analyses.

The surface layer observations are used to generate bulk estimates of the surface momentum flux, and the surface sensible and latent heat fluxes. These are then compared with the model-generated turbulent surface fluxes. The ECMWF surface sensible and latent heat flux time series compare reasonably well, with overestimates of only 13% and 10%, respectively. In contrast, the NCEP model overestimates the bulk fluxes by 51% and 27%, respectively. The differences between the bulk estimates and those of the two models are due to different surface heat flux algorithms. It is shown that the roughness length formula used in the NCEP reanalysis project is inappropriate for moderate to high wind speeds. Its failings are acute for situations of large air–sea temperature difference and high wind speed, that is, for areas of high sensible heat fluxes such as the Labrador Sea, the Norwegian Sea, the Gulf Stream, and the Kuroshio. The new operational NCEP bulk algorithm is found to be more appropriate for such areas.

It is concluded that surface turbulent flux fields from the ECMWF are within the bounds of observational uncertainty and therefore suitable for driving ocean models. This is in contrast to the surface flux fields from the NCEP reanalysis project, where the application of a more suitable algorithm to the model surface-layer meteorological data is recommended.

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Edgar L. Andreas, P. Ola G. Persson, Andrey A. Grachev, Rachel E. Jordan, Thomas W. Horst, Peter S. Guest, and Christopher W. Fairall

Abstract

The Surface Heat Budget of the Arctic Ocean (SHEBA) experiment produced 18 000 h of turbulence data from the atmospheric surface layer over sea ice while the ice camp drifted for a year in the Beaufort Gyre. Multiple sites instrumented during SHEBA suggest only two aerodynamic seasons over sea ice. In “winter” (October 1997 through 14 May 1998 and 15 September 1998 through the end of the SHEBA deployment in early October 1998), the ice was compact and snow covered, and the snow was dry enough to drift and blow. In “summer” (15 May through 14 September 1998 in this dataset), the snow melted, and melt ponds and leads appeared and covered as much as 40% of the surface with open water. This paper develops a bulk turbulent flux algorithm to explain the winter data. This algorithm predicts the surface fluxes of momentum, and sensible and latent heat from more readily measured or modeled quantities. A main result of the analysis is that the roughness length for wind speed z 0 does not depend on the friction velocity u * in the drifting snow regime (u * ≥ 0.30 m s−1) but, rather, is constant in the SHEBA dataset at about 2.3 × 10−4 m. Previous analyses that found z 0 to increase with u * during drifting snow may have suffered from fictitious correlation because u * also appears in z 0. The present analysis mitigates this fictitious correlation by plotting measured z 0 against the corresponding u * computed from the bulk flux algorithm. Such plots, created with data from six different SHEBA sites, show z 0 to be independent of the bulk u * for 0.15 < u * ≤ 0.65 m s−1. This study also evaluates the roughness lengths for temperature zT and humidity zQ, incorporates new profile stratification corrections for stable stratification, addresses the singularities that often occur in iterative flux algorithms in very light winds, and includes an extensive analysis of whether atmospheric stratification affects z 0, zT, and zQ.

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Taneil Uttal, Judith A. Curry, Miles G. McPhee, Donald K. Perovich, Richard E. Moritz, James A. Maslanik, Peter S. Guest, Harry L. Stern, James A. Moore, Rene Turenne, Andreas Heiberg, Mark. C. Serreze, Donald P. Wylie, Ola G. Persson, Clayton A. Paulson, Christopher Halle, James H. Morison, Patricia A. Wheeler, Alexander Makshtas, Harold Welch, Matthew D. Shupe, Janet M. Intrieri, Knut Stamnes, Ronald W. Lindsey, Robert Pinkel, W. Scott Pegau, Timothy P. Stanton, and Thomas C. Grenfeld

A summary is presented of the Surface Heat Budget of the Arctic Ocean (SHEBA) project, with a focus on the field experiment that was conducted from October 1997 to October 1998. The primary objective of the field work was to collect ocean, ice, and atmospheric datasets over a full annual cycle that could be used to understand the processes controlling surface heat exchanges—in particular, the ice–albedo feedback and cloud–radiation feedback. This information is being used to improve formulations of arctic ice–ocean–atmosphere processes in climate models and thereby improve simulations of present and future arctic climate. The experiment was deployed from an ice breaker that was frozen into the ice pack and allowed to drift for the duration of the experiment. This research platform allowed the use of an extensive suite of instruments that directly measured ocean, atmosphere, and ice properties from both the ship and the ice pack in the immediate vicinity of the ship. This summary describes the project goals, experimental design, instrumentation, and the resulting datasets. Examples of various data products available from the SHEBA project are presented.

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