Comments on “Response of the Hurricane Boundary Layer to Changes of Sea Surface Temperature in a Numerical Model”

1979 ◽  
Vol 36 (9) ◽  
pp. 1825-1825 ◽  
Author(s):  
C. S. Ramage
Keyword(s):  
Boundary Layer ◽  
Numerical Model ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Sea Surface ◽  
Hurricane Boundary Layer

Modeling the Atmospheric Boundary Layer Wind Response to Mesoscale Sea Surface Temperature Perturbations

2014 ◽  
Vol 142 (11) ◽  
pp. 4284-4307 ◽  
Author(s):  
Natalie Perlin ◽  
Simon P. de Szoeke ◽  
Dudley B. Chelton ◽  
Roger M. Samelson ◽  
Eric D. Skyllingstad ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Wind Speed ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Coupling Coefficient ◽  
Eddy Viscosity ◽  
Sea Surface ◽  
Coupling Coefficients ◽  
Wind Response ◽  
Speed Response

Abstract The wind speed response to mesoscale SST variability is investigated over the Agulhas Return Current region of the Southern Ocean using the Weather Research and Forecasting (WRF) Model and the U.S. Navy Coupled Ocean–Atmosphere Mesoscale Prediction System (COAMPS) atmospheric model. The SST-induced wind response is assessed from eight simulations with different subgrid-scale vertical mixing parameterizations, validated using Quick Scatterometer (QuikSCAT) winds and satellite-based sea surface temperature (SST) observations on 0.25° grids. The satellite data produce a coupling coefficient of sU = 0.42 m s−1 °C−1 for wind to mesoscale SST perturbations. The eight model configurations produce coupling coefficients varying from 0.31 to 0.56 m s−1 °C−1. Most closely matching QuikSCAT are a WRF simulation with the Grenier–Bretherton–McCaa (GBM) boundary layer mixing scheme (sU = 0.40 m s−1 °C−1), and a COAMPS simulation with a form of Mellor–Yamada parameterization (sU = 0.38 m s−1 °C−1). Model rankings based on coupling coefficients for wind stress, or for curl and divergence of vector winds and wind stress, are similar to that based on sU. In all simulations, the atmospheric potential temperature response to local SST variations decreases gradually with height throughout the boundary layer (0–1.5 km). In contrast, the wind speed response to local SST perturbations decreases rapidly with height to near zero at 150–300 m. The simulated wind speed coupling coefficient is found to correlate well with the height-averaged turbulent eddy viscosity coefficient. The details of the vertical structure of the eddy viscosity depend on both the absolute magnitude of local SST perturbations, and the orientation of the surface wind to the SST gradient.

scholarly journals Mean Biases, Variability, and Trends in Air–Sea Fluxes and Sea Surface Temperature in the CCSM4

2012 ◽  
Vol 25 (22) ◽  
pp. 7781-7801 ◽  
Author(s):  
Susan C. Bates ◽  
Baylor Fox-Kemper ◽  
Steven R. Jayne ◽  
William G. Large ◽  
Samantha Stevenson ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Time Scales ◽  
Hydrological Cycle ◽  
Sea Surface ◽  
Specific Humidity ◽  
Shortwave Radiation ◽  
Climate System Model ◽  
Frequency Bands

Abstract Air–sea fluxes from the Community Climate System Model version 4 (CCSM4) are compared with the Coordinated Ocean-Ice Reference Experiment (CORE) dataset to assess present-day mean biases, variability errors, and late twentieth-century trend differences. CCSM4 is improved over the previous version, CCSM3, in both air–sea heat and freshwater fluxes in some regions; however, a large increase in net shortwave radiation into the ocean may contribute to an enhanced hydrological cycle. The authors provide a new baseline for assessment of flux variance at annual and interannual frequency bands in future model versions and contribute a new metric for assessing the coupling between the atmospheric and oceanic planetary boundary layer (PBL) schemes of any climate model. Maps of the ratio of CCSM4 variance to CORE reveal that variance on annual time scales has larger error than on interannual time scales and that different processes cause errors in mean, annual, and interannual frequency bands. Air temperature and specific humidity in the CCSM4 atmospheric boundary layer (ABL) follow the sea surface conditions much more closely than is found in CORE. Sensible and latent heat fluxes are less of a negative feedback to sea surface temperature warming in the CCSM4 than in the CORE data with the model’s PBL allowing for more heating of the ocean’s surface.

scholarly journals Relationship of the Arctic and Antarctic Oscillations to the Outgoing Longwave Radiation

2003 ◽  
Vol 16 (10) ◽  
pp. 1583-1592 ◽  
Author(s):  
A. J. Miller ◽  
S. Zhou ◽  
S-K. Yang
Keyword(s):  
Numerical Model ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Outgoing Longwave Radiation ◽  
Longwave Radiation ◽  
Sea Surface ◽  
Radiation Budget ◽  
The Arctic ◽  
Relationship Of ◽  
The Relationship

Abstract While several mechanisms have been suggested to account for the association of the Arctic and Antarctic Oscillations (AO/AAO) with atmospheric parameters, this paper focuses on the relationship with the atmospheric outgoing longwave radiation (OLR). The main objective of this paper is to demonstrate through AO/AAO composite analysis that the NCEP–NCAR reanalysis OLR agrees with the independent observations of the NASA Earth Radiation Budget Experiment (ERBE) broadband satellite instruments both in zonal averages and in geographically mapped space, and to verify AO/AAO characterized general circulations derived from models and analyses. The results indicate several pronounced areas of storminess that are AO/AAO dependent. One is the well-known variation over the North Atlantic Ocean toward Europe. Also, several major areas are indicated in the tropical region—one in the Indian Ocean and the others in the west and central Pacific Ocean. In addition to demonstrating that the signals are statistically significant, also tested is the relationship of the features to other well-known tropical forcing mechanisms: the Madden–Julian oscillation (MJO) and the El Niño–La Niña sea surface temperature variations. It is shown that the tropical features do, in fact, have a strong relationship to the MJO, which indicates an additional tropical–extratropical interaction. With regard to the sea surface temperature, no correlation associated with the AO/AAO variability is seen. These associations with the cloudiness and atmospheric radiation budget suggest that if there is to be improvement of numerical model forecasts to an extended time period that numerical model radiation physics will have to be taken into consideration and improved.

scholarly journals Twenty-Four-Hour Observations of the Marine Boundary Layer Using Shipborne NOAA High-Resolution Doppler Lidar

2005 ◽  
Vol 44 (11) ◽  
pp. 1723-1744 ◽  
Author(s):  
Volker Wulfmeyer ◽  
Tijana Janjić
Keyword(s):  
Boundary Layer ◽  
High Resolution ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Wind Shear ◽  
Marine Boundary Layer ◽  
Sea Surface ◽  
Doppler Lidar ◽  
Sensible Heat ◽  
Wind Profiles

Abstract Shipborne observations obtained with the NOAA high-resolution Doppler lidar (HRDL) during the 1999 Nauru (Nauru99) campaign were used to study the structure of the marine boundary layer (MBL) in the tropical Pacific Ocean. During a day with weak mesoscale activity, diurnal variability of the height of the convective MBL was observed using HRDL backscatter data. The observed diurnal variation in the MBL height had an amplitude of about 250 m. Relations between the MBL height and in situ measurements of sea surface temperature as well as latent and sensible heat fluxes were examined. Good correlation was found with the sea surface temperature. The correlation with the latent heat flux was lower, and practically no correlation between the MBL height and the sensible heat and buoyancy fluxes could be detected. Horizontal wind profiles were measured using a velocity–azimuth display scan of HRDL velocity data. Strong wind shear at the top of the MBL was observed in most cases. Comparison of these results with GPS radiosonde data shows discrepancies in the wind intensity and direction, which may be due to different observation times and locations as well as due to multipath effects at the ship’s platform. Vertical wind profiles corrected for ship’s motion were used to derive vertical velocity variance and skewness profiles. Motion compensation had a significant effect on their shape. Normalized by the convective velocity scale and by the top of the mixed layer zi, the variance varied between 0.45 and 0.65 at 0.4z/zi and decreased to 0.2 at 1.0z/zi. The skewness ranged between 0.3 and 0.8 in the MBL and showed in almost all cases a maximum between 1.0z/zi and 1.1z/zi. These profiles revealed the existence of another turbulent layer above the MBL, which was probably driven by wind shear and cloud condensation processes.

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