Ali, A., Christensen, K. H., Breivik, Ø., Malila, M., Raj, R. P., Bertino, L., et al. (2019). A comparison of Langmuir turbulence parameterizations and key wave effects in a numerical model of the North Atlantic and Arctic Oceans. Ocean Modelling , 137 , 76–97.
Abstract: Five different parameterizations of Langmuir turbulence (LT) effect are investigated in a realistic model of the North Atlantic and Arctic using realistic wave forcing from a global wave hindcast. The parameterizations mainly apply an enhancement to the turbulence velocity scale, and/or to the entrainment buoyancy flux in the surface boundary layer. An additional run is also performed with other wave effects to assess the relative importance of Langmuir turbulence, namely the Coriolis-Stokes forcing, Stokes tracer advection and wave-modified momentum fluxes. The default model (without wave effects) underestimates the mixed layer depth in summer and overestimates it at high latitudes in the winter. The results show that adding LT mixing reduces shallow mixed layer depth (MLD) biases, particularly in the subtropics all year-around, and in the Nordic Seas in summer. There is overall a stronger relative impact on the MLD during winter than during summer. In particular, the parameterization with the most vigorous LT effect causes winter MLD increases by more than 50% relative to a control run without Langmuir mixing. On the contrary, the parameterization which assumes LT effects on the entrainment buoyancy flux and accounts for the Stokes penetration depth is able to enhance the mixing in summer more than in winter. This parametrization is also distinct from the others because it restrains the LT mixing in regions of deep MLD biases, so it is the preferred choice for our purpose. The different parameterizations do not change the amplitude or phase of the seasonal cycle of heat content but do influence its long-term trend, which means that the LT can influence the drift of ocean models. The combined impact on water mass properties from the Coriolis-Stokes force, the Stokes drift tracer advection, and the wave-dependent momentum fluxes is negligible compared to the effect from the parameterized Langmuir turbulence.
Huang, N. E., Wu, Z., Pinzón, J. E., Parkinson, C. L., Long, S. R., Blank, K., et al. (2009). Reductions Of Noise And Uncertainty In Annual Global Surface Temperature Anomaly Data. Adv. Adapt. Data Anal. , 01 (03), 447–460.
Zavala-Hidalgo, J., Pares-Sierra, A., & Ochoa, J. (2002). Seasonal variability of the temperature and heat fluxes in the Gulf of Mexico. Atmosfera , 15 (2), 81–104.
Zuromski, L. (2015). Investigating Relationships Between Rising Temperatures and Heavy Rainfall Events in the Southeastern U.S. Using Analog Methods . Bachelor's thesis, Florida State University, Tallahassee, FL.
McNaught, C. (2014). The Increasing Intensity and Frequency of ENSO and its Impacts to the Southeast U.S. Bachelor's thesis, Florida State University, Tallahassee, FL.
Selman, C. M. (2015). Simulating the Impacts and Sensitivity of the Southeastern United States Climatology to Irrigation . Ph.D. thesis, Florida State University, Tallahassee, FL.
Glazer, R. H. (2014). The Influence of Mesoscale Sea Surface Temperature Gradients on Tropical Cyclones . Master's thesis, Florida State University, Tallahassee, FL.
Hughes, P. J. (2014). The Influence of Small-Scale Sea Surface Temperature Gradients on Surface Vector Winds and Subsequent Impacts on Oceanic Ekman Pumping . Tallahassee, FL: Florida State University.
Smith, R. A. (2007). Trends in Maximum and Minimum Temperature Deciles in Select Regions of the United States . Master's thesis, Florida State University, Tallahassee, FL.
Abstract: Daily maximum and minimum temperature data from 758 COOP stations in nineteen states are used to create temperature decile maps. All stations used contain records from 1948 through 2004 and could not be missing more than 5 consecutive years of data. Missing data are replaced using a multiple linear regression technique from surrounding stations. For each station, the maximum and minimum temperatures are first sorted in ascending order for every two years (to reduce annual variability) and divided into ten equal parts (or deciles). The first decile represents the coldest temperatures, and the last decile contains the warmest temperatures. Patterns and trends in these deciles can be examined for the 57-year period. A linear least-squares regression method is used to calculate best-fit lines for each decile to determine the long-term trends at each station. Significant warming or cooling is determined using the Student's t-test, and bootstrapping the decile data will further examine the validity of significance. Two stations are closely examined. Apalachicola, Florida shows significant warming in its maximum deciles and significant cooling in its minimum deciles. The maximum deciles seem to be affected by some localized change. The minimum deciles are discontinuous, and the trends are a result of a minor station move. Columbus, Georgia has experienced significant warming in its minimum deciles, and this appears to be the result of an urban heat-island effect. The discontinuities seen in the Apalachicola case study illustrate the need for a quality control method. This method will eliminate stations from the regional analysis that experience large changes in the ten-year standard deviations within their time series. The regional analysis shows that most of the region is dominated by significant cooling in the maximum deciles and significant warming in the minimum deciles, with more variability in the lower deciles. Field significance testing is performed on subregions (based on USGS 2000 land cover data) and supports the findings from the regional analysis; it also isolates regions, such as the Florida peninsula and the Maryland/Delaware region, that appear to be affected by more local forcings.
Weihs, R. (2016). Surface and Atmospheric Boundary Layer Responses to Diurnal Variations of Sea Surface Temperature in an NWP Model . Ph.D. thesis, Florida State University, Tallahassee, FL.
