Diurnal Variation Of Sea Surface Temperature Research Articles

Role of Strong Sea Surface Temperature Diurnal Variation in Triggering the Summer Monsoon Onset Over the Bay of Bengal in a Climate Model

AbstractThe earliest Asian summer monsoon onset (SMO) occurs in the Bay of Bengal (BoB), heralding the coming of the rainy season. In late April or early May, the strong sea surface temperature (SST) diurnal variation accompanied by ocean surface warming triggers the SMO. However, this observed diurnal cycle intensity cannot be reasonably simulated by state‐of‐the‐art climate models, resulting in a spurious delayed SMO. To address this issue, the SST diurnal cycle parameterized by a diagnostic sublayer scheme was incorporated into a climate model named FIO‐ESM v2.0. The large diurnal amplitude of SST contributes to surface warming and changes atmospheric circulation. Consequently, the high‐pressure anomaly at high levels and an inverted trough at low levels promote more convective activity, triggering an earlier SMO. Our findings improve the ability of climate models in simulating the evolution of the Asian monsoon system.

Evaluation and Improvement of FY-4A/AGRI Sea Surface Temperature Data

The advanced geosynchronous radiation imager (AGRI) aboard the Chinese Fengyun-4A (FY-4A) satellite can provide operational hourly sea surface temperature (SST) product. However, the temporal and spatial variation of the errors for this product is still unclear. In this article, FY-4A/AGRI SST is evaluated using the in situ SST from 2019-2021, and a cumulative distribution function matching method is adopted to reduce the errors. Statistical results show that the mean bias and root-mean-square error (RMSE) of FY-4A/AGRI SST are −0.37 °C and 0.98 °C, the median and robust standard deviation (RSD) are −0.30 °C and 0.90 °C. The variations in daily and monthly errors are large and there are no prominent seasonal variations during the period analyzed. There are negative biases exceeding −1.0 °C in low-mid latitude regions and larger positive biases in southern high latitude region. There are dependencies of satellite SST minus in situ SST on satellite zenith angle and on SST itself. After the bias correction, the bias and RMSE are reduced to −0.02 °C and 0.72 °C, and the median and RSD are reduced to 0.00 °C and 0.60 °C. On the time scale, the fluctuation ranges of bias and median are smaller. The difference of satellite SST minus in situ SST can reflect the diurnal variation of SST. The biases are generally within ±0.2 °C in full disk. The error dependencies on satellite zenith angle and SST are also greatly reduced.

Seasonal and intra-seasonal variations of surface hydrological parameters over North Yellow Sea and its implications for applicability of quasi-synchronous ship-based multi-station hydrological investigation data

The quasi-synchronous ship-based multi-station hydrological investigation is the most basic and classic oceanographic research method. Nevertheless, the temporal variability of regional hydrological parameters raises the uncertainty of interpreting quasi-synchronous multi-station datasets. There has been a lack of in-depth assessment of the accuracy of survey results. In this study, two hydrological investigations during the summer of 2016 and winter of 2017 in the North Yellow Sea (NYS), accompanied by time series buoy observations, are presented to elucidate its influencing factors and applicability evaluation of cruise hydrological investigation data. The results indicate that the solar radiation and tidal condition account for the diurnal and semi-diurnal cycle of sea surface temperature (SST) in the summer and winter seasons, respectively. The sea surface salinity shows no significant variation during the cruise survey period, while the seasonal characteristic is dominated by the regional ocean circulation. The vertical hydrological structures (stratified in summer or well-mixed in winter) limit or enhance the upward diffusion of bottom resuspended sediment in the offshore area, furtherly causing higher surface turbidity in winter. The upwelling phenomenon is underestimated in summer cruises due to the diurnal variation of SST, while the cold-water tongue may be overinterpreted in winter cruise because of the northerly wind event. The applicability of multi-station hydrological investigation data depends on the comparison of the spatio-temporal scale of the scientific question being studied with the time-varying of the data. The coefficient of variation (CV) of sea surface parameters ranges from 0.03 to 0.36 for SST, 0.02 to 0.04 for SSS, 0.01 to 1.37 for chl a, and 0.06 to 0.50 for Rrs_555. The sea surface parameters display higher variabilities during spring and autumn season than summer and winter season over NYS, and the coastal areas show larger temporal variation than central NYS. It is suggested that the multi-station investigation should be conducted at the time when the hydrological structure is relatively stable as far as possible, especially for the nearshore stations. This study provides a meaningful reference for oceanographic research that although the background hydrologic field can be well described through the ship-based investigation data, attention should also be paid to the influence of time-varying meteorological and hydrological conditions to achieve more objective data interpretation.

Retrieval of Daily Mean VIIRS SST Products in China Seas

Sea surface temperature (SST) is one of the most important factors in regulating air-sea heat flux and, thus, climate change. Most of current global daily SST products are derived from one or two transient measurements of polar-orbiting satellites, which are not the same to daily mean SST values. In this study, high-temporal-resolution SST measurements (32–40 snapshots per day) from a geostationary satellite, FengYun-4A (FY–4A), are used to analyze the diurnal variation of SST in China seas. The results present a sinusoidal pattern of the diurnal variability in SST, with the maximum value at 13:00–15:00 CST and the minimum at 06:00–08:00 CST. Based on the diurnal variation of SST, a retrieval method for daily mean SST products from polar-orbiting satellites is established and applied to 7716 visible infrared imaging radiometer (VIIRS) data in China seas. The results suggest that it is feasible and practical for the retrieval of daily mean SST with an average RMSE of 0.133 °C. This retrieval method can also be utilized to other polar-orbiting satellites and obtain more daily mean satellite SST products, which will contribute to more accurate estimation and prediction between atmosphere and ocean in the future.

MJO induced diurnal sea surface temperature variations off the northwest shelf of Australia observed from Himawari geostationary satellite

High frequency coupling between the tropical upper ocean and atmosphere at diurnal time scales is being recognised to be important for the behaviour of large scale climate modes such as the Madden Julian Oscillation (MJO). Sea surface temperature (SST) variability in the Eastern Indian Ocean warm pool and on the Northwest Shelf of Australia is strongly influenced by the MJO activity. In this study, we use the hourly Himawari-8 geostationary satellite SST data to understand the modulation of the amplitude of SST diurnal variations in the region by the MJO during two austral summer seasons of 2015–16 and 2016–17. The high temporal and spatial resolutions of the Himawari-8 SST data are able to capture the temporal and spatial variability of diurnal SST amplitude. Our results show that the MJO onset (active phase) is preceded by strong diurnal SST variations during the MJO suppressed phase. The amplitudes of the SST diurnal variations are mainly modulated by surface wind variability in the region, as denoted by their spatial and temporal correlations. The very strong El Niño event in 2015–16 may have significantly weakened the MJO activities in the region, resulting in prolonged MJO suppressed phase, high diurnal SST variation and mean SST. This study provides background knowledge for future research on how the diurnal SST variation in the region may influence the progression of the MJO events.

Sea surface temperature data from coastal observation stations: quality control and semidiurnal characteristics

Sea surface temperature (SST) data obtained from coastal stations in Jiangsu, China during 2010–2014 are quality controlled before analysis of their characteristic semidiurnal and seasonal cycles, including the correlation with the variation of the tide. Quality control of data includes the validation of extreme values and checking of hourly values based on temporally adjacent data points, with 0.15°C/h considered a suitable threshold for detecting abnormal values. The diurnal variation amplitude of the SST data is greater in spring and summer than in autumn and winter. The diurnal variation of SST has bimodal structure on most days, i.e., SST has a significant semidiurnal cycle. Moreover, the semidiurnal cycle of SST is negatively correlated with the tidal data from March to August, but positively correlated with the tidal data from October to January. Little correlation is detected in the remaining months because of the weak coastal-offshore SST gradients. The quality control and understanding of coastal SST data are particularly relevant with regard to the validation of indirect measurements such as satellite-derived data.

Effects of Australian Summer Monsoon on Sea Surface Temperature Diurnal Variation Over the Australian North‐Western Shelf

AbstractFive‐year (2010 to 2014) sea surface temperature (SST) data from the Advanced Very High Resolution Radiometer are used to study the effects of the Australian summer monsoon on SST diurnal variation (DV) over the Australian northwestern shelf (NWS, defined as 105°E–125°E, 25°S–10°S). Strong DV events identified with amplitude of 0.5–2 K were observed over the NWS. A double‐peak seasonal pattern of DV is obtained, with the strongest DV occurring in February/March and October/November. This seasonal DV pattern over the NWS is largely due to the Australian summer monsoon, which reduces the easterly trade wind during the summer monsoonal period, favoring the development of SST DV. Since the monsoon region is distributed globally in the tropical oceans, in the western and eastern North Pacific, as well as in the southern Indian Ocean, we anticipate that strong SST DV may also exist in these parts of coastal oceans.

Evaluation of three temperature profiles of a sublayer scheme to simulate SST diurnal cycle in a global ocean general circulation model

AbstractThe diurnal cycle of sea surface temperature (SST) plays an important role in the upper ocean and climate system. One way to represents the diurnal variation of SST in Ocean General Circulation Models (OGCMs) with coarse vertical resolution is to parameterize the diurnal cycle of SST without considering detailed dynamic processes within the mixed layer. In this study, a diagnostic sublayer parameterization scheme following Schiller and Godfrey (2005) was incorporated into a global OGCM (NEMO), for the first time, to simulate the diurnal cycle of SST. Moreover, three different sublayer temperature profiles (constant, linear, and exponential) were evaluated. Comparison with satellite SST and mooring temperature data indicated that the parameterization scheme with an exponential temperature profile showed the most reasonable diurnal warming simulation results, significantly improving the probability of (from 1.7% with constant temperature profile to 13.4%) diurnal SST amplitude larger than 1.0°C. Furthermore, the mean biases in each season were all reduced to less than 0.16°C, in good agreement with observations.

Seasonal patterns of SST diurnal variation over the Tropical Warm Pool region

Five-year (2010 through 2014) Advanced Very High Resolution Radiometer (AVHRR) sea surface temperature (SST) data produced by the Australian Bureau of Meteorology have been validated against drifting buoy data and then used to study the seasonal patterns of the SST diurnal variation (DV) events over the Tropical Warm Pool region (TWP, 25°S–15°N, 90°E–170°E). The in-situ validation results illustrate the overall good quality of the AVHRR SST data set, although an average 0.19 K underestimation of the daytime measurements has been observed. The night-time observations are in good agreement with in-situ buoys with an average bias of 0.03 K and a 0.30 K standard deviation of the biases. This SST data set is then used to characterise the SST DV seasonal patterns, together with wind speeds, daily maximum solar shortwave insolation (SSImax) and latent heat flux (LHF). A double-peak seasonal pattern of SST DV is observed over the study region: the strongest DVs are found in March and October and the weakest in June. Sensitivity tests of DV to wind, SSImax, and LHF are conducted. The results indicate: (1) different morning and early afternoon winds (7 am to 2 pm local time, LT) affect DV by as much as 0.73 K when the half-daily (defined as 2 am to 2 pm LT in this study) average winds are fixed between 2-3 ms−1; (2) SSImax levels regulate DV less significantly (< 0.68 K) under fixed winds; and (3) LHF effects on DV are relatively weak (< 0.35 K). This article is protected by copyright. All rights reserved.

Investigating sea surface temperature diurnal variation over the Tropical Warm Pool using MTSAT-1R data

Abstract Diurnal variation (DV) of sea surface temperature (SST) plays an important role in air–sea interaction. We have validated four months (January to April 2010) of the version 3 Australian Bureau of Meteorology reprocessed Multifunction Transport SATellite-1R (v3 MTSAT-1R) SST data over the Tropical Warm Pool (TWP) region (90°E to 170°E, 25°S to 15°N) against both drifting buoy and Advanced Along-Track Scanning Radiometer (AATSR) SST data. Validation against collocated point measurements from drifting buoys, under conditions where the surface ocean is well-mixed, shows that overall the v3 MTSAT-1R SSTs perform well with an average bias of 0.00 °C and a 0.73 °C standard deviation (STD). The average daytime and night-time mean bias is − 0.06 °C and 0.08 °C, respectively. For all hours of the diurnal cycle, the mean biases are within ± 0.25 °C, indicating the consistency between day and night v3 MTSAT-1R data. However, on average, the v3 MTSAT-1R SSTs are overestimated at cold SSTs and underestimated at warm SSTs. Similar results are obtained from validation against the AATSR satellite SSTs but with smaller STD (0.48 °C) and smaller average daytime and night-time mean biases (− 0.04 °C and 0.06 °C, respectively). These results indicate that the v3 MTSAT-1R data set is suitable for SST DV investigations and validation of DV models. Using the validated v3 MSTAT-1R data, together with surface wind speed and solar shortwave insolation (SSI) outputs from the Australian Community Climate and Earth-System Simulator – Regional (ACCESS-R) numerical prediction model, we investigate SST DV events over the TWP region. Good correlation is found between DV events and low wind and high SSI conditions. The dominant role of wind speed in SST DV events over the SSI is also revealed.

A Study of CINDY/DYNAMO MJO Suppressed Phase

Abstract The diurnal variability and the environmental conditions that support the moisture resurgence of MJO events observed during the Cooperative Indian Ocean Experiment on Intraseasonal Variability (CINDY)/DYNAMO campaign in October–December 2011 are investigated using in situ observations and the cloud-resolving fully air–ocean–wave Coupled Ocean–Atmosphere Mesoscale Prediction System (COAMPS). Spectral density and wavelet analysis of the total precipitable water (TPW) constructed from the DYNAMO soundings and TRMM satellite precipitation reveal a deep layer of vapor resurgence during the observed Wheeler and Hendon real-time multivariate MJO index phases 5–8 (MJO suppressed phase), which include diurnal, quasi-2-, quasi-3–4-, quasi-6–8-, and quasi-16-day oscillations. A similar oscillatory pattern is found in the DYNAMO moorings sea surface temperature analysis, suggesting a tightly coupled atmosphere and ocean system during these periods. COAMPS hindcast focused on the 12–16 November 2011 event suggests that both the diurnal sea surface temperature (SST) pumping and horizontal and vertical moisture transport associated with the westward propagating mixed Rossby–Gravity (MRG) waves play an essential role in the moisture resurgence during this period. Idealized COAMPS simulations of MRG waves are used to estimate the MRG and diurnal SST contributions to the overall moisture increase. These idealized MRG sensitivity experiments showed the TPW increase varies from 9% to 13% with the largest changes occurring in the simulations that included a diurnal SST variation of 2.5°C as observed.

An initial estimate of the global distribution of diurnal variation in sea surface salinity

AbstractDiurnal variations in sea surface salinity (SSS) have been observed at a few selected locations with adequate in situ instrumentation. Such variations result primarily from imbalances between surface freshwater fluxes and vertical mixing of deeper water to the surface. New observations becoming available from satellite salinity remote sensing missions could help to constrain estimates of diurnal variations in air‐sea exchange of freshwater, and provide insight into the processes governing diurnal variability of mixing processes in the upper ocean. Additionally, a better understanding of variation in near surface salinity is required to compare satellite measured SSS with in situ measurements at a few meters depth. The diurnal SSS variations should be reflected as differences between ascending and descending pass retrievals from the Aquarius and SMOS satellites; however, the diurnal signal can be masked by inadequacies of the geophysical corrections used in processing the satellite measurements. In this study, we quantify the expected range of diurnal SSS variations using a model developed for predicting diurnal sea surface temperature variations. We present estimates for the mean and variance of the global diurnal SSS cycle, contrasting it with the diurnal cycle of sea surface temperature. We find the SSS diurnal cycle can be significant throughout the tropics, with mean amplitudes of up to 0.1 psu in areas with heavy precipitation. Predicted maximum diurnal ranges approach 2 psu in select regions. Surface freshening in Aquarius salinity retrievals is shown to be larger for ascending than descending passes, consistent with the expectations from the model simulation.

A New Method to Produce Sea Surface Temperature Using Satellite Data Assimilation into an Atmosphere–Ocean Mixed Layer Coupled Model

AbstractA new method of producing sea surface temperature (SST) data for numerical weather prediction is suggested, which is obtained from the assimilation of satellite-derived SST into an atmosphere–ocean mixed layer coupled model. The Weather Research and Forecasting (WRF) Model and the Noh mixed layer model are used for the atmosphere and ocean mixed layer models, respectively. Data assimilation (DA) is carried out in two steps, based on the estimation from the covariance matching method that the daily mean SST of satellite data is more accurate than the model data, if the number of data in a grid per day is sufficiently large—that is, the daily mean SST bias correction in the first DA and the sequential SST anomaly correction in the second DA. For the second DA, the model restarts from the initial condition corrected by the first DA, and DA is applied every 30 min using the nudging method. The daily mean and the diurnal variation of satellite SST are assimilated to the bulk and skin SST, respectively. The modeled results with the new data assimilation scheme are validated by statistical comparison with independent satellite and buoy data such as correlation coefficient, root-mean-square difference, and bias. Furthermore, the sensitivity and seasonal variation of the weighting factor in the second DA are examined. The new approach illustrates the possibility of applying the atmosphere–ocean mixed layer coupled model for the production of SST data combined with the assimilation of satellite data.

Effects of the diurnal cycle in solar radiation on the tropical Indian Ocean mixed layer variability during wintertime Madden-Julian Oscillations

[1] The effects of solar radiation diurnal cycle on intraseasonal mixed layer variability in the tropical Indian Ocean during boreal wintertime Madden-Julian Oscillation (MJO) events are examined using the HYbrid Coordinate Ocean Model. Two parallel experiments, the main run and the experimental run, are performed for the period of 2005–2011 with daily atmospheric forcing except that an idealized hourly shortwave radiation diurnal cycle is included in the main run. The results show that the diurnal cycle of solar radiation generally warms the Indian Ocean sea surface temperature (SST) north of 10 � S, particularly during the calm phase of the MJO when sea surface wind is weak, mixed layer is thin, and the SST diurnal cycle amplitude (dSST) is large. The diurnal cycle enhances the MJO-forced intraseasonal SST variability by about 20% in key regions like the Seychelles-Chagos Thermocline Ridge (SCTR; 55 � –70 � E, 12 � –4 � S) and the central equatorial Indian Ocean (CEIO; 65 � –95 � E, 3 � S–3 � N) primarily through nonlinear rectification. The model also well reproduced the upper-ocean variations monitored by the CINDY/DYNAMO field campaign between September-November 2011. During this period, dSST reaches 0.7 � C in the CEIO region, and intraseasonal SST variability is significantly amplified. In the SCTR region where mean easterly winds are strong during this period, diurnal SST variation and its impact on intraseasonal ocean variability are much weaker. In both regions, the diurnal cycle also has a large impact on the upward surface turbulent heat flux QT and induces diurnal variation of QT with a peak-to-peak difference of O(10 W m � 2 ).

The Diurnal Variation Of Sea Surface Temperature (Sst) Through The Rama Mooring Observation In Indian Ocean

Diurnal cycles or variation of sea surface temperature (SST) is an interesting phenomenon to be investigated since it relates with sea-air interaction phenomena such as Madden Julian Oscilation (MJO) and diurnal warming in large ocean. An integrated observation by using a subsurface mooring and atmospheric buoy in Indian Ocean through RAMA (Research Moored Array for African-Asian-Australian Monsoon Analysis) Buoy Project provided a time series physical oceanography and meteorological data.The diurnal cycles of SST analysis use hourly SST data at depth of 1 meter and 10 meter for the period from March 2009 to February 2010.The diurnal variation of SST has significant amplitude, varies from 0.5 to 2 centigrade, for period March 2009 to February 2010. The seasonal montly mean diurnal cycle calculation for SST indicated the changes of maximum values of SST due to season, while in March-April-May 2009 the SST reached mostly maximum values compared to other seasons and the SST had lower values in September-November-December 2009.

Inclusion of sea‐surface temperature variation in the U.S. Navy ensemble‐transform global ensemble prediction system

The local ensemble transform (ET) analysis perturbation scheme is adapted to generate perturbations to both atmospheric variables and sea‐surface temperature (SST). The adapted local ET scheme is used in conjunction with a prognostic model of SST diurnal variation and the Navy Operational Global Atmospheric Prediction System (NOGAPS) global spectral model to generate a medium‐range forecast ensemble. When compared to a control ensemble, the new forecast ensemble with SST variation exhibits notable differences in various physical properties including the spatial patterns of surface fluxes, outgoing longwave radiation (OLR), cloud radiative forcing, near‐surface air temperature and wind speed, and 24‐h accumulated precipitation. The structure of the daily cycle of precipitation also is substantially changed, generally exhibiting a more realistic midday peak of precipitation. Diagnostics of ensemble performance indicate that the inclusion of SST variation is very favorable to forecasts in the Tropics. The forecast ensemble with SST variation outscores the control ensemble in the Tropics across a broad set of metrics and variables. The SST variation has much less impact in the Midlatitudes. Further comparison shows that SST diurnal variation and the SST analysis perturbations are each individually beneficial to the forecast from an overall standpoint. The SST analysis perturbations have broader benefit in the Tropics than the SST diurnal variation, and inclusion of the SST analysis perturbations together with the SST diurnal variation is essential to realize the greatest gains in forecast performance.

Effects of sea surface temperature, cloud radiative and microphysical processes, and diurnal variations on rainfall in equilibrium cloud-resolving model simulations

The effects of sea surface temperature (SST), cloud radiative and microphysical processes, and diurnal variations on rainfall statistics are documented with grid data from the two-dimensional equilibrium cloud-resolving model simulations. For a rain rate of higher than 3 mm·h−1, water vapor convergence prevails. The rainfall amount decreases with the decrease of SST from 29 °C to 27 °C, the inclusion of diurnal variation of SST, or the exclusion of microphysical effects of ice clouds and radiative effects of water clouds, which are primarily associated with the decreases in water vapor convergence. However, the amount of rainfall increases with the increase of SST from 29 °C to 31 °C, the exclusion of diurnal variation of solar zenith angle, and the exclusion of the radiative effects of ice clouds, which are primarily related to increases in water vapor convergence. For a rain rate of less than 3 mm·h−1, water vapor divergence prevails. Unlike rainfall statistics for rain rates of higher than 3 mm·h−1, the decrease of SST from 29 °C to 27 °C and the exclusion of radiative effects of water clouds in the presence of radiative effects of ice clouds increase the rainfall amount, which corresponds to the suppression in water vapor divergence. The exclusion of microphysical effects of ice clouds decreases the amount of rainfall, which corresponds to the enhancement in water vapor divergence. The amount of rainfall is less sensitive to the increase of SST from 29 °C to 31 °C and to the radiative effects of water clouds in the absence of the radiative effects of ice clouds.

An empirical model for the statistics of sea surface diurnal warming

Abstract. A statistical model is derived relating the diurnal variation of sea surface temperature (SST) to the net surface heat flux and surface wind speed from a numerical weather prediction (NWP) model. The model is derived using fluxes and winds from the European Centre for Medium-Range Weather Forecasting (ECMWF) NWP model and SSTs from the Spinning Enhanced Visible and Infrared Imager (SEVIRI). In the model, diurnal warming has a linear dependence on the net surface heat flux integrated since (approximately) dawn and an inverse quadratic dependence on the maximum of the surface wind speed in the same period. The model coefficients are found by matching, for a given integrated heat flux, the frequency distributions of the maximum wind speed and the observed warming. Diurnal cooling, where it occurs, is modelled as proportional to the integrated heat flux divided by the heat capacity of the seasonal mixed layer. The model reproduces the statistics (mean, standard deviation, and 95-percentile) of the diurnal variation of SST seen by SEVIRI and reproduces the geographical pattern of mean warming seen by the Advanced Microwave Scanning Radiometer (AMSR-E). We use the functional dependencies in the statistical model to test the behaviour of two physical model of diurnal warming that display contrasting systematic errors.

Numerical Simulation of Sea Surface Transient Temperature Field

Sea surface temperature (SST) is a prerequisite for sea surface infrared imaging simulation. A temperature model suitable for seawater heat exchange is proposed based on the heat balance of air-sea interface and equations of fluid heat exchange. The model considers the air-sea heat transfer characteristics and influences of penetrating solar radiation in seawater. Effects of the solar radiation, sea surface wind speed and air temperature on SST are analyzed. Temperature model is also used to simulate the SST diurnal variation and compared with the measured values to verify the validity of the model. The results show that the model is useful for solution of sea surface transient temperature field and provides the basis for infrared imaging simulation of sea surface.

An Investigation of Sea Surface Temperature Influence on Microwave Refractivity: The Wallops-2000 Experiment

AbstractThe Wallops-2000 experiment took place in April and May 2000 in the vicinity of Wallops Island, Virginia, to collect high-resolution measurements of microwave propagation and coincident meteorological parameters in a complex coastal environment. These data are used in conjunction with a mesoscale numerical weather prediction model to examine the impact of sea surface temperature (SST) on microwave ducting. Analysis of time series of meteorological fields at the location of an instrumented buoy indicates reliable forecast skill. Statistics from vertical profiles and of derived ducting characteristics (duct frequency, duct strength, duct-base height, and duct thickness) show that the model reproduced observed duct characteristics with modest accuracy, allowing for a 3–6-h error in synoptic airmass transitions. In addition to the control run, two experiments are conducted to examine the impact of SST on ducting. In one experiment a climatological SST field is used, and in the other a diurnal variation in SST is imposed. The higher SST in the diurnally varying simulations promotes stronger turbulent mixing, deep boundary layers, and small vertical gradients in mixing ratio in comparison with the control, which lead to reduced duct frequency and strength in many cases. The study further reveals that, while advection of large-scale air masses (vertical and horizontal) plays a crucial role in determining whether an environment is favorable for microwave ducting, diurnal variations in SST can be influential in determining the onset of ducting and the frequency of surface-based ducting in coastal regions.