A 31-year Global Diurnal Sea Surface Temperature Dataset Created by an Ocean Mixed-Layer Model

2018 ◽  
Vol 35 (12) ◽  
pp. 1443-1454 ◽  
Author(s):  
Xiang Li ◽  
Tiejun Ling ◽  
Yunfei Zhang ◽  
Qian Zhou
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Mixed Layer ◽  
Sea Surface ◽  
Ocean Mixed Layer ◽  
Layer Model ◽  
Mixed Layer Model

scholarly journals Sensitivity of the Short-Range Precipitation Forecast in South China Region to Sea Surface Temperature Variations

Atmosphere ◽  
2021 ◽  
Vol 12 (9) ◽  
pp. 1138
Author(s):  
Diah Valentina Lestari ◽  
Xiaoming Shi
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Mixed Layer ◽  
Short Range ◽  
Wrf Model ◽  
Extreme Rainfall ◽  
Sea Surface ◽  
Precipitation Forecast ◽  
Layer Model ◽  
Mixed Layer Model

Ocean variability plays an essential role in the climate system at different time scales through air–sea interactions. Recent studies have addressed the importance of the ocean mixed layer in cooling feedback to tropical cyclones (TCs). However, using constant sea surface temperature (SST) in short-range weather forecasts remains common, especially in high-resolution regional models. This study investigates the role of subsurface ocean mixing in the short-range forecast of non-TC extreme rainfall with the Weather Research and Forecast (WRF) model. In the simulations of 26 heavy rainfall cases, we found that using a one-dimensional mixed layer model leads to a 15% enhancement (reduction) of rainfall maximum in six (two) cases compared to using constant SST. When the initial depth of the mixed layer model is perturbed by the amount of daily variability, 13 cases exhibit larger than 15% increases or decreases. A detailed analysis of one case suggests that the radiative process dominates the overall response of SST. The warming and moistening of boundary layer air cause significant strengthening of updrafts in convection. Although the SST change in most cases due to varying mixed layer model setups is less than 0.5 K, convective motions in some cases are surprisingly sensitive to small changes.

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

2013 ◽  
Vol 30 (12) ◽  
pp. 2926-2943 ◽  
Author(s):  
Eunjeong Lee ◽  
Yign Noh ◽  
Naoki Hirose
Keyword(s):  
Data Assimilation ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Mixed Layer ◽  
Satellite Data ◽  
Weather Prediction ◽  
Coupled Model ◽  
Sea Surface ◽  
New Method ◽  
Ocean Mixed Layer

Abstract A 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.

On the Ocean Mixed Layer influence on the genesis of Mediterranean Tropical-Like cyclones

2020 ◽  
Author(s):  
Antonio Ricchi ◽  
Davide Bonaldo ◽  
Mario Marcello Miglietta ◽  
Sandro Carniel
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Case Studies ◽  
Mixed Layer ◽  
Heat Content ◽  
Heat Fluxes ◽  
Ocean Heat Content ◽  
Sea Surface ◽  
Lapse Rate ◽  
Ocean Mixed Layer

<p>The Mediterranean basin is the formation site of a vast number and type of cyclones. Among these, we can occasionally identify intense vortices showing tropical characteristics, called Tropical-Like Cyclones (TLC) or MEDIcanes (Mediterranean Hurricane). Their development has been studied in several case studies, showing the influence of synoptic scale upper level forcings and mesoscale features, such as the sea surface temperature and the characteristics of the air masses on the formation area. The importance of Sea Surface Temperature (SST) consists in modulating the intense latent and sensible heat fluxes, which control the development of the TLC. For tropical cyclones, one of the most studied factors in recent years is the ocean heat content in the formation basin of these storms. We plan here to extend this analysis to TLC. Besides innovative studies with coupled atmosphere-waves-ocean numerical models, a simpler approach for investigating the sole effect of the ocean heat content consists of adopting a simplified ocean (1-Dimensional) description by varying the local characteristics of the Ocean Mixed Layer (OML). In this work we use the WRF (Weather Research and Forecasting system) model, in standalone (atmospheric) mode, with 3 km grid spacing, forced with GFS-GDAL (0.25°x0.25° horizontal resolution) and SST initialization provided by the MFS-CMEMs Copernicus dataset. Three case studies of TLC are examined here, namely ROLF (06-09/11/2011), ILONA (19-21/01/2014) and NUMA (11-20/11/2017). The ocean is simulated with an OML approach, with SST updated at each iteration as a function of the atmospheric heat fluxes and with an average mixed layer deph (MDL) provided by the MFS-CMEMS dataset. For each TLC studied, the MDL is modified by increasing and decreasing its depth by 50% and increasing and decreasing its lapse rate by 50%. The results show how the structure of the MDL influences not only the intensity of the cyclone but also the structure and precipitation both in terms of quantity and location. These outcomes suggest that, as for hurricanes, also for MEDICANES the heat content of the mass of seawater plays a fundamental role in their intensification, suggesting further studies also in a climate change perspective.</p>

scholarly journals Upper-Ocean Mixed Layer and Wintertime Sea Surface Temperature Anomalies in the North Pacific

2006 ◽  
Vol 19 (2) ◽  
pp. 300-307 ◽  
Author(s):  
Tomohiko Tomita ◽  
Masami Nonaka
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Mixed Layer ◽  
North Pacific ◽  
Sea Surface ◽  
Upper Ocean ◽  
Ocean Mixed Layer ◽  
The North ◽  
The Impact ◽  
The North Pacific

Abstract In the North Pacific, the wintertime sea surface temperature anomaly (SSTA), which is represented by March (SSTAMar), when the upper-ocean mixed layer depth (hMar) reaches its maximum, is formed by the anomalous surface forcing from fall to winter (S′). As a parameter of volume, hMar has a potential to modify the impact of S′ on SSTAMar. Introducing an upper-ocean heat budget equation, the present study identifies the physical relationship among the spatial distributions of hMar, S′, and SSTAMar. The long-term mean of hMar adjusts the spatial distribution of SSTAMar. Without the adjustment, the impact of S′ on SSTAMar is overestimated where the hMar mean is deep. Since hMar is partially due to seawater temperature, it leads to nonlinearity between the S′ and the SSTAMar. When the SSTAMar is negative (positive), the sensitivity to S′ is impervious (responsive) with the deepening (shoaling) of the hMar compared to the linear sensitivity. The thermal impacts from the ocean to the atmosphere might be underestimated under the assumption of the linear relationship.

scholarly journals On the Ocean Mixed Layer influence on the genesis of Mediterranean Tropical-Like cyclones

2021 ◽  
Author(s):  
Antonio Ricchi ◽  
Giovanni Liguori ◽  
Leone Cavicchia ◽  
Mario Marcello Miglietta ◽  
Davide Bonaldo ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Case Studies ◽  
Mixed Layer ◽  
Heat Content ◽  
Heat Fluxes ◽  
Ocean Heat Content ◽  
Sea Surface ◽  
Ocean Mixed Layer ◽  
Vast Number

<p>The Mediterranean basin is the formation site of a vast number and type of cyclones. Among these, we can occasionally identify intense vortices showing tropical characteristics, called Tropical-Like Cyclones (TLC). Their development has been studied in several case studies, showing the influence of synoptic scale upper level forcings and mesoscale features, such as the sea surface temperature and the characteristics of the air masses on the formation area. The importance of Sea Surface Temperature (SST) consists in modulating the intense latent and sensible heat fluxes, which control the development of the TLC. For tropical cyclones, one of the most studied factors in recent years is the ocean heat content in the formation basin of these storms. We plan here to extend this analysis to TLC. Besides innovative studies with coupled atmosphere-waves-ocean numerical models, a simpler approach for investigating the sole effect of the ocean heat content consists of adopting a simplified ocean description by varying the local characteristics of the Ocean Mixed Layer (OML). In this work we use the WRF (Weather Research and Forecasting system) model, in standalone (atmospheric) mode, with 3 km grid spacing, forced with GFS-GDAL (0.25°x0.25° horizontal resolution) and SST initialization provided by the MFS-CMEMs Copernicus dataset. Two case studies of TLC are examined here, namely ROLF (06-09/11/2011) and IANOS (14-19/09/2020). The ocean is simulated with an OML approach, with SST updated at each iteration as a function of the atmospheric heat fluxes and with an average mixed layer deph (MDL) provided by the MFS-CMEMS dataset. For each TLC studied, the MDL is modified by increasing and decreasing its depth by 10 mt, 30 mt, 50 mt . The preliminary results show how the structure of the MDL influences  the intensity of the cyclone but also the structure and precipitation both in terms of quantity and location. </p>

scholarly journals Interannual Variability of Sea Surface Temperature off Java and Sumatra in a Global GCM*

2008 ◽  
Vol 21 (11) ◽  
pp. 2451-2465 ◽  
Author(s):  
Yan Du ◽  
Tangdong Qu ◽  
Gary Meyers
Keyword(s):  
Indian Ocean ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Mixed Layer ◽  
Heat Budget ◽  
Sea Surface ◽  
Surface Mixed Layer ◽  
Horizontal Advection ◽  
Cold Anomaly ◽  
Sst Anomalies

Abstract Using results from the Simple Ocean Data Assimilation (SODA), this study assesses the mixed layer heat budget to identify the mechanisms that control the interannual variation of sea surface temperature (SST) off Java and Sumatra. The analysis indicates that during the positive Indian Ocean Dipole (IOD) years, cold SST anomalies are phase locked with the season cycle. They may exceed −3°C near the coast of Sumatra and extend as far westward as 80°E along the equator. The depth of the thermocline has a prominent influence on the generation and maintenance of SST anomalies. In the normal years, cooling by upwelling–entrainment is largely counterbalanced by warming due to horizontal advection. In the cooling episode of IOD events, coastal upwelling–entrainment is enhanced, and as a result of mixed layer shoaling, the barrier layer no longer exists, so that the effect of upwelling–entrainment can easily reach the surface mixed layer. Horizontal advection spreads the cold anomaly to the interior tropical Indian Ocean. Near the coast of Java, the northern branch of an anomalous anticyclonic circulation spreads the cold anomaly to the west near the equator. Both the anomalous advection and the enhanced, wind-driven upwelling generate the cold SST anomaly of the positive IOD. At the end of the cooling episode, the enhanced surface thermal forcing overbalances the cooling effect by upwelling/entrainment, and leads to a warming in SST off Java and Sumatra.

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