Estimation of Sea Surface Temperature from the Spinning Enhanced Visible and Infrared Imager, improved using numerical weather prediction

2011 ◽  
Vol 115 (1) ◽  
pp. 55-65 ◽  
Author(s):  
P. Le Borgne ◽  
H. Roquet ◽  
C.J. Merchant
Author(s):  
Amirul Islam ◽  
Andy Chan ◽  
Matthew Ashfold ◽  
Chel Gee Ooi ◽  
Majid Azari

Maritime Continent (MC) positions in between Asian and Australian summer monsoons zone. Its complex topography and shallow seas around it is a major challenge for the climate researchers to model and understand it. Monsoon in this area is affected by inter-scale ocean-atmospheric interactions like El-Niño Southern Oscillation (ENSO), Indian Ocean Dipole (IOD) and Madden-Julian Oscillation. Monsoon rainfall in MC (especially in Indonesia and Malaysia) profoundly exhibits its variability dependency on ocean-atmospheric phenomena in this region. This monsoon shift often introduces to dreadful events like biomass burning (BB) in Southeast Asia (SEA) which sometimes leads to severe trans-boundary haze pollution. In this study, the episode of BB in 2015 of SEA is highlighted and discussed. Observational satellite datasets are tested by performing simulations with numerical weather prediction (NWP) model using WRF-ARW (Advanced research WRF). Observed and model datasets are compared to study the sea surface temperature (SST) and precipitation (rainfall) anomalies influenced by ENSO, IOD and MJO. Correlations have been recognised which explains the delayed rainfall of regular monsoon in MC due to the influence of ENSO, IOD and MJO during 2015 BB episode, eventually leading to intensification of fire and severe haze.


2020 ◽  
Vol 12 (22) ◽  
pp. 3771
Author(s):  
Gary A. Wick ◽  
Sandra L. Castro

We evaluate the reliability and basic characteristics of observations of extreme DW events from current operational geostationary satellite sea surface temperature (SST) products through examination of three months of diurnal warming (DW) estimates derived by different methodologies from the Spinning Enhanced Visible and Infrared Imager on Meteosat-11, Advanced Himawari Imager on Himawari-8, and Advanced Baseline Imager on the Geostationary Operational Environmental Satellite (GOES)-16. This work primarily focuses on the following research questions: (1) Can these operational SST products accurately characterize extreme DW events? (2) What are the amplitudes and frequencies of these events? To answer these, we compute distributions of DW and DW exceedance and compare them amongst the different methods and geostationary sensors. Examination of the DW estimates demonstrates several challenges in accurately deriving distributions of the DW amplitude, particularly associated with estimating the “foundation” temperature and uncertainties in cloud screening. Overall, the results suggest that current geostationary sensors can reliably assess extreme DW, but the estimates are sensitive to the computational methods applied. We thus suggest careful processing/screening of the SST retrievals. We find a value of 3 K, corresponding to the 99th percentile, provides a potential practical threshold for extreme warming, but events of at least 6 K were reliably observed. Warming in excess of 6 K occurred somewhere an average of 47% of the time, and its probability at a given location was of O(10−6).


2020 ◽  
Vol 12 (4) ◽  
pp. 720 ◽  
Author(s):  
Simon Good ◽  
Emma Fiedler ◽  
Chongyuan Mao ◽  
Matthew J. Martin ◽  
Adam Maycock ◽  
...  

The Operational Sea Surface Temperature and Sea Ice Analysis (OSTIA) system generates global, daily, gap-filled foundation sea surface temperature (SST) fields from satellite data and in situ observations. The SSTs have uncertainty information provided with them and an ice concentration (IC) analysis is also produced. Additionally, a global, hourly diurnal skin SST product is output each day. The system is run in near real time to produce data for use in applications such as numerical weather prediction. Data production is monitored routinely and outputs are available from the Copernicus Marine Environment Monitoring Service (CMEMS; marine.copernicus.eu). As an operational product, the OSTIA system is continuously under development. For example, since the original descriptor paper was published, the underlying data assimilation scheme that is used to generate the foundation SST analyses has been updated. Various publications have described these changes but a full description is not available in a single place. This technical note focuses on the production of the foundation SST and IC analyses by OSTIA and aims to provide a comprehensive description of the current system configuration.


2013 ◽  
Vol 30 (12) ◽  
pp. 2926-2943 ◽  
Author(s):  
Eunjeong Lee ◽  
Yign Noh ◽  
Naoki Hirose

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.


2021 ◽  
Author(s):  
Iam-Fei Pun ◽  
John Knaff ◽  
Charles Sampson

<p>The sea surface temperature (SST) beneath a tropical cyclone (TC) is of great importance to its dynamics; therefore, understanding and accurately estimating the magnitude of SST cooling is of vital importance.  Existing studies have explored important influences on SST such as TC translation speed, maximum surface winds, ocean thermal condition and ocean stratification.  But the influence of the TC wind radii (or collectively called the TC size) on SST has been largely overlooked.  In this study we assess the influence of wind radii uncertainty on SST cooling by a total of 15,983 numerical simulations for the western North Pacific during the 2014-2018 seasons.  Results show a 6-20% SST cooling error induced using wind radii from the Joint Typhoon Warning Center official forecast and a 35-40% SST cooling error using wind radii from the operational runs of the Hurricane Weather Research and Forecasting (HWRF) model.  Our results indicate that SST cooling is most sensitive to the radius of 64 kt winds.  The correlation between SST cooling induced by the TC and its size is 0.49, which is highest among all the parameters tested.  This suggests that it is extremely important to get TC size correct in order to predict the SST cooling response, which then impacts TC evolution in numerical weather prediction models.</p>


2014 ◽  
Vol 14 (9) ◽  
pp. 4409-4418 ◽  
Author(s):  
J. K. Sweeney ◽  
J. M. Chagnon ◽  
S. L. Gray

Abstract. The sensitivity of sea breeze structure to sea surface temperature (SST) and coastal orography is investigated in convection-permitting Met Office Unified Model simulations of a case study along the south coast of England. Changes in SST of 1 K are shown to significantly modify the structure of the sea breeze immediately offshore. On the day of the case study, the sea breeze was partially blocked by coastal orography, particularly within Lyme Bay. The extent to which the flow is blocked depends strongly on the static stability of the marine boundary layer. In experiments with colder SST, the marine boundary layer is more stable, and the degree of blocking is more pronounced. Although a colder SST would also imply a larger land–sea temperature contrast and hence a stronger onshore wind – an effect which alone would discourage blocking – the increased static stability exerts a dominant control over whether blocking takes place. The implications of prescribing fixed SST from climatology in numerical weather prediction model forecasts of the sea breeze are discussed.


2010 ◽  
Vol 49 (11) ◽  
pp. 2267-2284 ◽  
Author(s):  
Jason C. Knievel ◽  
Daran L. Rife ◽  
Joseph A. Grim ◽  
Andrea N. Hahmann ◽  
Joshua P. Hacker ◽  
...  

Abstract This paper describes a simple technique for creating regional, high-resolution, daytime and nighttime composites of sea surface temperature (SST) for use in operational numerical weather prediction (NWP). The composites are based on observations from NASA’s Moderate Resolution Imaging Spectroradiometer (MODIS) aboard Aqua and Terra. The data used typically are available nearly in real time, are applicable anywhere on the globe, and are capable of roughly representing the diurnal cycle in SST. The composites’ resolution is much higher than that of many other standard SST products used for operational NWP, including the low- and high-resolution Real-Time Global (RTG) analyses. The difference in resolution is key because several studies have shown that highly resolved SSTs are important for driving the air–sea interactions that shape patterns of static stability, vertical and horizontal wind shear, and divergence in the planetary boundary layer. The MODIS-based composites are compared to in situ observations from buoys and other platforms operated by the National Data Buoy Center (NDBC) off the coasts of New England, the mid-Atlantic, and Florida. Mean differences, mean absolute differences, and root-mean-square differences between the composites and the NDBC observations are all within tenths of a degree of those calculated between RTG analyses and the NDBC observations. This is true whether or not one accounts for the mean offset between the skin temperatures of the MODIS dataset and the bulk temperatures of the NDBC observations and RTG analyses. Near the coast, the MODIS-based composites tend to agree more with NDBC observations than do the RTG analyses. The opposite is true away from the coast. All of these differences in point-wise comparisons among the SST datasets are small compared to the ±1.0°C accuracy of the NDBC SST sensors. Because skin-temperature variations from land to water so strongly affect the development and life cycle of the sea breeze, this phenomenon was chosen for demonstrating the use of the MODIS-based composite in an NWP model. A simulated sea breeze in the vicinity of New York City and Long Island shows a small, net, but far from universal improvement when MODIS-based composites are used in place of RTG analyses. The timing of the sea breeze’s arrival is more accurate at some stations, and the near-surface temperature, wind, and humidity within the breeze are more realistic.


2013 ◽  
Vol 13 (9) ◽  
pp. 24785-24807
Author(s):  
J. K. Sweeney ◽  
J. M. Chagnon ◽  
S. L. Gray

Abstract. The sensitivity of sea breeze structure to sea surface temperature (SST) and coastal orography is investigated in convection-permitting Met Office Unified Model simulations of a case study along the south coast of England. Changes in SST of 1 K are shown to significantly modify the structure of the sea breeze. On the day of the case study the sea breeze was partially blocked by coastal orography, particularly within Lyme Bay. The extent to which the flow is blocked depends strongly on the static stability of the marine boundary layer. In experiments with colder SST, the marine boundary layer is more stable, and the degree of blocking is more pronounced. The implications of prescribing fixed SST from climatology in numerical weather prediction model forecasts of the sea breeze are discussed.


Sign in / Sign up

Export Citation Format

Share Document