Assimilation of Satellite Sea Surface Temperature Retrievals

2003 ◽  
Vol 84 (11) ◽  
pp. 1575-1580 ◽  
Author(s):  
Andrew Harris ◽  
Eileen Maturi
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Satellite Data ◽  
Weather Prediction ◽  
Information Service ◽  
Sea Surface ◽  
Science Center ◽  
Optimal Method ◽  
External Data ◽  
The Impact

The Workshop on Assimilation of Satellite Sea Surface Temperatures (SST) Retrievals was held on 24–26 April 2001 in Camp Springs, Maryland, at the National Oceanic and Atmospheric Administration (NOAA) Science Center. The purpose of the workshop was for NOAA's National Environmental Satellite Data and Information Service Office of Research and Applications to initiate a collaborative project with the U.S. Navy, National Centers for Environmental Prediction, the industry, and academia. The concept of the project was to develop an optimal method for assimilating satellite data into operational analyses of sea surface temperature. The aim of the workshop was to develop a demonstration system with the following results. First, ensure that the advantages of each data type (polar orbiting and geostationary) are fully exploited, while minimizing the impact of potential errors. Second, employ state-of-the-art radiative transfer modeling, variational assimilation techniques, intersensor calibration, and use of external data such as upper-air temperatures and humidities. The resulting product will represent the next big step in use of satellite data for sea surface temperature and should be the product of choice for numerical weather prediction, operational oceanography, and fisheries and climate research.

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.

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

2011 ◽  
Vol 50 (11) ◽  
pp. 2319-2337 ◽  
Author(s):  
William T. Thompson ◽  
Tracy Haack
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Large Scale ◽  
Weather Prediction ◽  
Numerical Weather Prediction Model ◽  
Sea Surface ◽  
Microwave Propagation ◽  
Air Masses ◽  
The Impact ◽  
Analysis Of Time Series

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.

scholarly journals The SST Quality Monitor (SQUAM)

2010 ◽  
Vol 27 (11) ◽  
pp. 1899-1917 ◽  
Author(s):  
Prasanjit Dash ◽  
Alexander Ignatov ◽  
Yury Kihai ◽  
John Sapper
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Real Time ◽  
Satellite Data ◽  
Information Service ◽  
Sea Surface ◽  
Gaussian Shape ◽  
Cross Platform ◽  
National Environmental

Abstract The National Environmental Satellite, Data, and Information Service (NESDIS) has been operationally generating sea surface temperature (SST) products (TS) from the Advanced Very High Resolution Radiometers (AVHRR) onboard NOAA and MetOp-A satellites since the early 1980s. Customarily, TS are validated against in situ SSTs. However, in situ data are sparse and are not available globally in near–real time (NRT). This study describes a complementary SST Quality Monitor (SQUAM), which employs global level 4 (L4) SST fields as a reference standard (TR) and performs statistical analyses of the differences ΔTS = TS − TR. The results are posted online in NRT. The TS data that are analyzed are the heritage National Environmental Satellite, Data, and Information Service (NESDIS) SST products from NOAA-16, -17, -18, and -19 and MetOp-A from 2001 to the present. The TR fields include daily Reynolds, real-time global (RTG), Operational Sea Surface Temperature and Sea Ice Analysis (OSTIA), and Ocean Data Analysis System for Marine Environment and Security for the European Area (MERSEA) (ODYSSEA) analyses. Using multiple fields facilitates the distinguishing of artifacts in satellite SSTs from those in the L4 products. Global distributions of ΔTS are mapped and their histograms are analyzed for proximity to Gaussian shape. Outliers are handled using robust statistics, and the Gaussian parameters are trended in time to monitor SST products for stability and consistency. Additional TS checks are performed to identify retrieval artifacts by plotting ΔTS versus observational parameters. Cross-platform TS biases are evaluated using double differences, and cross-L4 TR differences are assessed using Hovmöller diagrams. SQUAM results compare well with the customary in situ validation. All satellite products show a high degree of self- and cross-platform consistency, except for NOAA-16, which has flown close to the terminator in recent years and whose AVHRR is unstable.

scholarly journals Interannual Variability and Trends in Sea Surface Temperature, Lower and Middle Atmosphere Temperature at Different Latitudes for 1980–2019

Atmosphere ◽  
2021 ◽  
Vol 12 (4) ◽  
pp. 454
Author(s):  
Andrew R. Jakovlev ◽  
Sergei P. Smyshlyaev ◽  
Vener Y. Galin
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Lower Stratosphere ◽  
Middle Atmosphere ◽  
Southern Oscillation ◽  
Lower Troposphere ◽  
Reanalysis Data ◽  
Sea Surface ◽  
The Arctic ◽  
The Impact

The influence of sea-surface temperature (SST) on the lower troposphere and lower stratosphere temperature in the tropical, middle, and polar latitudes is studied for 1980–2019 based on the MERRA2, ERA5, and Met Office reanalysis data, and numerical modeling with a chemistry-climate model (CCM) of the lower and middle atmosphere. The variability of SST is analyzed according to Met Office and ERA5 data, while the variability of atmospheric temperature is investigated according to MERRA2 and ERA5 data. Analysis of sea surface temperature trends based on reanalysis data revealed that a significant positive SST trend of about 0.1 degrees per decade is observed over the globe. In the middle latitudes of the Northern Hemisphere, the trend (about 0.2 degrees per decade) is 2 times higher than the global average, and 5 times higher than in the Southern Hemisphere (about 0.04 degrees per decade). At polar latitudes, opposite SST trends are observed in the Arctic (positive) and Antarctic (negative). The impact of the El Niño Southern Oscillation phenomenon on the temperature of the lower and middle atmosphere in the middle and polar latitudes of the Northern and Southern Hemispheres is discussed. To assess the relative influence of SST, CO2, and other greenhouse gases’ variability on the temperature of the lower troposphere and lower stratosphere, numerical calculations with a CCM were performed for several scenarios of accounting for the SST and carbon dioxide variability. The results of numerical experiments with a CCM demonstrated that the influence of SST prevails in the troposphere, while for the stratosphere, an increase in the CO2 content plays the most important role.

scholarly journals The impact of climate model sea surface temperature biases on tropical cyclone simulations

2018 ◽  
Vol 53 (1-2) ◽  
pp. 173-192 ◽  
Author(s):  
Wei-Ching Hsu ◽  
Christina M. Patricola ◽  
Ping Chang
Keyword(s):  
Tropical Cyclone ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Climate Model ◽  
Sea Surface ◽  
The Impact

scholarly journals STUDY ON CYCLONE INDUCED PHYTOPLANKTON BLOOM IN THE ARABIAN SEA THROUGH GAP-FREE RECONSTRUCTED CHLOROPHYLL-A DATA

2020 ◽  
Vol XLIII-B3-2020 ◽  
pp. 1391-1396
Author(s):  
R. Shunmugapandi ◽  
S. Gedam ◽  
A. B. Inamdar
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Chlorophyll A ◽  
Arabian Sea ◽  
Phytoplankton Bloom ◽  
Suitable Condition ◽  
Sea Surface ◽  
Cyclone Track ◽  
Chl A ◽  
The Impact

Abstract. Ocean surface phytoplankton responses to the tropical cyclone (TC)/storms have been extensively studied using satellite observations by aggregating the data into a weekly or bi-weekly composite. The reason behind is the significant limitations found in the satellite-based observation is the missing of valid data due to cloud cover, especially at the time of cyclone track passage. The data loss during the cyclone is found to be a significant barrier to efficiently investigate the response of chl-a and SST during cyclone track passage. Therefore it is necessary to rectify the above limitation to effectively study the impact of TC on the chlorophyll-a concentration (chl-a) and the sea surface temperature (SST) to achieve a complete understanding of their response to the TC prevailed in the Arabian Sea. Intending to resolve the limitation mentioned above, this study aims to reconstruct the MODIS-Aqua chl-a, and SST data using Data Interpolating Empirical Orthogonal Function (DINEOF) for all the 31 cyclonic events occurred in the Arabian Sea during 2003-2018 (16 years). Reconstructed satellite retrieved data covering all the cyclonic events were further used to investigate the chl-a and SST dynamics during TC. From the results, the exciting fact has been identified that only two TC over the eastern-AS were able to induce phytoplankton bloom. On investigating this scenario using sea surface temperature, it was disclosed that the availability of nutrients decides the suitable condition for the phytoplankton to proliferate in the surface ocean. Relevant to the precedent criterion, the results witnessed that the 2 TC (Phyan and Ockhi cyclone) prevailed in the eastern AS invoked a suitable condition for phytoplankton bloom. Other TC found to be less provocative either due to less intensity, origination region or the unsuitable condition. Thereby, gap-free reconstructed daily satellite-derived data efficiently investigates the response of bio-geophysical parameters during cyclonic events. Moreover, this study sensitised that though several TC strikes the AS, only two could impact phytoplankton productivity and SST found to highly consistent with the chl-a variability during the cyclone passage.

Experience in developing a method for long-term forecasting of the ice breakup time for the Vyatka River basin

2021 ◽  
Vol 4 ◽  
pp. 99-111
Author(s):  
Y.A Pavroz . ◽  
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
River Basin ◽  
Geopotential Height ◽  
Sea Surface ◽  
River Ice ◽  
Northwest Pacific ◽  
Ice Breakup ◽  
The Impact ◽  
Breakup Time

An attempt is made to develop a method for long-term forecasting of the ice breakup time for the Vyatka River basin, to identify the impact of the distribution of sea surface temperature and geopotential height in the informative regions at the levels H100 and H500 over the Northern Hemisphere on the river ice breakup. The location and boundaries of the informative regions in the fields of H100 and H500 were revealed by the discriminant analysis, the EOF expansion coefficients of the fields of anomalies of monthly mean values of H100 and H500 for January and February and the anomalies of monthly mean sea surface temperature in the North Atlantic and Northwest Pacific were used as potential predictors. The stepwise regression analysis allowed deriving good and satisfactory (S/σ = 0.45–0.73) complex prognostic equations for forecasting the ice breakup time for the Vyatka River basin. The essential influence of H100 and H500 geopotential height fields and the spatial distribution of sea surface temperature anomalies in the North Atlantic and Northwest Pacific in January and February on the river ice breakup time is revealed. It is proposed to improve the method by considering the impact of air temperature, maximum ice thickness per winter, and other indirect characteristics on the processes of river ice breakup in the Vyatka River basin. Keywords: ice regime, long-range forecast, river ice breakup, expansion coefficients, geopotential height fields, spring ice phenomena, energy-active zones of the oceans, complex prognostic equation

scholarly journals The Role of Sea Surface Temperature Forcing in the Life-Cycle of Mediterranean Cyclones

2020 ◽  
Vol 12 (5) ◽  
pp. 825 ◽  
Author(s):  
Christos Stathopoulos ◽  
Platon Patlakas ◽  
Christos Tsalis ◽  
George Kallos
Keyword(s):  
Life Cycle ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Early Warning Systems ◽  
Life Cycles ◽  
Heat Fluxes ◽  
Sea Surface ◽  
Mediterranean Cyclones ◽  
The Mediterranean ◽  
The Impact

Air–sea interface processes are highly associated with the evolution and intensity of marine-developed storms. Specifically, in the Mediterranean Sea, the air–ocean temperature deviations have a profound role during the several stages of Mediterranean cyclonic events. Subsequently, this enhances the need for better knowledge and representation of the sea surface temperature (SST). In this work, an analysis of the impact and uncertainty of the SST from different well-known datasets on the life-cycle of Mediterranean cyclones is attempted. Daily SST from the Real Time Global SST (RTG_SST) and hourly SST fields from the Operational SST and Sea Ice Ocean Analysis (OSTIA) and the NEMO ocean circulation model are implemented in the RAMS/ICLAMS-WAM coupled modeling system. For the needs of the study, the Mediterranean cyclones Trixi, Numa, and Zorbas were selected. Numerical experiments covered all stages of their life-cycles (five to seven days). Model results have been analyzed in terms of storm tracks and intensities, cyclonic structural characteristics, and derived heat fluxes. Remote sensing data from the Integrated Multi-satellitE Retrievals (IMERG) for Global Precipitation Measurements (GPM), Blended Sea Winds, and JASON altimetry missions were employed for a qualitative and quantitative comparison of modeled results in precipitation, maximum surface wind speed, and wave height. Spatiotemporal deviations in the SST forcing rather than significant differences in the maximum/minimum SST values, seem to mainly contribute to the differences between the model results. Considerable deviations emerged in the resulting heat fluxes, while the most important differences were found in precipitation exhibiting spatial and intensity variations reaching 100 mm. The employment of widely used products is shown to result in different outcomes and this point should be taken into consideration in forecasting and early warning systems.

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