How consistent is the satellite derived SST–LHF relationship in comparison with observed values?

Time series data for sea surface temperature (moored buoy), wind speed, air temperature, sea level pressure, relative humidity, short wave radiation and rainfall were collected close to the Lakshadweep islands for five months from July 2000 to cover two seasons, namely summer monsoon and autumn. Day and night passes of TMI data for the same period were analysed to compare with the observed values. Daily mean values were then generated from both satellite‐derived as well as observed parameters and daily latent heat flux (LHF) values computed using the advanced COARE‐3.0 version of the model. In concurrence with earlier studies, the observed LHF–SST relationship was inverse as the SST during this season seldom fell below 27°C. On the contrary, the satellite derived LHF–SST relationship exhibited a direct correlation. It is also observed that the satellite underestimation of SST increases linearly on either side of a threshold value of 28.5°C. Although the SST over the eastern Arabian Sea was generally above 27°C, the satellite underestimation often produced SSTs less than 27°C, thereby supporting a linear relationship with LHF, as suggested by Zhang and McPhaden. Similarly for SSTs higher than 28°C, the satellite underestimation prevented a further decrease of LHF (to sustain the linear relationship) by virtue of the inverse relationship for SSTs higher than 28°C. The overestimation of SST and wind speed in the satellite scenario generates a virtual enhancement of LHF values without cooling the sea surface. The linear relationship between SST and LHF is thus nothing but a virtual display of the observed inverse SST–LHF relationship.     

Intraseasonal signals in the daily high resolution blended Reynolds sea surface temperature product over the tropical Indian Ocean and their validation

National Oceanic and Atmospheric Administration daily sea surface temperature (SST) products based on Advanced Microwave Scanning Radiometer (AMSR) and Advanced Very High Resolution Radiometer (AVHRR) have been used to understand the variability in the tropical Indian Ocean SST. These products are comparable with the deep sea moored buoy observations and the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) SST in the tropical Indian Ocean. However considerable difference is noticed between these satellite SST products and deep sea buoys, especially at the intraseasonal time scale. Further the first Complex Empirical Orthogonal Function (CEOF) mode of TMI and AVHRR SST explains respectively 46.49% and 46.19% of the total variance. The second CEOF mode of TMI and AVHRR SST explains respectively 23.19% and 18.94% of the total SST variance in the tropical Indian Ocean. The AVHRR SST product is important because this daily product has been available since 1985. The analysis shows that AMSR measurements are contributing considerably to the understanding of the tropical Indian Ocean SST variability. Though satellite SST products are able to capture the observed intraseasonal variability reasonably well, more accurate satellite SST products are therefore necessary to understand the climatologically important Indian Ocean region and its air–sea interaction processes.     

Comparison of AMSR‐E and TMI sea surface temperature with Argo near‐surface temperature over the Indian Ocean

Sea surface temperature (SST) measurements from the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR‐E) and the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) are compared with near‐surface temperature (foundation SST) in situ measurements obtained from Argo floats over the Indian Ocean. Spatial variation was compared for 2002–2006 and 11 floats were used for temporal variation collocated observations. The results show that TMI and AMSR‐E SST measurements are slightly overestimated during the pre‐ and post‐monsoon seasons and underestimated during the monsoon season. Statistical analysis shows that the SST from the AMSR‐E is better correlated with the Argo foundation SST compared to the TMI. The standard deviation (SD) and root mean square error (RMSE) for AMSR‐E SST are 0.58°C and 0.35°C, respectively, over the Equatorial Indian Ocean (EIO). The corresponding values for the TMI are 0.66°C and 0.47°C. Over the Arabian Sea the SD values are slightly higher compared to the EIO values, whereas RMSE values are less for both TMI and AMSR‐E SST. These retrieval accuracies are above the expected retrieval accuracy. The seasonal average spatial distribution of AMSR‐E SST shows a better match with the Argo foundation SST compared to TMI SST distributions. The robustness of the good spatial match during the monsoon season may be attributed to strong winds.     

Microwave measurement of rain and sea surface temperature by the TRMM Microwave Imager (TMI)

The Tropical Rainfall Measuring Mission (TRMM) is important for studies of the global hydrological cycle and for testing the realism of climate models and their ability to simulate and predict climate accurately; the effect of El Nino on climate could be addressed as well. This paper investigates the microwave rain measurement using satellite data from the TRMM Microwave Imager (TMI). The physical bases of rainfall estimation algorithms, vertical structure of rain and its physical processes are explained. The algorithms for processing TMI radiance and brightness temperature data are presented. Various rain maps and sea surface temperature (SST) maps are produced using TMI microwave data. The performance, calibration, analysis of results and sources of errors in the averaged monthly surface rain rate estimation are discussed.     

Identification of dry and wet soil conditions using TRMM/TMI brightness temperatures and potential for drought monitoring

In this study we present a methodology for monitoring drought conditions directly from microwave brightness temperature observations. Tropical Rainfall Measurement Mission (TRMM)/TRMM Microwave Imager (TMI) 10.7 GHz brightness temperatures were analysed along with TRMM merged rainfall products during June–August for 4 years to depict the spatial and temporal extent of dry and wet soil conditions. Comparison of brightness temperature anomalies with rainfall anomalies clearly shows the contrasting features of drought year 2002 and normal monsoon year 2001.     

Bimodal variation of SST and related physical processes over the North Indian Ocean: special emphasis on satellite observations

Using sea surface temperature (SST) and wind speed retrieved by the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI), for the period of 1998–2003, we have studied the annual cycle of SST and confirmed the bimodal distribution of SST over the north Indian Ocean. Detailed analysis of SST revealed that the summer monsoon cooling (winter cooling) over the eastern Arabian Sea (Bay of Bengal) is more prominent than winter cooling (summer monsoon cooling). A sudden drop in surface short wave radiation by 57 W m^?2 (74 W m^?2) and rise in kinetic energy per unit mass by 24 J kg^?1 (26 J kg^?1) over the eastern Arabian Sea (Bay of Bengal) is observed in summer monsoon cooling period. The subsurface profiles of temperature and density for the spring warming and summer monsoon cooling phases are studied using the Arabian Sea Monsoon Experiment (ARMEX) data. These data indicate a shallow mixed layer during the spring warming and a deeper mixed layer during the summer monsoon cooling. Deepening of the mixed layer by 30 to 40 m with corresponding cooling of 2°C is found from warming to summer monsoon cooling in the eastern Arabian Sea. The depth of the 28°C isotherm in the eastern Arabian Sea during the spring warming is 80 m and during summer monsoon cooling it is about 60 m, while over the Bay of Bengal the 28°C isotherm is very shallow (35 m), even during the summer monsoon cooling. The time series of the isothermal layer depth and mixed layer depth during the warming phase revealed that the formation of the barrier layer in the spring warming phase and the absence of such layers during the summer cooling over the Arabian Sea. However, the barrier layer does exist over the Bay of Bengal with significant magnitude (20–25 m). The drop in the heat content with in first 50 m of the ocean from warming to the cooling phase is about 2.15 × 10⁸ J m^?2 over the Arabian Sea.     

Study of geophysical parameters associated with the Orissa super cyclone using active and passive microwave remote sensing measurements

A detailed study of the Orissa super cyclone over the Bay of Bengal from 25 to 29 October 1999 has been carried out using various spaceborne sensors, namely VHRR, SSM/I, TMI, MSMR, TOPEX‐RA and TMR. The raining areas are delineated using dual frequency TOPEX altimeter and coaligned three‐frequency TOPEX microwave radiometer (TMR) in addition to DMSP SSM/I, TRMM TMI and IRS‐P4 MSMR. Various oceanic parameters like rain rate (RR), cloud liquid water (CLW), integrated water vapour (IWV), ocean surface wind speed (OWS), and wave conditions on the ocean surface near and within the cyclonic vicinity were studied. This paper has two innovative aspects: (1) it indirectly validates the empirically developed MSMR algorithms for water vapour and wind speed under moderate cloud water conditions, and (2) it makes non‐conventional use of TOPEX altimeter and TMR, especially for rain rate and cloud liquid water over the cyclone. Results and significance of the synergistic measurements from various active and passive microwave and infrared observations from satellites have been discussed. The combined capabilities of these measurements portray the several important features associated with cyclones in a more informative way than any individual satellite component.     

Study of upper ocean parameters during passage of tropical cyclones over Indian seas

The primary energy supply for tropical cyclones is the upward latent heat fluxes that are directly related to Sea Surface Temperatures (SST). The strong winds induce a negative SST anomaly in the tropical cyclone wake. This is usually referred to as the ‘cold wake’. Many studies have suggested that the cold wake results in a significant reduction of upward latent heat fluxes that supply energy to the tropical cyclone, and hence provides a negative feedback on its intensity. The cold-wake feedback on the intensity of tropical cyclones is a strong motivation to understand the oceanic response to tropical cyclones. A recent study of re-examining the mechanisms controlling the cold wake has shown the importance of vertical Ekman pumping. Under the core of tropical cyclones (typically over a disk of 100 km radius), vertical pumping is responsible for a cooling of the entire water column, while surface heat fluxes and vertical mixing both contribute to the surface cooling during the cyclone passage. Farther away from the cyclone core, vertical mixing generally overwhelms the effect of vertical pumping, and also the effect of heat fluxes in the case of strong tropical cyclones. The study examines the Ekman pumping during the passage of few cyclonic storms in the Arabian Sea (AS) and Bay of Bengal (BOB) during last decade using different datasets such as Satellite (QuikScat) and reanalysis (ERA-Interim) data and calls up the value for satellite deliverables. Surface currents and subsurface temperature structure is examined further and for different Ekman pumping velocity (EPV), variable subsurface response is illustrated. The changes in ocean surface temperature, sea level and heat content obtained from the remote sensing data products, in the wake of cyclone are also reported and thus the usefulness of satellite products to study the coupled tropical system is demonstrated.     

Upper ocean response to Super Typhoon Tembin (2012) explored using multiplatform satellites and Argo float observations

Using multiplatform satellites and in situ Argo float observations, this study systematically examined the upper ocean response to Super Typhoon Tembin (2012) in the western north pacific, and the interaction between typhoon and a pre-existing cold core eddy (CCE) was particularly focused on. Significant sea surface temperature (SST) cooling and sea surface height anomaly (SSHA) decrease was detected along track after typhoon, with the maximum SST cooling and SSHA decrease reaching 4.0°C and 25 cm, respectively. The pre-existing CCE was located to the left of the typhoon track, resulting in an intriguing leftward bias of SST cooling. The maximum SST cooling appeared at about 25 km to the left of the typhoon track, with SST cooling to the left of the track 40–100% larger than that to the right. After typhoon, the CCE was expanded by 50% due to the typhoon’s cyclonic wind stress. The thermocline was uplifted by 15–25 m by the typhoon-induced upwelling. Typhoon-enhanced vertical mixing was inferred from high-resolution Argo float data based on the Gregg–Henyey–Polzin parameterization method. The diapycnal diffusivity reached 9 × 10^?4 m² s^?1 after typhoon, which was more than 10 times larger than that before typhoon.     

Eddy-advective effects on the temperature and wind speed of the sea surface in the Northwest Pacific Subtropical Countercurrent area from satellite observations

In this study, satellite microwave and altimeter data from 1998 to 2007 are used to quantify the eddy-induced meridional heat advection (EMHA) in the Northwest Pacific Subtropical Countercurrent area. Generally, from March to May, the robust EMHA is formed at the point where meridional currents of eddies cross a zonal front of climatological background sea surface temperature (SST). The EMHA shifts westwards with eddies and varies seasonally with the SST front. It warms (cools) the sea surface west of anticyclonic (cyclonic) eddies, inducing noticeable SST anomalies (SSTAs), which are westwardly phase shifted from the eddy-induced sea surface height anomalies by about 90°. Surface wind subsequently varies with the induced SSTAs: it blows faster (slower) over the warm (cold) SST regions than the surroundings. The spatial variations of SST and sea surface wind due to the EMHA shift westwards with eddy motion. These findings from satellite observations give us the possibility of studying the role of oceanic eddies in ocean–atmosphere interaction at the timescale of weather systems in an open ocean.     

Comparison between satellite and ship measurements of sea surface temperature in the north-east Atlantic Ocean

Abstract

A comparison is made between in situ measurements of sea surface temperature (SST) in the north-east Atlantic Ocean, obtained during Cruise 145 of RRS Discovery, and SSTs derived from several overpasses of the Advanced Very High Resolution Radiometer on the NOAA-7 satellite during the same period in March 1984. The objective of the analysis was to test the ability of the satellite to map the detailed features of SST structure and to examine the performance of atmospheric correction and temperature calibration procedures in this context. Gross comparison between all the cloud-free ship and satellite data confirms agreement normally within 1 degC. More detailed comparison of SST structure along the cruise tracks shows that the satellite data are able to identify features with a resolution of 0.3°C.     

Effect of May 2003 tropical cyclone on physical and biological processes in the Bay of Bengal

Satellite observations are beginning to show the remarkable effects of tropical cyclones on upper ocean temperature and chlorophyll concentration. We use weekly, 4 km resolution chlorophyll‐a and sea surface temperature (SST) from TERRA Moderate Resolution Imaging Spectroradiometer, weekly averaged SST at 0.25° resolution from Tropical Rainfall Measuring Mission Microwave Imager, modeled primary productivity (PP) from Goddard Space Flight Center and mixed layer depth generated by US Navy's Fleet Numerical Meteorology and Oceanography Center to study the response of upper ocean physics and biology to the passage of a tropical cyclone in the southern Bay of Bengal. Decrease in SST up to 5°C, associated with the deepening of mixed layer by about 12 m, was observed. Directly under the cyclone track, PP increased from its pre‐storm value by up to 3800 mg C m^?2 day^?1, and chlorophyll‐a concentration also increased. The increase in chlorophyll‐a and productivity were not confined to the region under the cyclone track, but covered a much broader area, possibly due to forced coastal upwelling south of Sri Lanka. After the passage of the cyclone the SST slowly increased, and the chlorophyll decreased.     

Simulation of microphysical structure associated with tropical cloud clusters using mesoscale model and comparison with TRMM observations

An attempt has been made in the present study to examine the microphysical structure of a non‐squall Tropical Cloud Cluster (TCC). Three‐dimensional model simulations of cloud microphysical structure associated with a non‐squall TCC occurred on 26 October 2005 over the South Bay of Bengal have been carried out. The initial conditions for the model simulations were improved by incorporating upper air radiosonde observations and Indian Mesosphere Stratosphere Troposphere (MST) radar wind observations through analysis nudging. The horizontal and vertical distribution of the cloud hydrometeor fields observed from the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) are compared to those simulated by a mesoscale model using a sophisticated microphysical scheme. Substantial differences are noticed in the amounts of cloud microphysical parameters, with simulated values of hydrometeors being higher than TMI retrievals. Spatial distribution of Cloud Liquid Water (CLW) and Rain Water (RNW) from TMI and model simulations correspond well with each other. The cloud microphysical structure during the initial and mature phases of the storm is also investigated. Comparisons of horizontal and vertical reflectivity structure from the TRMM‐Precipitation Radar (PR) and those simulated by the model show reflectivity cores of values greater than 30 dBZ. The TRMM‐PR echo tops are 3–4 km higher than the simulated echo tops. The 24 hr accumulated precipitation from model simulations are then verified with the combined rainfall product from the TRMM observations.     

Validation and application of MODIS-derived SST in the South China Sea

Using a variety of in situ sea surface temperature (SST) data sets in the South China Sea, we validate the satellite-derived SST from the Moderate Resolution Imaging Spectroradiometer (MODIS). Analysis of a large number of match-up samples during 2008–2012 shows that the MODIS SSTs have biases ranging from –0.19°C to –0.34°C and standard deviation (STD) errors ranging from 0.58°C to 0.68°C. Specifically, mean biases are all negative but there are smaller cool biases in daytime than those in night-time. The monthly validation analysis shows that the biases exhibit apparent seasonal variations. The biases in daytime have relatively small magnitudes in spring and summer, while the negative biases in night-time are most apparent in summer. On the other hand, the time series of MODIS SSTs may exhibit an evident diurnal variation for some months, which roughly agrees with the in situ SST measurements. This study also highlights that the MODIS SSTs under cloud-free conditions are effective at detecting the high-frequency and small-scale oceanic features, such as the localized diurnal variation, oceanic front, and coastal upwelling.     

Relationship between SST gradients and upwelling off Peru and Chile: model/satellite data analysis

The upwelling system off Peru/Chile is characterized by significant mesoscale to submesoscale surface variability that results from the instability of the coastal currents (due to the strong vertical and horizontal shears) and to the marked density cross-shore gradients (associated with the mean upwelling). Here we investigate to what extent upwelling intensity can be inferred from sea surface temperature (SST) derived from remote sensing. As a first step in validation, a comparison between SST observations is performed, which indicates that the 1 km gridded multi-scale ultra-high-resolution (MUR) SST data set is defining a zone of maximum SST gradients closer to shore than the low-resolution National Centers for Environmental Information 0.25° resolution data set. Two model versions, at nominal resolutions of 2 km and 4 km, of the Massachusetts Institute of Technology general circulation model are analysed. A high-resolution version at 2 km is examined for the period 13 September 2011–23 January 2013, while a 4 km version is examined for 6 March 2011–22 April 2013. MUR shows maxima SST gradients in the range of 0.03 ± 0.02 K km^?1 while the model showed higher gradients around 0.05 ± 0.02 K km^?1. Based on coherence spectra, the relationship between upwelling rate (as inferred from the vertical velocity) and SST gradient is documented in the model from intraseasonal to annual timescales. It suggests that changes in SST gradient magnitudes are related to changes in the intensity of coastal upwelling off Peru and Chile. Such a relationship between SST gradients and vertical velocity would allow for the use of satellite-derived SSTs to monitor the intensity of coastal upwelling from the intraseasonal to annual timescales.     

Seasonal variation of sea surface temperature in the Bay of Bengal during 1992 as derived from NOAA-AVHRR SST data

Monthly maps of sea surface temperature (SST) derived from NOAA (National Oceanic and Atmospheric Administration)-AVHRR (Advanced Very High Resolution Radiometer) data during 1992 for the Bay of Bengal are analysed and compared with the available/compiled monthly seatruth (bucket thermometer) data of this region. It was noticed that the computed SST bias (AVHRR SST minus Seatruth SST), in general, varied between 2.0 and 2.5 C with smaller bias values (1.5 to 1.5 C) during January-June and December. Larger bias values were noticed in the south-eastern Bay in July and in the Andaman Sea in October. The large SST biases suggested the necessity for improvement of SST algorithms by properly removing the clouds. The spatial variation of Standard Deviation of SST bias was particularly high (0.7) in the western Bay when compared to other parts of the Bay of Bengal. The monthly maps of AVHRR SST clearly depicted the seasonal cycle of SST showing the well known bi-modal SST distribution of the study region with winter cooling, summer heating, monsoonal cooling and post-monsoon warming phases. The seasonal cycle of SST further revealed the persistence of Warm Pool (SST 28 C) in the Bay of Bengal from March through October.     

Seasonal SST patterns along the West India shelf inferred from AVHRR

Sea surface temperature (SST) patterns along the west India shelf, extending from 8° to 24°N, are analyzed during 1993-1996 to characterize seasonal variability using the advanced very high-resolution radiometer (AVHRR) SST, momentum and heat fluxes derived from ERS-1 winds and NCEP/NCAR reanalysis data. During winter monsoon (December-March), a 4-year mean SST spatial pattern shows a strong cooling north of 15°N due to surface heat depletion, while warm SSTs evolve in the south due to the intrusion of warm equatorial water. Cold water occupies the entire shelf during summer monsoon, with high degree of SST cooling dominating the Kerala coast, where Ekman pumping and upwelling promoted by the dominant alongshore wind stress component overwhelms the surface heat loss. The spectral analysis reveals semiannual and annual peaks in SST and forcing functions, which highlight the influence of monsoon forcing on the SST variability along the west India shelf.     

Variations of chlorophyll-a in the northeastern Indian Ocean after the 2004 South Asian tsunami

Analysis of satellite remote sensing data has revealed changes in distribution of chlorophyll-a (Chl-a) and sea surface temperature (SST) in the Indian Ocean during the South Asian tsunami in December 2004. Chl-a data derived from Moderate Resolution Imaging Spectroradiometer (MODIS) and Sea-viewing Wide Field-of-view Sensor (SeaWiFS) images were examined for the period from 1998 to 2005. Around the epicentre of the Sumatra earthquake, the Chl-a concentration was found to increase prior to the main event on 26 December 2004 and then decrease during the tsunami event, while a high SST (～30–31°C) was observed in and around the epicentral region. Chl-a concentrations in the coastal waters of the Southeast Asian countries were remarkably low during and after the tsunami. Similar but relatively small variations in Chl-a and SST were observed during the second earthquake on 28 March 2005. Analysis of Chl-a, SST, wind and upwelling water has provided information for understanding the changes in Chl-a concentration during the tsunami. A very large offshore phytoplankton bloom (～300 km²) appeared to the southeast of Sri Lanka about 3 weeks after the tsunami; this might have been caused by a tropical storm that could be responsible for the enhancement of nutrients.     

Variability of chlorophyll concentration in the Arabian Sea and Bay of Bengal as observed from SeaWiFS data from 1997–2000 and its interrelationship with Sea Surface Temperature (SST) derived from NOAA AVHRR

Variability of chlorophyll concentration in the Arabian Sea and Bay of Bengal has been studied using SeaWiFS eight‐day average, 9 km processed data for the period 1997–2000. The interrelationship with sea surface temperature (SST) was studied with the National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR) derived, best SST product. The chlorophyll pattern shows in general high concentrations during February to March in the Arabian Sea and November to December in the Bay of Bengal. Year‐to‐year variations in temperature show an inverse relation with chlorophyll, at different locations, even on a monthly basis. However, the intraannual variability in chlorophyll at different locations shows differences in the relationship with SST. The Arabian Sea showed an inverse relationship at most of the locations, while a positive relationship was observed in the northwest region during October to December and an inverse relationship during January to April. The Bay of Bengal showed positive relationships at northeast locations, whereas no definite assessment could be made for other locations due to the narrow range of chlorophyll concentration.A longer time series (～10 years) will be required to establish a more concrete relationship but definitely consistent patterns are emerging from this study. The results form an additional dimension to the criteria for partitioning the ocean, required for global productivity or biophysical coupled modelling.