New diagnostic sea surface current fields to trace floating algae in the Yellow Sea
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The 1997/98 is a strong El Nino warm event, while the 1998/99 is a moderate La Nina cold event. We have investigated surface heat budgets and sea surface temperature (SST) tendency for these two events in the tropical western Pacific and eastern Indian Oceans using satellite-retrieved surface radiative and turbulent fluxes. The radiative fluxes are taken from the Goddard Satellite-retrieved Surface Radiation Budget (GSSRB), derived from radiance measurements of the Japanese Geostationary Meteorological Satellite 5. The GSSRB covers the domain 40 deg S - 4 deg N, 90 deg E-17 deg W and a period from October 1997 to December 2000. The spatial resolution is 0.5 deg x 0.5 deg lat-long and the temporal resolution is 1 day. The turbulent fluxes are taken from Version 2 of the Goddard Satellite-based Surface Turbulent Fluxes (GSSTF-2). The GSSTF-2 has a spatial resolution of 1 deg x 1 deg lat-long over global Oceans and a temporal resolution of 1 day covering the period July 1987-December 2000. Daily turbulent fluxes are derived from the S S M (Special Sensor Microwave/Imager) surface wind and surface air humidity, and the SST and 2-m air temperature of the NCEP/NCAR reanalysis, using a stability-dependent bulk flux algorithm. The changes of surface heat budgets, SST and tendency, cloudiness, wind speed, and zonal wind stress of the 1997/98 El Nino relative to the1998/99 La Nina for the northern winter and spring seasons are analyzed. The relative changes of surface heat budgets and SST tendency of the two events are quite different between the tropical eastern Indian and western Pacific Oceans. For the tropical western Pacific, reduced solar heating (more clouds) is generally associated with decreased evaporative cooling (weaker winds), and vise versa. The changes in evaporative cooling over-compensate that of solar heating and dominate the spatial variability of the changes in net surface heating. Both solar heating and evaporative cooling offset each other to reduce interannual variability of net surface heating. In addition, the area of increased SST tendency is larger than that of increased net surface heating, due to less solar radiation penetration through the bottom of deeper ocean mixed layer (stronger winds). For the tropical eastern Indian Ocean, enhanced solar heating (less clouds) is generally associated with reduced evaporative cooling (weaker winds). Both solar heating and evaporative cooling reinforce each other to increase interannual variability of net surface heating. In addition, the area of increased SST tendency is smaller than that of increased net surface heating in the southern domain. The relative changes in wind and zonal wind stress indicate more solar radiation penetration through the ocean mixed layer and more northward heat transport by Ocean current from the south to the north Indian Ocean for the El Nino than for the La Nina.
Sea surface turbulent heat flux is one of the key components in global freshwater and energy balances and plays an important role in atmospheric dynamics, thermodynamics and general circulation. This turbulent heat flux is dominantly decided by sea surface latent heat release with some contribution from sensible heat exchange. The flux and its anomaly could significantly affect ocean heat storage and ocean circulation. They are part of and have great impacts on climate variability. Though the turbulent heat flux is extremely important for the climate and weather systems, only very limited ship and buoy observations of the flux are available over open oceans. There are no global, operational, direct measurements of this crucial meteorological variable. Global estimates are, basically, indirectly calculated from bulk turbulent flux parameterization with a combination of satellite column water vapor, sea surface water temperature, and wind speed observations. Critical parameters such as sea surface air temperature and humidity are estimated from empirical relations of theses variables with the water vapor and sea surface water temperature, respectively. Lacking accurate knowledge on surface air temperature and humidity, uncertainties in the parameterization and potential changes in the non-linear turbulent processes with long-term climate variations could cause large errors in estimated long-term turbulent fluxes from the indirect method as shown in current global sea surface turbulent flux datasets. This study uses synergized data of satellite global radiation, precipitation, and other meteorological variable observations to estimate sea surface turbulent heat fluxes. The radiation observations are made by the satellite Clouds and the Earth’s Radiant Energy System (CERES) sensors, while the global precipitation data is from NASA’s satellite Global Precipitation Climatology Project (GPCP). Other data includes satellite sea surface water temperature and wind speed observations. These datasets are obtained from a wide range of space sensors from passive to active instruments and from visible and near infrared to thermal infrared and microwave spectral sounders. One significant feature of these datasets is that they have multi-decades long climate records. Top-of-atmosphere (TOA) radiation and its anomaly represents the net heat energy input to the climate system, and the oceanic precipitation and ocean-land moisture transport can be used to quantify sea surface latent heat release. Based on the synergized datasets and the principle of global water and energy balances, global mean turbulent heat fluxes are estimated. The turbulent heat anomalies for the first two decades of the 21st century are, then, obtained mainly from global CERES radiation and GPCP precipitation anomalies, along with CERES derived ocean-land heat transports. Analysis indicates that the uncertainties in the estimated turbulent flux anomalies may be reduced considerably. The results suggest a strong needs in synchronized and synergized observations of atmospheric radiation, precipitation, and oceanic meteorological variables for long-term climate studies.
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As part of the verification phase of the TOPEX/POSEIDON mission, 10-day gridded fields of altimeter data derived from TOPEX geophysical data records are compared with 10-day gridded fields of dynamic height derived from more than 60 moorings of the Tropical Ocean and Global Atmosphere-Tropical Atmosphere Ocean (TOGA-TAO) array in the equatorial Pacific Ocean. Access to TAO data in real time permits the first 500 days of the TOPEX/POSEIDON mission to be placed in the context of complementary, in-situ measurements of surface winds, sea surface temperatures, and upper ocean thermal structure, as well as the time history of these variables prior to launch. Analysis of the space-time structure in the TOPEX and TAO surface topography data increases sea level variability primarily due to equatorial Kelvin wave activity generated by intense wind bursts west of the date line in association with the 1991-1993 El Nino. Cross correlations between the two data sets are generally greater than 0.7, with root mean square (RMS) differences less than 4 cm. However, for reasons not fully understood, correlations drop to less than 0.5 in certain regions off the equator in the eastern Pacific and RMS differences can be greater than 5 cm north of the equator in the central and eastern Pacific.
Biomass burning (BB) aerosols exert a strong surface cooling effect over the southeast Atlantic (SEA) via aerosol-radiation and aerosol-cloud interactions. The reduction of the sea surface temperature (SST) can trigger the SST-low cloud feedback. Whether this feedback can amplify the surface cooling effect is examined. The modeling results from the Community Earth System Model version 2 (CESM2) demonstrate that counterintuitively the cloud radiative effect (CRE) caused by the BB aerosols is weaker if SST-low cloud feedback is considered compared to fixed-SST simulation (-2.99 W m -2 vs. -4.79 W m -2 ). This is caused by (a) stronger sea breeze due to larger sea-land temperature contrast causing less smoke transport over SEA and (b) less moisture supply from surface due to colder SST. Changes in SST also lead to counterclockwise rotation of ocean circulation anomalies. Consequently, the excess heat transport from the equator reverses the direction of SST-cloud feedback in this region.
Sea surface salinity is a key parameter for the study of ocean circulation, global water cycle and hence climate changes.
Sea surface brightness temperatures are the radiometric power measure of blackbody radiation from sea water. This radiation is the electromagnetic waves excited by the random thermal motion of charged particles in the sea water. The energy transmitted through the air- water interface produces a scattering of electromagnetic waves into the atmosphere. Polarimetric microwave emissions are investigated.
Sea surface temperature (SST) studies are often focused on improving accuracy, or understanding and quantifying uncertainties in the measurement, as SST is a leading indicator of climate change and represents the longest time series of any ocean variable observed from space. Over the past several decades SST has been studied with the use of satellite data. This allows a larger area to be studied with much more frequent measurements being taken than direct measurements collected aboard ship or buoys. The Group for High Resolution Sea Surface Temperature (GHRSST) is an international project that distributes satellite derived sea surface temperatures (SST) data from multiple platforms and sensors. The goal of the project is to distribute these SSTs for operational uses such as ocean model assimilation and decision support applications, as well as support fundamental SST research and climate studies. Examples of near real time applications include hurricane and fisheries studies and numerical weather forecasting. The JPL group has produced a new 1 km daily global Level 4 SST product, the Multiscale Ultrahigh Resolution (MUR), that blends SST data from 3 distinct NASA radiometers: the Moderate Resolution Imaging Spectroradiometer (MODIS), the Advanced Very High Resolution Radiometer (AVHRR), and the Advanced Microwave Scanning Radiometer ? Earth Observing System(AMSRE). This new product requires further validation and accuracy assessment, especially in coastal regions.We examined the accuracy of the new MUR SST product by comparing the high resolution version and a lower resolution version that has been smoothed to 19 km (but still gridded to 1 km). Both versions were compared to the same data set of in situ buoy temperature measurements with a focus on study regions of the oceans surrounding North and Central America as well as two smaller regions around the Gulf Stream and California coast. Ocean fronts exhibit high temperature gradients (Roden, 1976), and thus satellite data of SST can be used in the detection of these fronts. In this case, accuracy is less of a concern because the primary focus is on the spatial derivative of SST. We calculated the gradients for both versions of the MUR data set and did statistical comparisons focusing on the same regions.
Sea surface temperatures (SSTs) mapped by IR satellite images and in situ hydrographic measurements off the west coast of British Columbia for early-winter and midsummer periods were correlated with in situ measurements of surface chlorophyll and zooplankton concentration. Correlations between winter log(e) transformed zooplankton concentrations and SSTs demonstrated that IR satellite imagery could explain 49 percent of the sampled zooplankton concentration variance. A least-squares-fit nonlinear equation showed that satellite-measured SST patterns explained 72 percent of the log(e) transformed chlorophyll variance. However, summer zooplankton concentrations were not consistently related to satellite temperature patterns.
The Arctic is one of the most important regions in the world’s oceans for understanding the impacts of a changing climate. Yet, it is also difficult to measure because of extreme weather and ice conditions. In this work, we directly compare four datasets from the Group for High-Resolution Sea Surface Temperature (GHRSST) with a NASA Saildrone deployment along the Alaskan Coast and the Bering Sea and Bering Strait. The four datasets used are the Remote Sensing Systems Microwave Infrared Optimally Interpolated (MWIR) product, the Canadian Meteorological Center (CMC) product, the Daily Optimally Interpolated Product (DOISST), and the Operational Sea Surface Temperature and Ice Analysis (OSTIA) product. Spatial sea surface temperature (SST) gradients were derived for both the Saildrone deployment and GHRSST products, with the GHRSST products collocated with the Saildrone deployment. Overall, statistics indicate that the OSTIA product had a correlation of 0.79 and a root mean square difference of 0.11 °C/km when compared with Saildrone. CMC had the highest correlation of 0.81. Scatter plots indicate that OSTIA had the slope closest to one, thus best reproducing the magnitudes of the Saildrone gradients. Differences increased at latitudes > 65°N where sea ice would have a greater impact. A trend analysis was then performed on the gradient fields. Overall, positive trends in gradients occurred in areas along the coastal regions. A negative trend occurred at approximately 60°N. A major finding of this study is that future work needs to revolve around the impact of changing ice conditions on SST gradients. Another major finding is that a northward shift in the southern ice edge occurred after 2010 with a maxima at approximately 2019. This indicates that the shift of the southern ice edge is not gradual but has dramatically increased over the last decade. Future work needs to revolve around examining the possible causes for this northward shift.
Sea surface salinity is measured optimally at the long wavelength end of the microwave spectrum in order to maximize radiometric sensitivity to changes in salinity. Long wavelengths (e.g. L-band) mean large antennas in space, and because of the technological challenge associated with putting large scanning antennas in orbit, no system currently exists to measure salinity. Aperture synthesis is an interferometric technique to make deployment of large antenna apertures in space feasible. It uses pairs of small antennas and signal processing to achieve the resolution of a single large aperture. Aperture synthesis has been demonstrated successfully for remote sensing by the aircraft prototype radiometer, ESTAR. ESTAR is an L-band instrument which employs aperture synthesis in the cross track dimension. Recent measurements with ESTAR of the fresh water outflow from the Delaware River are in good agreement (about 1 psu) with shipboard thermosalinograph measurements. Synthetic aperture radiometers are currently being developed for remote sensing from space. HYDROSTAR is an instrument for remote sensing from space based on the design of ESTAR. It employs aperture synthesis in one dimension and is being proposed as a pathfinder instrument to make global maps of soil moisture and sea surface salinity and to demonstrate the feasibility of aperture synthesis for remote sensing from space. Instruments which use remote sensing in two dimensions are currently being developed by the European Space Agency. These instruments include additional channels (frequencies and polarizations) and may be able to achieve radiometric sensitivity and spatial resolution to meet the diverse needs of the coastal zone and open ocean oceanographic communities.
Two ongoing space missions share the scientific objective of mapping the global Sea Surface Salinity (SSS), yet their observations show significant discrepancies. ESA's Soil Moisture and Ocean Salinity (SMOS) and NASA's Aquarius use L-band (1.4 GHz) radiometers to measure emission from the sea surface and retrieve SSS. Significant differences in SSS retrieved by both sensors are observed, with SMOS SSS being generally lower than Aquarius SSS, except for very cold waters where SMOS SSS is the highest overall. Figure 1 is an example of the difference between the SSS retrieved by SMOS and Aquarius averaged over one month and 1 degree in longitude and latitude. Differences are mostly between -1 psu and +1 psu (psu, practical salinity unit), with a significant regional and latitudinal dependence. We investigate the impact of the vicarious calibration and retrieval algorithm used by both mission on these differences.
Active and passive microwave remote sensing techniques have been investigated for the remote sensing of ocean surface wind and salinity. We revised an ocean surface spectrum using the CMOD-5 geophysical model function (GMF) for the European Remote Sensing (ERS) C-band scatterometer and the Ku-band GMF for the NASA SeaWinds scatterometer. The predictions of microwave brightness temperatures from this model agree well with satellite, aircraft and tower-based microwave radiometer data. This suggests that the impact of surface roughness on microwave brightness temperatures and radar scattering coefficients of sea surfaces can be consistently characterized by a roughness spectrum, providing physical basis for using combined active and passive remote sensing techniques for ocean surface wind and salinity remote sensing.
During the lifetime of the Coastal Zone Color Scanner, there were 21 instances in which both satellite-derived ocean color and sea-surface temperature are simultaneously available over large areas of the Sargasso Sea. These images reveal close correspondence between mesoscale structures observed in temperature and pigment fields. In general, higher (lower) pigment biomass occurs in mesoscale features consisting of cold (warm) temperature anomalies. This relationship is consistent with the idea that upward displacement of isopycnals at the base of the euphotic zone by mesoscale eddies is an important mechanism of nutrient supply in the region.