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Observing the development of upwelling on the northeast coast of Africa by measuring ocean surface emission with infrared radiometers on Nimbus satellites is reported. Using the temperature of the ocean as telemetered by the satellite, the biological potential of an area is estimated, and consequently the highest potential for fisheries.
One of the important objectives of the NIMBUS-7 Scanning Multichannel Microwave Radiometer (SMMR) is to demonstrate the feasibility of all weather measurements of various ocean parameters; such as sea surface temperature (SST) and near surface wind speed (WS). These ocean parameters can be determined from multispectral measurements of ocean brightness temperatures in the microwave region of the electromagnetic spectrum. These microwave measurements, however, are distorted if the field of view of the SMMR antenna encounters radio transmissions from terrestrial sources. Sources of terrestrial Radio Frequency Interference (RFI) in the SMMR ocean data were identified. Its extent and characteristics over different ocean areas on the Earth were determined.
This project was part of a previous grant at MIT that was moved over to the Scripps Institution of Oceanography (SIO) together with the principal investigator. The final report provided here is concerned only with the work performed at SIO since January 2000. The primary focus of this project was the study of the three-dimensional, absolute and time-evolving general circulation of the global ocean from a combined analysis of remotely sensed fields of sea surface temperature (SST) and sea surface height (SSH). The synthesis of those two fields was performed with other relevant physical data, and appropriate dynamical ocean models with emphasis on constraining ocean general circulation models by a combination of both SST and SSH data. The central goal of the project was to improve our understanding and modeling of the relationship between the SST and its variability to internal ocean dynamics, and the overlying atmosphere, and to explore the relative roles of air-sea fluxes and internal ocean dynamics in establishing anomalies in SST on annual and longer time scales. An understanding of those problems will feed into the general discussion on how SST anomalies vary with time and the extend to which they interact with the atmosphere.
In Central Southwest Asia (CSWA; 22°N to 40°N and 30°E to 70°E), winter (November to February) precipitation contributes up to 70% of the annual mean, but substantial interannual variations exist. Dynamical models exhibit subpar predictability in this region, but the limits of their skills are not well established. Here, we identify the tropical and extratropical forcings that explain ~75% of area-averaged seasonal variability in CSWA winter precipitation. Tropical forcing comes from the indirect El Niño-Southern Oscillation (ENSO) pathway, the leading mode of tropical Indian Ocean precipitation variability. This mode is coupled with ENSO-related Pacific Ocean sea surface temperature variability. A direct ENSO influence on CSWA does not extend beyond its Indian Ocean connection. Extratropical forcing comes from a large-scale mode of internal atmospheric variability. The spatial structure, variability of tropical forcing, and teleconnection with CSWA winter precipitation are skillfully depicted in two seasonal forecasting systems: the fifth-generation seasonal forecasting system (SEAS5) and Seamless System for Prediction and Earth System Research (SPEAR). Extratropical forcing’s spatial structure is also produced skillfully in the two modelling systems; however, the representation of its interannual variability and teleconnection requires improvement. While SEAS5 displays skill in representing extratropical forcing influence on CSWA winter precipitation and marginal skill in reproducing interannual variability, SPEAR has negligible ability in both areas. Consequently, these models have limited predictive skills over CSWA in winter. While improvements in representing extratropical forcing may be inherently limited as it arises from internal atmospheric variability, further research is needed to establish its predictability limits fully.
One of the principal roles of the ocean in the global heat balance is storage of heat, which moderates seasonal extremes and leads to the contrast between ocean and continent temperatures.
Ocean salinity and temperature differences drive thermohaline circulations. These properties also play a key role in the ocean-atmosphere coupling. With the availability of L-band space-borne observations, it becomes possible to provide global scale sea surface salinity (SSS) distribution. This study analyzes globally the along-track (Level 2) Aquarius SSS retrievals obtained using both passive and active L-band observations. Aquarius alongtrack retrieved SSS are assimilated into the ocean data assimilation component of Version 5 of the Goddard Earth Observing System (GEOS-5) assimilation and forecast model. We present a methodology to correct the large biases and errors apparent in Version 2.0 of the Aquarius SSS retrieval algorithm and map the observed Aquarius SSS retrieval into the ocean models bulk salinity in the topmost layer. The impact of the assimilation of the corrected SSS on the salinity analysis is evaluated by comparisons with insitu salinity observations from Argo. The results show a significant reduction of the global biases and RMS of observations-minus-forecast differences at in-situ locations. The most striking results are found in the tropics and southern latitudes. Our results highlight the complementary role and problems that arise during the assimilation of salinity information from in-situ (Argo) and space-borne surface (SSS) observations
The latest Geostationary Operational Environmental Satellites (GOES) have facilitated significant improvements in our ability to measure sea surface temperature (SST) from geostationary satellites. Nonetheless, difficulties associated with sensor calibration and oceanic near-surface temperature gradients affect the accuracy of the measurements and our ability to estimate and interpret the diurnal cycle of the bulk SST. Overall, measurements of SST from the GOES Imagers on the GOES 8-10 satellites are shown to have very small bias (less than 0.02 K) and rms differences of between 0.6 and 0.9 K relative to buoy observations. Separate consideration of individual measurement times, however, demonstrates systematic bias variations of over 0.6 K with measurement hour. These bias variations significantly affect both the amplitude and shape of estimates of the diurnal SST cycle. Modeled estimates of the temperature difference across the oceanic cool skin and diurnal thermocline show that bias variations up to 0.3 K can result from variability in the near-surface layer. Oceanic near-surface layer and known "satellite midnight" calibration effects, however, explain only a portion of the observed bias variations, suggesting other possible calibration concerns. Methods of explicitly incorporating skin layer and diurnal thermocline effects in satellite bulk SST measurements were explored in an effort to further improve the measurement accuracy. While the approaches contain more complete physics, they do not yet significantly improve the accuracy of bulk SST measurements due to remaining uncertainties in the temperature difference across the near-surface layer.
An oceanic data assimilation system which allows to utilize the forthcoming Tropical Rainfall Measuring Mission (TRMM) data has been developed and applied to the Pacific Ocean to produce the velocity field. The assimilated data will be indispensable to examine the effects of rainfall and its variability on the structure and circulation of the tropical oceans and to assess the impact of global warming due to the increase of carbon dioxide on the ocean circulation system and the marine pollution caused by oil spill and ocean damping of radionuclide. The data will also provide the verification for the oceanic and ocean-atmosphere coupled General Circulation Models (GCM's). The system consists of oceanic GCM, analysis scheme and data. In the system the flow field has been determined to be physically consistent with the observed density field and the sea surface winds derived from the Special Sensor Microwave Imagery (SSM/I) data which drive the ocean current. The time integration has been performed for five years until the flow field near the surface attained the steady state starting from the rest ocean with observed temperature and salinity fields, and the SSM/I surface wind velocity. The resultant flow field showed high producibility of the system. Especially the flow near the ocean surface agreed well with available observed data. The system, for the first time, succeeded to produce the eastward subtropical current which has been discovered in the joint investigation on Kuroshio current (CSK) in the 1960s. To verify the quality of the flow field a trajectory analysis has been carried out and compared with the Algos buoy data. BRIEF DESCRIPTION OF THE DATA ASSIMILATION SYSTEM ## Oceanic GCM and analysis scheme--The basic equations are much the same as used for the GCM's, except for the Newtonian damping terms introduced into the prediction equations for the potential temperature and salinity to maintain these fields as observed. The C grid of 2'lat. by 2'long. in horizontal and the 11 vertical levels are applied to the entire Pacific Ocean. At the east and west ocean boundaries the periodic boundary conditions are applied creating fictitious ocean there. The SMAC Method is used to increase the accuracy of mass conservation. * Data--The JODC temperature and salinity data obtained from 1906 to 1988 are used in the system between Long.100'E. and 60'W. The surface wind data are derived from the SSM/I data by Dr-R. Atlas of NASA/GSFC. The data set contains every 6 hours data from July 1987 to June 1989 on the grid of 2'lat. by 2.5'long. The averaged for the whole period and then interpolated into the 2'lat. by 2'long. grid data are used to force the system. The sea bottom topography data was based on the General Bathymetric Chart of the Ocean (GEBCO) supplied by the Canadian Hydrographic Service under contract with the International Hydrographic Organization and International Oceanographic Commission of UNESCO.
The third Stokes parameter of ocean surface brightness temperatures measured by the WindSat instrument is sensitive to the rotation angle between the polarization vectors at the ocean surface and the instrument. This rotation angle depends on the spacecraft attitude (roll, pitch, yaw) as well as the Faraday rotation of the electromagnetic radiation passing through the Earth's ionosphere. Analyzing the WindSat antenna temperatures, we find biases in the third Stokes parameter as function of the along-scan position of up to 1.5 K in all feedhorns. This points to a misspecification of the reported spacecraft attitude. A single attitude correction of -0.16deg roll and 0.18deg pitch for the whole instrument eliminates all the biases. We also study the effect of Faraday rotation at 10.7 GHz on the accuracy of the third Stokes parameter and the sea surface wind direction retrieval and demonstrate how this error can be corrected using values from the International Reference Ionosphere for the total electron content when computing Faraday rotation.
Microwave brightness temperature data from the Nimbus 5 satellite are analyzed, using threshold brightness temperatures, to yield tropical oceanic precipitation frequencies for several classes of rainfall rates during the season December 1972 through February 1973. Data taken near local noon and near local midnight are analyzed. The overall results are consistent with both climatological precipitation frequency and with concurrent satellite-derived frequency of highly reflective clouds. The difference between the local noon and local midnight frequencies is small, but the heavier rainfall rates tend to occur more frequently near local noon. The ratios of the frequencies of light, moderate, and heavy rain were observed to be relatively constant over the tropical oceans. Passive microwave measurements from space seem to be an important step toward accurate measurement of oceanic precipitation.
Microwave brightness temperature data from the Nimbus 5 satellite have been analyzed by using threshold brightness temperatures to yield tropical oceanic precipitation frequencies for several classes of rainfall rates during the season December 1972 through February 1973. Data taken near local noon and near local midnight were analyzed. The overall results are consistent with both climatological precipitation frequency and with concurrent satellite-derived frequency of highly reflective clouds. The difference between the local noon and the local midnight frequency is small, but the heavier rainfall rates tend to occur more frequently near local noon. The ratios of the frequencies of light, moderate, and heavy rain were observed to be relatively constant over the tropical oceans. Passive microwave measurements from space seem to be an important step toward accurate measurement of oceanic precipitation.
During the past few years the Goddard Earth Observing System (GEOS) and Massachusetts Institute of Technology (MIT) modeling groups have produced, respectively, global atmosphere-only and ocean-only simulations with km-scale grid spacing. These simulations have proved invaluable for process studies and for the development of satellite and in-situ sampling strategies. Nevertheless, a key limitation of these "nature" simulations is the lack of interaction between the ocean and the atmosphere, which limits their usefulness for studying air-sea interactions and for designing observing missions to study these interactions. To remove this limitation, we aim to perform a coupled simulation using the km-scale GEOS atmosphere and the km-scale MIT ocean models. The initial attempt at the km-scale coupled simulation resulted in computational issues which will be presented here. As a preliminary step towards the km-scale objective, we present results from a high resolution but not yet km-scale simulation, wherein we have coupled a cubed-sphere-720 (~ 1/8) configuration of the GEOS atmosphere to a lat-lon-cap-1080 (~ 1/12) configuration of the MIT ocean. We compare near-surface diagnostics of this fully coupled ocean-atmosphere set-up to equivalent atmosphere-only and ocean-only simulations. A particular focus of the comparisons is the differences in interactions between Sea Surface Temperature (SST) and ocean surface wind for the coupled and uncoupled simulations. We discuss observed and modeled high temporal variability (~days) SST-wind cycle and how it is represented in the different systems. A mechanism for the cycle, which is driven by SST-wind feedback, is proposed.
The National Oceanic and Atmospheric Administration (NOAA) began processing global measurements of emitted radiation in the 10.5 to 12.5 micron atmospheric window for purposes of deriving weekly composite and mean monthly sea surface temperature fields in the early 1970s. Atmospheric attenuation corrections, begun with empirical means, were accomplished chiefly with the aid of coarser resolution measurements from atmospheric sounders aboard the same polar orbiting spacecraft. Cloud filtering depended heavily upon the use of histogram techniques applied to 11 x 11 arrays of 8 km resolution Scanning Radiometer Infrared (SRIR) data. Details of the SRIR processing for SST are found in a NOAA Technical Memorandum.
A proposed system would exploit the ocean thermal gradient for recharging the batteries in a battery-powered unmanned underwater vehicle [UUV (essentially, a small exploratory submarine robot)] of a type that has been deployed in large numbers in research pertaining to global warming. A UUV of this type travels between the ocean surface and depths, measuring temperature and salinity. The proposed system is related to, but not the same as, previously reported ocean thermal energy conversion (OTEC) systems that exploit the ocean thermal gradient but consist of stationary apparatuses that span large depth ranges. The system would include a turbine driven by working fluid subjected to a thermodynamic cycle. CO2 has been provisionally chosen as the working fluid because it has the requisite physical properties for use in the range of temperatures expected to be encountered in operation, is not flammable, and is much less toxic than are many other commercially available refrigerant fluids. The system would be housed in a pressurized central compartment in a UUV equipped with a double hull (see figure). The thermodynamic cycle would begin when the UUV was at maximum depth, where some of the CO2 would condense and be stored, at relatively low temperature and pressure, in the annular volume between the inner and outer hulls. The cycle would resume once the UUV had ascended to near the surface, where the ocean temperature is typically greater than or equals 20 C. At this temperature, the CO2 previously stored at depth in the annular volume between the inner and outer hulls would be pressurized to approx. equals 57 bar (5.7 MPa). The pressurized gaseous CO2 would flow through a check valve into a bladder inside the pressurized compartment, thereby storing energy of the relatively warm, pressurized CO2 for subsequent use after the next descent to maximum depth.
The results of two regional atmospheric model simulations are compared to assess the influence of the eastern tropical Atlantic sea-surface temperature maximum on local precipitation, transient easterly waves and the West African summer monsoon. Both model simulations were initialized with reanalysis 2 data (US National Center for Environmental Prediction and Department of Energy) on 15 May 2006 and extended through 6 October 2006, forced by synchronous reanalysis 2 lateral boundary conditions introduced four times daily. One simulation uses 2006 reanalysis 2 sea-surface temperatures, also updated four times daily, while the second simulation considers ocean forcing absent the sea-surface temperature maximum, achieved here by subtracting 3 K at every ocean grid point between 0 and 15 N during the entire simulation. The simulation with 2006 sea-surface temperature forcing produces a realistic distribution of June-September mean precipitation and realistic westward propagating swaths of maximum rainfall, based on validation against Tropical Rainfall Measuring Mission (TRMM) estimates. The simulation without the sea-surface temperature maximum produces only 57% of the control June-September total precipitation over the eastern tropical Atlantic and about 83% of the Sahel precipitation. The simulation with warmer ocean temperatures generates generally stronger circulation, which in turn enhances precipitation by increasing moisture convergence. Some local precipitation enhancement is also attributed to lower vertical thermal stability above the warm water. The study shows that the eastern tropical Atlantic sea-surface temperature maximum enhances the strength of transient easterly waves and broadens the spatial extent of associated precipitation. However, large-scale circulation and its interaction with the African continent, and not sea-surface temperatures, control the timing and trajectories of the waves.
Understanding recent large-scale drought patterns and the mechanisms producing extreme drought events is vital for future drought forecasts and understanding future drought risks. Increasingly, vapor pressure deficit (VPD) has been used as an important measure of evaporative demand and proxy for drought detection. In this study, VPD is used to calculate the new Standardized VPD Drought Index (SVDI) with NASA North American Land Data Assimilation System (NLDAS) data. Previous studies have shown that SVDI accurately identifies the timing and magnitude short-term droughts in the United States (U.S). In the present study, SVDI is now used to identify large-scale drought patterns between 1980 and 2021 and drought variability driven by selected global teleconnections originating in the Pacific and Atlantic Oceans. Spatial drought characteristics were extracted from SVDI using empirical orthogonal function (EOF) analysis. Then a k-means clustering algorithm was applied to both EOF principal components and primary teleconnections, including the El Nino-Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO) to identify drought events driven by the Pacific Ocean. Results show that the SVDI is useful in evaluating large-scale drought variability in the U.S. related to global teleconnections, and that mechanisms influencing summer drought patterns in the Western and Southwestern U.S. are driven by a tropical-extratropical interactions originating in the equatorial Pacific Ocean related to ENSO dynamics with interdecadal variability modulated by PDO. The large-scale droughts in the Central and Southern U.S., like those in 2011 and 2012, on the other hand, are driven by the North Pacific Ocean warm pool during a strong negative PDO, which subsequently influenced variability in the Bermuda-Azores High in the Atlantic Ocean. In summer 2011, the Bermuda-Azores High weakened, reducing the onshore winds and moisture transport along the eastern Gulf of Mexico and contributing to ongoing drought in the region. The Northern Pacific and Atlantic Ocean sea surface temperatures (SSTs) have increased between 1980 and 2021. In conclusion, as SSTs continue to rise in the Northern Pacific Ocean, one consequence of the coupled North Pacific warm pool and atmospheric dynamics, is to increase summer drought variability over a large region in the southern and midwestern U.S. under global warming.
During the past few years the Goddard Earth Observing System (GEOS) and Massachusetts Institute of Technology (MIT) modeling groups have produced, respectively, global atmosphere-only and ocean-only simulations with km-scale grid spacing. These simulations have proved invaluable for process studies and for the development of satellite and in-situ sampling strategies. Nevertheless, a key limitation of these "nature" simulations is the lack of interaction between the ocean and the atmosphere, which limits their usefulness for studying air-sea interactions and for designing observing missions to study these interactions. We present here results from a coupled GEOS-MIT "nature run" simulation, wherein we have coupled a cubed-sphere-720 (~ 1/8) configuration of the GEOS atmosphere to a lat-lon-cap-1080 (~ 1/12) configuration of the MIT ocean. We compare near-surface diagnostics of this fully coupled ocean-atmosphere simulation to equivalent atmosphere-only and ocean-only simulations. A particular focus of the comparisons is the coupled versus uncoupled differences in interactions between Sea Surface Temperature (SST) and ocean surface wind. We discuss, in particular, a several-day mode of temporal variability in the SST-wind cycle and how it is represented in the different model simulations and in observationally-based products. A mechanism for the cycle, which is driven by SST-wind feedback, is proposed.
Reanalyses in the Arctic are widely used for model evaluation and for understanding contemporary climate change. Nevertheless, differences among reanalyses in fundamental meteorological variables including surface air temperature are large. For example, the 1980-2009 mean surface air temperature for the north polar cap (70ÂdegN-90ÂdegN) among global reanalyses span a range of 2.4 K, which approximates the average warming trend from these reanalyses over the 30-year period of 2.1 K. Understanding these differences requires evaluation over the three principal surface domains of the Arctic: glaciated land, the unglaciated terrestrial surface, and sea ice/ocean. An examination is conducted of contemporary global reanalyses of the ECMWF Interim project, NASA MERRA, MERRA-2, JRA-55, and NOAA CFSR using available in situ data and assessments of the surface energy budget. Overly-simplistic representations of the Greenland Ice Sheet surface are found to be associated with local warm air temperature biases in winter. A review of progress made in the development of the MERRA-2 land-ice representation is presented. Large uncertainty is also found in temperatures over the Arctic tundra and boreal forest zone. But a key focus of temperature differences for northern high latitudes is the Arctic Ocean. Near-surface air temperature differences over the Arctic Ocean are found to be related to discrepancies in sea ice and sea surface temperature boundary data, which are severely compromised in current reanalyses. Issues with the modeled representation of sea ice cover are an additional factor in reanalysis temperature trends. Differences in the representation of the surface energy budget among the various reanalyses are also reviewed.