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A numerical reconstruction of the brightness temperature is examined as a potential way to improve the retrieval of salinity from Aquarius measurements closer to landwater boundaries. A test case using simulated ocean-land scenes suggest promise for the technique.
The development, implementation, and evaluation of a new weakly coupled ocean data assimilation (WCODA) system for the fully coupled Energy Exascale Earth System Model version 2 (E3SMv2) utilizing the four-dimensional ensemble variational (4DEnVar) method are presented in this study. The 4DEnVar method, based on the dimension-reduced projection four-dimensional variational (DRP-4DVar) approach, replaces the adjoint model with the ensemble technique, thereby reducing computational demands. Monthly mean ocean temperature and salinity data from the EN4.2.1 reanalysis are integrated into the ocean component of E3SMv2 from 1950 to 2021 with the goal of providing realistic initial conditions for decadal predictions and predictability studies. The performance of the WCODA system is assessed using various metrics, including the reduction rate of the cost function, root mean square error (RMSE) differences, correlation differences, and model biases. Results indicate that the WCODA system effectively assimilates the reanalysis data into the climate model, consistently achieving negative reduction rates of the cost function and notable improvements in RMSE and correlation across various ocean layers and regions. Significant enhancements are observed in the upper ocean layers across the majority of global ocean regions, particularly in the north Atlantic, north Pacific, and Indian Ocean. Model biases in sea surface temperature and salinity are also substantially reduced. For sea surface temperature, cold biases in the north Pacific and north Atlantic are diminished by about 1–2 °C, and warm biases in the Southern Ocean are corrected by approximately 1.5–2.5 °C. In terms of salinity, improvements are observed with bias reductions of about 0.5–1 psu in the north Atlantic and north Pacific and up to 1.5 psu in parts of the Southern Ocean. The ultimate goal of the WCODA system is to advance the predictive capabilities of E3SM for subseasonal to decadal climate predictions, thereby supporting research on strategic energy-sector policies and planning.
Marine dimethyl sulfide (DMS) is important to climate due to the ability of DMS to alter Earth's radiation budget. Knowledge of the global-scale distribution, seasonal variability, and sea-to-air flux of DMS is needed in order to improve understanding of atmospheric sulfur, aerosol/cloud dynamics, and albedo. Here we examine the use of an artificial neural network (ANN) to extrapolate available DMS measurements to the global ocean and produce a global climatology with monthly temporal resolution. A global database of 82 996 ship-based DMS measurements in surface waters was used along with a suite of environmental parameters consisting of latitude–longitude coordinates, time of day, time of year, solar radiation, mixed layer depth, sea surface temperature, salinity, nitrate, phosphate, and silicate. Linear regressions of DMS against the environmental parameters show that on a global-scale mixed layer depth and solar radiation are the strongest predictors of DMS. These parameters capture ~9 % and ~7 % of the raw DMS data variance, respectively. Multilinear regression can capture more of the raw data variance (~39 %) but strongly underestimates DMS in high-concentration regions. In contrast, the artificial neural network captures ~66 % of the raw data variance in our database. Like prior climatologies our results show a strong seasonal cycle in surface ocean DMS with the highest concentrations and sea-to-air fluxes in the high-latitude summertime oceans. We estimate a lower global sea-to-air DMS flux (20.12±0.43 Tg S yr –1 ) than the prior estimate based on a map interpolation method when the same gas transfer velocity parameterization is used. Our sensitivity test results show that DMS concentration does not change unidirectionally with each of the environmental parameters, which emphasizes the interactions among these parameters. The ANN model suggests that the flux of DMS from the ocean to the atmosphere will increase with global warming. Given that larger DMS fluxes induce greater cloud albedo, this corresponds to a negative climate feedback.
We have examined the L-band radiometer and radar data from NASA’s Soil Moisture Active Passive (SMAP) mission for ocean research and applications. We find that the SMAP data are in excellent agreement with the geophysical model function (GMF) derived from the Aquarius data up to a wind speed of 20 ms-1. For severe wind conditions, the higher resolution data from SMAP allowed us to assess the sensitivity of L-band radiometer signals to hurricane force winds. We applied the L-band GMF to the retrieval of ocean surface wind and SSS from the SMAP data. Comparison with the European Center for Medium-Range Weather Forecasting, WindSat and RapidSCAT wind speeds suggests that SMAP’s radiometer wind speed reaches an excellent accuracy of about 1.1-1.7 ms-1 below a wind speed of 20 ms-1. We have also found that the maximum wind speed derived from the SMAP radiometer data can reach 140 knots for severe storms and are generally in good agreement with the hurricane track analysis and operational aircraft Stepped Frequency Microwave Radiometer wind speeds. The spatial patterns of the SMAP SSS agree well with climatological distributions, but exhibit several unique spatial and temporal features.
Principal satellite remote sensing techniques and instruments are described and attention is given to the application of such techniques to ocean current measurement. The use of radiometers, satellite tracking drifters, and altimeters for current measurement is examined. Consideration is also given to other applications of satellite remote sensing in physical oceanography, including measurements of surface wind stress, sea state, tides, ice, sea surface temperature, salinity, ocean color, and oceanic leveling.
Requirements are defined for Earth observation microwave radiometry for the decade of the 1990's by using large space antenna (LSA) systems with apertures in the range from 50 to 200 m. General Earth observation needs, specific measurement requirements, orbit mission guidelines and constraints, and general radiometer requirements are defined. General Earth observation needs are derived from NASA's basic space science program. Specific measurands include soil moisture, sea surface temperature, salinity, water roughness, ice boundaries, and water pollutants. Measurements are required with spatial resolution from 10 to 1 km and with temporal resolution from 3 days to 1 day. The primary orbit altitude and inclination ranges are 450 to 2200 km and 60 to 98 deg, respectively. Contiguous large scale coverage of several land and ocean areas over the globe dictates large (several hundred kilometers) swaths. Radiometer measurements are made in the bandwidth range from 1 to 37 GHz, preferably with dual polarization radiometers with a minimum of 90 percent beam efficiency. Reflector surface, root mean square deviation tolerances are in the wavelength range from 1/30 to 1/100.
The presentation addresses how to infer the front side temperatures for the Aquarius L-band reflector based upon backside measurement sites. Slides discussing the mission objectives and design details are at the same level found on typical project outreach websites and in conference papers respectively. The test discussion provides modest detail of an ordinary thermal balance test using mockup hardware. The photographs show an off-Lab vacuum chamber facility with no compromising details.
The U.S. Department of Energy's Energy Exascale Earth System Model (E3SM) version 2.1 builds on E3SMv2 with several changes, with the most notable being the addition of the Fox-Kemper et al. (2011) mixed-layer eddy parameterization. This parameterization captures the effect of finite-amplitude, mixed-layer eddies as an overturning streamfunction and has the primary function of restratification. Herein, we outline the changes to the mean climate state of E3SM that were introduced by the addition of this parameterization. Overall, the presence of the submesoscale parameterization improves the fidelity of the v2.1 simulation by reducing the ocean surface biases in the North Atlantic present in v2, as illustrated by changes in the climatological sea surface temperature and salinity and the Arctic sea-ice extent. Other impacts include a slight shoaling of the mixed-layer depths in the North Atlantic and a small improvement in the Atlantic Meridional Overturning Circulation (AMOC). We note that the expected shoaling due to the parameterization is regionally dependent in our coupled configuration. In addition, we investigate why the parameterization and its impacts on mixed-layer depth have little impact on the simulated AMOC: despite increased dense-water formation in the Norwegian Sea, only a small fraction of the water formed makes its way south into the North Atlantic basin. Version 2.1 also exhibits small improvements in the atmospheric climatology, with smaller biases in many notable quantities and modes of variability.
The application of passive microwave techniques from airborne and surface platforms for oceanography measurements is discussed. The program is designed to determine: (1) the optimum system parameters, (2) measurement techniques, and (3) the physical phenomena to enable unambiguous all-weather determination of the sea surface properties of sea roughness, surface wind fields, temperature, salinity, sea ice, and pollution. The advantages and disadvantages of the airborne and fixed station operations are examined.
Sea-surface temperature with an accuracy of 1 C and salinity with an accuracy of 1% were measured with a 1.43 and 2.65 GHz radiometer system after correcting for the influence of cosmic radiation, intervening atmosphere, sea-surface roughness, and antenna beamwidth. The radiometers are a third-generation system using null-balancing and feedback noise injection. Flight measurements from aircraft over bay regions and coastal areas of the Atlantic resulted in contour maps with spatial resolution of 0.5 km.
Columbia River megafloods occurred repeatedly during the last deglaciation, but the impacts of this fresh water on Pacific hydrography are largely unknown. To reconstruct changes in ocean circulation during this period, we used a numerical model to simulate the flow trajectory of Columbia River megafloods and compiled records of sea surface temperature, paleo-salinity, and deep-water radiocarbon from marine sediment cores in the Northeast Pacific. The North Pacific sea surface cooled and freshened during the early deglacial (19.0-16.5 ka) and Younger Dryas (12.9-11.7 ka) intervals, coincident with the appearance of subsurface water masses depleted in radiocarbon relative to the sea surface. We infer that Pacific meltwater fluxes contributed to net Northern Hemisphere cooling prior to North Atlantic Heinrich Events, and again during the Younger Dryas stadial. Abrupt warming in the Northeast Pacific similarly contributed to hemispheric warming during the Bølling and Holocene transitions. These findings underscore the importance of changes in North Pacific freshwater fluxes and circulation in deglacial climate events.
A model of the thermally mixed layer in the upper ocean as developed by Kraus and Turner and extended by Denman is further extended to investigate the effects of salinity. In the tropical and subtropical Atlantic Ocean rapid increases in salinity occur at the bottom of a uniformly mixed surface layer. The most significant effects produced by the inclusion of salinity are the reduction of the deepening rate and the corresponding change in the heating characteristics of the mixed layer. If the net surface heating is positive, but small, salinity effects must be included to determine whether the mixed layer temperature will increase or decrease. Precipitation over tropical oceans leads to the development of a shallow stable layer accompanied by a decrease in the temperature and salinity at the sea surface.
The possibility of North Atlantic Deep Water (NADW) changes in both past and future climates has raised the issue of how the Southern Ocean would respond. Recent experiments with the GISS coupled atmosphere-ocean model have shown that a "bipolar see-saw" between NADW production and Antarctic Bottom Water (AABW) production in the Weddell Sea can occur in conjunction with freshening of the North Atlantic. However, this effect operates not through a slow ocean response but via a rapid atmospheric mechanism. As NADW reduces, colder temperatures in the North Atlantic, and Northern Hemisphere in general, are associated with higher surface pressure (increased atmospheric mass). Reduced mass in the Southern Hemisphere occurs in response, with lower pressure over the South Pole (an EOF #1 effect, the "high phase" of the Antarctic Oscillation).The lower pressure is associated with stronger west winds that generate an intensified Antarctic Circumpolar Current (ACC), which leads to longitudinal heat divergence in the South Atlantic (and heat convergence in the Southern Indian Ocean). Colder temperatures in the Weddell Sea region lead to sea ice growth, increased salinity and surface water density, and greater Weddell Sea Bottom Water production. Increased poleward transport of heat occurs in the South Atlantic in conjunction with increased bottom water production, but its convergence at high latitudes is not sufficient to offset the longitudinal heat divergence due to the intensified ACC. The colder temperatures at high latitudes in the South Atlantic increase the latitudinal temperature gradient, baroclinic instability, eddy energy and eddy poleward transport of momentum, helping to maintain the lower pressure over the pole in an interactive manner. The heat flux convergence in the Indian Ocean provides a warming tendency in that region, and overall global production of AABW remains unchanged. These results have implications for the interpretation of the ice core records of the last deglaciation, but may also be relevant for changes during the Holocene and perhaps even in response to increased CO2 forcing,
Anthropogenically forced changes in ocean biogeochemistry are underway and critical for the ocean carbon sink and marine habitat. Detecting such changes in ocean biogeochemistry will require quantification of the magnitude of the change (anthropogenic signal) and the natural variability inherent to the climate system (noise). Here we use Large Ensemble (LE) experiments from four Earth system models (ESMs) with multiple emissions scenarios to estimate Time of Emergence (ToE) and partition projection uncertainty for anthropogenic signals in five biogeochemically important upper-ocean variables. We find ToEs are robust across ESMs for sea surface temperature and the invasion of anthropogenic carbon; emergence time scales are 20–30 yr. For the biological carbon pump, and sea surface chlorophyll and salinity, emergence time scales are longer (50+ yr), less robust across the ESMs, and more sensitive to the forcing scenario considered. We find internal variability uncertainty, and model differences in the internal variability uncertainty, can be consequential sources of uncertainty for projecting regional changes in ocean biogeochemistry over the coming decades. In combining structural, scenario, and internal variability uncertainty, this study represents the most comprehensive characterization of biogeochemical emergence time scales and uncertainty to date. Our findings delineate critical spatial and duration requirements for marine observing systems to robustly detect anthropogenic change.
Abstract The global air‐sea CO 2 flux (F) impacts and is impacted by a plethora of climate‐related processes operating at multiple time scales. In bulk mass transfer formulations, F is driven by physico‐ and bio‐chemical factors such as the air‐sea partial pressure difference (∆pCO 2 ), gas transfer velocity, sea surface temperature, and salinity–all varying at multiple time scales. To de‐convolve the impact of these factors on variability in F at different time scales, time‐resolved estimates of F were computed using a global data set assembled between 1988 and 2015. The F anomalies were defined as temporal deviations from the 28‐year time‐averaged value. Spectral analysis revealed four dominant timescales of variability in F–subseasonal, seasonal, interannual, and decadal with relative amplitude differences varying across regions. A second‐order Taylor series expansion was then conducted along these four timescales to separate drivers across differing regions. The analysis showed that on subseasonal timescales, wind speed variability explains some 66% of the global F anomaly and is the dominant driver. On seasonal, interannual, and decadal timescales, the ∆pCO 2 effect controlled by the ∆pCO 2 anomaly, explained much of the F anomaly. On decadal timescales, the F anomaly was almost entirely governed by the ∆pCO 2 effect with large contributions from high latitudes. The main drivers across timescales also dominate the regional F anomaly, particularly in the mid‐high latitude regions. Finally, the driver of the ∆pCO 2 effect was closely connected with the relative strength of atmospheric pCO 2 and the nonthermal component of oceanic pCO 2 anomaly associated with dissolved inorganic carbon and alkalinity.
Abstract Quantifying factors that influence marine predator distributions is essential to understanding the current and future change in marine biodiversity. Here, we test whether marine predator distribution relates to prey, or is better predicted by other specific habitat features. We examine the correlation between spatial distribution of three seabird species and their prey, as well as environmental proxies (oceanographic characteristics) in the Gulf of Cadiz, NE Atlantic. We modeled the at-sea distribution of Cory's shearwater, Balearic shearwater and Northern gannet, based on: (i) pelagic fish abundance according to acoustic surveys, and (ii) a forecast-model of remotely sensed environmental variables (productivity, sea surface temperature, and salinity). In general, seabird distributions were better predicted by abundance of fish than by environmental variables at the habitat scale. We obtained consistent correlations between seabird presence and the abundance of medium-sized (10–20 cm) sardines, anchovies and Mediterranean horse mackerel, providing information on their preferred prey. Additionally, oceanographic productivity variables moderately contributed to seabird distribution models, with better predictive value for the critically endangered Balearic shearwater and Northern gannet in the summer, whilst the model for Cory's shearwater's produced poorer predictions. Predator–prey combined studies may represent essential tools for an efficient ecosystem-based management of marine environments.
A technique to remotely measure sea-surface temperature and salinity (for concentrations greater than 5 parts-per-thousand) with accuracies of 1 C and 1 part-per-thousand, respectively, was demonstrated with a two-frequency microwave radiometer system.