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NASA NTRS2007

Salinity Remote Sensing and the Study of the Global Water Cycle

The SMOS and AquariusISAC-D satellite missions will begin a new era to map the global sea surface salinity (SSS) field and its variability from space within the next twothree years. They will provide critical data needed to study the interactions between the ocean circulation, global water cycle and climate. Key scientific issues to address are (1) mapping large expanses of the ocean where conventional SSS data do not yet exist, (2) understanding the seasonal and interannual SSS variations and the link to precipitation, evaporation and sea-ice patterns, (3) links between SSS and variations in the oceanic overturning circulation, (4) air-sea coupling processes in the tropics that influence El Nino, and (4) closing the marine freshwater budget. There is a growing body of oceanographic evidence in the form of salinity trends that portend significant changes in the hydrologic cycle. Over the past several decades, highlatitude oceans have become fresher while the subtropical oceans have become saltier. This change is slowly spreading into the subsurface ocean layers and may be affecting the strength of the ocean's therrnohaline overturning circulation. Salinity is directly linked to the ocean dynamics through the density distribution, and provides an important signature of the global water cycle. The distribution and variation of oceanic salinity is therefore attracting increasing scientific attention due to the relationship to the global water cycle and its influence on circulation, mixing, and climate processes. The oceans dominate the water cycle by providing 86% of global surface evaporation (E) and receiving 78% of global precipitation (P). Regional differences in E-P, land runoff, and the melting or freezing of ice affect the salinity of surface water. Direct observations of E-P over the ocean have large uncertainty, with discrepancies between the various state-of-the-art precipitation analyses of a factor of two or more in many regions. Quantifying the climatic influence of the oceanic water cycle requires more accurately resolving the net air-sea water flux. Measuring global SSS trends on seasonal to interannual timescales by satellite is fundamental to this problem because the SSS trends represent detectable time-integrated signals of the variable marine hydrological cycle. Satellite measurements, coupled with an array of in situ observations, will provide global synoptic SSS fields for the first time history. These data will provide a strong constraint on climate models and data assimilation efforts, which must properly represent the freshwater budget in terms of E-P, ocean advection and surface layer mixing in order to accurately simulate the true ocean state. The SSS fields will allow us to quantify the covariability between the SSS and the strong seasonal E-P cycle in the tropics and high latitudes. Field measurement campaigns to exploit satellite and in situ measurements to close the seasonal E-P cycle over an ocean region are being considered. Lastly the satellite systems will monitor and trace the large long-lived SSS anomalies from year to year that have the potential to influence El Nino and the large scale ocean circulation.

Lagerloef, G. S. E.↗
NASA NTRS2001

The Aquarius Mission: Sea Surface Salinity from Space

Aquarius is a new satellite mission concept to study the impact of the global water cycle on the ocean, including the response of the ocean to buoyancy forcing and the subsequent feedback of the ocean on the climate. The measurement objective of Aquarius is sea surface salinity, which reflects the concentration of freshwater at the ocean surface. Salinity affects the dielectric constant of sea water and, consequently, the radiometric emission of the sea surface to space. Rudimentary space observations with an L-band radiometer were first made from Skylab in the mid-70s and numerous aircraft missions of increasing quality and improved technology have been conducted since then. Technology is now available to carry out a global mission, which includes both an accurate L band (1.413 Ghz) radiometer and radar system in space and a global array of in situ observations for calibration and validation, in order to address key NASA Earth Science Enterprise questions about the global cycling of water and the response of the ocean circulation to climate change. The key scientific objectives of Aquarius examine the cycling of water at the ocean's surface, the response of the ocean circulation to buoyancy forcing, and the impact of buoyancy forcing on the ocean's thermal feedback to the climate. Global surface salinity will also improve our ability to model the surface solubility chemistry needed to estimate the air-sea exchange of CO2. In order to meet these science objectives, the NASA Salinity Sea Ice Working Group over the past three years has concluded that the mission measurement goals should be better than 0.2 practical salinity units (psu) accuracy, 100 km resolution, and weekly to revisits. The Aquarius mission proposes to meet these measurement requirements through a real aperture dual-polarized L band radiometer and radar system. This system can achieve the less than 0.1 K radiometric temperature measurement accuracy that is required. A 3 m antenna at approx. 600km altitude in a sun-synchronous orbit and 300 km swath can provide the desired 100 km resolution global coverage every week. Within this decade, it may be possible to combine satellite sea surface salinity measurements with ongoing satellite observations of temperature, surface height, air-sea fluxes; vertical profiles of temperature and salinity from the Argo program; and modern ocean/atmosphere modeling and data assimilation tools, in order to finally address the complex influence of buoyancy on the ocean circulation and climate.

Koblinsky, Chester↗
NASA NTRS2004

NASA GEOS-3/TRMM Re-analysis: Capturing Observed Tropical Rainfall Variability in Global Analysis for Climate Research

Understanding climate variability over a wide range of space-time scales requires a comprehensive description of the earth system. Global analyses produced by a fixed assimilation system (i.e., re-analyses) - as their quality continues to improve - have the potential of providing a vital tool for meeting this challenge. But at the present time, the usefulness of re-analyses is limited by uncertainties in such basic fields as clouds, precipitation, and evaporation - especially in the tropics, where observations are relatively sparse. Analyses of the tropics have long been shown to be sensitive to. the treatment of cloud precipitation processes, which remains a major source of uncertainty in current models. Yet, for many climate studies it is crucial that analyses can accurately reproduce the observed rainfall intensity and variability since a small error of 1 mm/d in surface rain translates into an error of approx. 30 W/sq m in energy (latent heat) flux. Currently, discrepancies between the observed and analyzed monthly-mean rain rates averaged to 100 km x 100 km resolution can exceed 4 mm/d (or 120 W/sq m ), compared to uncertainties in surface radiative fluxes of approx. 10-20 W/sq m . Improving precipitation in analyses would reduce a major source of uncertainty in the global energy budget. Uncertainties in tropical precipitation have also been a major impediment in understanding how the tropics interact with other regions, including the remote response to El Nino/Southern Oscillation (ENSO) variability on interannual time scales, the influence of Madden-Julian Oscillation (MJO) and monsoons on intraseasonal time scales. A global analysis that can replicate the observed precipitation variability together with physically consistent estimates of other atmospheric variables provides the key to breaking this roadblock. NASA Goddard Space Flight Center has been exploring the use of satellite-based microwave rainfall measurements in improving global analyses and has recently produced a multi-year, 1 x 1 TRMM re-analysis , which assimilates 6-hourly TMI and SSM/I surface rain rates over tropical oceans using a ID variational continuous assimilation (VCA) procedure in the GEOS-3 global data assimilation system. The analysis period extends from 1 November 1997 through 3 1 December 2002. The goal is to produce a multi-year global analysis that is dynamically consistent with available tropical precipitation observations for the community to assess its utility in climate applications and identify areas for further improvements. A distinct feature of the GEOS-3RRMh4 re-analysis is that its precipitation analysis is not derived from a short-term forecast (as done in most operational systems) but is given by a time- continuous model integration constrained by precipitation observations within a 6-h analysis window, while the wind, temperature, and pressure fields are allowed to directly respond to the improved precipitation and associated latent heating structures within the same analysis window. In this talk, I will assess the impact VCA precipitation assimilation on analyses of climate signals ranging from a few weeks to interannual time scales and compare results against other operational and reanalysis products.

Hou, Arthur Y.↗
NASA NTRS1978

Advanced marine information delivery

The paper examines the information delivery challenges of the follow-on programs to Seasat-1 as they may progress through the next decade. These challenges include coping with the vast amounts of data to be transferred, fulfilling the temporal requirements on data delivery, and the tradeoffs and developments needed to accomplish the various levels of processing required to convert sensor output into useful information. A need for critical development is clearly identifiable in the areas of (1) low cost ground terminals capable of image extraction and image correlation; (2) dynamic data assimilation to accommodate forecasters; (3) low resolution onboard correlators; and (4) low cost user advisory (display) terminals. The system planners for the Ocean Satellite advanced programs are using an end-to-end data systems approach in meeting these challenges.

Durstenfeld, R.↗
NASA NTRS2021

Sensitivity of Low Tropospheric Arctic Temperatures to Assimilation of AIRS Cloud-Cleared Radiances: Impact on Mid-Latitude Waves

In this work, it is shown that the prediction of individual mid-latitude waves in a global forecast framework is sensitive to the initialization over the Arctic and may benefit from the assimilation of cloud-cleared radiances (CCRs) from the Atmospheric Infrared Sounder (AIRS), particularly in partially cloudy regions with active dynamics. This study shows that the assimilation of AIRS CCRs over the Arctic Ocean, providing more information than clear-sky radiances from areas affected by broken low-level stratus clouds, produces slightly cooler low-level temperatures and lower mid-tropospheric height through hydrostatic adjustment. In areas that are data void, as observed by clear-sky radiances, and dynamically active, the assimilation of CCRs provides valuable information that can improve the representation of individual baroclinic waves and their subsequent forecasts. The modifications induced by the assimilation of AIRS CCRs over the Arctic Ocean slightly modifies the geopotential height gradients between the Arctic and the mid-latitudes, leading to potential improvements in the forecast of individual baroclinic waves as is shown through a case study. The observing system experiment (OSE) is performed with the NASA Goddard Earth Observing System (GEOS) data assimilation and forecast system during boreal autumn 2014. AIRS CCRs are thinned to approximately one quarter the density of operationally assimilated AIRS radiances, consistent with their higher information content. Global, 6-hourly analyses are produced from 1 September to 10 November 2014 and 7-day forecasts are initialized at 0000 UTC daily. Since the CCR methodology is widely applicable, these findings are also relevant to other infrared sensors.

Cloud-clearing↗
NASA NTRS1999

The Special Sensor Microwave Imager Wind Dataset: A Source of Quantitative Information for the Ocean-to-Land Advection

It is well recognized that advection from the North Atlantic has a profound effect on the climatic conditions in central Europe. A new dataset of the ocean-surface winds, derived from the Special Sensor Microwave Imager, SSM/1, is now available. This satellite instrument measures the wind speed, but not the direction. However, variational analysis developed at the Data Assimilation Office, NASA Goddard Space Flight Center, by combining the SSM/I measurements with wind vectors measured from ships, etc., produced global maps of the ocean surface winds suitable for climate analysis. From this SSM/I dataset, a specific index I(sub na) of the North Atlantic surface winds has been developed, which pertinently quantifies the low-level advection into central Europe. For a selected time-period, the index I(sub na) reports the average of the amplitude of the wind, averaging only the speed when the direction is from the southwest (when the wind is from another direction, the contribution counts to the average as zero speed). Strong correlations were found between February I(sub na) and the surface air temperatures in Europe 50-60 deg N. In the present study, we present the correlations between I(sub na) and temperature I(sub s), and also the sensitivity of T(sub s), to an increase in I(sub na), in various seasons and various regions. We specifically analyze the flow of maritime-air from the North Atlantic that produced two extraordinary warm periods: February 1990, and early-winter 2000/2001. The very cold December 2001 was clearly due to a northerly flow. Our conclusion is that the SSM/I dataset is very useful for providing insight to the forcing of climatic fluctuations in Europe.

Otterman, J.↗
NASA NTRS2014

The Effects of Chlorophyll Assimilation on Carbon Fluxes in a Global Biogeochemical Model

In this paper, we investigated whether the assimilation of remotely-sensed chlorophyll data can improve the estimates of air-sea carbon dioxide fluxes (FCO2). Using a global, established biogeochemical model (NASA Ocean Biogeochemical Model, NOBM) for the period 2003-2010, we found that the global FCO2 values produced in the free-run and after assimilation were within -0.6 mol C m(sup -2) y(sup -1) of the observations. The effect of satellite chlorophyll assimilation was assessed in 12 major oceanographic regions. The region with the highest bias was the North Atlantic. Here the model underestimated the fluxes by 1.4 mol C m(sup -2) y(sup -1) whereas all the other regions were within 1 mol C m(sup -2) y(sup -1) of the data. The FCO2 values were not strongly impacted by the assimilation, and the uncertainty in FCO2 was not decreased, despite the decrease in the uncertainty in chlorophyll concentration. Chlorophyll concentrations were within approximately 25% of the database in 7 out of the 12 regions, and the assimilation improved the chlorophyll concentration in the regions with the highest bias by 10-20%. These results suggest that the assimilation of chlorophyll data does not considerably improve FCO2 estimates and that other components of the carbon cycle play a role that could further improve our FCO2 estimates.

Biogeochemical Model↗
NASA NTRS2022

Observation Impact and Information Retention in the Lower Troposphere of the GMAO GEOS Data Assimilation System

In this study, we have assessed the effectiveness of the use of existing observing systems in the lower troposphere in the GEOS hybrid–4DEnVar data assimilation system through a set of observing system experiments. The results show that microwave radiances have a large impact in the Southern Hemisphere and Tropical ocean, but the large influence is mostly observed above 925 hPa and dissipates relatively quickly with longer forecast lead times. Conventional data information holds better in the forecast ranging from the surface to 100 hPa, depending on the field evaluated, in the Northern Hemisphere and lowest model levels in the Tropics. Infrared radiances collectively have much less impact in the lower troposphere. Removing surface observations has small but persistent impact on specific humidity in the upper atmosphere, but small or negligible impact on planetary boundary layer (PBL) height and temperature. The model responses to the incremental analysis update (IAU) forcing are also analyzed. In the IAU assimilation window, the physics responds strongly to the IAU forcing in the lower troposphere, and the changes of physics tendency in the lower troposphere and hydrodynamics tendency in the mid- and upper troposphere are viewed as beneficial to the reduction of state error covariance. In the subsequent forecast, the model tendencies continue to deviate further from the original free forecast with forecast lead times around 300–400 hPa, but physics tendency has showed signs of returning to its original free forecast mechanisms at 1-day forecast in the lower troposphere.

GEOS↗
NASA NTRS1992

Integration of space and in-situ observations to study atmosphere, ocean and land processes

A research investigation was conducted into the possibility of using atmospheric observations made in the past from both terrestrial and space-based platforms to create a global, coherent four dimensional analysis for the purpose of studying atmospheric, oceanic, and land surface processes relevant to climate simulation, monitoring, and change. This investigation consisted of the following tasks: (1) a mature global data assimilation system was obtained from the National Meteorological Center and modified for use on a Cray X-MP computer system; (2) atmospheric observations for the period 20 Nov. 1982 through 1 Mar. 1983, including rawinsonde soundings, aircraft-based measurements, pilot balloons, and temperature soundings from polar orbiting satellites were obtained from several sources; and (3) the global data assimilation system was used to reassimilate the atmospheric observations to produce a new atmospheric analysis which was then compared with the contemporaneous analysis. The global hydrologic cycle, including fluxes between the atmosphere and both the land and ocean surfaces, was estimated. The flux of water from the ocean surface into the atmosphere, its transport in the form of latent heat to remote regions, and its return to the surface in the form of precipitation were estimated globally. In addition, several regional budgets for selected tropical oceanic and extratropical continental areas were also done.

Shukla, J.↗
NASA NTRS1999

Assimilation of SeaWinds Scatterometer Data in the GEOS Data Assimilation System

The first SeaWinds scatterometer was launched in to space aboard the Quikscat satellite on June 19, 1999 at 7:15 p.m. PDT. Flying in a near polar orbit 800 km above the earth's surface, SeaWinds uses an advanced scatterometer design to measure surface wind velocity over 90 percent of the ice free oceans ever 24 hours. This first SeaWinds mission is designed to replace the NASA Scatterometer (NSCAT) which ceased providing wind velocity data when the ADEOS I satellite failed. A second SeaWinds is scheduled to be launched late in 2000 aboard ADEOS II. Previous scatterometer assimilation experiments conducted by the NASA Data Assimilation Office, using both ERS and NSCAT wind observations, have demonstrated considerable potential for this type of data to improve both atmospheric analyses and forecasts, however much of the smaller scale information content of the scatterometer data could not be taken into account in the early coarse resolution versions of the Goddard (GEOS) Data Assimilation System (DAS) or in operational data assimilation systems. In this paper, we will describe data assimilation experiments in which the new higher resolution versions of the GOES DAS are used to assimilate SeaWinds scatterometer winds. Following a brief discussion of the SeaWinds design and the methodology used to assimilate scatterometer data in the GOES DAS, the quality of the SeaWinds data and the impact of SeaWinds on GOES analyses and forecasts at different resolutions will be presented.

Atlas, Robert↗
NASA NTRS2014

Exploring the Utility of the Planned CYGNSS Mission for Investigating the Initiation and Development of the Madden-Julian Oscillation

CYGNSS is a planned constellation consisting of multiple micro-satellites that leverage the Global Positioning System (GPS) to provide rapidly updated, high resolution (approx. 15-50 km, approx. 4 h) surface wind speeds (via bi-static scatterometry) over the tropical oceans in any weather condition, including heavy rainfall. The approach of the work to be presented at this conference is to utilize a limited-domain, cloud-system resolving model (Weather Research and Forecasting or WRF) and its attendant data assimilation scheme (Three-Dimensional Variational Assimilation or 3DVAR) to investigate the utility of the CYGNSS mission for helping characterize key convectiveto- mesoscale processes - such as surface evaporation, moisture advection and convergence, and upscale development of precipitation systems - that help drive the initiation and development of the Madden-Julian Oscillation (MJO) in the equatorial Indian Ocean. The proposed work will focus on three scientific objectives. Objective 1 is to produce a high-resolution surface wind dataset resolution (approx. 0.5 h, approx. 1-4 km) for multiple MJO onsets using WRF-assimilated winds and other data from the DYNAmics of the MJO (DYNAMO) field campaign, which took place during October 2011 - March 2012. Objective 2 is to study the variability of surface winds during MJO onsets at temporal and spatial scales of finer resolution than future CYGNSS data. The goal is to understand how sub-CYGNSS-resolution processes will shape the observations made by the satellite constellation. Objective 3 is to ingest simulated CYGNSS data into the WRF model in order to perform observing system simulation experiments (OSSEs). These will be used to test and quantify the potential beneficial effects provided by CYGNSS, particularly for characterizing the physical processes driving convective organization and upscale development during the initiation and development of the MJO. The proposed research is ideal for answering important questions about the CYGNSS mission, such as the representativeness of surface wind retrievals in the context of the complex airflow processes that occur during heavy precipitation, as well as the tradeoffs in retrieval accuracy that result from finer spatial resolution of the CYGNSS winds versus increased errors/noisiness in those data. Research plans and initial progress toward these objectives will be presented.

Lang, Timothy↗
NASA NTRS2004

ENSO Bred Vectors in Coupled Ocean-Atmosphere General Circulation Models

The breeding method has been implemented in the NASA Seasonal-to-Interannual Prediction Project (NSIPP) Coupled General Circulation Model (CGCM) with the goal of improving operational seasonal to interannual climate predictions through ensemble forecasting and data assimilation. The coupled instability as cap'tured by the breeding method is the first attempt to isolate the evolving ENSO instability and its corresponding global atmospheric response in a fully coupled ocean-atmosphere GCM. Our results show that the growth rate of the coupled bred vectors (BV) peaks at about 3 months before a background ENSO event. The dominant growing BV modes are reminiscent of the background ENSO anomalies and show a strong tropical response with wind/SST/thermocline interrelated in a manner similar to the background ENSO mode. They exhibit larger amplitudes in the eastern tropical Pacific, reflecting the natural dynamical sensitivity associated with the presence of the shallow thermocline. Moreover, the extratropical perturbations associated with these coupled BV modes reveal the variations related to the atmospheric teleconnection patterns associated with background ENSO variability, e.g. over the North Pacific and North America. A similar experiment was carried out with the NCEP/CFS03 CGCM. Comparisons between bred vectors from the NSIPP CGCM and NCEP/CFS03 CGCM demonstrate the robustness of the results. Our results strongly suggest that the breeding method can serve as a natural filter to identify the slowly varying, coupled instabilities in a coupled GCM, which can be used to construct ensemble perturbations for ensemble forecasts and to estimate the coupled background error covariance for coupled data assimilation.

Yang, S. C.↗
NASA NTRS2008

Energetic Consistency and Coupling of the Mean and Covariance Dynamics

The dynamical state of the ocean and atmosphere is taken to be a large dimensional random vector in a range of large-scale computational applications, including data assimilation, ensemble prediction, sensitivity analysis, and predictability studies. In each of these applications, numerical evolution of the covariance matrix of the random state plays a central role, because this matrix is used to quantify uncertainty in the state of the dynamical system. Since atmospheric and ocean dynamics are nonlinear, there is no closed evolution equation for the covariance matrix, nor for the mean state. Therefore approximate evolution equations must be used. This article studies theoretical properties of the evolution equations for the mean state and covariance matrix that arise in the second-moment closure approximation (third- and higher-order moment discard). This approximation was introduced by EPSTEIN [1969] in an early effort to introduce a stochastic element into deterministic weather forecasting, and was studied further by FLEMING [1971a,b], EPSTEIN and PITCHER [1972], and PITCHER [1977], also in the context of atmospheric predictability. It has since fallen into disuse, with a simpler one being used in current large-scale applications. The theoretical results of this article make a case that this approximation should be reconsidered for use in large-scale applications, however, because the second moment closure equations possess a property of energetic consistency that the approximate equations now in common use do not possess. A number of properties of solutions of the second-moment closure equations that result from this energetic consistency will be established.

Cohn, Stephen E.↗
NASA NTRS2019

Assessment of Satellite Sea Surface Salinity Products Using a Coupled ENSO Prediction Model

Much work has gone into revising and updating algorithms for converting satellite-measured radiances to useful ocean variables like sea surface salinity (e.g. SMOS - Boutin et al., 2017, SMAP - Fore et al., 2016 and Aquarius - Meissner et al., 2018). As part of our Ocean Salinity Science Team work, we utilize an intermediate-complexity air/sea coupled model as a transfer function to test if more mature satellite SSS model algorithms actually improve ENSO forecast skill. For initialization of the coupled forecast, we demonstrate that the positive impact of SSS assimilation is brought about by surface freshening near the eastern edge of the western Pacific warm pool and density changes that lead to shallower mixed layer between 10S-5N. In addition, salting near the ITCZ leads to a deepening of the mixed layer and thermocline near 8N. These patterns together provide the background state to amplify equatorial Kelvin waves and improve ENSO hindcasts (Hackert et al., 2019). Here we extend this work to compare the impact of various pairs of original and improved satellite SSS algorithms. For instance we compare SMAP V4.1 with the latest, SMAP V4.2, to see what impact algorithm improvements may have on ENSO forecasts. SSS observations are tested on seasonal to interannual variability of tropical Indo-Pacific Ocean dynamics as well as on dynamical ENSO forecasts by initializing twelve-month forecasts for each month of available data. All experiments assimilate satellite sea level (SL), sea surface temperature (SST), and in situ subsurface temperature and salinity observations (Tz, Sz). Additionally various satellite, blended, and in-situ SSS products are assimilated. We find that including satellite SSS significantly improves Niño3.4 sea surface temperature anomaly validation, more mature SSS model algorithms are generally improving ENSO forecasts over time, and more satellite SSS data coverage helps to extend useful forecasts.

Ocean↗
NASA NTRS1999

The Potential for Predicting Precipitation on Seasonal-to-Interannual Timescales

The ability to predict precipitation several months in advance would have a significant impact on water resource management. This talk provides an overview of a project aimed at developing this prediction capability. NASA's Seasonal-to-Interannual Prediction Project (NSIPP) will generate seasonal-to-interannual sea surface temperature predictions through detailed ocean circulation modeling and will then translate these SST forecasts into forecasts of continental precipitation through the application of an atmospheric general circulation model and a "SVAT"-type land surface model. As part of the process, ocean variables (e.g., height) and land variables (e.g., soil moisture) will be updated regularly via data assimilation. The overview will include a discussion of the variability inherent in such a modeling system and will provide some quantitative estimates of the absolute upper limits of seasonal-to-interannual precipitation predictability.

Koster, R. D.↗
NASA NTRS2006

Polarimetric Microwave Remote Sensing of Hurricane Ocean Winds

We presented the analysis of Windsat data for hurricanes Isabel and Fabian in 2003. The polarimetric third and fourth Stokes parameter observations from the Windsat 10, 18 and 37 GHz channels were collocated with the ocean surface winds from the Holland wind model, the QuikSCAT wind vectors and the Global Data Assimilation System (GDAS) operated by the National Center for Environmental Prediction (NCEP). The collocated data were binned as a function of wind speed and wind direction, and were expanded by sinusoidal series of the relative azimuth angles between wind and observation directions. The coefficients of the sinusoidal series, corrected for atmospheric attenuation, have been used to develop an empirical geophysical model function (GMF). The Windsat GMF for extreme high wind compares very well with the aircraft radiometer and radar measurements.

widebands↗
NASA NTRS2006

Combined Active and Passive Remote Sensing of Hurricane Ocean Winds

The synergism of active and passive microwave techniques for hurricane ocean wind remote sensing is explored. We performed the analysis of Windsat data for Atlantic hurricanes in 2003-2005. The polarimetric third Stokes parameter observations from the Windsat 10, 18 and 37 GHz channels were collocated with the ocean surface winds from the Holland wind model, the QuikSCAT wind vectors and the Global Data Assimilation System (GDAS) operated by the National Center for Environmental Prediction (NCEP). The collocated data were binned as a function of wind speed and wind direction, and were expanded by sinusoidal series of the relative azimuth angles between wind and observation directions. The coefficients of the sinusoidal series, corrected for atmospheric attenuation, have been used to develop an empirical geophysical model function (GMF). The Windsat GMF for extreme high wind compares very well with the aircraft radiometer and radar measurements.

sea surface winds↗
NASA NTRS1999

Tidal Energy Available for Deep Ocean Mixing: Bounds from Altimetry Data

Maintenance of the large-scale thermohaline circulation has long presented a problem to oceanographers. Observed mixing rates in the pelagic ocean are an order of magnitude too small to balance the rate at which dense bottom water is created at high latitudes. Recent observational and theoretical work suggests that much of this mixing may occur in hot spots near areas of rough topography (e.g., mid-ocean ridges and island arcs). Barotropic tidal currents provide a very plausible source of energy to maintain these mixing processes. Topex/Poseidon (T/P) satellite altimetry data have made precise mapping of open ocean tidal elevations possible for the first time. We can thus obtain empirical, spatially localized, estimates of barotropic tidal dissipation. These provide an upper bound on the amount of tidal energy that is dissipated in the deep ocean, and hence is available for deep mixing. We will present and compare maps of open ocean tidal energy flux divergence, and estimates of tidal energy flux into shallow seas, derived from T/P altimetry data using both formal data assimilation methods and empirical approaches. With the data assimilation methods we can place formal error bars on the fluxes. Our results show that 20-25% of tidal energy dissipation occurs outside of the shallow seas, the traditional sink for tidal energy. This suggests that up to 1 TW of energy may be available from the tides (lunar and solar) for mixing the deep ocean. The dissipation indeed appears to be concentrated over areas of rough topography.

Egbert, Gary D.↗