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An L-band radiometer-radar concept has been studied for spaceborne remote sensing of land surface wetness, freeze-thaw state, and ocean surface salinity.
The present state of knowledge of the synoptic scale, the mesoscale, and the microscale in describing the winds, especially over the ocean, is summarized both in terms of conventional data and remotely sensed properties and effects of the winds. A description is then given of some of the areas posing problems in modeling each scale and interpreting the various kinds of measurements that are made. It is noted that not much is known about the wind, especially in the mesoscale, that affects the ability to use remotely sensed data in an optimum way.
Satellite radar interferometry is a powerful technique to measure the surface velocity and topography of glacier ice. On ice shelves, a quadruple difference technique separates tidal motion from the steady creep flow deformation of ice. The results provide a wealth of information about glacier grounding lines , mass fluxes, stability, elastic properties of ice, and tidal regime. The grounding line, which is where the glacier detaches from its bed and becomes afloat, is detected with a precision of a few tens of meters. Combining this information with satellite radar altimetry makes it possible to measure glacier discharge into the ocean and state of mass balance with greater precision than ever before, and in turn provide a significant revision of past estimates of mass balance of the Greenland and Antarctic Ice Sheets. Analysis of creep rates on floating ice permits an estimation of basal melting at the ice shelf underside. The results reveal that the action of ocean water in sub-ice-shelf cavities has been largely underestimated by oceanographic models and is the dominant mode of mass release to the ocean from an ice shelf. Precise mapping of grounding line positions also permits the detection of grounding line migration, which is a fine indicator of glacier change, independent of our knowledge of snow accumulation and ice melting. This technique has been successfully used to detect the rapid retreat of Pine Island Glacier, the largest ice stream in West Antarctica. Finally, tidal motion of ice shelves measured interferometrically provides a modern, synoptic view of the physical processes which govern the formation of tabular icebergs in the Antarctic.
Sea surface height (SSH) from altimeter observations from 1992 on and from modeling results is investigated to determine the modes of variability and the linkages to the state of oceanic circulation in the North Atlantic. First the altimeter and model simulated SSH are analyzed using the empirical orthogonal function (EOF) analysis. They are found to share a similar leading mode where the center of action is along the Gulf Stream and North Atlantic Current with opposite sign anomalies in the subpolar gyre and in the slope waters along the Eastern Seaboard. The time series of the leading EOF mode from the altimeter data shows that between winters of 1995 and 1996, SSH over the Gulf Stream decreased by about 12cm which change is reproduced by the model simulation. Based on the relationship from the model simulations between the time series of the SSH EOF1 and meridional heat transport, it is suggested that associated with this SSH change in 1995-96, the overturning has slowed down from its heights in the early 90's. Furthermore, it is shown that decadal variability in the leading SSH mode originates from the thermal forcing component. This adds confidence to the qualitative relationship between the state of overturning/meridional heat transport and SSH in the limited area described by the EOF1. SSH variability in the eastern side of the North Atlantic basin, outside the western boundary current region, is determined by local and remote (Rossby waves) wind stress curl forcing.
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The efficient estimation of ocean wave-structure parameters with a remote, narrow-beam, pulsed, microwave radar at intermediate incidence angles is discussed. The sea surface is described as the sum of random small- and large-scale structures (waves), the latter the sum of a sinusoid and a random field. It is shown that the small-scale structure is responsible for scattering and that the scatter depends parametrically on the large-scale structure. For the estimation problem it is assumed, reasonably, that the received signal is normally distributed: a relatively simple processor which will efficiently estimate parameters of the sinusoidal structure is illustrated and its performance discussed. A brief comparison is made with a normal incidence system with which the variance of the large-scale random roughness can be estimated.
Phytoplankton photosynthesis in the sun lit upper layer of the global ocean is the overwhelmingly dominant source of organic matter that fuels marine ecosystems. Phytoplankton contribute roughly half of the global (land and ocean) net primary production (NPP; gross photosynthesis minus plant respiration) and phytoplankton carbon fixation is the primary conduit through which atmospheric CO2 concentrations interact with the ocean s carbon cycle. Phytoplankton productivity depends on the availability of sunlight, macronutrients (e.g., nitrogen, phosphorous), and micronutrients (e.g., iron), and thus is sensitive to climate-driven changes in the delivery of these resources to the euphotic zone
The Geostationary Operational Environmental Satellite R (GOES-R) series is the planned next generation of operational weather satellites for the United States National Oceanic and Atmospheric Administration (NOAA). The National Aeronautics and Space Administration (NASA) is procuring the GOES-R spacecraft and instruments with the first launch of the GOES-R series planned for October 2016. Included in the GOES-R Instrument suite is the Geostationary Lightning Mapper (GLM). GLM is a single-channel, near-infrared optical detector that can sense extremely brief (800 s) transient changes in the atmosphere, indicating the presence of lightning. GLM will measure total lightning activity continuously over the Americas and adjacent ocean regions with near-uniform spatial resolution of approximately 10 km. Due to its large CCD (1372x1300 pixels), high frame rate, sensitivity and onboard event filtering, GLM will require extensive post launch characterization and calibration. Daytime and nighttime images will be used to characterize both image quality criteria inherent to GLM as a space-based optic system (focus, stray light, crosstalk, solar glint) and programmable image processing criteria (dark offsets, gain, noise, linearity, dynamic range). In addition ground data filtering will be adjusted based on lightning-specific phenomenology (coherence) to isolate real from false transients with their own characteristics. These parameters will be updated, as needed, on orbit in an iterative process guided by pre-launch testing. This paper discusses the planned tests to be performed on GLM over the six-month Post Launch Test period to optimize and demonstrate GLM performance.
The Geostationary Operational Environmental Satellite R (GOES-R) series is the planned next generation of operational weather satellites for the United States National Oceanic and Atmospheric Administration (NOAA). The National Aeronautics and Space Administration (NASA) is procuring the GOES-R spacecraft and instruments with the first launch of the GOES-R series planned for October 2016. Included in the GOES-R Instrument suite is the Geostationary Lightning Mapper (GLM). GLM is a single-channel, near-infrared optical detector that can sense extremely brief (800 microseconds) transient changes in the atmosphere, indicating the presence of lightning. GLM will measure total lightning activity continuously over the Americas and adjacent ocean regions with near-uniform spatial resolution of approximately 10 km. Due to its large CCD (1372x1300 pixels), high frame rate, sensitivity and onboard event filtering, GLM will require extensive post launch characterization and calibration. Daytime and nighttime images will be used to characterize both image quality criteria inherent to GLM as a space-based optic system (focus, stray light, crosstalk, solar glint) and programmable image processing criteria (dark offsets, gain, noise, linearity, dynamic range). In addition ground data filtering will be adjusted based on lightning-specific phenomenology (coherence) to isolate real from false transients with their own characteristics. These parameters will be updated, as needed, on orbit in an iterative process guided by pre-launch testing. This paper discusses the planned tests to be performed on GLM over the six-month Post Launch Test period to optimize and demonstrate GLM performance.
The Geostationary Operational Environmental Satellite R (GOES-R) series is the planned next generation of operational weather satellites for the United States National Oceanic and Atmospheric Administration. The first launch of the GOES-R series is planned for October 2016. The GOES-R series satellites and instruments are being developed by the National Aeronautics and Space Administration (NASA). One of the key instruments on the GOES-R series is the Advance Baseline Imager (ABI). The ABI is a multi-channel, visible through infrared, passive imaging radiometer. The ABI will provide moderate spatial and spectral resolution at high temporal and radiometric resolution to accurately monitor rapidly changing weather. Initial on-orbit calibration and performance characterization is crucial to establishing baseline used to maintain performance throughout mission life. A series of tests has been planned to establish the post launch performance and establish the parameters needed to process the data in the Ground Processing Algorithm. The large number of detectors for each channel required to provide the needed temporal coverage presents unique challenges for accurately calibrating ABI and minimizing striping. This paper discusses the planned tests to be performed on ABI over the six-month Post Launch Test period and the expected performance as it relates to ground tests.
Forcing ocean models with reanalysis data is a common practice in ocean modeling. As part of this practice, prescribed atmospheric state variables and interactive ocean SST (Sea Surface Temperature) are used to calculate fluxes between the ocean and the atmosphere. When forcing an ocean model with reanalysis fields, errors in the reanalysis data, errors in the ocean model and errors in the forcing formulation will generate a different solution compared to other ocean reanalysis solutions (which also have their own errors). As a first step towards a consistent coupled ocean-atmosphere reanalysis, we compare surface heat fluxes from a state-of-the-art atmospheric reanalysis, the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2), to heat fluxes from a state-of-the-art oceanic reanalysis, the Estimating the Circulation and Climate of the Ocean Version 4, Release 2 (ECCO-v4). Then, we investigate the errors associated with the MITgcm (Massachusetts Institute of Technology general circulation model) ocean model in its ECCO-v4 ocean reanalysis configuration (1992-2011) when it is forced with MERRA- 2 atmospheric reanalysis fields instead of with the ECCO-v4 adjoint optimized ERA-interim state variables. This is done by forcing ECCO-v4 ocean with and without feedbacks from MERRA-2 related to turbulent fluxes of heat and moisture and the outgoing long wave radiation. In addition, we introduce an intermediate forcing method that includes only the feedback from the interactive outgoing long wave radiation. The resulting ocean circulation is compared with ECCO-v4 reanalysis and in-situ observations. We show that, without feedbacks, imbalances in the energy and the hydrological cycles of MERRA-2 (which are directly related to the fact it was created without interactive ocean) result in considerable SST drifts and a large reduction in sea level. The bulk formulae and interactive outgoing long wave radiation, although providing air-sea feedbacks and reducing model-data misfit, strongly relax the ocean to observed SST and may result in unwanted features such as large change in the water budget. These features have implications in a desired forcing recipe to be used. The results strongly and unambiguously argue for next generation data assimilation climate studies to involve fully coupled systems.
During our participation in the NASA Crustal Dynamics Project under NASA contract NAS-27339 and grant NAG5-814 for the period 1982-1991, we published or submitted for publication 30 research papers and 52 abstracts of presentations at scientific meetings. In addition, five M.I.T. Ph.D. students (Eric Bergman, Steven Bratt, Dan Davis, Jeanne Sauber, Anne Sheehan) were supported wholly or in part by this project during their thesis research. Highlights of our research progress during this period include the following: application of geodetic data to determine rates of strain in the Mojave block and in central California and to clarify the relation of such strain to the San Andreas fault and Pacific-North American plate motions; application of geodetic data to infer post seismic deformation associated with large earthquakes in the Imperial Valley, Hebgen Lake, Argentina, and Chile; determination of the state of stress in oceanic lithosphere from a systematic study of the centroid depths and source mechanisms of oceanic intraplate earthquakes; development of models for the state of stress in young oceanic regions arising from the differential cooling of the lithosphere; determination of the depth extent and rupture characteristics of oceanic transform earthquakes; improved determination of earthquake slip vectors in the Gulf of California, an important data set for the estimation of Pacific-North American plate motions; development of models for the state of stress and mechanics of fold-and-thrust belts and accretionary wedges; development of procedures to invert geoid height, residual bathymetry, and differential body wave travel time residuals for lateral variations in the characteristic temperature and bulk composition of the oceanic upper mantle; and initial GPS measurements of crustal deformation associated with the Imperial-Cerro Prieto fault system in southern California and northern Mexico. Full descriptions of the research conducted on these topics may be found in the Semi-Annual status Reports submitted regularly to NASA over the course of this project and in the publications listed.
Mean absolute sea level reflects the deviation of the Ocean surface from geoid due to the ocean currents and is an important characteristic of the dynamical state of the ocean. Values of its spatial variations (order of 1 m) are generally much smaller than deviations of the geoid shape from ellipsoid (order of 100 m) that makes the derivation of the absolute mean sea level a difficult task for gravity and satellite altimetry observations. Technique used by Niiler et al. for computation of the absolute mean sea level in the Kuroshio Extension was then developed into more general method and applied by Niiler et al. (2003b) to the global Ocean. The method is based on the consideration of balance of horizontal momentum.
While current-generation CMIP and OMIP models have clear biases in their upper Arctic Ocean hydrography, it is less clear how these biases impact the models' ability to simulate the observed Arctic sea ice mean state and trends. In this study we seek to quantify cross-relationship between sea ice and ocean states in CMIP6 historical simulations and identify common model behaviors. Multi-model mean (MMM) simulations exhibit accelerated changes in the ice and ocean system since the late 20th century. Underlying the MMM is strong inter-model variation in the simulated ice and ocean mean states and their temporal variability including trends. Despite such inter-model differences, all models show a similar ratio between sea ice reduction and upper ocean warming such that models with higher ocean warming also have higher SIE reduction and vice versa. Our results also highlight the urgent needs of reliable Arctic Ocean observations or data products in order to better contextualize modeling results.
Knowing the spatial and temporal distribution of the underwater light field, i.e., the spectral and angular structure of the radiant intensity at any point in the water column, is essential to understanding the biogeochemical processes that control the composition and evolution of aquatic ecosystems and their impact on climate and reaction to climate change. At present, only a few properties are reliably retrieved from space, either directly or via water-leaving radiance. Existing satellite products are limited to planar photosynthetically available radiation (PAR) and ultraviolet (UV) irradiance above the surface and diffuse attenuation coefficient. Examples of operational products are provided, and their advantages and drawbacks are examined. The usefulness and convenience of these products notwithstanding, there is a need, as expressed by the user community, for other products, i.e., sub-surface planar and scalar fluxes, average cosine, spectral fluxes (UV to visible), diurnal fluxes, absorbed fraction of PAR by live algae (APAR), surface albedo, vertical attenuation, and heating rate, and for associating uncertainties to any product on a pixel-by-pixel basis. Methodologies to obtain the new products are qualitatively discussed in view of most recent scientific knowledge and current and future satellite missions, and specific algorithms are presented for some new products, namely sub-surface fluxes and average cosine. A strategy and roadmap (short, medium, and long term) for usage and development priorities is provided, taking into account needs and readiness level. Combining observations from satellites overpassing at different times and geostationary satellites should be pursued to improve the quality of daily-integrated radiation fields, and products should be generated without gaps to provide boundary conditions for general circulation and biogeochemical models. Examples of new products, i.e., daily scalar PAR below the surface, daily average cosine for PAR, and sub-surface spectral scalar fluxes are presented. A procedure to estimate algorithm uncertainties in the total uncertainty budget for above-surface daily PAR, based on radiative simulations for expected situations, is described. In the future, space-borne lidars with ocean profiling capability offer the best hope for improving our knowledge of sub-surface fields. To maximize temporal coverage, space agencies should consider placing ocean-color instruments in L1 orbit, where the sunlit part of the Earth can be frequently observed.
Often a science user will discover data of interest in a general-purpose discovery tool like Earthdata Search. At that point it might be beneficial for the science user to switch to a more specialized tool. Smart handoffs allow the user to switch from one tool to another with their context (collection, spatial and temporal constraints) intact. This provides an efficient means of traversing tools and services. The idea of smart handoffs could be expanded to commercial search engines such as Google, visualization tools like State of the Ocean and Giovanni and domain-specific search tools like Earthdata Search.
Simulation characteristics from eighteen global ocean-sea-ice coupled models are presented with a focus on the mean Atlantic meridional overturning circulation (AMOC) and other related fields in the North Atlantic. These experiments use inter-annually varying atmospheric forcing data sets for the 60-year period from 1948 to 2007 and are performed as contributions to the second phase of the Coordinated Oceanice Reference Experiments (CORE-II). The protocol for conducting such CORE-II experiments is summarized. Despite using the same atmospheric forcing, the solutions show significant differences. As most models also differ from available observations, biases in the Labrador Sea region in upper-ocean potential temperature and salinity distributions, mixed layer depths, and sea-ice cover are identified as contributors to differences in AMOC. These differences in the solutions do not suggest an obvious grouping of the models based on their ocean model lineage, their vertical coordinate representations, or surface salinity restoring strengths. Thus, the solution differences among the models are attributed primarily to use of different subgrid scale parameterizations and parameter choices as well as to differences in vertical and horizontal grid resolutions in the ocean models. Use of a wide variety of sea-ice models with diverse snow and sea-ice albedo treatments also contributes to these differences. Based on the diagnostics considered, the majority of the models appear suitable for use in studies involving the North Atlantic, but some models require dedicated development effort. atmospheric forcing atmospheric temperatures
The NASA GMAO seasonal (9 months) and subseasonal (45 days) forecasts are produced with the Goddard Earth Observing System (GEOS) Atmosphere-Ocean General Circulation Model and Data Assimilation System Version S2S-2_1. The new system replaces version S2S-1.0 described in Borovikov et al (2017), and includes upgrades to many components of the system. The atmospheric model includes an upgrade from a pre-MERRA-2 version running on a latitude-longitude grid at approx. 1 degree resolution to a current version running on a cubed sphere grid at approximately 1/2 degree resolution. The important developments are related to the dynamical core (Putman et al., 2011), the moist physics (''two-moment microphysics'' of Barahona et al., 2014) and the cryosphere (Cullather et al., 2014). As in the previous GMAO S2S system, the land model is that of Koster et al (2000). GMAO S2S-2_1 now includes the Goddard Chemistry Aerosol Radiation and Transport (GOCART, Colarco et al., 2010) single moment interactive aerosol model that includes predictive aerosols including dust, sea salt and several species of carbon and sulfate. The previous version of GMAO S2S specified aerosol amounts from climatology, which were used to inform the atmospheric radiation only. The ocean model includes an upgrade from MOM4 to MOM5 (Griffies 2012), and continues to be run on the tripolar grid at approximately 1/2 degree resolution in the tropics with 40 vertical levels. As in S2S-1.0, the sea ice model is from the Los Alamos Sea Ice model (CICE4, Hunke and Lipscomb 2010). The Ocean Data Assimilation System (ODAS) has been upgraded from the one described in Borovikov et al., 2017 to one that uses a modified version of the Penny, 2014 Local Ensemble Transform Kalman Filter (LETKF), and now assimilates along-track altimetry. The ODAS also does a nudging to MERRA-2 SST and sea ice boundary conditions. The atmospheric data assimilation fields used to constrain the atmosphere in the ODAS have been upgraded from MERRA to a MERRA-2 like system. The system is initialized using a MERRA-2-like atmospheric reanalysis (Gelaro et al. 2017) and the GMAO S2S-2_1 ocean analysis. Additional ensemble members for forecasts are produced with initial states at 5-day intervals, with additional members based on perturbations of the atmospheric and ocean states. Both subseasonal and seasonal forecasts are submitted to the National MultiModel Ensemble (NMME) project, and are part of the US/Canada multimodel seasonal forecasts (http://www.cpc.ncep.noaa.gov/products/NMME/). A large suite of retrospective forecasts (''hindcasts'') have been completed, and contribute to the calculation of the model's baseline climatology and drift, anomalies from which are the basis of the seasonal forecasts.