[1] In this study, we estimate a time series of geocenter anomalies from a combination of data from the Gravity Recovery and Climate Experiment (GRACE) satellite mission and the output from ocean models. A matrix equation is derived relating total geocenter variations to the GRACE coefficients of degrees two and higher and to the oceanic component of the degree one coefficients. We estimate the oceanic component from two state-of-the-art ocean models. Results are compared to independent estimates of geocenter derived from other satellite data, such as satellite laser ranging and GPS. Finally, we compute degree one coefficients that are consistent with the processing applied to the GRACE Level-2 gravity field coefficients. The estimated degree one coefficients can be used to improve estimates of mass variability from GRACE, which alone cannot provide them directly.

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Using satellite gravity data between February 2003 and January 2008, we examine changes in Greenland's mass distribution on a regional scale. During this period, Greenland lost mass at a mean rate of 179 ± 25 Gt/yr, equivalent to a global mean sea level change of 0.5 ± 0.1 mm/yr. Rates increase over time, suggesting an acceleration of the mass loss, driven by mass loss during summer. The largest mass losses occurred along the southeastern and northwestern coast in the summers of 2005 and 2007, when the ice sheet lost 279 Gt and 328 Gt of ice respectively within 2 months. In 2007, a strong mass loss is observed during summer at elevations above 2000 m, for the first time since the start of the observations.

The current Earth's Energy Imbalance (EEI) is mostly the result of human activities and is driving global warming. The absolute value of EEI represents the most fundamental metric defining the status of global climate change and will be more useful than using global surface temperature. EEI can best be estimated from Ocean Heat Content changes, complemented by radiation measurements from space. Sustained observations from the Argo array of autonomous profiling floats and further development of the ocean observing system to sample the deep ocean, marginal seas, and the sea ice regions are crucial to refining future estimates of EEI. Combining multiple measurements in an optimal way holds considerable promise for estimating EEI and thus assessing the status of global climate change, improving climate syntheses and models, and testing the effectiveness of mitigation actions. Progress has been and can be achieved with a concerted international effort. Earth's energy imbalanceWeather and climate on planet Earth arise primarily from differential radiative heating and resulting movement of energy by the dynamic components of the climate system: the atmosphere and the oceans. Both of these fluids can move heat and moisture through advective processes by atmospheric winds and ocean currents, as well as through eddies, large-scale atmospheric jet streams and convection. Other major components of the climate system include sea ice, the land and its features (including albedo, vegetation, other biomass, and ecosystems), snow cover, land ice (including the ice sheets of Antarctica and Greenland, and mountain glaciers), rivers, lakes, and surface and ground water. About 30% of the incoming solar radiation is reflected and scattered from clouds and the Earth's surface back to space. The remaining absorbed solar radiation (ASR) in the climate system is transformed into various forms (internal heat, potential energy, latent energy, kinetic energy, and chemical forms), moved, stored and sequestered primarily in the ocean, but also in the atmosphere, land and ice components of the climate system. Ultimately it is radiated back to space as outgoing longwave radiation (OLR) [1][2][3] . In an equilibrium climate there is a global balance 2 between the ASR and OLR, which determines the Earth's radiation budget 1-2 . Perturbations of this budget from internal or external climate variations create EEI 4 , manifested as a radiative flux imbalance at the top of the atmosphere (TOA).The EEI is shaped by a number of climate forcings, some of which occur naturally and others that are anthropogenic in origin. A sense of the relative importance of these factors for a given timescale is obtained through estimates of their "Effective Radiative Forcing" (ERF, Fig. 1). The phenomena giving rise to changes in ERF vary regionally and over time. Internal climate variability occurs from day-to-day and month-to-month associated with weather systems and phenomena like the MaddenJulian Oscillation (MJO) that cause short-term changes in cloudiness 5 . On ...

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Presented here are three mean dynamic topography maps derived with different methodologies. The first method combines sea level observed by the high-accuracy satellite radar altimetry with the geoid model of the Gravity Recovery and Climate Experiment (GRACE), which has recently measured the earth’s gravity with unprecedented spatial resolution and accuracy. The second one synthesizes near-surface velocities from a network of ocean drifters, hydrographic profiles, and ocean winds sorted according to the horizontal scales. In the third method, these global datasets are used in the context of the ocean surface momentum balance. The second and third methods are used to improve accuracy of the dynamic topography on fine space scales poorly resolved in the first method. When they are used to compute a multiyear time-mean global ocean surface circulation on a 0.5° horizontal resolution, both contain very similar, new small-scale midocean current patterns. In particular, extensions of western boundary currents appear narrow and strong despite temporal variability and exhibit persistent meanders and multiple branching. Also, the locations of the velocity concentrations in the Antarctic Circumpolar Current become well defined. Ageostrophic velocities reveal convergent zones in each subtropical basin. These maps present a new context in which to view the continued ocean monitoring with in situ instruments and satellites.

This study quantifies mean annual and monthly fluxes of Earth's water cycle over continents and ocean basins during the first decade of the millennium. To the extent possible, the flux estimates are based on satellite measurements first and data-integrating models second. A careful accounting of uncertainty in the estimates is included. It is applied within a routine that enforces multiple water and energy budget constraints simultaneously in a variational framework in order to produce objectively determined optimized flux estimates. In the majority of cases, the observed annual surface and atmospheric water budgets over the continents and oceans close with much less than 10% residual. Observed residuals and optimized uncertainty estimates are considerably larger for monthly surface and atmospheric water budget closure, often nearing or exceeding 20% in North America, Eurasia, Australia and neighboring islands, and the Arctic and South Atlantic Oceans. The residuals in South America and Africa tend to be smaller, possibly because cold land processes are negligible. Fluxes were poorly observed over the Arctic Ocean, certain seas, Antarctica, and the Australasian and Indonesian islands, leading to reliance on atmospheric analysis estimates. Many of the satellite systems that contributed data have been or will soon be lost or replaced. Models that integrate ground-based and remote observations will be critical for ameliorating gaps and discontinuities in the data records caused by these transitions. Continued development of such models is essential for maximizing the value of the observations. Next-generation observing systems are the best hope for significantly improving global water budget accounting.