scholarly journals The Global Ocean Water Cycle in Atmospheric Reanalysis, Satellite, and Ocean Salinity

2017 ◽  
Vol 30 (10) ◽  
pp. 3829-3852 ◽  
Author(s):  
Lisan Yu ◽  
Xiangze Jin ◽  
Simon A. Josey ◽  
Tong Lee ◽  
Arun Kumar ◽  
...  
Keyword(s):  
Water Cycle ◽  
Global Ocean ◽  
Large Spread ◽  
Uncertainty Structure ◽  
Ocean Salinity ◽  
Seasonal Migrations ◽  
Tropical Areas ◽  
Freshwater Budget ◽  
The Mean ◽  
Wet Zone

Abstract This study provides an assessment of the uncertainty in ocean surface (OS) freshwater budgets and variability using evaporation E and precipitation P from 10 atmospheric reanalyses, two combined satellite-based E − P products, and two observation-based salinity products. Three issues are examined: the uncertainty level in the OS freshwater budget in atmospheric reanalyses, the uncertainty structure and association with the global ocean wet/dry zones, and the potential of salinity in ascribing the uncertainty in E − P. The products agree on the global mean pattern but differ considerably in magnitude. The OS freshwater budgets are 129 ± 10 (8%) cm yr−1 for E, 118 ± 11 (9%) cm yr−1 for P, and 11 ± 4 (36%) cm yr−1 for E − P, where the mean and error represent the ensemble mean and one standard deviation of the ensemble spread. The E − P uncertainty exceeds the uncertainty in E and P by a factor of 4 or more. The large uncertainty is attributed to P in the tropical wet zone. Most reanalyses tend to produce a wider tropical rainband when compared to satellite products, with the exception of two recent reanalyses that implement an observation-based correction for the model-generated P over land. The disparity in the width and the extent of seasonal migrations of the tropical wet zone causes a large spread in P, implying that the tropical moist physics and the realism of tropical rainfall remain a key challenge. Satellite salinity appears feasible to evaluate the fidelity of E − P variability in three tropical areas, where the uncertainty diagnosis has a global indication.

Internal salt content: a useful framework for understanding the oceanic branch of the water cycle

2021 ◽  
Author(s):  
Christopher Bladwell ◽  
Ryan M. Holmes ◽  
Jan D. Zika
Keyword(s):  
Fresh Water ◽  
Ocean Circulation ◽  
Water Cycle ◽  
Salt Content ◽  
Ocean Model ◽  
Global Ocean ◽  
Freshwater Forcing ◽  
Freshwater Fluxes ◽  
Ocean Salinity ◽  
Isopycnal Mixing

AbstractThe global water cycle is dominated by an atmospheric branch which transfers fresh water away from subtropical regions and an oceanic branch which returns that fresh water from subpolar and tropical regions. Salt content is commonly used to understand the oceanic branch because surface freshwater fluxes leave an imprint on ocean salinity. However, freshwater fluxes do not actually change the amount of salt in the ocean and – in the mean – no salt is transported meridionally by ocean circulation. To study the processes which determine ocean salinity we introduce a new variable: “internal salt” and its counterpart “internal fresh water”. Precise budgets for internal salt in salinity coordinates relate meridional and diahaline transport to surface freshwater forcing, ocean circulation and mixing, and reveal the pathway of fresh water in the ocean. We apply this framework to a 1° global ocean model. We find that in order for fresh water to be exported from the ocean’s tropical and subpolar regions to the subtropics, salt must be mixed across the salinity surfaces that bound those regions. In the tropics, this mixing is achieved by parameterized vertical mixing, along-isopycnal mixing, and numerical mixing associated with truncation errors in the model’s advection scheme, while along-isopycnal mixing dominates at high latitudes. We analyze the internal freshwater budgets of the Indo-Pacific and Atlantic Ocean basins and identify the transport pathways between them which redistribute fresh water added through precipitation, balancing asymmetries in freshwater forcing between the basins.

scholarly journals Biases in CloudSat Falling Snow Estimates Resulting from Daylight-Only Operations

2021 ◽  
Vol 13 (11) ◽  
pp. 2041
Author(s):  
Lisa Milani ◽  
Norman B. Wood
Keyword(s):  
Water Cycle ◽  
Mean Values ◽  
The Mean ◽  
Satellite Missions ◽  
The Impact ◽  
Global Mean

Falling snow is a key component of the Earth’s water cycle, and space-based observations provide the best current capability to evaluate it globally. The Cloud Profiling Radar (CPR) on board CloudSat is sensitive to snowfall, and other satellite missions and climatological models have used snowfall properties measured by it for evaluating and comparing against their snowfall products. Since a battery anomaly in 2011, the CPR has operated in a Daylight-Only Operations (DO-Op) mode, in which it makes measurements primarily during only the daylit portion of its orbit. This work provides estimates of biases inherent in global snowfall amounts derived from CPR measurements due to this shift to DO-Op mode. We use CloudSat’s snowfall measurements during its Full Operations (Full-Op) period prior to the battery anomaly to evaluate the impact of the DO-Op mode sampling. For multi-year global mean values, the snowfall fraction during DO-Op changes by −10.16% and the mean snowfall rate changes by −8.21% compared with Full-Op. These changes are driven by the changes in sampling in DO-Op and are very little influenced by changes in meteorology between the Full-Op and DO-Op periods. The results highlight the need to sample consistently with the CloudSat observations or to adjust snowfall estimates derived from CloudSat when using DO-Op data to evaluate other precipitation products.

scholarly journals The Role of Averaging for Improving Sea Surface Salinity Retrieval from the Soil Moisture and Ocean Salinity (SMOS) Satellite and Impact of Auxiliary Data

2007 ◽  
Vol 24 (2) ◽  
pp. 255-269 ◽  
Author(s):  
Sabine Philipps ◽  
Christine Boone ◽  
Estelle Obligis
Keyword(s):  
Soil Moisture ◽  
Sensitivity Study ◽  
Sea Surface ◽  
Sea Surface Salinity ◽  
Global Ocean ◽  
Surface Salinity ◽  
Auxiliary Data ◽  
Additional Information ◽  
Ocean Salinity

Abstract Soil Moisture and Ocean Salinity (SMOS) was chosen as the European Space Agency’s second Earth Explorer Opportunity mission. One of the objectives is to retrieve sea surface salinity (SSS) from measured brightness temperatures (TBs) at L band with a precision of 0.2 practical salinity units (psu) with averages taken over 200 km by 200 km areas and 10 days [as suggested in the requirements of the Global Ocean Data Assimilation Experiment (GODAE)]. The retrieval is performed here by an inverse model and additional information of auxiliary SSS, sea surface temperature (SST), and wind speed (W). A sensitivity study is done to observe the influence of the TBs and auxiliary data on the SSS retrieval. The key role of TB and W accuracy on SSS retrieval is verified. Retrieval is then done over the Atlantic for two cases. In case A, auxiliary data are simulated from two model outputs by adding white noise. The more realistic case B uses independent databases for reference and auxiliary ocean parameters. For these cases, the RMS error of retrieved SSS on pixel scale is around 1 psu (1.2 for case B). Averaging over GODAE scales reduces the SSS error by a factor of 12 (4 for case B). The weaker error reduction in case B is most likely due to the correlation of errors in auxiliary data. This study shows that SSS retrieval will be very sensitive to errors on auxiliary data. Specific efforts should be devoted to improving the quality of auxiliary data.

Estimating Global Ocean Heat Content Changes in the Upper 1800 m since 1950 and the Influence of Climatology Choice*

2014 ◽  
Vol 27 (5) ◽  
pp. 1945-1957 ◽  
Author(s):  
John M. Lyman ◽  
Gregory C. Johnson
Keyword(s):  
Heat Content ◽  
Ocean Heat Content ◽  
Global Ocean ◽  
Ocean Temperature ◽  
Vertical Separation ◽  
Ocean Heat Uptake ◽  
Expendable Bathythermograph ◽  
Heat Uptake ◽  
The Mean

Abstract Ocean heat content anomalies are analyzed from 1950 to 2011 in five distinct depth layers (0–100, 100–300, 300–700, 700–900, and 900–1800 m). These layers correspond to historic increases in common maximum sampling depths of ocean temperature measurements with time, as different instruments—mechanical bathythermograph (MBT), shallow expendable bathythermograph (XBT), deep XBT, early sometimes shallower Argo profiling floats, and recent Argo floats capable of worldwide sampling to 2000 m—have come into widespread use. This vertical separation of maps allows computation of annual ocean heat content anomalies and their sampling uncertainties back to 1950 while taking account of in situ sampling advances and changing sampling patterns. The 0–100-m layer is measured over 50% of the globe annually starting in 1956, the 100–300-m layer starting in 1967, the 300–700-m layer starting in 1983, and the deepest two layers considered here starting in 2003 and 2004, during the implementation of Argo. Furthermore, global ocean heat uptake estimates since 1950 depend strongly on assumptions made concerning changes in undersampled or unsampled ocean regions. If unsampled areas are assumed to have zero anomalies and are included in the global integrals, the choice of climatological reference from which anomalies are estimated can strongly influence the global integral values and their trend: the sparser the sampling and the bigger the mean difference between climatological and actual values, the larger the influence.

scholarly journals Developing and Demonstrating Climate Indicators for Monitoring the Changing Water Cycle

2016 ◽  
Vol 2016 ◽  
pp. 1-18 ◽  
Author(s):  
Xia Feng ◽  
Paul Houser
Keyword(s):  
Water Cycle ◽  
Spatial Scales ◽  
Atmospheric Moisture ◽  
Spatial Correlations ◽  
Climate Indicators ◽  
Terrestrial Water ◽  
The Mean ◽  
Atmospheric Moisture Content ◽  
Daily Total

In this study, we developed a suite of spatially and temporally scalable Water Cycle Indicators (WCI) to examine the long-term changes in water cycle variability and demonstrated their use over the contiguous US (CONUS) during 1979–2013 using the MERRA reanalysis product. The WCI indicators consist of six water balance variables monitoring the mean conditions and extreme aspects of the changing water cycle. The variables include precipitation (P), evaporation (E), runoff (R), terrestrial water storage (dS/dt), moisture convergence flux (C), and atmospheric moisture content (dW/dt). Means are determined as the daily total value, while extremes include wet and dry extremes, defined as the upper and lower 10th percentile of daily distribution. Trends are assessed for annual and seasonal indicators at several different spatial scales. Our results indicate that significant changes have occurred in most of the indicators, and these changes are geographically and seasonally dependent. There are more upward trends than downward trends in all eighteen annual indicators averaged over the CONUS. The spatial correlations between the annual trends in means and extremes are statistically significant across the country and are stronger forP,E,R, andCcompared todS/dtanddW/dt.

The Met Office operational global ocean forecast system FOAM-ORCA12

2021 ◽  
Author(s):  
Ana Barbosa Aguiar ◽  
Jennifer Waters ◽  
Martin Price ◽  
Gordon Inverarity ◽  
Christine Pequignet ◽  
...  
Keyword(s):  
Computational Cost ◽  
Absolute Error ◽  
Global Ocean ◽  
Background Error ◽  
Verification Methods ◽  
Climate Simulations ◽  
Forecast Models ◽  
The Mean ◽  
Lower Continuous ◽  
Better Than

<div> <p>The importance of oceans for atmospheric forecasts as well as climate simulations is being increasingly recognised with the advent of coupled ocean / atmosphere forecast models. Having comparable resolutions in both domains maximises the benefits for a given computational cost. The Met Office has recently upgraded its operational global ocean-only model from an eddy permitting 1/4 degree tripolar grid (ORCA025) to the eddy resolving 1/12 degree ORCA12 configuration while retaining 1/4 degree data assimilation. </p> </div><div> <p>We will present a description of the ocean-only ORCA12 system, FOAM-ORCA12, alongside some initial results. Qualitatively, FOAM-ORCA12 seems to represent better (than FOAM-ORCA025) the details of mesoscale features in SST and surface currents. Overall, traditional statistical results suggest that the new FOAM-ORCA12 system performs similarly or slightly worse than the pre-existing FOAM-ORCA025. However, it is known that comparisons of models running at different resolutions suffer from a double penalty effect, whereby higher-resolution models are penalised more than lower-resolution models for features that are offset in time and space. Neighbourhood verification methods seek to make a fairer comparison using a common spatial scale for both models and it can be seen that, as neighbourhood sizes increase, ORCA12 consistently has lower continuous ranked probability scores (CRPS) than ORCA025. CRPS measures the accuracy of the pseudo-ensemble created by the neighbourhood method and generalises the mean absolute error measure for deterministic forecasts. </p> </div><div> <p>The focus over the next year will be on diagnosing the performance of both the model and assimilation. A planned development that is expected to enhance the system is the update of the background-error covariances used for data assimilation. </p> </div>

Upper ocean salinity variabilities in the Southern Ocean responding to the recent surface salting in perspective of climate changes

2021 ◽  
Author(s):  
Ling Du ◽  
Xubin Ni
Keyword(s):  
Southern Ocean ◽  
Deep Water ◽  
Water Mass ◽  
Water Cycle ◽  
Upper Ocean ◽  
Tropical Ocean ◽  
Circumpolar Deep Water ◽  
Salinity Changes ◽  
Ocean Salinity ◽  
The Antarctic

<p>Water cycle have prevailed on upper ocean salinity acting as the climate change fingerprint in the numerous observation and simulation works. Water mass in the Southern Ocean accounted for the increasing importance associated with the heat and salt exchanges between Subantarctic basins and tropical oceans. The circumpolar deep water (CDW), the most extensive water mass in the Southern Ocean, plays an indispensable role in the formation of Antarctic Bottom Water. In our study, the observed CTDs and reanalysis datasets are examined to figure out the recent salinity changes in the three basins around the Antarctica. Significant surface salinity anomalies occurred in the South Indian/Pacific sectors south of 60ºS since 2008, which are connected with the enhanced CDW incursion onto the Antarctic continental shelf. Saltier shelf water was found to expand northward from the Antarctica coast. Meanwhile, the freshening of Upper Circumpolar Deep Water(UCDW), salting and submergence of Subantarctic Mode Water(SAMW) were also clearly observed. The modified vertical salinity structures contributed to the deepen mixed layer and enhanced intermediate stratification between SAMW and UCDW. Their transport of salinity flux attributed to the upper ocean processes responding to the recent atmospheric circulation anomalies, such as the Antarctic Oscillation and Indian Ocean Dipole. The phenomena of SAMW and UCDW salinity anomalies illustrated the contemporaneous changes of the subtropical and polar oceans, which reflected the meridional circulation fluctuation. Salinity changes in upper southern ocean (< 2000m) revealed the influence of global water cycle changes, from the Antarctic to the tropical ocean, by delivering anomalies from high- and middle-latitudes to low-latitudes oceans.</p>

Ocean Salinity changes in the global ocean under global warming conditions Part 1: Mechanisms in a strong warming scenario

2021 ◽  
pp. 1-56
Author(s):  
Anju Sathyanarayanan ◽  
Armin Köhl ◽  
Detlef Stammer
Keyword(s):  
Large Scale ◽  
Water Cycle ◽  
Spatial Scales ◽  
Sea Surface Salinity ◽  
Global Ocean ◽  
Dynamical Response ◽  
Freshwater Flux ◽  
Near Surface ◽  
Salinity Changes ◽  
Circulation Changes

AbstractWe investigate mechanisms underlying salinity changes projected to occur under strong representative concentration pathway (RCP) 8.5 forcing conditions. The study is based on output of the Max Planck Institute Earth System Model Mixed Resolution (MPI-ESM-MR) run with an ocean resolution of 0.4°. In comparison to the present-day oceanic conditions, sea surface salinity (SSS) increases towards the end of the 21st century in the tropical and the subtropical Atlantic. In contrast, a basin-wide surface freshening can be observed in the Pacific and Indian Oceans. The RCP8.5 scenario of the MPI-ESM-MR with a global surface warming of ~2.3°C marks a water cycle amplification of 19 %, which is equivalent to ~8%°C−1 and thus close to the water cycle amplification predicted according to the Clausius–Clapeyron (CC) relationship (~7%°C−1). Large scale global SSS changes are driven by adjustments of surface freshwater fluxes. On smaller spatial scales, it is predominantly advection related to circulation changes that affects near-surface SSS. With respect to subsurface salinity, it is changes in surface freshwater flux that drive their changes over the upper 500 m of the subtropical Pacific and Indian oceans by forcing changes in water mass formation (spice signal). In the subtropical Atlantic Ocean, in contrast, the dynamical response associated with wind stress, circulation changes and associated heaving of isopycnals is equally important in driving subsurface salinity changes over the upper 1000 m.

scholarly journals Impact of Multiple Altimeter Data and Mean Dynamic Topography in a Global Analysis and Forecasting System

2019 ◽  
Vol 36 (7) ◽  
pp. 1255-1266 ◽  
Author(s):  
Mathieu Hamon ◽  
Eric Greiner ◽  
Pierre-Yves Le Traon ◽  
Elisabeth Remy
Keyword(s):  
Data Assimilation ◽  
Sea Surface ◽  
Global Ocean ◽  
Altimeter Data ◽  
Dynamic Topography ◽  
Mean Dynamic Topography ◽  
Ocean Data Assimilation ◽  
The Mean ◽  
Data Assimilation System ◽  
Assimilation System

AbstractSatellite altimetry is one of the main sources of information used to constrain global ocean analysis and forecasting systems. In addition to in situ vertical temperature and salinity profiles and sea surface temperature (SST) data, sea level anomalies (SLA) from multiple altimeters are assimilated through the knowledge of a surface reference, the mean dynamic topography (MDT). The quality of analyses and forecasts mainly depends on the availability of SLA observations and on the accuracy of the MDT. A series of observing system evaluations (OSEs) were conducted to assess the relative importance of the number of assimilated altimeters and the accuracy of the MDT in a Mercator Ocean global 1/4° ocean data assimilation system. Dedicated tools were used to quantify impacts on analyzed and forecast sea surface height and temperature/salinity in deeper layers. The study shows that a constellation of four altimeters associated with a precise MDT is required to adequately describe and predict upper-ocean circulation in a global 1/4° ocean data assimilation system. Compared to a one-altimeter configuration, a four-altimeter configuration reduces the mean forecast error by about 30%, but the reduction can reach more than 80% in western boundary current (WBC) regions. The use of the most recent MDT updates improves the accuracy of analyses and forecasts to the same extent as assimilating a fourth altimeter.

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