Benefits of dynamically modelled river discharge input for ocean and coupled system.

2020 ◽  
Author(s):  
Hao Zuo ◽  
Eric de Boisseson ◽  
Ervin Zsoter ◽  
Shaun Harrigan ◽  
Patricia de Rosnay ◽  
...  
Keyword(s):  
River Discharge ◽  
River Mouth ◽  
Sea Surface Salinity ◽  
Global Network ◽  
Global Ocean ◽  
Management Service ◽  
Freshwater Input ◽  
Data Set ◽  
Discharge Data ◽  
Ocean Models

<p><span>River freshwater input is crucial in modelling global ocean. </span><span><span>Most ocean models used in CMEMS services rely on climatological river discharge data with various deficiencies, which can lead to biased simulated ocean states. The Copernicus Emergency Management Service (CEMS) Global Flood Awareness System (GloFAS) provides state-of-the-art global flood forecasts and downstream river discharge. A GloFAS-ERA5 global river discharge reanalysis dataset has been produced using the same system, modelled by routing runoff from ECMWF’s (European Centre for Medium- Range Weather Forecasts) atmospheric reanalysis ERA5 via a river network. As a global gridded data set that covers from 1979 to near-real-time, GloFAS-ERA5 reanalysis can provide an improved and standardized input of land freshwater input for global, regional and coastal ocean models. Evaluation results suggest that the overall performance of this new river discharge reanalysis is reasonably good in general when verified against a global network of 1801 discharge observation stations. A new method has been developed for conversion of the GloFAS-ERA5 reanalysis data into land freshwater input for the NEMO ocean model. This method has been tested with a climatology of GloFAS-ERA5 river discharge. Compared to the DRAKKAR climatology of land freshwater input (BT06, hereafter) used by most CMEMS services, this new data set has an increased global mean value of ~1.33 Sv, but with reduced seasonal variations. Assessment of this GloFAS-ERA5 land freshwater input has been carried out with the operational ECMWF ocean analysis system-OCEAN5, driven by the same ERA5 atmospheric forcing. Evaluation of simulated ocean state against in-situ observations show improvements in regions affected by Amazon freshwater input when use GloFAS-ERA5 instead of BT06, by reducing a negative sea surface salinity bias in these regions. However, negative impact from switching to GloFAS-ERA5 land freshwater input is also visible in several regions, e.g. in the Maritime Continent and west coast of central America, which is associated with a large positive bias in the GloFAS-ERA5 river discharge at these regions. This issue can be mitigated by applying bias-correction to the GloFAS-ERA5 land freshwater input, and by adding extra vertical mixing in several affected regions that are close to the river mouth. Assessments of module simulated ocean Essential Climate Variables (ECVs) have been carried out to quantify the benefit of this realistic freshwater time series input. Improvements in climate signals like the Atlantic Meridional Overturning transports is also recorded.</span></span></p>

Improving SAR Altimeter processing over the coastal zone and inland waters - the ESA HYDROCOASTAL project

2021 ◽  
Author(s):  
David Cotton ◽  
Keyword(s):  
Coastal Zone ◽  
Test Data ◽  
River Discharge ◽  
Altimeter Data ◽  
Inland Waters ◽  
Data Sets ◽  
Data Set ◽  
Discharge Data ◽  
Processing Algorithms ◽  
The Impact

<p><strong>Introduction</strong></p><p>HYDROCOASTAL is a two year project funded by ESA, with the objective to maximise exploitation of SAR and SARin altimeter measurements in the coastal zone and inland waters, by evaluating and implementing new approaches to process SAR and SARin data from CryoSat-2, and SAR altimeter data from Sentinel-3A and Sentinel-3B. Optical data from Sentinel-2 MSI and Sentinel-3 OLCI instruments will also be used in generating River Discharge products.</p><p>New SAR and SARin processing algorithms for the coastal zone and inland waters will be developed and implemented and evaluated through an initial Test Data Set for selected regions. From the results of this evaluation a processing scheme will be implemented to generate global coastal zone and river discharge data sets.</p><p>A series of case studies will assess these products in terms of their scientific impacts.</p><p>All the produced data sets will be available on request to external researchers, and full descriptions of the processing algorithms will be provided</p><p> </p><p><strong>Objectives</strong></p><p>The scientific objectives of HYDROCOASTAL are to enhance our understanding  of interactions between the inland water and coastal zone, between the coastal zone and the open ocean, and the small scale processes that govern these interactions. Also the project aims to improve our capability to characterize the variation at different time scales of inland water storage, exchanges with the ocean and the impact on regional sea-level changes</p><p>The technical objectives are to develop and evaluate  new SAR  and SARin altimetry processing techniques in support of the scientific objectives, including stack processing, and filtering, and retracking. Also an improved Wet Troposphere Correction will be developed and evaluated.</p><p><strong>Project  Outline</strong></p><p>There are four tasks to the project</p><ul><li>Scientific Review and Requirements Consolidation: Review the current state of the art in SAR and SARin altimeter data processing as applied to the coastal zone and to inland waters</li> <li>Implementation and Validation: New processing algorithms with be implemented to generate a Test Data sets, which will be validated against models, in-situ data, and other satellite data sets. Selected algorithms will then be used to generate global coastal zone and river discharge data sets</li> <li>Impacts Assessment: The impact of these global products will be assess in a series of Case Studies</li> <li>Outreach and Roadmap: Outreach material will be prepared and distributed to engage with the wider scientific community and provide recommendations for development of future missions and future research.</li> </ul><p> </p><p><strong>Presentation</strong></p><p>The presentation will provide an overview to the project, present the different SAR altimeter processing algorithms that are being evaluated in the first phase of the project, and early results from the evaluation of the initial test data set.</p><p> </p>

scholarly journals A Last Glacial Maximum forcing dataset for ocean modelling

2019 ◽  
Author(s):  
Anne L. Morée ◽  
Jörg Schwinger
Keyword(s):  
Last Glacial Maximum ◽  
Computational Cost ◽  
Coupled Model ◽  
Glacial Maximum ◽  
Sea Surface Salinity ◽  
Specific Humidity ◽  
Data Set ◽  
Last Glacial ◽  
Ocean Models ◽  
Fully Coupled

Abstract. Model simulations of the Last Glacial Maximum (LGM, ~ 21 000 years before present) can aid the interpretation of proxy records, help to gain an improved mechanistic understanding of the LGM climate system and are valuable for the evaluation of model performance in a different climate state. Ocean-ice only model configurations forced by prescribed atmospheric data (referred to as “forced ocean models”) drastically reduce the computational cost of paleoclimate modelling as compared to fully coupled model frameworks. While feedbacks between the atmosphere and ocean-sea-ice compartments of the Earth system are not present in such model configurations, many scientific questions can be addressed with models of this type. The data presented here are derived from fully coupled paleoclimate simulations of the Palaeoclimate Modelling Intercomparison Project (PMIP3). The data are publicly accessible at the NIRD Research Data Archive at https://doi.org/10.11582/2019.00011 (Morée and Schwinger, 2019). They consist of 2-D anomaly forcing fields suitable for use in ocean models that employ a bulk forcing approach. The data include specific humidity, downwelling longwave and shortwave radiation, precipitation, wind (v and u components), temperature and sea surface salinity (SSS). All fields are provided as climatological mean anomalies between LGM and pre-industrial times. These anomaly data can therefore be added to any pre-industrial ocean forcing data set in order to obtain forcing fields representative of LGM conditions as simulated by PMIP3 models. These forcing data provide a means to simulate the LGM in a computationally efficient way, while still taking advantage of the complexity of fully coupled model set-ups. Furthermore, the dataset can be easily updated to reflect results from upcoming and future paleo model intercomparison activities.

Future salt intrusion climate scenarios: the case of the Po river

2021 ◽  
Author(s):  
Giorgia Verri ◽  
Sahameddin Mahmoudi Kurdistani ◽  
Nadia Pinardi ◽  
Giovanni Coppini ◽  
Andrea Valentini ◽  
...  
Keyword(s):  
Time Window ◽  
River Mouth ◽  
Box Model ◽  
Salt Flux ◽  
Global Ocean ◽  
Volume Flux ◽  
Climate Scenarios ◽  
Ocean Water ◽  
Salt Wedge ◽  
Ocean Models

<p>A 2-layer Estuary Box Model, named CMCC EBM (Verri et al., 2020), has been devised by the CMCC Foundation to offer a proper representation of the estuarine overturning circulation and mixing processes in a coupled modelling framework with hydrology models and ocean models. The regional to global ocean models reaching the mesoscale cannot solve the estuarine dynamics because they cannot represent the estuary geometry due to their low resolution. Thus, the idea of an estuary box model that gives reasonable values of water volume flux and salinity at the river mouth, which in turn affects the ocean dynamics.</p><p>A further development of the model equations (Verri et al. 2021, under revision) considers the estuary length, i.e.  the length of the salt wedge intrusion, as a model unknown which depends on the competition between the riverine freshwater and the salt ocean water.</p><p>The physical core of the model consists of two conservation equations for volume flux and salt flux both averaged over the diurnal tidal cycle. Moreover, two non-dimensional equations based on the Buckingham theorem have been conceived to provide the estuary length and the along-estuary eddy diffusivity (Verri et al., under revision) as time-variable parameters instead of assuming they are static as most box models do.</p><p>The input fields required by the CMCC EBM are the river runoff at the estuary head and the ocean inflow at the river mouth in terms of both barotropic tidal inflow through the water column and baroclinic inflow at the bottom. The estuary width and depth at the river mouth are the only tunable parameters of the CMCC EBM.</p><p>The model capability to estimate the length of the salt wedge intrusion has been tested and validated. The Po di Goro branch of the Po delta system has been selected as case study. It is representative of the river-dominated estuaries in a micro-tidal sea, the so called “salt wedge estuaries”, with a multiannual average of the salt wedge intrusion around 15 km according to the ArpaE monitoring campaigns.</p><p>Overall the high statistical performance, the short computation time and the minimal calibration encourage to use the CMCC EBM in coupled mode with mesoscale ocean models to produce more realistic operational forecasts and climate scenarios.</p><p>In the framework of the Operandum H2020 project (https://www.operandum-project.eu), the CMCC EBM has been used to provided historical simulations (1981-2010 time window) and mid-term scenarios (2021-2050 time window under RCP 8.5) of both the salt wedge length and the salinity at the Po di Goro mouth. The final aim is to design and develop a site-specific nature-based solution which may address the pressing issue of the salinization of the inland waters. The CMCC EBM results clearly showed a stronger intrusion of saltier ocean water in the middle term. The average, the minimum and the maximum values of salinity at the river mouth provided by the model projections are assumed as reference values to investigate the behaviour of two halophyte species which have been selected to reduce the saline intrusion problem because of their high salinity absorption capacity.</p>

scholarly journals On the permeability of barrier layers

2009 ◽  
Vol 6 (1) ◽  
pp. 799-818 ◽  
Author(s):  
J. Mignot ◽  
C. de Boyer Montégut ◽  
M. Tomczak
Keyword(s):  
Large Scale ◽  
Sea Surface Salinity ◽  
Global Ocean ◽  
Computation Method ◽  
Western Boundary ◽  
Climatic Impact ◽  
Surface Salinity ◽  
Data Set ◽  
Barrier Layer Thickness ◽  
Barrier Layers

Abstract. We present a revisited 2-degree resolution global ocean climatology of monthly mean Barrier Layer Thickness (BLT) first proposed by de Boyer Montégut et al. (2007a). In addition to using an extended data set, we present a modified computation method in order to take into account the observed permeability of Barrier Layers (BL). We name permeability the fact that barrier layers can, in some areas, be very patchy regarding the space and time scales that are considered. This patchiness may have important consequences for the climatic impact of BLs. Differences between the two computation methods are weak for robust BLs that are formed by large-scale processes. The former approach can however largely underestimate the thickness of short and/or localized barrier layers. This is especially the case for the ones formed by mesoscale mechanisms (under the ITCZ for example and along western boundary currents) and patchy barrier layers detected equatorward of the sea surface salinity subtropical maxima. Complete characterisation of regional BL dynamics therefore requires the description of BL robustness through the determination of both BLT and BL permeability.

scholarly journals Stochastic generation of spatially coherent river discharge peaks for large-scale, event-based flood risk assessment

2018 ◽  
Author(s):  
Dirk Diederen ◽  
Ye Liu ◽  
Ben Gouldby ◽  
Ferdinand Diermanse ◽  
Sergiy Vorogushyn
Keyword(s):  
Risk Assessment ◽  
Flood Risk ◽  
River Discharge ◽  
Large Scale ◽  
Time Window ◽  
Insurance Industry ◽  
Flood Risk Assessment ◽  
Data Set ◽  
Discharge Data ◽  
Short Time Window

Abstract. Flood risk assessments are required for long-term planning, e.g. for investments in infrastructure and other urban capital. Vorogushyn et al. (2018) call for new methods in large-scale Flood Risk Assessment (FRA) to enable the capturing of system interactions and feedbacks. With the increase of computational power, large-scale, continental FRAs have recently become feasible (Ward et al., 2013; Alfieri et al., 2014; Dottori et al., 2016; Vousdoukas, 2016; Winsemius et al., 2016; Paprotny et al., 2017). Flood events cause large damages worldwide (Desai et al., 2015). Moreover, widespread flooding can potentially cause large damage in a short time window. Therefore, large-scale (e.g. pan-European) events and for instance maximum probable damages are of interest, in particular for the (re)insurance industry, because they want to know the chance of their widespread portfolio of assets getting affected by large-scale events (Jongman et al., 2014). Using a pan-European data set of modelled, gridded river discharge data, we tracked discharge waves in all major European river basins. We synthetically generated a large catalogue of synthetic, pan-European events, consisting of spatially coherent discharge peak sets.

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.

The geography of numerical mixing in a suite of global ocean models

2021 ◽  
Author(s):  
Ryan Holmes ◽  
Jan Zika ◽  
Stephen Griffies ◽  
Andrew Hogg ◽  
Andrew Kiss ◽  
...  
Keyword(s):  
Ocean Circulation ◽  
General Circulation ◽  
Horizontal Resolution ◽  
Global Ocean ◽  
Vertical Diffusivity ◽  
Mixing Parameters ◽  
Ocean Models ◽  
Numerical Mixing ◽  
Comparable Magnitude ◽  
Ice Model

<p>Numerical mixing, the physically spurious diffusion of tracers due to the numerical discretization of advection, is known to contribute to biases in ocean circulation models. However, quantifying numerical mixing is non-trivial, with most studies utilizing specifically targeted experiments in idealized settings. Here, we present a precise method based on water-mass transformation for quantifying numerical mixing, including its spatial structure, that can be applied to any conserved variable in global general circulation ocean models. The method is applied to a suite of global MOM5 ocean-sea ice model simulations with differing grid spacings and sub-grid scale parameterizations. In all configurations numerical mixing drives across-isotherm heat transport of comparable magnitude to that associated with explicitly-parameterized mixing. Numerical mixing is prominent at warm temperatures in the tropical thermocline, where it is sensitive to the vertical diffusivity and resolution. At colder temperatures, numerical mixing is sensitive to the presence of explicit neutral diffusion, suggesting that much of the numerical mixing in these regions acts as a proxy for neutral diffusion when it is explicitly absent. Comparison of equivalent (with respect to vertical resolution and explicit mixing parameters) 1/4-degree and 1/10-degree horizontal resolution configurations shows only a modest enhancement in numerical mixing at the eddy-permitting 1/4-degree resolution. Our results provide a detailed view of numerical mixing in ocean models and pave the way for future improvements in numerical methods.</p>

scholarly journals Forward modelling of tree-ring width and comparison with a global network of tree-ring chronologies

2014 ◽  
Vol 10 (2) ◽  
pp. 437-449 ◽  
Author(s):  
P. Breitenmoser ◽  
S. Brönnimann ◽  
D. Frank
Keyword(s):  
Data Assimilation ◽  
Tree Ring ◽  
Ring Width ◽  
Global Network ◽  
Threshold Temperature ◽  
Tree Ring Width ◽  
Data Set ◽  
Observation Operator ◽  
Tree Ring Data ◽  
Wide Range

Abstract. We investigate relationships between climate and tree-ring data on a global scale using the process-based Vaganov–Shashkin Lite (VSL) forward model of tree-ring width formation. The VSL model requires as inputs only latitude, monthly mean temperature, and monthly accumulated precipitation. Hence, this simple, process-based model enables ring-width simulation at any location where monthly climate records exist. In this study, we analyse the growth response of simulated tree rings to monthly climate conditions obtained from the CRU TS3.1 data set back to 1901. Our key aims are (a) to assess the VSL model performance by examining the relations between simulated and observed growth at 2287 globally distributed sites, (b) indentify optimal growth parameters found during the model calibration, and (c) to evaluate the potential of the VSL model as an observation operator for data-assimilation-based reconstructions of climate from tree-ring width. The assessment of the growth-onset threshold temperature of approximately 4–6 °C for most sites and species using a Bayesian estimation approach complements other studies on the lower temperature limits where plant growth may be sustained. Our results suggest that the VSL model skilfully simulates site level tree-ring series in response to climate forcing for a wide range of environmental conditions and species. Spatial aggregation of the tree-ring chronologies to reduce non-climatic noise at the site level yielded notable improvements in the coherence between modelled and actual growth. The resulting distinct and coherent patterns of significant relationships between the aggregated and simulated series further demonstrate the VSL model's ability to skilfully capture the climatic signal contained in tree-ring series. Finally, we propose that the VSL model can be used as an observation operator in data assimilation approaches to reconstruct past climate.

scholarly journals Infectious Disease Hospitalizations Among American Indian/Alaska Native and Non–American Indian/Alaska Native Persons in Alaska, 2010-2011

2016 ◽  
Vol 132 (1) ◽  
pp. 65-75 ◽  
Author(s):  
Prabhu P. Gounder ◽  
Robert C. Holman ◽  
Sara M. Seeman ◽  
Alice J. Rarig ◽  
Mary McEwen ◽  
...  
Keyword(s):  
Infectious Disease ◽  
American Indian ◽  
Alaska Native ◽  
Rate Ratio ◽  
Common Reason ◽  
Data Set ◽  
Discharge Data ◽  
Public Health Programs ◽  
Hospitalization Rates ◽  
Population Rate

Objective: Reports about infectious disease (ID) hospitalization rates among American Indian/Alaska Native (AI/AN) persons have been constrained by data limited to the tribal health care system and by comparisons with the general US population. We used a merged state database to determine ID hospitalization rates in Alaska. Methods: We combined 2010 and 2011 hospital discharge data from the Indian Health Service and the Alaska State Inpatient Database. We used the merged data set to calculate average annual age-adjusted and age-specific ID hospitalization rates for AI/AN and non-AI/AN persons in Alaska. We stratified the ID hospitalization rates by sex, age, and ID diagnosis. Results: ID diagnoses accounted for 19% (6501 of 34 160) of AI/AN hospitalizations, compared with 12% (7397 of 62 059) of non-AI/AN hospitalizations. The average annual age-adjusted hospitalization rate was >3 times higher for AI/AN persons (2697 per 100 000 population) than for non-AI/AN persons (730 per 100 000 population; rate ratio = 3.7, P < .001). Lower respiratory tract infection (LRTI), which occurred in 38% (2486 of 6501) of AI/AN persons, was the most common reason for ID hospitalization. AI/AN persons were significantly more likely than non-AI/AN persons to be hospitalized for LRTI (rate ratio = 5.2, P < .001). Conclusions: A substantial disparity in ID hospitalization rates exists between AI/AN and non-AI/AN persons, and the most common reason for ID hospitalization among AI/AN persons was LRTI. Public health programs and policies that address the risk factors for LRTI are likely to benefit AI/AN persons.

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