Science topic

# Physical Oceanography - Science topic

Physical oceanography is the study of physical conditions and physical processes within the ocean, especially the motions and physical properties of ocean waters.
Questions related to Physical Oceanography
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I am interested in analyzing satellite-derived swell spectra data from Sentinel 1. This is a L2 product that contains different wave properties for each vignette, which is currently maintained by Copernicus:
Does anyone knows how to access this data? I tried exploring the links available and could only find handbooks and technical information about the data, but not the data itself.
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For the RHUM-RUM project, we are writing a SKS paper and I try to review SKS measurements carried out in the context of Mantle Plumes with or without ocean-bottom seismometers.
Hello, We are now making a second attempt at the Cape Verde. I will keep you informed.
Vest regards
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Discussion of the state of art on the application of the Ertel's potential vorticity theorem in atmospheric physics & physical oceanography.
Prof. H. Ertel generalized Rossby's work proposal of 1939. Prof. Rossby firstly proposed that instead of the full three-dimensional vorticity vector, the local vertical component of the absolute vorticity is the most important component for large-scale atmospheric flow.
Via an independent paper published in 1942, Prof. Ertel identifying a conserved quantity following the motion of an air parcel proved that a certain quantity called the Ertel potential vorticity is also conserved for an idealized continuous fluid.
A very complete review on Ertel potential vorticity theorem, thank you for suggesting its reading, Prof. Aref Wazwaz .
Best Regards.
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I am interested in the Cenozoic history of surface circulation in the Atlantic Ocean, particularly in the subtropical and tropical regions. However, most information I have found so far is related to the North Atlantic.
In particular, I would like to know if the main currents and countercurrents have changed their intensity, in response to climatic and tectonic dynamics during the last 66 million years. What are the evidences for these changes? What literature would you recomend for solving questions on this topic?
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Are filters the only way or it can be done by following other algorithms.
Above mentioned pl66tn function is available in https://github.com/sea-mat/bobstuff/blob/master/pl66tn.m
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Physical oceanography
Oceanography
Satellite oceanography
You may check sentinel 3 data provided by ESA.
Best of luck!
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I do not have the PAR data. Fluorescence can be detected from dead particles too, but can it be utilized to get an idea about the euphotic depth.
Have a look at our paper, "Resolving the Euphotic Zone," Deep-Sea Research I, vol. 83, pp. 45-50. We propose that the biological compensation depth is roughly equivalent to the depth of the base of the fluorescence maximum.
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I need your help and guidance in a paper using ARIMA modeling. I am working on sea surface temperature modeling based on MODIS remote sensing data, ARIMA model has been used with SPSS.
I am new with ARIMA so results are already obtained but unable to define proper methodology and explain results.
Well, I am using raster data averages that are in monthly from Aug 2002 toApril2020 (213 months). I used SPSS for ARIMA the model is (3,1,1) (3,1,1). As I am new with this, I need your help to understand the model equation and meaning of these R-squared, R-squared, RMSE, MAPE, MaxAPE, MAE, MaxA, and Normalized BIC in model fitting.
I need to know model equation how to write this and SPSS based results interpretation. Though I have model results already.
Your help will be much appreciated. Would you like to help me with this?
If your result is SARIMA(3,1,1)(3,1,1) it means that you have both seasonal and nonseasonal autoregressive orders of 3, moving average of orders 1 and orders of difference of 1.
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I need recommendation on getting reputable journals in the areas of physical oceanography
If you are looking for a reputable Journals in Physical Oceanography you should first look to the Journal impact factor. (IR) .
So from my experience if you wish to publish in peer reviewed Journals,
I recommend the following Journals
1- Journal of Progress in Oceanography (Elsevier)
2- Journal of Dynamics of Atmospheres and Oceans (Elsevier)
3- Journal of Marine Science and Engineering (MDPI)
There are others such as Journal of Physical Oceanography , Ocean modelling ...
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I am a 4th-year undergraduate student from BSMR Maritime University, Bangladesh. By curriculum, we have to carry out a thesis (Credit-6) in the final year.
I am interested in physical oceanography, acoustical oceanography, satellite oceanography. But the dear respected guide, if you have a better idea regarding my interesting field as well as other fields which may become important in the near future, you may suggest.
Your kind suggestion will help me a lot.
Dear Alamgir,
There are too many interesting topics, these some remote sensing of oceanography applications could help you!
- coastal erosion by GIS & RS
- Coral reef change detection
- water quality variables obtained by satellites
- Sea level rise
Best of luck!
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Hi,
I'm trying to merge two chlorophyll datasets from different sensors by applying linear regression on their data overlap. The journal that I'm following log transformed (base 10) the data from both datasets before applying regression, and then used the resulting coefficients to correct one of the datasets. This means I have to log transform all my data to create my merged time series. However, I am hoping to use untransformed chlorophyll in the end.
My questions are (1) is it necessary to log transform the data in this situation, or just directly input untransformed data for regression? (2) If I do use the coefficients from the log-log regression, how should I apply it to the uncorrected dataset? Thank you very much!
Justin -
Could you be using logs to reduce heteroscedasticity?
It sounds like you want to use the overlap in data sets to see how one predicts for the other, and then assume that relationship holds up outside of that set? Hopefully you have reason to think that. If you have enough "overlap" data, perhaps you can see if you get compatible results when you do this for the first half of these "overlap" data, and then for the second half, considering the estimated variances of the prediction errors, or at least the standard errors of the slopes.
At any rate, to consider heteroscedasticity, I would avoid any transformations and use weighted least squares regression, considering heteroscedasticity in the error structure. The first link below provides some examples, and the next is for a tool you can use to do this.
However, it sounds like you should also look into serial correlation. That isn't an area I can help you with though. I've worked more with finite populations than time series. I suggest you might want to research "generalized least squares" (GLS regression).
Best wishes - Jim
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I'm trying to obtain a gridded bathymetric dataset of a certain region for use in a model, but all of the openly accessible products that I'm aware of (GEBCO, SRTM+) are very poorly constrained by in-situ observations in this region so are mainly based on gravity data. Unfortunately, I know as a fact that this has introduced some major errors (e.g. islands that don't exist).
I have point depth observations for this region from various historical studies which have not been incorporated into the above data products, and I would like to use them to modify the GEBCO grid to nudge depths in incorrect regions but I was wondering if there's an established method for doing this without introducing serious artefacts.
Hi Volney Junior Borges de Bitencourt, thanks for your reply. Just to check I've understood this method, the suggestion is that I carry out a weighted interpolation based on a composite of the DEM and measured values? I will give this a try but my (possibly naive) concern is that this would result in obvious bumps around my measured points since in many locations, the elevation difference between these points and the DEM is really extreme, and the spacing of observed points is much higher than the DEM resolution.
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Many papers estimate near-inertial energy flux as the product of wind stress and near-inertial current, where the wind stress is estimated by the bulk formula, which only gives a total amount of wind stress, no matter what frequency it is. Dose wind stress at all frequency could input energy into near-inertial current? If so, how? It will be appreciated if you answer this naïve question.
Thank a lot for your answer. The paper you shared did helped a lot on distinguish and verify the effect of daily wind. But the paper also use the bulk formula estimating the wind stress, which is not capable to exclude the effect of surface wave. But the paper did open an new pathway for me on how to verify the effect of different scale of motions. Thank you very much for your help! @Auad
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I want to calculate MLD from CTD data, while going through the literature I found different criteria for density (0.1, 0.3, 0.03, 0.25 etc density difference from the surface). What determines the density difference?
Experimenting with different criteria is the way to go as L. J. Hamilton suggested. Plot number of profiles with the UML depth and visually check, how the criteria works.
One might consider also vertical density gradient criteria instead of density difference from surface. I tried and played a lot with this and ended up gradient criteria depending on background stratification:
You can also check the paper discussing the topic:
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Downwelling due to negative wind curl.
using the temperature and salinity profile, you can compute the potential density at each points and draw the isopycnal, the downward movement of isopycnals indicate the downwelling phenomina
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This is in relation to the sampling done at various stations along a cruise track at different times of the day. The surface temperature would be affected by the time of the day it was sampled. How can I eliminate that difference to look at the trend?
Working with time-of-day as a factor will be a challenge because I assume your sampling times are random randomly spaced. That means you might be better off fitting for a trend plus some model of diurnal variation. The problem is that latter can take many functional forms, depending on solar forcing, whether there is nighttime convection, and so on.
I would advise starting by regressing to a formula that has a trend, plus both a sine() and a cosine() with period one day. (Using both sin and cos lets you find the phase, but still in a linear regression, which is easier to deal with than a nonlinear one, unless you are experienced.) Then add a twice-daily harmonic. Then add a thrice-daily harmonic. By comparing the results you may start to learn how the diurnal variation is affecting your estimate of the trend.
I would start with artificial data, so you can test the accuracy. AIC or other methods should be used to avoid overfitting. (If you don't know what AIC means, you ought to give yourself some time to learn elementary stats, before trying anything complicated with your data.)
Whether you will see a linear trend is questionable. I've never seen such a simple pattern in ocean data. So you might want to start by fitting this sort of sequence of diurnal models, then removing the diurnal signal, and then simply plotting the results, rather than expecting a trend.
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I have encountered several ways to detect ocean eddies: Okubo-Weiss, Vector Geometry, winding angle, from SST fronts, etc. However I don't know which one to use. Does a method differ in detecting eddies with latitude or region? I also find that validation of some methods require experts looking at the SLA and geostrophic velocity maps but it has also high uncertainties.
Regardless of the method, an important thing is to consider the methods uncertainty in your results. Indicators such as Success of Detection Rate (SDR, identifying those eddies that exist), and Excess of Detection Rate (EDR, identifying as an eddy something that is not) should be part of your results. Some methods publish those (or others) indicators in their description, others don't. For an example, see Fig. 2 of Chaigneau et al (2008), where their method has a similar SDR as using Okubo-Weiss method (~90%), but much lower (but still ~20%) EDR.
My suggestion is to use a method of your choice and then do a manual identification of 10-20 sample images, to validate the code in your results by visually identifying the eddies. The more colleagues that can help your with this, the better.
REF: Chaigneau, A., Gizolme, A., & Grados, C. (2008). Mesoscale eddies off Peru in altimeter records: Identification algorithms and eddy spatio-temporal patterns. Progress in Oceanography, 79(2-4), 106-119.
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I'm trying to plot U and V vectors in ArcGIS. I followed the method:
In which, point no. 7) Choose <expression> in the drop-down list was not available in 9.3 version.
To do this in other way, I added a field in the attribute table "Rotation".
Using Filed Calculator, I tried the 'function' written in point no. 9)
9). Specify one of the following expression:
Oceanographic Convention: (180/3.14) * Atn2([u],[v])
Meteorological Convention: (180/3.14) * Atn2([u],[v])+180
It was failed due to error in the code.
What is the correct code to write the "Oceanographic Convention: (180/3.14) * Atn2([u],[v])"?
Or is the any other way to plot in Arc?
Thanks.
How can I plot U and V wind vectors in ArcGIS 9.3
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Hello Everyone.,
I am having confusion regarding to calculate wave breaker angle.
wave breaker angle was calculated as the difference between the peak wave direction and the direction normal to the depth contour.
I don't know how to find breaker angle in the right manner.
Thank you in advance, who helped me
This paper may help in your research Direct Formula to Compute Wave Height and Angle at Incipient Breaking, JWPCE, ASCE
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Ice fields significantly limits the wind waves growth and propagation. Is it any instruments to use grided Ice fields in SWAN Wave model?
It is a very big limitiation for using SWAN model. In wavewatch3 all features for shallow water was added and ice module working good.
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We have two super moon next January (1st and 31th Jan 2018). If the distance between two super moon is 412 days, how it is possible?
Are the super moons alarm for marine activities?
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I have wave spectra time series and I use some partitioning and tracking algorithms to identify swell events and wind sea events. My aim is to model separately frequency time evolution in a swell event case and a wind sea event case.
- In case of swell event, since the swell celerity in deep water is g/(4pf), the frequency of waves generated at a single remote location and arriving at some observation point increases linearly with time. According to this, I choose an increasing linear model for pic frequency time evolution in a swell event.
- Now, what kind of model can I choose in wind sea event case? Actually I use a decreasing linear model assuming that the energy transferred by wind to sea water contribute to decrease the frequency. Is it a coherent hypothesis? Can you recommend another model to me?
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Hi, everyone.
there are many papers about river plume. But each paper looks from a different facet such as salinity, temperature distribution, density, currents and etc. I need a book to know river plume system basically and comprehensively. can any one offer the book?
thanks a lot.
Thanks a lot.
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I want to use ocean data view to view my data  (salinity, water temperature and bathymetry) for use in my research
Hi, you can use Ocean Data View to plot/view time series data.
Use "View->Derived Variables" and request the "Time (station date&time)" derived
variable.
or search online by keywords"Ocean Data View Instructions to generate time series plots"
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Currentmeter data (u, and v current, and temperature at 35m depth) have no correlations with local longshore wind. However, if I calculate the theoretical Ekman transport (or upwelling), I get some reasonable numbers. I am wondering if I can invoke the above lack of correlation to ignorer Ekman theory in my study region. Or should I proceed with some caution by assuming only a fraction of the theoretical Ekman transport actually occurs despite no correlation between wind and current? Where should the factor for the fraction come from? There is one limitation: I don’t have measurements at depths shallower than 35 m to look at correlations with the wind. The Ekman depth at my location is roughly 30 m.
Thanks Guillermo. Yes, I do have wind data and estimated the Ekman upwelling strength, which I think is acceptable (5-10 m/day).  The problem is that I don't have the evidence for the local wind effect on upwelling to accept the theoretically calculated Ekman upwelling strength. Hence, I am searching for a sound reason to include only a fraction of that upwelling in a model.  The current meter data comes in hourly time resolution but I low pass filter them to get rid of tidal components.  I am in a coastal region (southern Vancouver Island) and yes there are wind speed and direction gradients  along the west coast of North America with less upwelling favorable winds near my region. It appears now the poor correlation between current (from depths shallower than mine) and local wind in my study region has been documented in another work . I know some upwelling regions where observed water properties were satisfactorily explained without Ekman upwelling (Best example is a paper by Allen J Clarke, http://onlinelibrary.wiley.com/doi/10.1029/JC084iC07p03743/abstract).  When it comes to my region, the issue of whether Ekman upwelling is negligible is not settled. Therefore, including at least a fraction of it in a model is what I am convinced to do.
ps. I use reanalysis wind with 32 km grid spacing and wind location is not a problem. Some grid points are right next to the mooring.
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im a Master degree candidate,i need a literature'Statistical variability of sea state parameters as a function of wave spectrum' to obtain a formula in it .but i cant download it anywhere
I guess, Liu means the paper from Goda 1988?! Its probably not the paper, Jan has mentioned?!
Yoshimi Goda, STATISTICAL VARIABILITY OF SEA STATE PARAMETERS
AS A FUNCTION OF WAVE SPECTRUM, Coastal Engineering in Japan, Vol. 31, No. 1, 1988
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I want achieve anomaly position of itcz.
1- get the (apr1980_1.jpg) from grads(use the ECMWF data)
2-I draw itcz line in photo shop(same apr1980_11)
3- Finally achieved this(apr1980_2.jpg)
4-In MATLAB it(apr1980_2.jpg) was Digital
thank you(it would be definitely do-able using GrADS maxloc() function. You may want to further polish with some maskout() function to provide any criterion of your liking)
it is very good. thank you very much
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I am analysing a coastal time-series of hourly temperature and salinity measurements. I have calculated the density using Gibbs seawater toolbox (TEOS10). In addition I have also calculated the seawater density/stability ratio $R_{\rho}$,
$R_{\rho} = \frac{\alpha \Delta\Theta}{\beta \Delta S_A}$.
Specifically, I want to distinguish between density changes affected by either changes in temperature or salinity. So far I have just seen articles analysing the spatial distribution of the density/stability ratio, either vertical or horizontal, and mentioning that when $-1 < R_{\rho} < 1$, the density is affected mostly by changes in salinity.
Could anyone please suggest further references, especially analysing this ratio using time-series?
Cheers!
I think your interest to examine these temperature and salinity density/stability ratio on the coastline rather on the open water. If so, I suggest you look in other factors i.e., tidal chandes, local current circulation and bathymetry.
These elements are affected local dwillers in many ways i.e., induce spawning
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I have been wondering what would be the best strategy to assimilate moored ADCP and current meter data. In my particular case, I have several moorings (approx. 30) scattered through a regional domain. M2 and K1 internal tides are important in a portion of the domain.
Usually, the uv data is lowpass filtered before assimilation (lets say 48h cut freq.). However, this eliminates any improvement the assimilation can have on the representation of high frequency processes. My experience with HF Radars showed that assimilating data with 2h resolution can reduce phase errors for both internal and barotropic tides.
I wonder if someone else have been assimilating high frequency currents in regional ocean models.
I am using ROMS with strong constraint 4DVar.
Thank you Guillermo.

In this paper they assimilate data from an on-board ADCP. The data is "averaged" to remove small scale features not represented by the model.
My case, however, is a little different since the ADCP is moored.
The model is able to reproduce the high frequency I am interested on. Given the processed data is provided hourly, there should not be any "mandatory" a priori filtering for the assimilation...
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Air-sea interaction
I had generated some sketches for the air-entrainment, bubble formation and buoyant degassing processes occurring during plunging breaking for my review article.
Here's a link to the paper. I hope this helps. Best regards.
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SST should be along Arabian sea and Bay of Bengal around Indian Waters.
Hello Sri Hari,
You can check for SST data from the following websites. https://climexp.knmi.nl/select.cgi?id=someone@somewhere&field=coads_sst
Check the source of the data in the beginning of the page. Go to the end of the page and download the NetCDF file.
Cheers :-)
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Dear all, good afternoon!!
I'm running two numerical experiments (HYCOM model) and compare them to a reference (WOA climatology).
My first experiment (control one) gives a bias when compared to the reference: (expt1 - ref). I want to evaluate how the difference brought by the effect introduced in the second experiment (wave-modified surface stress: expt2 - expt1) improve or worsen the model results.
It seems hard to gather everything in a single map since the bias can be positive or negative and the effect brought can over compensate the original bias (move the SST toward the reference more than the original bias and give a new bias of opposite sign).
All I could figure out is to get rid of the sign and use error instead of bias, where error = abs(bias). I have then the error variation: abs(exp2-ref) - abs(expt1-ref). I can divide it by the original error to get the relative variation and know for instance if the original error is over compensated but it gives noisy maps for the whole domain.
I guess I could focus on specific areas like the Benguela resurgence and the Brazil-Malvinas convergence area. Is there any classic approach to show and evaluate this variation in a nice way?
Have a good day,
Nicolas
Dear Nicolas,
You can also use a Bland Altman diagram by ploting the series of differences as a function of the mean of the series and compute the limit you admit for the differences (e.g. +/- one sigma). One limit of the method is the gaussian distribution of the difference series
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HI.
I need sea surface salinity data in northwest of Persian gulf near the Arvandrud river. Does anyone know how can i obtain this data? Does anyone know how can i obtain ROPME 2006 data in Persian gulf?
you can try to find it in marine copernicus
it's free
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Hello, I need in-situ data include sea surface salinity at near of Arvandrud (Shatt ell Arab) river Mouth in Persian gulf. I am grateful if anyone can help me to find this type of data such as Ropme 2006 databases. Thank you
Abbas,
It would be better to ask the relevant institution that concerns about the records of that region at least they might guide you to your goal.
M. Basel
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Trying to get information on the Indian Ocean Dipole cycle!
Hello Tom,
Apologies for my delayed response. Many thanks for letting know about the paper.
Best regards,
Netra
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Abundance, number of species and diversity
Very interesting question. The bottom current has an effect on detrital input which in turn, may influence the feeding activities of macrobenthic polychaete community.
Regards.
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I'm aware that K-H instabilities arise when there are two overlying parallel flows of different shear and density.  In this case the instability would occur at the interface.  What of an instance where the flows are perpendicular?  I haven't come across any literature discussing this possibility.  Anyone know of a source?
The problem that I'm investigating is related to topics in atmospheric science, specifically the planetary boundary layer. A lot of overlap can be found between the two branches, but I'm looking at a specific problem that might require a detour in this direction. I have found laboratory experiments discussing the interaction of two jets, but these are narrow jets, and I'm not sure the same would result if the jets were much broader O~100km.
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Vertical land movements need to be removed from the tide gauge records in order to convert the time series of relative sealevel change to absolute sea levels. At global scale, the vertical crustal uplift due to the isostatic readjustment of the Earth’s crust and mantle
From the great webpage of Colorado Sea level Group: "the ocean basins are getting slightly larger since the end of the last glacial cycle. GIA is not caused by current glacier melt, but by the rebound of the Earth from the several kilometer thick ice sheets that covered much of North America and Europe around 20,000 years ago. Mantle material is still moving from under the oceans into previously glaciated regions on land. The effect is that currently some land surfaces are rising and some ocean bottoms are falling relative to the center of the Earth (the center of the reference frame of the satellite altimeter). Averaged over the global ocean surface, the mean rate of sea level change due to GIA is independently estimated from models at -0.3 mm/yr (Peltier, 2001, 2002, 2009; Peltier & Luthcke, 2009)." Check it, ypu will probably find a good answer: http://sealevel.colorado.edu/content/what-glacial-isostatic-adjustment-gia-and-why-do-you-correct-it
To go deeper, my suggestions is to read Peltier, as Arvind suggested you: Peltier, W. R. (2004). Global glacial isostasy and the surface of the ice-age Earth: the ICE-5G (VM2) model and GRACE. Annu. Rev. Earth Planet. Sci., 32, 111-14, although he is more phocused in the modelling on every paper he publishes, and I do not know if you are so interested on theses details.
Nevertheless, do not only take into account these isostasic models. If you are dealing with local data, check tide gauges time series, and especially, compare them with global measn sea level rise time series (Church and White, 2012) and altimetry satellite data, to check what is going on in your area. Peltier model is clear for higher lattitudes but it is still unclear about mid latitudes.
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I am using the SWAN wave model to hindcast waves in an estuary. I have an offshore boundary condition containing some swell energy. I output the energy spectrum in my fine resolution domain but the swell energy does not show up anywhere in the time series. The energy spectrum seems to be shifted toward higher resolution when comparing to field measurements.
Hi Thomas,
What is the directional resolution you use in your SWAN discretization for swell?
If you scroll down to the last three paragraphs on directional space:
You will see that for swell, a directional resolution of 2 degrees or less may be required, for swell with a directional spreading of less than 10 degrees.
Heng
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if flood basalt is out pored on land as well as ocean then what will be the difference in magnetic behavior over land and ocean??
@Alastair Bain McDonald,,, thank you sir
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"Cold upwelled water alters local weather. Weather onshore of regions of upwelling tend to have fog, low stratus clouds, a stable stratified atmosphere, little convection, and little rain." from the book "Introduction to Physical Oceanography "(Robert H. Stewart). If the upwelled water in the coastal area is relatively warmer than ambient water, how does it change the local weather?
Upwelling, such as that typical in eastern boundary current regions (California Current, Peru-Chile Current, Benguela Current), brings relatively cooler water to the surface. This creates cool, moist air over the ocean surface. If this air moves over the relatively warmer land mass, the moisture condenses and creates fog.
There is a natural onshore flow that develops in response to the warm thermal low that typically sets up over the land mass adjacent to the eastern boundary, such as in the SW US. This pattern draws cooler marine air over the land, resulting in a persistent foggy condition during the local summer (high upwelling and warm continent). Local vegetation can adapted to this condition, and agriculture interests take advantage of it.
One interesting area of study is how anthropogenic warming will affect this pattern. The hypothesis is that global warming will lead to a warmer continent AND greater upwelling-favorable winds, which may result in greater fog. I am not aware of any substantive study to confirm this. One problem with looking at historical records of fog and SST is that other factors contribute to fog in coastal regions, and the fog is spatially very heterogeneous and localized.
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I'm working on modelling the propagation and dissipation of waves in both the marginal ice zone and also in the ice pack. My understanding is that in the ice pack we may get both scattering (from changes in ice thickness as described in papers by Squire for example) and dissipation which may occur due to the viscosity in the water (this I know how to deal with) and also the creep effect in the ice. I've found the 1973 paper by Wadhams about this but I imagine that there may be more recent updates on the ice properties ... and that these properties may be different for steady or oscillating loads. I just started to read a few papers by Timco, but I am a bit lost.
So, basically I was going to use Wadhams' theory, with some updates on the mechanical properties of sea ice. Any advice is welcome.
Thanks to all. I finally found an answer in Cole et al. (JGR 1998): "Cyclic loading and creep response of aligned first-year sea ice" which is generally consistent with Wadhams (JGR 1973), in proposing a reduced B coefficient for creep. This is now in version 5.10 of WAVEWATCH III (to be released in a few months) ... and was used for this paper:
But yes it is in general a function of ice temperature and thickness and floe sizes are very important parameters too.
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I've read that SST fronts stimulate biological productivity (e.g. Woodson and Litvin 2015, PNAS). But my question is how strong of a SST front is needed to significantly enhance productivity? Of course this will be dependent on a number of factors, but what is a rough estimate? Will a front with 1 ℃ SST change be relevant? Or is this only found with much bigger gradients (e.g. 10 ℃ change)?
I'm particularly interested in the application of this question in the Gulf of California, Mexico.
Particularmente en el Golfo de California ocurren demasiados procesos de diferente índole que resultan en frentes superficiales de temperatura. En el norte la mezcla de marea genera frentes térmicos de hasta 3 grados en el archipielago central, y frentes más difusos en el alto golfo. En el sur del golfo los procesos predominantes que generan frentes son la surgencia en invierno/primavera y los remolinos en verano, En la boca por otro lado la interacción con la corriente de California y el agua tropical generan frentes de masas de agua.
Entonces, todo el golfo es susceptible a los procesos de mesoescala, pero hablar de un frente superficial, sin tomar en cuenta su origen, dificulta evaluar en que medida promueve el aumento de la productividad.
Particularly in the Gulf of California too many different kinds processes resulting in surface temperature fronts. In the north, tidal mixing generates thermal fronts up to 3 degrees in the central archipelago, and more diffuse fronts in the upper gulf. In the southern Gulf, predominant processes that generate fronts are upwelling in winter / spring and eddys in summer. In the mouth, interaction with the California current and tropical water, and gulf water generate fronts throughout the year.
Then, the entire Gulf is susceptible to mesoscale processes, but talk of a surface front, regardless of its origin, difficult to assess to what extent promotes increased productivity.
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i'm confused on the differences between PSS and PSU for ocan salinity measurements. Im wondering are there any differences between them or almost similar??
Can anyone give me suggestion on how can i convert salinity unit from PSS to ppm or ppt? since most of my sources only convert between ppm,atm and other except PSS
The 'Pactical Salinity Scale' (PSS) was defined in 1978 and later promulgated by the UNESCO/ICES/SCOR/IAPSO Joint Panel on Oceanographic Tables and Standards in Sidney, BC, Canada, 1-5 September 1980. Because it makes no sense to say the salinity is , for example, 35 PSS, the term PSU was introduced, as the scale is composed of units. However, the use of PSU is discouraged and, because salinity is by definition a dimensionless parameter, it should simply be represented by a number. As practical salinity has been given the symbol S (cf. Unesco Technical Papers in Marine Science 45, 1985, or IAPSO Publication Scientifique No. 32, 1985), one should speak of a salinity of, for example, S = 35.
Burg Flemming
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I mean the temperature in the Philippine islands or its ambient maritime landmasses rather than its ambient surface ocean.
Dear Prof. Stigter, Thank you very much!
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Please see attached figure and note the high turbidity belt at 123.6 °E. This phenomenon was captured in March of 2013 (winter). What's the reason? Is it caused by sediments resuspension or other possible mechanisms? Propagating eddies as reported by Nagai et al. (2015)?
Many thanks for all the answers!
Please see the location of Transect A given in the attached Figures. The T, S, and Density profiles are also attached. This feature is just a snapshot of one cruise. Is the slope break sharp? There is a relative strong density gradient at 123.5 °E (with high turbidity). Can the density front lead to upwelling? I remember that the wintertime upwelling off the Zhe-Min Coast is due to the strong density front (Qiao et al., 2006JGR). Are they similar or different?
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Topic :
" Mixing processes and turbulence in the surface and bottom boundary layers in the oceans and lakes"
Kindly if you have then help me ? In advance thank you...
Basic information can be found in McWilliam note:
Large, W G., J.C. Mc Williams, and S.C. Doney, 1994: Ocean vertical mixing: A review and a model with a nonlocal boundary layer parameterization. Rev. Geophys.,32, 363-403.
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I want to determine light intensity profiles at different depths (down to 1000m) in the North Atlantic ocean. Is there any databases which provide this information ready available?
Dear Peter,
You may find other indications in Paulson and Simpson (1977) JPO 7, 952-956 and in Prieur and Legendre (1988) in "Toward a theory on biological-Physical interactions of the world ocean" (Elsevier, New-York). But the best for you is the climatology of mean optuical properties of Simonot and Letreut (1986), JGR, 91, 6642-6646 that will provide you the Jerlov's coefficients for the North Atlantic basin
Best
G.C.
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Does anyone have a reference that gives the exact number, as I cannot find the original paper online anywhere!
Thanks
Our article published in peer-reviewed Journal "Communicative & Integrative Biology". A few major points discussed in the paper:
(1) Brain is not the source of consciousness.
(2) Consciousness is ubiquitous in all living organisms, starting from bacteria to human beings.
(3) The individual cells in the multicellular organisms are also individually cognitive entities.
(4) Proposals like “artificial life”, “artificial intelligence”, “sentient machines” and so on are only fairytales because no designer can produce an artifact with the properties like internal teleology (Naturzweck) and formative force (bildende Kraft).
(5) The material origin of life and objective evolution are only misconceptions that biologists must overcome.
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hi
i want to calculate Froude number in a positive estuary that its water column density and current velocity obtained by using numerical method. To calculate the Froude Number What formula should I use?
Hi  Abbas,
The Froude Number is broadly defined as a ratio of some current speeds over some wave phase speeds. Specifically in the estuaries, there are three forms of Froude Number.
• The densimetric Froude Number is defined as: Fm=uf/sqrt[g*h*(d_rho/rho)], that is the depth averaged flow velocity over the density abnormally induced internal wave velocity. In the "Fm" formula, "uf" is fluvial velocity defined as uf=Qr/A with A=cross-section area of the estuary Qr=riverine volume flux, "g" is gravitational acceleration, "h" is the estuary depth and "d_rho" is the density different between riverine water and sea water which has the density of "rho". The densimetric Froude Number was first given by Hansen and Rattray (1966) to classify the estuaries with the Stratification-Circulation diagram. They shown that the estuarine circulation depends entirely on the "FM". You could also link the densimetric Froude Number with bulk Richardson Number by simplifications. That is: Ri=[g/d_z*d_rho/rho]/[d_u/d_z]^2, cancel "d_z" in the numerator and in the denominator, and assuming the turbulent boundary layer is over whole water column (i.e. d_z=h), you would end up with Rib=[g*h*d_rho/rho]/d_u^2, then you might see Rib=1/Fm^2. BUT be aware that in the estuaries the stratification depth is usually much shallower than the turbulent boundary layer depth. It means that to cancel the "d_z" term in the numerator and in the denominator in the "Ri" calculation might not be physically correct.
• Other two not so commonly used Froude Numbers in the estuaries are barotropic Froude Number "FT" and baroclinic Froude Number "FB". They are defined as: FT=xi_M/h with "xi_m" the mean tidal amplitude and "h" mean estuarine depth, and FB=d/D*sqrt(d_rho_h/d_rho_v) with "d/D" the ratio of fresher upper layer thickness to saltier lower thickness and "d_rho_h/d_rho_v" the ratio of horizontal estuarine density difference to the vertical estuarine density difference. Both parameters are introduced by Jay and Smith (1988) to distinguish the highly stratified estuaries from weakly stratified ones.
The detailed descriptions about estuarine dimensionless numbers could be found in the book: "Estuaries, a physical introduction, 2nd Edition" by Keith R. Dyer, published in 1997.
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Does anyone know where I can source high resolution chlorophyll concentration data for the North Sea region from present day back to 2004 for free other than NASA Earth Observations (NEO)?
Any help would be greeted with the upmost appreciation.
Thank you,
Edward Lavallin
Give a lool to the Copernicus Marine Environmental Monitoring Service (CMEMS), formerly MyOcean.
There are various bio-physical parameters - including chlorophyll -  obtained both from Earth Observation data and models which are provided at different resolutions. In some cases the data series start from earlier than 2000.
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Such as in:
Triple collocation
Document NWPSAF-KN-TR-021
A simple version of TC and ETC results,  based on :
McColl, K. A., J. Vogelzang, A. G. Konings,
D. Entekhabi, M. Piles, and A. Stoffelen
(2014), Extended triple collocation:
Estimating errors and correlation
coefficients with respect to an unknown
target, Geophys. Res. Lett., 41,
6229–6236, doi:10.1002/2014GL061322.
c=cov(x);
q=[];
q(1)=sqrt(c(1,1)-c(1,2).*c(1,3)/c(2,3));
q(2)=sqrt(c(2,2)-c(1,2).*c(2,3)/c(1,3));
q(3)=sqrt(c(3,3)-c(1,3).*c(2,3)/c(1,2));
p=[];
p(1)=sqrt((c(1,2)*c(1,3))/(c(1,1)*c(2,3)));
p(2)=sqrt((c(1,2)*c(2,3))/(c(2,2)*c(1,3)));
p(3)=sqrt((c(1,3)*c(2,3))/(c(3,3)*c(1,2)));
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Hello all,
I have a wave buoy time-series of significant wave height (Hs) and wave period (Tz). I want to separate the series into swell (long wavelength, far field) and locally generated wind wave (storm) components for some further investigation into wave-tide interaction. Is there a theoretical limit that I can use to classify if a wave observed at time t; Hs(t) and Tz(t), is a "swell" or "storm" wave?
Matt
Having 'integral' properties of the wave field, as Hs & Tz it is IMPOSSIBLE to make a separation; a sum of say two contributions , far & local fields. The reason is that the 'Significant Wave' and 'wave period' are  properties derived from the wave spectra in ALL its contributions (if you only know the sum, it is just out of the question to separate 'contributions'). Only if you have the time series from which such integral properties were estimated, then it is (if the local and far fields have 'non-overlaping' spectra) plausible a separation.....via computing spectra & figuring out which peaks /bands to add as separate contributions.
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I have some tide gauge records (several months) recorded in a semi enclosed basin and need to know the surge fluctuations. I tried T-Tide package to separate tide and surge, but it seems that there are some de-tiding errors in the residuals. Could you please introduce me another software package, code to use?
The most straight forward way is to use harmonic analysis to create a tide time series and then subtract that from the data to create a residual. However, in our experience, there will always be some "tidal frequency" left overs for various reasons. A better way is to Fourier transform your time series and patch over the tidal bands in frequency space with random phase oscillations that match the adjacent spectrum. Then re-transform to time domain. This approach was successful for the long San Francisco tide gauge record. See: Bromirski, Flick, and Cayan, 2003. Storminess Variability along the California Coast: 1858 - 2000, J. Climate 16(6), 982-993. Your record is short, so that may create difficulty narrowing the spectral peaks, but on the other hand noise form errors and glitches will be easier to deal with.
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Hi
I try to use optimal interpolation and kalman filter method of data assimilation for water wave data with fortran and matlab. but before using these methods in wave modeling, I want to test my fortran and matlab codes with simple examples. so I tried to estimate a supposed simple quadratic equation with methods mentioned above but the results are Disappointing. could u plz give me a numerical example that helps me to learn these methods?
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We found 40m diameter stone rings around a WWI battleship off Gallipoli, Turkey and can't determine what type of explosive may have caused the impact craters (assuming they are in fact craters).
You may wish to check:
Robert H. Cole: "Underwater Explosions" , Princeton University Press (1948), reprinted in 1965 by Dover Publications Inc, in particular chapters 6, 7 and 8.
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How can I estimate the wave attenuation over Posidonia Oceanica with Simulating WAves Nearshore (SWAN)?
I haven't the program SWAN-VEG (Modelling wave attenuation by vegetation).
Thanks Carlo,
I think Collins coefficient is a good solution to this issue.
V.V.T
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There are models for the structure of hurricane winds (e.g. Holland, 1980, Holland et al., 2010) which are typically applied at the the sea surface for studies of air-sea interaction. We know that in the surface boundary layer, under neutral conditions, Monin-Obikov theory may be applied to find the wind speed as a function of altitude and this is an exponential curve (so called "law of the wall"). Is there any reason that the wind direction might also be a function of altitude? Has the vertical profile of wind direction in a hurricane ever been measured (at a stationary point in the hurricane reference frame)?
I have to respectfully disagree with Alastair McDonald's reply.  The upper air away from the surface does of course follow the cylindrical circulation (so long as you are still low in the atmosphere).  But the question is about wind close to the surface, which is governed not only by the pressure gradient and coriolis effects of the upper air, but also frictional effects from the surface.
The Eckman calculation is single column, and is indifferent to the large scale circulation.  In a low pressure system you see the effects as air near the ground cuts across the pressure contours at nearly 45 degrees, but upper air follows the pressure contours.  A hurricane is just a massive low pressure system.  The Eckman profile holds at each location, so that the wind near the ground inclines towards the local low pressure (not directly towards it) while higher  air will circulate perpendicular to the pressure.  Higher still the wind becomes vertical, then eventually switches to circulating the opposite direction.  But all this higher stuff is not Eckman circulation, and does not pertain to the question about surface winds.  About a km high the air is moving around the local low pressure; below it begins to turn so that near the ground it has a component towards the low pressure.
Over ocean, the friction is low ccmpared to land, so near the surface the wind will be closer to circulating around the low pressure than over land, but will still have a component towards the low pressure.
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Apart from the fact that the latter is not dependent on the concentration of suspended particles, what about general performance? I'd appreciate to know about the experience of someone who used both
Dear Nathan,
Thanks for your reply. In fact I just need the best possible estimation of the horizontal current at a fixed point. Current speed module and direction in N-S, E-W coordinates, that's all. My interest is to obtain time series of the current itself at the depth of deployment of the meter, and also to compute (horizontal) suspended sediment flux by means of a coupled turbidimeter.
Best regards, Jacobo
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Intercontinental dispersion through the cloud drafts is only a "possibility" which you have suggested, right? Other than not having previous records of the species in India, are there other reasons for reaching this assumption?
Thanks for the clarification, Felix. It is fascinating, and we should study these possibilities. If not the algae, we will get something else I am sure! We have CAIPEEX cloud experiments, but I am not sure if they can detect organic components.. let us see. Meanwhile, are there other instances of cloud drafts carrying algae (or algae-like) particles??
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We need to study more about dynamics of water temperature due to climate change and its effect on marine organisms in Indian Ocean
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I have a series of temperature since 1950 to 2000 year, measured with local station and I have a series of temperature since 2000 to 2015 measured with satellite. I have to combine the series and make some series times. The problem is that I have to normalize o standarize the data because it was measured with differents instruments. Any idea of how to do this? thank you so much.
Dear Francisco, satellite ground truth and weather stations provide readings that have in common the name "temperature" but are essentially different and need a calibration to be related to each other. This calibration should be made over a relatively long period of common readings, in wich both sources were active. Missin this calibration, the uncertainty may be large to very large. Yoiu may try to rely on a third station, that was common to the weather station and later to the satellite data. This triangulation increases uncertiainty but in better than nothing and your homogenization becomes more reasonable, being based on some objective reference attempt.
Good luck and good work!
Dario
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I have been working on some SAR data Sets like RISAT-1 and RADARSAT-2 , I have extracted the pixel information using python and I would like to know how this information can be used to extract wave and wind information over open ocean
Hi,
There are a few oceanography and climate libraries for python. You should check a list like this:
As for extracting the exact parameters you're requesting I would advise checking scientific literature (since I don't know how to do it). A quick google search for "RISAT-1 ocean waves" revealed this article:
You can request the full article here in research gate. I'm sure a more extensive search would reveal a lot more info on the subject.
Best of luck.
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I am correlating pCO2 with fluorescence in the Western basin of the Mediterranean Sea. This basin is oligotrophic, but in the spring blooms can occur. I was expecting during this season the pCO2 to decrease due to the biological activity, but the correlation coefficient is positive. What could be the cause behind that?
I do not agree with what Alastair has said, pCO2 depends on pH of the water, it is other way around, pH of the sea water is dependent on pCO2. moreover, blooms can be also limited by CO2 in the oceans if not having constitute CCM. an increase in pH has been observed many times with enhancement in phytoplankton biomass. However, I agree with the last part of your answer. and also what Koji has mentioned. This is possible that for warming or upwelling, significant amount of CO2 is added up to the surface water and there could be simultaneous uptake also by phytoplankton and enhancement of fluorescence. However, the net increase in CO2 could be more and hence positively correlating with the fluorescence. In the Oligotrophic condition under high solar light there can be photo-inhibition leading to net heterotrophy and can may not uptake considerable amount of pCO2. As Koji said, phytoplankton stock is also important.
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We can find on the world wide web many derivatives of the original model (GFDL) based on primitive equations. Is there any text to explain what are the differences between the various models?
If you want nice explanations about the difference between model and their numerical formalism you can check S. Griffies books especially:
Griffies, Stephen M., 2005: Some ocean model fundamentals In Ocean Weather Forecasting: An Integrated View of Oceanography, Berlin, Germany, Springer, 19-74.
cheers
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What are the chemical and isotopic elements that I have to analyze for detecting marine intrusion?
Hi you can proceed by analyzing hydrochemical composition, ionic ratios (Na+/Cl–, Ca2+/Cl–, Mg2+/Cl–, SO42-/Cl- and especially Br–/Cl– molar ratios; Ca2+/Mg2+ weight ratio; and chloride concentrations) and calcite-saturation index (SIcalcite) of seawater and groundwater from selected wells. Also, isotope analysis of (2H/18O, 3H, 14C, 34S).
Chloride/Br ratios are used to determine the causes of groundwater salinisation for water.
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I would like to have information on the temperature variations in the Pacific Ocean floor as you move north-south or west-east.
You could also look at the WOCE Pacific Atlas - see http://www-pord.ucsd.edu/whp_atlas/pacific_index.html   This is a graphical representataion of the data referred to by Loic in the previous answer.
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Due to subduction beneath various plates pacific is closing ocean. which are the other closing oceans? Is Mediterranean a closing one?
Hi Archana... while this is not my area of expertise, I do know that the Mediterranean Sea is closing between the north moving African plate and the European plate.  The Atlantic Ocean is opening wider at the mid-Atlantic ridge and the Pacific plate is subducting beneath the Asian and Australian Plates. The Australian and African plates are spreading making the Indian Ocean larger.
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I just start using R and I know there are several specific packages for oceanographers. Can anyone suggest me a good one for physical oceanography?
Thanks ;)
oce: Analysis of Oceanographic data
Developed by Dan Kelley
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I am looking to read comprehensive texts in Physical Oceanography and in the Evolution and Ecology of Infectious Diseases and am looking for direction into which texts may be the best to acquire.
Regarding the "evolution of infectious diseases" there are quite numerous papers in the field of palaeoparasitology, but nearly exclusively on material from archaeological and Quaternary contexts. Some recent review papers are:
Araújo, A., Reinhard, K., Leles, D., Sianto, L., Iñiguez, A., Fugassa, M., Arriaza, B., Orellana, N., Ferreira, L.F. 2011. Paleoepidemiology of intestinal parasites and lice in pre-Columbian South America. Chungara, Revista de Antropología Chilena: 43(2): 303-313.
Beltrame, M.O., Souza, M.V., Araújo, A., Sardella, N.H. 2014, in press. Review of the rodent paleoparasitological knowledge from South America. Quaternary International.
Bryant, V.M., Reinhard, K.J. 2012. Coprolites and archaeology: the missing links in understanding human health. New Mexico Museum of Natural History and Science Bulletin 57: 379-387.
Frías, L., Leles, D., Araújo, A. 2013. Studies on protozoa in ancient remains - A Review. Mem Inst Oswaldo Cruz 108(1): 1-12.
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In case you are interested in pre-Quaternary parasites, this is the reference list (not textbook or review-type papers):
da Silva, P.A., Borba, V.H., Dutra, J.M.F., Leles, D., da-Rosa, A.A.S., Ferreira, L.F., Araujo, A. 2014. A new ascarid species in cynodont coprolite dated of 240 million years. Anais da Academia Brasileira de Ciências 86(1): 265–269.
Dentzien-Dias, P.C., Poinar, G.Jr., de Figueiredo, A.E.Q., Pacheco, A.C.L., Horn, B.L.D., Schultz, C.L. 2013. Tapeworm Eggs in a 270 Million-Year-Old Shark Coprolite. PLoS ONE 8(1): e55007. http://dx.doi.org/10.1371/journal.pone.0055007
Hugot, J.P., Gardner, S.L., Borba, V., Araujo, P., Leles, D., Da-Rosa, Á., Dutra, J., Ferreira, L.F., Araújo, A. 2014. Did the dinosaurs have pinworms? Discovery of a 240 million year old nematode parasite egg in a cynodont coprolite sheds light on the early origin of nematode parasites in vertebrates. Parasites & Vectors 11-2014.
Poinar, G., Boucot, A.J. 2006. Evidence of intestinal parasites of dinosaurs. Parasitology. http://dx.doi.org/ 10.1017/S0031182006000138
Tweet, Chin, K., Murphy, N. 2006. Paleobiological implications of diminutive invertebrate burrows within probable gut contents of a hadrosaurid dinosaur from the Upper Cretaceous (Middle Campanian) Judith River Formation of Montana. Geological Society of America, Abstracts with Programs 38(7), p. 476. https://gsa.confex.com/gsa/2006AM/finalprogram/abstract_112739.htm
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Some recent review papers on palaeovirology:
Aswad, A., Katzourakis, A. 2012. Paleovirology and virally derived immunity. Trends in Ecology and Evolution 27(11): 627-636.
Feschotte, C., Gilbert, C. 2012. Endogenous viruses: insights into viral evolution and impact on host biology. Nature Reviews / Genetics 13, April 2012: 283-296.
Katzourakis, A. 2013. Paleovirology: inferring viral evolution from host genome sequence data. Phil Trans R Soc B 368: 20120493. http://dx.doi.org/10.1098/rstb.2012.0493
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Seamount subduction has been well studied especially since 2000 (Kodaira et al.). In some cases such as the 1946 Nankai earthquake (Mw 8.2), it has been suggested that seamounts act as a barrier and hence prevent earthquake rupture due to weak coupling. On the other hand Husen et al (2002), suggest that seamount acted as an asperity (and hence strong interplate coupling) in the 1990 Gulf of Nicoya earthquake (Mw 7). Is the debate still open or a conclusion has been reached on the role subducted seamounts play in earthquake generation?
I suppose, that subducting seamounts induce weak interplate coupling,  but they can sometimes result in the change of the subduction regime and to be the cause of the slabe break-up as we can see in west Pacific near south Kuril and north Japan.
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Hello.
I was wondering if anyone knows about the availability of free data on tides and currents in the Mediterranean area. In particular, I am interested in south central Mediterranean (Sicily and North Africa).
As for the winds, I have found this interesting resource http://www.windfinder.com/, which provides the data of one yea free of charger, while previous data must be purchased.
I was wondering if anything similar related to the tides and currents is currently available somewhere on the Web.
Best,
Gm A
Hello - you should contact "http://www.seadatanet.org" the network of European Ocean Data Centres (and beyond) as Sofia recommended.
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An implication of this modelling study is that the net export of carbon at intermediate depths to the open ocean increases as the shelf seas grow and in particular as the area of the stratified shelf seas increases.
Is there a proxy which could be used, possibly from the sediments across the shelf break to test this idea?
Many thanks for your prompt response. Excuse a Physical Oceanographers ignorance - but how well is the ratio preserved on glacial-interglacial timescales?
I'd guess a good test of the idea put forward in our GRL paper would be to look at ratios in cores at the shelf break and see if they change as the shelves flood, and so test the idea that carbon export to the ocean increases as region subject to seasonal stratification grows.
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