Sea state and rain: a second take on dual-frequency altimetry

TOPEX and Jason were the first two dual-frequency altimeters in space, with both operating at Ku- and C-band. Each thus gives two measurements of the normalized backscatter, sigma0, (from which wind speed is calculated) and two estimates of wave height. Departures from a well-defined relationship between the Ku- and C-band sigma0 values give an indication of rain.This paper investigates differences between the two instruments using data from Jason's verification phase. Jason's Ku-band estimates of wave height are ~1.8% less than TOPEX's, whereas its sigma0 values are higher. When these effects have been removed the root mean square (r.m.s.) mismatch between TOPEX and Jason's Ku-band observations is close to that for TOPEX's observations at its two frequencies, and the changes in sigma0 with varying wave height conditions are the same for the two altimeters. Rain flagging and quantitative estimates of rain rate are both based on the atmospheric attenuation derived from the sigma0 measurements at the two frequencies. The attenuation estimates of TOPEX and Jason agree very well, and a threshold of -0.5 dB is effective at removing the majority of spurious data records from the Jason GDRs. In the high sigma0 regime, anomalous data can be cause by processes other than rain. Consequently, for these low wind conditions, neither can reliable rain detection be based on altimetry alone, nor can a generic rain flag be expected to remove all suspect data

On the vertical phytoplankton response to an ice free Arctic Ocean

Rapidly retreating sea ice is expected to influence future phytoplankton production in the Arctic Ocean by perturbing nutrient and light fields, but poor understanding of present phytoplankton distributions and governing mechanisms make projected changes highly uncertain. Here we use a simulation that reproduces observed seasonal phytoplankton chlorophyll distributions and annual nitrate to hypothesize that surface nitrate limitation in the Arctic Ocean deepens vertical production distributions where light-dependent growth rates are lower. We extend this to interpret depth-integrated production changes projected by the simulation for an ice-free Arctic Ocean. Future spatial changes correspond to patterns of reduced surface nitrate and increased light. Surface nitrate inventory reductions in the Beaufort Gyre and Atlantic inflow waters drive colocated production distributions deeper to where light is lower, offsetting increases in light over the water column due to reduced ice cover and thickness. Modest production increases arise, 10% in a seasonally ice-free Arctic Ocean and increasing to 30% by the end of the century, occurring at depth

A tale of three islands: Downstream natural iron fertilization in the Southern Ocean

Iron limitation of primary productivity prevails across much of the Southern Ocean but there are exceptions; in particular, the phytoplankton blooms associated with the Kerguelen Plateau, Crozet Islands and South Georgia. These blooms occur annually, fertilized by iron and nutrient-rich shelf waters that are transported downstream from the islands. Here we use a highresolution (1/12°) ocean general circulation model and Lagrangian particle tracking to investigate whether inter-annual variability in the potential lateral advection of iron, could explain the inter-annual variability in the spatial extent of the blooms. Comparison with ocean color data, 1998 to 2007, suggests that iron fertilization via advection can explain the extent of each island's annual bloom, but only the inter-annual variability of the Crozet bloom. The area that could potentially be fertilized by iron from Kerguelen was much larger than the bloom, suggesting that there is another primary limiting factor, potentially silicate, that controls the inter-annual variability of bloom spatial extent. For South Georgia, there are differences in the year-to-year timing of advection and consequently fertilization, but no clear explanation of the inter-annual variability observed in the bloom's spatial extent has been identified. The model results suggest that the Kerguelen and Crozet blooms are terminated by nutrient exhaustion, probably iron and or silicate, whereas the deepening of the mixed layer in winter terminates the South Georgia bloom. Therefore, iron fertilization via lateral advection alone can explain the annual variability of the Crozet bloom, but not fully that of the Kerguelen and South Georgia blooms. This article is protected by copyright. All rights reserved

Source regions of infragravity waves recorded at the bottom of the equatorial Atlantic Ocean, using OBS of the PI‐LAB experiment

Infragravity waves are generated along coasts, and some small fraction of their energy escapes to the open oceans and propagates with little attenuation. Due to the scarcity of deep‐ocean observations of these waves, the mechanism and the extent of the infragravity waves energy leakage from the coasts remains poorly understood. Understanding the generation and pathways of infragravity wave energy is important among others for understanding the breakup of ice‐shelves and the contamination of high‐resolution satellite radar altimetry measurements of sea level. We examine data from 37 differential pressure gauges of Ocean Bottom Seismometers (OBS) near the equatorial mid‐Atlantic ridge, deployed during the Passive Imaging of the Lithosphere‐Asthenosphere Boundary (PI‐LAB) experiment. We use the beamforming technique to investigate the incoming directions of infragravity waves. Next, we develop a graph‐theory‐based global back‐projection method of noise cross‐correlation function envelopes, which minimizes the effects of array geometry using an adaptive weighting scheme. This approach allows us to locate the sources of the infragravity energy. We assess our observations by comparing to a global model of infragravity wave heights. Our results reveal strong coherent energy from sources and/or reflected phases at the west coast of Africa and some sources from South America. These energy sources are in good agreement with the global infragravity wave model. In addition, we also observe infragravity waves arriving from North America during specific events that mostly occur during October–February 2016. Finally, we find indications of waves that propagate with little attenuation, long distances through sea ice, reflecting off Antarctica

Seasonal intensification and trends of rogue wave events on the US western seaboard

Studies of changes in wave climate typically consider trends in sea state statistics, such as the significant wave height. However, the temporal variability of individual rogue waves, which pose a hazard to users of the sea and coastal environment has not been investigated. We use time series of continuous surface elevation over 124–270 months (spanning 1994–2016), from 15 wave buoys along the US western seaboard, to investigate regional trends in significant wave height and individual rogue waves. We find high spatial variability in trends in significant wave height and rogue waves across the region. Rogue wave occurrence displays a mostly decreasing trend, but the relative height – or severity – of the waves is increasing. We also identify seasonal intensification in rogue waves with increased rogue wave occurrence, of higher severity, in the winter than in the summer. Therefore, the common practice of stating a single occurrence likelihood for an ocean basin is not valid. In addition, the buoy data show that the magnitude and significance of trends in significant wave height increases towards higher percentiles, supporting previous findings

Can rogue waves be predicted using characteristic wave parameters?

Rogue waves are ocean surface waves larger than the surrounding sea that can pose a danger to ships and offshore structures. They are often deemed unpredictable without complex measurement of the wave field and computationally intensive calculation which is infeasible in most applications, consequently there a need for fast predictors. Here we collate, quality control, and analyse the largest dataset of single‐point field measurements from surface following wave buoys to search for predictors of rogue wave occurrence. We find that analysis of the sea state parameters in bulk yields no predictors, as the subset of seas containing rogue waves sits within the set of seas without. However, spectral bandwidth parameters of rogue seas display different probability distributions to normal seas, but these parameters are rarely provided in wave forecasts. When location is accounted for, trends can be identified in the occurrence of rogue waves as a function of the average seas state characteristics at that location. These trends follow a power law relationship with the characteristic sea state parameters: mean significant wave height and mean zero up‐crossing wave period. We find that frequency of occurrence of rogue waves and their generating mechanism is not spatially uniform, and each location is likely to have its own unique sensitivities which increase in the coastal seas. We conclude that forecastable predictors of rogue wave occurrence will need to be location specific and reflective of their generation mechanism. Therefore, given location and a sufficiently long historical record of sea state characteristics, the likelihood of occurrence can be obtained for mariners and offshore operators. Plain Language Summary Rogue waves are waves much larger than expected for the surrounding sea state and their size and unexpected nature can pose a danger to ships and offshore structures. They are often thought to be unpredictable without complex computational calculation. Here we try to find the relationship between rogue wave occurrence and the characteristics of the sea state they occur in to circumnavigate this and allow prediction. Here we find that when all the data is analysed in bulk only weak relationships can be seen; however, when the data is analysed spatially relationships can be found between wave height and wave period and rogue wave occurrence. We find that the number of rogue waves and their cause differs spatially and note that each location is likely to have its own unique sensitivities which increase in the coastal seas. We conclude that forecastable predictors of rogue wave occurrence will need to be location specific, reflecting their cause. Therefore, given location and a sufficiently long historical record of sea state characteristics, the likelihood of occurrence can be obtained for mariners and offshore operators

Reduced ascending/descending pass bias in SMOS salinity data demonstrated by observing westward-propagating features in the South Indian Ocean

The European Space Agency (ESA) Soil Moisture and Ocean Salinity (SMOS) satellite has been providing data, including sea surface salinity (SSS) measurements, for more than five years. However, the operational ESA Level 2 SSS data are known to have significant spatially and temporally varying biases between measurements from ascending passes (SSSA) and measurements from descending passes (SSSD). This paper demonstrates how these biases are reduced through the use of SSS anomalies. Climatology products are constructed using SMOS Level 2 data to provide daily, one-degree by one-degree climatologies separately for ascending and descending passes using a moving window approach (in time and space). The daily, one-degree products can then be averaged to provide values of climatological SSS at different spatial and/or temporal resolutions. The averaged values of the SMOS climatology products are in good general agreement with data from the World Ocean Atlas 2013. However, there are significant differences at high latitudes, as well as in coastal and dynamic regions, as found by previous studies. Both the mean and standard deviation of the differences between data from ascending passes and data from descending passes for the anomalies are reduced compared with those obtained using the original salinity values. Geophysical signals are clearly visible in the anomaly products and an example is shown in the Southern Indian Ocean of westward-propagating signals that we conclude represent the surface expression of Rossby waves or large-scale non-linear eddies. The signals seen in salinity data agree (in speed) with those from sea surface temperature and sea surface height and are consistent with previous studies

Adapting to life : ocean biogeochemical modelling and adaptive remeshing

An outstanding problem in biogeochemical modelling of the ocean is that many of the key processes occur intermittently at small scales, such as the sub-mesoscale, that are not well represented in global ocean models. This is partly due to their failure to resolve sub-mesoscale phenomena, which play a significant role in vertical nutrient supply. Simply increasing the resolution of the models may be an inefficient computational solution to this problem. An approach based on recent advances in adaptive mesh computational techniques may offer an alternative. Here the first steps in such an approach are described, using the example of a simple vertical column (quasi-1-D) ocean biogeochemical model. <br><br> We present a novel method of simulating ocean biogeochemical behaviour on a vertically adaptive computational mesh, where the mesh changes in response to the biogeochemical and physical state of the system throughout the simulation. We show that the model reproduces the general physical and biological behaviour at three ocean stations (India, Papa and Bermuda) as compared to a high-resolution fixed mesh simulation and to observations. The use of an adaptive mesh does not increase the computational error, but reduces the number of mesh elements by a factor of 2–3. Unlike previous work the adaptivity metric used is flexible and we show that capturing the physical behaviour of the model is paramount to achieving a reasonable solution. Adding biological quantities to the adaptivity metric further refines the solution. We then show the potential of this method in two case studies where we change the adaptivity metric used to determine the varying mesh sizes in order to capture the dynamics of chlorophyll at Bermuda and sinking detritus at Papa. We therefore demonstrate that adaptive meshes may provide a suitable numerical technique for simulating seasonal or transient biogeochemical behaviour at high vertical resolution whilst minimising the number of elements in the mesh. More work is required to move this to fully 3-D simulations

Quantifying mesoscale-driven nitrate supply: a case study

The supply of nitrate to surface waters plays a crucial role in maintaining marine life. Physical processes at the mesoscale (~10-100?km) and smaller have been advocated to provide a major fraction of the global supply. Whilst observational studies have focussed on well-defined features, such as isolated eddies, the vertical circulation and nutrient supply in a typical 100-200?km square of ocean will involve a turbulent spectrum of interacting, evolving and decaying features. A crucial step in closing the ocean nitrogen budget is to be able to rank the importance of mesoscale fluxes against other sources of nitrate for surface waters for a representative area of open ocean. While this has been done using models, the vital observational equivalent is still lacking.To illustrate the difficulties that prevent us from putting a global estimate on the significance of the mesoscale observationally, we use data from a cruise in the Iceland Basin where vertical velocity and nitrate observations were made simultaneously at the same high spatial resolution. Local mesoscale nitrate flux is found to be an order of magnitude greater than that due to small-scale vertical mixing and exceeds coincident nitrate uptake rates and estimates of nitrate supply due to winter convection. However, a non-zero net vertical velocity for the region introduces a significant bias in regional estimates of the mesoscale vertical nitrate transport. The need for synopticity means that a more accurate estimate can not be simply found by using a larger survey area. It is argued that time-series, rather than spatial surveys, may be the best means to quantify the contribution of mesoscale processes to the nitrate budget of the surface ocean