Improving the altimetric rain record from Jason-1 & Jason-2

Dual-frequency rain-flagging has long been a standard part of altimetric data analysis, both for quality control of the data and for the study of rain itself, because altimeters can provide a finer spatial sampling of rain than can passive microwave instruments. However, there have been many varied implementations, using different records of the surface backscatter and different thresholds. This paper compares four different measures available for the recently-launched Jason-2. The evaluation compares these measures against clearly desired properties, finding that in most cases the adjusted backscatter and that from the ice retracker perform much better than that recommended in the users' handbook. The adjusted backscatter measure also provides a much better link to observations from Jason-1, opening up a much longer period for consistent rain investigations, and enabling greatly improved analysis of the short-scale variability of precipitation. Initial analysis shows that although the spatial and temporal gradients of backscatter increase at very low winds, the spatial gradients in rain attenuation are concentrated where rainfall is greatest, whilst the temporal changes have a simple broad latitudinal pattern

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

Measuring rainfall from above and below the sea surface

Satellites play a major role in the determination of the rainfall at sea. Researchers at Southampton Oceanography Centre (SOC) have been involved in two projects addressing this task. First they have been instrumental in developing techniques to retrieve rain rate information from the 10+ years of dual-frequency altimeter data. The TOPEX radar measures rainfall via the attenuation it causes, producing a climatology that is independent of those derived from passive microwave (PM) and infrared (IR) sensors. Because TOPEX is an active microwave sensor, it can have a much smaller footprint than PM sensors. Therefore it can be used to estimate the size of rain cells, showing that the ITCZ and mid-latitude storm tracks are characterized by larger rain systems than elsewhere. TOPEX’s simultaneous recording of wind and wave data reveal that, for mid-latitude systems, rain is most likely in association with developing seas.All satellite-based datasets require validation, and SOC's work on the development and testing of acoustic rain gauges is the second aspect of this paper. By listening at a range of frequencies, an underwater hydrophone may distinguish the spectra of wind, rain, shipping etc., and estimate the wind speed or rain rate according to the magnitude of the signals. All our campaigns have shown a good acoustic response to changes in wind speed. However the quantitative inversion for recent trials has given values that are too high, possibly because of significant acoustic reflection from the sea bottom. The changes in spectral slope often agree with other observations of rain, although validation experiments in coastal regions are hampered by the extraneous sources present. Acoustic rain gauges would eventually see service not only for routine satellite validation, but also for real-time monitoring of locations of interest

Modeling Envisat RA-2 waveforms in the coastal zone: case-study of calm water contamination

Radar altimeters have so far had limited use in the coastal zone, the area with most societal impact. This is due to both lack of, or insufficient accuracy in the necessary corrections, and more complicated altimeter signals. This paper examines waveform data from the Envisat RA-2 as it passes regularly over Pianosa (a 10 km2 island in the NW Mediterranean). Forty-six repeat passes were analysed, with most showing a reduction in signal upon passing over the island, with weak early returns corresponding to the reflections from land. Intriguingly one third of cases showed an anomalously bright hyperbolic feature. This feature may be due to extremely calm waters in the Golfo della Botte (northern side of the island), but the cause of its intermittency is not clear. The modelling of waveforms in such a complex land/sea environment demonstrates the potential for sea surface height retrievals much closer to the coast than is achieved by routine processing. The long-term development of altimetric records in the coastal zone will not only improve the calibration of altimetric data with coastal tide gauges, but also greatly enhance the study of storm surges and other coastal phenomena

Weathering the storm: developments in the acoustic sensing of wind and rain

An Acoustic Rain Gauge (ARG) analyses the underwater sound levels across a wide frequency range, classifies the observed spectrum according to likely source and then determines the local wind speed or rain rate as appropriate. Thispaper covers a trial on the Scotian Shelf off Canada, comparing the geophysical information derived from the acoustic signals with those obtained from other sources

On arrangement and expression of love poem in Kokin-wakashu

<p>Annual integrated net flux with rain components, <i>F</i>_<i>T</i> (Tg C yr^-1) from 1999–2006, for each of the ocean basins, and the impact of each rain component on <i>F</i>_<i>T</i> (Tg C yr^-1), where <i>F</i>_<i>T</i> = <i>F</i>_<i>DIC</i> + <i>F</i>_{<i>k-rain</i>} and all-rain = <i>F</i>_<i>T</i><i>−F</i>_<i>ref</i>.</p

A new phase in the production of quality-controlled sea level data

Sea level is an essential climate variable (ECV) that has a direct effect on many people through inundations of coastal areas, and it is also a clear indicator of climate changes due to external forcing factors and internal climate variability. Regional patterns of sea level change inform us on ocean circulation variations in response to natural climate modes such as El Niño and the Pacific Decadal Oscillation, and anthropogenic forcing. Comparing numerical climate models to a consistent set of observations enables us to assess the performance of these models and help us to understand and predict these phenomena, and thereby alleviate some of the environmental conditions associated with them. All such studies rely on the existence of long-term consistent high-accuracy datasets of sea level. The Climate Change Initiative (CCI) of the European Space Agency was established in 2010 to provide improved time series of some ECVs, including sea level, with the purpose of providing such data openly to all to enable the widest possible utilisation of such data. Now in its second phase, the Sea Level CCI project (SL_cci) merges data from nine different altimeter missions in a clear, consistent and well-documented manner, selecting the most appropriate satellite orbits and geophysical corrections in order to further reduce the error budget. This paper summarises the corrections required, the provenance of corrections and the evaluation of options that have been adopted for the recently released v2.0 dataset (https://doi.org/10.5270/esa-sea_level_cci-1993_2015-v_2.0-201612). This information enables scientists and other users to clearly understand which corrections have been applied and their effects on the sea level dataset. The overall result of these changes is that the rate of rise of global mean sea level (GMSL) still equates to ∼ 3.2 mm yr−1 during 1992–2015, but there is now greater confidence in this result as the errors associated with several of the corrections have been reduced. Compared with v1.1 of the SL_cci dataset, the new rate of change is 0.2 mm yr−1 less during 1993 to 2001 and 0.2 mm yr−1 higher during 2002 to 2014. Application of new correction models brought a reduction of altimeter crossover variances for most corrections