Changes in significant and maximum wave heights in the Norwegian Sea

This paper analyses 10 years of in-situ measurements of significant wave height (Hs) and maximum wave height (Hmax) from the ocean weather ship Polarfront in the Norwegian Sea. The 30-minute Ship-Borne Wave Recorder measurements of Hmax and Hs are shown to be consistent with theoretical wave distributions. The linear regression between Hmax and Hs has a slope of 1.53. Neither Hs nor Hmax show a significant trend in the period 2000–2009. These data are combined with earlier observations. The long-term trend over the period 1980–2009 in annual Hs is 2.72 ± 0.88 cm/year. Mean Hs and Hmax are both correlated with the North Atlantic Oscillation (NAO) index during winter. The correlation with the NAO index is highest for the more frequently encountered (75th percentile) wave heights. The wave field variability associated with the NAO index is reconstructed using a 500-year NAO index record. Hs and Hmax are found to vary by up to 1.42 m and 3.10 m respectively over the 500-year period. Trends in all 30-year segments of the reconstructed wave field are lower than the trend in the observations during 1980–2009. The NAO index does not change significantly in 21st century projections from CMIP5 climate models under scenario RCP85, and thus no NAO-related changes are expected in the mean and extreme wave fields of the Norwegian Sea.

Using airborne laser altimetry to improve river flood extents delineated from SAR data

Flood extent maps derived from SAR images are a useful source of data for validating hydraulic models of river flood flow. The accuracy of such maps is reduced by a number of factors, including changes in returns from the water surface caused by different meteorological conditions and the presence of emergent vegetation. The paper describes how improved accuracy can be achieved by modifying an existing flood extent delineation algorithm to use airborne laser altimetry (LiDAR) as well as SAR data. The LiDAR data provide an additional constraint that waterline (land-water boundary) heights should vary smoothly along the flooded reach. The method was tested on a SAR image of a flood for which contemporaneous aerial photography existed, together with LiDAR data of the un-flooded reach. Waterline heights of the SAR flood extent conditioned on both SAR and LiDAR data matched the corresponding heights from the aerial photo waterline significantly more closely than those from the SAR flood extent conditioned only on SAR data.

Calibration of uncertain flood inundation models using remotely sensed water levels

A traditional method of validating the performance of a flood model when remotely sensed data of the flood extent are available is to compare the predicted flood extent to that observed. The performance measure employed often uses areal pattern-matching to assess the degree to which the two extents overlap. Recently, remote sensing of flood extents using synthetic aperture radar (SAR) and airborne scanning laser altimetry (LIDAR) has made more straightforward the synoptic measurement of water surface elevations along flood waterlines, and this has emphasised the possibility of using alternative performance measures based on height. This paper considers the advantages that can accrue from using a performance measure based on waterline elevations rather than one based on areal patterns of wet and dry pixels. The two measures were compared for their ability to estimate flood inundation uncertainty maps from a set of model runs carried out to span the acceptable model parameter range in a GLUE-based analysis. A 1 in 5-year flood on the Thames in 1992 was used as a test event. As is typical for UK floods, only a single SAR image of observed flood extent was available for model calibration and validation. A simple implementation of a two-dimensional flood model (LISFLOOD-FP) was used to generate model flood extents for comparison with that observed. The performance measure based on height differences of corresponding points along the observed and modelled waterlines was found to be significantly more sensitive to the channel friction parameter than the measure based on areal patterns of flood extent. The former was able to restrict the parameter range of acceptable model runs and hence reduce the number of runs necessary to generate an inundation uncertainty map. A result of this was that there was less uncertainty in the final flood risk map. The uncertainty analysis included the effects of uncertainties in the observed flood extent as well as in model parameters. The height-based measure was found to be more sensitive when increased heighting accuracy was achieved by requiring that observed waterline heights varied slowly along the reach. The technique allows for the decomposition of the reach into sections, with different effective channel friction parameters used in different sections, which in this case resulted in lower r.m.s. height differences between observed and modelled waterlines than those achieved by runs using a single friction parameter for the whole reach. However, a validation of the modelled inundation uncertainty using the calibration event showed a significant difference between the uncertainty map and the observed flood extent. While this was true for both measures, the difference was especially significant for the height-based one. This is likely to be due to the conceptually simple flood inundation model and the coarse application resolution employed in this case. The increased sensitivity of the height-based measure may lead to an increased onus being placed on the model developer in the production of a valid model

Cloud-radar observations of insects in the UK convective boundary layer

Radar has been applied to the study of insect migration for almost 40 years, but most entomological radars operate at X-band (9.4 GHz, 3.2 cm wavelength), and can only detect individuals of relatively large species, such as migratory grasshoppers and noctuid moths, over all of their flight altitudes. Many insects (including economically important species) are much smaller than this, but development of the requisite higher power and/or higher frequency radar systems to detect these species is often prohibitively expensive. In this paper, attention is focussed upon the uses of some recently-deployed meteorological sensing devices to investigate insect migratory flight behaviour, and especially its interactions with boundary layer processes. Records were examined from the vertically-pointing 35 GHz ‘Copernicus’ and 94 GHz ‘Galileo’ cloud radars at Chilbolton (Hampshire, England) for 12 cloudless and convective occasions in summer 2003, and one of these occasions (13 July) is presented in detail. Insects were frequently found at heights above aerosol particles, which represent passive tracers, indicating active insect movement. It was found that insect flight above the convective boundary layer occurs most often during the morning. The maximum radar reflectivity (an indicator of aerial insect biomass) was found to be positively correlated with maximum screen temperature.

Flight periodicity and the vertical distribution of high-altitude moth migration over southern Britain

The continuous operation of insect-monitoring radars in the UK has permitted, for the first time, the characterization of various phenomena associated with high-altitude migration of large insects over this part of northern Europe. Previous studies have taken a case-study approach, concentrating on a small number of nights of particular interest. Here, combining data from two radars, and from an extensive suction- and light-trapping network, we have undertaken a more systematic, longer-term study of diel flight periodicity and vertical distribution of macro-insects in the atmosphere. Firstly, we identify general features of insect abundance and stratification, occurring during the 24-hour cycle, which emerge from four years’ aggregated radar data for the summer months in southern Britain. These features include mass emigrations at dusk and to a lesser extent at dawn, and daytime concentrations associated with thermal convection. We then focus our attention on the well-defined layers of large nocturnal migrants that form in the early evening, usually at heights of 200–500 m above ground. We present evidence from both radar and trap data that these nocturnal layers are composed mainly of noctuid moths, with species such as Noctua pronuba, Autographa gamma, Agrotis exclamationis, A. segetum, Xestia c-nigrum and Phlogophora meticulosa predominating.

The influence of the atmospheric boundary layer on nocturnal layers of noctuids and other moths migrating over southern Britain

Insects migrating at high altitude over southern Britain have been continuously monitored by automatically-operating, vertical-looking radars over a period of several years. During some occasions in the summer months, the migrants were observed to form well-defined layer concentrations, typically at heights of 200-400 m, in the stable night-time atmosphere. Under these conditions, insects are likely to have control over their vertical movements and are selecting flight heights which are favourable for long-range migration. We therefore investigated the factors influencing the formation of these insect layers by comparing radar measurements of the vertical distribution of insect density with meteorological profiles generated by the UK Met. Office’s Unified Model (UM). Radar-derived measurements of mass and displacement speed, along with data from Rothamsted Insect Survey light traps provided information on the identity of the migrants. We present here three case studies where noctuid and pyralid moths contributed substantially to the observed layers. The major meteorological factors influencing the layer concentrations appeared to be: (a) the altitude of the warmest air, (b) heights corresponding to temperature preferences or thresholds for sustained migration and (c), on nights when air temperatures are relatively high, wind-speed maxima associated with the nocturnal jet. Back-trajectories indicated that layer duration may have been determined by the distance to the coast. Overall, the unique combination of meteorological data from the UM and insect data from entomological radar described here show considerable promise for systematic studies of high-altitude insect layering.

Improving flood inundation models using remotely sensed data

The paper discusses the wide variety of ways in which remotely sensed data are being utilized in river flood inundation modeling. Model parameterization is being aided using airborne LiDAR data to provide topography of the floodplain for use as model bathymetry, and vegetation heights in the floodplain for use in estimating floodplain friction factors. Model calibration and validation are being aided by comparing the flood extent observed in SAR images with the extent predicted by the model. The recent extension of this to the observation of urban flooding using high resolution TerraSAR-X data is described. Possible future research directions are considered.

Detection of flood extent in urban areas using high resolution TerraSAR-X data

Flooding is a major hazard in both rural and urban areas worldwide, but it is in urban areas that the impacts are most severe. An investigation of the ability of high resolution TerraSAR-X data to detect flooded regions in urban areas is described. An important application for this would be the calibration and validation of the flood extent predicted by an urban flood inundation model. To date, research on such models has been hampered by lack of suitable distributed validation data. The study uses a 3m resolution TerraSAR-X image of a 1-in-150 year flood near Tewkesbury, UK, in 2007, for which contemporaneous aerial photography exists for validation. The DLR SETES SAR simulator was used in conjunction with airborne LiDAR data to estimate regions of the TerraSAR-X image in which water would not be visible due to radar shadow or layover caused by buildings and taller vegetation, and these regions were masked out in the flood detection process. A semi-automatic algorithm for the detection of floodwater was developed, based on a hybrid approach. Flooding in rural areas adjacent to the urban areas was detected using an active contour model (snake) region-growing algorithm seeded using the un-flooded river channel network, which was applied to the TerraSAR-X image fused with the LiDAR DTM to ensure the smooth variation of heights along the reach. A simpler region-growing approach was used in the urban areas, which was initialized using knowledge of the flood waterline in the rural areas. Seed pixels having low backscatter were identified in the urban areas using supervised classification based on training areas for water taken from the rural flood, and non-water taken from the higher urban areas. Seed pixels were required to have heights less than a spatially-varying height threshold determined from nearby rural waterline heights. Seed pixels were clustered into urban flood regions based on their close proximity, rather than requiring that all pixels in the region should have low backscatter. This approach was taken because it appeared that urban water backscatter values were corrupted in some pixels, perhaps due to contributions from side-lobes of strong reflectors nearby. The TerraSAR-X urban flood extent was validated using the flood extent visible in the aerial photos. It turned out that 76% of the urban water pixels visible to TerraSAR-X were correctly detected, with an associated false positive rate of 25%. If all urban water pixels were considered, including those in shadow and layover regions, these figures fell to 58% and 19% respectively. These findings indicate that TerraSAR-X is capable of providing useful data for the calibration and validation of urban flood inundation models.

Comparison of balloon-carried atmospheric motion sensors with Doppler lidar turbulence measurements

Magnetic sensors have been added to a standard weather balloon radiosonde package to detect motion in turbulent air. These measure the terrestrial magnetic field and return data over the standard uhf radio telemetry. Variability in the magnetic sensor data is caused by motion of the instrument package. A series of radiosonde ascents carrying these sensors has been made near a Doppler lidar measuring atmospheric properties. Lidar-retrieved quantities include vertical velocity (w) profile and its standard deviation (w). w determined over 1 h is compared with the radiosonde motion variability at the same heights. Vertical motion in the radiosonde is found to be robustly increased when w>0.75 m s−1 and is linearly proportional to w. ©2009 American Institute of Physics

Tropospheric planetary wave dynamics and mixture modeling: Two preferred regimes and a regime shift

Investigation of preferred structures of planetary wave dynamics is addressed using multivariate Gaussian mixture models. The number of components in the mixture is obtained using order statistics of the mixing proportions, hence avoiding previous difficulties related to sample sizes and independence issues. The method is first applied to a few low-order stochastic dynamical systems and data from a general circulation model. The method is next applied to winter daily 500-hPa heights from 1949 to 2003 over the Northern Hemisphere. A spatial clustering algorithm is first applied to the leading two principal components (PCs) and shows significant clustering. The clustering is particularly robust for the first half of the record and less for the second half. The mixture model is then used to identify the clusters. Two highly significant extratropical planetary-scale preferred structures are obtained within the first two to four EOF state space. The first pattern shows a Pacific-North American (PNA) pattern and a negative North Atlantic Oscillation (NAO), and the second pattern is nearly opposite to the first one. It is also observed that some subspaces show multivariate Gaussianity, compatible with linearity, whereas others show multivariate non-Gaussianity. The same analysis is also applied to two subperiods, before and after 1978, and shows a similar regime behavior, with a slight stronger support for the first subperiod. In addition a significant regime shift is also observed between the two periods as well as a change in the shape of the distribution. The patterns associated with the regime shifts reflect essentially a PNA pattern and an NAO pattern consistent with the observed global warming effect on climate and the observed shift in sea surface temperature around the mid-1970s.

Sensitivity of radar backscatter to desert surface roughness

Synthetic aperture radar (SAR) data have proved useful in remote sensing studies of deserts, enabling different surfaces to be discriminated by differences in roughness properties. Roughness is characterized in SAR backscatter models using the standard deviation of surface heights (sigma), correlation length (L) and autocorrelation function (rho(xi)). Previous research has suggested that these parameters are of limited use for characterizing surface roughness, and are often unreliable due to the collection of too few roughness profiles, or under-sampling in terms of resolution or profile length (L-p). This paper reports on work aimed at establishing the effects of L-p and sampling resolution on SAR backscatter estimations and site discrimination. Results indicate significant relationships between the average roughness parameters and L-p, but large variability in roughness parameters prevents any clear understanding of these relationships. Integral equation model simulations demonstrate limited change with L-p and under-estimate backscatter relative to SAR observations. However, modelled and observed backscatter conform in pattern and magnitude for C-band systems but not for L-band data. Variation in surface roughness alone does not explain variability in site discrimination. Other factors (possibly sub-surface scattering) appear to play a significant role in controlling backscatter characteristics at lower frequencies.