Satellite-supported flood forecasting in river networks: a real case study

Satellite-based (e.g., Synthetic Aperture Radar [SAR]) water level observations (WLOs) of the floodplain can be sequentially assimilated into a hydrodynamic model to decrease forecast uncertainty. This has the potential to keep the forecast on track, so providing an Earth Observation (EO) based flood forecast system. However, the operational applicability of such a system for floods developed over river networks requires further testing. One of the promising techniques for assimilation in this field is the family of ensemble Kalman (EnKF) filters. These filters use a limited-size ensemble representation of the forecast error covariance matrix. This representation tends to develop spurious correlations as the forecast-assimilation cycle proceeds, which is a further complication for dealing with floods in either urban areas or river junctions in rural environments. Here we evaluate the assimilation of WLOs obtained from a sequence of real SAR overpasses (the X-band COSMO-Skymed constellation) in a case study. We show that a direct application of a global Ensemble Transform Kalman Filter (ETKF) suffers from filter divergence caused by spurious correlations. However, a spatially-based filter localization provides a substantial moderation in the development of the forecast error covariance matrix, directly improving the forecast and also making it possible to further benefit from a simultaneous online inflow error estimation and correction. Additionally, we propose and evaluate a novel along-network metric for filter localization, which is physically-meaningful for the flood over a network problem. Using this metric, we further evaluate the simultaneous estimation of channel friction and spatially-variable channel bathymetry, for which the filter seems able to converge simultaneously to sensible values. Results also indicate that friction is a second order effect in flood inundation models applied to gradually varied flow in large rivers. The study is not conclusive regarding whether in an operational situation the simultaneous estimation of friction and bathymetry helps the current forecast. Overall, the results indicate the feasibility of stand-alone EO-based operational flood forecasting.

Rainfall estimation by rain gauge-radar combination: a concurrent multiplicative-additive approach

A procedure (concurrent multiplicative-additive objective analysis scheme [CMA-OAS]) is proposed for operational rainfall estimation using rain gauges and radar data. On the basis of a concurrent multiplicative-additive (CMA) decomposition of the spatially nonuniform radar bias, within-storm variability of rainfall and fractional coverage of rainfall are taken into account. Thus both spatially nonuniform radar bias, given that rainfall is detected, and bias in radar detection of rainfall are handled. The interpolation procedure of CMA-OAS is built on Barnes' objective analysis scheme (OAS), whose purpose is to estimate a filtered spatial field of the variable of interest through a successive correction of residuals resulting from a Gaussian kernel smoother applied on spatial samples. The CMA-OAS, first, poses an optimization problem at each gauge-radar support point to obtain both a local multiplicative-additive radar bias decomposition and a regionalization parameter. Second, local biases and regionalization parameters are integrated into an OAS to estimate the multisensor rainfall at the ground level. The procedure is suited to relatively sparse rain gauge networks. To show the procedure, six storms are analyzed at hourly steps over 10,663 km2. Results generally indicated an improved quality with respect to other methods evaluated: a standard mean-field bias adjustment, a spatially variable adjustment with multiplicative factors, and ordinary cokriging.

An overview on the urban boundary-layer atmosphere network in Helsinki

The Helsinki Urban Boundary-Layer Atmosphere Network (UrBAN: http://urban.fmi.fi) is a dedicated research-grade observational network where the physical processes in the atmosphere above the city are studied. Helsinki UrBAN is the most poleward intensive urban research observation network in the world and thus will allow studying some unique features such as strong seasonality. The network's key purpose is for the understanding of the physical processes in the urban boundary layer and associated fluxes of heat, momentum, moisture, and other gases. A further purpose is to secure a research-grade database, which can be used internationally to validate and develop numerical models of air quality and weather prediction. Scintillometers, a scanning Doppler lidar, ceilometers, a sodar, eddy-covariance stations, and radiometers are used. This equipment is supplemented by auxiliary measurements, which were primarily set up for general weather and/or air-quality mandatory purposes, such as vertical soundings and the operational Doppler radar network. Examples are presented as a testimony to the potential of the network for urban studies, such as (i) evidence of a stable boundary layer possibly coupled to an urban surface, (ii) the comparison of scintillometer data with sonic anemometry above an urban surface, (iii) the application of scanning lidar over a city, and (iv) combination of sodar and lidar to give a fuller range of sampling heights for boundary layer profiling.

The chaotic frequency hopping signals for MIMO radar

In multiple-input multiple-output (MIMO) radar systems, the transmitters emit orthogonal waveforms to increase the spatial resolution. New frequency hopping (FH) codes based on chaotic sequences are proposed. The chaotic sequences have the characteristics of good encryption, anti-jamming properties and anti-intercept capabilities. The main idea of chaotic FH is based on queuing theory. According to the sensitivity to initial condition, these sequences can achieve good Hamming auto-correlation while also preserving good average correlation. Simulation results show that the proposed FH signals can achieve lower autocorrelation side lobe level and peak cross-correlation level with the increasing of iterations. Compared to the LFM signals, this sequence has higher range-doppler resolution.

A radar-based rainfall climatology of Great Britain and Ireland

The Met Office 1km radar-derived precipitation-rate composite over 8 years (2006–2013) is examined to evaluate whether it provides an accurate representation of annual-average precipitation over Great Britain and Ireland over long periods of time. The annual-average precipitation from the radar composite is comparable with gauge measurements, with an average error of +23mmyr−1 over Great Britain and Ireland, +29mmyr−1 (3%) over the United Kingdom and –781mmyr−1 (46%) over the Republic of Ireland. The radar-derived precipitation composite is useful over the United Kingdom including Northern Ireland, but not accurate over the Republic of Ireland, particularly in the south.

Clouds, aerosols, and precipitation in the marine boundary layer: an ARM Mobile Facility Deployment

The Clouds, Aerosol, and Precipitation in the Marine Boundary Layer (CAP-MBL) deployment at Graciosa Island in the Azores generated a 21-month (April 2009–December 2010) comprehensive dataset documenting clouds, aerosols, and precipitation using the Atmospheric Radiation Measurement Program (ARM) Mobile Facility (AMF). The scientific aim of the deployment is to gain improved understanding of the interactions of clouds, aerosols, and precipitation in the marine boundary layer. Graciosa Island straddles the boundary between the subtropics and midlatitudes in the northeast Atlantic Ocean and consequently experiences a great diversity of meteorological and cloudiness conditions. Low clouds are the dominant cloud type, with stratocumulus and cumulus occurring regularly. Approximately half of all clouds contained precipitation detectable as radar echoes below the cloud base. Radar and satellite observations show that clouds with tops from 1 to 11 km contribute more or less equally to surface-measured precipitation at Graciosa. A wide range of aerosol conditions was sampled during the deployment consistent with the diversity of sources as indicated by back-trajectory analysis. Preliminary findings suggest important two-way interactions between aerosols and clouds at Graciosa, with aerosols affecting light precipitation and cloud radiative properties while being controlled in part by precipitation scavenging. The data from Graciosa are being compared with short-range forecasts made with a variety of models. A pilot analysis with two climate and two weather forecast models shows that they reproduce the observed time-varying vertical structure of lower-tropospheric cloud fairly well but the cloud-nucleating aerosol concentrations less well. The Graciosa site has been chosen to be a permanent fixed ARM site that became operational in October 2013.

The representation of the West-African Monsoon vertical cloud structure in the Met Office Unified Model: an evaluation with CloudSat

Weather and climate model simulations of the West African Monsoon (WAM) have generally poor representation of the rainfall distribution and monsoon circulation because key processes, such as clouds and convection, are poorly characterized. The vertical distribution of cloud and precipitation during the WAM are evaluated in Met Office Unified Model simulations against CloudSat observations. Simulations were run at 40-km and 12-km horizontal grid length using a convection parameterization scheme and at 12-km, 4-km, and 1.5-km grid length with the convection scheme effectively switched off, to study the impact of model resolution and convection parameterization scheme on the organisation of tropical convection. Radar reflectivity is forward-modelled from the model cloud fields using the CloudSat simulator to present a like-with-like comparison with the CloudSat radar observations. The representation of cloud and precipitation at 12-km horizontal grid length improves dramatically when the convection parameterization is switched off, primarily because of a reduction in daytime (moist) convection. Further improvement is obtained when reducing model grid length to 4 km or 1.5 km, especially in the representation of thin anvil and mid-level cloud, but three issues remain in all model configurations. Firstly, all simulations underestimate the fraction of anvils with cloud top height above 12 km, which can be attributed to too low ice water contents in the model compared to satellite retrievals. Secondly, the model consistently detrains mid-level cloud too close to the freezing level, compared to higher altitudes in CloudSat observations. Finally, there is too much low-level cloud cover in all simulations and this bias was not improved when adjusting the rainfall parameters in the microphysics scheme. To improve model simulations of the WAM, more detailed and in-situ observations of the dynamics and microphysics targeting these non-precipitating cloud types are required.

G band atmospheric radars: new frontiers in cloud physics

Clouds and associated precipitation are the largest source of uncertainty in current weather and future climate simulations. Observations of the microphysical, dynamical and radiative processes that act at cloud scales are needed to improve our understanding of clouds. The rapid expansion of ground-based super-sites and the availability of continuous profiling and scanning multi-frequency radar observations at 35 and 94 GHz have significantly improved our ability to probe the internal structure of clouds in high temporal-spatial resolution, and to retrieve quantitative cloud and precipitation properties. However, there are still gaps in our ability to probe clouds due to large uncertainties in the retrievals. The present work discusses the potential of G band (frequency between 110 and 300 GHz) Doppler radars in combination with lower frequencies to further improve the retrievals of microphysical properties. Our results show that, thanks to a larger dynamic range in dual-wavelength reflectivity, dual-wavelength attenuation and dual-wavelength Doppler velocity (with respect to a Rayleigh reference), the inclusion of frequencies in the G band can significantly improve current profiling capabilities in three key areas: boundary layer clouds, cirrus and mid-level ice clouds, and precipitating snow.

Rayleigh scattering by hexagonal ice crystals and the interpretation of dual-polarisation radar measurements

Dual-polarisation radar measurements provide valuable information about the shapes and orientations of atmospheric ice particles. For quantitative interpretation of these data in the Rayleigh regime, common practice is to approximate the true ice crystal shape with that of a spheroid. Calculations using the discrete dipole approximation for a wide range of crystal aspect ratios demonstrate that approximating hexagonal plates as spheroids leads to significant errors in the predicted differential reflectivity, by as much as 1.5 dB. An empirical modification of the shape factors in Gans's spheroid theory was made using the numerical data. The resulting simple expressions, like Gans's theory, can be applied to crystals in any desired orientation, illuminated by an arbitrarily polarised wave, but are much more accurate for hexagonal particles. Calculations of the scattering from more complex branched and dendritic crystals indicate that these may be accurately modelled using the new expression, but with a reduced permittivity dependent on the volume of ice relative to an enclosing hexagonal prism.

The potential of flood forecasting using a variable-resolution global Digital Terrain Model and flood extents from Synthetic Aperture Radar images

A basic data requirement of a river flood inundation model is a Digital Terrain Model (DTM) of the reach being studied. The scale at which modeling is required determines the accuracy required of the DTM. For modeling floods in urban areas, a high resolution DTM such as that produced by airborne LiDAR (Light Detection And Ranging) is most useful, and large parts of many developed countries have now been mapped using LiDAR. In remoter areas, it is possible to model flooding on a larger scale using a lower resolution DTM, and in the near future the DTM of choice is likely to be that derived from the TanDEM-X Digital Elevation Model (DEM). A variable-resolution global DTM obtained by combining existing high and low resolution data sets would be useful for modeling flood water dynamics globally, at high resolution wherever possible and at lower resolution over larger rivers in remote areas. A further important data resource used in flood modeling is the flood extent, commonly derived from Synthetic Aperture Radar (SAR) images. Flood extents become more useful if they are intersected with the DTM, when water level observations (WLOs) at the flood boundary can be estimated at various points along the river reach. To illustrate the utility of such a global DTM, two examples of recent research involving WLOs at opposite ends of the spatial scale are discussed. The first requires high resolution spatial data, and involves the assimilation of WLOs from a real sequence of high resolution SAR images into a flood model to update the model state with observations over time, and to estimate river discharge and model parameters, including river bathymetry and friction. The results indicate the feasibility of such an Earth Observation-based flood forecasting system. The second example is at a larger scale, and uses SAR-derived WLOs to improve the lower-resolution TanDEM-X DEM in the area covered by the flood extents. The resulting reduction in random height error is significant.

Direct observations of the full Dungey convection cycle in the polar ionosphere for southward interplanetary magnetic field conditions

Tracking the formation and full evolution of polar cap ionization patches in the polar ionosphere, we directly observe the full Dungey convection cycle for southward interplanetary magnetic field (IMF) conditions. This enables us to study how the Dungey cycle influences the patches’ evolution. The patches were initially segmented from the dayside storm enhanced density plume at the equatorward edge of the cusp, by the expansion and contraction of the polar cap boundary due to pulsed dayside magnetopause reconnection, as indicated by in situ Time History of Events and Macroscale Interactions during Substorms(THEMIS) observations. Convection led to the patches entering the polar cap and being transported antisunward, while being continuously monitored by the globally distributed arrays of GPS receivers and Super Dual Auroral Radar Network radars. Changes in convection over time resulted in the patches following a range of trajectories, each of which differed somewhat from the classical twin-cell convection streamlines. Pulsed nightside reconnection, occurring as part of the magnetospheric substorm cycle, modulated the exit of the patches from the polar cap, as confirmed by coordinated observations of the magnetometer at Tromsø and European Incoherent Scatter Tromsø UHF radar. After exiting the polar cap, the patches broke up into a number of plasma blobs and returned sunward in the auroral return flow of the dawn and/or dusk convection cell. The full circulation time was about 3 h.

Improving the TanDEM-X Digital Elevation Model for flood modelling using flood extents from Synthetic Aperture Radar images

The topography of many floodplains in the developed world has now been surveyed with high resolution sensors such as airborne LiDAR (Light Detection and Ranging), giving accurate Digital Elevation Models (DEMs) that facilitate accurate flood inundation modelling. This is not always the case for remote rivers in developing countries. However, the accuracy of DEMs produced for modelling studies on such rivers should be enhanced in the near future by the high resolution TanDEM-X WorldDEM. In a parallel development, increasing use is now being made of flood extents derived from high resolution Synthetic Aperture Radar (SAR) images for calibrating, validating and assimilating observations into flood inundation models in order to improve these. This paper discusses an additional use of SAR flood extents, namely to improve the accuracy of the TanDEM-X DEM in the floodplain covered by the flood extents, thereby permanently improving this DEM for future flood modelling and other studies. The method is based on the fact that for larger rivers the water elevation generally changes only slowly along a reach, so that the boundary of the flood extent (the waterline) can be regarded locally as a quasi-contour. As a result, heights of adjacent pixels along a small section of waterline can be regarded as samples with a common population mean. The height of the central pixel in the section can be replaced with the average of these heights, leading to a more accurate estimate. While this will result in a reduction in the height errors along a waterline, the waterline is a linear feature in a two-dimensional space. However, improvements to the DEM heights between adjacent pairs of waterlines can also be made, because DEM heights enclosed by the higher waterline of a pair must be at least no higher than the corrected heights along the higher waterline, whereas DEM heights not enclosed by the lower waterline must in general be no lower than the corrected heights along the lower waterline. In addition, DEM heights between the higher and lower waterlines can also be assigned smaller errors because of the reduced errors on the corrected waterline heights. The method was tested on a section of the TanDEM-X Intermediate DEM (IDEM) covering an 11km reach of the Warwickshire Avon, England. Flood extents from four COSMO-SKyMed images were available at various stages of a flood in November 2012, and a LiDAR DEM was available for validation. In the area covered by the flood extents, the original IDEM heights had a mean difference from the corresponding LiDAR heights of 0.5 m with a standard deviation of 2.0 m, while the corrected heights had a mean difference of 0.3 m with standard deviation 1.2 m. These figures show that significant reductions in IDEM height bias and error can be made using the method, with the corrected error being only 60% of the original. Even if only a single SAR image obtained near the peak of the flood was used, the corrected error was only 66% of the original. The method should also be capable of improving the final TanDEM-X DEM and other DEMs, and may also be of use with data from the SWOT (Surface Water and Ocean Topography) satellite.

Collocating satellite-based radar and radiometer measurements — methodology and usage examples

Collocations between two satellite sensors are occasions where both sensors observe the same place at roughly the same time. We study collocations between the Microwave Humidity Sounder (MHS) on-board NOAA-18 and the Cloud Profiling Radar (CPR) on-board CloudSat. First, a simple method is presented to obtain those collocations and this method is compared with a more complicated approach found in literature. We present the statistical properties of the collocations, with particular attention to the effects of the differences in footprint size. For 2007, we find approximately two and a half million MHS measurements with CPR pixels close to their centrepoints. Most of those collocations contain at least ten CloudSat pixels and image relatively homogeneous scenes. In the second part, we present three possible applications for the collocations. Firstly, we use the collocations to validate an operational Ice Water Path (IWP) product from MHS measurements, produced by the National Environment Satellite, Data and Information System (NESDIS) in the Microwave Surface and Precipitation Products System (MSPPS). IWP values from the CloudSat CPR are found to be significantly larger than those from the MSPPS. Secondly, we compare the relation between IWP and MHS channel 5 (190.311 GHz) brightness temperature for two datasets: the collocated dataset, and an artificial dataset. We find a larger variability in the collocated dataset. Finally, we use the collocations to train an Artificial Neural Network and describe how we can use it to develop a new MHS-based IWP product. We also study the effect of adding measurements from the High Resolution Infrared Radiation Sounder (HIRS), channels 8 (11.11 μm) and 11 (8.33 μm). This shows a small improvement in the retrieval quality. The collocations described in the article are available for public use.

Climatology, storm morphologies, and environments of tornadoes in the British Isles: 1980–2012

A climatology is developed for tornadoes during 1980–2012 in the British Isles, defined in this article as England, Scotland, Wales, Northern Ireland, Republic of Ireland, Channel Islands, and the Isle of Man. The climatology includes parent storm type, interannual variability, annual and diurnal cycles, intensities, oc- currence of outbreaks (defined as three or more tornadoes in the same day), geographic distribution, and environmental conditions derived from proximity soundings of tornadoes. Tornado reports are from the Tornado and Storm Research Organization (TORRO). Over the 33 years, there were a mean of 34.3 tor- nadoes and 19.5 tornado days (number of days in which at least one tornado occurred) annually. Tornadoes and tornado outbreaks were most commonly produced from linear storms, defined as radar signatures at least 75 km long and approximately 3 times as long as wide. Most (78%) tornadoes occurred in England. The probability of a tornado within 10 km of a point was highest in the south, southeast, and west of England. On average, there were 2.5 tornado outbreaks every year. Where intensity was known, 95% of tornadoes were classified as F0 or F1 with the remainder classified as F2. There were no tornadoes rated F3 or greater during this time period. Tornadoes occurred throughout the year with a maximum from May through October. Finally, tornadoes tended to occur in low-CAPE, high-shear environments. Tornadoes in the British Isles were difficult to predict using only sounding-derived parameters because there were no clear thresholds between null, tornadic, outbreak, and significant tornado cases.

On mathematical and physical principles of transformations of the coherent radar backscatter matrix

The congruential rule advanced by Graves for polarization basis transformation of the radar backscatter matrix is now often misinterpreted as an example of consimilarity transformation. However, consimilarity transformations imply a physically unrealistic antilinear time-reversal operation. This is just one of the approaches found in literature to the description of transformations where the role of conjugation has been misunderstood. In this paper, the different approaches are examined in particular in respect to the role of conjugation. In order to justify and correctly derive the congruential rule for polarization basis transformation and properly place the role of conjugation, the origin of the problem is traced back to the derivation of the antenna height from the transmitted field. In fact, careful consideration of the role played by the Green’s dyadic operator relating the antenna height to the transmitted field shows that, under general unitary basis transformation, it is not justified to assume a scalar relationship between them. Invariance of the voltage equation shows that antenna states and wave states must in fact lie in dual spaces, a distinction not captured in conventional Jones vector formalism. Introducing spinor formalism, and with the use of an alternate spin frame for the transmitted field a mathematically consistent implementation of the directional wave formalism is obtained. Examples are given comparing the wider generality of the congruential rule in both active and passive transformations with the consimilarity rule.