Application of HF radar currents to oil spill modelling

In this work, the benefits of high-frequency (HF) radar currents for oil spill modeling and trajectory analysis of floating objects are analyzed. The HF radar performance is evaluated by means of comparison between a drifter buoy trajectory and the one simulated using a Lagrangian trajectory model. A methodology to optimize the transport model performance and to calculate the search area of the predicted positions is proposed. This method is applied to data collected during the Galicia HF Radar Experience. This experiment was carried out to explore the capabilities of this technology for operational monitoring along the Spanish coast. Two long-range HF radar stations were installed and operated between November 2005 and February 2006 on the Galician coast. In addition, a drifter buoy was released inside the coverage area of the radar. The HF radar currents, as well as numerical wind data were used to simulate the buoy trajectory using the TESEO oil spill transport model. In order to evaluate the contribution of HF radar currents to trajectory analysis, two simulation alternatives were carried out. In the first one, wind data were used to simulate the motion of the buoy. In the second alternative, surface currents from the HF radar were also taken into account. For each alternative, the model was calibrated by means of the global optimization algorithm SCEM-UA (Shuffled Complex Evolution Metropolis) in order to obtain the probability density function of the model parameters. The buoy trajectory was computed for 24 h intervals using a Monte Carlo approach based on the results provided in the calibration process. A bivariate kernel estimator was applied to determine the 95% confidence areas. The analysis performed showed that simulated trajectories integrating HF radar currents are more accurate than those obtained considering only wind numerical data. After a 24 h period, the error in the final simulated position improves using HF radar currents. Averaging the information from all the simulated daily periods, the mean search and rescue area calculated using HF radar currents, is reduced by approximately a 62% in comparison with the search area calculated without these data. These results show the positive contribution of HF radar currents for trajectory analysis, and demonstrate that these data combined with atmospheric forecast models, are of value for trajectory analysis of oil spills or floating objects.     

Backtracking drifting objects using surface currents from high-frequency (HF) radar technology

In this work, the benefits of high-frequency (HF) radar ocean observation technology for backtracking drifting objects are analysed. The HF radar performance is evaluated by comparison of trajectories between drifter buoys versus numerical simulations using a Lagrangian trajectory model. High-resolution currents measured by a coastal HF radar network combined with atmospheric fields provided by numerical models are used to backtrack the trajectory of two dataset of surface-drifting buoys: group I (with drogue) and group II (without drogue). A methodology based on optimization methods is applied to estimate the uncertainty in the trajectory simulations and to optimize the search area of the backtracked positions. The results show that, to backtrack the trajectory of the buoys in group II, both currents and wind fields were required. However, wind fields could be practically discarded when simulating the trajectories of group I. In this case, the optimal backtracked trajectories were obtained using only HF radar currents as forcing. Based on the radar availability data, two periods ranging between 8 and 10?h were selected to backtrack the buoy trajectories. The root mean squared error (RMSE) was found to be 1.01?km for group I and 0.82?km for group II. Taking into account these values, a search area was calculated using circles of RMSE radii, obtaining 3.2 and 2.11?km² for groups I and II, respectively. These results show the positive contribution of HF radar currents for backtracking drifting objects and demonstrate that these data combined with atmospheric models are of value to perform backtracking analysis of drifting objects.     

Assessing the fidelity of surface currents from a coastal ocean model and HF radar using drifting buoys in the Middle Atlantic Bight

The rapid expansion of urbanization along the world’s coastal areas requires a more comprehensive and accurate understanding of the coastal ocean. Over the past several decades, numerical ocean circulation models have tried to provide such insight, based on our developing understanding of physical ocean processes. The systematic establishment of coastal ocean observation systems adopting cutting-edge technology, such as high frequency (HF) radar, satellite sensing, and gliders, has put such ocean model predictions to the test, by providing comprehensive observational datasets for the validation of numerical model forecasts. The New York Harbor Observing and Prediction System (NYHOPS) is a comprehensive system for understanding coastal ocean processes on the continental shelf waters of New York and New Jersey. To increase confidence in the system’s ocean circulation predictions in that area, a detailed validation exercise was carried out using HF radar and Lagrangian drifter-derived surface currents from three drifters obtained between March and October 2010. During that period, the root mean square (RMS) differences of both the east–west and north–south currents between NYHOPS and HF radar were approximately 15 cm s^?1. Harmonic analysis of NYHOPS and HF radar surface currents shows similar tidal ellipse parameters for the dominant M₂ tide, with a mean difference of 2.4 cm s^?1 in the semi-major axis and 1.4 cm s^?1 in the semi-minor axis and 3° in orientation and 10° in phase. Surface currents derived independently from drifters along their trajectories showed that NYHOPS and HF radar yielded similarly accurate results. RMS errors when compared to currents derived along the trajectory of the three drifters were approximately 10 cm s^?1. Overall, the analysis suggests that NYHOPS and HF radar had similar skill in estimating the currents over the continental shelf waters of the Middle Atlantic Bight during this time period. An ensemble-based set of particle tracking simulations using one drifter which was tracked for 11 days showed that the ensemble mean separation generally increases with time in a linear fashion. The separation distance is not dominated by high frequency or short spatial scale wavelengths suggesting that both the NYHOPS and HF radar currents are representing tidal and inertial time scales correctly and resolving some of the smaller scale eddies. The growing ensemble mean separation distance is dominated by errors in the mean flow causing the drifters to slowly diverge from their observed positions. The separation distance for both HF radar and NYHOPS stays below 30 km after 5 days, and the two technologies have similar tracking skill at the 95 % level. For comparison, the ensemble mean distance of a drifter from its initial release location (persistence assumption) is estimated to be greater than 70 km in 5 days.     

Simulation and detection of tsunami signatures in ocean surface currents measured by HF radar

High-frequency (HF) surface wave radars provide the unique capability to continuously monitor the coastal environment far beyond the range of conventional microwave radars. Bragg-resonant backscattering by ocean waves with half the electromagnetic radar wavelength allows ocean surface currents to be measured at distances up to 200 km. When a tsunami propagates from the deep ocean to shallow water, a specific ocean current signature is generated throughout the water column. Due to the long range of an HF radar, it is possible to detect this current signature at the shelf edge. When the shelf edge is about 100 km in front of the coastline, the radar can detect the tsunami about 45 min before it hits the coast, leaving enough time to issue an early warning. As up to now no HF radar measurements of an approaching tsunami exist, a simulation study has been done to fix parameters like the required spatial resolution or the maximum coherent integration time allowed. The simulation involves several steps, starting with the Hamburg Shelf Ocean Model (HAMSOM) which is used to estimate the tsunami-induced current velocity at 1 km spatial resolution and 1 s time step. This ocean current signal is then superimposed to modelled and measured HF radar backscatter signals using a new modulation technique. After applying conventional HF radar signal processing techniques, the surface current maps contain the rapidly changing tsunami-induced current features, which can be compared to the HAMSOM data. The specific radial tsunami current signatures can clearly be observed in these maps, if appropriate spatial and temporal resolution is used. Based on the entropy of the ocean current maps, a tsunami detection algorithm is described which can be used to issue an automated tsunami warning message.     

Observation-based evaluation of surface wave effects on currents and trajectory forecasts

Knowledge of upper ocean currents is needed for trajectory forecasts and is essential for search and rescue operations and oil spill mitigation. This paper addresses effects of surface waves on ocean currents and drifter trajectories using in situ observations. The data set includes colocated measurements of directional wave spectra from a wave rider buoy, ocean currents measured by acoustic Doppler current profilers (ADCPs), as well as data from two types of tracking buoys that sample the currents at two different depths. The ADCP measures the Eulerian current at one point, as modelled by an ocean general circulation model, while the tracking buoys are advected by the Lagrangian current that includes the wave-induced Stokes drift. Based on our observations, we assess the importance of two different wave effects: (a) forcing of the ocean current by wave-induced surface fluxes and the Coriolis–Stokes force, and (b) advection of surface drifters by wave motion, that is the Stokes drift. Recent theoretical developments provide a framework for including these wave effects in ocean model systems. The order of magnitude of the Stokes drift is the same as the Eulerian current judging from the available data. The wave-induced momentum and turbulent kinetic energy fluxes are estimated and shown to be significant. Similarly, the wave-induced Coriolis–Stokes force is significant over time scales related to the inertial period. Surface drifter trajectories were analysed and could be reproduced using the observations of currents, waves and wind. Waves were found to have a significant contribution to the trajectories, and we conclude that adding wave effects in ocean model systems is likely to increase predictability of surface drifter trajectories. The relative importance of the Stokes drift was twice as large as the direct wind drag for the used surface drifter.

     

Observation-based evaluation of surface wave effects on currents and trajectory forecasts

Knowledge of upper ocean currents is needed for trajectory forecasts and is essential for search and rescue operations and oil spill mitigation. This paper addresses effects of surface waves on ocean currents and drifter trajectories using in situ observations. The data set includes colocated measurements of directional wave spectra from a wave rider buoy, ocean currents measured by acoustic Doppler current profilers (ADCPs), as well as data from two types of tracking buoys that sample the currents at two different depths. The ADCP measures the Eulerian current at one point, as modelled by an ocean general circulation model, while the tracking buoys are advected by the Lagrangian current that includes the wave-induced Stokes drift. Based on our observations, we assess the importance of two different wave effects: (a) forcing of the ocean current by wave-induced surface fluxes and the Coriolis–Stokes force, and (b) advection of surface drifters by wave motion, that is the Stokes drift. Recent theoretical developments provide a framework for including these wave effects in ocean model systems. The order of magnitude of the Stokes drift is the same as the Eulerian current judging from the available data. The wave-induced momentum and turbulent kinetic energy fluxes are estimated and shown to be significant. Similarly, the wave-induced Coriolis–Stokes force is significant over time scales related to the inertial period. Surface drifter trajectories were analysed and could be reproduced using the observations of currents, waves and wind. Waves were found to have a significant contribution to the trajectories, and we conclude that adding wave effects in ocean model systems is likely to increase predictability of surface drifter trajectories. The relative importance of the Stokes drift was twice as large as the direct wind drag for the used surface drifter.     

Surface current patterns observed by HF radar: methodology and analysis of currents to the north of the Yaeyama Islands,East China Sea

A new method was developed to compare the classifications of different kind of data maps based on the self-organizing map (SOM) analysis. The surface current maps of the northern coast of Ishigaki and Iriomote Islands, East China Sea, observed by high-frequency (HF) radar were classified by SOM. Winds, sea surface temperatures (SST), and reanalysis data were also classified by SOM. The optimum area for classification was determined objectively by the new method, which relates these patterns to HF radar current patterns. We found two typical surface patterns: the first was that northeastward flows are dominant in the observation area and the second was that a clockwise eddy was also dominant in this area. The southwestward wind pattern was strongly related to the dominant clockwise eddy pattern of the HF radar current field.     

Mapping dune dynamics by InSAR coherence

It is generally held that subtle changes in sandy environments are very difficult to detect in imagery. Nonetheless, this study demonstrates how synthetic aperture radar (SAR) interferometric decorrelation can be used to identify changes in individual sand dunes. The use of coherence maps over time facilitates the analysis of dune dynamics, both temporally and spatially. The Ashdod‐Nizzanim coastal dunes, along the southern coastal plain of Israel, were chosen as an illustrative example of the analysis of dune dynamics. High‐resolution TerraSAR‐X (TSX) radar images covering the entire research area were acquired for the period February to July 2012, together with meteorology data (wind and rain) for the area. The coherence results enabled the stability of individual dunes to be described as a function of time. It was found that the dune crests were more stable than the windward slopes and that the degree of stability was dependent on the distance of the dune from the sea. The results of this study show the potential of using interferometric synthetic aperture radar (InSAR) decorrelation for aeolian studies, even in areas characterized by low coherence. Copyright © 2017 John Wiley & Sons, Ltd.     

Tsunami detection by high-frequency radar in British Columbia: performance assessment of the time-correlation algorithm for synthetic and real events

The authors recently proposed a new method for detecting tsunamis using high-frequency (HF) radar observations, referred to as “time-correlation algorithm” (TCA; Grilli et al. Pure Appl Geophys 173(12):3895–3934, 2016a, 174(1): 3003–3028, 2017). Unlike standard algorithms that detect surface current patterns, the TCA is based on analyzing space-time correlations of radar signal time series in pairs of radar cells, which does not require inverting radial surface currents. This was done by calculating a contrast function, which quantifies the change in pattern of the mean correlation between pairs of neighboring cells upon tsunami arrival, with respect to a reference correlation computed in the recent past. In earlier work, the TCA was successfully validated based on realistic numerical simulations of both the radar signal and tsunami wave trains. Here, this algorithm is adapted to apply to actual data from a HF radar installed in Tofino, BC, for three test cases: (1) a simulated far-field tsunami generated in the Semidi Subduction Zone in the Aleutian Arc; (2) a simulated near-field tsunami from a submarine mass failure on the continental slope off of Tofino; and (3) an event believed to be a meteotsunami, which occurred on October 14th, 2016, off of the Pacific West Coast and was measured by the radar. In the first two cases, the synthetic tsunami signal is superimposed onto the radar signal by way of a current memory term; in the third case, the tsunami signature is present within the radar data. In light of these test cases, we develop a detection methodology based on the TCA, using a correlation contrast function, and show that in all three cases the algorithm is able to trigger a timely early warning.     

A short-term predictive system for surface currents from a rapidly deployed coastal HF radar network

In order to address the need for surface trajectory forecasts following deployment of coastal HF radar systems during emergency-response situations (e.g., search and rescue, oil spill), a short-term predictive system (STPS) based on only a few hours data background is presented. First, open-modal analysis (OMA) coefficients are fitted to 1-D surface currents from all available radar stations at each time interval. OMA has the effect of applying a spatial low-pass filter to the data, fills gaps, and can extend coverage to areas where radial vectors are available from a single radar only. Then, a set of temporal modes is fitted to the time series of OMA coefficients, typically over a short 12-h trailing period. These modes include tidal and inertial harmonics, as well as constant and linear trends. This temporal model is the STPS basis for producing up to a 12-h current vector forecast from which a trajectory forecast can be derived. We show results of this method applied to data gathered during the September 2010 rapid-response demonstration in northern Norway. Forecasted coefficients, currents, and trajectories are compared with the same measured quantities, and statistics of skill are assessed employing 16 24-h data sets. Forecasted and measured kinetic variances of the OMA coefficients typically agreed to within 10–15%. In one case where errors were larger, strong wind changes are suspected and examined as the cause. Sudden wind variability is not included properly within the STPS attack we presently employ and will be a subject for future improvement.     

VHF radar observations of surface currents off the northern Opal coast in the eastern English Channel

Two very high-frequency radars (VHFR) operating on the Opal coast of eastern English Channel provided a nearly continuous 35-day long dataset of surface currents over a 500 km² area at 0.6–1.8 km resolution. Argo drifter tracking and CTD soundings complemented the VHFR observations, which extended approximately 25 km offshore. The radar data resolve three basic modes of the surface velocity variation in the area, that are driven by tides, winds and freshwater fluxes associated with seasonal river discharge. The first mode, accounting for 90% of variability, is characterized by an along-shore flow pattern, whereas the second and third modes exhibit cross-shore, and eddy-like structures in the current velocity field. All the three modes show the dominant semi-diurnal variability and low-frequency modulation by the neap-spring tidal cycle. Although tidal forcing provides the major contribution to variability of local currents, baroclinicity plays an important role in shaping the 3D velocity field averaged over the tidal cycle and may strongly affect tracer dynamics on larger time scales. An empirical orthogonal function (EOF) decomposition and a spectral rotary analysis of the VHFR data reveal a discontinuity in the velocity field occurring approximately 10 km offshore which was caused by the reversal in the sign of rotation of the current vector. This feature of local circulation is responsible for surface current convergence on ebb, divergence on flood and strong oscillatory vertical motion. Spectral analysis of the observed currents and the results of the Agro drifter tracking indicate that the line of convergence approximately follows the 30-m isobath. The most pronounced feature of the radar-derived residual circulation is the along-coast intensification of surface currents with velocity magnitude of 0.25 m/s typical for the Regions of Freshwater Influence (ROFI). The analysis has provided a useful, exploratory examination of surface currents, suggesting that the circulation off the Opal coast is governed by ROFI dynamics on the hypertidal background.     

Surface current variability in the Keum River Estuary (South Korea) during summer 2002 as observed by high-frequency radar and coastal monitoring buoy

High-frequency (HF) radar observations of surface currents were conducted for 3 months during summer 2002 in the Keum River estuary. A comparison between HF radar-derived currents and directly measured ones form a buoy showed that the regression slope is close to 1 and the correlation coefficient greater than 0.86, with an RMS difference less than 13 cm/s which is less than 17% of the tidal current. This fairly good agreement allows us to use HF radar observation in investigating the surface flow and circulation in this tidal-current-dominant coastal-plume area. To examine the spatial variation in tidal current characteristics, as well as currents associated with non-tidal forcing, the HF radar-derived currents were separated into tidal and sub-tidal frequency currents. The overall pattern of M₂-current ellipse distribution in the study area showed a counterclockwise rotation, with the offshore maximum current direction to the northeast. Eccentricity, the direction of maximum current, and the phase of net motion of the ellipse changed near the estuary mouth and near the gap of the Saemangeum reclamation tide dyke due to the complex coastal geometry and the out-flowing jet during the ebb period.     

Characterization of ocean surface current properties from single site HF/VHF radar

Surface current mapping from HF/VHF coastal radars traditionally requires at least two distant sites. Vector velocities are estimated by combining the radial velocity components measured by the radars. In many circumstances (e.g., failures, interferences, logistics constraints), such a combination is not possible by lack of data from one station. Two methods are evaluated to get information on surface circulation from a single site radar: the Vectorial Reconstruction Method (VRM) for current vector mapping and the Vortex Identification Method (VIM) for detecting eddy-like structures. The VRM assumes a non-divergent horizontal surface current, and the VIM analyzes radial velocities and their radial and orthoradial gradients. These two methods are tested on modeled and measured data sets in the Northwestern Mediterranean Sea where both high-resolution ocean circulation model and radar campaigns are available. The VRM performance is strongly limited by the divergence-free hypothesis which was not satisfied in our real data. The VIM succeeded in detection of vortex in the Gulf of Lions and from an operating single site radar located on the Provence coasts in summer.     

Surface currents and winds at the Delaware Bay mouth

Knowledge of the circulation of estuaries and adjacent shelf waters has relied on hydrographic measurements, moorings, and local wind observations usually removed from the region of interest. Although these observations are certainly sufficient to identify major characteristics, they lack both spatial resolution and temporal coverage. High-resolution synoptic observations are required to identify important coastal processes at smaller scales. Long observation periods are needed to properly sample low-frequency processes that may also be important. The introduction of high-frequency (HF) radar measurements and regional wind models for coastal studies is changing this situation. Here we analyze synoptic, high-resolution surface winds and currents in the Delaware Bay mouth over an 8-month period (October 2007 through May 2008). The surface currents were measured by two HF radars while the surface winds were extracted from a data-assimilating regional wind model. To illustrate the utility of these monitoring tools we focus on two 45-day periods which previously were shown to present contrasting pictures of the circulation. One, the low-outflow period is from 1 October through 14 November 2007; the other is the high-outflow period from 3 March through 16 April 2008. The large-scale characteristics noted by previous workers are clearly corroborated. Specifically the M2 tide dominates the surface currents, and the Delaware Bay outflow plume is clearly evident in the low frequency currents. Several new aspects of the surface circulation were also identified. These include a map of the spatial variability of the M2 tide (validating an earlier model study), persistent low-frequency cross-mouth flow, and a rapid response of the surface currents to a changing wind field. However, strong wind episodes did not persist long enough to set up a sustained Ekman response.     

Ocean Surface Geostrophic Circulation Climatology and Annual Variations Inferred from Satellite Altimetry and GOCE Gravity Data

We have studied, for the first time, variations in absolute surface geostrophic currents (SGC) using satellite data only. The proposed approach combines 18 years’ altimetry data, which provide reliable measurements of absolute sea level (ASL), with a gravity field and steady-state ocean circulation explorer geoid model to obtain dynamic topography, and achieves unprecedented precision and accuracy. Our proposal overcomes the main limitations of existing approaches based solely on altimetry data (which suffer from lack of an independent reference for derivation of ASL maps), and approximations based on in-situ data (which are characterized by a sparse and inhomogeneous coverage in time and space). Features of annual variations of SGC are also addressed. As a result of our study we provide new absolute SGC climatology in the form of a 52-week data set of surface current fields, gridded at quarter degree longitude and latitude resolution and resolving spatial scales as short as 140 km. For presentation, this data set is averaged monthly and the results, presented as monthly climatology, are compared with climatology based on in-situ observations from drifter data.     

Forest-height inversion using repeat-pass spaceborne polInSAR data

Forest-height inversion using airborne double-antenna synthetic aperture radar(SAR)systems has been widely researched,leading to increasing accuracy.Polarimetric SAR Interferometry(PolInSAR)data from spaceborne single-antenna SAR systems,which are influenced by temporal decorrelation,have difficulty inverting forest height.Given the temporal decorrelation effect,the classical random volume over ground(RVoG)model has been proven to invert forest height with significant errors,using repeat-pass PolInSAR data.In consideration of this problem,the temporal decorrelation RVoG(TD-RVoG;based on the RVoG)model was proposed.In this study,an improved TD-RVoG model is presented,with a new temporal decorrelation function.Compared with TD-RVoG,the new model has fewer unknown parameters and can be applied in a three-stage inversion procedure.Validity of the new model is demonstrated by Advanced Land Observing Satellite/Phased Array type L-band SAR(ALOS/PALSAR)data.Results show that the improved TD-RVoG has better accuracy,with inversion error less than 1.5m.     

Assimilation of Doppler Weather Radar Radial Velocity and Reflectivity Observations in WRF-3DVAR System for Short-Range Forecasting of Convective Storms

In this paper the impact of Doppler weather radar (DWR) reflectivity and radial velocity observations for the short range forecasting of a tropical storm and associated rainfall event have been examined. Doppler radar observations of a tropical storm case that occurred during 29–30 October 2006 from SHARDWR (13.6° N, 80.2° E) are assimilated in the WRF 3DVAR system. The observation operator for radar reflectivity and radial velocity is included within latest version of WRF 3DVAR system. Keeping all model physics the same, three experiments were conducted at a horizontal resolution of 30?km. In the control experiment (CTRL), NCEP Final Analysis (FNL) interpolated to the model grid was used as the initial condition for 48-h free forecast. In the second experiment (NODWR), 6-h assimilation cycles have been carried out using all conventional (radiosonde and surface data) and non-conventional (satellite) observations from the Global Telecommunication System (GTS). The third experiment (DWR) is the same as the second, except Doppler radar radial velocity and reflectivity observations are also used in the assimilation cycle. Continuous 6-h assimilation cycle employed in the WRF-3DVAR system shows positive impact on the rainfall forecast. Assimilation of DWR data creates several small scale features near the storm centre. Additional sensitivity experiments were conducted to study the individual impact of reflectivity and radial velocity in the assimilation cycle. Radar data assimilation with reflectivity alone produced large analysis response on both thermodynamical and dynamical fields. However, radial velocity assimilation impacted only on dynamical fields. Analysis increments with radar reflectivity and radial velocity produce adjustments in both dynamical and thermodynamical fields. Verification of QPF skill shows that radar data assimilation has a considerable impact on the short range precipitation forecast. Improvement of the QPF skill with radar data assimilation is more clearly seen in the heavy rainfall (for thresholds >7?mm) event than light rainfall (for thresholds of 1 and 3?mm). The spatial pattern of rainfall is well simulated by the DWR experiment and is comparable to TRMM observations.     

Correction of inertial oscillations by assimilation of HF radar data in a model of the Ligurian Sea

This article aims at analyzing if high-frequency radar observations of surface currents allow to improve model forecasts in the Ligurian Sea, where inertial oscillations are a dominant feature. An ensemble of ROMS models covering the Ligurian Sea, and nested in the Mediterranean Forecasting System, is coupled with two WERA high-frequency radars. A sensitivity study allows to determine optimal parameters for the ensemble filter. By assimilating observations in a single point, the obtained correction shows that the forecast error covariance matrix represents the inertial oscillations, as well as large- and meso-scale processes. Furthermore, it is shown that the velocity observations can correct the phase and amplitude of the inertial oscillations. Observations are shown to have a strong effect during approximately half a day, which confirms the importance of using a high temporal observation frequency. In general, data assimilation of HF radar observations leads to a skill score of about 30% for the forecasts of surface velocity.     

Investigation of the scale-dependent variability of radar-rainfall and rain gauge error covariance

There is a significant spatial sampling mismatch between radar and rain gauge data. The use of rain gauge data to estimate radar-rainfall error variance requires partitioning of the variance of the radar and rain gauge difference to account for the sampling mismatch. A key assumption in the literature pertaining to the error variance separation method used to partition the variance is that the covariance between radar-rainfall error and the error of rain gauges in representing radar sampling domain is negligible. Our study presents the results of an extensive test of this assumption. The test is based on empirical data and covers temporal scales ranging from 0.25 to 24 h and spatial scales ranging from 1 to 32 km. We used a two-year data set from two high quality and high density rain gauge networks in Oklahoma and excluded the winter months. The results obtained using a resampling procedure show that covariance can be considerable at large scales due to the significant variability. As the variability of the covariance rapidly increases with larger spatial and shorter temporal scales, applications of the error variance separation method at those scales require more caution. The variability of the covariance and one of its constituting variables, the variance ratio of radar and gauge errors, shows simple scaling behavior well characterized by a power-law.