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Larry K. Berg and Peter J. Lamb
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Jonas Olsson, Peter Berg, and Akira Kawamura

Abstract

Many hydrological hazards are closely connected to local precipitation (extremes), especially in small and urban catchments. The use of regional climate model (RCM) data for small-scale hydrological climate change impact assessment has long been nearly unfeasible because of the low spatial resolution. The RCM resolution is, however, rapidly increasing, approaching the size of small catchments and thus potentially increasing the applicability of RCM data for this purpose. The objective of this study is to explore to what degree subhourly temporal precipitation statistics in an RCM converge to observed point statistics when gradually increasing the resolution from 50 to 6 km. This study uses precipitation simulated by RCA3 at seven locations in southern Sweden during 1995–2008. A positive impact of higher resolution was most clearly manifested in 10-yr intensity–duration–frequency (IDF) curves. At 50 km the intensities are underestimated by 50%–90%, but at 6 km they are nearly unbiased, when averaged over all locations and durations. Thus, at 6 km, RCA3 apparently generates low-frequency subdaily extremes that resemble the values found in point observations. Also, the reproduction of short-term variability and less extreme maxima were overall improved with increasing resolution. For monthly totals, a slightly increased overestimation with increasing resolution was found. The bias in terms of wet fraction and wet spell characteristics was overall not strongly dependent on resolution. These metrics are, however, influenced by the cutoff threshold used to separate between wet and dry time steps as well as the wet spell definition.

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Philippe Lucas-Picher, Fredrik Boberg, Jens H. Christensen, and Peter Berg

Abstract

To retain the sequence of events of a regional climate model (RCM) simulation driven by a reanalysis, a method that has not been widely adopted uses an RCM with frequent reinitializations toward its driving field. In this regard, this study highlights the benefits of an RCM simulation with frequent (daily) reinitializations compared to a standard continuous RCM simulation. Both simulations are carried out with the RCM HIRHAM5, driven with the European Centre for Medium-Range Weather Forecasts (ECMWF) Interim Re-Analysis (ERA-Interim) data, over the 12-km-resolution European Coordinated Regional Climate Downscaling Experiment (CORDEX) domain covering the period 1989–2009. The analysis of daily precipitation shows improvements in the sequence of events and the maintenance of the added value from the standard continuous RCM simulation. The validation of the two RCM simulations with observations reveals that the simulation with reinitializations indeed improves the temporal correlation. Furthermore, the RCM simulation with reinitializations has lower systematic errors compared to the continuous simulation, which has a tendency to be too wet. A comparison of the distribution of wet day precipitation intensities shows similar added value in the continuous and reinitialized simulations with higher variability and extremes compared to the driving field ERA-Interim. Overall, the results suggest that the finescale climate dataset of the RCM simulation with reinitializations better suits the needs of impact studies by providing a sequence of events matching closely the observations, while limiting systematic errors and generating reliable added value. Downsides of the method with reinitializations are increased computational costs and the introduction of temporal discontinuities that are similar to those of a reanalysis.

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Jacob Berg, Edward G. Patton, and Peter P. Sullivan

Abstract

Large-eddy simulation (LES) is used to model turbulent winds in a nominally neutral atmospheric boundary layer at varying mesh resolutions. The boundary layer is driven by wind shear with zero surface heat flux and is capped by a stable inversion. Because of entrainment the boundary layer is in a weakly stably stratified regime. The simulations use meshes varying from 1282 × 64 to 10242 × 512 grid points in a fixed computational domain of size (2560, 2560, 896) m. The subgrid-scale (SGS) parameterizations used in the LES vary with the mesh spacing. Low-order statistics, spectra, and structure functions are compared on the different meshes and are used to assess grid convergence in the simulations. As expected, grid convergence is primarily achieved in the middle of the boundary layer where there is scale separation between the energy-containing and dissipative eddies. Near the surface second-order statistics do not converge on the meshes studied. The analysis also highlights differences between one-dimensional and two-dimensional velocity spectra; differences are attributed to sampling errors associated with aligning the horizontal coordinates with the vertically veering mean wind direction. Higher-order structure functions reveal non-Gaussian statistics on all scales, but are highly dependent on the mesh resolution. A generalized logarithmic law and a k −1 spectral scaling regime are identified with mesh-dependent parameters in agreement with previously published results.

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Claudia Lorrai, Daniel F. McGinnis, Peter Berg, Andreas Brand, and Alfred Wüest

Abstract

The eddy correlation technique is rapidly becoming an established method for resolving dissolved oxygen fluxes in natural aquatic systems. This direct and noninvasive determination of oxygen fluxes close to the sediment by simultaneously measuring the velocity and the dissolved oxygen fluctuations has considerable advantages compared to traditional methods. This paper describes the measurement principle and analyzes the spatial and temporal scales of those fluctuations as a function of turbulence levels. The magnitudes and spectral structure of the expected fluctuations provide the required sensor specifications and define practical boundary conditions for the eddy correlation instrumentation and its deployment. In addition, data analysis and spectral corrections are proposed for the usual nonideal conditions, such as the time shift between the sensor pair and the limited frequency response of the oxygen sensor. The consistency of the eddy correlation measurements in a riverine reservoir has been confirmed—observing a night–day transition from oxygen respiration to net oxygen production, ranging from −20 to +5 mmol m−2 day−1—by comparing two physically independent, eddy correlation instruments deployed side by side. The natural variability of the fluctuations calls for at least ∼1 h of flux data record to achieve a relative accuracy of better than ∼20%. Although various aspects still need improvement, eddy correlation is seen as a promising and soon-to-be widely applied method in natural waters.

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Clare E. Reimers, H. Tuba Özkan-Haller, Andrea T. Albright, and Peter Berg

Abstract

Interest in validating the eddy covariance (EC) technique under wave-induced flows led to a series of experiments in a 104-m-long large wave flume (LWF) using an acoustic Doppler velocimeter (ADV) and two oxygen microelectrodes (tips ~2 mm apart) mounted on a sturdy tripod. Four additional ADVs positioned within the flume provided comparative near-bed velocity measurements during experiments with irregular waves over a sand bed. These measurements revealed that modifications of local turbulence by the tripod frame were insignificant. However, errors in velocity measurements were at times observed for setups where the microelectrode tips protruded into the ADV’s measurement volume. Disparate oxygen microelectrode velocity effects (stirring sensitivities) combined with response time offsets were also identified as problems, adding biases to EC flux derivations. Microelectrode velocity effects were further investigated through modeling designed to mimic the LWF data, and through examination of a 12-h dataset from the Oregon shelf. The modeling showed that under progressive waves, an artificial EC flux, or bias, arises most severely when the velocity sensitivity of the microelectrode is unequal in opposing flow directions or augmented by horizontal currents, and the velocity and oxygen data are not perfectly aligned in time. Sensitivities to wave motions were seen in the oxygen measurements from the Oregon shelf, contributing to an average flux of +2.7 ± 0.6 mmol m−2 day−1 (SE, n = 22) at wave frequencies. Since overall EC fluxes equaled only −4.1 ± 1.8 mmol m−2 day−1 (SE, n = 22), sources of EC biasing coupled to waves cannot be ruled out as potential problems for estimating exact benthic oxygen fluxes under common continental shelf field conditions.

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Curt Covey, Peter J. Gleckler, Charles Doutriaux, Dean N. Williams, Aiguo Dai, John Fasullo, Kevin Trenberth, and Alexis Berg

Abstract

Metrics are proposed—that is, a few summary statistics that condense large amounts of data from observations or model simulations—encapsulating the diurnal cycle of precipitation. Vector area averaging of Fourier amplitude and phase produces useful information in a reasonably small number of harmonic dial plots, a procedure familiar from atmospheric tide research. The metrics cover most of the globe but down-weight high-latitude wintertime ocean areas where baroclinic waves are most prominent. This enables intercomparison of a large number of climate models with observations and with each other. The diurnal cycle of precipitation has features not encountered in typical climate model intercomparisons, notably the absence of meaningful “average model” results that can be displayed in a single two-dimensional map. Displaying one map per model guides development of the metrics proposed here by making it clear that land and ocean areas must be averaged separately, but interpreting maps from all models becomes problematic as the size of a multimodel ensemble increases.

Global diurnal metrics provide quick comparisons with observations and among models, using the most recent version of the Coupled Model Intercomparison Project (CMIP). This includes, for the first time in CMIP, spatial resolutions comparable to global satellite observations. Consistent with earlier studies of resolution versus parameterization of the diurnal cycle, the longstanding tendency of models to produce rainfall too early in the day persists in the high-resolution simulations, as expected if the error is due to subgrid-scale physics.

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Irena Ott, Doris Duethmann, Joachim Liebert, Peter Berg, Hendrik Feldmann, Juergen Ihringer, Harald Kunstmann, Bruno Merz, Gerd Schaedler, and Sven Wagner

Abstract

The impact of climate change on three small- to medium-sized river catchments (Ammer, Mulde, and Ruhr) in Germany is investigated for the near future (2021–50) following the Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenarios (SRES) A1B scenario. A 10-member ensemble of hydrological model (HM) simulations, based on two high-resolution regional climate models (RCMs) driven by two global climate models (GCMs), with three realizations of ECHAM5 (E5) and one realization of the Canadian Centre for Climate Modelling and Analysis version 3 (CCCma3; C3) is established. All GCM simulations are downscaled by the RCM Community Land Model (CLM), and one realization of E5 is downscaled also with the RCM Weather Research and Forecasting Model (WRF). This concerted 7-km, high-resolution RCM ensemble provides a sound basis for runoff simulations of small catchments and is currently unique for Germany. The hydrology for each catchment is simulated in an overlapping scheme, with two of the three HMs used in the project. The resulting ensemble hence contains for each chain link (GCM–realization–RCM–HM) at least two members and allows the investigation of qualitative and limited quantitative indications of the existence and uncertainty range of the change signal. The ensemble spread in the climate change signal is large and varies with catchment and season, and the results show that most of the uncertainty of the change signal arises from the natural variability in winter and from the RCMs in summer.

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