The additive model with different smoothness for the components

We consider an additive regression model consisting of two components $f^0$ and $g^0$, where the first component $f^0$ is in some sense "smoother" than the second $g^0$. Smoothness is here described in terms of a semi-norm on the class of regression functions. We use a penalized least squares estimator $(\hat f, \hat g)$ of $(f^0, g^0)$ and show that the rate of convergence for $\hat f$ is faster than the rate of convergence for $\hat g$. In fact, both rates are generally as fast as in the case where one of the two components is known. The theory is illustrated by a simulation study. Our proofs rely on recent results from empirical process theory.Comment: 26 pages, 4 figure

Media stickiness and cognitive imprinting: inertia and creativity in cooperative work & learning with ICTs

This paper attempts to build a bridge between the fields of Computer Supported Cooperative Work and learning in online communities. Of particular importance is their use of information and communication technologies. Each field has independently developed notions of inertia in the behaviour of users of these technologies. The notion of media stickiness is examined and related to that of imprinting in learning communities. Various suggestions are made of value to both fields and further research identified.Education for the 21 st century - impact of ICT and Digital Resources ConferenceRed de Universidades con Carreras en Informática (RedUNCI

Introducing hydrometeor orientation into all-sky microwave and submillimeter assimilation

Numerical weather prediction systems still employ many simplifications when assimilating microwave radiances under all-sky conditions (clear sky, cloudy, and precipitation). For example, the orientation of ice hydrometeors is ignored, along with the polarization that this causes. We present a simple approach for approximating hydrometeor orientation, requiring minor adaption of software and no additional calculation burden. The approach is introduced in the RTTOV (Radiative Transfer for TOVS) forward operator and tested in the Integrated Forecast System (IFS) of the European Centre for Medium-Range Weather Forecasts (ECMWF). For the first time within a data assimilation (DA) context, this represents the ice-induced brightness temperature differences between vertical (V) and horizontal (H) polarization-the polarization difference (PD). The discrepancies in PD between observations and simulations decrease by an order of magnitude at 166.5 GHz, with maximum reductions of 10-15 K. The error distributions, which were previously highly skewed and therefore problematic for DA, are now roughly symmetrical. The approach is based on rescaling the extinction in V and H channels, which is quantified by the polarization ratio. Using dual-polarization observations from the Global Precipitation Mission microwave imager (GMI), suitable values for were found to be 1.5 and 1.4 at 89.0 and 166.5 GHz, respectively. The scheme was used for all the conical scanners assimilated at ECMWF, with a broadly neutral impact on the forecast but with an increased physical consistency between instruments that employ different polarizations. This opens the way towards representing hydrometeor orientation for cross-track sounders and at frequencies above 183.0 GHz where the polarization can be even stronger

Media stickiness and cognitive imprinting: inertia and creativity in cooperative work & learning with ICTs

This paper attempts to build a bridge between the fields of Computer Supported Cooperative Work and learning in online communities. Of particular importance is their use of information and communication technologies. Each field has independently developed notions of inertia in the behaviour of users of these technologies. The notion of media stickiness is examined and related to that of imprinting in learning communities. Various suggestions are made of value to both fields and further research identified.Education for the 21 st century - impact of ICT and Digital Resources ConferenceRed de Universidades con Carreras en Informática (RedUNCI

On the accuracy of RTTOV-SCATT for radiative transfer at all-sky microwave and submillimeter frequencies

With the new generation of microwave instruments and, especially, the Ice Cloud Imager covering submillimeter frequencies, it is necessary to evaluate the performance of the operational Radiative Transfer model for TOVS (RTTOV). Thus, an intercomparison study has been conducted between RTTOV and the reference model ARTS (Atmospheric Radiative Transfer Simulator), with an emphasis on cloudy and precipitating conditions, covering frequencies between ≈53.6 and ≈664.0 GHz. Overall a rather good agreement is found between the δ-Eddington solution embedded in the scattering solver of RTTOV, RTTOV-SCATT, and the discrete ordinate solution embedded in ARTS. Under clear-sky conditions, given a consistent spectroscopy, the agreement is within 0.4 K over all frequencies considered. When idealized, homogeneous cloudy conditions are employed, the agreement is mostly \ub12 K; this range is exceeded only at high scattering conditions. However, the following weaknesses are identified: the δ-Eddington solution fails to produce deep enough brightness temperature depressions at increasingly high scattering conditions and is not sufficient to capture the phase function structures at size parameters above 2–3; conditions typically found at around 664.0 GHz. When realistic hydrometeor profiles are employed, δ-Eddington leads to a root mean squared error of 1 K, with individual errors between 0 and 4 K. Infrequently, and in localized areas, larger discrepancies are identified, exceeding 10 K. However, these inaccuracies stemming from the simplified physics of RTTOV-SCATT were found at least an order of magnitude smaller than the cloud and precipitation representation errors assigned in data assimilation. Thus, we support the use of RTTOV-SCATT at submillimeter frequencies for operational purposes

On the accuracy of RTTOV-SCATT for radiative transfer at all-sky microwave and submillimeter frequencies

With the new generation of microwave instruments and, especially, the Ice Cloud Imager covering submillimeter frequencies, it is necessary to evaluate the performance of the operational Radiative Transfer model for TOVS (RTTOV). Thus, an intercomparison study has been conducted between RTTOV and the reference model ARTS (Atmospheric Radiative Transfer Simulator), with an emphasis on cloudy and precipitating conditions, covering frequencies between ≈53.6 and ≈664.0 GHz. Overall a rather good agreement is found between the δ-Eddington solution embedded in the scattering solver of RTTOV, RTTOV-SCATT, and the discrete ordinate solution embedded in ARTS. Under clear-sky conditions, given a consistent spectroscopy, the agreement is within 0.4 K over all frequencies considered. When idealized, homogeneous cloudy conditions are employed, the agreement is mostly ±2 K; this range is exceeded only at high scattering conditions. However, the following weaknesses are identified: the δ-Eddington solution fails to produce deep enough brightness temperature depressions at increasingly high scattering conditions and is not sufficient to capture the phase function structures at size parameters above 2–3; conditions typically found at around 664.0 GHz. When realistic hydrometeor profiles are employed, δ-Eddington leads to a root mean squared error of 1 K, with individual errors between 0 and 4 K. Infrequently, and in localized areas, larger discrepancies are identified, exceeding 10 K. However, these inaccuracies stemming from the simplified physics of RTTOV-SCATT were found at least an order of magnitude smaller than the cloud and precipitation representation errors assigned in data assimilation. Thus, we support the use of RTTOV-SCATT at submillimeter frequencies for operational purposes.Fil: Barlakas, Vasileios. Chalmers University of Technology; SueciaFil: Galligani, Victoria Sol. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Centro de Investigaciones del Mar y la Atmósfera. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Centro de Investigaciones del Mar y la Atmósfera; Argentina. Instituto Franco-Argentino sobre Estudios del Clima y sus Impactos; ArgentinaFil: Geer, Alan J.. European Centre For Medium-range Weather Forecasts; Reino UnidoFil: Eriksson, Patrick. Chalmers University of Technology; Sueci

A non‐parametric way to estimate observation errors based on ensemble innovations

Previous studies that inferred the observation error statistics from the innovation statistics can only provide the second moment of the error probability density function (pdf). However, the observation errors are sometimes non‐Gaussian, for example, for observation operators with unknown representation errors, or for bounded observations. In this study, we propose a new method, the Deconvolution‐based Observation Error Estimation (DOEE), to infer the full observation error pdf. DOEE does not rely on linear assumptions on the observation operator, the optimality of the data assimilation algorithm, or implicit Gaussian assumptions on the error pdf. The main assumption of DOEE is the availability of an ensemble of background forecasts following the independent and identically distributed (i.i.d.) assumption. We conduct idealized experiments to demonstrate the ability of the DOEE to accurately retrieve a non‐Gaussian (bimodal, skewed, or bounded) observation error pdf. We then apply the DOEE to construct a state‐dependent observation error model for satellite radiances by stratifying the observation errors based on cloud amount. In general, we find that the observation error pdfs in many categories are skewed. By adding a new predictor, total column water vapor (TCWV), into the state‐dependent model, we find that for cloudy pixels, when TCWV is small, the observation error pdfs are quite similar and Gaussian‐like, whereas when TCWV is large, the observation error pdfs differ for different cloud amount, while all of them are positively biased. This result suggests that exploring other predictors, like cloud type, might improve the stratification of the observation error model. We also discuss ways to include a non‐parametric observation error pdf into modern data assimilation schemes, including a consideration of the strong‐constraint 4D‐Var perspective, as well as the implications for other observation types including observations with bounded range

Bulk hydrometeor optical properties for microwave and sub-millimetre radiative transfer in RTTOV-SCATT v13.0

Satellite observations of radiation in the microwave and sub-millimetre spectral regions (broadly from 1 to 1000 GHz) can have strong sensitivity to cloud and precipitation particles in the atmosphere. These particles (known as hydrometeors) scatter, absorb, and emit radiation according to their mass, composition, shape, internal structure, and orientation. Hence, microwave and sub-millimetre observations have applications including weather forecasting, geophysical retrievals and model validation. To simulate these observations requires a scattering-capable radiative transfer model and an estimate of the bulk optical properties of the hydrometeors. This article describes the module used to integrate single-particle optical properties over a particle size distribution (PSD) to provide bulk optical properties for the Radiative Transfer for TOVS microwave and sub-millimetre scattering code, RTTOV-SCATT, a widely used fast model. Bulk optical properties can be derived from a range of particle models including Mie spheres (liquid and frozen) and non-spherical ice habits from the Liu and Atmospheric Radiative Transfer Simulator (ARTS) databases, which include pristine crystals, aggregates, and hail. The effects of different PSD and particle options on simulated brightness temperatures are explored, based on an analytical two-stream solution for a homogeneous cloud slab. The hydrometeor scattering "spectrum" below 1000 GHz is described, along with its sensitivities to particle composition (liquid or ice), size and shape. The optical behaviour of frozen particles changes in the frequencies above 200 GHz, moving towards an optically thick and emission-dominated regime more familiar from the infrared. This region is little explored but will soon be covered by the Ice Cloud Imager (ICI)