This paper aims to offer the first detailed inter-comparison of the performance from the numerical weather prediction models Consortium for Small-scale Modeling (COSMO) and Icosahedral Nonhydrostatic General Circulation Model, Limited Area Mode (ICON-LAM), integrated for the Romanian territory at the horizontal resolution of 2.8 km. As the ICON numerical model is set to replace COSMO, a comparison is carried out between the operational configurations of the two models. First, two cases with severe weather (strong atmospheric instability, observed heavy precipitation, and strong wind) are analyzed: February 3-6, 2020 (heavy precipitation [snow] and very strong wind) and May 3-5, 2020 (heavy precipitation). This is followed by a statistical inter-comparison between the two models for the summer of 2020 (June, July, August). A statistical evaluation of the forecast quality from the two models is performed objectively, through statistical scores computed using surface observations from all available meteorological stations on the Romanian territory. Stratifications depending on station altitude and location are carried out, with emphasis on stations of particular interest, depending on the evolution of the synoptic situation. Following the statistical evaluation, results for the precipitation forecast do not show significant improvement in favor of either model. However, ICON-2.8 km mostly outperforms COSMO-2.8 km for surface parameters.

Statistical Intercomparison of Similarity Metrics in Sea Level Pressure Pattern Classification

Statistical intercomparison and validation of multisensory aerosol optical depth retrievals over three AERONET sites in Kenya, East Africa

Large-scale atmospheric circulations associated with 133 moderate to heavy cold-weather precipitation events recorded at Mehrabad station in Tehran, Iran, during the period 1951–2013 are analysed. To this end, the performance of un-rotated, orthogonally rotated and obliquely rotated solutions of T-mode principal component analysis (PCA) is examined in classifying the atmospheric circulations into a few representative circulation types (CTs). The T-mode PCAs were applied to the 500-hPa geopotential height for the events in a domain from 10∘E to 70∘E and from 20∘N to 50∘N. The first six leading principal components were retained and then orthogonally and obliquely rotated using varimax and promax solutions, respectively. Statistical inter-comparison of the CTs obtained using the three solutions suggests that the obliquely rotated solution is the better choice for circulation classification in the present study. The six CTs obtained using the oblique rotation were then linked to the daily total precipitation and daily mean temperature variability at Tehran station as well as to the standardized anomalies of the daily total precipitation and mean daily temperature of a dense network of stations distributed across Iran. It is found that the CTs identified, though generally comparable in producing significant precipitation in Tehran, vary in their potential to bring cold weather and generate snowfall in Tehran specifically and in the country in general. While the first three CTs give rise to regional patterns of standardized precipitation anomalies centred in Tehran, the next three CTs leave a pronounced precipitation signature almost across the whole country. As regards the standardized temperature anomalies, with the exception of one CT that causes deep and widespread negative standardized anomalies over most parts of the country, the other CTs are characterized with a dipolar structure of a deep intrusion of cold weather to the west and prevailing warm weather to the east of the country.

Abstract. The spatio-temporal variability of integrated water vapour (IWV) on small scales of less than 10 km and hours is assessed with data from the 2 months of the High Definition Clouds and Precipitation for advancing Climate Prediction (HD(CP)2) Observational Prototype Experiment (HOPE). The statistical intercomparison of the unique set of observations during HOPE (microwave radiometer (MWR), Global Positioning System (GPS), sun photometer, radiosondes, Raman lidar, infrared and near-infrared Moderate Resolution Imaging Spectroradiometer (MODIS) on the satellites Aqua and Terra) measuring close together reveals a good agreement in terms of random differences (standard deviation ≤1 kg m−2) and correlation coefficient (≥ 0.98). The exception is MODIS, which appears to suffer from insufficient cloud filtering. For a case study during HOPE featuring a typical boundary layer development, the IWV variability in time and space on scales of less than 10 km and less than 1 h is investigated in detail. For this purpose, the measurements are complemented by simulations with the novel ICOsahedral Nonhydrostatic modelling framework (ICON), which for this study has a horizontal resolution of 156 m. These runs show that differences in space of 3–4 km or time of 10–15 min induce IWV variabilities on the order of 0.4 kg m−2. This model finding is confirmed by observed time series from two MWRs approximately 3 km apart with a comparable temporal resolution of a few seconds. Standard deviations of IWV derived from MWR measurements reveal a high variability (> 1 kg m−2) even at very short time scales of a few minutes. These cannot be captured by the temporally lower-resolved instruments and by operational numerical weather prediction models such as COSMO-DE (an application of the Consortium for Small-scale Modelling covering Germany) of Deutscher Wetterdienst, which is included in the comparison. However, for time scales larger than 1 h, a sampling resolution of 15 min is sufficient to capture the mean standard deviation of IWV. The present study shows that instrument sampling plays a major role when climatological information, in particular the mean diurnal cycle of IWV, is determined.

Abstract A statistical method is developed for comparing precipitation data from measurements performed by (hypothetical) perfect instruments using a recently developed stochastic model of rainfall. The stochastic dynamical equation that describes the underlying random process naturally leads to a consistent spectrum and incorporates the subtle interdependence of the length and time scales governing the statistical fluctuations of the rain rate field. The main attraction of such a model is that the complete set of second‐moment statistics embodied in the space‐time covariance of both the area‐averaged instantaneous rain rate (represented by radar or passive microwave data near the ground) and the time‐averaged point rain rate (represented by rain gauge data) can be expressed as suitable integrals over the spectrum. With the help of this framework, the model allows one to carry out a faithful intercomparison of precipitation estimates derived from radar or passive microwave remote sensing over an area with direct observations by rain gauges or disdrometers, assuming all the measuring instruments to be ideal. A standard linear regression analysis approach to the intercomparison of radar and gauge rain rate estimates is formulated in terms of the appropriate observed and model‐derived quantities. We also estimate the relative sampling error as well as separate absolute sampling errors for radar and gauge measurements of rainfall from the spectral model.

New color‐measuring instruments known as multiangle spectrophotometers have been recently created to measure and characterize the goniochromism of special‐effect pigments in many materials with a particular visual appearance (metallic, interference, pearlescent, sparkle, or glitter). These devices measure the gonioapparent color from the spectral relative reflectance factor and the L*a*b* values of the sample with different illumination and observation angles. These angles usually coincide with requirements marked in American Society for Testing and Materials (ASTM) and Deutsches Institut Für Normung standards relating to the gonioapparent color, but the results of comparisons between these instruments are still inconclusive. Therefore, the main purpose of this study is to compare several multiangle spectrophotometers at a reproducibility level according to ASTM E2214‐08 guidelines. In particular, we compared two X‐Rite multi‐gonio spectrophotometers (MA98 and MA68II), a Datacolor multi‐gonio spectrophotometer (FX10), and a BYK multi‐gonio spectrophotometer (BYK‐mac). These instruments share only five common measurement geometries: 45° × −30° (as 15°), 45° × −20° (as 25°), 45° × 0° (as 45°), 45° × 30° (as 75°), 45° × 65° (as 110°). Specific statistical studies were used for the reproducibility comparison, including a Hotelling test and a statistical intercomparison test to determine the confidence interval of the partial color differences ΔL*, Δa*, Δb*, and the total color difference ΔE*ab. This was conducted using a database collection of 88 metallic and pearlescent samples that were measured 20 times without the replacement of all the instruments. The final findings show that in most measurement geometries, the reproducibility differences between pairs of instruments are statistically significant, although in general, there is a better reproducibility level at certain common geometries for newer instruments (MA98 and BYK‐mac). This means that these differences are due to systematic or bias errors (angle tolerances for each geometry, photometric scales, white standards, etc.), but not exclusively to random errors. However, neither of the statistical tests used is valid to discriminate and quantify the detected bias errors in this comparison between instruments. © 2012 Wiley Periodicals, Inc. Col Res Appl, 38, 160–167, 2013.

Abstract. This paper summarizes and classifies the various approaches to validation of remote measurements of atmospheric state variables, and tries to recommend a clear and unambiguous terminology. The following approaches have been identified: Intercomparison of individual profiles for accuracy validation; statistical comparison of matched pairs of measurements with respect to bias determination and precision validation; statistical intercomparison of randomly sampled measurements by two instruments, and comparison of a single measurement to an ensemble of measurements. Applicable statistics are shortly reviewed, and recipes for evaluation of the co-incidence error due to less than perfect co-incidences are presented. An approach is suggested to quantitatively validate profile measurements when full covariance matrices are unavailable.

The ability to predict the arrival of interplanetary shocks near earth is of great interest in space weather because of their relationship to sudden impulses and geomagnetic storms. A number of models have been developed for this purpose. For models to be used in forecasting, it is important to provide verification in the operational environment using standard statistical techniques because this enables the intercomparison of different models. A verification method is described here, comparing the prediction capabilities of four models that use solar observations for input. Three of the models are based on metric Type II radio burst observations, and one uses halo/partial-halo coronal mass ejections. A method of associating solar events with interplanetary shocks is described. The predictions are compared to associated shocks observed at L1 by the Advanced Composition Explorer (ACE) spacecraft. The time period of this study is January 2002-May 2002. Although the data sample is small, the statistical intercomparison of the results of these models is presented as a demonstration of the verification method.

The objective of the present study was the elaboration of a procedure for the determination of Y, La, Ce, Pr and Nd in soils by spectrophotometry with Arsenazo III preceded by a separation-concentration stage, which includes coprecipitation and ion exchange. Multielement analysis by energy dispersive X-ray fluorescence (including Y, La, Ce and Nd) and flame atomic absorption spectrophotometry was carried out simultaneously in order to obtain a general characterization of the soil samples. Certified reference materials and statistical intercomparison of the obtained results were used to evaluate the accuracy of the methods. The precision was examined by analyzing replicate samples.

A statistical intercomparison between “urban” and “rural” precipitation chemistry data from greater Manchester and two nearby secondary national network sites in the United Kingdom

On statistical intercomparison of EV1 estimators by Monte Carlo simulation