scholarly journals Quality Assessment of a 1985–2007 Mediterranean Sea Reanalysis

2011 ◽  
Vol 28 (4) ◽  
pp. 569-589 ◽  
Author(s):  
Mario Adani ◽  
Srdjan Dobricic ◽  
Nadia Pinardi
Keyword(s):  
Mediterranean Sea ◽  
Sea Level ◽  
Root Mean Square ◽  
Three Dimensional ◽  
Optimal Interpolation ◽  
Mean Square ◽  
Sea Level Anomalies ◽  
Mean Fields ◽  
Along Track ◽  
Mean Square Errors

Abstract A simulation and two reanalyses from 1985 to 2007 have been produced for the Mediterranean Sea using different assimilation schemes: a reduced-order optimal interpolation [System for Ocean Forecast and Analysis (SOFA)] and a three-dimensional variational scheme (OceanVar). The observational dataset consists of vertical temperature and salinity in situ profiles and along-track satellite sea level anomalies; daily mean fields of satellite sea surface temperature are used for correcting the air–sea fluxes. This paper assesses the quality of the reanalyses with respect to observations and the simulation. Both the SOFA and OceanVar schemes give very similar root-mean-square errors and biases for temperature and salinity fields compared with the assimilated observations. The largest errors are at the thermocline level and in regions of large eddy field variability. However, OceanVar gives 20% better results for sea level anomaly root-mean-square error.

Global Climate Model Performance over Alaska and Greenland

2008 ◽  
Vol 21 (23) ◽  
pp. 6156-6174 ◽  
Author(s):  
John E. Walsh ◽  
William L. Chapman ◽  
Vladimir Romanovsky ◽  
Jens H. Christensen ◽  
Martin Stendel
Keyword(s):  
Sea Level ◽  
Root Mean Square ◽  
Global Climate ◽  
Systematic Errors ◽  
The Arctic ◽  
Future Climate Change ◽  
Mean Square ◽  
Sea Level Pressure ◽  
Level Pressure ◽  
Mean Square Errors

Abstract The performance of a set of 15 global climate models used in the Coupled Model Intercomparison Project is evaluated for Alaska and Greenland, and compared with the performance over broader pan-Arctic and Northern Hemisphere extratropical domains. Root-mean-square errors relative to the 1958–2000 climatology of the 40-yr ECMWF Re-Analysis (ERA-40) are summed over the seasonal cycles of three variables: surface air temperature, precipitation, and sea level pressure. The specific models that perform best over the larger domains tend to be the ones that perform best over Alaska and Greenland. The rankings of the models are largely unchanged when the bias of each model’s climatological annual mean is removed prior to the error calculation for the individual models. The annual mean biases typically account for about half of the models’ root-mean-square errors. However, the root-mean-square errors of the models are generally much larger than the biases of the composite output, indicating that the systematic errors differ considerably among the models. There is a tendency for the models with smaller errors to simulate a larger greenhouse warming over the Arctic, as well as larger increases of Arctic precipitation and decreases of Arctic sea level pressure, when greenhouse gas concentrations are increased. Because several models have substantially smaller systematic errors than the other models, the differences in greenhouse projections imply that the choice of a subset of models may offer a viable approach to narrowing the uncertainty and obtaining more robust estimates of future climate change in regions such as Alaska, Greenland, and the broader Arctic.

scholarly journals A Comparison between Coastal Altimetry Data and Tidal Gauge Measurements in the Gulf of Genoa (NW Mediterranean Sea)

2020 ◽  
Vol 8 (11) ◽  
pp. 862
Author(s):  
Paola Picco ◽  
Stefano Vignudelli ◽  
Luca Repetti
Keyword(s):  
Mediterranean Sea ◽  
Sea Level ◽  
Root Mean Square ◽  
High Frequency ◽  
Mean Square ◽  
Altimetry Data ◽  
Tidal Station ◽  
Nw Mediterranean ◽  
Mean Square Difference ◽  
Nw Mediterranean Sea

Satellite altimetry data from X-TRACK products were analyzed for an overall assessment of their capability to detect coastal sea level variability in the Ligurian Sea. Near-coastal altimetry data, collected from 2009 to 2016 along track n.044, were compared with simultaneous high frequency sampled data at the tidal station in Genoa (NW Mediterranean Sea). The two time series show a very good agreement: correlation between total sea level elevation from the altimeter and sea level variation from the tidal gauge is 0.92 and root mean square difference is 4.5 cm. Some relevant mismatches can be ascribed to the local high frequency coastal variability due to shelf and harbor oscillation detected at the tidal station, which might not be observed at the location of the altimetry points of measurement. The analysis evidences discrepancies (root mean square difference of 4.7 cm) between model results for open sea tides and harmonic analysis at the tidal station, mainly occurring at the annual and semiannual period. On the contrary, the important part of dynamic atmospheric correction due to the inverse barometer effect, well agrees with that computed at the tidal station.

scholarly journals Three Dimensional Radiative Effects in Passive Millimeter/Sub-Millimeter All-sky Observations

2020 ◽  
Vol 12 (3) ◽  
pp. 531
Author(s):  
Vasileios Barlakas ◽  
Patrick Eriksson
Keyword(s):  
Radiative Transfer ◽  
Root Mean Square ◽  
Three Dimensional ◽  
Mean Square ◽  
Photon Transport ◽  
Ice Cloud ◽  
Modeling Uncertainties ◽  
3D Effects ◽  
Mean Square Errors ◽  
Satellite Instruments

This study was conducted to quantify the errors prompted by neglecting three-dimensional (3D) effects, i.e., beam-filling and horizontal photon transport effects, at millimeter/sub-millimeter wavelengths. This paper gives an overview of the 3D effects that impact ice cloud retrievals of both current and proposed (Ice Cloud Imager) satellite instruments operating at frequencies of ≈186.3 and ≈668 GHz. The 3D synthetic scenes were generated from two-dimensional (2D) CloudSat (Cloud Satellite) observations over the tropics and mid-latitudes using a stochastic approach. By means of the Atmospheric Radiative Transfer Simulator (ARTS), three radiative transfer simulations were carried out: one 3D, one independent beam approximation (IBA), and one-dimensional (1D). The comparison between the 3D and IBA simulations revealed a small horizontal photon transport effect, with IBA simulations introducing mostly random errors and a slight overestimation (below 1 K). However, performing 1D radiative transfer simulations results in a significant beam-filling effect that increases primarily with frequency, and secondly, with footprint size. For a sensor footprint size of 15 km, the errors induced by neglecting domain heterogeneities yield root mean square errors of up to ≈4 K and ≈13 K at 186.3 GHz and 668 GHz, respectively. However, an instrument operating at the same frequencies, but with a much smaller footprint size, i.e., 6 km, is subject to smaller uncertainties, with a root mean square error of ≈2 K at 186.3 GHz and ≈7.1 K at 668 GHz. When designing future satellite instruments, this effect of footprint size on modeling uncertainties should be considered in the overall error budget. The smallest possible footprint size should be a priority for future sub-millimeter observations in light of these results.

scholarly journals Optical tomography of the aurora and EISCAT

1998 ◽  
Vol 16 (10) ◽  
pp. 1332-1342 ◽  
Author(s):  
H. U. Frey ◽  
S. Frey ◽  
B. S. Lanchester ◽  
M. Kosch
Keyword(s):  
Electron Density ◽  
Root Mean Square ◽  
Three Dimensional ◽  
Emission Computed Tomography ◽  
Mean Square ◽  
Arc Model ◽  
Reconstruction Methods ◽  
Mean Square Errors ◽  
The Given ◽  
Algebraic Reconstruction

Abstract. Tomographic reconstruction of the three-dimensional auroral arc emission is used to obtain vertical and horizontal distributions of the optical auroral emission. Under the given experimental conditions with a very limited angular range and a small number of observers, algebraic reconstruction methods generally yield better results than transform techniques. Different algebraic reconstruction methods are tested with an auroral arc model and the best results are obtained with an iterative least-square method adapted from emission-computed tomography. The observation geometry used during a campaign in Norway in 1995 is tested with the arc model and root-mean-square errors, to be expected under the given geometrical conditions, are calculated. Although optimum geometry was not used, root-mean-square errors of less than 2% for the images and of the order of 30% for the distribution could be obtained. The method is applied to images from real observations. The correspondence of original pictures and projections of the reconstructed volume is discussed, and emission profiles along magnetic field lines through the three-dimensionally reconstructed arc are calibrated into electron density profiles with additional EISCAT measurements. Including a background profile and the temporal changes of the electron density due to recombination, good agreement can be obtained between measured profiles and the time-sequence of calculated profiles. These profiles are used to estimate the conductivity distribution in the vicinity of the EISCAT site. While the radar can only probe the ionosphere along the radar beam, the three-dimensional tomography enables conductivity estimates in a large area around the radar site.Key words. Tomography · Aurora · EISCAT · Ionosphere · Conductivity

scholarly journals Histamine Control in Raw and Processed Tuna: A Rapid Tool Based on NIR Spectroscopy

Foods ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 885
Author(s):  
Sergio Ghidini ◽  
Luca Maria Chiesa ◽  
Sara Panseri ◽  
Maria Olga Varrà ◽  
Adriana Ianieri ◽  
...  
Keyword(s):  
Root Mean Square ◽  
Near Infrared ◽  
Nir Spectroscopy ◽  
Partial Least Square ◽  
Least Square ◽  
Partial Least Square Regression ◽  
Coefficient Of Determination ◽  
Mean Square ◽  
Tuna Fish ◽  
Mean Square Errors

The present study was designed to investigate whether near infrared (NIR) spectroscopy with minimal sample processing could be a suitable technique to rapidly measure histamine levels in raw and processed tuna fish. Calibration models based on orthogonal partial least square regression (OPLSR) were built to predict histamine in the range 10–1000 mg kg−1 using the 1000–2500 nm NIR spectra of artificially-contaminated fish. The two models were then validated using a new set of naturally contaminated samples in which histamine content was determined by conventional high-performance liquid chromatography (HPLC) analysis. As for calibration results, coefficient of determination (r2) > 0.98, root mean square of estimation (RMSEE) ≤ 5 mg kg−1 and root mean square of cross-validation (RMSECV) ≤ 6 mg kg−1 were achieved. Both models were optimal also in the validation stage, showing r2 values > 0.97, root mean square errors of prediction (RMSEP) ≤ 10 mg kg−1 and relative range error (RER) ≥ 25, with better results showed by the model for processed fish. The promising results achieved suggest NIR spectroscopy as an implemental analytical solution in fish industries and markets to effectively determine histamine amounts.

scholarly journals Evidence That Supertriangles Exist in Nature from the Vertical Projections of Koelreuteria paniculata Fruit

Symmetry ◽  
2021 ◽  
Vol 14 (1) ◽  
pp. 23
Author(s):  
Yuping Li ◽  
Brady K. Quinn ◽  
Johan Gielis ◽  
Yirong Li ◽  
Peijian Shi
Keyword(s):  
Root Mean Square ◽  
Goodness Of Fit ◽  
Mean Square ◽  
Sea Stars ◽  
Different Types ◽  
Koelreuteria Paniculata ◽  
Two Parameters ◽  
Mean Square Errors

Many natural radial symmetrical shapes (e.g., sea stars) follow the Gielis equation (GE) or its twin equation (TGE). A supertriangle (three triangles arranged around a central polygon) represents such a shape, but no study has tested whether natural shapes can be represented as/are supertriangles or whether the GE or TGE can describe their shape. We collected 100 pieces of Koelreuteria paniculata fruit, which have a supertriangular shape, extracted the boundary coordinates for their vertical projections, and then fitted them with the GE and TGE. The adjusted root mean square errors (RMSEadj) of the two equations were always less than 0.08, and >70% were less than 0.05. For 57/100 fruit projections, the GE had a lower RMSEadj than the TGE, although overall differences in the goodness of fit were non-significant. However, the TGE produces more symmetrical shapes than the GE as the two parameters controlling the extent of symmetry in it are approximately equal. This work demonstrates that natural supertriangles exist, validates the use of the GE and TGE to model their shapes, and suggests that different complex radially symmetrical shapes can be generated by the same equation, implying that different types of biological symmetry may result from the same biophysical mechanisms.

scholarly journals The effect of cyclones crossing the Mediterranean region on sea level anomalies at the Mediterranean Sea coast

2019 ◽  
Author(s):  
Piero Lionello ◽  
Dario Conte ◽  
Marco Reale
Keyword(s):  
Mediterranean Sea ◽  
Sea Level ◽  
Eastern Mediterranean ◽  
Storm Track ◽  
Western Mediterranean ◽  
Residual Water ◽  
Positive Anomaly ◽  
Western Basin ◽  
Sea Level Anomalies ◽  
The Mediterranean

Abstract. Large positive and negative sea level anomalies at the coast of the Mediterranean Sea are linked to intensity and position of cyclones moving along the Mediterranean storm track, with dynamics involving different factors. This analysis is based on a model hindcast and considers nine coastal stations, which are representative of sea level anomalies with different magnitude and characteristics. When a shallow water fetch is present, the wind around the cyclone center is the main cause of sea level positive and negative anomalies, depending on its onshore or offshore direction. The inverse barometer effect produces a positive anomaly at the coast near the cyclone pressure minimum and a negative anomaly at the opposite side of the Mediterranean Sea, because a cross-basin mean sea level pressure gradient is associated to the presence of a cyclone. Further, at some stations, negative sea level anomalies are reinforced by a residual water mass redistribution within the basin, which is associated with a transient response to the atmospheric pressure forcing. Though the link between presence of a cyclone in the Mediterranean has comparable importance for positive and negative anomalies, the relation between cyclone position and intensity is stronger for the magnitude of positive events. Area of cyclogenesis, track of the central minimum and position at the time of the event differ depending on the location where the sea level anomaly occurs and on its sign. The western Mediterranean is the main cyclogenesis area for both positive and negative anomalies, overall. Atlantic cyclones mainly produce positive sea level anomalies in the western basin. At the easternmost stations, positive anomalies are caused by Cyclogenesis in the Eastern Mediterranean. North Africa cyclogeneses are a major source of positive anomalies at the central African coast and negative anomalies at the eastern Mediterranean and North Aegean coast.

scholarly journals Reconstruction of the Surface Inshore Labrador Current from SWOT Sea Surface Height Measurements

2019 ◽  
Vol 11 (11) ◽  
pp. 1264 ◽  
Author(s):  
Zhimin Ma ◽  
Guoqi Han
Keyword(s):  
High Resolution ◽  
Root Mean Square ◽  
Surface Current ◽  
Sea Surface Height ◽  
Sea Surface ◽  
Root Mean Square Difference ◽  
Optimal Interpolation ◽  
Mean Square ◽  
Labrador Current ◽  
Mean Square Difference

Utilizing a high-resolution (2-km) coastal ocean model output off Eastern Newfoundland, this paper explores the potential for reconstructing the sea surface height (SSH) and the surface inshore Labrador Current from high-resolution SSH data of the upcoming Surface Water and Ocean Topography (SWOT) satellite mission. The model results are evaluated against in-situ data from tide gauges and nadir altimetry for the period from June to October, 2010. The hourly model SSH output is used as true SSH and sampled along-swath with expected measurement errors by using a SWOT simulator, which produces SWOT-like data. We reconstruct half-day SSH fields from the SWOT-like data using optimal interpolation and average them into weekly fields. The average normalized root-mean-square difference between the weekly reconstructed SSH field and the model SSH filed is 0.07 for the inshore Labrador Current. Between the geostrophic surface current derived from the reconstructed SSH field and the model surface current, the average normalized root-mean-square difference is 0.26 for the inshore Labrador Current. For the surface unit-depth transport of the inshore Labrador Current, the normalized root-mean-square differences are 0.32–0.38 between the reconstructed current and the model current.

scholarly journals The Accuracy of Real-Time hmF2 Estimation from Ionosondes

2020 ◽  
Vol 12 (17) ◽  
pp. 2671
Author(s):  
Carlo Scotto ◽  
Dario Sabbagh
Keyword(s):  
Data Analysis ◽  
Real Time ◽  
Root Mean Square ◽  
Magnetic Activity ◽  
Mean Square ◽  
Incoherent Scatter Radar ◽  
Incoherent Scatter ◽  
Scatter Radar ◽  
Mean Square Errors

A total of 4991 ionograms recorded from April 1997 to December 2017 by the Millstone Hill Digisonde (42.6°N, 288.5°E) were considered, with simultaneous Ne(h)[ISR] profiles recorded by the co-located Incoherent Scatter Radar (ISR). The entire ionogram dataset was scaled with both the Autoscala and ARTIST programs. The reliability of the hmF2 values obtained by ARTIST and Autoscala was assessed using the corresponding ISR values as a reference. Average errors Δ and the root mean square errors RMSE were computed for the whole dataset. Data analysis shows that both the Autoscala and ARTIST systems tend to underestimate hmF2 values with |Δ| in all cases less than 10 km. For high magnetic activity ARTIST offers better accuracy than Autoscala, as evidenced by RMSE[ARTIST] < RMSE[Autoscala], under both daytime and nighttime conditions, and considering all hours of the day. Conversely, under low and medium magnetic activity Autoscala tends to estimate hmF2 more accurately than the ARTIST system for both daytime and nighttime conditions, when RMSE[Autoscala] < RMSE[ARTIST]. However, RMSE[Autoscala] slightly exceeds RMSE[ARTIST] for the day as a whole. RMSE values are generally substantial (RMSE > 16 km in all cases), which places a limit on the results obtainable with real-time models that ingest ionosonde data.

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