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The aim of this research was to describe, interpret, and analyze an objective reality of surgical nursing service management at Makassar Regional Hospital. A qualitative approach has been employed since the data were gathered through interviews, observation, and documentation. Some significant findings to emerge from this research are the general performance of surgical nursing service management at the Makassar Regional Hospital which have utilized management resources as inputs. Those are also determinably managed through proper managerial processes with some outputs referring to the hospital service standard indicator. The process of supervision in the context of surgical nursing service management automatically runs by forcing the implementation of valid Standard Operating Procedure in surgery. In line with that, the management evaluation have been done periodically but not in the context of core business process analysis. As a result, it is recommended for three features of the business process analysis to be further added: the first is by measuring the performance quality towards customers’ (patients) attributes for improving service accuracy and precision; the second is by updating the system to increase the process effectiveness of nursing service management through identified evaluation; and the last is by optimizing an efficient productivity.

Obstructive sleep apnea (OSA) severity assessment is based on manually scored respiratory events and their arbitrary definitions. Thus, we present an alternative method to objectively evaluate OSA severity independently of the manual scorings and scoring rules. A retrospective envelope analysis was conducted on 847 suspected OSA patients. Four parameters were calculated from the difference between the nasal pressure signal's upper and lower envelopes: average (AV), median (MD), standard deviation (SD), and coefficient of variation (CoV). We computed the parameters from the entirety of the recorded signals to perform binary classifications of patients using three different apnea–hypopnea index (AHI) thresholds (5-15-30). Additionally, the calculations were undertaken in 30-second epochs to estimate the ability of the parameters to detect manually scored respiratory events. Classification performances were assessed with areas under the curves (AUCs). As a result, the SD (AUCs ≥ 0.86) and CoV (AUCs ≥ 0.82) were the best classifiers for all AHI thresholds. Furthermore, non-OSA and severe OSA patients were separated well with SD (AUC = 0.97) and CoV (AUC = 0.95). Respiratory events within the epochs were identified moderately with MD (AUC = 0.76) and CoV (AUC = 0.82). In conclusion, envelope analysis is a promising alternative method by which to assess OSA severity without relying on manual scoring or the scoring rules of respiratory events. [ABSTRACT FROM AUTHOR]

Background: Breast symmetry remains a challenging quality to measure. The question arises of how much baseline breast symmetry exists in the female plastic surgical patient population.Material and methods: Several linear dimensional assessments were collected based on a retrospective analysis of objective data of women with natural breasts, who presented for an initial consultation in a plastic surgical clinic and were measured with the 3D Vectra Camera by the company Canfield Scientific Inc., U.S.A. The first 100 cases were extracted from the large database in alphabetical order. The nipple positions were examined, including the following linear dimensions: distances from the jugulum to the nipple, from the nipple to the inframammary fold, and from the nipple to midline. Furthermore, the under-breast widths were obtained. Results: The objective three-dimensional imaging method determined that all patients had some degree of asymmetry. The linear distances from the jugulum and midline to the nipple revealed that the measurements were larger on the left side. However, the nipple to the inframammary fold measurements were roughly the same. In the sample of plastic surgical patients, the average distance between the jugulum and nipple was around 20 cm, the distance between the nipple and inframammary fold was around 6.5 cm, the distance between the nipple and midline was around 10 cm, and the under-breast width was around 13 cm.On average, the jugulum-nipple distance on the right side was and 20.1±2.4 cm on the left side. The distance between the nipple and the inframammary fold was 6.4±1.1 cm, revealing a similar distribution on both sides. The mean distance from the nipple to the midline was much larger on the left side of the body at than on the right side at 9.4±1.3 cm. The under-breast width on the right side was slightly larger than the left side, with measurements of 13.4±1.8 cm versus 13.2±1.7 cm. Conclusion: Breast dimensions can be described comprehensively by an objective three-dimensional imaging process, which can detect asymmetry in all patients. The differences related to the nipple position were larger on the left side than the right regarding the distances from the jugulum and particularly the midline to the nipple, which seems to be of special importance, but not from the nipple to the inframammary fold.The linear measurements for the distances from the jugulum and the midline to the nipple are essential to accurate symmetry assessments and form an aesthetic triangle of the breast, which is a new term and the key to a simplified shape analysis.

The effect of considering correlated errors in AMV (Atmospheric Motion Vectors) satellite observations of wind in the local ensemble transform Kalman filter data assimilation system is studied. It is customary to use a diagonal covariance matrix of errors in observations taking part in assimilation. When assimilating satellite data with correlated errors, the data are thinned, and the values of diagonal elements of the error covariance matrix are often overestimated. This is accompanied by the loss of useful information about the correlation between the errors. The present study uses a different method: the elements of the error covariance matrix for AMV satellite observations are simulated using a second-order autoregressive function. It is shown that such approach reduces the root-mean-square error in initial data for a numerical weather prediction model, in particular on small scales, and improves the forecast quality. It is found that the application of the non-diagonal AMV observation error covariance matrix increases the accuracy of analysis and forecast fields. [ABSTRACT FROM AUTHOR]

Obstructive sleep apnea (OSA) severity assessment is based on manually scored respiratory events and their arbitrary definitions. Thus, we present an alternative method to objectively evaluate OSA severity independently of the manual scorings and scoring rules. A retrospective envelope analysis was conducted on 847 suspected OSA patients. Four parameters were calculated from the difference between the nasal pressure signal’s upper and lower envelopes: average (AV), median (MD), standard deviation (SD), and coefficient of variation (CoV). We computed the parameters from the entirety of the recorded signals to perform binary classifications of patients using three different apnea–hypopnea index (AHI) thresholds (5-15-30). Additionally, the calculations were undertaken in 30-second epochs to estimate the ability of the parameters to detect manually scored respiratory events. Classification performances were assessed with areas under the curves (AUCs). As a result, the SD (AUCs ≥ 0.86) and CoV (AUCs ≥ 0.82) were the best classifiers for all AHI thresholds. Furthermore, non-OSA and severe OSA patients were separated well with SD (AUC = 0.97) and CoV (AUC = 0.95). Respiratory events within the epochs were identified moderately with MD (AUC = 0.76) and CoV (AUC = 0.82). In conclusion, envelope analysis is a promising alternative method by which to assess OSA severity without relying on manual scoring or the scoring rules of respiratory events.

A new marine meteorological climatology named Marine Meteorological Atlas for Tropical Indian Ocean (MaMetAtTIO) is generated for tropical Indian Ocean (TIO). The climatology is derived from ship-based observations of International Comprehensive Ocean-Atmosphere Dataset (ICOADS) Release 3.0 and those obtained from the India Meteorological Department (IMD). The climatologies of several independent and derived variables are constructed and the framework is presented in detail. The enhancement in MaMetAtTIO is statistically evaluated with reference to ICOADS R3.0 climatology. ICOADS Release 3.0 dataset has been found to be self-robust, as there was no significant improvement in the monthly and annual climatology of independent variables in MaMetAtTIO even after adding new records to ICOADS Release 3.0. However, there are few filled grid points in the individual year–month summaries owing to the addition of unique data from IMD. An attempt to correct the systematic error in Beaufort estimated wind speed, has reduced the annual net heat flux for TIO by 14 W/m2. Furthermore, MaMetAtTIO is compared with in-situ data from moored buoys and Tropflux datasets. Two case studies (Madden–Julian oscillation (MJO) study, empirical orthogonal function (EOF) analysis) were undertaken to highlight the importance of adding individual observations to ICOADS R3.0 and the gridded fields of MaMetAtTIO. Better correlation (difference being significant) was observed between the time series derived from MaMetAtTIO and MJO index and the addition of new data resulted in filling of gaps in individual year–month summaries favourable to carry out statistical analyses such as EOF. Research highlights: Marine meteorological atlas constructed exclusively from ship observations. Gridded fields of annual, monthly climatologies and individual year–month summaries are available for all marine-meteorological parameters including fluxes. A long climatology dataset showing well-defined features of most of the climate phenomenon and their influences across tropical Indian Ocean. A 14 W/m2 reduction in net annual heat flux for tropical Indian Ocean obtained through observational error correction. [ABSTRACT FROM AUTHOR]

To clarify the role of thermohaline factors in the formation of climatic trends in the North Atlantic (NA) thermohaline circulation, the contributions of changes in potential temperature and salinity to trends of the stream function of the Atlantic meridional overturning circulation (AMOC) were determined. To do this, using the INMOM (Institute of Numerical Mathematics Ocean Model) and data of the EN4 electronic atlas (MetOffice, United Kingdom), the NA circulation was reconstructed by the diagnosis–adjustment method for the characteristic periods of 1951–2017, 1951–1990, and 1991–2017. In two selected periods of 1951–2017 and 1951–1990, all the main features of changes in the AMOC are explained mainly by temperature changes, which prevail over changes in salinity. At the same time, the observed trend towards weakening of the main core of the AMOC stream function from 1991 to 2017 is caused by changes in salinity, and the strengthening of the main core of the AMOC stream function from 1951 to 1990 is caused by changes in potential temperature. A relationship has been found between the trends of the AMOC stream function maximum at 38.5 N and differences between zonally-averaged sea levels at 34.5 N and 57.5 N, which can possibly be used as the variability index of the AMOC stream function. [ABSTRACT FROM AUTHOR]

We used the objective analysis method in conjunction with the successive correction method to assimilate MODerate resolution Imaging Spectroradiometer (MODIS) Aerosol Optical Depth (AOD) data into the Chimère model in order to improve the modeling of fine particulate matter (PM 2.5 ) concentrations and AOD field over Europe. A data assimilation module was developed to adjust the daily initial total column aerosol concentrations based on a forecast-analysis cycling scheme. The model is then evaluated during one-month winter period to examine how such a data assimilation technique pushes the model results closer to surface observations. This comparison showed that the mean biases of both surface PM 2.5 concentrations and the AOD field could be reduced from − 34 to −15% and from −45 to −27%. The assimilation, however, leads to false alarms because of the difficulty in distributing AOD 550 over different particle sizes. The impact of the influence radius is found to be small and depends on the density of satellite data. This work, although preliminary, is important in terms of near-real time air quality forecasting using the Chimère model and can be further developed to improve modeled PM 2.5 and ozone concentrations. [ABSTRACT FROM AUTHOR]

Gravimetry measurements from the GRACE and GRACE-Follow-On satellites provide observations of ocean bottom pressure (OBP), which can be differenced between basin boundaries to infer mass transport variability at a given level in the deep ocean. However, GRACE data products are limited in spatial resolution, and conflate signals from many depth levels along steep continental slopes. To improve estimates of OBP variability near steep bathymetry, ocean bottom pressure observations from a JPL GRACE mascon product are downscaled using an objective analysis procedure, with OBP covariance information from an ocean model with horizontal grid spacing of ∼18 km. In addition, a depth-based adjustment was applied to enhance correlations at similar depths. Downscaled GRACE OBP shows realistic representations of sharp OBP gradients across bathymetry contours and strong currents, albeit with biases in the shallow ocean. In validations at intraannual (3–12 month) timescales, correlations of downscaled GRACE data (with depth adjustment) and in situ bottom pressure recorder time series were improved in ∼79% of sites, compared to correlations that did not involve downscaled GRACE. Correlations tend to be higher at sites where the amplitude of the OBP signal is larger, while locations where surface eddy kinetic energy is high (e.g., Gulf Stream extension) are more likely to have no improvement from the downscaling procedure. The downscaling procedure also increases the amplitude (standard deviation) of OBP variability compared to the non-downscaled GRACE at most sites, resulting in standard deviations that are closer to in situ values. A comparison of hydrography-based transport from RAPID with estimates based on downscaled GRACE data suggests substantial improvement from the downscaling at intraannual timescales, though this improvement does not extend to longer interannual timescales. Possible efforts to improve the downscaling technique through process studies and analysis of alongtrack GRACE/GRACE-FO observations are discussed. [ABSTRACT FROM AUTHOR]

In this study, we developed a new high-resolution regional climatology (0.1° by 0.1° by 19 levels) in the East/Japan Sea. National Centers for Environmental Information and Korea Oceanic Data Center already released the regional climatology of East Asian seas including the East/Japan Sea with 0.1° by 0.1° resolution. It provides a reliable temperature and salinity structure compared to previous 1° or 0.25° climatologies. However, this study found an abnormal meridional temperature gradient problem when calculating geostrophic currents based on this new climatology. Geostrophic currents show a strong repetitive eastward flow along the 1° latitudinal band especially in the East/Japan Sea, which corresponds with abnormal meridional temperature gradients at the same areas. This problem could be related to the objective analysis procedure generating the high-resolution climatology. Here, we reproduced a high-resolution climatology without the abnormal meridional temperature gradient problem by using the optimal interpolation method. Results show that the meridional gradient problem can partly be attributed to both the use of the World Ocean Atlas background field on the 1° grid, and the spatial distribution of World Ocean database observation data; however, these are not the primary causes. We corrected the abnormal temperature gradient by increasing the meridional decorrelation length scale without losing the meso-scale feature in the East/Japan Sea, as shown by the wavelet analysis. Improvement of the new gridded field is also validated by using serial hydrographic data and the altimetry-derived surface current product.

The process of forensic handwriting examination consists of two steps: the first step is the objective phase of the process and requires correct ocular observation to make a note of similarities and dissimilarities in the two samples of writing; the second step is subjective phase and depends on proper evaluation of what is observed based on expert’s belief, assumption and experience. The second phase, because of its subjective nature, can also be exploited by dishonest expert resulting in conflicting evidence. This scenario is obviously disruptive for justice, and generally weakens the credibility of this type of evidence.

We used the objective analysis method in conjunction with the successive correction method to assimilate MODerate resolution Imaging Spectroradiometer (MODIS) Aerosol Optical Depth (AOD) data into the Chimère model in order to improve the modeling of fine particulate matter (PM2.5) concentrations and AOD field over Europe. A data assimilation module was developed to adjust the daily initial total column aerosol concentrations based on a forecast-analysis cycling scheme. The model is then evaluated during one-month winter period to examine how such a data assimilation technique pushes the model results closer to surface observations. This comparison showed that the mean biases of both surface PM2.5 concentrations and the AOD field could be reduced from −34 to −15% and from −45 to −27%. The assimilation, however, leads to false alarms because of the difficulty in distributing AOD550 over different particle sizes. The impact of the influence radius is found to be small and depends on the density of satellite data. This work, although preliminary, is important in terms of near-real time air quality forecasting using the Chimère model and can be further developed to improve modeled PM2.5 and ozone concentrations.

Gravimetry measurements from the GRACE and GRACE-Follow-On satellites provide observations of ocean bottom pressure (OBP), which can be differenced between basin boundaries to infer mass transport variability at a given level in the deep ocean. However, GRACE data products are limited in spatial resolution, and conflate signals from many depth levels along steep continental slopes. To improve estimates of OBP variability near steep bathymetry, ocean bottom pressure observations from a JPL GRACE mascon product are downscaled using an objective analysis procedure, with OBP covariance information from an ocean model with horizontal grid spacing of ∼18 km. In addition, a depth-based adjustment was applied to enhance correlations at similar depths. Downscaled GRACE OBP shows realistic representations of sharp OBP gradients across bathymetry contours and strong currents, albeit with biases in the shallow ocean. In validations at intraannual (3–12 month) timescales, correlations of downscaled GRACE data (with depth adjustment) and in situ bottom pressure recorder time series were improved in ∼79% of sites, compared to correlations that did not involve downscaled GRACE. Correlations tend to be higher at sites where the amplitude of the OBP signal is larger, while locations where surface eddy kinetic energy is high (e.g., Gulf Stream extension) are more likely to have no improvement from the downscaling procedure. The downscaling procedure also increases the amplitude (standard deviation) of OBP variability compared to the non-downscaled GRACE at most sites, resulting in standard deviations that are closer to in situ values. A comparison of hydrography-based transport from RAPID with estimates based on downscaled GRACE data suggests substantial improvement from the downscaling at intraannual timescales, though this improvement does not extend to longer interannual timescales. Possible efforts to improve the downscaling technique through process studies and analysis of alongtrack GRACE/GRACE-FO observations are discussed.

Zonally averaged characteristics of the North Atlantic (NA) thermohaline circulation are investigated in different phases of the Atlantic Multidecadal Oscillation (AMO) index over the past 70 years using ocean objective analyses EN4 and WOA13 and reanalyses GFDL, ESTOC, ORA-S4, and GECCO2. It is shown that similar thermohaline patterns appear in zonally averaged climatic trends and in differences in the composites of anomalies of the potential temperature and salinity fields for all data sets. To find out how the variability in the thermohaline state of waters in the NA is accompanied by the variability in its thermohaline circulation, we have analyzed the variability of the Atlantic Meridional Overturning Circulation (AMOC) stream function. The average AMOC stream functions calculated from ocean objective analyses and reanalyses, reflecting the NA thermohaline circulation, are generally similar to each other. Nonetheless, they can be divided according to their spatial structure into two groups: (EN4, WOA13, and GFDL) and (ESTOC, ORAS4, and GECCO2). In their trends and anomaly composite differences, the AMOC stream functions differ significantly among themselves, as well as from EN4 and WOA13. Moreover, the main distinction is in the sign of climatic trends and composite differences, which determines changes in the direction of the zonally averaged thermohaline circulation. It is found that positive and negative temperature (salinity) anomalies in alternating successive phases of the AMO index circulate with a period of roughly 60 years along the pathway of water in the AMOC, sinking into deep ocean layers at about 60° N and rising toward the surface at 25° N. This process is most pronounced for the EN4 and WOA13 objective analyses and ORAS4 reanalysis. It can be assumed that this mechanism contributes substantially to the formation of the AMO index phases. [ABSTRACT FROM AUTHOR]

Copyright of Al-Mustansiriya Journal of Arts is the property of Republic of Iraq Ministry of Higher Education & Scientific Research (MOHESR) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The Tibetan Plateau vortex (TPV) is a mesoscale weather system active in the near-surface layer, which is one of the major systems for the generation of precipitation in the Tibetan Plateau (TP). However, no long-term observations of the TPVs are available due to the scarcity of observations in the TP. Thereby, long-term, high-accuracy reanalysis products are a reliable source for the analysis of characteristic TPV activities and possible mechanisms behind. In the present study, an objective analysis method is implemented to obtain a complete dataset of TPV based on several reanalysis products, including the ERA-Interim, ERA40, JRA55, NCEP CFSR, and NASA MERRA2. The TPVs are detected and tracked by the minima in geopotential height at 500 hPa. Results indicate that the TPVs derived from multiple reanalysis products have quite similar spatial patterns and temporal variability. The characteristic parameters of the TPVs derived from a given reanalysis data are related to the resolution of this reanalysis product. Higher-resolution reanalysis products can yield more low-pressure systems, which explains why the TPVs derived from high-resolution reanalysis datasets generally have longer lifetime, stronger and larger vortex scale than those from low-resolution reanalysis products, although the total number of TPVs are similar. The annual average number of TPVs generated in the TP is 63.5, and these TPVs largely originate in the mountainous area of the central western TP around (34° N, 78–95° E) and a belt zone (30° N, 80–84° E) in the southern TP, where the elevation is around 5500 m. The TPVs often dissipate in low valleys and the lee side of mountains. They mainly occur in the warm season during May–September, most active in the summer and least active in the winter. More TPVs form in the daytime than in the nighttime. Those TPVs that move out of the TP account for less than 10–14% of all TPVs, and they usually follow three moving paths: eastward (6.9–7.8%), northeastward (2.3–3.4%) and southward (2.3–3.5%). [ABSTRACT FROM AUTHOR]

Nipple‐sparing mastectomies (NSMs) are accepted as safe oncologic procedures for select patient populations, but objective evaluation of aesthetic outcomes has not been clearly established. The purpose of this study was to utilize BCCT.core computer software to objectively evaluate NAC malposition following bilateral NSM with implant reconstruction and compare the analysis to an expert panel. Postoperative photographs of 43 patients who underwent bilateral NSM were analyzed with the BCCT.core and by an expert panel of plastic surgery residents and attendings. The panel was asked to only evaluate nipple asymmetry and position. The intraclass correlation coefficient (ICC) was used to determine interrater reliability (n = 12) and between expert panel ratings and BCCT.core ratings. Statistics were performed using SPSS statistical package version 24.0. The ICC for the expert panel interrater reliability was excellent (ICC = 0.941, 95% CI: 0.912‐0.964). The analysis between BCCT.core individual parameters, specifically the breast retraction assessment (ie, BRA score = the difference in nipple position between the two breasts assessing breast symmetry) and expert panel, showed statistically significant positive correlation. The parameters provided by the BCCT.core software were correlated with both the mean expert panel rating and BCCT.core ratings. Therefore, it is plausible that BCCT.core parameters could be used to objectively quantify NAC malposition/asymmetry and guide treatment in patients undergoing bilateral NSM with implant reconstruction. [ABSTRACT FROM AUTHOR]

As flood events become increasingly prevalent in coastal regions with sea level rise, multiple communities have deployed water level monitoring networks across estuaries in addition to existing tide gauges located primarily at immediate coasts. Due to the spatially-distributed nature of sensor deployments, however, water level data are only available at specific sensor locations during the time of monitoring. As a result, an information gap on water levels exists along estuarine channels outside of active monitoring locations. To fill such a gap, this study presents a physics-based empirical modeling approach to assimilate coastal water levels using observations from hyper-local water level sensors. We implement an Objective Analysis (OA) procedure for sensor observation datasets obtained from the Smart Sea Level Sensors project along the U.S. Georgia coasts, based on spatial covariance structures of water levels that are extracted from high-resolution coastal-ocean hydrodynamic simulations. The approach is validated using simulated water levels, which provide basis functions for spatial covariance information. Additionally, the implementation is validated using actual water levels from active monitoring stations. The assimilated results of water levels are compared to those obtained by the same OA procedure but with a commonly-used Gaussian covariance function, which lacks prior knowledge of spatial covariance structures. To demonstrate the capability of the assimilation approach, we extend its application to a hurricane event, during which other dynamic processes may be relevant to variability in coastal water levels. Overall, the presented approach provides an accurate and efficient estimation of estuarine water levels along channels, which can support community officials to promptly identify localized flood threats to critical infrastructure systems in coastal regions. • Objective Analysis is implemented to reconstruct water levels from sensor observations. • Spatial covariance statistics are derived from coastal-ocean hydrodynamic model simulations. • Variability in water levels is better captured by combining spatial covariance information. • Real-time assimilation can provide situational awareness of floods in coastal communities. [ABSTRACT FROM AUTHOR]

Wind power forecasting tools are as crucial for independent system operators (ISO) as it is for individual wind farm owners. ISO integrate wind power forecasting tools into power system operations for a number of applications and processes such as balancing energy, regulation and energy reserve services. To deal with the challenges that have surfaced in implementing wind power forecasting tools from an ISO's perspective, a hybrid model is proposed which is based on the correlation between wind power and load demand. The proposed model has used a bi-sectional vector auto-regressive model in conjunction with a nonlinear auto-regressive with exogenous output model forming a hybrid model that gives better results on real-world data sets as well. The case study taken for validating the model is the Electric Reliability Council of Texas system that has seen tremendous increase in the installed capacity of wind power generation sources in the recent past. [ABSTRACT FROM AUTHOR]

Copyright of Industria Textila is the property of Institutul National de Cercetare-Dezvoltare pentru Textile si Pielarie and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Highlights • A survey of exemplar-based texture synthesis methods. • Synthesis approaches are divided into procedural, exemplar-based and model-based methods. • Non-parametric methods generally outperform parametric approaches in the synthesis of regular structured textures. • Parametric and stochastic methods have a better efficiency in the synthesis of irregular textures. Abstract Texture synthesis has become an important topic in image processing, with many fundamental applications in computer vision and image understanding. The purpose of this survey is to give an overview and classification of texture synthesis approaches. According to how they represent, analyze and synthesize textures, the methods are divided into three families; procedural synthesis, exemplar-based synthesis and model-based synthesis, while focusing on exemplar-based methods including most of the synthesis techniques. Finally, experimental evaluations on different textures show that non-parametric synthesis methods lead to the best results when dealing with regular structured textures while parametric algorithms are better for the synthesis of more irregular textures. [ABSTRACT FROM AUTHOR]

Information about the statistical structure of the lake surface water temperature (LSWT) field is needed for assimilation of lake observations into Numerical Weather Prediction (NWP) models, to describe the lake surface state at each grid-point containing lakes. In this study, we obtain the autocorrelation function for LSWT from two types of observations, in situ and satellite-based. We use summer time measurements during 2010–2014 over selected Fennoscandian lakes and Northern European domain. The estimated autocorrelations decrease exponentially (from 0.99 to 0.73 for in situ and from 0.97 to 0.61 for satellite observations), when the distance between observations increases from zero to one thousand kilometres .A large difference in lake depth leads to a decrease of the correlation. Typical error standard deviation of LSWT observations was found to be 0.9 $ ^{\,\circ } $C for in situ observations and 1.2$ ^{\,\circ } $C for satellite observations. The exponential approximation for the LSWT autocorrelation functions is proposed, which depends on both the distance and the difference in lake depth. These results are directly applicable for the LSWT objective analysis in NWP. New autocorrelation functions, which allow interpolation of observations within and between lakes, were used in numerical experiments with the High-Resolution Limited Area Model (HIRLAM). In this preliminary assessment, we suggest adaptation of the presently used functions by increasing the influence radius and taking into account the lake depth difference. Generalization of the results to cover the melting and freezing seasons, their assessment for different geographical areas as well as their application to other prognostic lake variables within NWP are foreseen.