scholarly journals A Simple Method to Retrieve Cloud Properties from Atmospheric Transmittance and Liquid Water Column Measurements

2011 ◽  
Vol 50 (2) ◽  
pp. 283-295 ◽  
Author(s):  
Salvador Matamoros ◽  
Josep-Abel González ◽  
Josep Calbó
Keyword(s):  
Standard Deviation ◽  
Optical Depth ◽  
Liquid Water ◽  
Surface Albedo ◽  
Effective Radius ◽  
Droplet Radius ◽  
Similar Data ◽  
Simple Method ◽  
The Mean ◽  
Atmospheric Transmittance

Abstract A deeper knowledge of the effects and interactions of clouds in the climatic system requires developing both satellite and ground-based methods to assess their optical properties. A simple method based on a parameterized inversion of a radiative transfer model is proposed to estimate the optical depth of thick liquid water clouds from the atmospheric transmittance at 415 nm, solar zenith angle, surface albedo, effective droplet radius, and aerosol load. When concurrent measurements of atmospheric transmittance and liquid water path are available, the effective radius of the droplet size distribution can also be retrieved. The method is compared with a reference algorithm from Min and Harrison, which uses similar data, except aerosol load. When applied to measurements performed at the Southern Great Plains site of the Atmospheric Radiation Measurement Program, the mean bias deviation between the proposed method and the reference method is only −0.08 in units of optical depth, whereas the standard deviation is only 0.46. For the effective droplet radius estimations, the mean bias deviation is −0.13 μm, and the standard deviation is 0.14 μm. Maximum relative deviations are lower than 5% and 8% for cloud optical depth and effective radius, respectively. The effects on these retrievals of the assumed aerosol optical depth and surface albedo are also analyzed.

scholarly journals Influence of spatial heterogeneity of local surface albedo on the area-averaged surface albedo retrieved from airborne irradiance measurements

2013 ◽  
Vol 6 (3) ◽  
pp. 527-537 ◽  
Author(s):  
E. Jäkel ◽  
M. Wendisch ◽  
B. Mayer
Keyword(s):  
Optical Depth ◽  
Surface Albedo ◽  
Radiative Transfer Model ◽  
Small Scale ◽  
Mean Deviation ◽  
Transfer Model ◽  
Horizontal Distance ◽  
Local Surface ◽  
Atmospheric Scattering ◽  
The Mean

Abstract. Spectral airborne upward and downward irradiance measurements are used to derive the area-averaged surface albedo. Real surfaces are not homogeneous in their reflectivity. Therefore, this work studies the effects of the heterogeneity of surface reflectivity on the area-averaged surface albedo to quantify how well aircraft measurements can resolve the small-scale variability of the local surface albedo. For that purpose spatially heterogeneous surface albedo maps were input into a 3-dimensional (3-D) Monte Carlo radiative transfer model to simulate 3-D irradiance fields. The calculated up- and downward irradiances in altitudes between 0.1 and 5 km are used to derive the area-averaged surface albedo using an iterative retrieval method that removes the effects due to atmospheric scattering and absorption within the layer beneath the considered level. For the case of adjacent land and sea surfaces, parametrizations are presented which quantify the horizontal distance from the coastline that is required to reduce surface heterogeneity effects on the area-averaged surface albedo to a given limit. The parametrization which is a function of altitude, aerosol optical depth, single scattering albedo, and the ratio of local land and sea albedo was applied for airborne spectral measurements. In addition, the deviation between area-averaged and local surface albedo is determined for more complex surface albedo maps. For moderate aerosol conditions (optical depth less than 0.4) and a wavelength range between 400 and 1000 nm, the altitude and the heterogeneity of the surface albedo are the dominant factors determining the mean deviation between local and area-averaged surface albedo. A parametrization of the mean deviation is applied to an albedo map that was derived from a Landsat image of an area in East Anglia (UK). Parametrization and direct comparison of local and area-averaged surface albedo show similar mean deviations (20% vs. 25%) over land.

scholarly journals Assessing Snow Albedo Feedback in Simulated Climate Change

2006 ◽  
Vol 19 (11) ◽  
pp. 2617-2630 ◽  
Author(s):  
Xin Qu ◽  
Alex Hall
Keyword(s):  
Climate Change ◽  
Standard Deviation ◽  
Northern Hemisphere ◽  
Surface Albedo ◽  
Climate Models ◽  
Attenuation Effect ◽  
Albedo Feedback ◽  
Snow Albedo ◽  
The Mean ◽  
Planetary Albedo

Abstract In this paper, the two factors controlling Northern Hemisphere springtime snow albedo feedback in transient climate change are isolated and quantified based on scenario runs of 17 climate models used in the Intergovernmental Panel on Climate Change Fourth Assessment Report. The first factor is the dependence of planetary albedo on surface albedo, representing the atmosphere's attenuation effect on surface albedo anomalies. It is potentially a major source of divergence in simulations of snow albedo feedback because of large differences in simulated cloud fields in Northern Hemisphere land areas. To calculate the dependence, an analytical model governing planetary albedo was developed. Detailed validations of the analytical model for two of the simulations are shown, version 3 of the Community Climate System Model (CCSM3) and the Geophysical Fluid Dynamics Laboratory global coupled Climate Model 2.0 (CM2.0), demonstrating that it facilitates a highly accurate calculation of the dependence of planetary albedo on surface albedo given readily available simulation output. In all simulations it is found that surface albedo anomalies are attenuated by approximately half in Northern Hemisphere land areas as they are transformed into planetary albedo anomalies. The intermodel standard deviation in the dependence of planetary albedo on surface albedo is surprisingly small, less than 10% of the mean. Moreover, when an observational estimate of this factor is calculated by applying the same method to the satellite-based International Satellite Cloud Climatology Project (ISCCP) data, it is found that most simulations agree with ISCCP values to within about 10%, despite further disagreements between observed and simulated cloud fields. This suggests that even large relative errors in simulated cloud fields do not result in significant error in this factor, enhancing confidence in climate models. The second factor, related exclusively to surface processes, is the change in surface albedo associated with an anthropogenically induced temperature change in Northern Hemisphere land areas. It exhibits much more intermodel variability. The standard deviation is about ⅓ of the mean, with the largest value being approximately 3 times larger than the smallest. Therefore this factor is unquestionably the main source of the large divergence in simulations of snow albedo feedback. To reduce the divergence, attention should be focused on differing parameterizations of snow processes, rather than intermodel variations in the attenuation effect of the atmosphere on surface albedo anomalies.

scholarly journals Influence of spatial heterogeneity of local surface albedo on the area-averaged surface albedo retrieved from airborne irradiance measurements

2012 ◽  
Vol 5 (5) ◽  
pp. 7457-7487
Author(s):  
E. Jäkel ◽  
M. Wendisch ◽  
B. Mayer
Keyword(s):  
Optical Depth ◽  
Surface Albedo ◽  
Radiative Transfer Model ◽  
Small Scale ◽  
Mean Deviation ◽  
Transfer Model ◽  
Horizontal Distance ◽  
Local Surface ◽  
Atmospheric Scattering ◽  
The Mean

Abstract. Spectral airborne upward and downward irradiance measurements are used to derive the area-averaged surface albedo. Real surfaces are not homogeneous in their reflectivity. Therefore, this work studies the effects of the heterogeneity of surface reflectivity on the area-averaged surface albedo to quantify how well aircraft measurements can resolve the small-scale variability of the local surface albedo. For that purpose spatially heterogeneous surface albedo maps were input into a 3-dimensional (3-D) Monte Carlo radiative transfer model to simulate 3-D irradiance fields. The calculated up- and downward irradiances in altitudes between 0.1 km and 5 km are used to derive the area-averaged surface albedo using an iterative retrieval method that removes the effects due to atmospheric scattering and absorption within the layer beneath the considered level. For the case of adjacent land and sea surfaces a parametrization is presented which quantifies the horizontal distance to the coastline that is required to reduce surface heterogeneity effects on the area-averaged surface albedo to a given limit. The parametrization which is a function of altitude, aerosol optical depth, and the ratio of local land and sea albedo was applied for airborne spectral measurements. In addition, the deviation between area-averaged and local surface albedo is determined for more complex surface albedo maps. For moderate aerosol conditions (optical depth less than 0.4) and the visible wavelength range, the altitude and the heterogeneity of the surface albedo are the dominant factors determining the mean deviation between local and area-averaged surface albedo. A parametrization of the mean deviation is applied to an albedo map that was derived from a Landsat image of an area in East Anglia (UK). Parametrization and direct comparison of local and area-averaged surface albedo show similar mean deviations (20% vs. 25%) over land.

scholarly journals Regression to the mean correction for Collision Modification Factors

2021 ◽  
Author(s):  
Bernard James
Keyword(s):  
Standard Deviation ◽  
Road Safety ◽  
Relative Number ◽  
Highway Safety ◽  
Regression To The Mean ◽  
Simple Method ◽  
Highway Safety Manual ◽  
The Mean ◽  
Site Population

Collision Modification Factors (CMFs) are a simple method of representing the effectiveness of road safety treatments. With the release of the Highway Safety Manual (HSM) and the recent launching of a CMF Clearinghouse website, CMFs are likely to become more widely used for estimating the effects of potential road safety treatments. The presence of regression to the mean (RTM) bias has long been shown to affect the accuracy of CMFs that did not account for the RTM in their development. The purpose of this research was to study how the RTM depends on the number of years of data used for selecting high collision sites for treatment and on the relative number of sites selected. From this analysis, a function based on the number of years, percentage of high collision sites selected, and the mean and standard deviation of the site population from which the treated sites are drawn was developed to more accurately estimate the magnitude of the RTM effect. This function can be used to adjust CMFs that do not account for RTM, complementing the procedure developed and used to correct CMFs included in the HSM.

scholarly journals Correction of a lunar irradiance model for aerosol optical depth retrieval and comparison with star photometer

2020 ◽  
Author(s):  
Roberto Román ◽  
Ramiro González ◽  
Carlos Toledano ◽  
África Barreto ◽  
Daniel Pérez-Ramírez ◽  
...  
Keyword(s):  
Standard Deviation ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Correction Factor ◽  
The Moon ◽  
Night Time ◽  
Technological Advances ◽  
Fast Change ◽  
The Mean ◽  
Cycle Dependent

Abstract. The emergence of Moon photometers is allowing measurements of lunar irradiance over the world and increasing the potential to derive aerosol optical depth (AOD) at night-time, that is very relevant in polar areas. Actually, new photometers implement the latest technological advances that permit lunar irradiance measurements together with classical Sun photometry measurements. However, a proper use of these instruments for AOD retrieval requires accurate time-dependent knowledge of the extraterrestrial lunar irradiance over time, due to its fast change throughout the Moon's cycle. This paper uses the RIMO model (an implementation of the ROLO model) to estimate the AOD at night-time assuming that the calibration of the solar channels can be transferred to the Moon by a vicarious method. However, the obtained AOD values using a Cimel CE318-T Sun/sky/Moon photometer for 98 pristine nights with low and stable AOD at the Izaña Observatory (Tenerife, Spain) are not in agreement with the expected (low and stable) AOD values, estimated by linear interpolations from daytime values obtained during the previous evening and the following morning. Actually, AOD calculated using RIMO shows negative values and with a marked cycle dependent on the optical airmass. The differences between the AOD obtained using RIMO and the expected values are assumed to be associated with inaccuracies in the RIMO model, and these differences are used to calculate the RIMO correction factor (RCF). The RCF is a proposed correction factor that, multiplied by RIMO value, gives an effective extraterrestrial lunar irradiance that provides the expected AOD values. The RCF varies with the Moon phase angle (MPA) and with wavelength, ranging from 1.01 to 1.14, which reveals an overall underestimation of RIMO to the lunar irradiance. These obtained RCF values are modeled for each photometer wavelength to a second order polynomial as function of MPA. The AOD derived by this proposed method is compared with the independent AOD measurements obtained by a star photometer at Granada (Spain) for two years. The mean of the Moon-star AOD differences are between −0.015 and −0.005 and the standard deviation between 0.03 and 0.04 (which is reduced to about 0.01 if one month of data affected by instrumental issues is not included in the analysis), for 440, 500, 675 ad 870 nm; however, for 380 nm, the mean and standard deviation of these differences are higher. The Moon-star AOD differences are also analyzed as a function of MPA, showing no significant dependence.

scholarly journals Combined observational and modeling based study of the aerosol indirect effect

2006 ◽  
Vol 6 (3) ◽  
pp. 3757-3799 ◽  
Author(s):  
T. Storelvmo ◽  
J. E. Kristjansson ◽  
G. Myhre ◽  
M. Johnsrud ◽  
F. Stordal
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Liquid Water ◽  
Indirect Effect ◽  
Cloud Droplet ◽  
Effective Radius ◽  
Liquid Water Path ◽  
Cloud Liquid Water ◽  
Aerosol Indirect Effect ◽  
Cloud Liquid Water Path

Abstract. The indirect effect of aerosols via liquid clouds is investigated by comparing aerosol and cloud characteristics from the Global Climate Model CAM-Oslo to those observed by the MODIS instrument onboard the TERRA and AQUA satellites (http://modis.gsfc.nasa.gov). The comparison is carried out for 15 selected regions ranging from remote and clean to densely populated and polluted. For each region, the regression coefficient and correlation coefficient for the following parameters are calculated: Aerosol Optical Depth vs. Liquid Cloud Optical Thickness, Aerosol Optical Depth vs. Liquid Cloud Droplet Effective Radius and Aerosol Optical Depth vs. Cloud Liquid Water Path. Modeled and observed correlation coefficients and regression coefficients are then compared for a 3-year period starting in January 2001. Additionally, global maps for a number of aerosol and cloud parameters crucial for the understanding of the aerosol indirect effect are compared for the same period of time. Significant differences are found between MODIS and CAM-Oslo both in the regional and global comparison. However, both the model and the observations show a positive correlation between Aerosol Optical Depth and Cloud Optical Depth in practically all regions and for all seasons, in agreement with the current understanding of aerosol-cloud interactions. The correlation between Aerosol Optical Depth and Liquid Cloud Droplet Effective Radius is variable both in the model and the observations. However, the model reports the expected negative correlation more often than the MODIS data. Aerosol Optical Depth is overall positively correlated to Cloud Liquid Water Path both in the model and the observations, with a few regional exceptions.

scholarly journals Have You Seen the Standard Deviation?

2019 ◽  
Vol 3 ◽  
pp. 1-10
Author(s):  
Jyotirmoy Sarkar ◽  
Mamunur Rashid
Keyword(s):  
Standard Deviation ◽  
Cumulative Distribution Function ◽  
Geometric Method ◽  
Cumulative Distribution ◽  
Mean Deviation ◽  
Similar Data ◽  
Tabular Data ◽  
Empirical Cumulative Distribution Function ◽  
Quadratic Transformation ◽  
The Mean

Background: Sarkar and Rashid (2016a) introduced a geometric way to visualize the mean based on either the empirical cumulative distribution function of raw data, or the cumulative histogram of tabular data. Objective: Here, we extend the geometric method to visualize measures of spread such as the mean deviation, the root mean squared deviation and the standard deviation of similar data. Materials and Methods: We utilized elementary high school geometric method and the graph of a quadratic transformation. Results: We obtain concrete depictions of various measures of spread. Conclusion: We anticipate such visualizations will help readers understand, distinguish and remember these concepts.

A Simple Linear Discrimination Algorithm for AD Patients and Normal Controls

2012 ◽  
Vol 155-156 ◽  
pp. 18-22
Author(s):  
Yun Yi Yan ◽  
Guo Zhang Hu ◽  
Bao Long Guo ◽  
Yu Jie He
Keyword(s):  
Standard Deviation ◽  
Confidence Intervals ◽  
Sensitivity And Specificity ◽  
Classification Accuracy ◽  
Simple Method ◽  
Linear Discrimination ◽  
Significant Difference ◽  
The Mean ◽  
Normal Controls ◽  
Discrimination Method

One simple but effective discrimination method was presented in this paper to separate AD from normal controls. After detecting the thickness of cortex with highly significant difference, the mean and standard deviation of these vertices are computed to construct confidence intervals. We introduced one relax coefficients to control the width of intervals and by experiments the coefficients was optimized. Experiments results showed that using this simple method, the classification accuracy, sensitivity and specificity of Alzheimer’s disease versus normal controls could be as high as 85%, 88.89% and 93.84% respectively.

scholarly journals Superspreading of SARS-CoV-2 in the USA

PLoS ONE ◽  
2021 ◽  
Vol 16 (3) ◽  
pp. e0248808
Author(s):  
Calvin Pozderac ◽  
Brian Skinner
Keyword(s):  
United States ◽  
Standard Deviation ◽  
Early Time ◽  
The United States ◽  
Simple Method ◽  
Early Stages ◽  
Secondary Infections ◽  
The Usa ◽  
Mean And Variance ◽  
The Mean

A number of epidemics, including the SARS-CoV-1 epidemic of 2002-2004, have been known to exhibit superspreading, in which a small fraction of infected individuals is responsible for the majority of new infections. The existence of superspreading implies a fat-tailed distribution of infectiousness (new secondary infections caused per day) among different individuals. Here, we present a simple method to estimate the variation in infectiousness by examining the variation in early-time growth rates of new cases among different subpopulations. We use this method to estimate the mean and variance in the infectiousness, β, for SARS-CoV-2 transmission during the early stages of the pandemic within the United States. We find that σβ/μβ ≳ 3.2, where μβ is the mean infectiousness and σβ its standard deviation, which implies pervasive superspreading. This result allows us to estimate that in the early stages of the pandemic in the USA, over 81% of new cases were a result of the top 10% of most infectious individuals.

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