scholarly journals Clustering a Global Field of Atmospheric Profiles by Mixture Decomposition of Copulas

2005 ◽  
Vol 22 (10) ◽  
pp. 1445-1459 ◽  
Author(s):  
Mathieu Vrac ◽  
Alain Chédin ◽  
Edwin Diday
Keyword(s):  
A Priori ◽  
Distribution Functions ◽  
Cumulative Distribution ◽  
Specific Humidity ◽  
Vertical Profiles ◽  
Copula Functions ◽  
Mixture Density ◽  
Temperature And Humidity ◽  
Priori Information ◽  
Humidity Profiles

Abstract This work focuses on the clustering of a large dataset of atmospheric vertical profiles of temperature and humidity in order to model a priori information for the problem of retrieving atmospheric variables from satellite observations. Here, each profile is described by cumulative distribution functions (cdfs) of temperature and specific humidity. The method presented here is based on an extension of the mixture density problem to this kind of data. This method allows dependencies between and among temperature and moisture to be taken into account, through copula functions, which are particular distribution functions, linking a (joint) multivariate distribution with its (marginal) univariate distributions. After a presentation of vertical profiles of temperature and humidity and the method used to transform them into cdfs, the clustering method is detailed and then applied to provide a partition into seven clusters based, first, on the temperature profiles only; second, on the humidity profiles only; and, third, on both the temperature and humidity profiles. The clusters are statistically described and explained in terms of airmass types, with reference to meteorological maps. To test the robustness and the relevance of the method for a larger number of clusters, a partition into 18 classes is established, where it is shown that even the smallest clusters are significant. Finally, comparisons with more classical efficient clustering or model-based methods are presented, and the advantages of the approach are discussed.

scholarly journals A New Technique for Estimation of Lower-Tropospheric Temperature and Water Vapor Profiles from Radio Occultation Refractivity

2009 ◽  
Vol 26 (6) ◽  
pp. 1075-1089 ◽  
Author(s):  
D. Jagadheesha ◽  
B. Simon ◽  
P-K. Pal ◽  
P. C. Joshi ◽  
A. Maheshwari
Keyword(s):  
Radio Occultation ◽  
Specific Humidity ◽  
New Technique ◽  
Radiosonde Data ◽  
Boreal Summer ◽  
Tropospheric Temperature ◽  
Lower Altitude ◽  
Temperature And Humidity ◽  
The Tropics ◽  
Humidity Profiles

Abstract An empirical technique is proposed to obtain temperature and humidity profiles over the tropics using radio occultation refractivity profiles and surface/available lower-altitude temperature and pressure measurements over humid tropical regions. The technique is tested on a large number of diverse radiosonde-derived refractivity profiles over the tropics (30°S–30°N) and selected Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) radio occultation refractivity profiles that have collocated radiosonde observations over the region 10°S–30°N during the boreal summer of 2006. In a number of cases, the results were in good agreement with the collocated radiosonde data. The error statistics of temperature and humidity profiles obtained from the proposed technique are discussed and compared with the previously published results from another technique and also with the results of a one-dimensional variational data assimilation (1DVAR) technique given with COSMIC data. It is found that the previously published results and proposed technique are marginally better (worse) in reproducing observed relative humidity (specific humidity) when compared to the 1DVAR technique. The proposed new technique is applied on COSMIC refractivity profiles over the Bay of Bengal during summer 2007 to derive changes in vertical thermal and moisture changes in the troposphere between active and break phases of the monsoon pattern and many of the observed features are captured reasonably well.

scholarly journals Rainfall Profiling Using Atmospheric Radiation Measurement Program Vertically Pointing 8-mm Wavelength Radars

2006 ◽  
Vol 23 (11) ◽  
pp. 1478-1491 ◽  
Author(s):  
Sergey Y. Matrosov ◽  
Peter T. May ◽  
Matthew D. Shupe
Keyword(s):  
Dynamic Range ◽  
A Priori ◽  
Rainfall Rate ◽  
Atmospheric Radiation ◽  
Vertical Profiles ◽  
A Priori Information ◽  
Test Bed ◽  
Height Range ◽  
Ka Band ◽  
Priori Information

Abstract An attenuation-based method to retrieve vertical profiles of rainfall rate from vertically pointing Ka-band radar measurements has been refined and adjusted for use with the U.S. Department of Energy’s cloud radars deployed at multiple Atmospheric Radiation Program (ARM) test bed sites. This method takes advantage of the linear relationship between the rainfall rate and the attenuation coefficient, and can account for a priori information about the vertical profile of nonattenuated reflectivity. The retrieval method is applied to a wide variety of rainfall events observed at different ARM sites ranging from stratiform events with low-to-moderate rainfall rates (∼5 mm h−1) to heavy convective rains with rainfall rates approaching 100 mm h−1. The Ka-band attenuation-based retrieval results expressed in both instantaneous rainfall rates and in rainfall accumulations are compared to available surface data and measurements of a scanning C-band precipitation polarimetric radar located near the Darwin, Australia, ARM test bed site. The Ka-band retrievals are found to be in good agreement with the C-band radar estimates, which are based both on conventional radar reflectivity approaches and on polarimetric differential phase shift measurements. Typically, the C-band–Ka-band radar estimate differences are within the expected retrieval uncertainties. The magnitude of the Ka-band rainfall-rate estimate error depends on the retrieval resolution, rain intensity, and uncertainties in the profiles of nonattenuated reflectivity. It is shown that reasonable retrieval accuracies (∼15%–40%) can be achieved for a large dynamic range of observed rainfall rates (4–100 mm h−1) and the effective vertical resolution of about 1 km. The potential enhancements of the Ka-band attenuation-based method by including a priori information on vertical profiles of nonattenuated reflectivity and increasing the height range of the retrievals by using Ka-band polarization measurements are also discussed. The addition of the precipitation products to the suite of ARM hydrometeor retrievals can enhance the overall characterization of the vertical atmospheric column.

scholarly journals Radiosonde-Observed Vertical Profiles and Increasing Trends of Temperature and Humidity during 2005–2018 at the South Pole

Atmosphere ◽  
2019 ◽  
Vol 10 (7) ◽  
pp. 365 ◽  
Author(s):  
Min Xu ◽  
Yubin Li ◽  
Qinghua Yang ◽  
Andrew E. Gao ◽  
Bo Han ◽  
...  
Keyword(s):  
Inversion Layer ◽  
Lower Troposphere ◽  
Specific Humidity ◽  
Radiosonde Data ◽  
Vertical Profiles ◽  
South Pole ◽  
The South ◽  
Yearly Average ◽  
Temperature And Humidity ◽  
Increasing Trends

The vertical profiles and trends of temperature and humidity at the South Pole up to 10 km above mean sea level (amsl) were investigated by using radiosonde data collected from March 2005 to February 2018. During an average year between 2005 and 2018, the highest (lowest) temperature in the lower troposphere was approximately −25 °C (−60 °C) in December (July) at a height of about 500 m above the surface (at the surface). A temperature inversion layer above the surface was found during the whole year but was weaker during the summer, while the inversion layers at the tropopause (about 8 km amsl) mostly disappeared during spring and winter. General warming trends were found at all heights and months, but in a few heights and months cooling trends still occurred (e.g., in September below 7 km amsl). Nevertheless, seasonal and yearly averaged temperatures all presented warming trends: 1.1, 1.3, 0.6, 1.5 and 1.1 °C/decade at the surface, and 0.7, 1.0, 0.3, 0.3 and 0.6 °C/decade for the layer average from the surface to 10 km amsl, for spring, summer, autumn, winter, and yearly average, respectively. Most of the water vapor was confined in the lowermost 3 km of the atmosphere with a maximum of 0.35 g kg−1 in December at a 200 m height above surface, and the specific humidity had the similar characteristic of annual cycle and inversion layers as the temperature. At heights below 5 km amsl, increasing trends of specific humidity larger than 0.02 g kg−1/decade occurred during summer months, including the late spring and early autumn, and the annual mean showed an increasing trend of about 0.01–0.02 g kg−1/decade. Meanwhile, above 5 km amsl, the trends became small and generally less than 0.02 g kg−1/decade in all the months, and beyond 7 km amsl the specific humidity remained almost invariant due to its small moisture content as compared with lower levels. From the surface to 10 km amsl, the specific humidity averaged trends of 0.0062, 0.019, 0.0013, 0.002 and 0.007 g kg−1/decade for spring, summer, autumn, winter and yearly average, respectively.

scholarly journals Maximum likelihood representation of MIPAS profiles

2015 ◽  
Vol 8 (3) ◽  
pp. 2501-2520
Author(s):  
T. von Clarmann ◽  
N. Glatthor ◽  
J. Plieninger
Keyword(s):  
Climate Model ◽  
A Priori ◽  
Michelson Interferometer ◽  
Vertical Profiles ◽  
Intergovernmental Panel ◽  
Model Calculations ◽  
Mixing Ratios ◽  
Base Functions ◽  
Priori Information ◽  
User Friendly

Abstract. In order to avoid problems connected with the content of a priori information in volume mixing ratio vertical profiles measured with the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS), a user-friendly representation of the data has been developed which will be made available in addition to the regular data product. In this representation, the data will be provided on a fixed pressure grid coarse enough to allow a virtually unconstrained retrieval. As to avoid data interpolation, the grid is chosen to be a subset of the pressure grids used by the Chemistry Climate Model Initiative and the Data Initiative within the Stratosphere-troposphere Processes And their Role in Climate (SPARC) project as well as the Intergovernmental Panel of Climate Change climatologies and model calculations. For representation, the profiles have been transformed to boxcar base functions, which means that volume mixing ratios are constant within a layer. This representation is thought to be more adequate for comparison with model data. While this method is applicable also to vertical profiles of other species, the method is discussed using ozone as an example.

SENSITIVITY ANALYSIS OF NONLINEAR MODELS TO PARAMETER PERTURBATIONS FOR SMALL SIZE ENSEMBLES OF MODEL OUTPUTS

2011 ◽  
Vol 21 (12) ◽  
pp. 3589-3609 ◽  
Author(s):  
L. M. IVANOV ◽  
R. T. TOKMAKIAN
Keyword(s):  
Sensitivity Analysis ◽  
Degrees Of Freedom ◽  
Nonlinear Models ◽  
A Priori ◽  
Distribution Functions ◽  
Cumulative Distribution ◽  
Model Parameters ◽  
Model Sensitivity ◽  
Climate System Model ◽  
Sensitivity Indices

A new technique for nonlinear sensitivity analysis of geophysical models for small size ensembles of model outputs has been developed. Such an analysis utilizes the following metrics: (a) Sobol–Saltelli sensitivity indices and cumulative distribution functions if perturbations of model parameters are random, and (b) a Hartley-like measure if perturbations of model parameters are nonrandom and parametrized through fuzzy sets. The indices and the Hartley-like measure allow for ranging model parameters along their significance to the model output. Our calculations demonstrate that accurate estimates of the sensitivity indices are possible even if an ensemble of random perturbations contains considerably less than 100 members. Some calculations were successfully provided for random ensembles with 20–30 members only but, in general 50–100 member ensembles are required to get robust and significant estimations of model sensitivity. The fuzzy set concept allows for robust estimations for small size nonrandom ensembles of model outputs (50–100 members) and accounts for additional a priori information on model sensitivity coming from different sources. The Lorenz 63 model (a few degrees of freedom) and the ocean component (POP) of the Community Climate System Model (CCSM3) (several thousand degrees of freedom) are used to illustrate the sensitivity analysis based on this approach.

scholarly journals An examination of the long-term CO records from MOPITT and IASI: comparison of retrieval methodology

2015 ◽  
Vol 8 (10) ◽  
pp. 4313-4328 ◽  
Author(s):  
M. George ◽  
C. Clerbaux ◽  
I. Bouarar ◽  
P.-F. Coheur ◽  
M. N. Deeter ◽  
...  
Keyword(s):  
A Priori ◽  
Correlation Coefficients ◽  
Global Scale ◽  
Vertical Profiles ◽  
Advantages And Disadvantages ◽  
Atmospheric State ◽  
Priori Information ◽  
Total Column ◽  
Aircraft Data

Abstract. Carbon monoxide (CO) is a key atmospheric compound that can be remotely sensed by satellite on the global scale. Fifteen years of continuous observations are now available from the MOPITT/Terra mission (2000 to present). Another 15 and more years of observations will be provided by the IASI/MetOp instrument series (2007–2023 >). In order to study long-term variability and trends, a homogeneous record is required, which is not straightforward as the retrieved quantities are instrument and processing dependent. The present study aims at evaluating the consistency between the CO products derived from the MOPITT and IASI missions, both for total columns and vertical profiles, during a 6-year overlap period (2008–2013). The analysis is performed by first comparing the available 2013 versions of the retrieval algorithms (v5T for MOPITT and v20100815 for IASI), and second using a dedicated reprocessing of MOPITT CO profiles and columns using the same a priori information as the IASI product. MOPITT total columns are generally slightly higher over land (bias ranging from 0 to 13 %) than IASI data. When IASI and MOPITT data are retrieved with the same a priori constraints, correlation coefficients are slightly improved. Large discrepancies (total column bias over 15 %) observed in the Northern Hemisphere during the winter months are reduced by a factor of 2 to 2.5. The detailed analysis of retrieved vertical profiles compared with collocated aircraft data from the MOZAIC-IAGOS network, illustrates the advantages and disadvantages of a constant vs. a variable a priori. On one hand, MOPITT agrees better with the aircraft profiles for observations with persisting high levels of CO throughout the year due to pollution or seasonal fire activity (because the climatology-based a priori is supposed to be closer to the real atmospheric state). On the other hand, IASI performs better when unexpected events leading to high levels of CO occur, due to a larger variability associated with the a priori.

scholarly journals Maximum likelihood representation of MIPAS profiles

2015 ◽  
Vol 8 (7) ◽  
pp. 2749-2757 ◽  
Author(s):  
T. von Clarmann ◽  
N. Glatthor ◽  
J. Plieninger
Keyword(s):  
Climate Model ◽  
A Priori ◽  
Michelson Interferometer ◽  
Vertical Profiles ◽  
Intergovernmental Panel ◽  
Model Calculations ◽  
Mixing Ratios ◽  
Base Functions ◽  
Priori Information ◽  
User Friendly

Abstract. In order to avoid problems connected with the content of a priori information in volume mixing ratio vertical profiles measured with the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS), a user-friendly representation of the data has been developed which will be made available in addition to the regular data product. In this representation, the data will be provided on a fixed pressure grid coarse enough to allow a virtually unconstrained retrieval. To avoid data interpolation, the grid is chosen to be a subset of the pressure grids used by the Chemistry–Climate Model Initiative and the Data Initiative within the Stratosphere-troposphere Processes And their Role in Climate (SPARC) project as well as the Intergovernmental Panel of Climate Change climatologies and model calculations. For representation, the profiles have been transformed to boxcar base functions, which means that volume mixing ratios are constant within a layer. This representation is thought to be more adequate for comparison with model data. While this method is applicable also to vertical profiles of other species, the method is discussed using ozone as an example.

scholarly journals Retrieval of the Atmospheric Temperature and Humidity Profiles Using a Feed-Forward Neural Network

2021 ◽  
Vol 8 (1) ◽  
pp. 17
Author(s):  
Raju Pathak
Keyword(s):  
Neural Network ◽  
Vertical Structure ◽  
Computational Cost ◽  
Inverse Model ◽  
Specific Humidity ◽  
Feed Forward Neural Network ◽  
Inverse Algorithm ◽  
Feed Forward ◽  
Temperature And Humidity ◽  
Humidity Profiles

Using a feed-forward neural network, an inverse algorithm was developed to profile the vertical structure of temperature and specific humidity. The inverse algorithm (inverse model) was used to calculate temperature and humidity profiles, which were then compared with other existing methods. The inverse model is found efficient in profiling the vertical structure of temperature and humidity as compared to other existing methods. For example, the statistical methods notorious for their high computational cost, altitude-dependent error, and inability to accurately retrieve the vertical temperature and humidity profiles, are enhanced with an inverse model. The inverse model’s diurnal and seasonal cycle profiles are also found superior to those of other existing methods, which could be useful for assimilation in numerical weather forecast models. We suggest that incorporating such an inverse model into the ground-based microwave radiometer (GMWR) will enhance the accuracy of the vertical structure of temperature and humidity profiles, and so the improvement in weather forecasting. The developed inverse model has a resolution of 50 m between the surface to 500 m and 100 m between 500–2000 m, and 500 m beyond 2000 m.

scholarly journals Ensuring functional stability of the information system with limited initial information about determining random values

2020 ◽  
Vol 69 (4) ◽  
Author(s):  
Yu. V. Berezovska ◽  
Keyword(s):  
Information System ◽  
Information Systems ◽  
A Priori ◽  
Random Variables ◽  
Distribution Functions ◽  
Functional Stability ◽  
A Priori Information ◽  
Experimental Development ◽  
Reliability Indicators ◽  
Priori Information

Ensuring functional stability, reliability and effective management in information systems is a complex and complex scientific task. At the stage of design and construction of information systems, reliability indicators are interpreted as characteristics of the created probabilistic mathematical models of objects, and at the stage of experimental development, testing and operation, the role of reliability indicators is performed by statistical assessments of the corresponding probabilistic characteristics. When assessing the reliability indicators of information systems, the necessary initial data for a priori probabilistic calculations are often lacking, and the statistical assessment is hampered by a small volume of tests, according to which it is possible to determine only the estimates of the moments of determining random variables of the process of functioning of information systems or its components (mathematical expectations and variances of mean time between failures, recovery time, standby time, etc.). However, in such a situation, it is necessary to substantiate some characteristics of the information system, for example, a reserve of time, guaranteed exact boundaries of the probability of system uptime and the availability factor. When obtaining specific estimates, the minimum a priori information is used, which corresponds to a large number of real situations when assessing the reliability of information systems with time redundancy in the process of design, testing and operation. This article highlights various types of functionals that characterize the efficiency of an information system, under conditions of incomplete a priori information about the distribution function of determining random variables, through which the main indicators of the reliability of information systems are expressed, an analytical method is proposed and substantiated for finding distribution functions that deliver the greatest or least linear value. or linear fractional functionals under moment constraints on variable distribution functions. The method is based on identifying the limiting distribution functions, constructing the corresponding limiting polynomials, and solving special inequalities.

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