All Publications

Below is the combined list of references from refs_sat.bib and refs_external.bib. It is intended for our group's internal use.

| 2c-ice | a-train | abs lookup | absorption | active | aerosol | aerosols | age of air | aggregation | airs | albedo | algorithm | amsos | amsu | annual cycle | anomalies | aqua | ar4 | ar5 | arctic | arm | arts | arts-dev | asr | assimilation | astronomy | astrophysics | asymmetry | atmosphere | atmospheric composition | atmospheric dynamics | atmospheric profiles | atsr-2 | avhrr | bachelor thesis | backscattering | basics | bayes | bias | biomass | book | calculation | calculations | calibration | calipso | ccn | cdr | ceres | cfmip | chemistry | cia | ciraclim | cirrus | cirrus anvil sublimation | cirrus cloud | cirrus clouds | cirrusstudy | ciwsir/cloudice | claus | cliccs | climate | climate change | climate dynamics | climate feedbacks | climate sensitivity | climate sensivity | climate variability | climatology | cloud feedback | cloud forcing | cloud fraction | cloud ice | cloud ice mission | cloud optical thickness | cloud properties | cloud radiative effects | cloud radiative forcing | cloud regimes | cloud top pressure | cloudice mission | clouds | cloudsat | clustering | cmip3 | cmip5 | cmip6 | cmsaf | co2 | collocation | collocations | comparison | computer science | continua | contrail | convection | convective clouds | convective processes | convective self-aggregation | correlated k | cosmic background | cosmic rays | cosp | cost 723 qjrms | cross-calibration | cth | cumulus | dardar | data assimilation | data bases | dda | deep convection | delta m | dimer | disort | diurnal cycle | dlr-smiles | dmsp | documentation | doppler | droplet size | dynamics | earth | earthcare | ec earth | echam | ecmwf | effective radius | electromagnetism | electron content | elevation | elevation satellite-2 | emd | emde | emissivity | enso | eof-pca-svd | erbe | error assessment | ers | eruption | esa planetary | exoplanets | extraterrestrial | fall speed | far-infrared | faraday-voigt | fcdr | feedback | feedbacks | fingerprinting | flux uav | forcing | forest fire | fox19_airborne_amt.pdf | friend | fun | fuzzy inference system | fuzzy logic | gcm | genesis | geostationary | gerrit_erca | global warming | gnss | goes | gps | gras | graupel | gravitational lensing | greenhouse effect | ground-based | groundbased | habil | hadley circulation | hail | hamburg | heating rate | heating rates | herschel | hiatus | hirs | history | hsb | humidity | hydrological sensitivity | hydrological sensivity | hydrometeors | iasi | ice | ice clouds | ice crystal growth | ice nucleation | ice water | icesat-2 | ici | icon | icz | in situ | infrared | infrared sounder | instruments | inter-calibration | intercalibration | intercomparison | interference | inverse modelling | ipcc | ir | ir/vis | iris | isccp | ismar | isotopes | itcz | iwc | iwp | iwv | john | jupiter | kalpana | kessler scheme | lblrtm | licentiate thesis | lidar | limb effect | limb sounding | limb-correction | linemixing | lineshape | liquid water | liquid water path | longwave radiation | low-cloud feedback | magnetic field | magnetism | mars | mas | mass-dimension relation | master thesis | masters thesis | math | megha-tropiques | mendrok | mesoscale organization | meteorology | meteosat | methane ocean | metop | mhs | microphysics | microwave | microwave humidity | microwave radiometry | milz | mipas | mirs | misr | mixed phase | mls | model | modeling | models | modis | monte carlo | moon | mspps | msu | mth | multi-moment scheme | multisensor | mwhs | mwi | net radiation | neural network | nicam | nlte | noaa | nonsphericity | npoess | observation | ocean | ocean reflection | ocean-atmosphere interactions | odin | olr | one-moment scheme | open loop | optical | optical depth | optical properties | optics | orbital drift | orbital drift correction | orbits | ozone | pacific ocean | particle orientation | particle shape | particle size | particle size distribution | passive | patmos-x | phase function | phd thesis | planetary evolution | polarimetry | polarization | polder | potss | precipitation | profile datasets | programming | projection | promet | propagation modeling | python | radar | radiation | radiation profiles | radiative convective equilibrium | radiative equilibrium | radiative feedback | radiative fluxes | radiative forcing | radiative processes | radiative transfer | radiative-convective equilibrium | radiative-equilibrium | radio occultation | radiometer | radiometers | radiosonde | radiosonde cloud liquid | radiosonde correction | radiosonde corrections | rain | reanalysis | refractive index | relative humidity | remote sensing | retrieval | retrievals | review | rodgers | rttov | sahara | sahel | sampling | sand/dust | sar | satellite | satellite missions | satellite observations | satellite simulator | sbuehler_habil | scattering | scattering databases | scintillations | scout-amma | self-aggregation | sensor geometry | seviri | shallow convection | simulated annealing | single scattering | smiles | sno | snow | snowfall | software | soil | solar | soot | sounders | spectral information | spectroscopy | split window technique | sreerekha | ssm/i | ssm/t | ssmis | ssmt2 | stability | stars | statistics | ste | stereo | stratosphere | submillimeter | submm | sun | supersaturation | surface | synergies | synergy | task2 | tempera | temperature | terra | thermodynamics | time series | titan | tkuhn | toa radiation | top of the atmosphere | total column | tovs | trade-wind clouds | trajectory analysis | trend | trmm | tropical circulation | tropical convection | tropical meteorology | tropics | tropopause | troposphere | ttl | turbulence | tutorial | two-moment scheme | upper troposphere | uth | uthmos | utls | validation | vater vapor | venus | visualization | volcanic ash | walker | walker circulation | walker rirculation | water | water cycle | water dimer | water vapor | water vapor continuum | water vapour | water vapour path | water-vapour | wind | zeeman |

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In the Pipeline

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                External references

                1. d' Agostini, G. (1995), Probability and Measurement Uncertainty in Physics — a Bayesian Primer, Universita "La Sapienza" and INFN.
                2. d' Agostini, G. (1996), A Theory of Measurement Uncertainty Based on Conditional Probability, Dip. di Fisca, Universita "La Sapienza" and INFN.
                3. d' Agostini, G. (1998), Bayesian Reasoning versus Conventional Statistics in High Energy Physics, Dipartimento di Fisca dell'Universita "La Sapienza".
                4. d' Agostini, G. (1998), Jeffreys Priors versus Experienced Physicist Priors Arguments against Objective Bayesian Theory, Universita di Roma "La Sapienza" and INFN.
                5. d' Agostini, G. (1999), Overcoming priors anxiety, Dipartimento di Fisca dell'Universita "La Sapienza" and Istituto Nazionale di Fisics Nucleare INFN.
                6. Anderberg, M. R. (ed.) (1973), Cluster Analysis for Applications (Probability & Mathematical Statistics Monograph), Academic Press, ISBN 0-120-57650-3.
                7. Benestad, R. E. (2008), A Simple Test for Changes in Statistical Distributions, Eos, 89(41).
                8. Clarmann, T. von, G. Stiller, U. Grabowski, E. Eckert, and J. Orphal (2010), Technical Note: Trend estimation from irregularly sampled, correlated data, Atmos. Chem. Phys., 10, 6737–6747, doi:10.5194/acp-10-6737-2010.
                9. de Elia, R. and E. Laprise (2005), The Unbearable Lightness of Probabilities, Bull. Amer. Met. Soc., 1224–1225, doi:10.1175/BAMS-86-9-1224.
                10. Evans, K. F. and W. J. Wiscombe (2004), An algorithm for generating stochastic cloud fields from radar profile statistics, Atmos. Res., 72, 263–289.
                11. Feldman, G. J. and R. D. Cousins (1997), A Unified Approach to the Classical Statistical Analysis of Small Signals, Havard University, University of California.
                12. Freund, J. E. and G. A. Simon (xxxx), Modern Elementary Statistics, chap. 15: Regression, Prentice-Hall International.
                13. Guinti, C. (1998), A new ordering principle for the classical statistical analysis of Poisson processes with background, INFN, Universita di Torino.
                14. Helberg, C. (xxxx), Pitfalls of Data Analysis (or How to Avoid Lies and Damned Lies), University of Wisconsin Schools of Nursing and Medicine.
                15. James, F. (1972), Function Minimization, European Organization for Nuclear Research, Cern, Geneva, Switzerland.
                16. James, F. (1980), Monte Carlo theory and practice, Rep. Prog. Phys., 43, 1145–1189.
                17. Jaynes, E. T. and G. L. Bretthorst (2003), Probability Theory: The Logic of Science, Cambridge University Press.
                18. Krystek, M. and M. Anton (2007), A weighted total least-squares algorithm for fitting a straight line, Meas. Sci. Technol., 18(11), 3484–3442, doi:10.1088/0957-0233/18/11/025.
                19. Lanzante, J. R. (1996), Resistant, Robust and Non-Parametric Techniques for the Analysis of Climate Data: Theory and Examples, including Applications to Historical Radiosonde Station Data, Int. J. Climatol., 16, 1197–1226.
                20. Larsen, R. J. and M. L. Marx (1990), Statistics, chap. 12: Regression-Correlation Data, Prentice-Hall International.
                21. McQuarrie, B. R., T. A. Osborn, and G. C. Tabisz (1998), Semiclassical Moyal quantum mechanics for atmonic systems, Phys. Rev., 58(4), 2944–2961.
                22. O'Carroll, A. G., J. R. Eyre, and R. W. Saunders (2008), Three-Way Error Analysis between AATSR, AMSR-E, and In Situ Sea Surface Temperature Observations, J. Atmos. Oceanic Technol., 25(7), 1197–1207, doi:10.1175/2007JTECHO542.1.
                23. Rienzner, M. and C. Gandolfi (2011), A composite statistical method for the detection of multiple undocumented abrupt changes in the mean value within a time series, Int. J. Climatol., 31(5), 742–755, doi:10.1002/joc.2113.
                24. Santer, B. D., T. M. L. Wigley, J. S. Boyle, D. J. Gaffen, J. J. Hnilo, D. Nychka, D. E. Parker, and K. E. Taylor (2000), Statistical significance of trends and trend differences in layer-average atmospheric temperature time series, J. Geophys. Res., 105(D6), 7337–7356, doi:10.1029/1999JD901105.
                25. Silverman, D. (1998), Joint Bayesian Treatment of Poission and Gaussian Experiments in a Chi-squared Statistic, University of California.
                26. Swain, J. and L. Taylor (1997), Numerical Construction of Likelihood Distributions and the Propagation of Errors, Northeastern University, Boston, Department of Physics.
                27. Termonia, P. (2001), On the removal of random variables in data sets of meteorological observations, Met. Atm. Phys., 78, 143–156.
                28. Toohey, M. and T. von Clarmann (2013), Climatologies from satellite measurements: the impact of orbital sampling on the standard error of the mean, Atmos. Meas. Tech., 6, 937–948, doi:10.5194/amt-6-937-2013.
                29. von Storch, H. and F. W. Zwiers (1999), Statistical Analysis in Climate Research, Cambridge University Press, ISBN 0-521-01230-9.
                30. Weatherhead, E. C., G. C. Reinsel, G. C. Tiao, X.-L. Meng, D. Choi, W.-K. Cheang, T. Keller, J. DeLuisi, D. J. Wuebbles, J. B. Kerr, A. J. Miller, S. J. Oltmans, and J. E. Frederick (1998), Factors affecting the detection of trends: Statistical considerations and applications to environmental data, J. Geophys. Res., 103(D14), 17149–17161, doi:10.1029/98JD00995.
                31. York, D., N. M. Evensen, M. López Martínez, and J. De Basabe Delgado (2003), Unified equations for the slope, intercept, and standard errors of the best straight line, Am. J. Phys., 72(3), 367–375, doi:10.1119/1.1632486.
                32. Zhao, G. and L. D. Girolamo (2007), Statistics on the macrophysical properties of trade wind cumuli over the tropical western Atlantic, J. Geophys. Res., 112(D10), D1024, doi:10.1029/2006JD007371.