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Items new to the Collection



These items were added to the collection on February 2019.

Ahrens CD, Henson R. 2019. Meteorology today an introduction to weather, climate, and the environment.

Bloch J. 2018. Effective Java. Boston: Addison-Wesley.

Camporeale E, Johnson JR, Wing S. 2018. Machine learning techniques for space weather.

Chollet F. 2018. Deep learning with Python.

Ciaburro G, Venkateswaran B. 2017. Neural networks with R : smart models using CNN, RNN, deep learning, and artificial intelligence principles.

Dey N, Bhatt CM, Ashour A. 2019. Big data for remote sensing : visualization, analysis and interpretation : digital Earth and smart Earth.

Doerr JE. 2018. Measure what matters : how Google, Bono, and the Gates Foundation rock the world with OKRs. New York, New York: Portfolio/Penguin.

Downey AB. 2016. Think Python. Beijing: O'Reilly.

Fu P. 2018. Getting to know Web GIS.

Fukao S, Hamazu K, Doviak RJ, Springer Science+Business M. 2014. Radar for meteorological and atmospheric observations. Tokyo: Springer.

Geron A, O'Reilly M. 2018. Hands-on machine learning with Scikit-Learn and TensorFlow : concepts, tools, and techniques to build intelligent systems. Beijing; Boston; Farnham; Sebastopol; Tokyo: O'Reilly.

Lackmann G, Mapes BE, Tyle KR. 2017. Synoptic-dynamic meteorology lab manual : visual exercises to complement midlatitude synoptic meteorology.

Lazaridis M. 2011. First principles of meteorology and air pollution. Dordrecht: Springer.

Lewis JM, Phillips JM, American Meteorological S. 2018. Verner Suomi the life and work of the founder of satellite meteorology.

Martin K, Hoffman B. 2013. Mastering CMake : [a cross-platform build system ; covers installing and running CMake ; details converting existing build processes to CMake ; create powerful cross-platform build scripts]. [Clifton Park, NY]: Kitware.

Matthes E. 2017. Python crash course.

Menke W. 2016. Geophysical data analysis : discrete inverse theory.

Mudelsee M. 2014. Climate time series analysis : classical statistical and bootstrap methods. Cham: Springer.

Raizer VY. 2017. Advances in passive microwave remote sensing of oceans.

Raschka S. 2015. Python machine learning. Birmingham: Packt.

Roy I. 2018. Climate variability and sunspot activity : analysis of the solar influence on climate. Cham: Springer International Publishing.

Schumann GJP, Bates PD, Apel H, Aronica GT, American Geophysical U. 2018. Global flood hazard : applications in modeling, mapping, and forecasting.

Slonosky VC, American Meteorological S. 2018. Climate in the age of empire : weather observers in colonial Canada.

Sweigart A. 2016. Automate the boring stuff with Python : practical programming for total beginners.

Ulaby FT, Long DG, Blackwell WJ, University of Michigan P. 2014. Microwave radar and radiometric remote sensing. Ann Arbor: The Uniwersity of Michigan Press.

Wells N. 2012. The Atmosphere and ocean : a physical introduction. Chichester: Wiley.

Zaccone GKMR. 2018. DEEP LEARNING WITH TENSORFLOW - : explore neural networks with python. [Place of publication not identified]: PACKT Publishing Limited.



These items were added to the collection on May 2018.



2015. The ArcGIS Book. Redlands: ESRI Press.

2018. Mathematical Geosciences Hybrid Symbolic-numeric Methods. Springer Verlag.

Ambaum MHP. 2010. Thermal physics of the atmosphere. Hoboken (N.J.): Wiley-Blackwell.

American Meteorological S, International Conference on Interactive I, Processing Systems for Meteorology O, Hydrology. 2002. 18th International Conference on Interactive Information and Processing Systems (IIPS) for Meteorology, Oceanography, and Hydrology : 13-17 January 2002, Orlando, Florida. Boston, Massachusetts: American Meteorological Society.

Attaway S. 2017. MATLAB : a practical introduction to programming and problem solving.

Banwell CN. 1983. Fundamentals of molecular spectroscopy. London: McGraw-Hill.

Bell R. 2012. Introductory Fourier Transform Spectroscopy. Burlington: Elsevier Science.

Black DA. 2006. Ruby for Rails cRuby Techniques for Rails Developers. Greenwich, CT: Manning Publications Co.

Bloomfield P. 1976. Fourier analysis of time series : an introduction. New York: Wiley.

Brasseur G, Jacob DJ. 2017. Modeling of atmospheric chemistry.

Cameron D, Raymond E, Rosenblatt B. 2000. Learning GNU emacs. Beijing: O'Reilly.

Carrieres T, Buehner M, Lemieux J-F, Pedersen LT. 2017. Sea ice analysis and forecasting : towards an increased reliance on automated prediction systems.

Churchill RV, Brown JW. 1983. Fourier series and boundary value problems. Auckland [u.a.: McGraw-Hill.

Collins-Sussman B, Fitzpatrick BW, Pilato CM. 2004. Version control with subversion : [next generation open source version control]. Beijing [u.a.]: O'Reilly.

Conference on P, Statistics in the Atmospheric S, American Meteorological S, Symposium on Environmental Applications: Facilitating the Use of Environmental I, Symposium on Global C, Climate V, Symposium on Observations DA, Probabilistic P. 16th Conference on Probability and Statistics in the Atmospheric Sciences : 13-17 January 2002, Orlando, Florida. In. 2002; Boston, Mass.: American Meteorological Society.

Cronin TM. 1999. Principles of paleoclimatology. New York: Columbia University Press.

Daley R. 1999. Atmospheric data analysis. Cambridge: Cambridge University Press.

Davis HT. 1975. Introduction to nonlinear differential and integral equations. New York, NY: Dover Publ.

Fletcher SJ. 2017. Data assimilation for the geosciences : from theory to application.

Foken T. 2017. Micrometeorology.

Frakes WB. 2002. Information retrieval : Data structures & algorithms. Upper Saddle River, New Jersey: Prentice Hall.

Goodrich D. 2018. HOLE IN THE WIND : a climate scientist's bicycle journey across the united states. [S.l.]: PEGASUS BOOKS.

Griffies SM. 2004. Fundamentals of ocean climate models. Princeton, N.J.: Princeton University Press.

Guttag J. 2017. Introduction to computation and programming using Python : with application to understanding data.

Hetland ML. 2005. Beginning Python : from novice to professional. Berkeley: Apress.

Hunt A, Thomas D. 2000. The pragmatic programmer : from journeyman to master. Reading, Mass.: Addison-Wesley.

Karmakar PK. 2012. Microwave propagation and remote sensing : atmospheric influences with models and applications. Boca Raton: CRC.

Kochan SG, Wood PH. 2001. UNIX shell programming. Carmel, Ind.: Hayden Books.

Kroto HW. 1992. Molecular rotation spectra. New York: Dover.

Lackmann G, Mapes BE, Tyle KR. 2017. Synoptic-dynamic meteorology lab manual : visual exercises to complement midlatitude synoptic meteorology.

Lamb L, Robbins A. 1998. Learning the vi editor. Beijing: O'Reilly.

Lantz B. 2015. Machine learning with R : discover how to build machine learning algorithms, prepare data, and dig deep into data prediction techniques with R.

Lee X. 2018. Fundamentals of boundary-layer meteorology.

Lenoble J. 1985. Radiative transfer in scattering and absorbing atmospheres : standard computational procedures. Hampton, Virginia: A. Deepak.

Mak M. 2017. Atmospheric Frontal Dynamics.

Marion JB, Thornton ST. 1995. Classical dynamics of particles and systems. Fort Worth; Phyladelphia; San Diego: Saunders College Pub.

Martin RC. 2009. Clean code : a handbook of agile software craftsmanship. Upper Saddle River, NJ [u.a.: Prentice-Hall.

Mason M. 2005. Pragmatic version control using subversion. Raleigh; Dallas: Pragmatic Bookshelf.

McAnally J, Arkin A. 2009. Ruby in practice. Greenwich (Conn.): Manning.

McKinney W. 2018. Python for data analysis : data wrangling with pandas, NumPy, and IPython.

Metcalf M, Reid J, Cohen M. 2010. FORTRAN 95-2003 explained. Oxford [u.a.]: Oxford Univ. Press.

Muller AC, Guido S. 2016. Introduction to Machine Learning with Python : A Guide for Data Scientists. New York: O'Reilly Media.

Olsen R. 2009. Design patterns in Ruby. Upper Saddle River, NJ [u.a.: Addison-Wesley.

Osborne A. 2003. Nonlinear ocean waves. Oxford: Academic.

Parker DJ, Diop-Kane M. 2017. Meteorology of tropical West Africa : the forecasters' handbook.

Pimpler E. 2017. Programming ArcGIS Pro with Python : automate your ArcGis Pro geoprocessing tasks with Python.

Raschka S, Mirjalili V. 2017. Python machine learning : machine learning and deep learning with Python, scikit-learn, and TensorFlow. Birmingham, Mumbai: Packt.

Rosenberg HM. 1988. The solid state : an introd. to the physics of crystals for students of physics, materials science, and engineering. Oxford u.a.: Clarendon Pr. u.a.

Rosenblatt B. 1994. Learning the Korn shell. Cambridge: O'Reilly & Associates.

Sloan JD. 2005. High performance Linux clusters with OSCAR, Rocks, openMosix, and MPI. Beijing: O'Reilly.

Stammer D, Cazenave A. 2018. Satellite altimetry over oceans and land surfaces.

Strang G. 1980. Linear algebra and its applications. New York: Academic Press.

Symposium on Global Change S, American Meteorological S, Symposium on E. Eighth Symposium on Global Change Studies : February 2-7, 1997. In. 1997; Boston, Mass.: American Meteorological Society.

Symposium on Observations DA, Probabilistic P, American Meteorological S. Symposium on Observations, Data Assimilation, and Probabilistic Prediction : 13-17 January 2002, Orlando, Florida. In. 2002; Boston, Mass.: American Meteorological Society.

Tarantola A. 1987. Inverse Problem Theory Methods for Data Fitting and Model Parameter Estimation. Burlington: Elsevier Science.

Tomasi C, Fuzzi S, Kokhanovsky AA. 2017. Atmospheric aerosols : life cycles and effects on air quality and climate.

Wadhams P. 2017. A farewell to ice : a report from the Arctic.

Waite M, Prata S, Waite G. 1993. The Waite Group's new C Primer Plus. Carmel, IN: H.W. Sams.

Wangsness RK. 2000. Electromagnetic fields. New York: John Wiley & Sons.

Wilks DS. 2010. Statistical methods in the atmospheric sciences. Amsterdam: Elsevier.

Zadeh LA, Kacprzyk J. 1992. Fuzzy logic for the management of uncertainty. New York: Wiley.

Zelle JM. 2017. Python programming : an introduction to computer science.

Zhang Z. 2018. Multivariate time series analysis in climate and environmental research.

These items were added to the collection on August 2017.



Armstrong L. 2015. Mapping and modeling weather and climate with GIS. Redlands, Calif: ESRI Press.

Baghdadi N, Zribi M. 2016. Microwave remote sensing of land surfaces techniques and methods. London: ISTE Press.

Boccotti P. 2015. Wave mechanics and wave loads on marine structures. Oxford, UK; Waltham, MA, USA: Elsevier Butterworth-Heinemann.

Chapple S, Troup E, Forster T, Sloan T. 2016. Mastering parallel programming with R : master the robust fearures of R parallel programming to accelerate your data science computations.

Chen KS. 2016. Principles of synthetic aperture radar imaging : a system simulation approach. Boca Raton: CRC Press.

Cushman-Roisin B, Beckers J-M. 2012. Introduction to geophysical fluid dynamics : physical and numerical aspects. Waltham, Mass.; Amsterdam: Academic Press ; Elsevier.

Doe R, Tornado, Storm Research O. 2016. Extreme weather : forty years of the Tornado and Storm Research Organisation (TORRO).

Flanagan D, Matsumoto Y. The Ruby programming language. Sebastopol, Calif.: O'Reilly.

Frain B. 2015. Responsive web design with HTML5 and CSS3 : build responsive and future-proof websites to meet the demands of modern web users.

Gardener M. 2012. Beginning R: the statistical programming language. Indianapolis: Wiley.

Georgiev CG, Santurette P, Maynard K. 2016. Weather analysis and forecasting : applying satellite water vapor imagery and potential vorticity analysis.

Haggard WH. 2016. Weather in the courtroom : memoirs from a career in forensic meteorology.

Henson R. 2010. Weather on the Air A History of Broadcast Meteorology. Dordrecht: Springer.

Iliinsky NPN, Steele J. 2011. Designing data visualizations. Beijing: O'Reilly.

Kampf J. 2014. Advanced ocean modelling. Springer.

Kampf J. 2010. Ocean modelling for beginners : using open-source software. Berlin; Heidelberg: Springer.

Knaflic CN. 2015. Storytelling with data : a data visualization guide for business professionals. Hoboken: Wiley.

Kokhanovsky AA, Leeuw GHd. 2009. Satellite aerosol remote sensing over land. Berlin; New York; Chichester, UK: in association with Praxis Publishing.

Koracin D, Dorman CE. Marine Fog: Challenges and Advancements in Observations, Modeling, and Forecasting.

Kutz JN. 2013. Data-Driven Modeling & Scientific Computation : Methods for Complex Systems & Big Data. Oxford: Oxford.

Lakshmivarahan S. 2017. Forecast error correction using dynamic data assimilation.

Matthes E. 2017. Python crash course.

Navidi WC. 2015. Statistics for engineers and scientists.

Niki H, Becker KH. The Tropospheric chemistry of ozone in the polar regions. Berlin; New York: Springer-Verlag.

Overway KS. 2017. Environmental chemistry : an analytical approach.

Park Y-S. 2015. Advanced modelling techniques studying global changes in environmental sciences. Amsterdam: Elsevier.

Qian SS. 2017. Environmental and ecological statistics with R. Boca Raton; London; New York: CRC Press, Taylor & Francis Group.

Quattrochi DA. 2017. Integrating scale in remote sensing and GIS.

Reich S, Cotter C. 2015. Probabilistic forecasting and bayesian data assimilation. Cambridge: Cambridge University Pres.

Sen Z. 2015. Applied drought modeling, prediction, and mitigation. Amsterdam: Elsevier.

Talley LD, Emery WJ, Pickard GL. 2012. Descriptive physical oceanography : an introduction. Amsterdam: Academic Press.

Walkowiak S. 2016. Big data analytics with R. Packt Publishing Limited.

White WM. 2013. Geochemistry. Wiley-Blackwell.

Yang CP. 2017. Introduction to GIS programming and fundamentals with Python and ArcGIS. Boca Raton: CRC Press.








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