Dr. John R. Mecikalski

"do or do not, there is no try" - Yoda, (The Empire Strikes Back)

mecikalski-map

birthofstorm

Associate Professor

Office: NSSTC
Phone: 256.961.7046
Fax: 256.961.7755
Email: john.mecikalski@nsstc.uah.edu 

 Research Interests

  • Satellite Data Assimilation
  • Mesoscale Modeling
  • Tropical Meterology
  • Atmospheric Convection
  • Satellite Remote Sensing 

Biography

Dr. Mecikalski received his Ph.D. in Atmospheric Science from the University of Wisconsin--Madison (UW) in August 1999. His B.S. and M.S. degrees in Atmospheric Science, with an emphasis in Mathematics, Computational Methods and Botany, from the University of Wisconsin-- Milwaukee, were completed in May 1988 and December 1991 respectively. Major areas of interest include dynamics of scale interaction within convectively driven weather systems, tropical meteorology, numerical modeling, boundary layer processes, regional energy budget estimations, and assessing the atmospheric boundary layer and convection using remote sensing technologies.

Why Atmospheric Science?

John's interest in weather started in elementary school, and this fed his curiosity to collect weather observations in Wisconsin for ~10 years. Chasing storms, modeling convective clouds, and understanding how to use satellite data provides the basis of his enthusiasm in a relatively wide variety of research he performs today at UAHuntsville.

Education

1993 - 1999 Ph.D., Atmospheric Science, University of Wisconsin - Madison, USA, Advisor: Dr. Gregory J. Tripoli
Dissertation: Inertial Stability, Cumulus Momentum Transport, and the Genesis of Tropical Plumes
1988 - 1991 M.S., Atmospheric Science, University of Wisconsin - Milwaukee, USA, Advisor: Dr. Jeffery S. Tilley
Thesis: Cold Surges along the Front Range of the Rocky Mountains: A Classification Scheme and Synoptic Case Study
1983 - 1988 B.S., Atmospheric Science [Minor: Mathemetics & Botany], University of Wisconsin - Milwaukee, USA

Accomplishments

  • Bill Carlson Scholarship for academic excellence in the field of Atmospheric Science; University of Wisconsin–Milwaukee 1987.
  • NASA New Investigator Award for outstanding research and education prospects in the area of convective initiation with an emphasis on aviation safety; UW/CIMSS 2002.
  • NASA Group Achievement Award, Earth Science Applications Team. In recognition of exceptional achievement in developing the highly successful air quality, aviation weather, and energy management applications for the earth science enterprise. September 21, 2006.
  • NASA Aviation Safety and Security Program for outstanding contributions to aviation weather safety research and development; September 21, 2006.
  • NASA Aviation Safety and Security Program for outstanding contributions to aviation weather safety research and development; University of Alabama in Huntsville – Institution Award. September 21, 2006.
  • NASA Group Achievement Award, Earth Science Applications Team. In recognition of exceptional achievement in developing the highly successful air quality, aviation weather, and energy management applications for the earth science enterprise. September 20, 2007.

Professional Experience

Dr. Mecikalski has been involved in many separate research initiatives since January 1995 (his arrival at CIMSS), several of which have been completed. Listed below are those that began since mid-1997 and/or those that have recently ended. These project have involved scientists at CIMSS, in the Department of Atmospheric and Oceanic Sciences at UW, the Department of Soil Sciences at UW, at OU, Penn State, the ONR, NCAR, NASA, the USDA, and the National Severe Storms Laboratory (NSSL), as well as other institutions. Collaborations since 2004 have grown to include the NASA Marshall Space Flight Center (MSFC) at UAH, and the NWS WFO Huntsville. The inception date of each project is listed.

  • Cumulus Momentum Transport, Convective Modeling and Convective Organization— Research and Applications using TRMM data. Funded project through NASA. [Principal Investigator April 2000–May 2003].
  • Developing the University of Wisconsin– Nonhydrostatic Modeling Systems (UW-NMS) model for implementation on a distributed memory, multiprocessor Linux PC cluster for GIFTS data processing and assimilation for numerical weather prediction. Working in collaboration with Dr. H.-L. Allen Huang (Associate Scientist, CIMSS) and Dr. Greg Tripoli (Professor, UW AOS). [April 2000–December 2001]
  • Studying Convection Initiation through the analysis of GOES and MODIS imagery. Working in collaboration with Rita Robert, Cathy Kessinger and Cindy Mueller (Re­search Scientists, NCAR). Newly funded through NASA New Investigator Program July 2002. [Since March 2001; Principal Investigator as of July 2002]
  • Developing Methods and Computational Processing for GIFTS within the Office of Naval Research UW and University of Hawaii (UH) MURI. Working in collaboration with Dr. H.-L. Allen Huang (Associate Scientist, CIMSS), Dr. Paul Lucey of UH, Dr. Ping Yang (Texas A & M University), Dr. Irina Sokolik (University of Colorado Boulder), and Dr. Gary Jedlovik (University of Alabama–Huntsville). [Program Manager June 2001–December 2003]
  • Studying ABL Turbulence and CI through the analysis of AERI, Raman lidar and GOES imagery. Working in collaboration with Dr. Tammy Weckwerth (Research Scientist, NCAR), and Wayne Feltz (Researcher, CIMSS). [August 2001–December 2003]
  • Developing improved methods for evaluating Forecast Sensitivities and optimal Satellite Data Assimilation Methods. Working in collaboration with Dr. Michael Morgan (Pro­fessor, UW AOS) and other UW AOS Graduate students. [December 2000–March 2001]
  • Surface Energy Flux Estimation using an Atmospheric-Land Exchange Model, and Validation with Oklahoma Mesonet Observations. Working in collaboration with Dr. Scott Richardson (Department of Meteorology, Penn State), Dr. George Diak (Se­nior Scientist, CIMSS), and Dr. Robert Rabin (Research Scientist, OU/NSSL). More recently, processing of LandSat-ETM+ data for flux disaggregation with NCAR collab­oration (Dr. Peggy LeMone, NCAR) [Co-Investigator since June 1997; Program Manager since September 2001]
  • Surface Energy Flux Climatology development using an Atmospheric-Land Exchange Inverse (ALEXI) model. Working in collaboration with Dr. George Diak (Senior Scientist, CIMSS), Dr. John Norman (Professor, UW Department of Soil Sciences, and Dr. Martha Anderson (Research Scientist, UW Department of Soil Sciences). [Co-Investigator since May 2000; Program Manager since September 2001]
  • Surface Energy Applications for Convective Initiation Studies and Numerical Modeling.Working in collaboration with Dr. Ken Davis (Assistant Professor, Penn State Univ.) and Dr. Dave Stauffer Professor, Penn State Univ.). [CIMSS Principal Investigator since January 2002]
  • Advanced Satellite Aviation Products (ASAP) Report Study Development for the Processing of satellite data for Aviation-related Products. Working in collaboration with NASA, NOAA and several CIMSS scientists. Coordinated by John Murray (NASA Langley Research Center). Project initiation date: October 2002. [Since July 2001; Principal Investigator since May 2003]
  • Implications of Field-scale Heterogeneity in Surface Moisture and Vegetation cover from Land-Atmosphere Modeling and Remote Sensing Perspectives. Work in support of the Soil Moisture Field Experiment (SMEX02) for NASA's Land Surface Hydrology Pro­gram Soil Moisture Mission (EX-4a) and the Global Water and Energy Cycle (GWEC) Research Program. In collaboration with the USDA, UW Soil Sciences, Utah State Univ., Texas A & M, and the Univ. of Virginia. [Co-Investigator since November 2001]
  • Precision Agricultural Applications and Meteorological Support for the NASA-funding Regional Earth Science Applications Centers (RESAC) at UW, the University of Min­nesota and Michigan State University. Working in collaboration with Dr. George Diak (Senior Scientist, CIMSS), Dr. John Norman (Professor, UW Department of Soil Sciences), Dr. John Foley (Professor, UW Department of Climate, People and the Environment), and Dr. S. Thomas Gower (Professor, UW Department of Forestry). [October 1998–September 2001]
  • Developing improved Tropical Storm Genesis indicators based on satellite-derived fields and basic research. Working in collaboration with Dr. Chris Velden (Scientist, UW­CIMSS). [Since January 2003; enhanced in 2010.]
  • Short-term Prediction, Nowcasting and Data Assimilation studies. Working in collab­oration with Dr. William Lapenta (NASA MSFC), Gary Jedlovec (NASA MSFC) and the NWS WFO Huntsville Science Operations Officer (Tom Bradshaw, Chris Darden) on ways to integrate satellite assimilation and nowcasting research to meet NWS needs. Involves Graduate students within UAH. [January 2004–Present]
  • National Weather Service Southern Region on efforts to transition of research products in short-term prediction to the local Huntsville WFO, as well as to other offices. Work with Morristown WFO to transition products into the AvnFPS for aviation safety forecasting. Involves Graduate students within UAH. [January 2004–2008]
  • WAAY-TV Channel 31 Huntsville. Development and transition of research products in short-term prediction to this local television station. Work with Brad Huffines (WAAY) to develop weather-related stories that may be presented on Channel 31 and/or CNN News. Involves Graduate students within UAH. [January 2004–January 2008]
  • The SIAM-SERVIR and CATHALAC. City of Knowledge, Panama. Work toward to transition of short-term prediction research to Mesoamerica. Collaborate with Drs. Dan Irwin and Tom Sever (NASA MSFC) [December 2005–Present]
  • NASA ROSES Convective Induced Turbulence. Development of new research towards enhancing the ability to detect convectively-induced turbulence (CIT), using satellite assets for detection. Development of "interest fields" for CIT. Collaborations with the NCAR and the Univ. Wisconsin–CIMSS, specifically Robert Sharman, John WIlliams, and Wayne Feltz.[January 2006–August 2009]
  • Enhanced ALEXI Development and Research. Perform new research related to the use of the ALEXI model in soil moisture data assimilation, soil moisture monitoring, for drought/plant stress monitoring, and for water management. Also involves research to develop the ALEXI model for use over Europe, and to help assess stream and river flows via drought monitoring. In collaboration with the USDA (Drs. Martha Anderson and Wade Crow), and others in the European research community. [January 2006– Present]
  • NASA ROSES Aviation Safety Research. Development of new research towards maxi­mizing the use of satellite towards nowcasting convection, rainfall and lightning on the 1-4 km scale. Collaborations with the MIT-Lincoln Labs, and NASA Marshall Space Flight Center. [2006–Present]
  • Advanced Satellite Aviation Products (ASAP) Development and Transition. A sub­component of ASAP to transition the SATCAST convective initiation algorithm into the Corridor Integrated Weather System, the 0-2 hr nowcasting component of the Consolidated Storm Prediction Algorithm (CoSPA). Involves collaboration with sev­eral members of the Convective Weather Product Development Team at MIT-Lincoln Laboratory, including Marilyn Wolfson. [June 2007–Present]
  • The EUMETSAT–Darmstadt, Germany. Transition activities towards the develop­ment and improvement of a convective initiation algorithm for the Meteosat Second Generation (MSG) satellite. Also, proceeding on new development efforts for using data from the Meteorsat Third Generation (MTG) imager and hyperspectral sounder. Involves staff at EUMETSAT, and at the Institute for Meteorology and Water Man­agement (IMWM) in Krawkow, Poland.[June 2007–December 2008]
  • The EUMETSAT–Darmstadt, Germany. Member of the EUMETSAT Convective Working Group. Involves ongoing collaboration with EUMETSAT staff members Mar­ianne Koenig and Volker Gaertner to enhance the use of SEVIRI data in the SATCAST algorithm for 0-1 hr convective initiation nowcasting. Collaborations occur with many in the European convective weather forecasting and nowcasting communities. [Jan­uary 2008–Present]
  • The Nooly Project–Jerusalem, Israel. Private sector venture towards the incorporation of the convective and lightning initiation algorithm within a cell-phone based alert ser­vice. Currently in development and discussion, at UAH and with Nooly. [December 2007–Present]
  • NASA Mesoamerican Biological Corridor Research. Basic research to assess the impact of changing land-use on nearby highly biologically diverse areas in Central American. Use a variety of remote-sensing datasets to perform analysis to detect trends caused by human activities. In collaboration with the UAHuntsville Department of Biology. [December 2008–Present]
  • NOAA Algorithm Working Group (AWG). Perform transition activities of SATCAST convective initiation nowcasting algorithm into the NOAA Algorithm Set in support of the forthcoming GOES-R satellite. Involves collaboration with many NOAA AWG personnel. [March 2008–Present]
  • National Science Foundation. Basic research to study relationships between dual­polarimetric radar, geostationary satellite, and lightning mapping array data. [August 2008–Present]

Interests and Volunteer Activities

Dr. John R. Mecikalski has been actively involved in the American Meteorological So­ciety (AMS) since joining in 1983. In addition to submitting papers to AMS, Royal Me­teorological Society and American Geophysical Union (AGU) journals (see above), he has been called to review papers for the AMS journals Journal of Applied Meteorology, Monthly Weather Review, Journal of Atmospheric Sciences, Journal of Hydrometeorology, Weather and Forecasting, Water Resources Research, Int. J. Climatology, Remote. Sens. Environ., J. Geophys. Res., and the International J. of Climatology. John has also been an active member of the AGU since 1994, and the Royal Meteorological Society since 2002.

Dr. Mecikalski has been asked to serve as a proposal reviewer for several NASA and NSF funding opportunities since 1999.

Dr. Mecikalski is serving on the program committee of the Atmospheric and Environmen tal Remote Sensing Data Processing and Utilization component of the International Society for Optical Engineering (SPIE), from 2004 to 2006. In 2007, John was nominated to the Tech nical Committee of the American Institute of Aeronautics and Astronautics (AIAA), and in January 2008 to the American Meteorological Society’s Aviation, Range, and Aerospace Meteorology (ARAM) component.

Research

Research Interests

  1. Satellite data assimilation for mesoscale and microphysical processes, of soil moisture, and for nowcasting. Forward model development of retrieval methods.
  2. Numerical modeling of moist convection, parameterization development, and cumulus momentum transport.
  3. Moist convective dynamics, tropical convection, factors influencing the initiation of deep moist convection. Remote sensing of convective weather systems. Theoretical studies of tropical weather systems.
  4. Diagnosing micro- and mesoscale weather phenomena from remotely-sensed (hyperspectral) data sets for the purpose of nowcasting and evaluating hazardous weather for aviation interests.
  5. Land surface energy and moisture fluxes. Developing remote sensing techniques for diagnosing such fluxes using satellite remote sensing.
  6. Modeling interactions between the biosphere and atmosphere on time scales of the meso- and synoptic scale.

Research Categories

han-coursesSatellite-based Convective Storm & Convective Initiation Studies

Satellite-based Surface Energy Flux/Soil Moisture Estimation

Solar Insolation & Water Management Studies

  • Solar Insolation & Water Management Studies

Data Assimilation

Publications

  • Mecikalski, J. R., D. M. Sumner, J. M. Jacobs, C. S. Pathak, S. J. Paech, and E. M. Douglas, 2011: Use of Visible Geostationary Operational Meteorological Satellite Imagery in Mapping Reference and Potential Evapotranspiration over Florida. Evapotranspiration. ISBN 978-953-307-251-7, Editor Leszek Labedzki, Chapter 10, pgs. 229-254.
  • Mecikalski, J. R., P. D. Watts, and M. Koenig, 2011: Use of Meteosat Second Generation optimal cloud analysis fields for understanding physical attributes of growing cumulus clouds. Atmos. Res.,102, 175-190.
  • Gambill, L. D., and J. R. Mecikalski, 2011: A satellite-based summer convective cloud frequency analysis over the Southeastern United States. J. Appl. Meteor. Climatol.,50, 1756-1769.
  • Hain, C. R., W. T Crow, J. R. Mecikalski, M. C. Anderson, and T. Holmes, 2011: An intercomparison of available soil moisture estimates from thermal infrared and passive microwave remote sensing and land surface modeling. J. Geophys. Res.,116, doi:10.1029/2011JD015633.
  • Anderson, M. C., C. Hain, B. Wardlow, A. Pimstein, J. R. Mecikalski, and W. P. Kustas, 2011: Evaluation of drought indices based on thermal remote sensing of evapotranspiration over the Continental United States. J.Climate,24, 2025–2044.
  • Anderson, M. C., W. P. Kustas, J. M. Norman, C. R. Hain, J. R. Mecikalski, L. Schultz, M. P. González-Dugo, C. Cammalleri, G. d'Urso, A. Pimstein, and F. Gao, 2011: Mapping daily evapotranspiration at field to continental scales using geostationary and polar orbiting satellite imagery. Hydrol. EarthSyst. Sci.,15, 223-239.
  • Mecikalski, J. R., W. M. Mackenzie, M. Koenig, and S. Muller, 2010a: Use of Meteosat Second Generation infrared data in 0-1 hour convective initiation nowcasting. Part 1. Infrared fields. J. Appl. Meteor. Climate.,49, 521-534.
  • Mecikalski, J. R., W. M. Mackenzie, M. Koenig, and S. Muller, 2010b: Use of Meteosat Second Generation infrared data in 0-1 hour convective initiation nowcasting. Part 2. Use of visible reflectance. J. Appl. Meteor. Climat.49, 2544-2558.
  • Gambill, L. D., and J. R. Mecikalski, 2010: A satellite-based summer convective cloud analysis over the Southeastern United States. Mon. Wea. Rev. Accepted.
  • Li, X., and J. R. Mecikalski, 2010: Assimilation of dual-polarization Doppler radar data for a convective storm with a warm-rain forward operator. J. Geophys. Res.115, D16208, doi:10.1029/2009JD013666.
  • Mecikalski, J. R., J. R. Walker, W. M. MacKenzie, and K. Bedka, 2010: NOAA NESDIS Center for Satellite Applications and Research, Algorithm Theoretical Basis Document, version 0.5, 55 pages.
  • Siewert, C. W., M. Koenig, and J. R. Mecikalski, 2010: Application of Meteosat Second Generation data towards improving the nowcasting of convective initiation. Meteorol. Appl.17, 442-451.
  • Jewett, C. P., and J. R. Mecikalski, 2009: Estimating convective momentum fluxes using geostationary satellite data. J. Geophys. Res.115, D14104, doi:10.1029/ 2009JD012919.
  • Harris, R. J., J. R. Mecikalski, W. M. MacKenzie, Jr., P. A. Durkee, and K. E. Nielsen, 2010: The definition of GOES infrared lightning initiation interest fields. J. Appl. Meteor. Climat.49, 2527-2543.
  • Asefi-Najafabady, S., K. Knupp, J. R. Mecikalski, R. M. Welch, and D. Phillips, 2010: Ground-based measurements and dual-Doppler analysis of 3D wind fields and atmospheric circulations induced by a meso-a scale inland lake. In Press. J. Geophys. Res.
  • Walker, J. R., J. R. Mecikalski, K. R. Knupp, and W. M. MacKenzie, Jr., 2009 : Development of a land surface heating index-based method to locate regions of potential mesoscale circulation formation, J. Geophys. Res.114, D16112, doi:10.1029/ 2009JD011853.
  • Bedka, K. M., C. S. Velden, R. Petersen, and J. R. Mecikalski, 2009: Statistical comparisons between satellite-derived atmospheric motion vectors, rawinsondes, and NOAA wind profiler observations. J. Appl. Meteor. Climate.48, 1542-1561.
  • Hain, C. R., J. R. Mecikalski, and M. C. Anderson, 2009: Retrieval of an available water-based soil moisture proxy from thermal infrared remote sensing. Part I: Methodology and validation. J. Hydrometeor.10, 665-683.
  • Paech, S. J., J. R. Mecikalski, D. M. Sumner, C. S. Pathak, Q. Wu, S. Islam, and T. Sangoyomi, 2009: Satellite-based solar radiation in support of potential and reference evapotranspiration estimates over Florida: A 10-year climatology. J. Amer. Water Res. Assoc.45(6), 1328-1342.
  • Harrison, S. J., J. R. Mecikalski, and K. R. Knupp, 2009: Analysis of outflow boundary collisions in north-central Alabama. Wea. Forecasting24, 1680-1690.
  • Jacobs, J., M. Anderson, J. Mecikalski, C. Hain, L. Schultz, M. Choi, and S. Bhat, 2009: Georgia evapotranspiration (ET) and drought estimation via remotely-sensed data. U. New Hampshire, Dept. Civil Engineering, 26 pp.
  • Anderson, M. C., J. R. Mecikalski, J. Jacobs, C. Hain, and L. Schultz, 2009: Estimation of actual evapotranspiration over South Florida, South Florida Water Management District, Technical Report, 21 September 2009, 99 pp.
  • Harmsen, E. W., J. Mecikalski, M. J. Cardona-Soto, A. R. Gonzalez, and R. Vasquez, 2009: Estimating daily evapotranspiration in Puerto Rico using satellite remote sensing.WSEAS Trans. Environ. Develop.5(6), 456-465.
  • Mecikalski, J. R., K. M. Bedka, S. J. Paech, and L. A. Litten, 2008: A statistical evaluation of GOES cloud-top properties for predicting convective initiation. Mon. Wea. Rev.,136, 4899-4914.
  • Berendes, T. A., J. R. Mecikalski, W. M. Mackenzie, K. M. Bedka, and U. S. Nair, 2008: Convective cloud detection in satellite imagery using standard deviation limited adaptive clustering. J. Geophys. Res.113, 20207, doi:10.1029/2008JD010287.
  • Mecikalski, J. R., W. M. Mackenzie, and K. M. Bedka, 2008: NOAA NESDIS Center for Satellite Applications and Research, Algorithm Theoretical Basis Document: Convective Initiation. Draft Document, version 0.1. August 29, 2008. 33 pp.
  • Jacobs, J., J. Mecikalski, and S. Paech, 2008: Satellite-based solar radiation, net radiation, and potential and reference evapotranspiration estimates over Florida. A Technical Report prepared for the State of Florida Water Management Districts. Available online at: http://hdwp.er.usgs.gov/ET/GOES_FinalReport.pdf
  • Mecikalski, J. R., J. Srikishen, and C. S. Pathak, 2008: Evapotranspiration (ET) Network Design Study: Part I - Solar Radiation Ground Sensor Network Design. A Technical Report prepared for the South Florida Water Management District (SFWMD). 1 October 2008, 120 pp.
  • Mecikalski, J. R., J. J. Murray, W. F. Feltz, D. B. Johnson, K. M. Bedka, S. T. Bedka, A. J. Wimmers, M. Pavolonis, T. A. Berendes, J. Haggerty, P. Minnis, B. Bernstein, and E. Williams, 2007: Aviation applications for satellite-based observations of cloud properties, convective initiation, in-flight icing, turbulence and volcanic ash. Bull. Amer. Meteor. Soc.88, 1589-1607.
  • Anderson, M. C., J. M. Norman, J. R. Mecikalski, J. P. Otkin, and W. P. Kustas, 2007 a: A climatological study of surface fluxes and moisture stress across the continental U.S. based on thermal remote sensing I. Model formulation. J. Geophys. Res.112, D10117, doi:10.1029/2006JD007506.
  • Anderson, M. C., J. M. Norman, J. R. Mecikalski, J. P. Otkin, and W. P. Kustas, 2007 b: A climatological study of surface fluxes and moisture stress across the continental U.S. based on thermal remote sensing II. Surface moisture climatology. J. Geophys. Res.112, D11112, doi:10.1029/2006JD007507.
  • Mecikalski, J. R., 2007: COVER: Bulletin of the American Meteorological Society, "Sensing Trouble – Satellite Applications for Aviaiton". 88.
  • Anderson, M. C., J. M. Norman, J. R. Mecikalski, J. P. Otkin, and W. P. Kustas, 2007: A climatological study of surface fluxes and moisture stress across the continental U.S. based on thermal remote sensing I. Model formulation. J. Geophys. Res.112, D10117, doi:10.1029/2006JD007506.
  • Anderson, M. C., J. M. Norman, J. R. Mecikalski, J. P. Otkin, and W. P. Kustas, 2007: A climatological study of surface fluxes and moisture stress across the continental U.S. based on thermal remote sensing II. Surface moisture climatology. J. Geophys. Res.112, D11112, doi:10.1029/2006JD007507.
  • Mecikalski, J. R., and K. M. Bedka, 2006: Forecasting convective initiation by monitoring the evolution of moving convection in daytime GOES imagery. Mon. Wea. Rev. 134, 49-78.
  • Mecikalski, J. R., K. M. Bedka, D. D. Turner, W. F. Feltz, and S. J. Paech, 2006: The ability to quantify coherent turbulent structures in the convective boundary layer using thermodynamic profiling instruments. J. Geophys. Res. 111, D12203, doi:10.1029/ 2005JD006456.
  • Bedka, K. M., and J. R. Mecikalski, 2005: Application of satellite-derived atmospheric motion vectors for estimating mesoscale flows. J. Appl. Meteor.44, 1761-1772.
  • Anderson, M. C., J. M. Norman, W. P. Kustas, F. Li, J. H. Prueger, and J. R. Mecikalski, 2005: Effects of vegetation clumping on two-source model predictions of surface energy fluxes from an agricultural landscape during SMACEX. J. Hydrometeor. 6, 892-909.
  • Molling, C. C., J. C. Strikwerda, J. M. Norman, C. A. Rodgers, R. Wayne, C. L. S. Morgan, G. R. Diak, and J. R. Mecikalski, 2005: Distributed runoff formulation designed for a precision agricultural- landscape modeling system. J. Amer. Water Res. Assoc. (JAWRA),41, 1289-1313.
  • Mecikalski, J. R., K. M. Bedka, and S. J. Paech, 2005: Correlating satellite infrared trends, total lightning, and rainfall with convective initiation and development. Bull. Amer. Meteor Soc., (NOWCAST: Conference Notebook section), 86, 21-22.
  • Otkin, J. A., M. C. Anderson, G. R. Diak, and J. R. Mecikalski, 2005: Vaidation of GOES-based insolation estimates using data from the United States climate reference network. J. Hydrometeor6, 460-475.
  • Anderson, M. C., J. M. Norman, J. R. Mecikalski, R. D. Torn, W. P. Kustas, and J. B. Basara, 2004: A multi-scale remote sensing model for disaggregating regional fluxes to micrometeorological scales. J. Hydrometeor., 5, 343-363.
  • Diak, G. R., J. R. Mecikalski, M. C. Anderson, J. M. Norman, W. P. Kustas, R. D. Torn, and R. L. DeWolf, 2004: Estimating land-surface energy budgets from space: Review and current efforts at the University of Wisconsin-Madison and USDA-ARS. Bull. Amer. Meteor. Soc.,85, 65-78.
  • Mecikalski, J. R., 2003: Estimating momentum fluxes of deep precipitating convection using profiling Doppler radar. J. Geophys. Res.108 (D6), AAC2-1 - AAC2-14. (March 2003)
  • Mecikalski, J. R., and G. J. Tripoli, 2003: The influence of upper tropospheric inertial stability on the cumulus transport of momentum. Q. J. R. Meteorol. Soc.,129, 1537-1563. (April 2003)
  • Feltz, W. F., D. J. Posselt, J. R. Mecikalski, G. S. Wade, and T. J. Schmit, 2003: Rapid boundary layer water vapor transitions. Bull. Amer. Meteor. Soc. (NOWCAST section), 84, 29-30.
  • Anderson, M. C., J. M. Norman, J. R. Mecikalski, R. D. Torn, W. P. Kustas, and J. B. Basara, 2003: A multi-scale remote sensing model for disaggregating regional fluxes to micrometeorological scales. J. Hydrometeor.5, 343-363.
  • Mecikalski, J. R., D. B. Johnson, J. J. Murray, and many others at UW-CIMSS and NCAR, 2002: NASA Advanced Satellite Aviation-weather Products (ASAP) Study Report, NASA Technical Report, 65 pp. [Available from the Schwerdtferger Library, 1225 West Dayton Street, Univ. of Wisconsin-Madison, Madison, WI 53706.]
  • Feltz, W. F., and J. R. Mecikalski, 2002: Monitoring high-temporal resolution stability using the ground-based Atmospheric Emitted Radiance Interferometer (AERI) during the 3 May 1999 Oklahoma/ Kansas tornado outbreak. Wea. Forecasting.,17, 445-455.
  • Mecikalski, J. R., 2004: COVER: Bulletin of the American Meteorological Society, "ALEXI Latent Heat Flux over IHOP: 31 May 2002". 84.
  • Norman, J. M., M. C. Anderson, W. P. Kustas, A. N. French, J. R. Mecikalski, R. D. Torn, G. R. Diak, T. J. Schmugge, and B. C. W. Tanner, 2002: Remote sensing of surface energy fluxes at 10^1-m pixel resolution. Water Resour. Res., 39, 1221.
  • Bindlish, R., W. P. Kustas, A. N. French, G. R. Diak, and J. R. Mecikalski, 2001: Influence of near-surface soil moisture on regional scale heat fluxes: Model results using microwave remote sensing data from SGP97. IEEE Transactions on Geoscience and Remote Sensing39, 1719-1728.
  • Diak, G. R., W. L. Bland, J. R. Mecikalski, and M. C. Anderson, 2000: Satellite-based estimates of longwave radiation for agricultural applications. Ag. For. Meteor. 103, 349-355.
  • Elsner, J. B., J. R. Mecikalski, and A. A. Tsonis, 1989: PICTURE OF THE MONTH: A shore parallel cloud band over Lake Michigan. Mon. Wea. Rev.117, 2822-2823.
  • Mecikalski, J. R., 1991: Cold surges along the front range of the Rocky Mountains: Synoptic climatology and case study analysis. MS Thesis, Department of the Geosciences, University of Wisconsin - Milwaukee, 226 pp.
  • Mecikalski, J. R., and J. S. Tilley, 1992: Cold surges along the front range of the Rocky Mountains: Development of a classification scheme. Meteorol. Atmos. Phys., 48, 249-271.
  • Diak, G. R., W. L. Bland, and J. R. Mecikalski, 1996: A note on first estimates of surface insolation from GOES-8 visible satellite data. Ag. For. Meteor.82, 219-226.
  • Mecikalski, J. R., G. R. Diak, J. M. Norman, and M. C. Anderson, 1997: A method for estimating regional surface sensible heating using shelter-level air temperature and upper-air data. Ag. For. Meteor.88, 101-110.
  • Anderson, M. C., J. M. Norman, G. R. Diak, W. P. Kustas, and J. R. Mecikalski, 1997: A two-source time-integrated model for estimating surface fluxes using thermal infrared remote sensing. Remote Sens. Environ.60, 195-216.
  • Mecikalski, J. R., and G. J. Tripoli, 1998: Inertial available kinetic energy and the dynamics of tropical plume formation. Mon. Wea. Rev.,126, 2200-2216.
  • Diak, G. R., M. C. Anderson, W. L. Bland, J. M. Norman, J. R. Mecikalski, and R. M. Aune, 1998: Agricultural management decision aids driven by real-time satellite data.Bull. Amer. Meteor. Soc.79, 1345-1355.
  • Mecikalski, J. R., 1999: Inertial stability, cumulus momentum transport, and the genesis of tropical plumes. Ph.D. Dissertation, Department of Atmospheric and Oceanic Sciences, University of Wisconsin - Madison, 375 pp.
  • Mecikalski, J. R., G. R. Diak, M. C. Anderson, and J. M. Norman, 1999: Estimating fluxes on continental scales using remotely-sensed data in an atmospheric-land exchange model. J. Appl. Meteor.,38, 1352-1369.

Courses

ATS 652 - Synoptic Meteorology

This course will overview concepts of objective analysis methods relevant to atmospheric science, atmospheric data assimilation, and remote-sensing based data assimilation procedures. In the process of presenting the above three areas, in depth discussions of numerical weather prediction (NWP), the governing atmospheric dynamic equation sets, and the characteristics of the data sources used within NWP models will be provided.

The goal of the course is to provide students in graduate level atmospheric science a broad background into atmospheric data assimilation, while focusing on several exercises of assimilation techniques. This is done through projects as a means of providing students hands-on examples to build expertise. Homework assignments will involve use of Fortran, C/C++, Matlab, and IDL. It is highly desirable for students to have or gain skills in programming compiled languages, like C, C++, and Fortran.

Course Syllabus:

  1. Overview:
    1. Course Description
    2. "Big Picture" of Data Assimilation
  2. Matrix Methods:
    1. Review: Matricies & Linear Algebra
    2. Adjoints
  3. Statistical Analysis:
    1. Statistics: Variance & Correlations
    2. Least Squares-Regression
    3. Interpolation
  4. Atmospheric NWP Models:
    1. Governing Equation; Scale Representation
    2. History
    3. Filtering & Descritization; Errors
    4. Initialization
  5. Methods of Objective Analysis:
    1. Cressman & The Barnes' Scheme
    2. Function Fitting
  6. The Assimilation of Data:
    1. Conventional Data
    2. Satellite & Remote Sensing
    3. Assimilation & Data Types; Data Quality Controls
  7. Applied Methods in Data Assimilation:
    1. Data Replacement; "Hot Start" Initialization
    2. Empirical Methods: Successive Correction & Nudging
    3. Background Errors; Covariances
    4. Multivariate Statistics and Optimal Interpolation
    5. Least Square Methods: Least Square & Variational Approaches
    6. Adjoints & Tangent Linear Models
    7. Kalman Filters; Ensemble Kalman Filters
  8. Advanced Topics:
    1. Chaotic Dynamical Systems
    2. Predictability & Error Growth
    3. Singular Vectors; Error Growths
    4. Ensemble Forecasting

ATS 656 - Tropical Meteorology & Moist Convective Systems

This course draws together concepts in the dynamics and climatology of the tropical atmosphere, as well as of significant precipitation systems across the Tropics. Specific topic areas include synoptic climatology, the dynamics of tropical flows (e.g., Kelvin waves, near Equatorial flows), convective scale dynamics, island meteorology, tropical cyclones, and the broad forces driving tropical circulations (e.g., ENSO, radiative-convective equilibrium, latent heating distributions, gregarious cloud systems). A review of key low-latitude jets, and oceanic currents, will be provided.

The goal of the class is to provide students in graduate level atmospheric science a background into tropical meteorology, emphasizing aspects of atmospheric convection across the Tropics. Exercises will focus on scales of weather between 30 N and 30 S, dynamical processes, building theoretical foundations, and real data analysis. The course will assume a strong familiarity with atmospheric thermodynamics (ATS 541) and dynamics (ATS 551) so this course's material can grow from these basic concepts.

Course Syllabus:

  1. Fundamentals:
    1. What makes the "Tropics" the Tropics?
    2. Heating distributions
    3. The Ocean-Atmosphere connection
    4. Climate versus Weather in the Tropics
  2. Tropical Dynamics:
    1. Tropical flow characteristics
    2. Scale analysis
    3. Comparison to Midlatitude systems
    4. Equatorial flows; Kelvin waves, Walker circulations
    5. Large scale flows: El Nino-Southern Oscillation (ENSO); Monsoons; ITCZ; Subtropical Anticyclones;
    6. Ocean dynamics, currents and SSTs in Tropics
  3. Synoptic Scale Circulations:
    1. Jet streams
    2. Westerly wind events
    3. Persistent convergent zones
    4. Influences of the land and sea
  4. Mesoscale Features:
    1. Easterly waves
    2. Island meteorology
    3. Convective systems and regimes
  5. Dynamics of Moist Convection:
    1. Scale analysis
    2. Convective modes
    3. Heat, moisture and momentum transports
    4. Oceanic influences
    5. Convective parameterizations
  6. Tropical Cyclones:
    1. TC Climatology
    2. TC development and maintenance
    3. Effects on tropical environment
  7. Large Scale Constraints:
    1. Radiative-Convective equilibrium
    2. WISHE
    3. Ocean currents and mountain ranges

ATS 675 - Atmospheric Data Assimilation

This course will overview concepts of objective analysis methods relevant to atmospheric science, atmospheric data assimilation, and remote-sensing based data assimilation procedures. In the process of presenting the above three areas, in depth discussions of numerical weather prediction (NWP), the governing atmospheric dynamic equation sets, and the characteristics of the data sources used within NWP models will be provided.

The goal of the course is to provide students in graduate level atmospheric science a broad background into atmospheric data assimilation, while focusing on several exercises of assimilation techniques. This is done through projects as a means of providing students hands-on examples to build expertise. Homework assignments will involve use of Fortran, C/C++, Matlab, and IDL. It is highly desirable for students to have or gain skills in programming compiled languages, like C, C++, and Fortran.

Course Syllabus:

  1. Overview:
    1. Course Description
    2. "Big Picture" of Data Assimilation
  2. Matrix Methods:
    1. Review: Matricies & Linear Algebra
    2. Adjoints
  3. Statistical Analysis:
    1. Statistics: Variance & Correlations
    2. Least Squares-Regression
    3. Interpolation
  4. Atmospheric NWP Models:
    1. Governing Equation; Scale Representation
    2. History
    3. Filtering & Descritization; Errors
    4. Initialization
  5. Methods of Objective Analysis:
    1. Cressman & The Barnes' Scheme
    2. Function Fitting
  6. The Assimilation of Data:
    1. Conventional Data
    2. Satellite & Remote Sensing
    3. Assimilation & Data Types; Data Quality Controls
  7. Applied Methods in Data Assimilation:
    1. Data Replacement; "Hot Start" Initialization
    2. Empirical Methods: Successive Correction & Nudging
    3. Background Errors; Covariances
    4. Multivariate Statistics and Optimal Interpolation
    5. Least Square Methods: Least Square & Variational Approaches
    6. Adjoints & Tangent Linear Models
    7. Kalman Filters; Ensemble Kalman Filters
  8. Advanced Topics:
    1. Chaotic Dynamical Systems
    2. Predictability & Error Growth
    3. Singular Vectors; Error Growths
    4. Ensemble Forecasting

ATS 740 - Advanced Mesoscale Meteorology

This course will overview cloud processes, beyond the scales of cloud physics, up to and including mesoscale processes that maintain and develop clouds, and mesoscale circulations that result from cloud systems. Therefore, an overview of moist dynamics will be provided from both an analytic and modeling perspective. As dynamic and thermodynamic processes are reviewed, topics related to various cloud types and cloud systems will be provided. This class will also provide students in graduate level atmospheric science a background cloud-scale processes, as well as an understanding of the dynamic and thermodynamic aspects of clouds in concert with cloud-physics and mesoscale meteorology.

Course Syllabus:

  1. Overview:
    1. Course Description
    2. Introduction: Clouds (types, formation, maintenance, etc.)
    3. Microphysics and the synoptic scale
    4. Cloud parameters
  2. Governing Dynamic Equations:
    1. Dynamic equations for moist convection
    2. Introduction to stability
    3. Scale analysis
    4. Non-hydrostatic conditions
  3. Moist Thermodynamics:
    1. Thermodynamic energy equation
    2. Conservative variables; phase changes
  4. Cloud Resolving Modeling:
    1. Model construction
    2. Parametrizations: Microphysics (bulk)
    3. Averaging
  5. Influence on Environment & Clouds
    1. Q1 and Q2
    2. Momentum flux
  6. Convection & Parcel Stability:
    1. Slantwise
    2. Vertical
  7. Moist Convective Systems; Dynamics of Clouds:
    1. Rainbands; isentropic flow
    2. Thunderstorms; deep, moist convection
    3. Mesoscale convective systems
    4. Tropical storms
  8. Observations of Clouds:
    1. Satellite data analysis
    2. Radar
    3. In situ; aircraft
    4. Ground-based instrumentation
    5. Assimilation of cloud observations