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publications

2024

Tracy, C., and J. R. Mecikalski, 2024: Mesoscale influences of land use, topography, antecedent rainfall, and atmospheric conditions on summertime convective storm initiation under weak synoptic-scale forcing. Wea. Forecasting39, 55–74.

2023

Jones, T. A., and J. R. Mecikalski, 2023: Convective initiation forecasting using synthetic satellite imagery from the Warn-on-Forecast System. J. Operational Meteor., 11, 132-139, https://doi.org/10.15191/nwajom.2023.1110.

Thompson, K. B., J. R. Mecikalski, and M. G. Bateman, 2023: Signatures of oceanic wind events in convection-resolving WRF model simulations. Wea. Forecasting38, 2189–2215.

 

2022

Li, X., J. R. Mecikalski, J. A. Otkin, D. S. Henderson, and J. A. Srikishen, 2022: A polarimetric radar operator and application for convective storm simulation. Atmosphere, 13, 645. https://doi.org/10.3390/atmos13050645

Elmer, N. J., J. R. Mecikalski, A. L. Mothan, D. J. Gochis, and U. Nair, 2022: Impact of real-time satellite-derived green vegetation fraction on National Water Model fluxes in humid Alabama watersheds. J. Amer. Water Resources Assoc., 58, 104–118. https://doi.org/10.1111/1752-1688.12982.

Henderson, D. S., J. A. Otkin, and J. R. Mecikalski, 2022: Examining the role of the land surface on convection using high-resolution model forecasts over the Southeastern U.S. J. Geophys. Res.–Atmos., 127, e2022JD036563.

Leinonen, J., U. Hamann, R. Germann, and J. R. Mecikalski, 2022: Nowcasting thunderstorm hazards using machine learning: the impact of data sources on performance. Nat. Hazards Earth Syst. Sci., 22, 577–597.


2021

Mecikalski, J. R., T. N. Sandmæl, E. M. Murillo, C. R. Homeyer, K. M. Bedka, J. M. Apke, and C. P. Jewett, 2021: A random forest model to assess predictor importance and nowcast severe storms using high-resolution radar-GOES satellite-lightning observations. Mon. Wea. Rev., 149, 1725–1746.

Henderson, D. S., J. A. Otkin, and J. R. Mecikalski, 2021: Evaluating convective initiation in high-resolution numerical weather prediction models using GOES-16 infrared brightness temperatures. Mon. Wea. Rev., 149, 1153–1172.

Thompson, K. B., M. G. Bateman, and J. R. Mecikalski, 2021: Signatures of oceanic wind events in geostationary cloud top temperature and lightning data. Wea. Forecasting, 36, 407–423.

Apke, J. M., and J. R. Mecikalski, 2021: On the origin of rotation derived from super rapid scan satellite imagery at the cloud-tops of severe deep convection. Mon. Wea. Rev., 149, 1827–1851.

Harkema, S. S., E. B. Berndt, J. R. Mecikalski, and A. Cordak, 2021: Advanced Baseline Imager cloud-top trajectories and properties of electrified snowfall flash initiation. Wea. Forecasting, 36, 2289–2303.

Ringhausen, J., P. Bitzer, W. Koshak, and J. Mecikalski, J. 2021: Classification of GLM flashes using random forests. Earth and Space Science, 8, e2021EA001861. 13 pp. https://doi.org/10.1029/2021EA001861.

Melancon, A. M., A. L. Molthan, R. E. Griffin, J. R. Mecikalski, L. A. Schultz, and J. R. Bell, 2021: Random forest classification of inundation following Hurricane Florence (2018) via L-Band synthetic aperture radar and ancillary datasets. Remote Sens., 13, 5098. doi.org/10.3390/rs13245098.

Harmsen, E. W., J. R. Mecikalski, V. J. Reventos, E. Álvarez Pérez, S. S. Uwakweh, and C. Adorno García, 2021: Water and energy balance model GOES-PRWEB: development and validation. Hydrology, 8, 113. doi.org/10.3390/hydrology8030113


2020

Mishra, V., J. F. Cruise, and J. R. Mecikalski, 2021: Assimilation of coupled microwave/thermal infrared soil moisture profiles into a crop model. European Journal of Agronomy123, 126208. doi.org/10.1016/j.eja.2020.126208

Li, X., J. R. Mecikalski, and T. J. Lang, 2020: A study on assimilation of CYGNSS wind speed data for tropical convection during 2018 January MJO. Remote Sens., 12, 1243; doi:10.3390/rs12081243.

Cheng, P., A. P- Biazar, R. T. McNider, and J. R. Mecikalski, 2020: Comparing satellite-based estimates of surface insolation with ground-based observations and Rapid Refresh assimilation/modeling system. J. Atmos. Ocean. Tech., 37, 553–571.

Cecil, D. J., D. E. Buechler, J. R. Mecikalski, and X. Li, 2020: Picture of the Month: Rapid scan visible imagery from the Geostationary Lightning Mapper (GLM) at 2.5-minute intervals. Mon. Wea. Rev., 148, 5105–5112.

Li, X., Mecikalski, J. R., Srikishen, J., Zavodsky, B., and Petersen, W. A., 2020: Assimilation of GPM rain rate products with GSI data assimilation system for heavy and light precipitation events. Journal of Advances in Modeling Earth Systems12, e2019MS001618. https://doi.org/10.1029/2019MS001618.

2019

Sandmæl, T. N., C. R. Homeyer, K. M. Bedka, J. M. Apke, J. R. Mecikalski, and K. Khlopenkov, 2019: Evaluating the ability of remote sensing observations to identify significantly severe and potentially tornadic storms. J. Appl. Meteorol. Climatol., 58, 2569–2590, doi:10.1175/jamc-d-18-0241.1.

Ren, T., A. D. Rapp, J. R. Mecikalski, and J. Apke, 2019: Lightning and associated convection features in the presence of absorbing aerosols over Northern Alabama. J. Geophys. Res., 124https://doi.org/10.1029/2019JD031544.

 Mecikalski, J. R., and E. W. Harmsen, 2019: “The Use of Visible Geostationary Operational Meteorological Satellite Imagery in Mapping the Water Balance over Puerto Rico for Water Resource Management. As published in Satellite Information Classification and Interpretation (ISBN: 978-953-51-7045-7). Editor Rustam B. Rustamov.


2018

Hoover, K. E., J. R. Mecikalski, T. J. Lang, T. J Castillo, X. Li, and T. Chronis, 2018: Use of an end-to-end simulator to analyze CYGNSS. J. Atmos. Ocean. Tech, 35, 35–55.

Mishra, V. W. L. Ellenburg, R. E. Griffin, J. R. Mecikalski, C. R. Hain, and M. C. Anderson, 2018: An initial assessment of SMAP soil moisture disaggregation scheme using TIR surface evaporation data over the continental United States. Int. J. Appl. Earth Obs. Geoinformation., 68, 92–104.

Mecikalski, J. R., W. B. Shoemaker, Q. Wu, M. A. Holmes, S. J. Paech, and D. M. Sumner, 2018: A 20-Year high-resolution GOES insolation–evapotranspiration dataset for water resource management over the State of Florida. J. Irrig. Drain. Eng., 144(9): 04018025.

Ren, T., A. D. Rapp, S. L. Nasiri, J. R. Mecikalski, and J. Apke, 2018: Is the awareness of the aerosol state useful in predicting enhanced lightning for lightning-producing storms over Northern Alabama?, J. Appl. Meteorol. Climatol., 57, 1663–1681.

Apke, J. M., J. R. Mecikalski, K. M. Bedka, E. W. McCaul, C. R. Homeyer, and C. P. Jewett, 2018: Investigating the relationship between deep convection updraft characteristics and satellite based super rapid scan mesoscale atmospheric motion vector derived flow. Mon. Wea. Rev., In Press.

Mishra, V., J. F. Cruise, C. R. Hain, J. R. Mecikalski, and M. C. Anderson, 2018: Development of soil moisture profiles through coupled microwave-thermal infrared observations in the Southeastern United States. Hydrol. Earth Syst. Sci. Discuss., 22, 4935–4857.

Mishra, V., J. F. Cruise, and J. R. Mecikalski, 2018: Assimilation of coupled microwave/thermal infrared soil moisture profiles into a crop model. Remote. Sens. Env., In review.

2017

Li, X., J. R. Mecikalski, and D. J. Posselt, 2017: An ice-phase microphysics forward model and preliminary results of polarimetric radar data assimilation. Mon. Wea. Rev., 145, 683–708.

2016

Mecikalski, J. R., C. P. Jewett, J. M. Apke, and L. D. Carey, 2016: Analysis of cumulus cloud updrafts as observed with 1–min resolution super rapid scan GOES imagery. Mon. Wea. Rev., 144, 811–830.

Mecikalski, J. R., D. Rosenfeld, and A. Manzato, 2016: A conceptual model for 1–2 hour nowcasts of storm intensity using geostationary satellite observations. J. Geophys. Res. Atmos., 121, 6374–6392.

Mecikalski, J. R., B. Shoemaker, Q. Wu, M. A. Holmes, S. J. Paech, and D. M. Sumner, 2016: A 20-yar high-resolution GOES solar insolation – evapotranspiration dataset for water resource management over the state of Florida, J. Amer. Water Res. Assoc., In review.

Apke, J. M., J. R. Mecikalski, and C. P. Jewett, 2016: Analysis of mesoscale atmospheric flows above mature deep convection using super rapid scan geostationary satellite data. J. Appl. Meteor. Climatol., 55, 1859–1887.

Gravelle, C. M., J. R. Mecikalski, K. M. Bedka, W. E. Line, R. A. Petersen, J. M. Sieglaff, G. T. Stano, and S. J. Goodman, 2016: Using GOES-R demonstration products to “bridge the gap” between severe weather watches and warnings: An example for the 20 May 2013 Moore, OK tornado outbreak. Bull. Amer. Meteorol. Soc., 97, 69–84.

2015

Mecikalski, J. R., J. K. Williams, C. P. Jewett, D. Ahijevych, A. LeRoy, and J. R. Walker, 2015: Optimizing use of geostationary satellite observations and the development of probabilistic 0–1 hour convective initiation nowcasts. J. Climat. Appl. Meteorol., 54, 1039-1059.

Gravelle, C. M., J. R. Mecikalski, K. M. Bedka, W. E. Line, R. A. Petersen, J. M. Sieglaff, G. T. Stano, and S. J. Goodman, 2015: Using GOES-R demonstration products to “bridge the gap” between severe weather watches and warnings: An example for the 20 May 2013 Moore, OK tornado outbreak. Bull. Amer. Meteorol. Soc., 97, 69–84.

Posselt, D. J., X. Li, S. A. Tushaus, and J. R. Mecikalski, 2015: Assimilation of dual-polarization radar observations in mixed- and ice- phase regions of convective storms: Information content and forward model error. Mon. Wea. Rev., 143, 2611-2635.

Teegavarapu, R. S. V., C. S. Pathak, J. R. Mecikalski, and J. Srikishen, 2015: Optimal solar radiation sensor network design using spatial and geostatistical analyses. J. Spatial Sci., doi:10.1080/14498596.2015.1051147.

 

2014

Matthee, R., J. R. Mecikalski, L. D. Carey, and P. M. Bitzer, 2014: Quantitative differences between lightning and non-lightning convective rainfall events as observed with polarimetric radar and MSG satellite data. Mon. Wea. Rev., 142, 3651–3665.

Vant-Hull, B., Mahani, S., Autones, F., Mecikalski, J.R. and Rabin, R. 2014: Infrared satellite rainfall monitoring: relationships between cloud towers, rainfall intensity, and lightning, Int. J. Water, 8, 343–367.

Harmsen, E. W., P. T. Cruz, and J. R. Mecikalski, 2014: Calibration of selected pyranometers and satellite derived solar radiation in Puerto Rico. Intl. J. Renew. Energy Tech., 5, 43–54.

Harmsen, E. W., J. R. Mecikalski, M. J. Cardona-Soto, A. Rojas-Gonzalez, and R. E. Vasquez.Daily, 2014: Evapotranspiration Estimations Using Satellite Remote Sensing. In Evapotranspiration – Principals and Applications for Water Management, p. 503. M. R. Goyal and E. W. Harmsen, Eds., Apple Academic Press, Inc., ISBN: 978-1-926895-58-1.

Harmsen, E. W., J. Mecikalski, A. Mercado Vargas, and P. Tosado, 2014: Evapotranspiration Using Satellite Remote Sensing for the Tropical Climate. In Evapotranspiration – Principals and Applications for Water Management, p. 545. M. R. Goyal and E. W. Harmsen, Eds., Apple Academic Press, Inc., ISBN: 978-1-926895-58-1.

Vant-Hull, B., Mahani, S., Autones, F., Mecikalski, J.R. and Rabin, R. 2014: Infrared satellite rainfall monitoring: relationships between cloud towers, rainfall intensity, and lightning, Int. J. Water, In press.

Harmsen, E. W., P. T. Cruz, and J. R. Mecikalski, 2014: Calibration of selected pyranometers and satellite derived solar radiation in Puerto Rico. Int. J. Renewable Energy Technology, 5, 43-54.

2013:
Mecikalski, J. R., X. Li, L. D. Carey, E. W. McCaul, Jr., and T. A. Coleman, 2013: Regional comparison of GOES cloud-top properties and radar characteristics in advance of first-flash lightning initiation. Mon. Wea. Rev. 141, 55-74.

Mecikalski, J. R., P. Minnis, and R. Palikonda, 2013: Use of satellite derived cloud properties to quantify growing cumulus beneath cirrus clouds. Atmos. Res., 120-121, 192-201.

Li, X., and J. R. Mecikalski, 2013: Evaluation of sensitivity of the dual–polarization Doppler radar data assimilation to radar forward operator. J. Meteorol. Soc. Japan. 91, 287–304.

Mecikalski, J. R., and M. Koenig, 2013: Application of high–resolution visible sharpening of partly cloudy pixels in Meteosat Second Generation infrared imagery. Atmos. Res., 134 , 1–11.

Matthee, R., and J. R. Mecikalski, 2013: Geostationary infrared methods for detecting lightning–producing cumulonimbus clouds. J. Geophys. Res. Atmos., 118, doi:10.1002/ jgrd.50485.

Harmsen, E., P. T. Cruz, and J. R. Mecikalski, 2013: Technical Note: Calibration of selected pyranometers and satellite derived solar radiation in Puerto Rico. Intl. J. Renew. Energy Tech., In press.

Jewett, C. P., and J. R. Mecikalski, 2013: Adjusting thresholds of satellite-based convective initiation interest fields based on the cloud environment, J. Geophys. Res. Atmos., 118, 12,649–12,660.

Mishra, V., J. F. Cruise, J. R. Mecikalski, C. R. Hain, and M. C. Anderson, 2013: A remote-sensing driven tool for estimating crop stress and yields. Remote Sens. 5, 3331-3356.

2012

Anderson, M. C., et al., 2012: A New Way To Map Drought and Water Use Worldwide. Agricultural Research, February 2012, 4-7.

Mecikalski, J. R., 2012: Flying friendlier skies. Huntsville R & D Journal. Huntsville Times, Winter 2012. 18-20.

Botes, D, J. R. Mecikalski, and G. Jedlovec, 2012: Atmospheric InfraRed Sounder (AIRS) sounding and stability analysis of the pre-convective environment. Wea. Forecasting. J. Geophys. Res., 117, D09205.

Walker, J. R., W. M. MacKenzie, J. R. Mecikalski, and C. P. Jewett, 2012: An enhanced geostationary satellite-based convective initiation algorithm for 0–2 hour nowcasting with object tracking. J. Appl. Meteor. Climatol., 51, 1931-1949.

Hain, C. R., W. T. Crow, M. C. Anderson, and J. R. Mecikalski, 2012: An ensemble Kalman filter dual assimilation of thermal infrared and microwave satellite observations of soil moisture into the Noah land surface model. Water Resources Res., 48, W11517.

Cammalleri, C., M. C. Anderson, G. Ciraolo, G. D’Urso, W. P. Kustas, C. Hain, L. Schultz, and J. R. Mecikalski, 2012: Analysis of energy flux estimates over Italy using time-differencing models based on thermal remote sensing data. Remote Sens. Hydrol., Proc., IAHS Publ. 352, 124-127.

Li, X. and J. R. Mecikalski, 2012: Impact of the dual–polarization Doppler radar data on two convective storms with a warm–rain forward operator. Mon. Wea. Rev., 140, 2147-2167.

Asefi-Najafabady, S., K. Knupp, J. R. Mecikalski, and R. M. Welch, 2012: Radar observations of mesoscale circulations induced by a small lake under varying synoptic-scale flows. J. Geophys. Res., 117, D01106.

Anderson, W. B., B. F. Zaitchik, C. R. Hain, M. C. Anderson, M. T. Yilmaz, J. Mecikalski, and L. Schultz, 2012: Towards an integrated soil moisture drought monitor for East Africa. Hydrol. Earth Syst. Sci., 16, 2893-2913.

2011
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. Earth Syst. Sci., 15, 223-239.

2010

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.

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.

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. J. Geophys. Res. Finalized.

2009
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. Forecasting, 24, 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.

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.

2008
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.

2007
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.

2006
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.

2005
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. Hydrometeor. 6, 460-475.

2004
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., 2004: COVER: Bulletin of the American Meteorological Society, "ALEXI Latent Heat Flux over IHOP: 31 May 2002". 84.

2003
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.

Norman, J. M., M. C. Anderson, W. P. Kustas, A. N. French, J. Mecikalski, R. Torn, G. R Diak, T. J Schmugge, and B. C. W. Tanner, 2003: Remote sensing of surface energy fluxes at 101-m pixel resolutions. Water Resour. Res., 39, 1221.

2002
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.

2001
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 Sensing, 39, 1719-1728.

2000
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.

1989-1999
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.