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DRAFT

 

 

NASA Applied Sciences Program

FY 2010 (Aviation) Weather Applications Plan

 

 

 

 

 

 

 

 

 

 

July 16, 2009

 

 

John A. Haynes, Program Manager

John J. Murray, Deputy Program Manager

 


Introduction

 

NASA Strategic Goals for Fiscal Year 2010. NASA Strategic Goal 3A is to “Study Earth from space to advance scientific understanding and meet societal needs. This goal comprises technical and programmatic outcomes, two of which apply fully to the weather element. Outcome 3A2 is to demonstrate “Progress in enabling improved predictive capability for weather and extreme weather events. Its related Annual Performance Goal for FY2010 (APG10ES4) is to “Demonstrate progress in enabling improved predictive capability for weather and extreme weather events”. This is the overarching technical metric for the weather element. The program continues to document that weather has consistently exceeded technical expectations since the inception of the Applied Sciences Program. Administratively, Outcome 3A7 which is to demonstrate “Progress in expanding and accelerating the realization of societal benefits from Earth system science” is the applicable metric. Again, the program’s weather applications area, through its extensive network of federal, university and private sector partners, continues to exceed expectations for this outcome. More specifically, three annual performance goals specified in the FY2010 NASA Strategic Goals apply. They are APG10ES14, to “Issue 12 reports with partnering organizations that validate using NASA research capabilities (e.g., observations and/or forecast products) could improve their operational decision support systems; APG10ES15, to “Increase the number of distinct users of NASA data and services; and APG10ES16, to “Maintain a high level of customer satisfaction, as measured by exceeding the most recently available federal government average rating of the Customer Satisfaction Index.

 

NASA Applied Science Program Strategic Goals. The NASA Applied Science Program plan states that “NASA’s Earth Science Division has a unique mandate to study our planet from space. Within the Earth Science Division, the Applied Sciences Program (ASP) leverages NASA’s in­vestment in Earth science to discover and dem­onstrate applications of international and national need for practical use in management and decision-making. The program currently manages competitively selected proj­ects across eight application areas: agriculture, air quality, weather, climate, public health, water resources, ecologi­cal forecasting, and disaster management.  

 

In 2007, the National Academy of Sciences issued a report entitled Earth Science and Applications from Space: National Imperatives for the Next Decade and Beyond. Commonly referred to as the “Decadal Survey” the report recommended “a renewal of the national commitment to a program of Earth observations in which attention to secur­ing practical benefits for humankind play an equal role with the quest to acquire new knowledge about the earth system”. Of the eight applications, the weather program element continues to provide contributions of superior quality and substantial quantity. These contributions are consistent with the overarching paradigm as excerpted above from the NASA Applied Science Program plan. They are all directly in consonance with NASA’s evolving strategic goals, planned outcomes and annual performance goals. Specifically, the Applied Sciences Strategic Goals and Objectives are as follows:

 

Strategic Goal #1, Global Sustainability: ASP will enhance the nation’s and world’s ability to confront to­day’s challenges as well as to forecast the impacts of and develop adaptation and mitigation strategies for climate and Earth system change.

• Objective 1.1: Discover, develop, and demonstrate applications of NASA Earth science data and tools that meet the needs of end-users, including resource managers and planners, policy makers, forecasters, and first responders.

• Objective 1.2: Increase the program’s focus on appli­cations for climate impact forecasting and adaptation at regional levels.

• Objective 1.3: Sponsor projects focusing across mul­tiple observations and areas of science to include the relationships among environmental factors in creating broad information tools.

•  Objective 1.4: Build and strengthen partnerships in government (federal, state, local, tribal), academia and the private sector to bring NASA Earth Science to bear on societal needs.

•  Objective 1.5: Participate in, and lead as appropriate, interagency and intergovernmental efforts to ensure alignment with national priorities and to communicate activities broadly.

 

Strategic Goal #2, National Needs: ASP will tailor projects to user and societal needs by diversifying its port­folio of projects, varying the size, duration, and risk/reward profile as appropriate to particular application areas.

• Objective 2.1: Establish clear project selection criteria for each solicitation that include factors such as (1) the potential social or economic benefit; (2) the level of user community participation; and (3) the unique NASA contribution to the intended results.

• Objective 2.2: Conduct joint solicitations with end-user organizations and the Earth science research com­munity to increase the rate of adoption of NASA-devel­oped applications.

• Objective 2.3: Support the creation of revolutionary applications, including those outside the current set of application areas, to address rapidly growing and changing needs.

• Objective 2.4: Establish mechanisms to build “com­munities of practice” or teams that will help identify the needs and promote the use of applications in particular areas. The teams will consist of end users, scientists, and mission planning experts to encompass the range of stakeholders.

• Objective 2.5: Establish Earth Science Application Collaboratives to focus on regional issues, such as those related to resource management and climate change.

 

Strategic Goal #3, Mission Definition and Utilization: ASP will facilitate the integration of applications needs into Earth science mission planning to ensure the nation realizes the full value of its investment and to accel­erate the utility of information to support decision-making.

Objective 3.1: Establish mechanisms to identify, engage, inform and solicit input from users of NASA Earth science data and tools.

• Objective 3.2: Sponsor the addition of applications representatives to mission science teams to promote collaboration and to ensure user needs are represented.

• Objective 3.3: Develop a process for incorporating user input into future mission planning in collaboration with the Earth Science Flight Program and the Re­search and Analysis Program.

• Objective 3.4: Accelerate the transition of science to applications by facilitating communication between the applications community and the basic research and flight mission communities.

• Objective 3.5: Assess and monitor society’s upcoming application needs over the duration of mission lifetimes.

 

Quarterly and annual reports for the recently completed and currently active projects administered by the weather element as well as the bibliography of 62 peer-reviewed journal articles listed in Appendix 1 of this report attest to the fact that weather has met and exceeded all applicable technical and administrative performance metrics.

 

Applied Science Program Implementation Strategies. The program employs four basic strategies to accomplish its goals and objectives. The weather applications area is implemented in a manner to optimize these strategies. The four basic strategies are:

 

Mission Applications Support will include sponsor­ship of applications representatives on mission science teams, as well as support to the NASA’s Earth Science Flight Program in engaging end users in the development process.

 

Feasibility Studies are short-term (1-2 year) projects that allow investigators to test new applications ideas and further develop end user partnerships. Solicitations for Feasibility Studies will be written broadly to provide opportunities for high-risk, high-gain projects, less mature application development, as well as projects that may not fall under the current set of application areas. Successful projects can be continued by proposing to Collaboratives or Decisions solicitations.

 

Decisions Projects are traditional 3-4 year projects that are conducted in collaboration with end-user partners and result in a demonstration of enhancement to their decision-making ability. The intended final outcome is continued use of the tools by the partners.

 

Joint Solicitations and management of projects will be utilized in two ways:

 

o   Joint solicitations will be conducted with other NASA programs, such as Earth Science Research and Analysis, to better engage the science community and to provide opportunities for investigators who fall into the “gap” between science and applications.

o   Joint solicitations will be conducted with end-user organizations, such as other agencies, state programs, or nongovernmental programs. These should both improve the incorporation of end-user needs into applied science projects and accelerate the transition from NASA to the end user.

 

 

Weather Applications Project Administration

 

The primary mechanism for administering weather applications is through the NASA ROSES solicitation program. Most years, the Applied Science Program’s Weather element typically selects from two to five research proposals for funding. This research is then implemented, monitored, coordinated and transitioned-to-operations through the Weather Element’s Advanced Satellite Aviation-weather Products (ASAP) Project. ASAP resides at the NASA Langley Research Center.

 

NASA Applied Science weather research priorities are primarily developed through close collaboration with the FAA Weather Office, the NOAA NWS Aviation Services branch, the DOD and others in a collective effort to support the development of the Next Generation Air Transportation System (NextGen). This is done through direct participation in the NextGen Weather Working Group and the NextGen Environmental Working Group. Coordination with the NextGen Weather Working Group includes direct support of the Working Group’s Environmental Information Team and its Weather Demonstration Team by the NASA program manager, the deputy program manager and affiliated researchers from the organizations supported by NASA Applied Sciences research grants. Coordination with the NextGen Environmental Working Group includes direct support of the Working Group’s Science Steering Committee as well as significant participation in the FAA Aviation Climate Change Research Initiative (ACCRI). The Weather Element also actively supports the Office of the Federal Coordinator for Meteorology (OFCM) Volcanic Ash Working Group and the OFCM Space Weather Working Group. All of these affiliations inform our research priorities.

 

The NASA Applied Sciences Program Weather Element conducts an annual review meeting each year to assess the progress of active research projects as well as their efficacy and applicability to NextGen. Particular emphasis is placed on the active participation of interagency partners and various research and operational centers of excellence (E.g. FAA AWRP, NOAA OS&T, NOAA NWS AvSB, NOAA ESRL GSD, NOAA NCEP SPWC, NOAA NESDIS, NOAA UW CIMSS, NCAR, MIT LL, etc.). The review also allows the program to identify research topics for upcoming ROSES solicitations and ASAP tasks. It also ensures that the program’s work is aligned with NextGen priorities and the related efforts of our federal partners. Particular emphasis is placed on identifying research where NASA is uniquely capable of providing data and/or research expertise. 

 

NASA Applied Science weather research proposals are subjected to objective peer-review and ranked for scientific merit and national priority by a panel of federal agency and academic subject matter experts. Final selection is made by an ad hoc committee convened by the NASA Science Mission Directorate. The program manager then administers 1-4 year research grants for the selected proposals in consonance with the period of performance outlined in the ROSES solicitation.

 

ASAP serves as the core project of the NASA Earth Science Division, Applied Sciences Program, Aviation Program Element. It is the vehicle by which all research is implemented. ASAP was established in 2002 as a partnership between the NASA Applied Sciences Program, The NASA Aviation Safety Program, the Federal Aviation Administration (FAA) Aviation Weather Research Program (AWRP), the NOAA National Weather Service (NWS) Aviation Services Branch and the broader aviation weather community. This ongoing partnership primarily entails the development or improvement of aviation weather products and information through the infusion of satellite data applications into aviation weather nowcast and forecast systems. Since 2003, the focus of these efforts has increasingly been aligned with the efforts of the interagency Joint Planning and Development Office (JPDO) to develop applications to support the Next Generation Air Transportation System (NextGen). For an in-depth overview of the ASAP Project, visit https://science.larc.nasa.gov/asap/index.html.

 

ASAP also conducts a number of directed research tasks in areas of legacy research where a substantial NASA investment exists or where unique NASA capabilities and data can fill critical gaps for NextGen. Another ASAP focus is the transition to operations of NASA Applied Sciences weather applications for NextGen. NASA Langley Research Center’s general support contract (STARSS, as of FY2007) supports ASAP through a number of sub-contracts at the NASA Langley Research Center, the University of Wisconsin Cooperative Institute for Meteorological Satellite Studies (CIMSS) and the University of Alabama-Huntsville (UAH) and with FAA Aviation Weather Research Program (AWRP) Product Development Teams (PDTs) at the National Center for Atmospheric Research (NCAR) Research Applications Laboratory (RAL) and other laboratories. ASAP has a direct program at MIT Lincoln Laboratory through Hanscom AFB.

 

Project Portfolio

 

 

a.      FY08-FY10 Active ROSES Portfolio and Budget

 

ROSES

Solicitation

Project Title

PI

PI Org

Budget

FY08

FY09

FY10

Dec.04*

Volcanic Cloud Data for NOAA, FAA, and USGS (OMI SO2 tools)

Kruger

UMBC

0

0

0

Dec.04*

CIT due to Thunderstorms

Sharman

NCAR

0

0

0

Dec.04*

Improvement of Operational  Aircraft Icing Forecasts

Minnis

LaRC

393

403

0

ROSES-05

Oceanic Convective Wx Diagnosis and Nowcasting

Kessinger

NCAR

250

0

0

ROSES-05

Solar Shield (Space Weather – surface propagation model)

Hesse

GSFC

314

328

0

ROSES-07

Satellite Data to Enhance FAA Forecasts of CI

Mecikalski

UAH

303

303

303

ROSES-07

Space Wx Nowcasting of AIR (Full physics propagation and human exposure model)

Mertens

LaRC

297

297

297

ROSES-07

Global Atmospheric Turbulence DSS for Aviation

Williams

NCAR

304

304

304

 

b.      FY09-FY12 Addendum to Active ROSES Portfolio and Budget

 

ROSES

Solicitation

Project Title

PI

PI Org

Budget

FY09

FY10

FY11

ROSES-08

Characteristics of oceanic storms for inclusion in aviation decision support systems

Kessinger

NCAR

110

0

0

ROSES-08

Merged Aqua/Terra MODIS and AMSR-E sea ice information for improved sea ice forecasts and ship routing.

Markus

NASA GSFC

109

0

0

ROSES-08

Application of A Train Satellite Observations to Enhance NWP Products for NextGen

Brown

NCAR

296

302

310*

ROSES-08

Improved Contrail and contrail cirrus formation and dissipation forecasts for climate change mitigation

Johnson

NCAR

79

31

0

ROSES-08

Satellite detection of high ice water content regions:  Exploration of a potential aviation hazard

Haggerty

NCAR

10

65

35

* FY12 - $265S for total 4 year grant of $1173K.

 

c.       FY09 – FY10 ASAP Portfolio.

 

Category

Task

Org(s)

Convection

Continue SATCAST integration into CoSPA, reduce execution time, add GOES-West processing, optimize use of satellite convective initiation (CI) indicators and evaluate alternative (object) tracking methods.

MIT LL, UAH, CIMSS

Convection

Evaluate UAH lightning initiation code for CoSPA

MIT LL, UAH

Turbulence

Refine and test climatologically-based MWT discriminators

NCAR, CIMSS

Turbulence

Refine the current fuzzy-logic based MWT algorithm developed under previous ASAP and FAA sponsored programs, using random forests artificial intelligence techniques to improve discrimination performance, with particular reference to severe turbulence events

NCAR, CIMSS

Turbulence

Continue the evaluation of satellite-based mountain wave discriminator for implementation into the FAA GTGN and GTGN products, which are scheduled to become part of the NextGen data cube for IOC (2013)

NCAR, CIMSS

† ASAP tasks extend to the end of each calendar year so that they can be updated soon after the annual program review meeting each fall.

 

 

 

 

 

FY09 – FY10 ASAP Portfolio* cont’d

 

Category

Task

Org(s)

Volcanic Ash

Provide polar and geostationary height assignment and cloud discrimination tools and expertise to NOAA NESDIS and FAA Ash-flow Team.

CIMSS

Volcanic Ash

Conduct Okmok, Kasatochi and Mt. Redoubt studies to validate UMBC OMI SO2 applications. Also compare height retrievals with Calipso lidar data

NASA LaRC, UMBC

Space Weather

Augment coverage of NAIRAS model PI to accelerate development of human exposure model for atmospheric ionizing radiation and share results with FAA, NOAA and AFRL.

NASA LaRC

NWP Enhancement

Accelerate assimilation testing of satellite-derived cloud properties for RUC and WRFRRC models

NASA LaRC, NOAA ESRL GSD

Environmental Impacts

Operate, maintain and conduct science for equipment installed at the NASA LaRC Air Quality Super Site

NASA LaRC

Climate

Assess the climate impact of contrails and cirrus with the goal of reducing the uncertainty of their contribution to climate assessment and prediction

NASA LaRC

General ASAP

Update 2006 National Polar-orbiting Operational Environmental Satellite System (NPOESS) Benchmark Report for Aviation Applications. add appendix on planned NASA Earth Observing Satellite applications

NASA LaRC, CIMSS, MIT LL, NCAR ,UAH

General ASAP

Consolidate oceanic convection and turbulence capabilities.

NASA LaRC, CIMSS, NCAR, UAH

General ASAP

Participate in NextGen Environmental Information Team planning activities, meetings telcons, etc.

NASA LaRC, CIMSS, NCAR, UAH

General ASAP

Participate in NextGen Demo Team planning activities, meetings telcons, etc.

NASA LaRC, CIMSS, NCAR, UAH

General ASAP

Conduct Annual Applied Sciences Weather Program Review meeting

NASA LaRC

General ASAP

Coordinate with NASA Aviation Safety Program IIFD Enabling Avionics Project. Support efforts related to their ice ingestion, forward-looking turbulence detection and other weather hazard research.

NASA LaRC

General ASAP

Coordinate with the FAA Weather Office’s Weather Technology In the Cockpit (WTIC) Project.

NASA LaRC

General ASAP

Participate in Office of the Federal Coordinator for Meteorology Working Groups.

NASA LaRC

General ASAP

Participate in the FAA Aviation Climate Change Research Initiative (ACCRI)

NASA LaRC

 

 

 

 

Appendix A

 

2007 – 2009 Applied Science Program Weather Applications Bibliography

 

 

Bani, P., C. Oppenheimer, V.I. Tsanev, S.A. Carn, S.J. Cronin, R. 

Crimp, J.A. Calkins, D. Charley, M. Lardy, and T.R. Roberts (2009). 

Surge in sulfur and halogen degassing from Ambrym volcano, Vanuatu, Bull. Volcanol., doi:10.1007/s00445-009-0293-7 (in press).

 

Bankert, R.L. and R.H. Wade, 2007: Optimization of an instance-based GOES cloud classification algorithm. Journal of Applied Meteorology and Climatology, 46, 36-49.

 

Bankert, R.L., C. Mitrescu, S.D. Miller, and R.H. Wade, 2009: Comparison of GOES cloud classification algorithms employing explicit and implicit physics.  J. Appl. Meteor. Clim., 48, 1411-1421.

 

Bou Karam, D., C. Flamant, P. Tulet, M. C. Todd, J. Pelon, and E. Williams (2009), Dry cyclogenesis and dust mobilization in the intertropical discontinuity of the West African Monsoon: A case study, J. Geophys. Res., 114, D05115, doi:10.1029/2008JD010952.

 

Bedka, K. M., J. Brunner, R. Dworak, W. Feltz, J. Otkin, and Thomas Greenwald, 2009. Objective Satellite-Based Overshooting Top Detection Using Infrared Window Channel Brightness Temperature Gradients, Accepted for publication, Journal of Applied Meteorology and Climatology.

 

Bedka, K. M., C. S. Velden, R. A. Petersen, W. F. Feltz, and J. R. Mecikalski, 2008: Comparisons of Satellite-Derived Atmospheric Motion Vectors, Rawinsondes, and NOAA Wind Profiler Observations, Accepted for publication by, J. Appl. Meteor and Clima.

 

Bedka, S. T.; Feltz, W. F.; Schreiner, A. J. and Holz, R. E.. Satellite-derived cloud top pressure product validation using aircraft-based cloud physics lidar data from the ATReC field campaign. International Journal of Remote Sensing, Volume 28, Issue 10, 2007, pp.2221-2239. Call Number: Reprint # 5409

 

Berendes, Todd A.; Mecikalski, John R.; MacKenzie, Wayne M. Jr.; Bedka, Kristopher M. and Nair, U. S.. Convective cloud identification and classification in daytime satellite imagery using deviation limited adaptive clustering. Journal of Geophysical Research, Volume 113, 2008, Doi.10:1029/2008JD010287, 2008. Call Number: Reprint # 5867

 

Bernstein, B., F. McDonough, M. Politovich, B. Brown, T. Ratvasky, D. Miller, C.A. Wolff, and G. Cunning, 2006: Current Icing Potential (CIP): Algorithm description and comparison with aircraft observations. J. Appl. Meteorol., 44, 969-986.

 

Brioude, J., O. R. Cooper, G. Feingold, M. Trainer, S. R. Freitas, D. Kowal, J. K. Ayers, E. Prins, P. Minnis, S. A. McKeen, G. J. Frost, and E.-Y. Hise, 2009: Effect of biomass burning on marine stratocumulus clouds off the California coast. Submitted to Atmos. Chem. Phys. 

 

Brunner, J.C., S.A. Ackerman, A.S. Bachmeier, and R.M. Rabin, 2007: A quantitative analysis of the enhanced-V feature in relation to severe weather. Wea. Forecasting, 22, 853-872.

 

Carn, S., N. Krotkov, K. Yang, R. Hoff, A. Prata, A. Krueger, S. Loughlin, and P. Levelt (2007). Extended observations of volcanic SO2 and sulfate aerosol in the stratosphere, Atmospheric Chemistry and Physics Discussions., 7, 2857-2871. 

 

Carn, S.A., N.A. Krotkov, A.J. Krueger, K. Yang, and P.F. Levelt (2007). Sulfur dioxide emissions from Peruvian copper smelters detected by the Ozone Monitoring Instrument, Geophys. Res. Lett. 34, L09801, doi:10.1029/2006GL029020.

 

Carn, S.A., A.J. Krueger, N.A. Krotkov, S. Arellano, and K. Yang (2008).  Daily monitoring of Ecuadorian volcanic degassing from space, J. Volcanol. Geotherm. Res., doi:10.1016/j.jvolgeores.2008.01.029.

 

 

Carn, S.A., A.J. Prata, and S. Karlsdóttir (2008). Circumpolar transport of a volcanic cloud from Hekla (Iceland). J. Geophys. Res., 113, D14311, doi:10.1029/2008JD009878.

 

Carn, S.A., A.J. Krueger, N.A. Krotkov, K. Yang, and K. Evans (2008).  Tracking volcanic sulfur dioxide clouds for aviation hazard mitigation.  Natural Hazards, doi:10.1007/s11069-008-9228-4.

 

Carn, S.A., A.J. Krueger, N.A. Krotkov, K. Yang, and K. Evans (2009). 

Tracking volcanic sulfur dioxide clouds for aviation hazard mitigation. Natural Hazards, doi:10.1007/s11069-008-9228-4 (in press).

 

Carn, S.A., J.S. Pallister, L. Lara, J.W. Ewert, S. Watt, A.J. Prata, R.J. Thomas, and G. Villarosa (2009). The unexpected awakening of Chaitén volcano, Chile, EOS Trans. AGU, 90(24), 205-206.

 

Clerbaux, C., P.-F. Coheur, L. Clarisse, J. Hadji-Lazaro, D. Hurtmans, S. Turquety, K. Bowman, H. Worden, and S. A. Carn (2008). Measurements of SO2 profiles in volcanic plumes from the NASA Tropospheric Emission Spectrometer (TES). Geophys. Res. Lett., 35, L22807, doi:

10.1029/2008GL035566.

 

Donovan, M., E. Williams, C. Kessinger, G. Blackburn, P. H. Herzegh, R. L. Bankert, S. D. Miller, and F. R. Mosher, 2008:  The identification and verification of hazardous convective cells over oceans using visible and infrared satellite observations. Journal of Applied Meteorology and Climatology, 47, 164-184.

 

Feltz, W. F.; Bedka, K. M.; Otkin, J. A.; Greenwald, T. and Ackerman, S. A., 2009. Understanding satellite-observed mountain-wave signatures using high-resolution numerical model data. Weather and Forecasting, Volume 24, Issue 1, 2009, pp.76-86. Call Number: Reprint # 6016

 

Frehlich, R. and R. Sharman: Climatology of Velocity and Temperature Turbulence Statistics Determined from Rawinsonde and ACARS Data.

Submitted to J. Appl. Meteor. Climatol.

 

Frehlich, R.  and R. Sharman, 2008:  The use of structure functions and spectra from numerical model output to determine effective model resolution.  Mon. Wea. Rev., 136, 1537-1553.

 

Gambill, L., and J. R. Mecikalski, 2009: A summertime convective cloud climatology over the Southeastern U.S.: Relationships to land cover and topography. Submitted. Mon. Wea. Rev.

 

Hong, G., P. Yang, P. Minnis, A. Dessler, Y. X. Hu, and G. North, 2008: Do contrails significantly reduce diurnal temperature range? Geophys. Res. Lett., 35, L23815, doi: 2008GL036108. 

 

Kärcher, B. U. Burkhardt, S. Unterstrasser, and P. Minnis, 2009: Factors controlling contrail cirrus optical depth. Submitted to Atmos. Chem. Phys. 

 

Krotkov, N.A., S.A. Carn, A.J.  Krueger, P.K. Bhartia, and K. Yang (2006), Band Residual Difference algorithm for retrieval of SO2 from the Aura Ozone Monitoring Instrument (OMI), IEEE Trans. Geosci. Remote Sensing, AURA Special Issue, 44(5), 1259-1266, doi:10.1109/TGRS.2005.861932.

 

Krotkov, N. A., B. McClure, R.R. Dickerson, S.A. Carn, C. Li, P.K. 

Bhartia, K. Yang, A.J. Krueger, Z. Li, P. Levelt, H. Chen, P. Wang, and D.R. Lu (2008), Validation of SO2 retrievals from the Ozone Monitoring Instrument (OMI) over NE China, J. Geophys. Res., 113, D16S40, doi:10.1029/2007JD008818.

 

Krueger, A., N. Krotkov, S. Carn, El Chichon: The genesis of volcanic sulfur dioxide monitoring from space, J. Volcanol. Geotherm. Res. (2008), http://dx.doi.org/10.1016/j.jvolgeores.2008.02.026 doi:10.1016/j.jvolgeores.2008.02.026 ; Journal of Volcanology and Geothermal Research, Volume 175, Issue 4, 20 August 2008, Pages 408-414

 

Lane, T. P. and R. D. Sharman, 2006:  Gravity wave breaking, secondary wave generation, and mixing above deep convection in a three-dimensional cloud model, Geophys. Res. Lett., 33, L23813, doi:10.1029/2006GL027988.

 

Lane, T. P., and R.D. Sharman, 2008: Some Influences of Background Flow Conditions on the Generation of Turbulence due to Gravity Wave Breaking above Deep Convection. J. Appl. Meteor. Climatol., 47, 2777–2796.

 

Lane, T. P., J. D. Doyle, R. D. Sharman, M. A. Shapiro, and C. D.

Watson: Statics and dynamics of aircraft encounters of turbulence over Greenland.  Accepted, to appear in Mon. Wea. Rev.

 

Lenz, A., 2008: Identification of Aviation Turbulence Signatures from Mesoscale Convective Features using Satellite Imagery.  UW-Madison Senior Undergraduate Thesis, Atmospheric Oceanic Sciences Department.

 

Lenz, A., K. Bedka, W. Feltz, and S. Ackerman, 2009:  Convectively-Induced Transverse Band Signatures in Satellite Imagery. Accepted for publication in J. of Weather and Forecasting.

 

Mackenzie, W. M., Mecikalski, J. R., and C. W. Siewert, 2009: Enhancements to 0-2 hour lightning initiation and nighttime convective initiation through use of the 3.9 µm channel on GOES. Submitted. J. Geophys. Res.

 

Martinsson, B.G., C.A.M. Brenninkmeijer, S.A. Carn, M. Hermann, K.-P. 

Heue, P.F.J. van Velthoven, and A. Zahn (2009). Influence of the 2008 Kasatochi volcanic eruption on sulfurous and carbonaceous aerosol constituents in the lower stratosphere. Geophys. Res. Lett., 36, L12813, doi:10.1029/2009GL038735.

 

McNutt, S.R. and E.R. Williams, Volcanic Lightning: Global observations and constraints on source mechanisms, Bulletin of Volcanology, (in review), 2008.

 

Mecikalski, J.R., and K.M. Bedka, 2006: Forecasting Convective Initiation by Monitoring the Evolution of Moving Cumulus in Daytime GOES Imagery. Mon. Wea. Rev., 134, 49–78.

 

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., W.F. Feltz, J.J. Murray, 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, Convection Initiation, In-Flight Icing, Turbulence, and Volcanic Ash. Bull. Amer. Meteor. Soc., 88, 1589–1607.

 

Mecikalski, John R.; Bedka, Kristopher M.; Paech, Simon J. and Litten, Leslie A.. A statistical evaluation of GOES cloud-top properties for nowcasting convective initiation. Monthly Weather Review, Volume 136, Issue 12, 2008, pp.4899-4914. Call Number: Reprint # 5926

 

Mecikalski, J. R., W. M. MacKenzie, Jr., M. Koenig, and S. A. Muller,

2009: Cloud-top Properties of Growing Cumulus prior to Convective Initiation as measured by Meteosat Second Generation. Part 1. Infrared fields. Submitted. J. Appl. Meteor. Clim.

 

Mecikalski, J. R., W. M. MacKenzie, Jr., and M. Koenig, 2009: Cloud-top Properties of Growing Cumulus prior to Convective Initiation as measured by Meteosat Second Generation. Part 2. Analysis of visible signatures.

Submitted. J. Appl. Meteor. Clim.

 

 

Minnis, P., J. Huang, B. Lin, Y. Yi, R. F. Arduini, T.-F. Fan, J. K. Ayers, and G. G. Mace, 2007: Ice cloud properties in ice-over-water cloud systems using TRMM VIRS and TMI data. J. Geophys. Res., 112, D06206, doi:10.1029/2006JD007626. 

 

Pavolonis, Michael J.; Feltz, Wayne F.; Heidinger, Andrew K. and Gallina, Gregory M.. A daytime complement to the reverse absorption technique for improved automated detection of volcanic ash. Journal of Atmospheric and Oceanic Technology, Volume 23, Issue 11, 2006, pp.1422-1444. Call Number: Reprint # 5242

 

Prata, A.J., S.A. Carn, A. Stohl, and J. Kerkmann (2007). Long range transport and fate of a stratospheric volcanic cloud from Soufriere Hills volcano, Montserrat, Atmos. Chem. Phys., 7, 5093-5103. (http://www.atmos-chem-phys.net/7/5093/2007/acp-7-5093-2007.html )

 

Prata, A.J., G.J.S. Bluth, C. Werner, V.J. Realmuto, S.A. Carn, and I.M. Watson (2009). Remote Sensing of Gas Emissions from Volcanoes, in Satellite Monitoring of Volcanoes: Spaceborne Images of the North Pacific, eds. K.G. Dean and J. Dehn (in press).

 

Sawyer, G.M., S.A. Carn, C. Oppenheimer, V.I. Tsanez, and M. Burton (2008). Investigation into magma degassing at Nyiragongo volcano, Democratic Republic of Congo. Geochem. Geophys. Geosyst., 9, Q02017, doi:10.1029/2007GC001829.

 

Siewert, C. W., M. Koenig, and J. R. Mecikalski, 2009: Application of Meteostat Second Generation data towards improving the nowcasting of convective initiation. Accepted. Meteorological Applications.

 

Smith, W. L., P. Minnis, H. Finney, R. Palikonda, and M. M. Khaiyer, 2008: An evaluation of operational GOES-derived single-layer cloud top heights with ARSCL over the ARM Southern Great Plains site. Geophys. Res. Lett., 35, L13820, doi:10.1029/2008GL034275. 

 

Thomas, H.E., I.M Watson, C. Kearney, S.A. Carn, and S.J. Murray (2009). A multi-sensor comparison of sulphur dioxide emissions from the 2005 eruption of Sierra Negra volcano, Galápagos Islands. Remote Sens. Environ., 113(6), 1331-1342, doi:10.1016/j.rse.2009.02.019.

 

Trier, S.B., and R. D. Sharman:  Convection-Permitting Simulations of the Environment Supporting Widespread Turbulence within the Upper-Level Outflow of an MCS.  Accepted, to appear in Mon. Wea. Rev.

 

Tupper, A., I. Itikarai, M. Richards, A.J. Prata, S.A. Carn, and D. 

Rosenfeld (2007). Facing the challenges of the International Airways Volcano Watch: the 2004/05 eruptions of Manam, Papua New Guinea, Weather and Forecasting 22(1), 175-191.

 

Uhlenbrock, N. L., K. M. Bedka, W. F. Feltz, and S. A. Ackerman, 2007: Mountain Wave Signatures in MODIS 6.7-μm Imagery and Their Relation to Pilot Reports of Turbulence. Wea. Forecasting, 22, 662–670.

 

Velden, Christopher S. and Bedka, Kristopher M.. Identifying the uncertainty in determining satellite-derived atmospheric motion vector height attribution. Journal of Applied Meteorology and Climatology, Volume 48, Issue 3, 2009, pp.450-463. Call Number: Reprint # 6017

 

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. In Press. J.

Geophys. Res.

 

Wolff, J. and R. Sharman, 2008: Climatology of upper-level turbulence over the continental Unites States.  J. Appl. Meteor. Climatol., 47, 2198-2214.

Xi, B., X. Dong, P. Minnis, and M. M. Khaiyer, 2009: A 10-year climatology of cloud cover and vertical distribution derived from both surface and GOES observations over the DOE ARM SGP site. Submitted to J. Geophys. Res. 

 

Yang, K., N. A. Krotkov, A. J. Krueger, S. A. Carn, P. K. Bhartia, and P. F. Levelt (2007), Retrieval of large volcanic SO2 columns from the Aura Ozone Monitoring Instrument: Comparison and limitations, J. Geophys. Res., 112, D24S43, doi:10.1029/2007JD008825.

 

Yang, K., X. Liu, N.A. Krotkov, A.J. Krueger and S.A. Carn (2009). 

Estimating the altitude of volcanic sulfur dioxide plumes from space- borne hyper-spectral UV measurements, Geophys. Res. Lett., 36, L10803, doi:10.1029/2009GL038025.

 

Yang, K., N.A. Krotkov, A.J. Krueger, S.A. Carn, P.K. Bhartia, and P.F Levelt (2009). Improving retrieval of volcanic sulfur dioxide from backscattered UV satellite observations. Geophys. Res. Lett., 36, L03102, doi:10.1029/2008GL036036.

 

Yang, P., G. Hong, A. E. Dessler, S. C. Ou, K.-N Liou, P. Minnis, and Harshvardan, 2009: Contrails and induced cirrus: Optics and radiation. Bull. Am. Meteorol. Soc., submitted.