Project Title: A Merged Atmospheric Water Data Set from the A-Train

Slides:

Advertisements

Similar presentations

Future Directions and Initiatives in the Use of Remote Sensing for Water Quality.

Advertisements

Extension and application of an AMSR global land parameter data record for ecosystem studies Jinyang Du, John S. Kimball, Lucas A. Jones, Youngwook Kim,

Communicating Uncertainties for Microwave-Based ESDRs Frank J. Wentz, Carl A. Mears, and Deborah K. Smith Remote Sensing Systems, Santa Rosa CA Supported.

Satellite SST Radiance Assimilation and SST Data Impacts James Cummings Naval Research Laboratory Monterey, CA Sea Surface Temperature Science.

Water in the Air When water drops form on a cold glass, the water comes from the air around the glass. Water vapor is water in the form of a gas. The amount.

Recent Progress on High Impact Weather Forecast with GOES ‐ R and Advanced IR Soundings Jun Li 1, Jinlong Li 1, Jing Zheng 1, Tim Schmit 2, and Hui Liu.

MISST FY1 team meeting April 5-6, Miami, FL NOAA: Gary Wick, Eric Bayler, Ken Casey, Andy Harris, Tim Mavor Navy: Bruce Mckenzie, Charlie Barron NASA:

ISCCP at 30, April 2013 Concurrent Study of a) 22 – year reanalysis and extension of global water vapor over both land and ocean (NVAP–M) and b) the matching.

MODIS Sea-Surface Temperatures for GHRSST-PP Robert H. Evans & Peter J. Minnett Otis Brown, Erica Key, Goshka Szczodrak, Kay Kilpatrick, Warner Baringer,

1._____process that forms clouds (water cycle 2) 2._____ process that adds heat and changes liquid water to water vapor (water cycle) 3._____what powers.

Clear sky Net Surface Radiative Fluxes over Rugged Terrain from Satellite Measurements Tianxing Wang Guangjian Yan

JCSDA Summer Colloquium Erica Dolinar 4 August 2015.

Modern Era Retrospective-analysis for Research and Applications: Introduction to NASA’s Modern Era Retrospective-analysis for Research and Applications:

NASA Snow and Ice Products NASA Remote Sensing Training Geo Latin America and Caribbean Water Cycle capacity Building Workshop Colombia, November 28-December.

ISCCP at 30, April 2013 Backup Slides. ISCCP at 30, April 2013 NVAP-M Climate Monthly Average TPW Animation Less data before 1993.

NACP A High-Resolution Daily Surface Weather Database for NACP Investigations Peter E. Thornton 1, Robert B. Cook 2, W. Mac Post 2, Bruce E. Wilson 2,

Science of the Aqua Mission By: Michael Banta ESS 5 th class Ms. Jakubowyc December 7, 2006.

Matt Rodell NASA GSFC Multi-Sensor Snow Data Assimilation Matt Rodell 1, Zhong-Liang Yang 2, Ben Zaitchik 3, Ed Kim 1, and Rolf Reichle 1 1 NASA Goddard.

AMSR-E Vapor and Cloud Validation Atmospheric Water Vapor –In Situ Data Radiosondes –Calibration differences between different radiosonde manufactures.

1._____process that forms clouds (water cycle 2) 2.____ layer of atmosphere that weather occurs in (atm layers) 3._____ process that adds heat and changes.

Earth Observing Satellites Update John Murray, NASA Langley Research Center NASA Aviation Weather Satellites Last Year NASA’s AURA satellite, the chemistry.

By: Kate Naumann And Colleen Simpkins. Aqua is a major international Earth Science satellite mission centered at NASA. It was launched on May 4, 2002.

A Study of Variability in Tropical Tropospheric Water Vapor Robert L. Herman 1, Robert F. Troy 2, Holger Voemel 3, Henry B. Selkirk 4, Susan S. Kulawik.

International GHRSST User Symposium Santa Rosa, California, USA 28-29th May 2009 MODIS Sea-Surface Temperatures Peter J Minnett & Robert H. Evans With.

© Crown copyright Met Office Vertical structure and diabatic processess of MJO: Initial results from the 2-day hindcasts Prince Xavier, Jon Petch N. Klingaman.

Principal Investigator: Eni G. Njoku

Atmospheric Heating.

Status and Outlook Evaluating CFSR Air-Sea Heat, Freshwater, and Momentum Fluxes in the context of the Global Energy and Freshwater Budgets PI: Lisan.

W. Smith, D. Spangenberg, S. Sun-Mack, P.Minnis

National Aeronautics and Space Administration

Characterizing Cloud and Convection Using the YOTC CloudSat-Centric,

WMO Space Programme Update

Ryan Kramer and Brian Soden University of Miami/RSMAS

Project Title: NEWS Science Integration Team PI: William B

NEWS linkages: (pull, push, collaborate, external)

Validation of Satellite-derived Lake Surface Temperatures

Model Uncertainties: IPCC GCMs

NEWS linkages: (pull, push, collaborate, external)

Principal Investigator: William Olson

Factors Affecting Evaporation

P. Minnis A. DelGenio Project Title: A Study of Arctic Radiation Budget using CERES/MODIS Satellite and.

Satellite-based data: ISCCP, GPCP.

The Carbon Cycle.

PI: R. Adler (NASA/GSFC) Co-I’s: G. Huffman, G. Gu, S.Curtis

Project title: An A-train Integrated Aerosol, Cloud, and Radiation Data Product Project Team: Seiji Kato Bruce A. Wielicki

Other data: ARM, CEOP, USGS and Global Runoff Data

Comparison of Satellite and Model-Based Heating Distributions

NEWS linkages: (pull, push, collaborate, external)

Project Title: The Sensitivity of the Global Water and Energy Cycles:

Oceanic Origin of the Precipitation Jump in the Sahel

Predictability and Model Verification of the Water and Energy Cycles:

Ice Cloud Generation by Mesoscale Convective Systems and Implications for Large-scale Heating Processes Robert Houze University of Washington As Ac CloudSat/CALIPSO.

TIMED SABER Data Enables Scientists to Derive a 70-year Time Series of the Thermosphere’s Infrared Energy Budget With its long, comprehensive dataset,

Assessment of NASA GISS CMIP5 and post-CMIP5 Simulated Clouds and Radiation fluxes Using Satellite Observations 1/15/2019 Ryan Stanfield(1), Xiquan Dong(1),

IPCC Model Uncertainty in Representing the

ICWG and Link to Other CGMS Working Groups

Satellite-based data: ISCCP, GPCP.

Project Title: Water and Energy Budget Study (WEBS)

Project Title: Oceanic Influence on Global Water/Energy Cycle

Get final-look Atlas/Ardizzone wind product.

Chapter 9 Section 1 What is the water cycle?

A Hydrologically-Consistent Multi-Satellite Climatology of Evaporation, Precipitation, and Water Vapor Transport Over the Oceans Project team: Frank Wentz.

Investigator: B. Lin Integrated satellite global energy data sets for climate analysis and modeling studies Investigator: B. Lin

PI: R. Adler (NASA/GSFC) Co-I’s: G. Huffman, G. Gu, S.Curtis

Atmospheric reanalysis at ECMWF

Integrated Satellite Global Energy Data for Climate Studies

Water and Energy Cycle Project Office (WECPO)

CURRENT Energy Budget Changes

Project Title: Water and Energy Budget Study (WEBS)

Presentation transcript:

Project Title: A Merged Atmospheric Water Data Set from the A-Train Project team: Eric Fetzer (Eric.J.Fetzer@jpl.nasa.gov) and JPL colleagues. Project status: Year 1 & 2 complete – Delivered two data sets to CREW. Team co-authored ~20 peer-reviewed papers. Year 3 (now) – Delivering data sets of 4 year duration. Analyzing Midwestern flood/drought in 2006-07. Continuing global intercomparisons of satellite observations. Year 4&5 -- Incorporate complete set of parameters in data sets. Publish North America flood/drought studies. Science issue: Advanced NASA satellite data sets will improve our understanding of energy and water cycle processes. Approach: Provide merged water vapor, cloud and temperature information from multiple, co-located satellite observations; share with NEWS and outside collaborators. Satellite-based data: AIRS, AMSR-E and MLS water vapor; AMSR-E, MODIS, MLS and CloudSat/CALIPSO clouds. Other data: None Models: None. Study Particulars: Post-May 2002 era. NEWS linkages: (pull, push, collaborate, external) Schlosser – Global water vapor budget using AIRS and AMSR-E. L’Ecuyer – Using high resolution data sets to improve radiative cooling rates. Lin -- Cloud liquid and ice water data for energy budget. Waliser -- Modeling and MJO studies. Planning collaborations on Midwestern flood/drought with several NEWS colleagues. Hui Su of JPL using our merged product. Major Result to go in lower left side: Figures should not be too complex or busy – this example is probably the limit of acceptable complexity. August 2005 mean water vapor from AIRS (left) and MLS (right) at 250 hPa, as observed solely by each instrument. Difference between the maps are indicative of sampling biases, one of several sources of discrepancy between the two satellite instruments’ water vapor data sets. Updated: November 1, 2007

How important are error estimates? Modern satellite data sets are observationally unbiased, and their sampling biases can be well characterized. Example: the difference between these two figures is the worst-case disagreement between MLS and AIRS UTWV. Would effort be better spent getting models to agree?