Transitioning unique NASA data and research technologies to the NWS 1 Evaluation of WRF Using High-Resolution Soil Initial Conditions from the NASA Land.

Slides:

Advertisements

Similar presentations

Mei Xu, Jamie Wolff and Michelle Harrold National Center for Atmospheric Research (NCAR) Research Applications Laboratory (RAL) and Developmental Testbed.

Advertisements

SNPP VIIRS green vegetation fraction products and application in numerical weather prediction Zhangyan Jiang 1,2, Weizhong Zheng 3,4, Junchang Ju 1,2,

Implementation and test of HRLDAS in CWB

Transitioning unique NASA data and research technologies to operations GOES-R Proving Ground Activities at the NASA Short-term Prediction Research and.

An Intercomparison of Surface Observations and High-Resolution Forecasting Model Output for the Lake Okeechobee Region By Kathryn Shontz July 19, 2006.

Jordan Bell NASA SPoRT Summer Intern  Background  Goals of Project  Methodology  Analysis of Land Surface Model Results  Severe weather case.

Jared H. Bowden Saravanan Arunachalam

National Weather Service Houston/Galveston Lance Wood Science and Operations Officer Assessing the Impact of SPoRT Datasets Utilizing a local WRF.

Transitioning unique NASA data and research technologies to the NWS 1 AIRS Products for the National Weather Service Brad Zavodsky SPoRT Science Advisory.

Danielle M. Kozlowski NASA USRP Intern. Background Motivation Forecasting convective weather is a challenge for operational forecasters Current numerical.

Recent performance statistics for AMPS real-time forecasts Kevin W. Manning – National Center for Atmospheric Research NCAR Earth System Laboratory Mesoscale.

Brian Ancell, Cliff Mass, Gregory J. Hakim University of Washington

Transitioning unique NASA data and research technologies to the NWS 1 Evaluation of WRF Using High-Resolution Soil Initial Conditions from the NASA Land.

Christa D. Peters-Lidard Head, Hydrological Sciences Branch NASA Goddard Space Flight Center Workshop Objectives 1.Describe the LIS-WRF Coupled System.

Consortium Meeting June 3, Thanks Mike! Hit Rates.

Ensemble Post-Processing and it’s Potential Benefits for the Operational Forecaster Michael Erickson and Brian A. Colle School of Marine and Atmospheric.

CPC’s U.S. Seasonal Drought Outlook & Future Plans April 20, 2010 Brad Pugh, CPC.

Warm Season Precipitation Predictions over North America with the Eta Regional Climate Model Model Sensitivity to Initial Land States and Choice of Domain.

Real-time SPoRT LIS and Applications in Modeling and Situational Awareness Sixth Meeting of the Science Advisory Committee 28 February to 1 March 2012.

SPoRT SAC Nov 21-22, 2005 Earth-Sun System Division National Aeronautics and Space Administration The Short-term Prediction Research and Transition (SPoRT)

Applied Meteorology Unit 1 An Operational Configuration of the ARPS Data Analysis System to Initialize WRF in the NWS Environmental Modeling System 31.

The Eta Regional Climate Model: Model Development and Its Sensitivity in NAMAP Experiments to Gulf of California Sea Surface Temperature Treatment Rongqian.

An empirical formulation of soil ice fraction based on in situ observations Mark Decker, Xubin Zeng Department of Atmospheric Sciences, the University.

Earth Science Division National Aeronautics and Space Administration 18 January 2007 Paper 5A.4: Slide 1 American Meteorological Society 21 st Conference.

Introducing the Lokal-Modell LME at the German Weather Service Jan-Peter Schulz Deutscher Wetterdienst 27 th EWGLAM and 12 th SRNWP Meeting 2005.

SPoRT Real-time Vegetation Dataset and Impact on Land Surface and Numerical Models Sixth Meeting of the Science Advisory Committee 28 February to 1 March.

UMAC data callpage 1 of 11NLDAS EMC Operational Models North American Land Data Assimilation System (NLDAS) Michael Ek Land-Hydrology Team Leader Environmental.

Land Processes Group, NASA Marshall Space Flight Center, Huntsville, AL Response of Atmospheric Model Predictions at Different Grid Resolutions Maudood.

Oceanic and Atmospheric Modeling of the Big Bend Region Steven L. Morey, Dmitry S. Dukhovksoy, Donald Van Dyke, and Eric P. Chassignet Center for Ocean.

Session 2: Modeling and Data Assimilation Sixth Meeting of the Science Advisory Committee 28 February - 1 March, 2012 National Space Science and Technology.

Project Title: High Performance Simulation using NASA Model and Observation Products for the Study of Land Atmosphere Coupling and its Impact on Water.

Enhancing the Value of GRACE for Hydrology

NW NCNE SCSESW Rootzone: TOTAL PERCENTILEANOMALY Noah VEGETATION TYPE 2-meter Column Soil Moisture GR2/OSU LIS/Noah 01 May Climatology.

A Comparison of the Northern American Regional Reanalysis (NARR) to an Ensemble of Analyses Including CFSR Wesley Ebisuzaki 1, Fedor Mesinger 2, Li Zhang.

Mesoscale model support for the 2005 MDSS demonstration Paul Schultz NOAA/Earth System Research Laboratory Global Systems Division (formerly Forecast Systems.

1 Precipitation verification Precipitation verification is still in a testing stage due to the lack of station observation data in some regions

NCEP Production Suite Review: Land-Hydrology at NCEP

Applications of the Land Information System (LIS) Fifth Meeting of the Science Advisory Committee November, 2009 Jonathan Case transitioning unique.

Mission: Transition unique NASA and NOAA observations and research capabilities to the operational weather community to improve short-term weather forecasts.

AN ENHANCED SST COMPOSITE FOR WEATHER FORECASTING AND REGIONAL CLIMATE STUDIES Gary Jedlovec 1, Jorge Vazquez 2, and Ed Armstrong 2 1NASA/MSFC Earth Science.

Earth-Sun System Division National Aeronautics and Space Administration SPoRT SAC Nov 21-22, 2005 Regional Modeling using MODIS SST composites Prepared.

Ligia Bernardet 1*, E. Uhlhorn 2, S. Bao 1* & J. Cione 2 1 NOAA ESRL Global Systems Division, Boulder CO 2 NOAA AOML Hurricane Research Division, Miami.

NWS / SPoRT Coordination Call August 19, 2010 Topics: LIS, SST Composite, Technical Issues.

Identification of side-door/back-door cold fronts for fire weather forecasting applications Joseph J. Charney USDA Forest Service Northern Research Station,

Course Evaluation Closes June 8th.

3 rd Annual WRF Users Workshop Promote closer ties between research and operations Develop an advanced mesoscale forecast and assimilation system   Design.

A Portable Regional Weather and Climate Downscaling System Using GEOS-5, LIS-6, WRF, and the NASA Workflow Tool Eric M. Kemp 1,2 and W. M. Putman 1, J.

2006(-07)TAMDAR aircraft impact experiments for RUC humidity, temperature and wind forecasts Stan Benjamin, Bill Moninger, Tracy Lorraine Smith, Brian.

Towards development of a Regional Arctic Climate System Model --- Coupling WRF with the Variable Infiltration Capacity land model via a flux coupler Chunmei.

Implementation and preliminary test of the unified Noah LSM in WRF F. Chen, M. Tewari, W. Wang, J. Dudhia, NCAR K. Mitchell, M. Ek, NCEP G. Gayno, J. Wegiel,

High-Resolution SST Impacts on WRF Forecasts Fifth Meeting of the Science Advisory Committee November, 2009 Jonathan Case Kevin Fuell Scott Dembek.

Transitioning Unique NASA Data and Research Technologies to Operations The Utility of the Real-Time NASA Land Information System for Drought Monitoring.

Current and Future Initialization of WRF Land States at NCEP Ken Mitchell NCEP/EMC WRF Land Working Group Workshop 18 June 2003.

NOAA’s Climate Prediction Center & *Environmental Modeling Center Camp Springs, MD Impact of High-Frequency Variability of Soil Moisture on Seasonal.

Transitioning unique NASA data and research technologies to the NWS AIRS Profile Assimilation - Case Study results Shih-Hung Chou, Brad Zavodsky Gary Jedlovec,

Transitioning research data to the operational weather community Overview of GOES-R Proving Ground Activities at the Short-term Prediction Research and.

The lower boundary condition of the atmosphere, such as SST, soil moisture and snow cover often have a longer memory than weather itself. Land surface.

Entrainment Ratio, A R -  R = c p  i / c p  s  sfc  ent c p  i c p  s PBL Schemes  = YSU  = MYJ  = MRF 12Z 00Z  adv Science issue: Assess.

An Investigation of the Mesoscale Predictability over the Northeast U.S.        Brian A. Colle, Matthew Jones, and Joseph Olson Institute for Terrestrial.

The SPoRT-WRF: Transitioning SPoRT Modeling Research Sixth Meeting of the Science Advisory Committee 28 February – 1 March, 2012 National Space Science.

Incorporation and use of the NOAH LSM in the Coupled/Ocean Atmosphere Mesoscale Prediction System (COAMPS) ® Incorporation and use of the NOAH LSM in the.

Modeling and Evaluation of Antarctic Boundary Layer

Earth-Sun System Division National Aeronautics and Space Administration WRF and the coastal marine environment Kate LaCasse SOO/SPoRT Workshop 11 July.

August 6, 2001Presented to MIT/LL The LAPS “hot start” Initializing mesoscale forecast models with active cloud and precipitation processes Paul Schultz.

Performance Comparison of an Energy- Budget and the Temperature Index-Based (Snow-17) Snow Models at SNOTEL Stations Fan Lei, Victor Koren 2, Fekadu Moreda.

Satellite Data Assimilation Activities at CIMSS for FY2003 Robert M. Aune Advanced Satellite Products Team NOAA/NESDIS/ORA/ARAD Cooperative Institute for.

1 Xiaoyan Jiang, Guo-Yue Niu and Zong-Liang Yang The Jackson School of Geosciences The University of Texas at Austin 03/20/2007 Feedback between the atmosphere,

1 WRF Configuration for Ukraine  Input & boundary conditions from NCEP GFS model  3 day forecasts every 6 hours  10 km horizontal grid, 200x200 gridpoints.

2. WRF model configuration and initial conditions  Three sets of initial and lateral boundary conditions for Katrina are used, including the output from.

Integration of NCAR DART-EnKF to NCAR-ATEC multi-model, multi-physics and mutli- perturbantion ensemble-RTFDDA (E-4DWX) forecasting system Linlin Pan 1,

Presentation transcript:

transitioning unique NASA data and research technologies to the NWS 1 Evaluation of WRF Using High-Resolution Soil Initial Conditions from the NASA Land Information System SPoRT Science Advisory Committee, 13 June 2007 Presented by: Jonathan L. Case Relevance to SPoRT objectives Work done since joining SPoRT team Project overview –Hypothesis –Background on Land Information System (LIS) Experiment design Results –Land Information System vs. Eta comparison –Impacts on short-term numerical forecasts Summary / Future Work

transitioning unique NASA data and research technologies to the NWS 2 Relevance to SPoRT Program Objectives LIS work a natural extension of MODIS SST research Focus on 0  24 hour forecast problems Use of NASA systems and tools –Land Information System developed by NASA Goddard Space Flight Center (GSFC) –Software capable of incorporating EOS datasets derived from MODIS Fosters collaborations with external agencies –GSFC Hydrological Sciences Branch –NASA Center for Computational Sciences computing resources LIS capable of being transitioned to operations –NCEP/AFWA operations

transitioning unique NASA data and research technologies to the NWS 3 Activities Since Previous SAC Meeting Mr. Case joined SPoRT team in June 2006 New SPoRT project since previous SAC meeting Gained familiarization with the LIS software Conducted preliminary modeling experiments using LIS with the Weather Research and Forecasting (WRF) model Built collaborations between SPoRT and the Hydrological Sciences Branch at GSFC Presented conference paper at annual AMS meeting (2007)

transitioning unique NASA data and research technologies to the NWS 4 Project Overview Hypothesis: Can short-term mesoscale numerical forecasts of sensible weather elements be improved by using optimally-tuned, high-resolution soil fields? Project Goals: Investigate and evaluate the potential benefits of using high-resolution land surface data derived from NASA systems and tools on regional short-term numerical guidance (0  24 hours) –Use LIS software to initialize soil temperature and moisture in the WRF model –Examine one month period with relatively benign weather Isolate influence of land-atmosphere interactions May 2004 over Florida peninsula

transitioning unique NASA data and research technologies to the NWS 5 The Land Information System (LIS) Software that runs multiple Land Surface Models (LSMs) efficiently using high-performance computing –Developed by GSFC Noah –LSMs: Noah, Community Land Model, SiB, VIC, Mosaic –Global, high-resolution datasets (down to 1 km) User configurable features –“Spin-up” time for soil equilibrium –Input datasets –Atmospheric forcing data LIS has been coupled to the WRF model –Can run WRF using LIS LSMs and land datasets not available in the standard WRF

transitioning unique NASA data and research technologies to the NWS 6 Experiment Design LIS offline simulation using Noah LSM –Nested 9-km/3-km grid domain over SE U.S. –Simulation from 1 May 2002 to 1 June 2004 –Output every 12 hours during May 2004 to initialize WRF runs –Atmospheric forcing datasets North American Land Data Assimilation System (NLDAS; hourly, ~14 km) Global Data Assimilation System (GDAS; 6-hourly, ~52 km) GDAS used where NLDAS forcing is missing Compare regional WRF simulations with high-resolution LIS soil data to WRF runs with Eta model soil data –Calculate verification statistics at 80 surface stations –Plot fields to compare phenomenology differences

transitioning unique NASA data and research technologies to the NWS 7 Common characteristics –Nested grids: 9-km and 3-km spacing –Noah LSM –Daily 24-hour forecasts during May 2004 initialized at 0000 UTC and 1200 UTC –Atmospheric initial & boundary conditions from NCEP Eta model on 40-km grid Differences –Control WRF: Initial soil data from Eta model –LIS/WRF experiment: Initial soil data from 2+ year LIS run on exact WRF grids Control WRF and LIS/WRF Configuration 9-km 3-km

transitioning unique NASA data and research technologies to the NWS 8 Daily 0-10 cm initial soil moisture (%) (0000 UTC values during May 2004) Eta soil moisture LIS soil moisture Difference (LIS – Eta)

transitioning unique NASA data and research technologies to the NWS 9 Daily 0-10 cm initial soil moisture (%) (0000 UTC values during May 2004) Eta soil moisture LIS soil moisture Difference (LIS – Eta) LIS Substantially Drier Much more detail in LIS (as expected) LIS drier, especially over N. FL & S. GA LIS slightly more moist over Everglades

transitioning unique NASA data and research technologies to the NWS 10 Daily 0-10 cm initial soil temperature (°C) (0000 UTC values during May 2004) Eta soil temperature LIS soil temperature Difference (LIS – Eta) LIS systematically cooler over most of domain

transitioning unique NASA data and research technologies to the NWS cm initial soil moisture (%) (1200 UTC 6 May 2004) Eta soil moisture LIS soil moisture Difference (LIS – Eta)

transitioning unique NASA data and research technologies to the NWS 12 Sample Sea Breeze Evolution Differences (9-hour forecast valid 2100 UTC 6 May)

transitioning unique NASA data and research technologies to the NWS 13 Sample Sea Breeze Evolution Differences (10-hour forecast valid 2200 UTC 6 May)

transitioning unique NASA data and research technologies to the NWS 14 Sample Sea Breeze Evolution Differences (11-hour forecast valid 2300 UTC 6 May)

transitioning unique NASA data and research technologies to the NWS 15 Sample Sea Breeze Evolution Differences (12-hour forecast valid 0000 UTC 7 May)

transitioning unique NASA data and research technologies to the NWS 16 Sample Sea Breeze Evolution Differences (Meteogram plots at 40J and CTY)

transitioning unique NASA data and research technologies to the NWS 17 Verification Stats: 0000 UTC Cycle (29 80 surface stations) LIS/WRF runs reduced RMS errors by a few tenths of a degree over most forecast hours Nocturnal warm bias and daytime cold bias both improved Not much change in dewpoint verification stats LIS/WRF daytime dewpoints about 0.5°C lower than control WRF Wind Speed (not shown): LIS/WRF improved nocturnal high bias

transitioning unique NASA data and research technologies to the NWS 18 Summary / Preliminary Conclusions Configured and tested LIS/WRF on Florida case –Initial soil fields generated on exact WRF grids –LIS generated soil fields cooler and drier than Eta model Simulated atmosphere sensitive to changes in soil characteristics provided by LIS –Demonstrated positive improvement in sea-breeze prediction on 6 May –Improvements in diurnal prediction of 2-m temperatures during whole month (both 0000 and 1200 UTC forecast cycles)

transitioning unique NASA data and research technologies to the NWS 19 Proposed Future Activities with LIS/WRF Merge MODIS sea-surface temperatures with LIS soil data Study impacts of LIS soil data on convective initiation –Different regional domains & cases –Varying weather regimes (e.g. supercells vs. air-mass storms) New case study period over Tennessee Valley –Very warm March followed by killing freeze in early April 2007 –Use real-time MODIS greenness fraction products in LIS/WRF system Regional modeling ensembles –Summertime forecast sensitivity to soil initial condition perturbations –Run different LSMs within LIS/WRF for ensemble members Pathway to operational regional LIS/WRF runs

transitioning unique NASA data and research technologies to the NWS 20 Alabama Freeze Case: April 2007

transitioning unique NASA data and research technologies to the NWS 21 Alabama Freeze Case: April 2007 Proposal: Use real greenness fraction data in LIS/WRF simulations, derived from MODIS vegetation index composite products Measure impact on WRF forecasts compared to climo datasets

transitioning unique NASA data and research technologies to the NWS 22 Backup Slides

transitioning unique NASA data and research technologies to the NWS 23 Soil Moisture: Grid-Wide Stats; Land Points LIS is a few % drier than Eta model in volumetric soil moisture Variation about mean is very similar to Eta model soil moisture

transitioning unique NASA data and research technologies to the NWS 24 Soil Temp: Grid-Wide Stats; Land Points LIS 0-10 cm soil temperatures typically cooler than Eta at 00z LIS 0-10 cm soil temperatures about the same or slightly warmer at 12z LIS deeper soil temperatures consistently colder than Eta

transitioning unique NASA data and research technologies to the NWS 25 Sample Sea Breeze Evolution Differences (Forecasts from 1200 UTC 6 May Simulations)

transitioning unique NASA data and research technologies to the NWS 26 Verification Stats: 1200 UTC Cycle (Surface station 40J)

transitioning unique NASA data and research technologies to the NWS 27 Verification Stats: 1200 UTC Cycle (Surface station CTY)