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Fourth Southwest Hydrometeorology Symposium U. Arizona, Tucson, AZ, 20-21 September 2007. Ken Mitchell Rongqian Yang, Jesse Meng, Youlong Xia, Zoltan Toth, Dingchen Hou. NCEP Environmental Modeling Center. Collaborative Drought Monitoring and Seasonal Prediction in CPPA: Support to NIDIS. - PowerPoint PPT Presentation
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Ken MitchellRongqian Yang, Jesse Meng, Youlong Xia, Zoltan Toth, Dingchen Hou
NCEP Environmental Modeling Center
Fourth Southwest Hydrometeorology SymposiumU. Arizona, Tucson, AZ, 20-21 September 2007
Collaborative Drought Monitoring and Seasonal Prediction in CPPA: Support to NIDIS
Partnering CPPA PIs:Eric Wood – Princeton U.,
Dennis Lettenmaier – U. Washington , Brian Cosgrove – NASA/GSFC/HSB,
Kingtse Mo – NCEP/CPCHuug van den Dool – NCEP/CPC
Pedro Restrepo – NWS/OHD
CPPA Partners in this Effort:• Ken Mitchell: NCEP/EMC
– Youlong Xia, Helin Wei, Jesse Meng, Rongqian Yang• Eric Wood: Princeton U.
– Lifeng Luo, Justin Sheffield• Dennis Lettenmaier: U. Washington
– Andy Wood, Ted Bohn• Brian Cosgrove: NASA/GSFC Hydro Sci Branc Branch
– Christa Peters-Lidard, Chuck Alonge, Matt Rodell, S. Kumar• Kingtse Mo: NCEP/CPC
– Wanru Wu, Muthuvel Chelliah • Huug Van den Dool: NCEP/CPC
– Yun Fan• Pedro Restrepo: NWS/OHD
– John Schaake, DJ Seo• Zoltan Toth: NCEP/EMC
– Dingchen Hou
CPPA: Climate Prediction Program for the Americas(Predecessor programs: GCIP and GAPP)
CPPA Science Objectives:
• Improve the understanding and model simulation of ocean, atmosphere and land-surface processes
• Determine the predictability of climate variations on intra-seasonal to interannual time scale
• Advance NOAA’s operational climate forecasts, monitoring, and analysis systems
• Develop climate-based hydrologic forecasting capabilities and decision support tools for water resource applications.
PACS
Outline of This Presentation• CPPA: Climate Prediction Program for the Americas
– Seasonal forecast scale is current emphasis• Two strategic approaches (objective, reproducible, retrospective)
– Coupled prediction models (and their 4DDA/analysis)– Uncoupled prediction models (and their 4DDA/analysis)
• Coupled Monitoring & Prediction (coupled atmosphere-land)– Global Models & Analysis:
• GFS (NCEP Global Forecast System): medium-range• CFS ( NCEP Climate Forecast System): seasonal-range
– Regional Models & Analysis• NARR (North American Regional Reanalysis): with realtime extension• RCMs (Regional Climate Models)
• Uncoupled Monitoring & Prediction (land component only)– Motivation: Downscaling, bias correction, multiple models– National focus (but with global potential)– NLDAS: N. American Land Data Assimilation System
• Climate Test Bed: NCEP-NCPO Partnership– Achieve future upgrades and NOAA operations for all above
Two Strategic Approaches to Hydrologic Prediction:A) Coupled B) Uncoupled
Atmospheric Model(GCM or RCM)
Land Surface Model
River Routing Model
Runoff
Precipitation
Land Surface Models:Noah, VIC, Mosaic, SAC
Bias-correctedPrecipitationForecasts (ensemble)
Runoff
River Routing Model
Stream FlowStream Flow
Post Processor:Downscaling &Bias Correction)
precipitation
Post Processor Post processor
Final ProductsFinal Product
Fluxes
Both approaches should be executed in ensemble mode.
Drought Variables to Monitor and PredictOn several time scales: weeks to seasonal
(energy demand, agriculture, fire risk, water resource, river commerce)
• Precipitation anomalies– weeks, months, seasonal, annual
• Temperature anomalies– weeks, months, seasonal
• Humidity anomalies– weeks, months, seasonal
• Surface evaporation anomalies– weeks, months, seasonal
• Soil Moisture anomalies– months, seasonal, interannual– vertical profiles
• Snowpack anomalies– months, seasonal, interannual
• Runoff and stream/river discharge anomalies– months, seasonal, interannual– OHD emphasis
Shorter Time Scales
Longer Time Scales
Drought / HydrologicalAnalysis/Monitoring
• Coupled Reanalysis & Monitoring (NCEP: EMC & CPC)– NARR: N. American Regional Reanalysis (includes precip assimilation)
• 32-km, 3-hourly, Jan 1979 – present• Eta Data Assimilation System (EDAS) of 2001 is frozen and executed for 28 years
– GR-1: NCEP/NCAR Global Reanalysis 1• ~ 2.5 deg, 6-hourly, 1948-present
– GR-2: NCEP/DOE Global Reanalysis 2• ~2.5 deg, 6-hourly, 1979-present
– All 3 above have daily realtime extensions & frozen configurations– Other coupled global reanalysis (ECMWF, NASA, JMA)
• Uncoupled Land Reanalysis and Monitoring (“LDAS”)– By CPPA PI Partners– Uses observed precipitation analysis to force land surface– NLDAS: N. American Land Data Assimilation
• CONUS, usually 1/8th degree (U. Washington version covers Mexico)• 10-year, 28 year, and 50+ year versions• Multiple institutions with multiple land models
– NCEP/EMC, NCEP/CPC, NASA/GSFC, U. Washington Princeton U.)– GLDAS: Global Land Data Assimilation (NCEP, NASA/GSFC, USAF)
• NCEP: 1979 – present, about 1-deg resolution
(Note: Mostly NARR and NLDAS are featured in following frames on monitoring)
NLDAS: N. American Land Data Assimilation SystemEnsemble Monitoring Mode
NLDAS (top row): Plots of Root Zone Soil Moisture Anomalies09 April 2006
(shown as percentiles wrt 10-year NLDAS climatology: 1997-2006)
NLDAS – Noah LSM Output
NLDAS – Mosaic LSM Output
NDMC – Weekly Drought Monitor
CPC - Leaky Bucket LSM Output
NLDAS results above are:1) objective2) quantifiable3) reproducible (over decadal periods)4) can manifest short & long time scales -- e.g. different soil depths
Traditional Weekly U.S. Drought Monitorat right is subjective, not reproducible, andtends to reflect rather long time scales
Precipitation Anomaly (Monthly): Summer 07
d) P anom Aug 2007
June-July: -- Wet S-Plains -- Dry SE
August: -- Wet N-Plains -- Less dry SE
Weak Southwest monsoon
Next Four Frames from CPCNew Experimental Drought Monitor Page:
(PI Kingtse Mo)
http://www.cpc.ncep.noaa.gov/products/Drought/
Precipitation Anomaly (Weekly): Aug 071
2
3
4
5
August:
Erin (TS) 8/15 - 8/19 Dean (Cat. 5) 8/13 - 8/23 Felix (Cat. 5) 8/31 - 9/5
(From Climate Review)
Erin
Dean
Dean
Precipitation Anomalies at Long Time ScalesExp: Standard Precipitation Index (SPI) thru Aug 07
Total Column Soil Moisture Anomaly (mm): Aug 07
Ensemble Average of Left 4 Frames AUG 2007
NA (Coupled) NLDAS:
NLDAS: NLDAS:
(Uncoupled)
(Uncoupled) (Uncoupled)
Monthly Soil Moisture Trend:Change in soil moisture from Jul to Aug 07
August:
S-Plains – decrease
N-Plains – increase
SE – not much change
Monthly Total Column Soil Moisture Anomaly (Model by Model and 4-model Ensemble Mean)
Rerun of NCEP Realtime NLDAS for 10 Years
Noah Mosaic
SAC VIC
NLDAS:Multi-Model
Ensemble MeanAnomaly
July 2006:Large changesince last year
From NCEP Realtime NLDAS for 10 Years: soon extended to 28 years
NOAH
SAC
MOSAIC
VIC
EnsembleMean
March SWE Climatology (mm)
Drought / Hydrological
Prediction
• Medium-Range: Ensemble coupled GFS
– GEFS: Global Ensemble Forecast System
• about 60 GFS two-week forecasts run daily
GEFS Forecast – Precipitation
Verification 27Aug2007-02Sep2007
Week1 Forecast Made 26Aug2007
Week2 Forecast Made 19Aug2007
Large uncertainties over SE for week2 forecast, overlapping with large errors
GEFS Forecast – Soil MoistureWeek1 Forecast
Made 26Aug2007 Week2 Forecast
Made 19Aug2007 Verification
27Aug2007-02Sep2007
Errors corresponding to large uncertainties
Drought/Hydrological:Prediction
• Seasonal-Range: 2 methods– 1) Dynamical:
• Coupled: – Operational: Ensemble CFS (coupled Atmosphere/Ocean/Land model)
» GFS Atmosphere/Land model coupled to GFDL MOM3 Ocean Model
» about 60 CFS 9-month forecasts run each month» plus companion 22-year hindcast (1982-2003): 15 members executed from every month of 1982-2003
– Experimental: Regional Climate Models RCMs) forced by CFS» RCM seasonal forecast experiment now underway in CPPA
• Uncoupled (Princeton U. and U. Washington): – Princeton U.: CFS land surface forcing is downscaled and bias-corrected
and then used to force high-res uncoupled VIC land-only hydrology models
– U. Washington: CPC official tercile forecasts of precipitation and temperature are downscaled to force high-res uncoupled VIC land-only hydrology models
– 2) Empirical: e.g Ensemble Schaake Shuffle
CFS Seasonal SST Forecast Skill:Correlation of forecast with observed SST over 1982-1983
Example below for December initial conditions
More examples at: http://www.cpc.ncep.noaa.gov/products/people/wwang/cfs_skills/
CFS Seasonal Precip Forecast Skill over CONUS:Correlation of forecast with observed precip over 22-year hindcast
Example below for December initial conditions
More examples at: http://www.cpc.ncep.noaa.gov/products/people/wwang/cfs_skills/
Example CFS Forecast for El’Nino Event: Winter 1983 SST Anomaly (JFM avg)
Observed (with respect to 5-year 2000-2004 observed
climatology)
CFS Predicted(with respect to CFS 5-year 2000-2004 model
climatology)
Predicted JFM Precipitation anomaly for Winter 1983 ENSO Ops CFS versus Experimental Eta RCM versus Observed
(in terms of mean monthly precipitation: mm)
Observed
ETA RCM CFS
Poor
Better Better
Eta Regional Climate Model Experiments Configuration of Eta RCM shown in previous frame:1) model domain (shown at bottom)2) model resolution: 32-km, 45-levels
3) winter forecasts: JFM (initial conditions from mid-to-late Dec, forecasts to end March)4) 7 members of Eta RCM and CFS forecasts for each winter of 1983, 2000-2004
5) 2000-2004: used to derive 5-year Eta RCM and CFS forecast climatology6) 1983: Eta RCM and CFS forecasts depicted as anomalies from 2000-2004 model
Remaining Frames areExamples of Uncoupled
Seasonal Prediction Approaches
The emphasis is on downscaling to higher resolution and correction of bias in coupled models precipitation forecasts before applying to multiple high-resolutionland surface models.
NLDAS: Uncoupled Prediction Mode
U. Washingtonfor Westside
Princeton U.for Eastside
2006
West-Wide(U. Washington)
East-Wide (Princeton U.)
U. Washington (UW) West-Wide and Princeton U. East-Wide Seasonal Forecast Systems
Princeton East-Wide Link: http://hydrology.princeton.edu/~luo/research/FORECAST/project.phpUW West-Wide Link: http://www.hydro.washington.edu/forecast/westwide
Streamflow Forecast Details for UWWest-Wide: An Example
Clicking the stream flow forecast map also accesses current basin-averaged conditionsObservation
Ensemble Mean
Uncertainty Range
Soil Moisture: 198805 Forecast(East-Wide System: An Example)
Lead time
Climatological Forecast
Observations
CFS-based Forecast
Multi-model Forecast(includes European models)
0
50
100
150
200
250
300
350
Late
nt H
eat F
lux
(W m
-2)
0 3 6 9 12 15 18 21 24LST
Bondville, IL
GFS_LH
GDAS_LH
GLDAS_LH
NARR_LH
NAM_LH
NDAS_LH
NLDAS_LH
OBS_LH-res
OBS_LH-ef
OBS_LH
0
50
100
150
200
250
300
350
Late
nt H
eat F
lux
(W m
-2)
0 3 6 9 12 15 18 21 24LST
Bondville, IL-2
GFS_LH
GDAS_LH
GLDAS_LH
NARR_LH
NAM_LH
NDAS_LH
NLDAS_LH
OBS_LH-res
OBS_LH-ef
OBS_LH
-50
0
50
100
Late
nt H
eat F
lux
(W m
-2)
0 3 6 9 12 15 18 21 24LST
Grassland, AZ
GFS_LH
GDAS_LH
GLDAS_LH
NARR_LH
NAM_LH
NDAS_LH
NLDAS_LH
OBS_LH-res
OBS_LH-ef
OBS_LH
0
50
100
150
200
250
Late
nt H
eat F
lux
(W m
-2)
0 3 6 9 12 15 18 21 24LST
Ft. Peck, MT
GFS_LH
GDAS_LH
GLDAS_LH
NARR_LH
NAM_LH
NDAS_LH
NLDAS_LH
OBS_LH-res
OBS_LH-ef
OBS_LH
0
50
100
150
200
250
300
350
Late
nt H
eat F
lux
(W m
-2)
0 3 6 9 12 15 18 21 24LST
Brookings, SD
GFS_LH
GDAS_LH
GLDAS_LH
NARR_LH
NAM_LH
NDAS_LH
NLDAS_LH
OBS_LH-res
OBS_LH-ef
OBS_LH
0
50
100
150
200
250
Late
nt H
eat F
lux
(W m
-2)
0 3 6 9 12 15 18 21 24LST
Black Hills, SD
GFS_LH
GDAS_LH
GLDAS_LH
NARR_LH
NAM_LH
NDAS_LH
NLDAS_LH
OBS_LH-res
OBS_LH-ef
OBS_LH
0
50
100
150
200
250
300
350
400
450
Late
nt H
eat F
lux
(W m
-2)
0 3 6 9 12 15 18 21 24LST
Columbia, MO
GFS_LH
GDAS_LH
GLDAS_LH
NARR_LH
NAM_LH
NDAS_LH
NLDAS_LH
OBS_LH-res
OBS_LH-ef
OBS_LH
0
50
100
150
200
250
300
350
400
450
Late
nt H
eat F
lux
(W m
-2)
0 3 6 9 12 15 18 21 24LST
Chestnut Ridge, TN
GFS_LH
GDAS_LH
GLDAS_LH
NARR_LH
NAM_LH
NDAS_LH
NLDAS_LH
OBS_LH-res
OBS_LH-ef
OBS_LH
0
50
100
150
200
250
300
350
400
450
Late
nt H
eat F
lux
(W m
-2)
0 3 6 9 12 15 18 21 24LST
Walker Branch, TN
GFS_LH
GDAS_LH
GLDAS_LH
NARR_LH
NAM_LH
NDAS_LH
NLDAS_LH
OBS_LH-res
OBS_LH-ef
OBS_LH
Modeled and Observed surface fluxes: at 9 ARL/ATDD sitesMonthly Mean Diurnal Cycle: May 2007
Conclusions• NCEP has developed and operationally implemented a
suite of coupled analysis and forecast systems applicable to hydrometeorological monitoring and prediction– Reanalysis: Global & Regional Reanalysis (realtime updates)– GEFS: Medium-Range Global Ensemble Forecast System– CFS: Seasonal-Range Climate Forecast System
• Under CPPA sponsorship, CPPA PIs are collaborating on developing and demonstrating new suites of uncoupled hydrometeorological monitoring & prediction systems– Downscaling Focus: plus bias-correction & multi land models– NLDAS monitoring mode (analysis and reanalysis)– NLDAS prediction mode
• Dynamical: forced with dynamical coupled global models• Empirical:
– RCMs: testing seasonal forecast skill of Regional Climate Models