NAME PRIMER
NAME Homepage:
http://www.joss.ucar.edu/name
OUTLINE
1. PROGRAM RATIONALE AND OBJECTIVES
2. NAME 2004 FIELD CAMPAIGN
•
Field Observation Networks (Tiers I, II, III)
3. NAME MODELING AND DATA ASSIMILATION
•
Science Questions and Activities (Tiers I, II, III)
WHAT IS NAME?
NAME is an internationally coordinated, joint
CLIVAR – GEWEX process study aimed at
determining the sources and limits of
predictability of warm season precipitation
over North America.
RATIONALE FOR NAME
• Global and regional models do not accurately simulate or predict
warm season precipitation, especially in tropical / subtropical
land-ocean interaction regions.
• NAME seeks improved understanding of the key physical
processes that must be parameterized for improved simulations
and predictions with coupled models.
• A fundamental first step towards improved prediction is the clear
documentation of the major elements of the NAMS and their
variability within the context of the evolving O-A-L annual cycle.
ROLE OF LOW-LEVEL JETS
There are 2 important low-level jets that transport significant
moisture to the continent and that play an important role in the
diurnal cycle of precipitation.
ROLE OF THE LAND SURFACE
• The land surface has its strongest influence
during the warm season (continents are warm;
evaporation is large).
• The land surface has many memory mechanisms
(e.g. soil moisture, snow, vegetation) that may
influence monsoon variability.
ROLE OF OCEANIC FORCING OF
CONTINENTAL CLIMATE ANOMALIES
• Ocean memory components evolve slowly and
are to some degree predictable in their own right.
• Warm season correlations between SST and
continental precipitation are at least marginal.
• Motivates studies of remote-vs-local SST’s;
antecedent influences; influences of MJO,
ENSO,PDO.
NORTH AMERICAN MONSOON EXPERIMENT (NAME)
HYPOTHESIS
Topographic and
Sea-Land Influence
The NAMS provides a physical
basis for determining the degree of
predictability of warm season
precipitation over the region.
Intraseasonal
Variability
Boundary
Forcing?
YEAR (2000+)
Planning
Preparations
Data Collection
Principal Research
Data Management
00 01 02 03 04 05 06 07 08
--------------|
--------------|
- - - ----------------|
----------------------------------|
-----------------------------------------|
OBJECTIVES:
Better understanding and
simulation of:
• warm season convective
processes in complex terrain
(TIER I);
• intraseasonal variability of
the monsoon (TIER II);
• response of warm season
circulation and precipitation
to slowly varying boundary
conditions (SST, soil
moisture) (TIER III);
• monsoon evolution and
variability (TIER I, II, III).
NAME IMPLEMENTATION
• Empirical and modeling studies that carry
forward the joint PACS/GAPP Warm Season
Precipitation Initiative (2000 onward), and
initiate new elements.
• NAME Field Campaign (JJAS 2004)
including build-up, field, analysis and
modeling phases.
US CLIVAR PAN AMERICAN
PROCESS STUDY TIMELINES
NAME PROJECT STRUCTURE
Science
Working
Group
Project
Office
Program
Managemen
t
•NAME Forecast Operations Center
•NAME International Project Support Team
http://www.joss.ucar.edu/name
NAME FIELD OBSERVATIONS (JJAS 2004)
Enhanced
Precipitation
Gauge Network
R.V. Ron Brown
Radiosondes/PIBALS
Radar/Profiling/Radiosondes
NAME FIELD NETWORKS
(JJAS 2004)
Tier I Instrumentation
–
–
–
–
–
–
–
–
–
–
UHF wind profiler (1)
VISS (5) (SMN sounding+UHF-RASS profiler)
NCAR ISS (4) (UHF-RASS profiler+sounding +sfc)
SMN 5cm Doppler radars (4) (3 Enterprise; 1 Eriksson)
10cm Doppler-polarimetric radar (NCAR S-POL)
Ron Brown shipboard platform (VISS, 5cm Doppler radar, Sfc fluxes)
Mexican Research Vessels
Buoys (1 ASIS; ??)
NOAA/ETL shipboard flux system (on UNAM/PUMA)
Advanced Lightning Direction Finder (5)
–
–
–
Raingauges (100 event logging; 1600 simple)
Research Aircraft (NOAA P-3, NASA P-3B)
Soil Moisture Sensors
Tiers II and III Instrumentation
–
–
Radiosonde
PIBAL
Addressing NAME Oceanographic Science
Proposed Location of the R/V
Ron Brown During NAME IOP
 Instrumentation
• R/V Ron Brown (radar, surface fluxes)
• ASIS Buoy (central GOC)
•SST’S??
• Mexican Research Vessels
•Wind profilers?
 Objectives
• Surge origins
• Sources of moisture and transports
• Precipitation statistics including diurnal cycle
• Structure of southern end of GC LLJ
• Surface fluxes/Ocean coupling
Additional Observations:
-buoys in GOC
-ships of opportunity (Paco)
NAME FIELD OBSERVATIONS (Tiers I, II and III)
Bolded red – NSF Deployment Pool; bolded blue –other NSF support; black – NOAA OGP or NASA THP
Platform / Data
Integrated Sounding
Systems /S-POL Radar
Instrumentation and Tier
Sponsor - Status
PI's
R. Carbone (NCAR), R. Cifelli(CSU),
R. Johnson (CSU), M. Moncrieff
(NCAR), W. Petersen (UAH)
S. Rutledge (CSU)
4 Integrated Sounding
Systems; S-POL Doppler
Polarimetric radar;
Upgrade for 4 SMN 5-cm
Doppler radars; 6 UHF
profilers; RV Ron Brown(Tier I)
NCAR/ATD NSF Field Deployment –
NOAA/ETL and/or AL NOAA/OGP
- Proposed
C. Fairall (NOAA/ETL), K. Gage
(NOAA/AL), G. Kiladis (NOAA/AL)
Lightning Detectors
5 sites (Mexico)
8 sites (US) (Tier I, III)
NSF/Hydrology and
Physical Meteorology
Proposed
W. Petersen (UAH), P. Krider (UAZ),
S. Rutledge (CSU) , R. Blakeslee
(NASA), S. Goodman (NASA),
B. Maddox (UAZ)
Radiosondes (Mexico)
17 sites (up to 2x-4x daily)
(Tier I-III)
NOAA/OGP - Proposed
M. Cortez (SMN),
A. Douglas(Creighton) , M. Cortez SMN
Pilot Balloons
6 US sites / 25 Mexican sites
(Tiers I-II)
NOAA/OGP - Proposed
M. Douglas (NSSL)
NOAA P-3Aircraft
Doppler radar, dropsondes,
Flight level inst. (Tier I)
NOAA - Proposed
M. Douglas (NOAA), W. Cotton (CSU)
D. Jorgensen (NOAA),
Surface Observations
Network (Mexico)
SMN - N/A
N/A
Coop Raingauge Network
79 synoptic stations; 60
automated met stations; 12
radars; 17 radiosonde sites;
1600 simple gauges (Tier I-II)
NOAA/OGP - Proposed
Lobato/ Higgins
ASIS Buoys (Mexico)
1 site (central GOC) (Tier I)
CICESE - Funded
F. Torres (CICESE)
GPS (Suominet)
3 sites (NW Mexico) (Tier I)
NOAA/OGP - Proposed
A. Hahmann (UAZ) ,R. Kursinsky (UAZ)
C. Sosa (IMADES) , C. WattsIMADES
Hydrometeorology Network
(Mexico, AZ) ;
Soil Moisture Field
Campaign;
NASA P-3B Aircraft
Unified Geographic Network
(Terrain, Hydrography,
Landcover); Agromet stations;
soil moisture sensors (Walnut
Gulch,AZ, Hermosillo (Tier I)
90-100 event logging
raingauges- funded (OGP)
D. Gochis (NCAR), J. Shuttleworth UAZ,
C. Watts (IMADES), J. Garatuza ITSON,
T. Cavazos (CICESE)
D. Lettenmaier (UW), D. Lettenmaier
(UW), T. Jackson
SMN Radars
Profilers, Soundings
Ship (see detail below)
NASA THP
NAME Tier-1 Scientific Questions
1.
2.
3.
5.
How are low-level circulations along the Gulf of California / west
slopes of the Sierra Madre Occidental related to the diurnal cycle of
moisture and convection? (low-level circulation)
What is the relationship between moisture transport and rainfall
variability (e.g. forcing of surge events; onset of monsoon details)?
(moisture transport and budget)
What is the typical life cycle of diurnal convective rainfall? Where
along the western slope of the Sierra Madre Occidental is convective
development preferred? (diurnal cycle)
What are the fluxes of water (and energy) from the land surface to
the atmosphere across the monsoon region, and how do these fluxes
evolve in time during the warm season? (role of land surface)
(see other questions in the NAME
Science and Implementation Plan)
NAME Tier-2 Scientific Questions
1.
2.
3.
4.
What is the nature of the relationship between the MJO, tropical
cyclone activity and monsoon precipitation? (role of MJO)
How important are interactions between tropical easterly waves and
mid-latitude westerly waves in the prediction of monsoon
precipitation? (dynamical linkages)
What is the physical setting for the bimodal distribution (i.e. wetdry-wet) in warm season precipitation over Mexico and Central
America and what factors influence its interannual variability?
(double peak structure)
What are the dominant sources of precipitable moisture for monsoon
precipitation over southwestern North America? (moisture sources,
GOC-vs-GOM)
(see other questions in the NAME
Science and Implementation Plan)
NAME Tier-3 Scientific Questions
1.
2.
3.
4.
What are the relative roles of local (e.g. Gulf of California) and
remote (e.g. tropical Pacific) SST’s on the predictability of the
NAMS? (role of SST’s, simultaneous and antecedent)
Can numerical models reproduce the observed summer precipitation
in average years and years with ENSO influence? (role of ENSO)
What are the influences of the core monsoon region on the larger
scales (e.g. relationship between precipitation variability in the SW
and Great Plains)? (dynamical linkages)
What are the relationships between extreme weather events (e.g.
floods, droughts, heat waves, hurricanes), climate variability and
long-term trends? (extreme events).
(see other questions in the NAME
Science and Implementation Plan)
THE NAME MODELING –OBSERVATIONS TEAM
Charge:
•
Provide guidance on needs and priorities for NAME 2004 field
observations.
“NAMAP” – 6 modeling groups; 1990 monsoon, global and regional
models
•
Identify the path to improved warm season precipitation prediction:
“White Paper” - NAME Modeling and Data Assimilation R&D
“NAME Modeling Workshop (College Park, MD, June 6th) ”
•
Identify additional process studies necessary to reduce uncertainties
in coupled models.
MODEL DEVELOPMENT IN NAME
Premise:
•
The leading factors that limit precipitation forecast skill in both
global and regional models during the warm season are deficiencies
in how we model “local” processes that modulate deep convection.
•
In order to achieve the desired improvements, NAME will focus on
the diurnal cycle of convection in the core monsoon region of NW
Mexico, a region of complex terrain and land/sea contrasts.
•
NAME 2004 will provide improved estimates of the 3-d structure of
the monsoon and its variability on diurnal to monthly time scales.
ROLE OF NAME 2004 OBSERVATIONS IN
MODEL DEVELOPMENT
The NAME modeling strategy recognizes three distinct roles that
observations play in model development:
(1) To guide model development by providing constraints on model
simulations at the process level (e.g. convection, land/atm and
ocean/atm interactions);
(2) To help assess the veracity of model simulations of the various key
NAMS phenomena (e.g. low level jets, land/sea breezes, tropical
storms) and the linkages to regional / larger-scale climate variability;
(3) To provide initial and boundary conditions, and
verification data, for model predictions.
NAME IN VAMOS
VAMOS
PANEL
PROCESS
STUDIES
NAME
MESA
VOCAL
VAMOS
MODELING
GROUP
NAME MODELING AND OTHER MODELING
ACTIVITIES
Linkages:
• What modeling groups do we link to?
GEWEX
•
•
•
GLDAS
GLASS
CEOP
CLIVAR
•
•
•
WGSIP
NSIP
Other groups doing ENSO predictability
DATA ASSIMILATION AND ANALYSIS
Linking the Tiers
Objectives:
1) To better understand and simulate the various components of the
NAMS including:
* moisture surge – precipitation relationships;
* tropical easterly wave – midlatitude (westerly) wave relationships;
* components of the moisture budget and sources of moisture;
* basic seasonal evolution (life cycle) of the monsoon.
2) To quantify the impact of the NAME 2004 observations;
3) To identify model errors and attribute them to the underlying
model deficiencies.
PREDICTABILITY AND FORECAST SKILL IN
GLOBAL MODELS
Objectives:
1) To examine the predictability of warm season precipitation over
the NAM region;
2) To quantify error growth due to model errors versus that due to
uncertainties in analyses and boundary conditions;
3) To assess the value of NAME observations for prediction;
4) To help define field campaigns to follow NAME 2004.
Key Questions (ultimately critical for climate prediction):
1) How is the life cycle of the monsoon related to the evolution of oceanic and
continental boundary conditions?
2) Can models reproduce the observed summertime precipitation in average years
and years with ENSO influence?
Models
On board: NSIPP, NCEP/GFS
Possible: GFDL, NCAR
NAME MODELING, DATA ASSIMILATION
AND PREDICTION TIMELINE
Expected Outcome (Objectives) of June 6 Meeting
* NAME “White Paper” roadmap for NAME Modeling, Data
Assimilation and Prediction R&D
- recommendations
* timeline of specific activities tied to specific individuals / groups
-recommendations for contacts not yet made
-develop linkages to other field campaigns in S.W. U.S. and
Mexico at this time (e.g. SALSA)
NAME MODELING AND DIAGNOSTIC STUDIES (Tiers I, II and III)
Activity
Focus
(and NAME Tiers)
Sponsor and Status
PI's
Cloud Resolving Models
Explicit convection; effect of
terrain; mesoscale aspects
of surges (Tier I)
Proposed
M. Moncrieff (NCAR)
North American Monsoon
Assessment Project
(NAMAP)
1990 Monsoon (Tiers I,II)
NOAA/OGP - Unfunded
D. Gutzler (UNM)
(6 modeling groups)
Moisture Budget of IntraAmericas Sea
Moisture Transport (Tier III)
NOAA/OGP – Funded
C. Zhang (RSMAS)
Moisture Budget of NAME
Moisture Transport /
Precipitation (Tiers I-III)
NOAA/OGP - Funded
W. Higgins (NOAA/CPC)
E. Yarosh (NOAA/CPC)
Daily Precipitation Analysis
(US_Mexico)
Monitoring and Assessment of
floods / droughts (Tiers I- III)
NOAA/OGP - Funded
W. Higgins (NOAA/CPC)
W. Shi (NOAA/CPC)
Diurnal Cycle and
Precipitation
Linkage to TRMM/GPM
(Tiers I-III)
NOAA/OGP - Funded
P. Arkin (U. Md.)
Subseasonal Variability
Role of MJO/ Model
Uncertainties (Tier II)
NASA/IDS - Proposed
S. Schubert (NASA/GSFC)
Global / Regional Analyses
and NAME Data Impact
NCEP Analyses and Forecasts
With Eta Model and Eta Model
Data Assimilation System
(EDAS) (Tiers I-III)
Relationship of Precipitation
characteristics to streamflow
(Tier I)
NOAA/OGP - Proposed
K. Mo (NOAA/CPC)
W. Higgins (NOAA/CPC)
F. Meisenger (UCAR)
H. Berbery (U. Md)
D. Gochis (NCAR)
B. Njissen (UAZ)
WJ Shuttleworth (UAZ)
Extend the long term land
surface dataset retrospectively
from LDAS (Tiers I and II).
NOAA/OGP
Hydrological interpretation of
monthly to seasonal
precipitation forecasts
Assessment of land Surface
Hydrologic Predictability
NOAA/OGP
D. Lettenmaier (UW)
T. Cavazos-Perez (CISESE)
CLIVAR - NAME DELIVERABLES
• Climate models capable of predicting North American monsoon
variability out to seasons in advance;
• More comprehensive understanding of North American summer
climate variability and predictability;
• Infrastructure to observe and monitor the North American
monsoon system;
• Contributions to the assessment of climate variability and longterm climate change in the North American monsoon region;
• Strengthened multinational scientific collaboration across the
Americas.