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Natural Resource Assessment for the State of Maryland:Status and Potentials
Rachel T. Pinker
Department of Meteorology University of Maryland College Park, MD 20742
pinker@atmos.umd.edu
Maryland Climate Change WorkshopMaryland Climate Change Stakeholder GroupAugust 6, 2003, Computer and Space Sciences BldgCollege Park, MD
Outline
Goal: explore benefits to the State of Maryland Current research effort International and National context Status of activity Illustrations:
• Climate research• Agricultural applications• Net primary productivity• Environmental modeling Prospects
Research Focus Development and evaluation of remote inference method for radiative fluxes Use of results in climate research and environmental applications
Scientific rationaleo Global hydrological cycle, energy budget, and net primary productivity-driven by radiative fluxeso Required information for coupling atmospheric and surface hydrological processes and parametrizationso Evaluation of large scale NWP and climate models to improve climate change assessment
U.S. Global Change Research Program Priority: Climate and Hydrologic Systems
o the role of clouds in the radiation budget of the atmosphere; o oceanic circulation patterns and the redistribution
of energy within the oceans;o the fluxes of water and energy between the atmosphere, bio-sphere, and land and ocean surfaces;
o the quantitative links in the climate system, including feedbacks among atmosphere, ocean, cryosphere, land surface and biosphere; and o the influence of polar ice sheets and sea ice on climate and the hydrologic cycle.
National context of activityNational context of activity
Cooling
Cooling
Warming
Warming
Clouds
Aerosols
Water
Vapor
Precipitation
Evaporation
COMPONENTSCOMPONENTSRole of Energy and Water in ClimateRole of Energy and Water in Climate
International
GEWEX Cloud System
Satellite CloudClimatology Project
(ISCCP)
Studies (GCSS) GEWEX
Continental-ScaleHydrometeorology Projects
GCIP/GAPPBALTEX
GAME
LBA
MAGSGlobal
Global Runoff Data
Precipitation ClimatologyProject (GPCP)
Center (GRDC)
SurfaceRadiation Budget
Project (SRB)
Baseline SurfaceRadiation Network
(BSRN)
GEWEX
Water Vapor Project
(GVaP)
Land Surface Modeling / Data Projects
GLASS
*
*ISLSCP
GACP - Global Aerosol Climatology
Project
(PILPS/GSWP)
Biogeochemistry
International context of activity
International context of activity
Monthly Mean Shortwave Downward Flux (W/m**2) at 0.5 Degree Resolution for January 1992 Derived with the U of MD GEWEX/SRB Model using GOES, METEOSAT, and
GMS DX Observations
An EOF iteration approach was used to obtain homogeneous fluxes from inhomogeneous satellite observations
Model run currently at NASA LaRC at 10 resolutionGlobal scale capabilitiesGlobal scale capabilities
Version 2
C1 and C2
1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004
ISCCP(Clouds)
SRB(Radiation)
GVAP(Water Vapor)
ISCCP 2D1 and DX
GVAPNVAP
ISLSCP(Land-Surface)
Version 2 Version 1.1
*Hatched lines represent planned data sets
Initiative IIInitiative I
GACPGACP(Aerosols)
New Satellite Launches
III
GLOBAL DATA SETSGLOBAL DATA SETS
GPCP(Precipitation)
Contribute to item #2-Surface Radiation Budget (SRB) dataContribute to item #2-Surface Radiation Budget (SRB) data
Global Surface Radiative Fluxes in support of GEWEX Available for July 1983-December 2001
Click on figure to see loopClick on figure to see loop
Radiation budget in AMIP II GCMs
Major uncertainty shortwave budget:
Partitioning of absorption of solar radiation between surface and atmosphere
SW Absorption SurfaceMean=163 Wm-2
Stdev= 8.4 Wm-2
SW Absorption AtmosphereMean= 73 Wm-2
Stdev= 7.3 Wm-2
After Wild et al. (2003)After Wild et al. (2003)
AMIP II GCMS SURFACE SW DOWN
After Wild et al. (2003)After Wild et al. (2003)
168
204
187 188
150
160
170
180
190
200
210
Wm
-2
mri (min) cola (max) mean GEWEX satellite
mri (min)
cola (max)
mean
GEWEX satellite
AMIP II GCMS SURFACE SW DOWN
50
60
70
80
90
100
Wm
-2
cola (min.) mpi (max.) mean GEWEX satellite
cola (min.)
mpi (max.)
mean
GEWEX satellite
SW ABSORPTION ATMOSPHERE
140145150155160165170175180185190
Wm
-2
mri (min.) cola (max.) mean GEWEX satellite
Wild et al(1998)
Ohmura+Gilgen(1993)
mri (min.)
cola (max.)
mean
GEWEX satellite
Wild et al (1998)
Ohmura+ Gilgen(1993)
SW ABSORPTION SURFACE
GEWEX UMD results-15 year average GEWEX UMD results-15 year average
GEWEX Continental Scale International Project (GCIP) and GEWEX Americas Prediction Project (GAPP):
Surface Radiation Budget (SRB) Data
Produced at real time at NOAA at 0.5 deg; distributed by the U of MD at:http://www.atmos.umd.edu/~srb/
Used at over 100 institutionsParameters provided: surface short-wave and PAR (global and diffuse); TOP net; cloud amount; cloud optical depth; surface skin temp
Selected parameters
•Downwelling fluxes – SW, PAR (global and diffuse)•Upwelling fluxes- SW and PAR•Surface temperature and snow cover•Fractional cloud cover•TOA net SW fluxes •Cloud optical depth
Upper: Capabilities developed to produce fluxes at 1/8 deg
Lower: IGBP concept of surface processes
Upper: Capabilities developed to produce fluxes at 1/8 deg
Lower: IGBP concept of surface processes
Reprocessed “legacy” radiative fluxes in support of GCIP 1996-2000
GEWEX Continental-Scale International Project (GCIP)To account for calibration drifts and operational restrictions, data are being reprocessed (click for loop)To account for calibration drifts and operational restrictions, data are being reprocessed (click for loop)
Surface skin temperature from GOES satellitesNOAA operational product “Reprocessed” at 1/2 “Reprocessed” at 1/8
Comparison of fractional snow cover as derived from ”reprocessing” algorithm at two spatial resolutions with the IMS product and snow cover from Air Force as initially used operationally
Fractional snow cover as derived at UMD ”reprocessing” at two spatial resolutions, the IMS and the Air Force
Validation sites
Validation results
Radiation climate from satellite and observed
Satellites can reproduce the radiation climate characteristics at each grid pointSatellites can reproduce the radiation climate characteristics at each grid point
Examples of product evaluation and use follow:
1. Comparison against buoy observations off the Atlantic coast
2. of product against NCEP Eta model off the Pacific coast
3. Use in Land Data Assimilation schemes
4. Evaluation of product in the LDAS framework
Radiative fluxes from GOES, NCEP Eta model, and buoy off the Atlantic coast
Baumgartner and Anderson (1999) Baumgartner and Anderson (1999)
Comparison of GCIP/GAPP and NCEP shortwave fluxes at a location 200 km off the California coast (K. Edwards, private communication, 2003). Larger discrepancies in summer (green/yellow colors): due to missed clouds in the NCEP model.
Comparison of GCIP/GAPP and NCEP shortwave fluxes at a location 200 km off the California coast (K. Edwards, private communication, 2003). Larger discrepancies in summer (green/yellow colors): due to missed clouds in the NCEP model.
The Multi-Institution North American
Land Data Assimilation System Project: (N-LDAS)
Ken MitchellNCEP Environmental Modeling Center
Mississippi River Climate & Hydrology Conference15 May 2002
P. Houser, E. Wood., A. Robock, J. Schaake, D. Lettenmaier, D. Lohmann, B. Cosgrove, J. Sheffield, L. Luo, Q. Duan,
W. Higgins, R. Pinker , D. Tarpley, J. Meng
GAPP GCIP
U of Md GEWEX Continental Scale International Project (GCIP) and GEWEX Americas Prediction Project (GAPP):
Surface Radiation Budget (SRB) Data –Collaborative Effort with NCEP and NOAA to Support LDAS Activity and Others
LDAS Implementation
Forcing: (top two are non-model based)Precipitation: 24 hour gauges, NCEP/OH Stage IV gage/radar precipitationRadiation: NESDIS 0.5-degree hourly GOES solar insolationMeteorology: NCEP EDAS (Eta 4DDA) analysis (wind, temperature, pressure, humidity, downward longwave)
GOES shortwave radiation [W/m^2] 20011101 18Z Gauge / Stage IV precip [mm] 20011101 18Z
LDAS Forcing Validation 2001 08-11
Monthly mean diurnal
solar insolation intercomparison
GOESEDAS
AGRMETvs
SURFRADSURFRAD
Examples how product used in research related to:
1. Climate models2. Agricultural applications3. Meso-scale modeling4. Ocean modeling5. New research on land degradation
Comparison of spectral surface albedos and their impact on the general circulation model simulated
surface climateRoesch A, Wild M, Pinker R, Ohmura A
JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES
107 (D14): art. no. 4221 JUL 2002
It is shown that ignoring the spectral dependence of the surface albedo will affect the predicted climate. The study reveals substantial changes in the climate over northern Africa when modifying the surface albedo of the Sahara deserts. Detailed information is given how the European Center/Hamburg General Circulation Model (ECHAM4) can be extended to include surface boundary conditions for both the visible and near-infrared incoming radiation.
Solar radiation and evapotranspiration in northern Mexico estimated from remotely sensed measurements of cloudiness
Garatuza-Payan J, Pinker RT, Shuttleworth WJ, Watts CJHYDROLOGICAL SCIENCES JOURNAL-JOURNAL DES
SCIENCES HYDROLOGIQUES 46 (3): 465-478 JUN 2001
Impact of ingesting satellite-derived cloud cover into the Regional
Atmospheric Modeling System
Yucel I, Shuttleworth WJ, Pinker RT, Lu L, Sorooshian SMONTHLY WEATHER REVIEW
130 (3): 610-628 MAR 2002
This study investigates the extent to which assimilating high-resolution remotely sensed cloud cover into the Regional Atmospheric Modeling System (RAMS) provides an improved regional diagnosis of downward short- and long-wave surface radiation fluxes and precipitation.
The role of daily surface forcing in the upper ocean over the tropical Pacific: A
numerical studySui CH, Li XF, Rienecker MM, Lau KM,
Laszlo I, Pinker RTJOURNAL OF CLIMATE
16 (4): 756-766 FEB 2003 The impacts of high-frequency surface forcing in the upper ocean over the equatorial Pacific are investigated using a nonlinear reduced-gravity isopycnal ocean circulation model forced by daily and monthly mean forcing. The simulated sea surface temperature (SST) in the daily forcing experiment is colder than that in the monthly forcing experiment near the equator.
Modeling and monitoring the impact of land degradation on primary productivity in Southern Africa with remotely
sensed data (Konrad Wessels, Ph.D. candidate Geography)
Most basic ecosystem function -Net Primary Productivity (NPP)
Biologicalvariables
NDVI
LAI
Plant functionaltype
Climate variables
Temperature
VPD
Rainfall
FPAR
GPP
Ra
Satellite remote sensing
Soil moisture
LUE
NPP
GLObal Production Efficiency Model (GLO-PEM)
PAR
Estimated NPP for the coterminous United States using the GLO-PEM model (S. Prince, private communication)
Sensitivity of the SRB model to aerosol information:
Difference in shortwave clear sky surface downward flux between old and updated aerosol climatology
August climatology of aerosol optical depth, single scattering albedo and asymmetry parameter from AERONET, transport model and GADS
New developments on aerosol effects (H. Liu, grad student) New developments on aerosol effects (H. Liu, grad student)
Summary
from satellite observations at global and local scales forImportant environmental parameters are currently derived improved environmental modeling
These products have been and are continuously evaluated by numerous groups This information has already proven its utility in a wide range of scientific applications
Work continues on product improvements to meet the needs of the scientific community
From this effort, benefit can accrue to the State of Maryland
Where information on radiative fluxes can be used
Maryland Climate Change Stakeholder Dialogue
WORKING GROUPS
Electricity
assessment of natural resources
Residential, Commercial, Industry
inputs to hydrological models
Transportation and Land-Use
inputs for flood modeling
Agriculture, Forestry, and Waste
net primary productivity; forestry management
Team:
Dr. I. LaszloQ.-H. LiDr. Xu LiDr. W. MengDr. D. SunDr. B. Zhang
Graduate students:
Hiroko KatoFan LeiHongqing LiuMeng-Pai HungHengmao WangMargaret WonsickShankar Ganesh Subramanian
Selected Collaboration:
NASA Langley Research Center-GEWEX/SRB NOAA/NESDIS/NCEP-GCIP/SRB NASA GSFC -AERONET University of Arizona- SALSA
University of Chiba -ADEOS-II
CPTEC-INPE, Brazil- LBA University of Ilorin, Nigeria-EOS Department of Geography, UMD- NPP UMIACS, UMD- GLCF Department of Civil and Environmental Engineering, UMD - SNOW University of Salamanca, Spain -CLIMATE
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