Down-scaling with historical meteorological data
Integrative Questions
Land Cover Development of the most representative
cover for linking to the climate modelNet Primary Productivity -
Climate Simulations
• What are the key factors driving the
dynamics? What components of the
climate-land use system appear to be
tightly coupled and which loosely
coupled? Is there hidden order within
complexity that can be understood
and described?
• Are the feedbacks between land use
change and climate linear or non-
linear? What interactions appear to
have negative feedbacks? Positive
feedbacks?
• Are there tipping points that cause
one system to change state?
• What are the important spatial and
temporal scales of interactions? To
what degree does the climate
response lag behind land use change,
and vice versa? What are the
important measures to consider when
scaling up from case studies to the
region?
David J. Campbell, Jeffrey Andresen, Jennifer Olson, Jiajuo Qi, Nathan Moore, Gopal Alagarswamy, Dave Lusch – Dept. of Geography, MSU; Marianne Huebner – Dept. of Statistics & Probability, MSU; Bryan Pijanowski - Purdue University; Brent Lofgren and Tavares Ford – NOAA;
Declan Conway and Clair Hanson – Univ of East Anglia; Ruth Doherty – Univ of Edinburgh; Jean Palutikof – Hadley Centre; Joseph Maitima, Robin Reid, Philip Thornton, - International Livestock Research Institute;
Salome Misana and Pius Yanda – Univ. of Dar es Salaam; John Ng’ang’a – Univ. of Nairobi; Stephen Magezi – Met. Office, Uganda; Sam Mugisha – Makerere Univ.
CLIP Project202 Manly Miles BuildingMichigan State University
East Lansing, MI 48824, USAhttp://clip.msu.edu
Project Summary
An important question in global
change research is, what is the
impact of human’s use of the land
on the climate? Land use
conversions such as deforestation
and agricultural expansion alter soil
moisture, surface reflectance and
other land conditions that greatly
affect local and regional climates.
Similarly, changes in the climate,
such as rising temperatures and
rainfall variability, will impact
agriculture and other land uses,
leading to alterations in land use
patterns. These processes are
behind the project’s research
question: What is the magnitude
and nature of the interaction
between land use and climate
change at regional and local
scales?
This is being examined in East
Africa, which is undergoing
extremely rapid land use change
including expansion of cropping
into savannas, irrigation,
deforestation and urbanization. The
region straddles the equator and is
characterized by a heterogeneous
landscape from glaciated volcanoes
and montane forests, to coffee,
corn and banana farms, and wide
expanses of semi-arid savanna.
Institutions whose scientists are contributing expertise:
Biocomplexity in the Environment Dynamics of Coupled Natural and
Human Systems, Award #0308420
Climate–Land Interaction Project (CLIP) in East AfricaInterim Report: Examples of Recent Activities
Regional Climate Simulation
Inner and outer domain of the regional climate model
RAMS Ave. Temp., Jan. 19931st atm level (49 m)
Validating the model:RAMS vs. CRU gridded observations,
Jan 1993 average temperature.
Historical climate stations and synthetic weather series sites
Long-term seasonal rainfall anomalies, Embu & Makindu,
Kenya (1908-1990)
Simulation of naturalvegetation under different climate regimes, LPJ model
CLIMATE DYNAMICS
Regional Local
LAND COVERNPP SIMULATIONS
LAND USE CHANGE
Case Studies Models
Role Playing Simulation
Crops Rangeland
INTEGRATIVESpatial and temporal scales
Uncertainty analysisFeedbacks and tipping points
Systems paradigmsRemote Sensing
CaseStudies
Human Systems
Global Climate
CLIMATE DYNAMICS
Regional Local
LAND COVERNPP SIMULATIONS
LAND USE CHANGE
Case Studies Models
Role Playing Simulation
Crops Rangeland
INTEGRATIVESpatial and temporal scales
Uncertainty analysisFeedbacks and tipping points
Systems paradigmsRemote Sensing
CaseStudies
Human Systems
Global Climate
Land Use Change Projections1958: primarily grazing 1985
1995 2001: primarily crops
1958: primarily grazing 1985
1995 2001: primarily crops
Land use change case study analysisLower Embu (Mbeere), Kenya
Expert Systems Workshops; Role Playing SimulationsWhat will be the pattern of future land use?
How will people respond to climate & NPP changes?
Land surface paramaterization of the
climate model
Ground truthing with digital video from aircraft
“CLIP cover” Hybrid Africover-GLC2000
Phenological curves of Leaf Area Index from MODIS satellite imagery for the land cover, Open Shrubs and Woody Vegetation
0.00
0.25
0.50
0.75
1.00
0 2000 4000 6000
Yield (kg ha -1)
Cu
m. P
rob
abili
ty
Embu
Makindu
Simulated rainfed maize yields, Embu and Makindu, Kenya,
1926-1998
Expansion of Rainfed AgriculturePreliminary LTM Results
Expansion of Rainfed AgriculturePreliminary LTM Results
Areas in green are correctly predictedRed = LTM predicts rainfed but it doesn’t exist (over-predict)Yellow = LTM does not predict rainfed but it exists (under-predict)
Areas in green are correctly predictedRed = LTM predicts rainfed but it doesn’t exist (over-predict)Yellow = LTM does not predict rainfed but it exists (under-predict)
