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)