Vulnerability to near-term warming in the Sahel Laura Harrison UCSB Geography Climate Hazards Group Famine Early Warning System Network.

Slides:

Advertisements

Similar presentations

Topic: How Climate Affects Us

Advertisements

Economic Impacts of Climate Change

U.S. Department of the Interior U.S. Geological Survey February 29, 2012 – Washington, D.C. Detection and Monitoring of Agricultural Drought for Famine.

Dr. Christos Giannakopoulos Dr. Basil Psiloglou Meteorological and pollution factors affecting hospital admissions in Athens, Greece ENSEMBLES WP6.2 Meeting.

Title Trends in the start of the wet season over Africa Dom Kniveton 1 Russ Layberry 2 Charlie Williams 3 1 Department of Geography, University of Sussex,

Links Between Clear-sky Radiation, Water Vapour and the Hydrological Cycle Richard P. Allan 1, Viju O. John 2 1 Environmental Systems Science Centre, University.

Dr. Adriana-Cornelia Marica & Alexandru Daniel

Lecture 8 Climate Feedback Processes GEU Forcing, Response, and Sensitivity Consider a climate forcing (e.g., a change in TOA net radiation balance,

Global Precipitation Precipitation averages just about 1 meter per year over Earth but, like wealth, varies widely from place to place and from time to.

Improved CanSIPS Initialization from Offline CLASS Simulation and Data Assimilation Aaron Berg CanSISE Workshop.

R. Hudson - VFR Research Evapotranspiration. R. Hudson - VFR Research Evapotranspiration n Evaporation + Transpiration –Evaporation = change of state.

1/13/2003IRI Presentation E D C F E W S An empirical study of the links between NDVI and atmospheric variables in Africa with applications to forecasting.

Climate changes in Southern Africa; downscaling future (IPCC) projections Olivier Crespo Thanks to M. Tadross Climate Systems Analysis Group University.

OBJECTIVES Evaporation, precipitation and atmospheric heating ‘communicate’ SSTA to the atmosphere, driving changes in temperature, precipitation and.

CHG Station Climatology Database (CSCD)

Climate Change Impacts on the Water Cycle Emmanouil Anagnostou Department of Civil & Environmental Engineering Environmental Engineering Program UCONN.

Jordan Bell NASA SPoRT Summer Intern  Background  Goals of Project  Methodology  Analysis of Land Surface Model Results  Severe weather case.

Water Vapor and Cloud Feedbacks Dennis L. Hartmann in collaboration with Mark Zelinka Department of Atmospheric Sciences University of Washington PCC Summer.

1 Climate change and the cryosphere. 2 Outline Background, climatology & variability Role of snow in the global climate system Contemporary observations.

U.S. Department of the Interior U.S. Geological Survey NASA/USDA Workshop on Evapotranspiration April 6, 2011 – Silver Spring, Maryland ET for famine early.

We are developing a seasonal forecast system for agricultural drought early warning in sub- Saharan Africa and other food insecure locations around the.

Early warning Systems in Sudan Meteorological Authority Ahmed M Abdel Karim Sudan Meteorological Authority Crop and RAngeland Monitoring.

Some Approaches and Issues related to ISCCP-based Land Fluxes Eric F Wood Princeton University.

Princeton University Global Evaluation of a MODIS based Evapotranspiration Product Eric Wood Hongbo Su Matthew McCabe.

Outline Background, climatology & variability Role of snow in the global climate system Indicators of climate change Future projections & implications.

Chapter 3. Why the Earth has seasons  Earth revolves in elliptical path around sun every 365 days.  Earth rotates counterclockwise or eastward every.

Alan F. Hamlet Dennis P. Lettenmaier JISAO Center for Science in the Earth System Climate Impacts Group and Department of Civil and Environmental Engineering.

Impact of Sea Surface Temperature and Soil Moisture on Seasonal Rainfall Prediction over the Sahel Wassila M. Thiaw and Kingtse C. Mo Climate Prediction.

Impacts of Climate Change on Corn and Soybean Yields in China Jintao Xu With Xiaoguang Chen and Shuai Chen June 2014.

Making sure we can handle the extremes! Carolyn Olson, Ph.D. 90 th Annual Outlook Forum February 20-21, 2014.

SC SC Forms conclusions about how climate is determined by interactions of the atmosphere, hydrosphere, geosphere, and biosphere.

Are Exceptionally Cold Vermont Winters Returning? Dr. Jay Shafer July 1, 2015 Lyndon State College 1.

MICHELLE M. MOYER CORNELL UNIVERSITY NYSAES-GENEVA Use of pan evaporation and temperature data in Powdery Mildew forecasting.

Weather Temporary behavior of atmosphere (what’s going on at any certain time) Small geographic area Can change rapidly.

Northwest Geographic Area Coordination Center Predictive Services Spring and early Summer 2015 Climate and Significant Fire Potential Outlook Wednesday.

Distribution of Climate Regions

NERC Centre for Global Atmospheric Modelling Department of Meteorology, University of Reading The role of the land surface in the climate and variability.

Influence of the blended ship log book and station SLP data set on Mediterranean temperature & precipitation back to 1750 June Jürg Luterbacher.

Assessing Predictability of Seasonal Precipitation for May-June-July in Kazakhstan Tony Barnston, IRI, New York, US.

Objectives –climatology –climate –normal Vocabulary –tropics –temperate zone –polar zone Recognize limits associated with the use of normals. Explain.

Regional Climate Simulations of summer precipitation over the United States and Mexico Kingtse Mo, Jae Schemm, Wayne Higgins, and H. K. Kim.

C20C Workshop ICTP Trieste 2004 The Influence of the Ocean on the North Atlantic Climate Variability in C20C simulations with CSRIO AGCM Hodson.

The Role of Antecedent Soil Moisture on Variability of the North American Monsoon System Chunmei Zhu a, Yun Qian b, Ruby Leung b, David Gochis c, Tereza.

Surface energy (and water) budget in the Sahel during the multi-decadal drought: combining remote sensing and in situ data. Laurent Kergoat (CNRS/LMTG,

Variation of Surface Soil Moisture and its Implications Under Changing Climate Conditions 1.

Evapotranspiration Partitioning in Land Surface Models By: Ben Livneh.

Kinematic Structure of the WAFR Monsoon ATS mb NCEP Climatology Zonal Winds.

Lake Superior Eddy Covariance Stannard Rock Light PI: Peter Blanken, CU-Boulder Reported by Ankur Desai DO NOT DISTRIBUTE.

Analysis of surface meteorological data at the Gourma sites focus on radiative fluxes & thermodynamics at diurnal & interannual time scales automatic weather.

WMO-JMA Public Forum Workshop of the World Conference on Disaster Reduction: Reducing Risks of Weather, Climate and Water Extremes through Advanced Detecting,

Northern Hemisphere: Weather & Climate over Major Crop Areas Update prepared by Climate Prediction Center / NCEP 2 May 2011 For Real-time information:

The lower boundary condition of the atmosphere, such as SST, soil moisture and snow cover often have a longer memory than weather itself. Land surface.

Northwest European High Summer Climate Variability, the West African Monsoon and the Summer North Atlantic Oscillation Jim Hurrell, NCAR, & Chris Folland,

DISASTER RISK REDUCTION CONFERENCE WARSZAWA, Urszula Somorowska Wydział Geografii i Studiów Regionalnych Uniwersytet Warszawski

Role of Soil Moisture Coupling on the Surface Temperature Variability Over the Indian Subcontinent J. Sanjay M.V.S Rama Rao and R. Krishnan Centre for.

U.S. Department of the Interior U.S. Geological Survey Exploring Western and Eastern Pacific contributions to the 21st century Walker circulation intensification.

Global Phenological Response to Climate in Crop Areas using Humidity and Temperature Models Molly E. Brown, GSFC Code 618 Kirsten M. de Beurs, University.

Surface Net SW Radiation Latitude Clouds Albedo Source Reanalysis for

4-1 Role of Climate. 1.What is climate and what is weather? A. Climate refers to the average year after year conditions of temperature and precipitation.

Insolation and the Earth’s Surface. Insolation- The portion of the Sun’s radiation that reaches the Earth INcoming SOLar RadiATION Angle of insolation.

Comparison of Precipitation Products for 2014 Ethiopian Growing Season chg.geog.ucsb.edu Pete Peterson 1, Chris C Funk 2,1, Gregory.

1 Xiaoyan Jiang, Guo-Yue Niu and Zong-Liang Yang The Jackson School of Geosciences The University of Texas at Austin 03/20/2007 Feedback between the atmosphere,

1. Session Goals 2 __________________________________________ FAMINE EARLY WARNING SYSTEMS NETWORK Understand use of the terms climatology and variability.

Desert environments in Namibia their formation, location and climate

Shortwave and longwave contributions to global warming under increased CO 2 Aaron Donohoe, University of Washington CLIVAR CONCEPT HEAT Meeting Exeter,

Hydrologic Losses - Evaporation Learning Objectives Be able to calculate Evaporation from a lake or reservoir using the following methods – Energy Balance.

Coupled crop-climate modelling

The Indian Monsoon and Climate Change

The absorption of solar radiation in the climate system

The course finished last lesson but what are you missing?

Presentation transcript:

Vulnerability to near-term warming in the Sahel Laura Harrison UCSB Geography Climate Hazards Group Famine Early Warning System Network

perspective Efficient and optimal planning/response to climate hazards… is dependent on our understanding regional vulnerability to meteorological shock

goals Link climate hazards to impacts Identify areas most vulnerable to climate shocks/change Place risk in context to regional livelihoods

general method Examine recent land-atmosphere interaction in response to climate variability Water & surface energy balance Where there is systematic response explore climate change scenarios

CMIP5 ensemble mean RCP4.5 PET projections for the Sahel Q: How will warming over next 25 years impact plant stress in the Sahel? + ~0.75 °C Air temperature, T a 10N-20N, 20W-40E

CMIP5 ensemble mean projected T a June July August September T a = µ µ Source: KNMI Climate Explorer Projected near-term warming Varies regionally and monthly

Sahel rainfall change uncertain JAS White: < 66% of models agree on direction of change Gray: > 80% of models show no significant change Source: James and Washington, 2012 Inter-model rain change agreement (CMIP3) Rainfall change with 1 °C global warming July-September A2 SRES scenario

Examine regional response to climate variability Approach 1.Assume aspects of local climate will remain same 2.Identify where: Higher than normal heat is associated with… …drier or windier or clearer sky than normal conditions

Climate constraint to plant growth

Climate constraint and livelihoods

Moisture availability within growing season

Model anomalous PET Build statistical model to explain recent PET variability as a function of temperature Quantify the role of temperature Estimate effect of projected T a

Model anomalous PET Where y(t) = Daily PET anomaly (mm) α = PET autocorrelation coefficient for lag 1 β = Slope coefficient for temperature anomaly (mm °C -1 day -1 ) γ = Intercept term ε = Model error Build statistical model to explain recent PET variability as a function of temperature GLDAS NOAH LSM daily data Variables - Potential evapotranspiration, PET (FA0-56 PM equation) - 2m air temperature

Model skill < 0.25 R-square value June July August September Skill attributed to temperature

Model-estimated relationship: T & PET GLDAS Noah LSM PET & T 2001:2010

Projected surface moisture loss 2026:2035 – 2001:2010 GLDAS Noah LSM PET & T CMIP5 model ensemble mean monthly T 2001:2010 RFE2.0 rainfall 2001:2010

Moisture availability within growing season GLDAS Noah LSM PET 2001:2010 RFE2.0 rainfall 2001:2010

Further research Physical mechanisms of Temperature-PET relationship -Stronger vapor pressure gradient -Higher incoming radiation (LW, SW) Use station-estimated T trends (CHG) Results in context to rangeland conditions Wet vs. dry years

Thank you Collaborators: Chris Funk, Joel Michaelsen, Leila Carvalho, Phaedon Kyriakidis, Chris Still, Michael Marshall, Elena Tarnavsky, Molly Brown Climate Hazards Group USGS FEWS NET USAID Questions, comments:

extra

PM equation

Temperature predictor coefficient by month From PET predictive model data Results: Hot spots chapter1 Source: KNMI Climate Explorer Projected warming by month Ensemble mean vs

Results: Hot spots chapter1 Source: KNMI Climate Explorer Projected warming by month Ensemble mean vs Temperature predictor coefficient by month From PET predictive model data

JJAS, PET increase per 1 deg T anomaly