Cristina Milesi Ecological Forecasting Lab CSU Monterey Bay / NASA Ames Research Center Co-Is: Forrest Melton and Weile Wang, CSU Monterey Bay / NASA Ames.

Slides:

Advertisements

Similar presentations

Ecological Conditions of US National Parks: Enabling Decision Support Through Monitoring, Analysis, and Forecasting NASA Applications Sciences Program:

Advertisements

Global Mapping of Impervious Surface Area Benjamin Tuttle* - CIRES, University of Colorado, Boulder Christopher D Elvidge, PhD - NOAA-National Geophysical.

Methods: TOPS Generated 1km monthly Tave, Precip, VPD and solar radiation surfaces from downscaled WCRP CMIP3 scenarios (Maurer et al., 2007) Input ParameterUnited.

Satellite Remote Sensing and Applications in Hydrometeorology Xubin Zeng Dept of Atmospheric Sciences University of Arizona Tucson, AZ

Observed Tropical Expansion: Impact on the Hydrological and Energy Cycles New Investigator Research Summary Joel Norris (Lead PI, UC San Diego) Robert.

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

NCAR GIS Program : Bridging Gaps

The Importance of Realistic Spatial Forcing in Understanding Hydroclimate Change-- Evaluation of Streamflow Changes in the Colorado River Basin Hydrology.

IPCC Projection (AR 4, 2007) The annual mean rainfall exhibits increasing trends in Bangladesh. Decadal rain anomalies are above long term averages since.

Integrating Satellite Data with Ecosystem Models Progress & Prospects Ramakrishna Nemani Petr Votava Andy Michaelis Forrest Melton Hirofumi Hashimoto Weile.

Mapping future snow cover in Idaho Brandon C. Moore University of Idaho.

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

Liu, J. et al., PNAS, 2012 World Weather Open Science Conference, Montreal, Canada, August 17, 2014 Jiping Liu University at Albany, State University of.

Soil Water Assessment Tool (SWAT) Model Input

Washington State Climate Change Impacts Assessment: Implications of 21 st century climate change for the hydrology of Washington Marketa M Elsner 1 with.

Hydrology in Land Surface Models Jessie Cherry International Arctic Research Center & Institute of Northern Engineering.

Kristie J. Franz Department of Geological & Atmospheric Sciences Iowa State University

Impact of Climate Change on Flow in the Upper Mississippi River Basin

Retrieval of Time-Varying Land Cover and Vegetation Properties from MODIS in Support of the NCEP- WRF Land Surface Model Year 1 Progress Report Mark Friedl,

Climate Modeling Elissa Lynn SCRO August 27, 28/ 2013.

Dr. Max Loewenstein ESD/ARC Dr. Laura Iraci ESD/ARC, Dr. Cristina Milesi CSUMB/ARC With Contributions from Katie Pitts, Ariana Gonzales, and Matthew Little.

Ecological Conditions of US National Parks: Enabling Decision Support Through Monitoring, Analysis, and Forecasting NASA Applications Sciences Program:

NASA Applied Sciences Program (NNH10ZDA001N - BIOCLIM) NPS I&M Program Landscape Climate Change Vulnerability Project (LCC_VP) Montana State University:

The University of Mississippi Geoinformatics Center NASA MRC RPC Review Meeting: April, 2008 Evaluation for the Integration of a Virtual Evapotranspiration.

Assessment of the Pra and White Volta River Basins to water stress conditions under changing climate Emmanuel Obuobie, Kwabena Kankam-Yeboah, Barnabas.

Remote Sensing Data Assimilation for a Prognostic Phenology Model How to define global-scale empirical parameters? Reto Stöckli 1,2

Applications of Remote Sensing and Ecosystem Modeling for Monitoring and Management of U.S. National Parks F Melton 1*,2, A Michaelis 1,2, W Wang 1,2,

Rapid Ecoregional Assessment. Climate was primarily modeled using models and data from the Scenarios Network for Alaska and Arctic Planning. See

Real-time integration of remote sensing, surface meteorology, and ecological models.

Page 1 Met Office contribution to RL5 Task ‘Large-scale interactions between atmospheric moisture and water availability - coupling of atmospheric.

Land Use, Land Cover, and the Impacts of Climate Change in Agriculture Hexbin plot of MLCT raw vs. NLCD (left) and of MLCT adjusted crop versus Agland2000.

Landscape Climate Change Vulnerability Project (LCC_VP) Andrew Hansen/ Montana State University Goal: Use NASA and other data and models to assess the.

Report on March Crystal City Workshop to Identify Grand Challenges in Climate Change Science By its cochair- Robert Dickinson For the 5 Sept

Notice: The views expressed here are those of the individual authors and may not necessarily reflect the views and policies of the United States Environmental.

Scott Goetz Changes in Productivity with Climate Change at High Latitudes: the role of Disturbance.

Reducing Canada's vulnerability to climate change - ESS J28 Earth Science for National Action on Climate Change Canada Water Accounts AET estimates for.

Downscaling Future Climate Scenarios for the North Sea 2006 ROMS/TOMS Workshop, Alcalá de Henares, 6-8 November Bjørn Ådlandsvik Institute of Marine Research.

Modeling Future Land Use, Regional Climate, and Maize Yields in East Africa Nathan Moore, B Pijanowski, B Lofgren, G Alagarswamy, J Andresen, J Olson B43H-03.

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

Environment Canada Environnement Canada Effects of elevated CO 2 on modelled ENSO variability Bill Merryfield Canadian Centre for Climate Modelling and.

Research Needs for Decadal to Centennial Climate Prediction: From observations to modelling Julia Slingo, Met Office, Exeter, UK & V. Ramaswamy. GFDL,

Downscaling a monthly ecosystem model to a daily time step: Implications and applications Zaixing Zhou, Scott Ollinger, Andrew Ouimette Earth Systems Research.

Atmospheric Hydrological Cycle in the Tropics in Twentieth Century Coupled Climate Simulations Hailan Wang and William Lau Laboratory for Atmospheres,

Feng Zhang and Aris Georgakakos School of Civil and Environmental Engineering, Georgia Institute of Technology Sample of Chart Subheading Goes Here Comparing.

Deforestation and the Stream Flow of the Amazon River -- Land Surface Processes and Atmospheric Feedbacks Michael T. Coe1, Marcos Heil Costa2, and Britaldo.

Office of Research and Development National Exposure Research Laboratory, Atmospheric Modeling and Analysis Division Using Dynamical Downscaling to Project.

Development of Climate Change Scenarios of Rainfall and Temperature over the Indian region Potential Impacts: Water Resources Water Resources Agriculture.

The evolution of climate modeling Kevin Hennessy on behalf of CSIRO & the Bureau of Meteorology Tuesday 30 th September 2003 Canberra Short course & Climate.

The USGS Resource for Advanced Modeling: Developing an operational capacity USGS (Morisette, PI) Montana State University (Hansen, PI) NASA Biodiversity.

Fine-Resolution, Regional-Scale Terrestrial Hydrologic Fluxes Simulated with the Integrated Landscape Hydrology Model (ILHM) David W Hyndman Anthony D.

Goal: to understand carbon dynamics in montane forest regions by developing new methods for estimating carbon exchange at local to regional scales. Activities:

Evapotranspiration Estimates over Canada based on Observed, GR2 and NARR forcings Korolevich, V., Fernandes, R., Wang, S., Simic, A., Gong, F. Natural.

Climate change impacts on water resources in the southeastern U.S. – Can we adapt? Peter Caldwell USDA Forest Service, Eastern Forest Environmental Threat.

How much water will be available in the upper Colorado River Basin under projected climatic changes? Abstract The upper Colorado River Basin (UCRB), is.

Copernicus Observations Requirements Workshop, Reading Requirements from agriculture applications Nadine Gobron On behalf Andrea Toreti & MARS colleagues.

Using Satellite Data and Fully Coupled Regional Hydrologic, Ecological and Atmospheric Models to Study Complex Coastal Environmental Processes Funded by.

Consistent Earth System Data Records for Climate Research: Focus on Shortwave and Longwave Radiative Fluxes Rachel T. Pinker, Yingtao Ma and Eric Nussbaumer.

Enabling Ecological Forecasting by integrating surface, satellite, and climate data with ecosystem models Ramakrishna Nemani Petr Votava Andy Michaelis.

NASA Earth Exchange (NEX) A collaborative supercomputing environment for global change science Earth Science Division/NASA Advanced Supercomputing (NAS)

References: 1)Ganguly, S., Samanta, A., Schull, M. A., Shabanov, N. V., Milesi, C., Nemani, R. R., Knyazikhin, Y., and Myneni, R. B., Generating vegetation.

NASA Ames Research Center Ecological Forecasting Lab presenter: Sam Hiatt NASA PI: Dr. Ramakrishna Nemani Hirofumi Hashimoto, Forrest Melton, Andrew Michaelis,

CLIP – Linkages between Land Cover and Regional Climate

Future Work Three timelines

Hydrologic response of Pacific Northwest Rivers to climate change

University of Washington Center for Science in the Earth System

Precipitation variability over Arizona and

Hydrology CIVL341.

Hydrologic Modeling in GCIP and GAPP

Hydrology CIVL341 Introduction

Assessment of climate change impacts on semi-arid watersheds in Peru

Presentation transcript:

Cristina Milesi Ecological Forecasting Lab CSU Monterey Bay / NASA Ames Research Center Co-Is: Forrest Melton and Weile Wang, CSU Monterey Bay / NASA Ames Research Center Rama Nemani, NASA Ames Research Center David Theobald Colorado State University PI: Scott Goetz, Woods Hole Center NASA LCLUC Science Team Meeting March 29, 2011 Modeling Strategies for Adaptation to Coupled Climate and Land Use Change in the United States

Motivation IPCC Fourth Assessment Report (AR4) projects warming of 4-12  C over the United States by 2100 Urban land cover and associated impervious surface are forecasted to increase by 50% over the next few decades across substantial portions of the U.S. Coupled effects of changes in climate and land use and land cover are expected to intensify impacts on ecosystems (changes in productivity, disturbance and hydrological properties) Low impact development (LID) and Best management practices (BMPs) for land use planning and design can mitigate impacts resulting from changes in climate and LU (e.g. reducing impervious surface cover)

Goal and Objectives Prepare for next generation regionally focused IPCC scenarios that better incorporate the influences of land use change by: Spatially predict future land use changes Incorporate land use and climate change predictions under different SRES scenarios into ecosystem process models Simulate the influence of potential mitigation and adaptation actions by predicting land use change scenarios that incorporate a range of best management practices (BMPs) associated with land cover and land use change.

Bierwagen et al. PNAS 2010;107: (A) actual housing density in 2000; (B) modeled housing density in 2100 for base case; (C) for scenario A2; and (D) for scenario B1. Methods: SERGoM Housing Density  Impervious Area covered by impervious surface over time for all five scenarios.

Methods: TOPS Generated 1km monthly Tave, Precip, VPD and solar radiation surfaces from downscaled WCRP CMIP3 scenarios (Maurer et al., 2007) Input ParameterChesapeake / Delaware (250m) United States (1km) Impervious surface area SERGoM (Theobald et al., 2009) Climate (baseline run) TOPS-SOGS Weather Surfaces Climate (forecast) WCRP CMIP3 (Maurer et al., 2007) GFDL CM2.0, NCAR CCSM3.0, GISS-ER Scenarios A1B, A2, B1 ElevationNational Elevation Dataset (resampled) Leaf Area Index (baseline run) MODIS MOD13Q1 NDVI and MOD15A2 LAI algorithm MODIS MOD15A2 LAI (Myneni et al., 2000) Leaf Area Index (forecast) MODIS MOD15A2 LAI Climatology Simulated by BIOME-BGC SoilsU.S. STATSGO2 database Land CoverNLCD2001 (Homer et al., 2004) Cross- walked to IGBP MODIS MOD12Q1 Land cover (Friedl et al., 2002)

Model Calibration: Land Cover Change Impacts Baseline LC (2000) Forecast LC (2030) Chesapeake Bay and Delaware River watersheds Current and Projected Impervious cover SERGoM on top of NLCD 2001

TOPS Results: Impact of Land Use Change on Runoff Baseline (2000) Forecast (2030) Change ( ) Average annual total runoff for the baseline (2000) and forecast (2030) scenarios, and the projected increase in average annual runoff

TOPS Results: Impact of Land Use Change on Vegetation Productivity Baseline (2000) Forecast (2030) Change

Projected Impervious Surface under IPCC SRES A1B 2010 to 2100

PrecipitationTaveVPD Projected Climate under IPPCC SRES A1B 1km Downscaled GFDL CM2.0

Projected Impervious and Climate GFDL CM2.0 A1B and A2

TOPS Results: Coupled Climate and Land Use Change 2100 Runoff 2100 GPP SRES A1 vs A2 over US urban areas Loss in GPP (kg C) Impervious Area (km 2 ) Total Runoff (mm) Coupled climate and land use change impacts over urban areas +54% +110% +60% +90% -40% -25%

Next Steps TOPS runs with other ecosystem and climate models (i.e., GISS-ER, CCSM3.0) and SRES B1 and B2 Regional analysis of impacts of land use changes versus climate Assess the effects on runoff and vegetation productivity of realistic Best Management Practices / Low Impact Development techniques by simulating:  increases of pervious surfaces  green roofs  urban afforestation programs

Data Sharing on NASA Earth Exchange Collaborative computing environment for sharing of data, code and science results

NEX Components