navarro-racines_c major global dataset: ccafs-climate
TRANSCRIPT
Carlos NavarroJ. Tarapues, J. Ramirez, A. Jarvis
Major global dataset: CCAFS-Climate
Concepts Homogenization• General Circulation Model (GCM): is a type of climate
model. It employs a mathematical model of the general circulation of a planetary atmosphere or ocean. These models are the basis for model predictions of future climate, such as are discussed by the IPCC.
• Downscaling: is a general concept that embraces various methods for increasing the spatial resolution and reduce some of the biases in order to improve the usability of climate scenarios.
• Bias correction: correct the climate input data provided by GCM for systematic statistical deviations from observational data. They generally adjust the long-term mean by adding the average difference between the simulated and observed data over the historical period to the simulated data, or by applying an associated multiplicative correction factor.
Climate and Agriculture
Reliable climatic data Gaps in representation of the climate system
Inadequate climate models
Assessment of impacts of climate change on agriculture
NeedsLimitations
High degree of uncertainty
• Multiple variables• Very high spatial
resolution• Mid-high temporal (i.e.
monthly, daily) resolution• Accurate weather
forecasts and climate projections
• High certainty. Both for present and future
–T°• Max,• Min, • Mean
–Prec– HR– Radiation– Wind– …….
Less
impo
rtan
ce
Mor
e ce
rtai
nty
Climate and AgricultureAgriculture, a niche business
Global scale Regional or local scale
Resolutions
• Horizontal resolution 100 to 300 km
GCMs are the only way we can predict the future
climate
GCM “Global Climate Model”
Problems
Needs
Options• Statistical or dynamical
downscaling methods.• Bias correction
methods.• Correct biases • Provide high
resolution and contextualized data
• Systematic errors or biases.• Low resolution (> 50 Km).• Incomplete knowledge of
climate system processes.• High deviations from
observational data.
Why Do We Need Downscaling?
Hawkins, 2012
GCM Biases and Calibration
http://ccafs-climate.orgCCAFS Climate
Ramírez-Villegas and Challinor, 2012AI GCM: GCM data “as is”, SD GCM: statistically downscaled GCM, PS GCM: pattern scaled GCM, WG GCM: GCM data through a weather generator, SC Variables: systematic changes in target key variables, Unclear: not specified clearly in study, ARPEGE: the ARPEGE Atmospheric GCM
Downcaling by serveral methods in CCAFS-Climate
CCAFS-ClimateUsers
Sessions
126,768 Users
66,682 Page Views
466,120 Pages/Session
3.68 Avg. Session Duration
00:04:44 Bounce Rate
42.11%
CCAFS-ClimateCitations
Significant impact by putting climate change
information into the hands of non-climate scientists
and next users which represent up to 19% of all
CCAFS-Climate users.
> 400 Publications
CORDEX Dynamical Downscaled Data
Undefined periods Prec, Tmax, Tmin, Bioclim + otrhers0.44deg (~50km)At least 2 CORDEX Domains
2014
ETA Dynamical Downscaled Data
4 GCM - 2 SCENARIOS,4 future periods.0.33deg (~40km)South America
4 RCP106 GCM (about 25 models per RCP)4 future periods5 climatological variables 4 spatial resolutions (the highest at 1 Km2)
Full set of CMIP5 Delta Method Downscaled Data
CMIP5 Raw and Processed Daily Data with several bias-correction Methodologies (Online processing)
2015-2016
DSSAT (.wtg)
APSIM (json)
Others (ascii)
2030’s, 2050’s, 2070’s, 2080’sPrec, Tmax, Tmin, RsdsRaw Resolution
Extractions online in formats of interest to
Crop Modelers
CCAFS-ClimateData Strategy
We are focused now in increase its use amongst
crop modelers
CCAFS-Climatehttp://ccafs-climate.org/data_bias_corrected/
CCAFS-Climatehttp://www.ccafs-climate.org/weather_stations
CCAFS-ClimateClimate Wizard integration
• A major barrier preventing informed climate-change adaptation planning is the difficulty accessing, analyzing, and interpreting climate-change information.
http://climatewizard.ciat.cgiar.org/
Applied climate change analysis
• Provides non-climate specialists with simple analyses and innovative graphical depictions for conveying.
• Provides both the data for impacts research, as well as the basic information that is needed to understand the IPCC climate projections within specific geographic areas throughout the world. Provides projections for policy and practice.
• It can get relatively complicated (such as when you visualize changing probabilities of extreme events) or it can be simple such as looking at maximum temperatures during a month of interest
CCAFS-ClimateWOCAT IntegrationThe World Overview of Conservation
Approaches and Technologies
API development: • Developer for
WOCAT Sustainable Land Management Database
• API to query climate change projections from ClimateWizard
GCMs
Effective adaptation options
MarkSim
DSSAT
Statistical Downscaling
Dynamical downscaling:Regional Climate Model
EcoCropStatistical Downscaling
MaxEnt
Based on niches
Prob
abili
ty
Environmental gradient
Based on process
We use calibrated GCM to quantify the impacts and adaptation options through
crops models
Gourdji et al. (in prep.)
Percent change in yields by 2030s and RCP4.5
Using crop models to look at crop yields under future climate
Vallejo and Ramirez-Villegas, BID Report (2016)
Rainfed agriculture vulnerability hotspots
… and to identify vulnerability hotspots
So take a look…Conservation plans, niche models, crop models, and biodiversity evaluation require high resolution inputs.
Downscaling produces precise tools that allow local rather than regional or global predictions of climatic changes.
CCAFS-Climate is a web service to query Downscaled data, Bias Corrected data and weather information for a broad of user, not only scientist.
Conclusions
