Contents
• Where does everything
start?
• Daily weather data
– Weather station
– Gridded
• Mean climatology
– Weather station
– Interpolated
• Future climate data
– GCM data
– Downscaled
Sources of daily weather data
• Our own met service
• Global Historical Climatology Network
(GHCN) -14k weather stations
• CIAT’s weather station database (9k
stations) –but loads of restrictions
• Global Summary of the Day (GSOD) -10k
weather stations –uh oh?
• GPCP, GPCC, NASA-Power (1 degree)
(1995 – now)
• TRMM (1998 – now)
Early
20th century
Optimal (mid)
20th century
Despite some improvements in data availability
0
500
1000
1500
2000
2500
0
2000
4000
6000
8000
10000
12000
14000
16000
1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 2010
Nu
mb
er
of
stat
ion
s (h
igh
qu
alit
y)
Nu
mb
er
of
stat
ion
s (a
ll)
All stations
Highly reliable
© Global Historical Climatology Network (GHCN)
http://www.ncdc.noaa.gov/ghcnm/v2.php
Mean climatology
• New et al. (2002) –CRU (10 min
resolution)
• Hijmans et al. (2005) –WorldClim (0.5 min)
Research areas: Available and
usable climate data
BCCR-BCM2.0 CCCMA-CGCM3.1-
T47
CNRM-CM3
CSIRO-MK3.0 CSIRO-MK3.5 GFDL-CM2.0
GFDL-CM2.1 INGV-ECHAM4 INM-CM3.0
IPSL-CM4 MIROC3.2-MEDRES MIUB-ECHO-G
MPI-ECHAM5 MRI-CGCM2.3.2A NCAR-CCSM3.0
NCAR-PCM1 UKMO-HADCM3 UKMO-HADGEM1
Global climate models
• Climate model skill (CMIP3)1961-1990 Rainfall 1961-1990 Temperature
Source: Ramirez and Challinor, 2012
Global Climate Models
• Global climate model skill (IPCC 4AR)
Source: Ramirez and Challinor, 2012
Mean
tem
pera
ture
Diu
rnal te
mp
era
ture
ran
ge
Rain
fall
Annual December-February June-July-August
Also, we need downscaling
• Even the most precise GCM is too coarse (~100km)
• To increase resolution, uniformise, provide high resolution and contextualised data
• Different methods exist… from interpolation to neural networks and RCMs
www.ccafs-climate.org
Notes to take
• Various sources of
weather/climate data exist,
pick the best for your case… if
there’s no data…
• Beware of errors in the data
• Improvements to data network
are needed
• Use downscaled information
carefully
• Assess the ability of these
data to make ag. predictions
(c) Neil Palmer (CIAT)