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THE FORMATION AND TRANSFORMATION OF SPACE AND KNOWLEDGE IN ANCIENT CIVILIZATIONSTHE FORMATION AND TRANSFORMATION OF SPACE AND KNOWLEDGE IN ANCIENT CIVILIZATIONSThe Formation and Transformation of Space and Knowledge in Ancient Civilizations
Statistical downscaling of precipitation of two transient Holocene AOGCM simulations for central Sudan
Sebastian Wagner1,4, Janina Körper2,4, Jonas Berking3,4
1GKSS Research Center, Institute for Coastal Research, Geeshacht, Germany2Free University of Berlin, Department of Meteorology, Berlin, Germany3Free University of Berlin, Department of Physical Geography, Berlin, Germany4TOPOI Excellence Cluster, Free University of Berlin, Germany
11th International Meeting on Statistical ClimatologyJuly 12-16, Edinburgh, Scotland
Outline
• Motivation
• Climatic conditions in central Sudan
• Calibration and Validation of downscaling model
• Downscaled precipitation in central Sudan during the Holocene for July
• Summary and Outlook
Motivation
• Hypothesis I [ local ]:
Menoric culture around 2000 BP:
Hydrological changes responsible for collapse culture
• Hypothesis II [ large scale ]:
Decrease in Large-scale precipitation in the northern Sahel zone during the Holocene
→ Test with climate models:
Changes in hyrdological variables [ mean/extremes ]
BUT GCMs cannot reproduce hyrdological changes with good skill
→ Downscaling of large-scale circulation
= location of Naga
[ Location of Naga: ]
Climatic conditions in central Sudan: precipitation
Climatic conditions in central Sudan: Sea level pressure
Precipitation = circulation + other
Important note: ε(t) can be quite large
)()()(1
0log ttpcaatAPRECK
k
SLPk
SLPk
Calibration and validation of downscaling model: PCR method
Basis for Downscaling:
Precipitation time series for grid point of VASCLIMO[ DWD ] co-located with the location of Naga 1951-2000
SLP data from NCEP/NCAR re-analysis for period 1951-2000
rvalid=+0.43RE=+0.16
Calibration and validation of downscaling model: Validation
Atmosphere ECHAM4[ 3.75º x 3.75º,19 vert. layers ]
Ocean HOPE-G[ 2.8 x 2.8 , 20 vert. layers ]
[ Experimental Setup for Holocene simulations ]
ECHO-G T30
Holocene simulations 7 ka BP – present:
ORB: Transient orbital forcing ORBSG: Transient orbital, solar and GHG forcing
Precipitation in central Sudan during the Holocene:
Changes in mean precipitation
95% confidence
ORBORBSG
ORBORBSG
Precipitation in central Sudan during the Holocene:
Comparison with original precipitation output from climate model[ Reference: mean of period 1900-2000 AD ]
σSD_dt_IA=35.3 mmσmodel_dt_IA=25.9 mm
ORBSG
Summary
Methodological aspects:
• Statistical downscaling is potentially suited also for arid/semi-arid regions:However: model fit on inter-annual time scales shows only weak model skill
Test of the hypothesis:
• Based on changes in mean precipitation no change between 2000 BP and present-day
• Other reasons: changes in extreme precipitation and/or non-climatic influences
• Reproduction by decrease in precipitation during the Holocene in downscaled precipitation
Outlook :
Mean changes in sea level pressure during the Holocene
Thank you for your attention !
Outlook:
[ Methods for selection of proper geographical domain ]
• One-point correlation map:
Naga
Calibration and validation of downscaling model: PCR method
[ EOF patterns and their interpretation in the context of PCR ]
Precipitation = circulation + other
Important note: ε(t) can be quite large
)()()(1
0log ttpcaatAPRECK
k
SLPk
SLPk
a1=-0.337 a2=-0.23 a3=-0.104
Calibration and validation of downscaling model: PCR method
Calibration and validation of downscaling model: PCR method
[ EOF patterns and their interpretation in the context of PCR ]
Precipitation = circulation + other
Important note: ε(t) can be quite large
)()()(1
0log ttpcaatAPRECK
k
SLPk
SLPk
a1=+0.337 a2=+0.23
Calibration and validation of downscaling model: PCR method
[ EOF patterns and their interpretation in the context of PCR ]
Precipitation = circulation + other
Important note: ε(t) can be quite large
)()()(1
0log ttpcaatAPRECK
k
SLPk
SLPk
a1=+0.337 a2=+0.23 a3=+0.104
EOFs and their interpretation in the context of PCR cont.
a5=+0.328a4=+0.118
Precipitation = circulation + other
Important note: ε(t) can be quite large
)()()(1
0log ttpcaatAPRECK
k
SLPk
SLPk
Solar and CO2 changes:
Motivation: Why Downscaling at all ?
Comparison between
‘real world’ world of a climate model
at a global scale
= location of Naga
Linking scales in the ‘real world’ and apply the link to the GCM large scale
Local scale variable, e.g. precipitation
The solution:
Skill of statistical model calibrated with SLP predictors:
June July August September October
Calibration
correlation +0.41 +0.55 +0.45 +0.52 +0.46
RedinErr +0.16 +0.29 +0.2 +0.27 +0.21
Validation
correlation +0.25 +0.43 +0.27 +0.38 +0.16
RedinErr 0 +0.16 0 +0.1 -0.12
Mean wind conditions during July
jJ
jjecX
1
jjeXc T
Estimation of principal components by means of EOF analysis:
k j cc kj | 0
obsmoTmo
jjeXc
,
Estimation of GCM-modelled principal components cj
Principal Component Regression (PCR):
)()()(1
0 ttcaatPRECK
k
SLPk
SLPk
Changes in variability for downscaled large scale circulation:
Comparison with original precipitation output from climate model[ Reference: mean of period 1900-2000 AD ]
σmodel_dt_IA=26.6mm
σSD_dt_IA=35.3 mmσmodel_dt_IA=25.9 mm
σSD_dt_IA=34.9 mm
Mean differences in precipitation between different periods of the Holocene and present day [ PD, 1900-2000 AD ]
Naga [ 67.7mm ] ORB ORBSG
7k-PD +53.9 +39.5
6k-PD +37.1 +39.2
5k-PD +33.3 +23.8
4k-PD +21.7 +19.3
3k-PD +12.0 +8.7
2k-PD +1.4 -4.5
1k-PD +1.1 -6.2
Experimental Setup for downscaling:
• ECHO-G simulations starting 7000 BP forced with
I) only changes in orbital forcing [ ORB ]
II) additional changes in solar and GHG forcing [ ORBSG ]
Control simulation: pre-industrial with constant condition of 1750 AD
Mean differences in incoming solar radiation Mid-Holocene – PD
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