THE FORMATION AND TRANSFORMATION OF SPACE AND KNOWLEDGE IN ANCIENT CIVILIZATIONS The Formation and Transformation of Space and Knowledge in Ancient Civilizations Statistical downscaling of precipitation of two transient Holocene AOGCM simulations for central Sudan Sebastian Wagner 1,4, Janina Körper 2,4, Jonas Berking 3,4 1 GKSS Research Center, Institute for Coastal Research, Geeshacht, Germany 2 Free University of Berlin, Department of Meteorology, Berlin, Germany 3 Free University of Berlin, Department of Physical Geography, Berlin, Germany 4 TOPOI Excellence Cluster, Free University of Berlin, Germany 11 th International Meeting on Statistical Climatology July 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 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 SLP data from NCEP/NCAR re-analysis for period

r valid =+0.43 RE=+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 ORB ORBSG ORB ORBSG

Precipitation in central Sudan during the Holocene: Comparison with original precipitation output from climate model [ Reference: mean of period AD ] σ SD_dt_IA =35.3 mm σ model_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 a 1 =-0.337a 2 =-0.23 a 3 = 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 a 1 =+0.337a 2 =+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 a 1 =+0.337a 2 =+0.23 a 3 =+0.104

EOFs and their interpretation in the context of PCR cont. a 5 = a 4 = Precipitation=circulation+ other Important note: ε(t)can be quite large

Solar and CO 2 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: JuneJulyAugustSeptemberOctober Calibration correlation RedinErr Validation correlation RedinErr

Mean wind conditions during July

Estimation of principal components by means of EOF analysis: Estimation of GCM-modelled principal components c j Principal Component Regression (PCR):

Changes in variability for downscaled large scale circulation:

Comparison with original precipitation output from climate model [ Reference: mean of period AD ] σ model_dt_IA =26.6mm σ SD_dt_IA =35.3 mm σ model_dt_IA =25.9 mm σ SD_dt_IA =34.9 mm

Mean differences in precipitation between different periods of the Holocene and present day [ PD, AD ] Naga [ 67.7mm ]ORBORBSG 7k-PD k-PD k-PD k-PD k-PD k-PD k-PD

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