Laux, P.

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KIT – Universität des Landes Baden-Württemberg und nationales Forschungszentrum in der Helmholtz-Gemeinschaft IINSTITUTE OF METEOROLOGY AND CLIMATE RESEARCH, GARMISCH-PARTENKIRCHEN, GERMANY www.kit.edu State-of-the-art in  climate modelling and CC impact analysis in EA Patrick Laux KIT, Institute of Meteorology and Climate Research  2  Post-Doc Position  KIT, IMK-IFU  Department Regional Climate Systems at IMK-IFU   Academic background  MSc. (Diploma) in Applied Environmental Sciences  PhD  at KIT, IMK-IFU, Garmisch-Partenkirchen   Research interests  Statistical and Dynamical Downscaling of GCMs  Bias correction of precipitation  Hydrometeorology: Precipitation variability in complex terrain and data poor regions  Agricultural impact studies   Geographical Focus: Alpine Space, Africa, South East Asia Patrick Laux RICE-EA workshop, Nairobi, Kenya 17.04. – 19.04.2012 KIT, Institute of Meteorology and Climate Research  3 Why do we need climate change information? Source: IPCC AR4, 2007 RICE-EA workshop, Nairobi, Kenya 17.04. – 19.04.2012 KIT, Institute of Meteorology and Climate Research  4 Stability of Food Security RICE-EA workshop, Nairobi, Kenya 17.04. – 19.04.2012 KIT, Institute of Meteorology and Climate Research  5 Stability of Food Security Bio-physical factors such as climate, biology, hydrology,  … but also: socio-economic aspects RICE-EA workshop, Nairobi, Kenya 17.04. – 19.04.2012 KIT, Institute of Meteorology and Climate Research  6 Main drivers for Food Insecurity in EA  Economy (e.g. GDP) mainly depends on agricultural sector (highly vulnerable to climate, CC and CV)  Limited agricultural productivity (low soil fertility, pest, crop diseases, lack of fertilizers)  Climate: → Agriculture: High rainfall variability on different scales         (Hulme et al., 2005) → Health:  Droughts/Floods contribute to diseases such as diarrhoe, cholera (Few et al., 2004) through poor nutrition Diseases such as Malaria spreads into new areas such as highlands of Central Kenya (Chen et al., 2006; Pascual et al., 2006)    RICE-EA workshop, Nairobi, Kenya 17.04. – 19.04.2012 KIT, Institute of Meteorology and Climate Research  7 Early warning system: Level Food Security for 04/2012 Source: FEWS-NET RICE-EA workshop, Nairobi, Kenya 17.04. – 19.04.2012 KIT, Institute of Meteorology and Climate Research  8 Impacts of CC/CV Climate Change is expected to aggravate the situation in EA  Water availability Health Agricultural productivity Biodiversity … but:  Little information about recent climate and expected future climate available!  RICE-EA workshop, Nairobi, Kenya 17.04. – 19.04.2012 Source: IPCC AR4, 2007 KIT, Institute of Meteorology and Climate Research  9 Rice Production in EA 20.02.2012 0 10,000 20,000 30,000 40,000 50,000 60,000 70,000 80,000 90,000 0 100,000 200,000 300,000 400,000 500,000 600,000 700,000 800,000 900,000 1,000,000 1,100,000 1,200,000 1,300,000 1,400,000 1,500,000 Production [t/year] Rice paddy-Tanzania Rice paddy-Kenya Data Source: FAOSTAT RICE-EA workshop, Nairobi, Kenya 17.04. – 19.04.2012 KIT, Institute of Meteorology and Climate Research  10 RICE-EA workshop, Nairobi, Kenya 17.04. – 19.04.2012 KIT, Institute of Meteorology and Climate Research  11 Climate in EA Source: WMO, UNEP - Arid to humid conditions  - Rainfall is limited to seasons with mono- to bimodal distribution  -  High spatial and temporal rainfall variability on different scales  - Alternating wet & dry periods: wet 1960s and dry 1980s         RICE-EA workshop, Nairobi, Kenya 17.04. – 19.04.2012 KIT, Institute of Meteorology and Climate Research  12 High spatio-temporal rainfall variability (Kenya)  Source:  Schreck & Semazzi, 2004 October November December OND rainfall amount [mm/m] (1961-1990) RICE-EA workshop, Nairobi, Kenya 17.04. – 19.04.2012 KIT, Institute of Meteorology and Climate Research  13 Past Climatic Trends in EA Temperature: Tmin increased faster than Tmax and Tmean (e.g. Conway et al., 2004)  Decreasing temperature trends at coastal (also inland lakes) stations from 1960-2000 (King‘uyu et al., 2000)  Rainfall:  La Nina years tend to become drier and El Nino years tend towards average in MAM season (Funk, 2010) induced by shift of large scale circulation (warming western Indian Ocean)  EA has experienced intensifying dipole character on decadal scale: increasing (decreasing) patterns over northern (southern) sector (Schreck and Semazzi, 2004)  RICE-EA workshop, Nairobi, Kenya 17.04. – 19.04.2012 KIT, Institute of Meteorology and Climate Research  14 RICE-EA workshop, Nairobi, Kenya 17.04. – 19.04.2012 KIT, Institute of Meteorology and Climate Research  15 Projected Temperature Anomalies (2001-2100) Source: IPCC AR4, 2007 B1 A1B A2 RICE-EA workshop, Nairobi, Kenya 17.04. – 19.04.2012 AOGCM Projections KIT, Institute of Meteorology and Climate Research  16 ΔT (2080-2099 - 1980-1999): 21 AOGCMs & A1B  Source: IPCC AR4, 2007 CC signal: approx. +3°C by end of 21th century (highly certain) Signal relatively homogeneous in space and time  RICE-EA workshop, Nairobi, Kenya 17.04. – 19.04.2012 KIT, Institute of Meteorology and Climate Research  17 ΔP (2080-2099 - 1980-1999): 21 AOGCMs & A1B  Annual DJF JJA Source: IPCC AR4, 2007 Tendency of increased rainfall (highly certain for DJF)  RICE-EA workshop, Nairobi, Kenya 17.04. – 19.04.2012 KIT, Institute of Meteorology and Climate Research  18 ΔT & ΔP : 21 AOGCM & A1B  EA Temperature Response [°C] Precipitation Response [%] * Extreme Seasons [%] Min 25 50 75 Max Min 25 50 75 Max Warm Wet Dry DJF 2 2.6 3.1 3.4 4.2 -3 6 13 16 33 100 25 1 MAM 1.7 2.7 3.2 3.5 4.5 -9 2 6 9 20 100 25 4 JJA 1.6 2.7 3.4 3.6 4.7 -18 -2 4 7 16 100   SON 1.9 2.6 3.1 3.6 4.3 -10 3 7 13 38 100 21 3 Annual 1.8 2.5 3.2 3.4 4.3 -3 2 7 11 25 100 30 1 * Values shown if at least 14 out of 21 agree on increase/decrease in extremes. A value of ≤ 5% indicates no change (nominal value for control period by construction) modified from IPCC AR4, 2007 RICE-EA workshop, Nairobi, Kenya 17.04. – 19.04.2012 KIT, Institute of Meteorology and Climate Research  19 Patrick Laux 20.02.2012 KIT, Institute of Meteorology and Climate Research  20 Regional Rainfall Anomalies source: KMNI, 2011 Ensemble of 8 dynamically downscaled AOGCMs RICE-EA workshop, Nairobi, Kenya 17.04. – 19.04.2012 KIT, Institute of Meteorology and Climate Research  21 source: KMNI, 2011 Regional Rainfall Anomalies Ensemble of 8 dynamically downscaled AOGCMs RICE-EA workshop, Nairobi, Kenya 17.04. – 19.04.2012 KIT, Institute of Meteorology and Climate Research  22 Summary: CC Simulations for EA  Regional projections generally agree with AOGCM projections Past rainfall variability could be reproduced using RCMs (except for Northern Kenya in MAM) Weak increase at coast, high increase in northern regions (OND)  Warming larger than global mean (all seasons) with drier subtropical regions warming more than moister tropics (very likely) Middle distribution indicates +2.5°C to +3.4°C (annual avg) Slightly higher increase in boreal summer than winter   Increase in annual rainfall, more pronounced in boreal winter (likely) Significant increase in rainfall of 10% - 30%, confirmed by Hulme et al.(2001) & Ruosteenoja et al. (2003) Higher tails: +38% for SON Extremely wet seasons increased (about 4 times)    RICE-EA workshop, Nairobi, Kenya 17.04. – 19.04.2012 KIT, Institute of Meteorology and Climate Research  23 Research Gaps: Climate Modeling GCM projections too coarse to capture regional/local climate variations → RCM at scale meaningful for decision makers/stakeholders → Bias correction methodologies  Limited research on changes in extreme events  → Extreme Value Theory  Future shifts of climate regimes  → Improved analysis of ENSO  Impact of LUC on climate and vice versa → Including dynamic vegetation models and feedbacks from aerosols in climate models → “What-if” LUC scenarios    RICE-EA workshop, Nairobi, Kenya 17.04. – 19.04.2012 KIT, Institute of Meteorology and Climate Research  24 Research Gaps: Climate Modeling (cont’d) Seasonal Climate Prediction   → Quantitative assessment for decision makers/stakeholders  → Role of teleconnections (ENSO, etc.) source: International Research Institute (IRI), 2012 RICE-EA workshop, Nairobi, Kenya 17.04. – 19.04.2012 KIT, Institute of Meteorology and Climate Research  25 RICE-EA workshop, Nairobi, Kenya 17.04. – 19.04.2012 KIT, Institute of Meteorology and Climate Research  26 CC Impact Studies  Many studies dealing with impact of climate change on crop productivity on different scales (e.g. Mati, 2000, Lobel, 2008, Laux et al., 2010)  → low number of studies for Africa and EA     Rare number of studies accounting for additional factors such as changes in supply patterns under different trade scenarios (Lotze-Campen et al., 2010), consumption, prices, and trade (Nelson et al., 2009)  Missing studies accounting additionally for regional and local supply-and-demand projections RICE-EA workshop, Nairobi, Kenya 17.04. – 19.04.2012 KIT, Institute of Meteorology and Climate Research  27 Agricultural Impact Studies for Africa Source: Müller, 2011 Expected change of agricultural productivity [%]  RICE-EA workshop, Nairobi, Kenya 17.04. – 19.04.2012 KIT, Institute of Meteorology and Climate Research  28 Agricultural Impact Studies for Africa (cont’d) By 2100, large parts of Africa may undergo negative changes: parts of Sahara have to expect losses of 2-7% of GDP, Western and Central Africa 2-4% of GDP (Mendelsohn et al., 2000) SRES B1: Marginal areas will become more marginal, especially in context of rainfall seasonality such as onset & intensity of rains (e.g. Jones & Thornton, 2003; Huntingford et al., 2005; Thornton et al., 2006)    HadCM3, SRES A1 HadCM3, SRES B1 Source: Thornton et al., 2006 LGA - Livestock-only system MRA-Mixed crop/livestock systems RICE-EA workshop, Nairobi, Kenya 17.04. – 19.04.2012 KIT, Institute of Meteorology and Climate Research  29 Agricultural Impact Studies for EA RICE-EA workshop, Nairobi, Kenya 17.04. – 19.04.2012 Moore et al., 2012 Maize productivity (2050-2059 – 2000-2009)  KIT, Institute of Meteorology and Climate Research  30 Agricultural Impact Studies for EA RICE-EA workshop, Nairobi, Kenya 17.04. – 19.04.2012 Moore et al., 2012 Heterogeneous responses in climate can result from homogeneous climate drivers   Effects of LUC/LCC can significantly influence crop yields (similar order than GHG effects)  Process-based fine resolution framework needed to capture this variability Regional variability may be masked at large scale (food production risk mainly associated to extreme events) In agreement with Jones and Thornton, 2003; Thornton et al., 2009  KIT, Institute of Meteorology and Climate Research  31 Agricultural Impacts in EA Growing season e.g. in Ethiopian highlands may lengthen (Thornton, 2006)  By the 2080s, a significant decrease in suitable rainfed land extent and production potential for cereals is expected  (Fischer et al., 2005) Semi-arid to arid could increase by 5-8% (60-90 million ha) Wheat production is likely to disappear  By end of 2030, Kenyan maize yields are predicted to increase / decrease depending on the location, yields changes relatively low <500 kg/ha (Mati, 2000) RICE-EA workshop, Nairobi, Kenya 17.04. – 19.04.2012 KIT, Institute of Meteorology and Climate Research  32 ΔProduction (2020-2039 – 1980-1999) Lobell, 2008  Hunger importance ranking (HIR):  Red: more important Orange: important Yellow: less important 20 GCM projections, 3 scenarios and statistical crop models RICE-EA workshop, Nairobi, Kenya 17.04. – 19.04.2012 KIT, Institute of Meteorology and Climate Research  33 Research Gaps: Agricultural Impact Modeling Number of model applications for rice in EA  Model implementation:  Plant pests/diseases (type and prevalence of pests) Extremes: temperature thresholds Parameterization of new varieties (NERICA) Improved (adapted) management options (Planting date, SRI)  Lack of coupled approaches for adaption / risk reduction: → Integrated climate-water-crop-economic approach accounting for global, regional, and local projections  Discrepancies field experiments and model results (e.g. CO2 fertilization effect)  RICE-EA workshop, Nairobi, Kenya 17.04. – 19.04.2012 KIT, Institute of Meteorology and Climate Research  34 Research Gaps: Impact Modeling (cont.’d) Lobell et al., 2009 What is the potential yield in EA under present and future conditions? Identification of reasons for YGM  to improve the models, but also to improve the yields of the farmers   Yield Gap (YGM) → min. ! RICE-EA workshop, Nairobi, Kenya 17.04. – 19.04.2012 KIT, Institute of Meteorology and Climate Research  35 RICE-EA workshop, Nairobi, Kenya 17.04. – 19.04.2012 KIT, Institute of Meteorology and Climate Research  36  Dr. Patrick Laux - PICREVAT workshop Embu (Kenya) 20.02.2012 KIT, Institute of Meteorology and Climate Research  37  Dr. Patrick Laux - PICREVAT workshop Embu (Kenya) 20.02.2012 KIT, Institute of Meteorology and Climate Research  38 Motivation RICE-EA cont. Dr. Patrick Laux - PICREVAT workshop Embu (Kenya) 20.02.2012 Source: IPCC AR4, 2007 KIT, Institute of Meteorology and Climate Research  39 Dr. Patrick Laux - PICREVAT workshop Embu (Kenya) 20.02.2012 KIT, Institute of Meteorology and Climate Research  40 Dr. Patrick Laux - PICREVAT workshop Embu (Kenya) 20.02.2012 KIT, Institute of Meteorology and Climate Research  41  Dr. Patrick Laux - PICREVAT workshop Embu (Kenya) 20.02.2012 KIT, Institute of Meteorology and Climate Research  42 Dr. Patrick Laux - PICREVAT workshop Embu (Kenya) 20.02.2012 KIT, Institute of Meteorology and Climate Research  43 Motivation RICE-EA Poor rains in last two seasons have led to one of most severe droughts in EA (food insecurity across Kenya, Ethiopia, Somalia, Uganda, Djibuti)  Climate plays crucial role in day-to-day economic development of Africa particularly for agricultural and water resources sector at different scales (regional, local, household)  Agricultural productivity, one of most important factors for food security, strongly linked to climatological conditions in EA (mostly seasonal rainfall amount, but also intraseasonal distribution of rainfall)  Agriculture already challenging under present climatic conditions: Impact of climate change?    Dr. Patrick Laux - PICREVAT workshop Embu (Kenya) 20.02.2012 KIT, Institute of Meteorology and Climate Research  44 Motivation RICE-EA cont. Dr. Patrick Laux - PICREVAT workshop Embu (Kenya) 20.02.2012 Many studies dealing with impact of climate change on crop productivity on different scales (e.g. Lobel, 2008, Laux et al., 2010)    Rare number of studies accounting for additional factors such as changes in supply patterns under different trade scenarios (Lotze-Campen et al., 2010), consumption, prices, and trade (Nelson et al., 2009)   Missing studies accounting additionally for regional and local supply-and-demand projections     KIT, Institute of Meteorology and Climate Research  45 20-Jun-12 Food Security FOOD UTILISATION FOOD  ACCESS • Affordability • Allocation • Preference • Nutritional Value • Social Value • Food Safety FOOD  AVAILABILITY • Production • Distribution • Exchange KIT, Institute of Meteorology and Climate Research  46 Agricultural facts … Dr. Patrick Laux - PICREVAT workshop Embu (Kenya) 20.02.2012   Population Area GDP   Total Density Active in Agriculture Total Cultivated Per Capita  Agric. Fraction    (1000 inh.)  (inh./km2) (%) (1000 ha) (%) (US$) (%) Europe 732,396 32 6 2,300,711 13 29,026 2 Africa 981,127 33 54 3,004,568 8 1,592 16 SSA 817,158 34 59 2,429,279 9 1,222 18 EA 211,414 72 77 292,718 14 481 33 Source: FAO-AQUASTAT, 2010 KIT, Institute of Meteorology and Climate Research  47 Agricultural facts … cont. Dr. Patrick Laux - PICREVAT workshop Embu (Kenya) 20.02.2012   Area equipped for irrigation (mio ha) Irrigated land (% of cultivated land)   1970 1990 2009 1970 1990 2009 Europe 15.1 25.7 22.7 4.6 8 7.7 Africa 8.4 11 13.6 4.7 5.4 5.4 SSA 4.1 5.9 7.2 2.6 3.3 3.2 EA 0.2 0.4 0.6 0.7 1 1.5 Source: FAO-AQUASTAT, 2010 KIT, Institute of Meteorology and Climate Research  48   Agricultural facts … cont. 20.02.2012 Dr. Patrick Laux - PICREVAT workshop Embu (Kenya) Source: FAO-AQUASTAT, 2008 Water withdrawn for Agriculture  KIT, Institute of Meteorology and Climate Research  49 Lack of Information for (East) Africa Dr. Patrick Laux - PICREVAT workshop Embu (Kenya) 20.02.2012 KIT, Institute of Meteorology and Climate Research  50 Climate: Impacts on human Health  Drouhts/Floods contribute to deseases such as diarrhoea, cholera (Few et al., 2004)  through poor nutrition  Malaria is spreading into new areas such as highlands of Central Kenya (Chen et al., 2006; Pascual et al., 2006)         Dr. Patrick Laux - PICREVAT workshop Embu (Kenya) 20.02.2012 KIT, Institute of Meteorology and Climate Research  51 Increased Vulnerability EA Malaria transmission: Increased temperature and rainfall in Northern sector (during SON) will increase malaria transmission by reduction in larval development length LUC: swamp reclamation for agricultural use, deforestation in highland of western Kenya (Munga et al., 2006; Afrane et al., 2005)    Dr. Patrick Laux - PICREVAT workshop Embu (Kenya) 20.02.2012 KIT, Institute of Meteorology and Climate Research  52 Complementary material to RCM simulations by KMNI  Dr. Patrick Laux - PICREVAT workshop Embu (Kenya) 20.02.2012 KIT, Institute of Meteorology and Climate Research  53 Health Aspects Dr. Patrick Laux - PICREVAT workshop Embu (Kenya) 20.02.2012 Source: IPCC AR4, 2007 KIT, Institute of Meteorology and Climate Research  54 Dr. Patrick Laux - PICREVAT workshop Embu (Kenya) 20.02.2012 

State-of-the-art in climate modelling and CC impact analysis in EA

https://publikationen.bibliothek.kit.edu/230087639/3816100

State-of-the-art in climate modelling and CC impact analysis in EA

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