Jose A. Marengo CEMADEN, Brazil

jose.marengo@cemaden.gov.br

Painel 4 - Variações e extremos Climáticos sobre a América do Sul: aspectos

continentais e regionais

January-July 2015: Global Temperature: +0.85°C (record warm) Was record warm for the year-to-date

Land Temperature : +1.34°C (record warm) Ocean Temperature: +0.67°C (record warm)

Land and Ocean Temperature percentiles

Source: NOAA National Centers for Environmental Information, State of the Climate: Global Analysis for July 2015, published online August 2015, retrieved on August 24, 2015 fromhttp://www.ncdc.noaa.gov/sotc/global/201507 (Adapted).

Jan-July 2015

South America +1.25°C was record warm for Jan–July

Asia was second warmest +1.86°C for Jan–July

o C oF

2015

Percentiles-Temperaturas continentales y oceanicas

Fuente: NOAA National Centers for Environmental Information, State of the Climate: Global Analysis for July 2015, published online August 2015, retrieved on August 24, 2015 fromhttp://www.ncdc.noaa.gov/sotc/global/201507 (Adapted).

Invierno Junio-Agosto 2015

Economic loss events worldwide 2014 Geographical overview

Un clima cambiante puede llevar a cambios en eventos extremos de tiempo y clima

5 IPCC SREX 2012

Impactos de los eventos extremos de tiempo y clima dependen de : naturaleza y severidad del evento, vulnerabilidad, exposicion ,

Un clima cambiante puede llevar a cambios en eventos extremos de tiempo y clima

6 IPCC SREX 2012

Impactos de los eventos extremos de tiempo y clima dependen de : naturaleza y severidad del evento, vulnerabilidad, exposicion ,

Local robust trends estimated annually for the 1969–2009 period for cold nights (upper left plot), cold days (upper right panel), warm nights (bottom left panel) and warm days (bottom right panel),

Skansi et al (2013)

Skansi et al (2013)

55.3%

12.3%

8.4%

8.9%

8.4%

1% 4%

1.7% Inundação Escorregamentos Estiagem Tempestades Incêndios Temperaturas extremas Terremotos Epidemias

Desastres Naturais no Brasil

Underlying Drivers of Disaster Risk

Source: IBGE, 2010

Over 5 million people mostly poor and vulnerable living

In areas of high disaster risk in Brazilian cities

Urban Growth: change from rural to urban population

Natural disaster of 11-12 January 2011 in the mountains west of Rio: over 900

fatalities and a catalist to DRR policies focused on

preventionCreation of CEMADEN

Source: Brazilian Atlas of Natural Disasters 1991-2012

Risk factors • more variable rain • hotter days

• Old infrastructure • Increase of water

use without regulation during a water stress situation

• Lack of political will, treating the situation as “temporary”

Risk Management/Adaptation • Improved water

management • Water stress

monitoring

• Drought forecasting

• Other sustainable options: desalinization, water trucks, recycled water, etc

Managing the risks: drought in the context of water and energy security (water crises) in large

cities Climate related

Natural Disasters and Population

Source: IBGE, 2010

*Source: Brazilian Atlas of Natural Disasters 1991-2012

Seasonal rainfall anomalies 2013-2105 in SE Brazil

D13JF14 D14J15

Sao Paulo

Marengo et al 2015

Munich Re 2015

Sistema Cantareira: Precipitação

Qual o período de recorrência que a estrutura de abastecimento de

megacidades como São Paulo deve levar em consideração?

Inundação no norte do país – Porto Velho

BR-364 Nível do rio Madeira na estação Porto Velho (ANA) 01/jan a 02/jun de 2014

O rio subiu 3 metros acima da cota de transbordamento.

Abunã

2014

1997

Máxima (2008-2013)

transbordamento

A reconstrução da infraestrutura de

estradas, portos fluviais, etc, deve levar em conta o nível alcançado pelo rio

em 2014?

Drought in Northeast Brasil since 2013: 15 million people affected!!!

The Evaluation of the 2011-2015 Drought in the Brazilian

Semiarid Region

Observational Data Interpolated – Percentiles of precipitation (Dataset: 17 years)

Monitoring Vegetative Drought (Remote Sensing)

Normalized VSWI

anomalies (%)

Dry

Very dry Dry Normal Wet Very wet

Projected changes in temperature and Precipitation to South America 2046-2065 and 2081-2100 for low (RCP2.6) and high (RCP8.5) emission scenarios

Annual Temperature Annual Precipitation mid-21st Century

RCP8.5 RCP8.5

RCP2.6

late-21st Century mid-21st Century late-21st Century

RCP2.6

RCP8.5 RCP8.5

RCP2.6 RCP2.6

Difference from 1986-2005 (%) Difference from 1986-2005(oC)

2046-2065

2046-2065

2046-2065

2046-2065

2081-2100

2081-2100 2081-2100

2081-2100

Change in temperature (oC)

TXx CMIP5

Robust spatially aggregated projections of climate extremes E. M. Fischer, U. Beyerle and R. Knutti

TXx CESM-IC

TNn CMIP5

TNn CESM-IC

Intensity of hot extremes (TXx): the annual maximum value of daily maximum temperature

Intensity of cold extremes (TNn), the annual minimum value of daily minimum temperature

2041–2060 with respect to 1986–2005 for the RCP8.5 scenario

Heavy precipitation intensity or maximum accumulated five-day precipitation (RX5day): the annual maximum value of precipitation amount in mm for the five-day interval.

Relative change in heavy precipitation (%)

Change in dry spell length (days)

Robust spatially aggregated projections of climate extremes E. M. Fischer, U. Beyerle and R. Knutti

2041–2060 with respect to 1986–2005 for the RCP8.5 scenario

RX5day CMIP5

RX5day CESM-IC

CDD CMIP5

CDD CESM-IC

RCP 8.5

Dry spell length or consecutive dry days (CDD): PR is the daily precipitation amount in mm on day i in period j. Count the largest number of consecutive days per time period (here calendar year) where PRij<1 mm.

21

Extreme and non-extreme weather or climate events affect vulnerability and exposure to future extreme events

The most effective adaptation and disaster risk reduction actions are those that offer development benefits in the relatively near term, as well as reductions in vulnerability over the longer term

Disaster risk management and climate change adaptation can influence the degree to which extreme events translate into impacts and disasters

What is the return period of a floods as in W. Amazonia that should be considered on the planning an construction roads and housing Infraestructure rebuilt and construction of ports, roads, etc in West Amazonia, Should they consider the record river levels reached in 2014?

What is the return period of droughts as in 2013-15 and 2012-13 in Northeast Brazil and São Paulo that should be considered on the planning an construction of a reservoir system?

What lessons can be learnt from recent droughts in Melbourne, Barcelona, California and now Sao Paulo? Are they attributed to climate change?

Questions relevant to extremes and adaptation

Should climate extremes (droughts, floods) be considered ad threats to national security (ex. Drought in Syria in 2010 leading to current political and humanitarian crises?)

Are short term and seasonal extremes getting more “extreme”?, why?, global warming?, changes in variability? Are they predictable?