Download - Climate Change: Why Worry?

April 19, 2023 Puerto Pérez 1

Climate Change: Why Worry?

Climate Change: Why Worry?

Primer Seminario de Investigación SANREM CRSP: Adaptación al Cambio en los Andes. La Paz, 24-

28 Abril, 2006

Anji Seth, University of Connecticut


F.A.Q.

F.A.Q.

How do we know climate is changing?

Doesn’t climate change naturally? So what’s the deal with Global

Warming? Can’t we wait to see what happens? Warmer temperatures would be kind

of nice…?


Doesn’t climate change naturally? So what’s the deal with Global

Warming? Can’t we wait to see what happens? Warmer temperatures would be kind

of nice…?





Austria





FIGURE [reprinted from Mann et al, 2003, Eos, (C) American Geophysical Union]. Comparison of proxy-based Northern Hemisphere (NH) temperature reconstructions (Jones et al., 1998; Mann et al., 1999; Crowley and Lowery, 2000)


Doesn’t climate change naturally?

Doesn’t climate change naturally?


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Yes!


So what’s the deal with global warming?

So what’s the deal with global warming?


Carbon Cycle BasicsCarbon Cycle Basics

Natural sources Natural sinks

Human sources


Carbon Cycle BasicsCarbon Cycle BasicsCO2

sources

CO2

sinks

atmospheric CO2








Can we wait to see, before taking action?

Can we wait to see, before taking action?

3 surprises


Surprise 1: Exponential increase

Surprise 1: Exponential increase

CO2

sources

CO2

sinks

atmospheric CO2






350

400

450

500

2006

2050


Surprise 2: FeedbacksSurprise 2: FeedbacksCO2

sources

CO2

sinks

atmospheric CO2 temperature

Feedbacks in the system amplify the temperature response


Surprise 3: Delayed response

Surprise 3: Delayed response

CO2

sources

CO2

sinks

atmospheric CO2 temperature

.75oC in pipelinebased on CO2

now in the atmosphere


Warmer temperatures would be kind of nice,

wouldn’t they?

Warmer temperatures would be kind of nice,

wouldn’t they?


Figure 9.5: (a) The time evolution of the globally averaged temperature change relative to the years (1961 to 1990) of the DDC simulations (IS92a). G: greenhouse gas only (top), GS: greenhouse gas and sulphate aerosols (bottom). The observed temperature change (Jones, 1994) is indicated by the black line. (Unit: °C). (b) The time evolution of the globally averaged precipitation change relative to the years (1961 to 1990) of the DDC simulations. GHG: greenhouse gas only (top), GS: greenhouse gas and sulphate aerosols (bottom). (Unit: %).


Mean Seasonal CycleMean Seasonal Cycle


Mean Seasonal Cycle: 69W, 15S


Prec Temp

WetDayFreq

FrostFreq




Prec Temp

WetDayFreq

FrostFreq


El Niño, Cold Pacific Events

El Niño, Cold Pacific Events


Summer Rainfall, Lake Increment

Summer Rainfall, Lake Increment



Garreaud & Aceituno (1999)

CRU gridded Precipitation data(Dec-Feb)

Lake level at Puno(Dec-Feb)


Altiplano Precipitation Variability

Altiplano Precipitation Variability

Garreaud & Aceituno (2001)




Precipitation Trends in AndesPrecipitation Trends in AndesVuille et al (2003)

Station Precipitation datatrends

Trends byaltitude




Temperature Trends in AndesTemperature Trends in AndesVuille et al (2003)

Station, gridded Temperature dataVariability, trends

Model simulatedTemperatureVariability, trends




Does RegCM3 add value when downscalingECHAM4.5 for South America?

(Sub-seasonal statistics)

Sara Rauscher (ICTP, Trieste)Anji Seth (U Connecticut, Storrs)

Brant Liebmann (NOAA/CDC, Boulder)Suzana Camargo & Joshua Qian (IRI, NY)

.

April 19, 2023 Puerto Pérez 32(Rauscher et al. 2006)

Daily Precipitation Frequency

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N. Amz S. Amz

Mon SE

NE ObservedNN-RegCMEC-RegCMECHAM

Regional model is as good or better that GCM in all but the N. Amazon region where a substantial dry bias is evident


Monsoon Rainy Season withdrawalImproved in RegCM3QuickTime™ and a

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Monsoon onsetAnd withdrawaldates

March Monsoon precipitation correlation with SSTa


Northeast Dry Spells



Regional model improvesthe dry spell frequencyin Northeast Brazil,especially during El Niño years.


South American MonsoonPrecipitation and Moisture Flux

in the SRES A2 Scenario

Maisa Rojas (U Chile, Santiago)Anji Seth (U Connecticut, Storrs)Sara Rauscher (ICTP, Trieste)

Acknowledgement: IPCC AR4 Modeling Groups and WG I for coordinating, archiving and making accessible the model integrations.


Monsoon: models capture the annual cycle.

Amazon: models simulate spurious semi-annual cycle, and delay/underestimate observed late summer (JFM) maximum.

Southeast: models underestimate summer rains (NDJF), reduce the amplitude of the annual cycle.

1970-2000 Monthly Precipitation


1970-2000 Monthly Moisture Flux Div. (Vertically Integrated)

Amazon: simulated semi-annual cycle in moisture flux divergence compared with annual cycle in reanalysis.

Monsoon: moisture flux convergence increases during onset of rains (SON) and levels off until end of rains(Mar). Models capture this.

Southeast: convergence is strong in summer (DJF) and weaker rest of year. Only 2 of 6 models simulate this.


Monsoon: Little agreement among models during rainy season (NDJFM). Drier early rainy season (SON), wetter late rainy season (JFM)?

Amazon: Little agreementamong models during onset of rains (SON). Most models suggest increased precipitation during middle/late rainy season (DJFM).

Southeast: General model agreement towards increased precipitation, especially in spring (OND).

(2070-2100)-(1970-2000) Monthly Precipitation


(2070-2100)-(1970-2000) Mon. Moist. Flx. Divg. (Vertically Integrated)

Amazon: model agreement increased convergence during middle/end of rainy season (DJFM).

Monsoon: Increased divergence in early rainy season (SON) and some agreement for increased convergence during themiddle/end of rainy season (JFM).

Southeast: model agreement in enhanced moisture flux convergence, especially in spring (OND).


Summary: South American Monsoon, SRES A2

Amazon: • Models simulate semi-annual, low amplitude, delayed rains.• There is little model agreement in precipitation change during rainy season onset (SON), due to delayed onset in simulations? • 5 of 6 models suggest increased precipitation during themiddle/late rainy season (DJFM) which is primary season in models.

Monsoon: • The annual cycle is well simulated. • There is little model agreement in precipitation change during the rainy season (Dec-Feb). • Possible shift in the timing of the rainy season (?), with drier conditions early and wetter conditions later, is consistent with projected changes in moisture flux convergence.

Southeast: • Models underestimate summer precipitation (NDJF).• Models show general agreement towards increased precipitation, especially in spring (OND). • Consistent with observed trend (Liebmann et al, JCL, 2004)


Discussion: Wetter spring in Southeast & drier spring in Monsoon?

Although the results in the Monsoon region are more uncertain than those in the Southeast, there is some suggestion in the models towards drier early season and wetter late season in the monsoon region. The projected increase in precipitation in the Southeast is supported by model agreement and observed recent trends (Liebmann et al, JCL 2004).

The difference between Monsoon and Southeast regions in spring could imply a southward shift in the SACZ during early season (OND) (see Nogues-Paegle and Mo, JCL, 1997), and is perhaps related to strengthening of the Atlantic subtropical high. We do see a strengthening of the high in the model runs (not shown), which would have implications for moisture transport flux convergence into the Southeast.

Moisture flux convergence changes seen here are consistent with this hypothesis.