Annual meeting of the Indian Academy of Science, University of Hyderabad, Hyderabad, November, 8-10, 2019.

Chandra Venkataraman, Prashant Dave, Kaushik Muduchuru, Nitin Patil, Arushi Sharma, Mani Bhushan, Arpita Mondal

Interdisciplinary Programme in Climate Studies andDepartment of Chemical EngineeringIndian Institute of Technology Bombay

Pollution particles influence intraseasonalrainfall suppression and high temperature extremes in the Indian region

Monsoon rainfall weakening linked to an asymmetric inter-hemispheric energy balance change attributed to:- Aerosol enhancement [e.g.

Bollasina et al. 2011; Ganguly et al. 2012a; Krishnan et al. 2015; Salzmann et al. 2014; Guo et al. 2016].

- western Indian ocean SST warming [Zhou et al. 2008; Roxy et al. 2014 and 2015].

Short-term rainfall enhancementfrom fast responses to radiative effects of non-local absorbing aerosols [Lau et al.2006, Vinoj et al., 2014].

Thermodynamic, convection and circulation adjustments influence rainfall weakening [Ramanathan et al.2005; Randles and Ramaswamy, 2008; Ganguly et al. 2012b].

(70°–90°E, 10°–28°N)

Krishnan et al., 2015

Influence of different forcing elements on the South Asian monsoon

Vinoj et al. 2014

Ganguly et al. 2012a

Roxy et al. 2015

Hot extremes in India, aerosol-surface temperature links• North and Central India heat

waves: linked with North-Atlantic blocking related anticyclonicconditions (Ratnam et al., 2016); subsidence over north India, depleted soil moisture, reduced precipitable water content, clear skies (Rohini et al., 2016).

• Surface temperature cooling results from aerosols, largely sulphates, in many world regions (Koch et al. 2009; Kloster et al. 2009; Zanis et al. 2012; Mickley et al. 2012; Pere et al. 2011)

• Cooling trends in the dry season, were linked to absorbing aerosols, with caveat that local cooling must be balanced by non-local warming. (Krishnan & Ramanathan, 2002).

• Low-altitude black carbon or increased aerosol absorption linked to surface warming through diabatic heating (Ban-Weiss et al. 2012; Panduthurai er al. 2008).

Pere et al. 2011

Ban-Weiss et al., 2012

Krishnan and Ramanathan 2002Bash et al., 2017, SREP

IMD Surface temperature Trends during 1969-2005

T2m = -0.3 0.06K

Aerosol influences on clouds, atmospheric conditions and rainfall

Observational studies to statistically extract aerosol effects on monsoon suppression:

Causal effects of aerosols on intra-seasonal monsoon suppression.

General circulation modelling to understand mechanisms of aerosol influences on seasonal scales:

Disentangling aerosol and SST influences on monsoon rainfall change.

Correlation analysis of daily in-situ and satellite observations, to link aerosol enhancement (AOD, AAI) to cloud properties, atmospheric variables and rainfall (CDER, LTS, rainfall), in regions of high/low aerosol & rainfall (HL/LL).

Granger causality and path analysis.

Dave et al. 2017, Scientific Reports (Nature publishing group)

Low aerosol low rainfall cluster

Observational analysis of aerosol-cloud-rainfall & aerosol-temperature interactions

Aerosol enhancement Granger causes intraseasonalsuppression of lagged daily rainfall

AOD

Precipitation

Significance: AOD increase is said to Granger cause rainfall decrease, if inclusion of pastinformation of both AOD and rainfall gives statistically significant improvement in theprediction of rainfall, as compared to only inclusion of past information of rainfall.

Ano

mal

y

1 10 20 30 40 50 60 70 80 90 100 110 120 Days

AOD and AAI increases had causal influence on decreases in rainfall, with lag times of 1-5 days, in high aerosol – low rainfall regions, 3-4 times a season. The effects manifested in 2004, 2009 (deficient monsoon) but

also in 2005 (normal monsoon).The behavior was absent in the low aerosol – low rainfall regions.Dave et al. 2017, Scientific

Reports.

Lag: 5 days

Increases in atmospheric stability, horizontal divergence of moisture and reduced convection, reduced cloud drop size, in high aerosol-low rainfall regions.

Behaviour absent in low aerosol-low rainfall regions.

Path analysis uncovers mechanism of aerosol induced intra-seasonal monsoon rainfall suppression

Higher frequency of breaks and longer break spells in HL regions

In HL vs LL regions total break days and number of break episodes were higher.Break episodes longer than 7 days were more frequent in HL region.Long break spells linked to rainfall deficits and drop in food-grain production in the second half of the 20th

century.

Monsoon breaks: Precipitation anomaly remains below threshold value consecutively for specified number of days.

SST & Sea Ice(AMIP)

General circulation

Model (ECHAM6)coupled with

AerosolModule (HAM2)Emission Inventory

(AMIP)

T63L31 1.8o x 1.8o

31 levels (surface to 10 hPa)

Disentangling SST and aerosol influences on South Asian monsoon rainfall: ECHAM6-HAM2

Patil et al. 2018, Climate Dynamics

Experiments Inputs and Simulation SetupESSTEaero: Evolving SST, Evolving Aerosols and GHGs.

Prescribed Emissions: evolving anthropogenicaerosols BC, OC, and SO2 (AEROCOM); evolvingannual mean GHGs.Prognostic Emissions: DMS, Dust, and Sea Salt.Evolving SST/SIC: Monthly AMIP observationaldatasets.Fixed land surface scheme, JSBACH.Model simulations: 1971-2010, three year spin-up, three-member ensemble, perturbed initial conditions.IITB HPC (192 cores, 12 nodes), supported by the DST-CoE in Climate Studies, IIT Bombay.

CSSTEaero: Climatological SST, Evolving Aerosols and GHGs.Haero: High Aerosols fixed at 2010, Evolving SST, GHGs.Laero: Low Aerosols fixed at 1971, Evolving SST, GHGs.

Sea surface temperature evolution induces observed drying pattern over subcontinent & adjoining oceans: July-Aug (1971-2010)

ClimatologySSTEvolvingaero EvolvingSSTEvolvingaero

Climatological SST: induces increasing rainfall trends over west of 80E and overArabian Sea and Bay of Bengal.

Evolving SST induces a significant drying trend over most of the subcontinent andadjoining ocean.

Captures spatial drying trends observed during 1950-2010.

Rainfall Trends show drying in response to SST

mm

day-1(40 yrs -1)

ClimatologySSTEvolvingaero EvolvingSSTEvolvingaero

in r

Increased aerosol levels induce intensification of modelled drying trend over peninsular India: Jul-Aug, 1971-2010

Aerosol levels of 2010 vs 1971, superimposed on SST forcing, causeintensification of drying in the peninsula during July-Aug.

mm day-1 (40 yrs-1)High Aerosols – 2010 levels

mm day-1 (40 yrs-1)Low Aerosols – 1971 levels

Patil et al. 2018, Climate Dynamics

Aerosol induced weakening of convective & stratiformrainfall : July-August Δ(Haero–Laero)

Increased atmospheric warming & surface

coolingStabilization along with

reduced evaporation

Stabilization suppresses convective instabilities

reducing convective rainfall

ΔLTS DegCΔEvaporationmm day-1

ΔConvective Rainfall mm day-1 Δ Stratiform Rainfall mm day-1

ΔMSLP & Winds @850hPahPa

BoB cyclonic circulation opposes

monsoon onflowReduced stratiform

rainfall over peninsular India

Absorbing aerosol influence on temperature maxima and heat wave eventsObservational studies to statistically extract aerosol effects on heat waves:

Links of local and non-local absorbing aerosol enhancement to extreme temperature events.

General circulation modelling to understand mechanisms of aerosol influences:

Pathways of absorbing aerosol modulation of high temperature extremes.

Tmax-AAI positive correlation on the temporal scale of heat-wave events (total20 heatwave events identified in Ratnam et al., 2017; Rohini et a., 2017) withAAI-NWI and AAI-CI.Correlation of Tmax with surface pressure is not statistically significant while itis statistically significant and positive with AAI-NW and AAI-CI.Increase in AAI itself augments the increase in temperature.During heatwaves which are associated with atmospheric blocking, role of AAIin exacerbating the heatwave conditions cannot be ruled out.

Heat-wave correlation between Tmax-NWI with AAI-NWI (local) and AAI-CI (non-local) (20 events during 1979-2013)

0.50.250.0-0.25-0.5

0.50.250.0-0.25-0.5

0.50.250.0-0.25-0.5

LOCAL AAI EFFECT NON-LOCAL AAI EFFECT

Dave et al. 2019, under revision

Causal effects of local and non-local absorbing aerosols on Tmax in NW India

Between 1979-2013 (35 years), heat-waves were recorded in 20 years.

For 9 years, local aerosol causality AAI-NW to Tmax-NW.

For 11 years, non local aerosol causality, AAI-CI to Tmax-NW.

In all cases, causality from Tmax to AAI was absent.

Plots are shifted as per the lag (3-days in this case).

EXAMPLE 1981: AAI-NW and AAI-CI leading Tmax-NW, by 3 days, respectively The smoothed curves are generated using loess method with span of 0.75 and the grey region depicts 95% confidence interval.

Analysis of composite of hot composite vs climatology:ECHAM6-HAM2 GCM

1981

2010

1982

Spatial Domain 1981-2010

Monthly Std. Anomalies

=−

Monthly Std. Anomalies (Tmax)

Pro

bab

ility

Hot composite = top10% of Tmax

anomaly distribition

Constraints on hot composite

At each pixel, composite is statistically distinguishable from the 1981-2010 climatological mean at 95% confidence level using 2-tailed Students t-test.Different calendar years, to ensure that they do not belong to the same hot spell

IMD Model

Composite of Tmax anomaly

Stippling shows statistical significant anomalies

4

2

0

-2

-4

(c)1

0.8

0.6

0.4

0.2

0

Anomaly correlation coefficient

Mondal et al. 2019, under revision

Anomalies in large-scale atmospheric features during hot extremes: hot_composite - climatology

Geopotential Height at 500 hPa Cloud Fraction

Vertical Velocity at 500 hPa Relative Humidity at 850 hPa

GCM simulations show anticyclonic blocking patterns suppress convection, enhance subsidence. Clear skies and dry conditions persist.

(m)

Aerosol forcing adds energy to atmosphere; heats surface layer: HotComposite-Climatologyp ggggyyy

• Positive atmospheric radiative forcing adds energy; negative single scatter albedo(more absorbing aerosols); enhanced shortwave heating rate 0.2–0.7 K/day.

• Consistent with pre-monsoon observational studies (Ahmedabad, Udaipur, Trivandrum, Delhi) of 0.6-1.3 K/day (Das et al., 2011; Rajeev et al. 2010; Pandithurai et al. 2008).

• Convention: Difference positive (negative) shows lower (higher) magnitudes.• Lower latent heat flux (lower evaporative cooling), but higher sensible heat flux (higher

LST, heat flow from ground).• Both flux changes are consistent with surface T increases.

Policy measures to mitigate climate change impacts of pollutants

Warming short lived climate pollutants (wSLCPs): warm the atmosphere for 1-2 decades after emission; effects are typically much larger than that of CO2; emission mitigation can deliver immediate atmospheric cooling.Include absorbing aerosol: black carbon or BC; precursor gases: CO, NOX , NMVOCs.Cooling SLCPs: SO2, organic carbon OC; mask atmospheric warming.Reportable to Climate and Clean Air Coalition, Arctic Council, UNFCCC (MPG, CoP-24, Katowice, 2018).

SMoG-India (Speciated Multi-pOllutant Generator): Emissions inventory data management and future emissions scenario generation system, IIT Bombay:

Evaluate ongoing programs including clean energy (Ujjwala, Saubhagya) and air pollution control (national program for management of crop residues NPMCR, emission regulations for brick kilns) to deliver SLCP mitigation.

FGD in power plants, BS-VI normsfor transport, PAT measures inindustry: primarily reduces SO2,unmasks warming.

Solar devices, low emission brickkilns, curbs on agr. Res. Burning;shifts to LPG cooking andelectric/solar lamps: reduces BCand precursor gases, reducedwarming.

Mitigating short-lived climate pollutants (SLCPs)

Evolution of Emissions ReductionPotential (ERP)

ERP

(GtC

O2-e

)

Solar devices (National solar Mission)Zigzag-fired bricks (Emissions standards); Ban on agricultural residue burningLPG cooking (Ujjwala Yojana); Household electrification (Saubhagya scheme)

FGD in powerplants; Energy conservation in industries (PAT); BS-VI norms for vehicles

GWPi = global warming potentialai = radiative efficiency ci(t) = time decaying concentration

Essential to monitor and evaluate these programs under climate reporting framework of NAPCC/SAPCC:• PMUY: affordable refills; expansion of distributing network; raising awareness. • Saubhagya: affordability; metered connection; “last-mile” connectivity.• NPMCR: On-site residue management; financial support for sowing machinery. • BRC_ES18: Technical assistance to brick manufacturers; financial support for

small-scale producers.

Synergizing clean energy & air quality programs with national climate agenda

ConclusionsCausal effects of aerosols lead to repeated intra-seasonal monsoonrainfall suppression, with aggravation of monsoon break conditions.Aerosol level increases act through different mechanisms than SSTchanges to weaken monsoon rainfall in GCM simulations.Tmax increases in NWI linked to causal effects of absorbing aerosolsenhancements in NWI (local effect) and in CI (non-local effect).High temperature extremes in NW India linked to increasedabundances of absorbing aerosols (BC and dust), enhancement inshortwave heating rate, reduced latent and increased sensible heatflux in GCM simulations.Traditionally, anthropogenic aerosols have been linked to airpollution; we must address their synergistic impacts on bothclimate and air pollution on regional scales.Identification of policy and regulation measures to mitigatewarming short-lived climate pollutant emissions:

Imperative to bring PUMY, Saubhagya, NPMCR, brick kilnemission standard implementation under reportingframework of NAPCC / SAPCC.

Thank you, questions welcome!

EXTRA SLIDES

Absorbing aerosols-temperature trends (spatially averaged for heatwave years)

Seasonal trends of spatially averaged AAI-NW, AAI-CI and Tmax-NW absolute andanomaly for heatwave years during period 1979-2013

There is an increase in AAI-NW, AAI-CI and Tmax-NW with a rate of ~0.019 yr-1,~0.016 yr-1 and ~0.026 oC-yr-1 respectively

The Mann-Kendall regression also showed significant positive trends of AAI-NW,AAI-CI and Tmax-NW

Tmax and Absorbing aerosols trends for 1979-2013

Tmax trend AAI trend

Tmax anomaly trend AAI anomaly trend

Seasonal average of Tmax(averaged for March-June) and AAI

Tmax is increasing at an approximate rate of 0.04 oC-yr-1

Increase in AAI is spread across the whole country with approximate rate of increase in absolute AAI is 0.03yr-1

Surface energy balance

Reflected Shortwave Radiation (S↑)

Incoming Shortwave Radiation (S↓)

Outgoing Longwave Radiation (L↑)

Latent heat flux (LE)

Sensible heat flux (H)

Ground flux (G)

Incoming Longwave Radiation (L↓)

The surface energy balance can be written as:= + LE + H +G

heat capacity of the layer, H is the sensible heat flux, LEthe latent heat flux, G is the ground heat flux and the net radiation:

= (1 - ) + -, are surface albedo/emissivity, , the downwelling shortwave/longwave

radiation. The turbulent heat flux:= - | |( )

is the heat transfer coefficient; TL temperature at top of model surface atmosphericlayer; is horizontal wind vector. is obtained from Monin-Obukhov similarity theoryby integrating flux profile relationship over lowest model layer.

(Roeckner et al., 2003)

Comparison to observationsRainfall seasonal cycleTrend in model and IMD rainfall anomaly

(70oE-90oE, 10oN-28oN) 1971-2010 climatology

Decreasing trend in rainfall anomaly both in model and IMD.Seasonal cycle shows underprediction in JAS (IMD obs).Spatial distribution (land points) has better agreement with IMD inpeninsular region, but significant over-prediction over Himalaya.

Months

Model vs. IMD: MNB=1.75, IA=0.85, RMSE=2.15

Months

AOD and AAI have causal effects increasing stability and decreasing CDER

AOD and AAI increases had causal influence on decreases in lagged lapse rate and CDER in the high-aerosol, low-rainfall, HL cluster, with lag times of 1-5 days. The behavior was absent in the low-aerosol low-rainfall, LL cluster.CDER suppression bore a 1-4 day lag to aerosol enhancement – suggests a

radiative effect. These effects manifested in several years (2004, 2005, 2009).

1 10 20 30 40 50 60 70 80 90 100 110 120 Days

Ano

mal

y

AOD-lapse rate

AAI-lapse rate

AOD-CDER

NDC: Nationally determined contributions; NAPCC: National action plan on Climate change; PAT: Perform,Achieve and Trade Scheme; NSM: National Solar Mission; TPP_ES16: Thermal power plants emissionsstandards 2015; BRC_ES2018: bricks emission standards 2018; TRA_ES16: Transport emission standards2016; NPMCR: National Policy for Management of Crop Residue; BGI: Biomass Gasifiers for industries;NEMM: National Electric Mobility Mission; PMUY: Pradhan Mantri Ujjwala Yojana; SAU: Saubhagya scheme

Aerosol optical & radiative effects: HotComposite-Climatology

∆ AOD ∆ BC AOD

∆ Dust AOD∆ Atm RF

0.25

0.1

0

-0.1

-0.25

0.3

0.2

0.1

0

-0.1

-0.2

-0.3

1.2

0.8

0.4

0

-0.4

-0.8

-1.2

W/

m2

0.003

0.002

0.001

0

-0.001

-0.002

-0.003

During hot extreme months, positive differences in AOD. Consistent with pre-monsoonaerosols in northern India (Das & Jayaraman 2011; Dey et al. 2004 ).

• During hot extremes, positive differences in BC-AOD and dust-AOD, ATM radiative forcing of 3-12 W/m2, ATM radiative forcing efficiency ( F/AOD-550), 8-29 W/m2.

• Consistent with enhancement in absorbing aerosol abundances, instantaneous ATM forcing efficiency, during European heat-waves (Lyamani et al. 2006; Chazette et al. 2017).

Higher AOD

Enhanced BC and Dust AOD

Enhanced aerosol ATMradiative forcing and

forcing efficiency

The strength aerosol radiative pathway, suppressing rainfall through stabilization (lapse rate), was comparable to moisture availability (CWV) pathway enhancing rainfall (path coefficient magnitude).The microphysical pathway suppressing rainfall, manifested only in 2005, with a weak effect, compared to the moisture effect.

Relative strength of moisture availability and aerosol effects: Microphysical (CDER) and radiative pathways (Lapse Rate)

HIGH AEROSOL-LOW RAINFALL, HL