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IUKWC Workshop Nov16: Developing Hydro-climatic Services for Water Security – Session 5 – Item 2 - S_Tripathi


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IUKWC Workshop Nov16: Developing Hydro-climatic Services for Water Security – Session 5.2 edited Sachchida Nand Tripathih

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IUKWC Workshop Nov16: Developing Hydro-climatic Services for Water Security – Session 5 – Item 2 - S_Tripathi

  1. 1. Sachchida Nand Tripathi Department of Civil Engineering Indian Institute of Technology, Kanpur, India Coupling of aerosol-land-cloud-rainfall system over Gangetic Plains: Observations and modelling analysis 1Nov, 2016 Indo-UK water workshop, Pune
  2. 2. We gratefully acknowledge the financial support given by the Earth System Science Organization, Ministry of Earth Sciences, Government of India (grant MM/NERC-MoES-03/2014/002) and Newton Fund to conduct this research under Monsoon Mission. Several other funding agencies (DST, MoES, MHRD, NCAR and several others) for providing financial support. IIT Kanpur for providing HPC facility for Model simulations  NASA for providing various satellite measurements Many graduate students in my group Acknowledgement Indo-UK water workshop, Pune 2Nov, 2016
  3. 3. Understanding the diurnality and interseasonality of Urban heat Island over Greater Kanpur Indo-UK water workshop, Pune 3Nov, 2016
  4. 4. Pre-monsoon (MAM) Monsoon (JJAS) UHI_canopyUHI_surface Diurnality of UHI effect at canopy and at surface Diurnal variation in the magnitude of UHI at canopy (ΔTc) for (a) dry (pre- monsoon), and (b) wet (monsoon) seasons. Similar plot for UHI at surface (ΔTs) for (c) dry (pre- monsoon), and (d) wet (monsoon) seasons. The dash- dot lines represent the mean sunrise and sunset times for the season. Significant nightime magnitude of ΔTc with values higher during the pre- monsoon season (3.6 oC during the pre-monsoon vs 2 oC for the monsoon). The value of ΔTs, on the other hand, is greater during the monsoon (5 oC during the monsoon vs 3.4 oC during the pre-monsoon). A B C D The value of the ΔTs is associated with the Δ (net radiation) and Δ (incoming longwave ) resulting in higher magnitude during daytime. The greater stored energy in urban structures, the differential cooling between the rural and the urban area, and a shallow, stable boundary-layer may together establish the magnitude of ΔTc at night Chakroborty, Sarangi and Tripathi., 2016, BLM Indo-UK water workshop, Pune 4Nov, 2016
  5. 5. Seasonal variation of enhanced vegetation index (EVI) over the urban and the rural station, Latent Heat flux over the urban and the rural station and ΔTs magnitude. EVI values represent the mean of four grid cells of 250 m 250 m surrounding the stations foreach 16-day period. LE values are the 16-day running averages from daily GLDAS/NOAH simulations. The ΔTs values are the monthly means ( one standard deviation) from in situ observations. Interseasonality of UHI effect at surface The inter-seasonality of ΔTs is primarily ascribed to the seasonal land-cover change of the rural area. The high values during the monsoon are due to faster cooling of the rural surface (compared to the urban area) due to higher latent heat flux for the rural site. Chakroborty, Sarangi and Tripathi., 2016, BLM Indo-UK water workshop, Pune 5Nov, 2016
  6. 6. Cloud resolving simulation of Aerosol-Cloud microphysics Interactions over Gangetic Basin Indo-UK water workshop, Pune 6Nov, 2016
  7. 7. Cloud Aerosol Interaction and Precipitation Enhancement Campaign (CAIPEEX) sorties on 23rd-25th August 2009 provided unprecedented collocated in situ measurements of aerosol and cloud microphysics over Gangetic Basin. WRF-Chem cloud resolving simulations with nested domain (27-9-3 km) from 20th – 29th Aug 2009 was performed to simulate these CAIPEEX observed convective clouds and associated aerosol-cloud interactions. The innermost domain is centered about the region of CAIPEEX sorties. We used Morrison double moment cloud microphysics scheme and MOSAIC 4 bin aerosol module for these simulations  Two aerosol sensitivity experiments were performed and compared to see aerosol-cloud interactions: 1. Low Aerosol Scenario, LAS ( default global MACCcity + INTEX-B anthropogenic emission rates) 2. High Aerosol Scenario, HAS ( 6 X LAS emission rates) WRF-Chem simulations of CAIPEXX observed convective clouds Sarangi, Tripathi et al., 2015, JGR 7Nov, 2016 Indo-UK water workshop, Pune
  8. 8. LAS Sor23 Comparison of spatially and temporally averaged (1200 UTC) modeled mean profile of different hydrometeor species for LAS and HAS runs during both sorties. 19.8.2015 8Aerosol-Cloud-Rainfall Aerosol-induced changes in Hydrometeor profiles  During the sortie of 23rd Aug, cloud microphysics was heavily dominated by ice phase hydrometeors while in case of the sortie on 25th Aug, liquid phase hydrometeors consists of major portion of cloud microphysics.  Increase in concentration of super cooled rain drops above freezing level (~ 5km) and increase in graupel concentration due to increase in aerosol loading is seen Sarangi, Tripathi et al., 2015, JGR 8Nov, 2016 HAS LAS HAS Sor25 Indo-UK water workshop, Pune
  9. 9.  Mean profiles of bias (HAS-LAS) in temperature and vertical wind speed for (a) 23rd Aug and (b) 25th Aug. Panels (c) and (d) illustrate corresponding mean difference in tendency of droplet condensation (CondC), auto-conversion of droplet to raindrops (Au) and formation of Graupel due to deposition (DepG) and rimming of rain drops (RimG) for 23rd and 25th Aug 2009. Increase in rate of exothermic processes like drop condensation near cloud base causes increase in updraft.  As a result more droplets are shifted upward across freezing line, which leads to increase in rate of Au, DepG and RimG above the freezing line Aerosol-induced increase in temperature at lower atmosphere below cloud layer (~1 km) leads to increase in CAPE ∼300 J/kg (∼50 J/kg) for Sor23(Sor25), which can also contribute partially to the increase in updraft. Aerosol-induced changes in Microphysical processes SOR23 SOR25 Sarangi, Tripathi et al., 2015, JGR 9Nov, 2016 Indo-UK water workshop, Pune
  10. 10. Observational analysis of Aerosol-Cloud-Rainfall- interactions over Gangetic Basin Indo-UK water workshop, Pune 10Nov, 2016
  11. 11. Data source Parameters Temporal resolution Time Period IMD** Accumulated rainfall Daily, 08:30 am – 08:30 am 2002-2013 MODIS Aqua L3 (c5.1) AOD, CF, CTT, CTP and CWV (IR) Daily, 1:30 pm local time 2002-2013 CLOUDSAT* 2B (V8) NC, WC, CER (both liquid- and ice- phase) Daily, 1:30 pm local time 2006-2011 TRMM* 3B42 (V7) Precipitation rate Daily, 12:00 pm local time 2002-2013 NOAA-NCEP GDAS Meteorological fields Daily, 11:30 am local time 2002-2013 CERES L3 (Edition 3A) TOA fluxes: Shortwave (0-5 µm) and Longwave (5-100 µm) Daily, 11:30 am – 2:30 pm local time 2002-2-13 Climatological mean of (left) accumulated daily rainfall, (middle) AOD and (right) cloud fraction for June through September 2002- 2013. The open square box indicates the Indian monsoon region used in our analysis. The inset shows the histogram density plot for all India accumulated daily rainfall. The median daily rainfall over the region was 6.3 mm/day Table: Summary of data products used in our analysis Region and data used in the analysis 11Nov, 2016 Sarangi , Tripathi et al., 2016, ACP, under review Indo-UK water workshop, Pune
  12. 12. Aerosol-Cloud Macrophysics association  Gridded datasets (1 deg x1 deg) of IMD’s Daily rainfall (DRF), TRMM’s Precipitation rate (PR) along with MODIS observed cloud fraction (CF), cloud top pressure (CTP) and cloud top temperature (CTT) were sorted as a function of MODIS observed aerosol optical depth (AOD), and averaged to create 50 scatter points for correlation analysis  All data samples of DRF, PR and cloud properties with collocated AOD measurements during 2002- 2013 were used  The analysis shows that with increase in aerosol loading clouds grow deeper and wider, indicating dominance of cloud invigoration phenomena over Gangetic Basin. The invigorating clouds results in intensification of PR and thereby in enhancement of daily accumulated rainfall.  The relations was found to be robust for different sub-regimes based on meteorological slicing, different regions and different cloud types. 12Nov, 2016 Sarangi , Tripathi et al., 2016, ACP, under review Indo-UK water workshop, Pune
  13. 13. Microphysical differences under high and low AOD scenario Observed differences in A) MODIS observed liquid-phase effective radius (Re), B) CLOUDSAT-observed ice-phase effective radius (Re, ICE) between low (AOD <33% percentile) and high aerosol loading (AOD >66% percentile). The dotted lines represent mean profiles and the thin lines represent 25th and 75th percentile. C) Difference (high AOD bin - low AOD bin) in mean profile of CLOUDSAT-observed (black) Liquid- and (pink) Ice-phase water content. Steeper growth in mean Re with increase in altitude before onset of warm rain (Re ~14 µm) indicate that rate of collision and coalescence is higher in low AOD bin. At the same time, mean Re, ICE is greater under high AOD bin indicating bigger ice particles Increase in AOD is also associated with great increase in ice phase mass concentration. 13 Sarangi , Tripathi et al., 2016, ACP, under review Indo-UK water workshop, PuneNov, 2016
  14. 14. WRF-SBM idealized simulations: Case study of typical rainfall A typical heavy rainfall event (23rd Aug 2009) near Patna is simulated using spectral bin microphysics module. The simulation is initiated with morning radiosonde over Patna and CCN values are prescribed as per CAIPEEX observations. Three simulations with CCN concentration of 2500/cc [Ex1], 5000/cc [Ex2], and 9000/cc [Ex3], at 0.4 % SS is performed. Figure shows A) Time evolution of column integrated domain averaged cloud water content (CWC; blue), rain water content (RWC; red), summation of ice water content, graupel water content and snow water content (IWC+GWC+SWC; black), vertical velocity (pink) and accumulated surface rainfall (green) for simulation Ex1. B) Same as Panel A, but for simulated differences between Ex2 and Ex1. C) Same as Panel A, but for simulated differences between Ex3 and Ex1. On a temporal scale Increase in CCN concentration causes initial suppression of warm rainfall , followed by increase in ice phase hydrometeors and eventually increase in rainfall Sarangi , Tripathi et al., 2016, ACP, under review 14Indo-UK water workshop, PuneNov, 2016
  15. 15. A significant urban heat island effect exists over greater kanpur and its diurnality and inter-seasonality can be explained by difference in surface energy components between city core and peripheral rural landscape. Urban land use can dictate the spatial distribution of surface rainfall precipitation over greater Kanpur. Urban core of greater Kanpur receives higher magnitude of rainfall than peripheral regions due to surface induced UHI effect which lead to wind convergence and moist convection. Increase in absorbing aerosol concentration can significantly perturb the surface energy flux partitioning by reducing sensible heat flux and thereby Bowen ratio. However, the partitioning is subject to soil and vegetation properties. Increase in aerosol can perturb the coupling between thermodynamics, cloud dynamics and microphysics, thereby resulting in cloud invigoration. Decadal analysis illustrate robust association between increase in aerosol and cloud macrophysics and microphysical properties, cloud radiative forcing and daily surface rainfall over ISMR. Increase in CCN concentration can cause initial suppression of warm rainfall, followed by increase in ice phase hydrometeors and eventually increase in rainfall causing spatiotemporal changes in rainfall Detailed consideration of aerosol radiative and microphysical processes is essential for NWP over Indian summer monsoon region Conclusions 15Nov, 2016 Indo-UK water workshop, Pune