Continuous real-time analysis of isotopic composition of precipitation during tropical rain events using a diffusion sampler

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Continuous real-time analysis of isotopic composition of precipitation during tropical rain events using a diffusion sampler Shaoneng He 1, Nathalie Goodkin 1,2, Dominik Jackisch 1, and Maria Rosabelle Ong 2 1 Earth Observatory of Singapore, Nanyang Technological University, Singapore 2 Asian School of the Environment, Nanyang Technological University, Singapore

Why Tropical Precipitation Isotopes? These international efforts have significantly improved our knowledge of controls on isotopic compositions of precipitations and global climate change. Past & Present Precipitation Stations from Global Network for Isotopes in Precipitation (GNIP) operated by the International Atomic Energy Agency (IAEA) in cooperation with the World Meteorological Organization (WMO). Most are monthly-collection stations.

Why Tropical Precipitation Isotopes? Amount Effect Mode (white= temperature, black= precipitation) of the strongest climatological correlation at all stations (From Bowen, 2008) Long-term monthly and annual mean δ 18 O and precipitation amount from GNIP tropic island stations (Rozanski et al. 1993)

Why Tropical Precipitation Isotopes? Daily precipitation data from tropic islands From Kurita et al., 2009

Why Tropical Precipitation Isotopes? (a) Modeled (CAM2), (b) observed (GNIP), and (c) modeled-observed mean annual δ 18 O of global precipitation (Lee et al, 2007) In Southeast, south central Asia, and Africa, the modeled mean δ 18 O values are several < observed, and Amount Effect is believed overestimated by GCMs.

Why Tropical Precipitation Isotopes? Correlation between isotopes and rain amount: Correlation coefficients of inter-annual relationship between monthly anomalies of precipitation δ 18 O and precipitation amount (Risi et al., 2010) Model simulation overestimates the correlation of δ 18 O with precipitation amount, especially in the tropic region

Why Tropical Precipitation Isotopes? These divergent findings show how limited our understanding is of the spatial and temporal variations in stable isotopic compositions of present-day precipitation and complexities of atmospheric and climate processes in the tropics.

Why Tropical Precipitation Isotopes? In 2013, IAEA launched a new Coordinated Research Project (CRP): Stable Isotopes in Precipitation and paleoclimatic Archives in Tropic Areas to Improve Regional Hydrological and Climatic Impact Models (2013-2017). The focus is on isotope information of Past & Present Precipitation Stations from Global Network for Isotopes in present-day Precipitation (GNIP) precipitation operated by the International (daily) Atomic Agency (IAEA) in cooperation with the World Meteorological Organization (WMO). Most are monthly-collection stations.

Why Tropical Precipitation Isotopes? Participants of the 1 st new IAEA RCP Meeting, Dec. 2 to 5, 2013, Vienna

Why Tropical Precipitation Isotopes? Location & types of proposed projects for IAEA 2013 CPR (from IAEA) (They do not present the number of observation stations)

Network of rain stations in SE Asia Sumatra Regional map of SE Asia with the locations of rain stations

Two monsoons dominate the climate Monsoons: Winds at 925hPa DJF Asian Monsoon Austral Monsoon JJA Source: Atmospheric Re-analysis

Rain collection in Singapore Sumatra Sumatra Singapore Two types of collection: Daily Event Regional map of SE Asia with the locations of rain stations

Continuous Real-time analysis of rain events Panel for rain event Floating Switch Pump Pump expanded PTFE (eptfe) Diffusion tubing Samplerdeveloped for medical applications Picarro Analyzer L2130-i Dr. Niels C. Munksgaard James Cook University

Continuous Real-time analysis of rain events

Continuous Real-time analysis of rain events July 4, 2015 September 15, 2015 Isotope exchange and evaporation of rain drops Mesoscale subsidence in downdraft

Continuous Real-time analysis of rain events Time series of highest (red) and lowest (blue) δ-values observed in daily rain events El Niño La Niña The El Niño-Southern Oscillation (ENSO) involves fluctuating ocean temperatures in the equatorial Pacific. Two states: warmer than normal central and eastern equatorial Pacific SSTs (El Niño) and cooler than normal central and eastern equatorial Pacific SSTs (La Niña)

Continuous Real-time analysis of rain events Time series of the variation in δ-values in single event (blue) and daily all events(red) El Niño La Niña

Continuous Real-time analysis of rain events Time series of the initial δ-value in daily rain events El Niño La Niña Events with low δ-values normally have very low initial values. δ-value of precipitation reflect on-site convection and the convection at up-wind area. Therefore, regional organized convection leads to very negative δ-values!

Continuous Real-time analysis of rain events Normal conditions in the tropical Pacific Anomalous conditions (EI Niño and La Niño) in the tropical Pacific Karumuri Ashok and Toshio Yamagata (2009)

Continuous Real-time analysis of rain events Hovmöller diagram of ORL (Outgoing Long Wave Radiation) OLR has been used as a proxy of deep tropical convection, and OLR values correspond to cold and high clouds

Continuous Real-time analysis of rain events 2014 JJAS 2015 JJAS 2016 JJAS OLR Average during SW monsoon

Continuous Real-time analysis of rain events 2014-2015 DJF 2015-2016 DJF 2016-2017 DJF OLR Average during NE monsoon

Conclusions δ-value of precipitation during events exhibit two major patterns: V and W; δ-value of precipitation can significantly change during a single event, especially those related to regional organized convection; Time series of initial, highest and lowest δ- values show clear pattern corresponding to ENSO event;

Conclusions (continued) ENSO is the major drive for intra-annual variation in δ-value of precipitation in the region; δ-value of precipitation reflect the on-site convection and the convection at up-wind areas; Precautions should be taken when apply d- excess to track the moisture source in the tropical region.

Acknowledgements We would like to thank Dr. Niels Muksgaard from James Cook University who helps us build the DS system, and Kyle Niezgoda for writing the script to process the DS data. This research is supported by the National Research Foundation Singapore and the Singapore Ministry of Education.

NTU Rain Station Thanks you!