IRI @ AGU Schedule of Events 2017
The International Research Institute for Climate and Society (IRI) will present on a range of areas of expertise at this year’s annual meeting of the American Geophysical Union (AGU). IRI scientists will present two tools for managing climate impacts — a decision-support tool for agriculture and a financial tool in the form of index-based flood insurance. Another presentation focuses on improving our fundamental ability to predict tropical cyclones. Security under changing conditions is a major theme in another two IRI presentations—one focused on water resources and the other on the effects of rising temperatures on fire risk. IRI scientists lent their expertise to an additional 17 posters and presentations on topics including Zika, heatwaves, floods, satellite data, soil moisture feedbacks and, of course, El Niño.
Below is the schedule of IRI’s posters and presentations in sequential order.
The Water Security Hydra
Session: H13S Pursuing Water Security in Socio-Hydrological Systems I
Mon, Dec 11; 1:40 – 1:55 PM
Ernest N. Morial Convention Center – 280-282
As the editor of a new journal on water security, I have been pondering what it can mean theoretically and practically. At one level, it is pretty obvious that it refers to the ability to affordably and reliably access water of appropriate quality, and to be protected from the water related ravages of nature, such as floods, droughts and water borne disease…New stresses are created by a changing climate, growing populations and an ever changing society, economic activity and environment. Thus, if assuring water security is a goal at any of the scales of interest, many factors need to be considered, and what can really be assured, where and for how long emerges as an interesting question. Local (place, time, individuals, politics) as well as global (climate, economics, hydrology) factors interact to determine outcomes, not all of which are readily mapped in our mathematical or cognitive models to a functional notion of what constitutes security in the face of changing conditions and actors…
Tropical cyclone prediction skills – MJO and ENSO dependence in S2S data sets
Chia-Ying Lee + Suzana Camargo + Fréderic Vitart + Adam Sobel + Michael Tippett
Session: A23M Subseasonal to Seasonal Forecasting of High-Impact Weather and Climate Events I
Tues, Dec 12; 3:25 – 3:40 PM
Ernest N. Morial Convention Center – R01
Read a Q&A with Lee about this research.
The El Niño–Southern Oscillation (ENSO) and the Madden-Julian Oscillation (MJO) are two important climate controls on tropical cyclone (TC) activity. The seasonal prediction skill of dynamical models is determined in large part by their accurate representations of the ENSO-TC relationship. Regarding intraseasonal TC variability, observations suggest MJO to be the primary control. Given the ongoing effort to develop dynamical seasonal-to-subseasonal (S2S) TC predictions, it is important to examine whether the global models, running on S2S timescales, are able to reproduce these known ENSO-TC and MJO-TC relationships, and how this ability affects forecasting skill.
Results from the S2S project (from F. Vitart) suggest that global models have skill in predicting MJO phase with up to two weeks of lead time (four weeks for ECMWF). Meanwhile, our results show that, qualitatively speaking, the MJO-TC relationship in storm genesis is reasonably captured, with some models (e.g., ECMWF, BoM, NCEP, MetFr) performing better than the others…
The Climate-Agriculture-Modeling and Decision Tool (CAMDT) for Climate Risk Management in Agriculture
Session: GC33C Toward Better Understanding of the Impacts of Climate Variability: From Ecosystem Processes to Agricultural Adaptation and Decision II
Wed, Dec 13; 1:40 – 6:00 PM
Ernest N. Morial Convention Center – Poster Hall D-F
Advances in seasonal climate forecasts (SCFs) during the past decades have brought great potential to improve agricultural climate risk managements associated with inter-annual climate variability. In spite of popular uses of crop simulation models in addressing climate risk problems, the models cannot readily take seasonal climate predictions issued in the format of tercile probabilities of most likely rainfall categories (i.e, below-, near- and above-normal). When a skillful SCF is linked with the crop simulation models, the informative climate information can be further translated into actionable agronomic terms and thus better support strategic and tactical decisions. In other words, crop modeling connected with a given SCF allows to simulate “what-if” scenarios with different crop choices or management practices and better inform the decision makers. In this paper, we present a decision support tool, called CAMDT (Climate Agriculture Modeling and Decision Tool), which seamlessly integrates probabilistic SCFs to DSSAT-CSM-Rice model to guide decision-makers in adopting appropriate crop and agricultural water management practices for given climatic conditions…
CAMDT GitHub: https://github.com/Agro-Climate/CAMDT
Fires in Non-drought Conditions in Indonesia: the Role of Increasing Temperatures
Kátia Fernandes + Louis Verchot + Walter Baethgen + Victor Gutierrez-Velez + Miguel Pinedo-Vasquez + Christopher MartiusSession
Session: GC44C The Role of Fire in the Earth System: Understanding Drivers, Feedbacks, and Interactions with the Land, Atmosphere, and Society II
Thurs, Dec 14; 4:15 – 4:30 PM
Ernest N. Morial Convention Center – 265-266
Read a Q&A with Fernandes about this research.
In Indonesia, drought driven fires occur typically during the warm phase of the El Niño Southern Oscillation (ENSO), such as those of 1997 and 2015 that resulted in months-long hazardous atmospheric pollution levels in Equatorial Asia and record greenhouse gas emissions. Nonetheless, anomalously active fire seasons have also been observed in non-drought years. In this work, we investigated whether fires are impacted by temperature anomalies and if so, if the responses differ under contrasting precipitation regimes. Our findings show that when the July-October dry-season is anomalously dry, the sensitivity of fires to temperature anomalies is similar regardless of the sign of the anomalies. In contrast, in wet condition, fire risk increases sharply when the dry season is anomalously warm. We also present a characterization of near-term regional climate projections over the next few decades and the implications of continuing global temperature increase in future fire probability in Indonesia….
In addition to the above posters and presentations led by IRI staff, the following activities are co-authored by IRI staff. The presenting author is listed first, followed by IRI staff.
(Julie Arrighi + Hannah Nissan)
Drought in West Africa: How CHIRPS and Reference Evapotranspiration can be used for Index Insurance in a Non-Stationary Setting
(Sari Lucille Blakeley + Daniel Osgood)
Financial Risk Reduction and Management of Water Reservoirs Using Forecasts: A Case for Pernambuco, Brazil
(Ipsita Kumar + Upmanu Lall)
(Masahiko Haraguchi + Upmanu Lall)
(Weston Anderson + Walter Baethgen)
Assessing the impact of model and climate uncertainty in malaria simulations for the Kenyan Highlands
(Adrian Tompkins + Madeleine Thomson)
(Katherine Schlef + Andrew Robertson)
(James Doss-Gollin + Upmanu Lall)
Causes and Model Skill of the Persistent Intense Rainfall and Flooding in Paraguay during the Austral Summer 2015-2016
(James Doss-Gollin + Ángel Muñoz)
Sub-hectare crop area mapped wall-to-wall in Tigray Ethiopia with HEC processing of WorldView sub-meter panchromatic image texture
(Christopher Neigh + Bristol Powell)
(Alexis Berg + Alessandra Giannini)
Climate-Agriculture-Modeling and Decision Tool for Disease (CAMDT-Disease) for seasonal climate forecast-based crop disease risk management in agriculture
Engaging informal audiences in learning about and responding to climate change through a portfolio of innovative approaches
(Stephanie Pfirman + Ben Orlove)
(Julian David Rojo Hernandez + Upmanu Lall)
(David Farnham + Upmanu Lall)
The Another Assimilation System for WRF-Chem (AAS4WRF): a new mass-conserving emissions pre-processor for WRF-Chem regional modelling
(Angel Liduvino Vara Vela + Ángel Muñoz)