IRI@AGU: Schedule of Events 2016
A range of IRI’s areas of expertise will be represented at this year’s annual meeting of the American Geophysical Union (AGU). Many of the presentations center on fundamental climate science, including analyses of the influence of climate variability and change on rainfall in the US, Iran, South America and the Sahel, as well as the tropics more generally. Tufa Dinku presents on the rainfall data estimated by satellites, upon which many climate analyses rely. Graduate students Pradipta Parhi and Catherine Pomposi both offer new understanding of how El Niño conditions in the ocean can lead to changes in precipitation patterns on land. Others take a look back at the impacts of and response to the 2015-16 El Niño event. Several scientists break down the barrier between the traditional weather and climate communities with presentations on improving forecasts at the sub-seasonal to seasonal scale and weather-within-climate techniques for agriculture-related decisions. Finally, Upmanu Lall will take a broader look at the complexity of climate risk as applied to water and energy systems, examining the multiple time and spatial dimensions of climate information that may influence these systems.
Below is the schedule of IRI’s posters and presentations in sequential order.
Validation of CHIRP Satellite Rainfall Estimates over Africa
Tufa Dinku + Chris C Funk + Tsegaye Tadesse
There are many satellite rainfall products from many centers. The quality and temporal/spatial resolution of these products has been improving over time. One of the factors that contributed to the improvement of satellite rainfall products has been the use of passive microwave data. However, this use of passive microwave data may have also introduced inhomogeneities in the rainfall time series due to changes in the numbers sensors over the years. In parallel to these products, there is also a need for historical rainfall time series derived from a single sensor (i.e., infrared sensors). Such products do exist (e.g. ARC and TAMSAT), but are limited in terms geographical coverage. There is now a new product from the Climate Hazard Group at University of California, Santa Barbara…
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Atlantic Multidecadal Variability as a Modulator of the Rainfall Sensitivity in the Continental US
Dong Eun Lee + Mingfang Ting + Nicolas Vigaud + Yochanan Kushnir + Anthony Barnston
The failure of the heavily expected drought relief in the west coast US, despite of the strong El Nino event in 2015/16, motivated ones to wonder what could be the source of the uncertainty around the canonical ENSO-dependent predictability. So far, it has been suggested that the uncertainty in the intraseasonal to seasonal (S/S) rainfall variability is due to the linear interference with ENSO, such as internal variability, the Arctic sea ice anomalies, or unusual longitudinal position of the SST anomalies associated with El Nino diversity. Here, we investigate another aspect that has been overlooked. Is the rainfall in the continental US invariantly responsive to the remote climate signals? We propose the Atlantic Multidecadal Variability (AMV) as one of the feasible candidates to provide such significant modulation on the rainfall sensitivity in the continental US…
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Iran’s Seasonal Precipitation Analysis Associated with El Niño Events: Historical Analysis and the 2015/2016 El Niño
Husain Najafi + Andrew William Robertson + Ángel Muñoz + Ali Reza Massah Bavani + Parviz Irannejad
The aim of this study is I) to understand potential predictability of 3-month precipitation total for the rainy season over Iran associated with El Niño events. Taking the contingency tables approach instead of typical composite and correlation, probabilistic seasonal precipitation anomalies conditional upon the phase of strongest El Niño events are provided. Probabilities of wet/dry climate conditions are evaluated for two gridded monthly precipitation datasets, GPCC and CRU. II) To see if historic analysis of previous El Niño events can be considered as an indication of what has been likely to occur (likelihood of wet/dry climate anomalies) during the 2015/2016 El Niño…
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The 2015-16 El Niño – Manifestation and US Impacts
David J. Farnham + Upmanu Lall + et al.
The impacts of ENSO, especially in the USA, are well studied. Given the past success at forecasting El Niño events and identifying their teleconnections to different parts of the country, there is a relatively well publicized understanding of the potential impacts, and the possible directions of management response. Consequently, a special course at Columbia University took advantage of the ongoing El Niño event in Winter/Spring 2016 to assess the forecasts of the potential impacts, forms of forecast-related communication, and the actual outcomes in selected sectors and regions of the USA…
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Heterogeneous Sensitivity of Tropical Precipitation Extremes during Growth and Mature Phases of Atmospheric Warming
Pradipta Parhi + Alessandra Giannini + Upmanu Lall + Pierre Gentine
Assessing and managing risks posed by climate variability and change is challenging in the tropics, from both a socio-economic and a scientific perspective. Most of the vulnerable countries with a limited climate adaptation capability are in the tropics. However, climate projections, particularly of extreme precipitation, are highly uncertain there. The CMIP5 (Coupled Model Inter- comparison Project – Phase 5) inter-model range of extreme precipitation sensitivity to the global temperature under climate change is much larger in the tropics as compared to the extra-tropics. It ranges from nearly 0% to greater than 30% across models (O’Gorman 2012). The uncertainty is also large in historical gauge or satellite based observational records. These large uncertainties in the sensitivity of tropical precipitation extremes highlight the need to better understand how tropical precipitation extremes respond to warming. We hypothesize that one of the factors explaining the large uncertainty is due to differing sensitivities during different phases of warming…
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A dynamical characterization of the uncertainty in projections of regional precipitation change in the semi-arid tropics
The uncertainty in CMIP multi-model ensembles of regional precipitation change in tropical regions is well known: taken at face value, models do not agree on the direction of precipitation change. Consequently, in adaptation discourse, either projections are discounted, e.g., by giving more relevance to temperature projections, or outcomes are grossly misrepresented, e.g., in extrapolating recent drought into the long-term future. That this is an unsatisfactory state of affairs, given the dominant role of precipitation in shaping climate-sensitive human endeavors in the tropics, is an understatement. Here I will provide a dynamical characterization of the uncertainty in regional precipitation projections that exploits the CMIP multi-model ensembles…
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Early Warning and Early Action during the 2015-16 El Nino Event
*This talk will be given by Andrew Robertson on behalf of Lisa Goddard.
Strong El Niño events have a marked impact on regional climate worldwide through their influence on large-scale atmospheric circulation. This talk will present some details on how we navigate the fine line between expectations and probabilistic forecasts, and how this information was used during the 2015-16 El Niño event. Examples are drawn from the health sector and food security community. Specific attention will be given to the importance of problem-focus and data availability in the appropriate tailoring of climate information for Early Warning/Early Action….
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Modulation of the ENSO Teleconnection to the Sahel
Catherine Pomposi + Alessandra Giannini + Yochanan Kushnir
During the spring of 2015 as a historic El Niño event was building, various news outlets warned of the potential for dry conditions and subsequent famine that could result from a reduction of rainfall during the summer months in the Sahel. These warnings followed the traditional understanding of ENSO’s impacts in sub-Saharan Africa to dynamically force drying in the region due to a reorganization of atmospheric circulation and increased convective thresholds. Yet, by the end of the 2015 rainy season, observations indicated that much of the Sahel experienced anomalously wet conditions rather than dry conditions. This recent conundrum motivates work in which we use 2015 as a case study to ask what additional forcings in the global ocean oppose (or alleviate) drying associated with El Niño in the Sahel…
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From Sub-Seasonal Prediction to Action: The Role of the Sub-Seasonal to Seasonal Prediction Project (S2S) in Promoting Forecasting Science and Services
Andrew Robertson + Frederic Vitart + Paolo Ruti + Michel Rixen
The World Weather and World Climate Research Programme’s Sub-seasonal to Seasonal Prediction Project (S2S) aims to provide predictions from two weeks to two months ahead. This is a critical timescale as the lead time is sufficiently long that much of the memory of the e.g. atmospheric initial conditions is lost and it is too short a timescale for the variability of e.g. the ocean to have a strong influence. The lead time is also long enough to allow decision makers time to take preventative action to help mitigate the impacts of high-impact weather events. This contribution will provide a status update of the S2S project, including training activities, the S2S forecast data base, and summarize progress to date on creating regional S2S science-to-service exemplars in Africa, South America and Asia…
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*Robertson is the primary convener of this session, as well as another presentation session and a poster session on the same topic.
Quantifying conditional risks for water and energy systems using climate information
There has been a growing recognition of the multi-scale spatio-temporal organization of climate dynamics, and its implications for predictable, structured risk exposure to populations and infrastructure systems. Climate informed predictions for water and energy systems can be thought of as efforts to infer conditional distributions of specific outcomes given information on climate state. Invariably, the climate state may be presented as a very high dimensional spatial set of variables, with limited temporal sampling, while the water and energy attributes may be regional and constitute a much smaller dimension. In this talk, I will provide examples of a few modern statistical and machine learning tools that allow a decomposition of the high dimensional climate state and its relation to specific regional or hemispheric outcomes that inform terrestrial water and energy (wind as well as hydropower) futures…
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Assessing the potential for improving S2S forecast skill through multimodel ensembling
Nicolas Vigaud + Andrew William Robertson + Michael K Tippett + Lei Wang + Michael James Bell
Non-linear logistic regression is well suited to probability forecasting and has been successfully applied in the past to ensemble weather and climate predictions, providing access to the full probabilities distribution without any Gaussian assumption. However, little work has been done at sub-monthly lead times where relatively small re-forecast ensembles and lengths represent new challenges for which post-processing avenues have yet to be investigated. A promising approach consists in extending the definition of non-linear logistic regression by including the quantile of the forecast distribution as one of the predictors. Results will be discussed over a broader North American region, where individual and MME forecasts generated out to 4 weeks lead are characterized by good probabilistic reliability but low sharpness, exhibiting systematically more skill in winter than summer…
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South American Monsoon: Recent Droughts in the Context of Changing Global Circulation
Anji Seth + Kátia Fernandes + Suzana J Camargo
The 2013-2015 drought in Southeast Brazil led to water shortages in São Paulo, the country’s most populous city. The observed drought during austral summers of 2013/2014 and 2014/2015 and related large-scale dynamics are examined. The 2013–2014 precipitation deficits were more concentrated in the state of São Paulo, while in 2014–2015 moderate deficits were seen throughout the region. We find that a persistent warm sea surface temperature (SST) anomaly in the western tropical Pacific Ocean was an important driver of drought via atmospheric teleconnection in the two December–February seasons. A first look at CMIP5 model projections to examine the role of large scale circulation changes to drought in the Sao Paulo region will be presented…
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Multi-Scale Weather-within-Climate Information and Forecasts for Decision Support in Agriculture
Amor Ines + Eunjin Han
The skill of seasonal climate forecast indicates the value of that information towards decision-making. While seasonal climate forecast’s skill varies by season and geographic locations, they are notoriously low-to-moderate skilled as well with exceptions when ENSO signal is strong. Regardless, seasonal climate forecast are valuable information for planning strategic decisions. One may ask in this situation, is climatology better? On the contrary, we should craft the question like this, is there a value of merging of multi-scale weather-within-climate information with seasonal climate forecasts to enhance skill or information for decision support in agriculture? Here, we present integrating multi-scale climate information from monitored, climatology and forecasts to improve the value of climate information for decision support in agriculture…
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