Category Archives: Forecasting

Famine in Somalia

I recently read “Famine in Somalia: Competing imperatives collective failures, 2011-2012”, which (as you may have guessed) picks apart the lead-up and response to the 2011-2012 famine in East Africa. It was fascinating, and I wanted to jot down three quick thoughts / takeaways from the book:

1. The famine was predicted. In fact, even the drought that set up the conditions for a potential famine was predicted. But the famine happened anyway. There were a number of reasons for this, chief among them the rise of Al-Shabaab, a fear of food-aid diversion, and a lack of coordination between remotely-managed disaster responses. But this points to the fact that it’s not only predicting disasters that we need to improve on. We need to consider how we can improve our responses to disasters in ways other than prediction.

2. The climate and disaster response community is already using some information about ENSO life-cycles in disaster management, but they could be doing much more. As the authors note, FEWSNET raised the alarm about a potential famine nearly a year in advance using information that La Niñas, which lead to drought in the Horn of Africa, often follow El Niños. We need to be incorporating this information into our “medium-term” preparedness, not just our disaster responses. For example, we could use this knowledge to know when we may need to pre-position food aid, or develop in-country networks for disaster response. The time it took to develop the in-country networks necessary was a major contributing factor to the famine. We could be using climate information to inform not only the delivery of food stock, but also for allocating time/money towards developing anticipatory in-country connections with key players ahead of an expected emergency.

3. One of the major themes of the book was a focus on bringing accountability to famines. I believe that as long as famines are treated as unforeseeable disasters, this will remain impossible. If, however, we move out of a disaster-response framework, and into a risk-reduction framework we may be able to make headway. If major droughts are viewed as an expected, recurring phenomena then a general preparedness may be reasonably expected. In this framework we need to begin focusing on how long we should expect between droughts. How severe will they be? By posing these questions publicly we can normalize the expectation of drought (and therefore of a planned response). This may provide political accountability for investments in institutions and infrastructure during non-crisis periods. Without a shift in the way we talk about food-security crises, we’re unlikely to see any change.

How (and whether) to Disseminate Climate Forecasts

One topic that I’ve been interested in for a while now, but haven’t yet had the chance to explore in any depth is the way in which we disseminate drought forecasts. In this blog post I’d like to look a little further into how we disseminate, what we disseminate, and whether it makes a difference. The short version is this: we have thought quite a bit about what we provide, but surprisingly little about whether it is effective (cost or otherwise).

Numerous studies have explored the way in which we provide information (see here and edited collections here and here). They have made some real advances in shedding some light on how farmers’ make use of climate forecasts, as well as the estimated impact (i.e. whether farmers changed their responses in the context of a workshop participation).

As it turns out, farmers’ are quite capable of understanding and acting on probabilistic information. For forecasters, this is good news. One question that I would be interested in exploring further is whether the workshops required to train farmers to use forecasts is cost effective. This question relates both to the initial cost, and to the question of information retention. When testing principles in the context of daylong participatory workshops, we are unable to address issues such as usage retention (particularly following forecasts that do not match the eventual seasonal totals).

A related question, raised by a colleague of mine here at IFPRI, is whether we should really be providing the information to individual farmers or if it is more effective to provide the information to regional met agencies. Again, the question is not whether farmers are capable of using the forecasts, but rather whether providing them directly is cost effective in the long run.

The most pressing question, however, is in many ways the most obvious: do climate forecasts improve yields? A rigorous study (read randomized control) of the real-world implications of climate yields is badly needed as a means of addressing whether climate forecasts are effective. Although I understand the desire to provide a high quality product (accurate forecast) in a reliable manner, it is past time that we begin discussing the hard evidence of cost effectiveness.

Much time has been dedicated to studying climate forecasts, but surprisingly little has been invested in understanding what role climate forecasts are likely to play in improving livelihoods. We can’t afford to silo these questions any longer.

Operational Drought Monitoring

To reduce the risk to food security posed by drought, it’s crucial that we develop systems able to disseminate accurate information in a timely manner. Although doing this may seem straightforward in an era of near-ubiquitous satellite measurements and increasingly high-powered computational models, there are challenges relating both to the analysis and dissemination of information in an operational context. I’ll explore the challenges to producing operational drought forecasts and monitors in this post and write about the challenges of disseminating those forecasts in my next post.

Broadly, most operational drought systems may be subdivided into those that monitor current conditions (and perhaps make historical readings available) and those that provide projections for future conditions. Coincidentally, while doing some research for this post I started to compile a list of available hydrological monitors and data portals, which you can find here. I focused on drought, but included a few others as well.

Drought monitoring, despite the availability of near real-time satellite data, faces great challenges of data availability. In fact, methods using satellite measurements currently perform comparably to those using only a handful of gauge stations. Satellite measurements are additionally challenged with a short climatology, and inconsistencies between products. Never-the-less, these products provide unparalleled coverage for regions with sparse in-situ measurements (as is often the case in developing countries), where drought monitoring has a crucial role to play in maintaining adequate levels of food security.

Although it is often described as a “slow onset” phenomenon, the development and evolution of drought can be remarkably difficult to predict. Part of this stems from an incomplete understanding of the oceanic forcings of drought (ENSO), and part of it stems from the inherently chaotic nature of the atmosphere. A chaotic systems sensitive to initial conditions creates an environment in which errors propagate through models and forecasts quickly diverge from one another. Shukla et al., 2013 analyzed the skill of a forecast as it relates to either (1) the initial conditions of the model or (2) the forecast skill, and found that the skill was dependent on both region and time of the year.

One means of improving both the monitoring and the forecasting of drought is to further explore the limitations to current model skill under different climate regimes. While Smith et al., explored times of the year and regions, the underlying factors of substance are the moisture-temperature-atmosphere regimes. It shouldn’t be ignored that during a drought, the region of interest (which may normally be energy-limited) will be abnormally arid (and therefore potentially moisture-limited). This shift may in fact mean that where the initial condition of soil moisture was once not a limiting factor for forecast skill, it may become one during the forecast of drought recovery. In that sense, forecasting the onset as opposed to the recovery of a drought may be two problems with distinct characteristics.

A second aspect of the drought system that warrants further exploration is the dynamics of vegetation during the evolution of multi-seasonal droughts. Previous studies have pointed towards dynamic vegetation as one source of increased interannual variability in precipitation, however, the impact of this dynamic vegetation on evapotranspiration and therefore on the atmospheric boundary layer may also play a significant role in determining how a drought develops. This is particularly true during multi-year droughts when drying of the soil occurs more deeply than during one-season droughts.

Information dissemination, financial systems and resiliency

The idea of resiliency in the face of climate change has been a popular idea lately, but a “resilient system” is difficult to define and a slippery concept at best.  Resiliency does not describe any one mechanism, nor does it describe a policy. Rather, resiliency describes the interaction between components of a system under stress. As a hydroclimate scientist, the idea of “resiliency” is particularly of interest to me in the context of agriculture.

New Security Beat is running a series of articles on resilient agriculture in the face of climate change. The most recent article begins with a point that is not often emphasized: resiliency is natural. As the author notes, “any effort to build resilience must begin with a deep understanding of existing strengths and adaptive mechanisms and make every effort to keep them intact”. Agricultural systems are a complex weave of formal and informal relationships (both financial and otherwise), which all play a part in determining the resiliency of the system. As such, agriculture cannot be approached from a single scale or a single perspective. The remainder of this post focuses primarily on financial and information-driven initiatives, but these are by no means the only perspectives at play in such systems.

From a financial perspective, we have been fairly good about discussing mechanisms that function across scales. On the micro-level there has been extensive study of micro-loan structures both formally through development banks and informally through community organizations. On a macro scale there has recently been interesting developments in the successful implementation of parametric weather-linked crop insurance. The IRI recently partnered with Oxfam and Swiss Re (among others) in a fascinating pilot study of weather-linked crop insurance for Northern Ethiopia, which I would encourage you to read. These two financial mechanisms, although applied in different manners, are complementary means to the same end.

From an information dissemination perspective we have had a somewhat more lopsided approach to providing support for the development of resilient systems. Many recent developments have pioneered exciting top-down information dissemination programs by partnering with local meteorological offices to issue growing season forecasts to farmers (please do watch the short video in the link, it is a great example of why such programs are invaluable). Despite these recent advances, we have too often overlooked the potential added value of low-tech community-scale information systems. Supplementing regional forecasts with local information is not a new concept, but it seems to be a discussion that is too-often missing from the academic literature. As a scientific community we need to consider not only how we can provide valuable forecasts, but also how those forecasts will interface with existing community-scale information systems.

Finally, looming in the substratum of any discussion involving climate change is the notion that no system is static, and no future certain. Although these are topics for another post, I’ll briefly point to an interesting article, which describes an increasing number of pastoralists in East Africa taking up farming due to the insecurities of a pastoral life in times of drought. If this trend continues, the dynamics of the East African agricultural system will change significantly and projections of growing season precipitation will become that much more valuable.

How we talk about Hurricane Sandy

As perhaps I should have expected, Google provided an incredibly useful, accessible tool for visualizing information immediately leading up to and in the wake of Hurricane Sandy. The tool provided the projected the track, intensity, precipitation and storm surge associated with the event. Even more useful, it included Red Cross shelters, FEMA shelters and food distribution points. Although this is a particularly powerful example of how social media and the web may aggregate available information to anticipate and respond to extreme weather, as a country we need to shift from a mindset of disaster response to one of disaster prevention.

Calling events like Hurricane Sandy the “New Normal” is not only scientifically simplistic, – see Curtis Brainard’s and Andrew Revikin’s discussion of Hurricane Sandy in the context of climate change – psychologically it implies that we should simply accept the increasing cost of extreme weather events (a cost that has largely come from increasing our exposure to extreme weather as opposed to an increase in the incidence of that weather). There is little that could be more dangerous than implying that as the climate changes there is neither anything we can do to mitigate that change, nor anything we can do to reduce our vulnerability to that change. When communicating projections of changing intensity and distributions of extreme events, language should be chosen very carefully. The risk management community has already provided numerous studies on the effects that word choice has on public perception as they have sought to express the risks posed by low frequency, high intensity events.

The risk posed by extreme weather is often obtuse and difficult to explain. People rarely understand how dangerous an area may be unless they have lived through a disaster, but that does not mean that the scientific community has no responsibility to work on effective communication. There must be a concerted effort on the part of the scientific community to develop a lexicon appropriate for the public, and one appropriate for decision makers. Without this effort we risk falling further into a mindset of reaction. Into a mindset that decouples our actions from the losses that ensue. There are too many examples of this already.

Perhaps the most frustrating example of policy reflecting a complacent acceptance of increasingly frequent weather-related losses is flood zone development. In this case it is often not an issue of risk communication, anyone that cantilevers a restaurant out over the ocean can take a look out the window at high tide to get an idea of flood risk. Despite a clear understanding and communication of potential losses, zoning continues to encourage development in high risk areas. An Article in the Huff Post does a particularly good job of detailing the paradoxical calls to action made by Mayor Bloomberg in the midst of continuing coastal development in NYC. The article cites at least a half dozen ways in which the city and the state pioneered funding research to characterize the risks posed by sea level rise and storm surge, only to promptly dismiss the most substantive concerns raised by these reports.

As a country we need to firmly establish a starting point for bringing our policies on coastal development in line with our risk assessment research. Although altering already developed coasts is a more difficult conversation, wrought with both moral and political issues, preventing knowingly locating people in the path of a disaster should be less controversial. We can’t afford to continue sending the message through implemented policies that coastal development is a matter of economic interest only. There is a certain audacity to pausing the breakneck development of coastal areas only long enough to grieve for those lost in the storm before resuming work as before. I’m not implying a halt to development, only a balance of the economic benefits with the physical risks.