Next Generation Earth System Prediction Strategies for Subseasonal to Seasonal Forecasts (2016) / Chapter Skim
Currently Skimming:
3 Enhancing the Value and Benefits of S2S Forecasts
3 Enhancing the Value and Benefits of S2S Forecasts
Pages 43-82
The Chapter Skim interface presents what we've algorithmically identified as the most significant single chunk of text within every page in the chapter.
Select key terms on the right to highlight them within pages of the chapter.
From page 43... ...
. Realizing potential benefits of S2S predictions will require physical science research to advance understanding of the many complex interactions at play within the Earth system and to overcome the many technical hurdles associated with translating such research into improved S2S forecast systems (see Chapters 4 through 7)
|
From page 44... ...
As the case tudies make s clear, some of the potential value of S2S forecasts lies in their ability to inform decision processes that begin months or even years in advance of a potential event. FIGURE 3.1 S2S forecasts (shown in blue and green)
|
From page 45... ...
snowmelt; summer water demands; precipitation; temperature; snowfall; evapotranspiration) Hydropower Available Probability of Changes in demand scheduling water supply reaching target and supply (changes in reservoirs; elevation levels in mean seasonal and anticipated in reservoir annual temperature demand (lake (snowmelt/inflow; across basin and levels; stream evaporative loss)
|
From page 46... ...
(probability of open (sea ice; famine (regional disruptive events, probability of changes in especially flooding disruptive events temperature and and drought) including flooding precipitation and famine)
|
From page 47... ...
unusable (sea ice; monthly temperatures) Energy Energy generation, Potential spikes Seasonal supplies trading, and in demand; of natural gas hedging availability of and renewable renewable energy energy sources; (heat waves/ trading with cold outbreaks; other producers, mean daily wind hedging in futures speed; daily solar markets and over radiation; adverse the-counter trades; weather impacts fuel adjustment such as ice storms, clauses (winter wind storms, and summer hurricanes)
|
From page 48... ...
waves, freeze) Commodity Protect profit; Protect profit; trading in grains anticipate market anticipate market and other high- movement movement value crops Ranching Forage Herd size, pasture Long-term changes management availability (total in viability of strategies; altering rainfall; vegetation operations in stocking rates health)
|
From page 49... ...
Risk awareness Encouraging Initiate public Changes in patterns people to stock awareness and or timing of severe sufficient supplies preparedness weather (changes (probability of campaigns in frequency or disruptive events) (probability of an magnitude of active season -- disruptive events)
|
From page 50... ...
Transportation Shipping and Disruptions Timing of opening Susceptibility of navigation to surface shipping lanes ports to inundation; transportation in the Arctic transit routes (sea systems; preparing (sea ice; summer level rise; storm evacuation routes temperatures; surge; ice-free Arctic) for hurricanes streamflow on (probability of major waterways)
|
From page 51... ...
Business Retail Supply chain Production and Probability of decisions, e.g., purchase of disruptive events promoting seasonal items, products in e.g., umbrellas, response to outdoor activities, weather events snow sports; (probability of possible disruption heavy rainfall; of supply chains extreme (seasonal snowfall, temperatures; number of rainy snowfall) days, extreme temperatures; probability of disruptive events)
|
From page 52... ...
disruptive events) favoring flooding or drought; extended periods of abnormally hot or cold temperatures)
|
From page 53... ...
days above temperature thresholds) Algal blooms/ High temperatures Probability of Changes in release of with relatively extended periods conditions conducive neurotoxins in stagnant water (weeks)
|
From page 54... ...
In contrast, seasonal forecasts prompted the restriction of credit for seed in Zimbabwe in 1997, which prevented planting and led to food shortages even though seasonal rainfall ended up at near-normal levels. Beyond the experience of negative consequences of seasonal forecast use, one important set of documented barriers to the use of S2S forecast products relates to mismatches between currently available products and the stated needs of end users.
|
From page 55... ...
studied seasonal forecast use in the agricultural sector and identified four barriers to the uptake of current seasonal forecasts, including mismatches between desired and available products: 1. Decision contexts rarely involve direct use of information about temperature and precipitation anomalies or climate indices.
|
From page 56... ...
Decisions are rarely made for a 3-month period across a large spatial domain; rather, decisions are based on discrete events occurring within a specific time frame and often for a very specific location. A product providing only above or below-normal or normal conditions over a very large domain may not be immediately useful to a water manager trying to regulate water usage or flow for several watersheds contained within that large domain or spanning several different forecast domains (see also water management case study; Robertson et al., 2014; Srinivasan et al., 2011)
|
From page 57... ...
Studies that have been conducted often indicate significant barriers to using S2S forecasts in decision-making, including mismatches between available and desired forecast products, barriers associated with policy and practice, and lack of understanding of what could be provided. Finding 3.3: Decision-makers generally express a need for a wider range of skillful model and forecast variables -- particularly information about the likelihood of disruptive or extreme events -- that are valid at finer spatial and temporal scales to inform management practices.
|
From page 58... ...
As an example, findings about the barriers to use of seasonal forecasts above are broadly consistent with previous research on the use of weather forecasts, which identified similar types of information that users generally consider to be the most relevant to decision-making (Pielke and Carbone, 2002) : • Extreme events, including droughts, hurricanes, floods, blizzards, tornadoes, and thunderstorms (including hail)
|
From page 59... ...
. Furthermore, seasonal forecast information, when presented at finer spatial and temporal scales, increasingly has larger bounds of uncertainty.
|
From page 60... ...
Creating some tailored products is possible using currently available forecast output. Developing other tailored forecast variables will require advances in the S2S forecasting system itself, particularly through an expansion of the capabilities of coupled Earth system models that enable, for example, new forecast variables such as the occurrence of unusual surf or extreme waves, mean cloud cover, and likelihood of harmful algal blooms.
|
From page 61... ...
Specifically, social science research can help to address many of the barriers to use previously highlighted in this chapter, including increasing understanding of users' confidence in the accuracy of forecasts, users' decision-making contexts and how to best integrate forecast information, and decision-making in contexts of high uncertainty and limited skill (see also NRC, 2010c)
|
From page 62... ...
Such understanding cannot be advanced without social and behavioral sciences research. Integrating Users into the Process of Developing Forecast Products Perhaps even more critical than improving forecast products and access is building trust in the S2S forecast process.
|
From page 63... ...
For example, IRI has found that seasonal climate forecasts of relatively low skill can still be successfully applied to water management problems in Brazil and Chile, but only through coupling climate forecasts with streamflow projections and working with managers to explicitly link such tailored forecasts to their reservoir management decision-making process (Robertson et al., 2014)
|
From page 64... ...
Decision processes on weather timescales could be instructive, such as how public safety officials change their decisions from the timescale of outlooks issued several days before an event, to watches issued hours before an event, and then warnings issued minutes before an event. Finding 3.9: Successfully aiding users with a multi-step decision model for mitigating the effects of adverse events is a difficult challenge and one not yet considered carefully in the S2S prediction community.
|
From page 65... ...
CASE STUDIES WITH EXAMPLE APPLICATIONS OF S2S FORECASTS Water Management in the Western United States Improved forecasting capability on S2S timescales is an oft-stated goal of water managers, especially in the drought-prone basins of the western United States (e.g., NIDIS Program Implementation Team, 2007; WGA, 2008)
|
From page 66... ...
In contrast to forecasts derived from observations of the winter snowpack, water managers have not relied heavily on the current array of operational S2S weather and climate forecast products. When used, the forecasts tend to be assessed qualitatively and used as a "tie-breaker" in higher stakes, scarcity situations (M.
|
From page 67... ...
. More accurate seasonal forecasts of winter precipitation, issued in the previous s ummer and fall, could substantially improve decision-making about allocations to water project contractors, planning for reservoir water and power operations, anticipation of the number of water transfer requests, and planning for emergency flows for endangered species management.
|
From page 68... ...
. Years of subsequent data collection, climate data and forecast output analysis, and collaboration with public health officials in Ghana has led to the development of relative humidity thresholds that can readily be incorporated into existing public health frameworks.
|
From page 69... ...
. The end of the dry season is paced by the ( annual northward migration of the Intertropical Convergence Zone, but rainfall events can modulate the timing of seasonal change on local-to-regional scales (Figure 3.4)
|
From page 70... ...
. A growing body of research suggests that integrating monthly to seasonal forecasts of sea surface temperatures, cumulative rainfall, and temperature variability -- especially from MMEs shown to have skill in regions of interest -- will likely allow for the development of malaria early warnings at longer (4-6 month)
|
From page 71... ...
For example: 1. Commander Third Fleet ship operation planning in the eastern North Pacific utilizes seasonal forecasts of northeast Pacific winds and waves, by month based on both standard climatologies and statistical predictions derived from multiyear model reanalyses as a basis to revise/update the timing of the operations.
|
From page 72... ...
The combination of thawing permafrost, decreasing sea ice, and rising sea level on the Alaskan coast have led to an increase in coastal erosion at several Air Force radar early warning and communication installations. According to installation officials, this erosion has damaged roads, utility infrastructure, seawalls, and runways.
|
From page 73... ...
Warm colors indicate a higher probability of attack. SOURCE: Naval Oceanographic Office, Warfighting Support Center.
|
From page 74... ...
Oil spill trajectory forecasting systems in 2010 were well-suited for responding to surface spills, even beyond the scale of the 1989 Exxon Valdez oil spill, and worked well for predicting where surface slicks moved for the 72 hours after the event, during which time weather forecasts were sufficiently accurate. However, the vast volume and depth of spilled hydrocarbons associated with the DWH, the extended duration of the spill, and the spatial extent of its impacts presented unique challenges for projecting the consequences of the spill to an alarmed public.
|
From page 75... ...
(B) A frame from a NOAA animation of dissolved oil concentrations that include (left)
|
From page 76... ...
. There is a high cost to incorrect projections of the direction of an oil spill, and in an emergency there is little time to identify the sources of incorrect current directions or other model biases.
|
From page 77... ...
and DOD DTRA consequence assessment assets can be mobilized for international events, as in Fukushima.) However, these simulation tools were not designed to provide forecast information on S2S timescales.
|
From page 78... ...
However, decision-makers need a wider range of model and forecast variables than what is generally available at present. Producing forecast products that are valid at finer spatial and temporal scales, and generating event- and impact-based information, are some of the most commonly expressed needs.
|
From page 79... ...
Such an assessment will be particularly important for developing forecasts of variables such as sea ice or harmful algal blooms that are not as readily available at the present time. Furthermore, quantification of the value of use of seasonal forecasts is needed to establish a baseline against which improvements in use can be measured.
|
From page 80... ...
Such iterative engagement will also provide guidance to the operational community on the critical research challenges, such as forecasting extreme events, and the way in which information can be most effectively delivered. As with weather forecasts, most decision-makers are likely to acquire information via an intermediary (Breuer et al., 2010; Lemos and Rood, 2010; Mase and Prokopy, 2014; Pagano et al., 2002)
|
From page 81... ...
Recommendation B: Establish an ongoing and iterative process in which stakeholders, social and behavioral scientists, and physical scientists codesign S2S forecast products, verification metrics, and decision-making tools. Specifically: • Engage users with physical, social, and behavioral scientists to develop re quirements for new products as advances are made in modeling technology and forecast skill, including forecasts for additional environmental variables.
|
Key Terms
This material may be derived from roughly machine-read images, and so is provided only to facilitate research.
More
information on Chapter Skim is available.