Climate Change Blogs

Let’s call it: 30 years of above average temperatures means the climate has changed

Published: Febrero 27, 2015
Let’s call it: 30 years of above average temperatures means the climate has changed

If you’re younger than 30, you’ve never experienced a month in which the average surface temperature of the Earth was below average.

Each month, the US National Climatic Data Center calculates Earth’s average surface temperature using temperature measurements that cover the Earth’s surface. Then, another average is calculated for each month of the year for the twentieth century, 1901-2000. For each month, this gives one number representative of the entire century. Subtract this overall 1900s monthly average – which for February is 53.9F (12.1C) – from each individual month’s temperature and you’ve got the anomaly: that is, the difference from the average.

The last month that was at or below that 1900s average was February 1985. Ronald Reagan had just started his second presidential term and Foreigner had the number one single with “I want to know what love is.”

These temperature observations make it clear the new normal will be systematically rising temperatures, not the stability of the last 100 years. The traditional definition of climate is the 30-year average of weather. The fact that – once the official records are in for February 2015 – it will have been 30 years since a month was below average is an important measure that the climate has changed.



Temperature history for all Februaries from 1880-2014
NCDC



How the Earth warms

As you can see in the graphic above, ocean temperature doesn’t vary as much as land temperature. This fact is intuitive to many people because they understand that coastal regions don’t experience as extreme highs and lows as the interiors of continents. Since oceans cover the majority of the Earth’s surface, the combined land and ocean graph strongly resembles the graph just for the ocean. Looking at only the ocean plots, you have to go all the way back to February 1976 to find a month below average. (That would be under President Gerald Ford’s watch.)

You can interpret variability over land as the driver of the ups and downs seen in the global graph. There are four years from 1976 onwards when the land was below average; the last time the land temperature was cool enough for the globe to be at or below average was February 1985. The flirtation with below-average temps was tiny – primarily worth noting in the spirit of accurate record keeping. Looking at any of these graphs, it’s obvious that earlier times were cooler and more recent times are warmer. None of the fluctuations over land since 1976 provide evidence contrary to the observation that the Earth is warming.

Some of the most convincing evidence that the Earth is warming is actually found in measures of the heat stored in the oceans and the melting of ice. However, we often focus on the surface air temperature. One reason for that is that we feel the surface air temperature; therefore, we have intuition about the importance of hot and cold surface temperatures. Another reason is historical; we have often thought of climate as the average of weather. We’ve been taking temperature observations for weather for a long time; it is a robust and essential observation.



Temperature history for every year from 1880-2014.
NOAA National Climatic Data Center



Despite variability, a stable signal

Choosing one month, February in this instance, perhaps overemphasizes that time in 1985 when we had a below average month. We can get a single yearly average for all the months in an entire year, January-December. If we look at these annual averages, then the ups and downs are reduced. In this case, 1976 emerges as the last year in which the global-average temperature was below the 20th century average of 57.0F (13.9C) – that’s 38 years ago, the year that Nadia Comaneci scored her seven perfect 10s at the Montreal Olympics.

I am not a fan of tracking month-by-month or even year-by-year averages and arguing over the statistical minutia of possible records. We live at a time when the Earth is definitively warming. And we know why: predominately, the increase of greenhouse gas warming due to increasing carbon dioxide in the atmosphere. Under current conditions, we should expect the planet to be warming. What would be more important news would be if we had a year, even a month, that was below average.

The variability we observe in surface temperature comes primarily from understood patterns of weather. Many have heard of El Niño, when the eastern Pacific Ocean is warmer than average. The eastern Pacific is so large that when it is warmer than average, the entire planet is likely to be warmer than average. As we look at averages, 30 years, 10 years, or even one year, these patterns, some years warmer, some cooler, become less prominent. The trend of warming is large enough to mask the variability. The fact that there have been 30 years with no month below the 20th century average is a definitive statement that climate has changed.

The 30-year horizon

There are other reasons that this 30-year span of time is important. Thirty years is a length of time in which people plan. This includes personal choices – where to live, what job to take, how to plan for retirement. There are institutional choices – building bridges, building factories and power plants, urban flood management. There are resource management questions – assuring water supply for people, ecosystems, energy production and agriculture. There are many questions concerning how to build the fortifications and plan the migrations that sea-level rise will demand. Thirty years is long enough to be convincing that the climate is changing, and short enough that we can conceive, both individually and collectively, what the future might hold.

Finally, 30 years is long enough to educate us. We have 30 years during which we can see what challenges a changing climate brings us. Thirty years that are informing us about the next 30 years, which will be warmer still. This is a temperature record that makes it clear that the new normal will be systematically rising temperatures, not the ups and downs of the last 100 years.

Those who are under 30 years old have not experienced the climate I grew up with. In thirty more years, those born today will also be living in a climate that, by fundamental measures, will be different than the climate of their birth. Future success will rely on understanding that the climate in which we are all now living is changing and will continue to change with accumulating consequences.

This article was originally published on The Conversation.
Read the original article.

Are We Entering a New Period of Rapid Global Warming?

Published: Febrero 24, 2015
Residents of New England may understandably look back at 2015 as the year of their never-ending winter. For the planet as a whole, though, this year could stand out most for putting to rest the “hiatus”— the 15-year slowdown in atmospheric warming that gained intense scrutiny by pundits, scientists, and the public. While interesting in its own right, the hiatus garnered far more attention than it deserved as a purported sign that future global warming would be much less than expected. The slowdown was preceded by almost 20 years of dramatic global temperature rise, and with 2014 having set a new global record high, there are signs that another decade-plus period of intensified atmospheric warming may be at our doorstep.

The most compelling argument for a renewed surge in global air temperature is rooted in the Pacific Decadal Oscillation (PDO). This index tracks the fingerprint of sea surface temperature (SST) across the Pacific north of 20°N. A closely related index, the Interdecadal Pacific Oscillation (IPO), covers a larger swath of the entire Pacific. Both the PDO and IPO capture back-and-forth swings in the geography of Pacific SSTs that affect the exchange of heat between ocean and atmosphere (see Figure 1). We’ll use PDO as shorthand for both indexes in the following discussion.

The PDO typically leans toward a positive or negative state for more than a decade at a time. The positive phase, which features warmer-than-average SSTs along the U.S. West Coast, was dominant from the mid-1970s to the late 1990s. The PDO then flipped to a negative phase between about 1999 and 2013, with cooler-than-average SSTs along the West Coast. Figure 2 shows that even when a particular mode is favored, the PDO can still flip back to its opposite mode for periods of a few months or so.


Figure 1. Departures from average sea-surface temperature (degrees C) and wind (arrows) that typically prevail when the Pacific Decadal Oscillation is in its positive mode (left) and negative mode (right). Image credit: University of Washington.


It’s not clear exactly what drives the PDO, but in some ways it can be viewed as a geographically expanded version of the SST patterns created by El Niño and La Niña, averaged over a longer time period. (See Figure 2.) It’s well-established that El Niño can raise global temperature for a few months by several tenths of a degree Celsius, as warm water spreads over the eastern tropical Pacific and mixes with the overlying atmosphere. Likewise, La Niña can act to pull down global average temperature, as cooler-than-average water extends further west than usual across the tropical Pacific. The PDO mirrors these trends, but over longer periods. When the PDO is positive, there are more El Niño and fewer La Niña events, and heat stored in the ocean tends to be spread across a larger surface area, allowing it to enter the atmosphere more easily. When the PDO is negative, SSTs are below average across a larger area, and global air temperatures tend to be lower.


Figure 2. Typical warm and cool anomalies in sea-surface temperature during positive PDO years (left) and El Niño years (right). The patterns are similar, though with differences in intensity over some regions. The anomalies are reversed for negative PDO and La Niña years. Image credit: University of Washington Climate Impacts Group.


Figure 3 shows a striking connection between favored PDO modes (top) and global air temperature anomalies (bottom). The vast majority of atmospheric warming over the last century occurred during positive PDO phases, with negative PDOs tending to result in flat temperature trends. It’s easy to see how an atmospheric warming “hiatus” could occur during a negative PDO phase.


Figure 3. PDO values (top) and global air temperature anomalies (bottom). Gray shading indicates positive PDO periods, when atmospheric warming was most evident. The NOAA PDO values shown here vary slightly from those discussed in the article, which are calculated by the University of Washington. Image credit: Jerimiah Brown, Weather Underground. Data sources:NOAA (top) and NOAA/NCDC (bottom).


From the AMS meeting
The hiatus was discussed at length in a series of talks during the annual meeting of the American Meteorological Society last month in Phoenix. Jerry Meehl, from the National Center for Atmospheric Research (my former employer), gave a whirlwind 15-minute overview of hiatus-oriented research conducted over the last six years. Meehl’s talk can be viewed online. More than 20 papers have studied the hiatus and its links to the PDO/IPO, according to Matthew England (University of New South Wales). Most of the flattening of global temperature during the hiatus can be traced to cooler-than-average conditions over the eastern tropical Pacific, which pulled down global averages. An emerging theme is that natural, or internal, variability in the tropical Pacific can explain at least half of the hiatus. NCAR’s Clara Deser presented new modeling evidence along these lines (see video online). Other factors may be involved as well, including a series of weak volcanic eruptions that could explain a small part of the hiatus, according to a recent analysis by Ben Santer (Lawrence Livermore National Laboratory).

One crucial point is that global warming didn’t “stop” during the hiatus: the world’s oceans actually gained heat at an accelerated pace. Trade winds blew more strongly from east to west across the Pacific, consistent with the tendency toward La Niña conditions, as described in this open-access article by NCAR’s Kevin Trenberth and John Fasullo. Over parts of the central tropical Pacific, trade winds averaged about 3 mph stronger during 1999-2012 compared to 1976-1988. These speeds are higher than for any previous hiatus on record, bolstering the idea that other factors may have joined this negative PDO/IPO phase. The faster trade winds encouraged upwelling of cooler water to the east and helped deepen and strengthen the warm pool to the west—enough, in fact, to raise sea level around the Philippines by as much as 8 inches. Other parts of the deep ocean warmed as well. A new study led by Dean Roemmich (Scripps Institution of Oceanography) maps the areas of greatest ocean heating from 2006 to 2013 and finds that significant warming extended to depths of greater than 6600 feet.

What next for the PDO?
The PDO index, as calculated at the University of Washington, scored positive values during every month in 2014, the first such streak since 2003. By December it reached +2.51, the largest positive value for any December in records that go back to 1900. The January value from UW was 2.45, again a monthly record. (NOAA calculates its own PDO values through a closely related methodology.)

Because the PDO can flip modes for a year or more within its longer-term cycle, we don’t yet know whether a significant shift to a positive PDO phase has begun. If trade winds weaken throughout this year, and positive PDO values persist, that’ll be strong evidence that a new cycle is indeed under way. The last time we saw a two-year streak of positive values was in 1992-93. If this occurs, and assuming no spikes in major volcanic activity, we could expect greater rises in global temperature over the next 10 to 15 years than we’ve seen during the hiatus. In addition, we should watch for El Niño to make its presence known more often.

“I am inclined to think the hiatus is over, mainly based on the PDO index change,” NCAR’s Kevin Trenberth told me. While Matthew England isn’t ready to offer such a prediction, he emphasized that any post-hiatus global temperature rise is likely to be fairly rapid. Trenberth also commented on an interesting NOAA analysis (see Figure 4): “If one takes the global mean temperature from 1970 on, everything fits a linear trend quite well except 1998.”


Figure 4. When looking at global temperature over a full PDO cycle (1970s to 2010s), the overall rise becomes evident, despite the flattening observed in the last 15 years. Image credit: NOAA.


A record-strong El Niño occurred in 1998, providing an unusually powerful boost to global temperature and fueling years of subsequent declarations that “global warming stopped in 1998.” The record warmth of 2014 made it clear that global warming has no intention of stopping, and the next few years are likely to reinforce that point. Nevertheless, snowbound New Englanders, and millions of other easterners now dealing with record cold for so late in the year, may be wondering why eastern North America has seen so much cold and snow in the past few winters--especially this one--and how long that climatic quirk might continue. Stay tuned for a separate post on that topic.

Bob Henson
Categories:Climate Change

New England Intense Hurricanes Much More Numerous 340 to 1800 Years Ago

Published: Febrero 17, 2015
Numerous Category 3 and 4 hurricanes frequently pounded New England during the first millennium, from the peak of the Roman Empire into the height of the Middle Ages, said a study accepted for publication this month in the open-access journal Earth’s Future, Climate Forcing of Unprecedented Intense-Hurricane Activity in the Last 2,000 Years. These prehistoric hurricanes were stronger than any hurricane documented to hit the region since the mid-1800s, and would be catastrophic if they hit the region today, according to Jeff Donnelly, a scientist at Woods Hole Oceanographic Institution (WHOI) in Massachusetts and lead author of the new paper. In a press release, Donnelly said, “We hope this study broadens our sense of what is possible and what we should expect in a warmer climate. We may need to begin planning for a category 3 hurricane landfall every decade or so rather than every 100 or 200 years.”


Figure 1. The storm surge from Category 2 Hurricane Carol in 1954 batters New England's Edgewood Yacht Club near Providence, Rhode Island. Image credit: NOAA Photo Library.

The paper is the latest contribution to the field of paleotempestology--the study of past tropical cyclone activity by means sediment deposits, cave speleothems, tree rings, coral deposits, as well as historical documentary records. In this case, the researchers took sediment cores from Salt Pond near Falmouth on Cape Cod, Massachusetts. The pond is separated from the ocean by a 1.3- to 1.8-meter (4.3- to 5.9-foot) high sand barrier. Over hundreds of years, storm surges from Category 2 and stronger hurricanes have deposited sediment over the barrier and into the pond. The scientists were able to calibrate the timing of the intense hurricane strikes by dating the layers from Category 2 Hurricane Bob of 1991, the 1675 (September 7) New England hurricane, and the Great Colonial Hurricane of 1635, which passed across southeastern New England and caused widespread damage consistent with a category 3 hurricane.


Figure 2. Scientists collect a sediment core from Salt Pond in Falmouth, Massachusetts, to study hurricane overwash deposits placed there by storm surges from intense hurricanes. The aluminum tube was vibrated into the muddy sediment at the bottom of the pond and then extracted with a hoist. Image Credit: WHOI

The prehistoric sediments showed that there were two periods of elevated intense hurricane activity on Cape Cod--from 150 to 1150, and from 1400 to 1675. Previous paleotempestology studies also found evidence of high hurricane activity during 150 - 1150 A.D. from the Caribbean to the Gulf Coast. Both time periods had unusually warm sea surface temperatures (SSTs) in the Main Development Region for hurricanes, from the Caribbean to the coast of Africa. Warm ocean temperatures in this region have been linked to increased intense hurricane activity by a number of recent research papers. In recent decades, ocean temperatures in the Main Development Region have surpassed the warmth of prehistoric levels, and these waters are expected to warm further over the next century as the climate heats up, suggesting that intense hurricane activity in New England may return to the levels of 340 to 1800 years ago. However, other factors besides warming SSTs will also shape what happens in the North Atlantic. For example, the pattern of ocean warming could bring more El Niño-style wind shear to the Atlantic, reducing hurricane activity. Still, New England would be wise to take heed of Donnelly's advice that we may need to begin planning for a category 3 hurricane landfall every decade or so rather than every 100 or 200 years.

Jeff Masters

Nell, Dudley and Snidely: Uncertainty

Published: Febrero 17, 2015
Nell, Dudley and Snidely: Uncertainty

In last week’s article I wrote:

Probability and likelihood are notoriously difficult ways to communicate in quiet consultation, and even more difficult in newspapers, on the radio, television and online. Probability and risk are just made for conflicting headlines. The conclusions are, therefore, by definition, uncertain, and uncertainty can always fuel both sides of a rhetorical or a political argument.

I got a very nice comment from Scott Sabol of WJW FOX 8 about the “uphill battle attempting to communicate uncertainty both in day-to-day weather forecasts and the describing of the components of extreme weather events/climate change influence without alienating the audience.” I have seen several blogs since the blizzard forecasts of January 23 – 26 that focus on the need to better quantify and describe the uncertainty associated with winter storms. Uncertainty is subject of this article.

Here’s a still growing record of the Northeast blizzard news cycle on my Tumblr site. This record includes some of the blogs referenced in the previous paragraph that discuss the need for better communication of uncertainty.

In the fall of 2014, I taught a small course on uncertainty, and specifically, on placing uncertainty of climate change in context with other sources of uncertainty in applying climate knowledge to planning and policy. My starting point in many uncertainty discussions is from the uncertainty fallacy; namely, that the quantification and reduction of uncertainty is the primary barrier that hinders the use of scientific knowledge in decision making. During the 1990s, many proposals and measurement missions were sold on the promise of “reducing uncertainty.” If you consider all of the complex processes that make up the climate system and their simplified representation in models, then casual statements that uncertainty will be reduced by any one investigation are not likely to hold up. Uncertainty might be better understood and be better described, but reduction is unlikely. Further, reduction does not assure better usability of knowledge, and in most cases it is not required.

One of my favorite classroom experiences is when the business students in class describe to the scientists and engineers that they are always making decisions in the face of great uncertainty. They want to know how climate uncertainty stacks up against other sources of uncertainty. They also what evidence that changes in the uncertainty descriptions will be incremental; that is, for example, from one assessment to the next, the description is largely the same.

If you listen to the NPR series on Risk and Reason, you will get a feeling of the difficulty of communicating uncertainty and the difficulty that people have in using information about uncertainty. In that series, there are those who advocate never using numbers describing uncertainty in policy contexts, and then there are those thinking of clever and effective ways to communicate numbers to individuals making important decisions. One take away is that how people use information about uncertainty is highly personal. There are often strong elements of fear and want.

Also, in many cases people have an agenda of how they want to use uncertainty – to make something happen or to keep something from happening ( a Rood blog, an ancient Rood blog, and yet another Rood blog, enough).

The quest for uncertainty quantification and highly quantified descriptions of uncertainty to assist in decision making is a mistake often made by scientists. In the cohort of clients I work with, the vast majority is simply not prepared to work with highly quantitative descriptions of uncertainty. Even more to the point, when climate uncertainty is placed into context with other sources of uncertainty, the quantification is overkill. There are studies that suggest, for instance Tang and Dessai (2012), that highly quantified descriptions of uncertainty can, on average, reduce the usability of climate information.

All of these factors together lead to at least one robust conclusion, there is no way to communicate uncertainty in a usable way to everyone. Therefore, you need have several strategies for communicating uncertainty, and you need to frame those strategies for different audiences. In the work that I have done with experts in public health, there is always the discussion about how to communicate a risk, for example, heat waves to the public. There is also the discussion of how to communicate information to first responders and to emergency health providers so that they will be on the lookout for heat-related afflictions. I am not aware that there is any discussion to communicate to anyone the numbers from epidemiological statisticians that one type of heat index has some fractional advantage in predicting heat-related afflictions.

An important point is the need to make a special effort to communicate to those who are trained professionals and have a framework in which to interpret and use uncertainty information. In the case of a weather emergency, one imagines that large cities might have such professionals. One of the most interesting responses that I saw in the Northeast blizzard news cycle was one where funding for experts, interpreters, in providing guidance on the use of forecasts had been eliminated. I don’t know the complete knowledge chain from weather forecast to shutting down a city, but this type of expertise is critical at some place in that knowledge chain.

My whole raison d’être these days is training interpreters on how to use climate knowledge in problem solving. Many of the same principles apply in how to use weather forecasts and how to use science-based knowledge in general. The Northeast blizzard news cycle has been and continues to be a real-world example for both climate and weather. The continued snow storms in Boston, for example, are a wonderful example of relentless patterns of weather that demonstrate that weather is not “random.” However, the biggest lessons are on uncertainty, communication and exaggeration for the benefit of telling a story.

I stated, above, that how we use uncertainty is highly personal. I have used climate knowledge and weather uncertainty to choose the location of a house on the Chesapeake Bay as well as to decide whether of not to take a kayak out into a hurricane. In neither case did I feel I was taking on large risk. This weekend, I (over)heard what seemed to be a discussion of two people deciding not to vaccinate their son because they had determined that their son had exceptional natural immunity. A relevant weather-related example of personal choice and, perhaps, the subconscious is the evidence that people take hurricanes named after women less seriously than hurricanes named after men. It made me think of naming winter storms and what Venus or Vesta might suggest compared to Jupiter or Mars. That, of course, led to Nell, Dudley and Snidely.

One thing that I count on from scientific organizations is a dispassionate description of events and uncertainty. Winter storms, especially if we are going to personify them, need a dispassionate, standard scale to describe them. The weather service has several scales that are effective for hurricanes, tornadoes and storms at sea. Winter storms offer a difficult detail, namely, the rain-ice-snow line, whose boundaries are tricky and important. Climate change offers the additional difficulty that characteristics of storms are changing and expected to change more. Therefore, placing storms within recent and historic context seems like a potentially usable piece of information. We need qualifiers, not number-heavy quantifiers. We don’t need to explain numerical dispersion errors in models to the masses. We don’t need to break down all of the pieces – to speak loudly and more slowly.

From the point of view of the climate scientist and the roles that climate change plays in a particular storm – it is always true that public communication is walking into a maelstrom where people have many agendas of how they want to use uncertainty – to make something happen or to keep something from happening. I have had colleagues tell me that there is an imperative to participate in ever loudening ways to convey the knowledge of climate change. This does not appeal or seem effective to me. Those conversations of deliberate disruption and doubt need to be identified for what they are and left in their stewing pool. We need to persistently differentiate the important aspects of climate change, isolate the deliberate disruption, and more effectively expose that which is important about climate change in the many conversations that are emerging.

r

Headlining Again: Flirting with Insufferable

Published: Febrero 9, 2015
Headlining Again: Flirting with Insufferable

Two weeks ago, on January 25, a public affairs representative asked me if I wanted to make a statement in advance of the historic blizzard predicted for the Northeast. After that conversation, a little write up was released offering me up as an expert for the press. My comment was that I didn’t think the storm should be conflated with climate change, and I had doubts about it being “historic.” This, of course, assured that no one would call me in advance of the blizzard. My more pithy comment, that it would be historic in the sense that it was consistent with history, did not carry the day either. Given the way the forecast and the reporting unfolded, I have been given an opportunity to be completely insufferable.

Here’s a little record of the news cycle on my Tumblr site.

Given that my last blog was on the role that we scientists sometimes play in fueling climate-science controversies, the blizzard seems like a natural follow on. In fact, the 2011 piece with Christine Shearer, “Changing the Media Discussion on Climate and Extreme Weather,” used the example of event attribution as a place where scientists fuel headlines that are not always productive.

Here are the three reasons that I declined to conflate the storm with climate change and to talk about a potential “historic” event.

1. The practice of trying to attribute some portion of a storm to climate change is a no-win practice. I understand the curiosity that leads to public interest. I understand the curiosity of the scientific investigation of event attribution. I am not convinced that there is any policy relevance of event attribution.

We have one climate, the Earth’s climate. We have one atmosphere. If we focus on the atmosphere, then we have weather that occurs in the atmosphere, and we have the climate of that atmosphere. Weather and climate are both ways that humans describe temperature, moisture, winds, etc., in this case, associated with the atmosphere. Weather and climate are not separate and independent things; they are different descriptions of the same measures of the atmosphere. If climate changes, weather changes. If weather changes, climate changes. Therefore, every weather event occurs in our changing climate on our warming Earth. Since our understanding and description of weather relies on temperature, moisture, wind, and how they vary, it is unrealistic to imagine that weather events are not influenced by the changing climate.

The questions of how an event differs, today, in our warmer climate from a similar event in the past, can be addressed, but such a determination relies upon statistics and statements of probability and likelihood. Conclusions are never definitively verifiable. Probability and likelihood are notoriously difficult ways to communicate in quiet consultation, and even more difficult in newspapers, on the radio, television and online. Probability and risk are just made for conflicting headlines. The conclusions are, therefore, by definition, uncertain, and uncertainty can always fuel both sides of a rhetorical or a political argument. Therefore, as with marking one temperature record after another, attribution headlines obscure what is important about climate change.

2. As in my series on the not so “super El Nino,” predicting an extreme event as super, historic or unprecedented mostly sets the predictor up as a foil to those interested in maintaining the turmoil of conflicting headlines. Extreme events are rare, and an event that is more extreme than any previous extreme event is rarer. Therefore, many things have to come together to justify such a prediction. I count on the dispassionate language of science-based organizations to describe model forecasts. The appearance of imprecise adjectives of extremes should be expected to fuel an extreme-fascinated society into its next exercise of false urgency and compulsion for crisis management. When I was asked to comment on whether or not a historic storm was likely for a particular place at a particular time, the forecast was far too distant in the future; too many things had to come together, perfectly, to justify such a prediction.

3. I am not a weather forecaster. I have worked with outstanding forecasters. I have managed the building and verification of weather-forecasting systems and climate models. There were a number of attributes of the model prediction that raised yellow flags. This included the fact that weather-forecast reporting, now, has the gamesmanship of Euro versus U.S.

What were the yellow flags? The forecast was for a fast moving disturbance to move across the continent, to interact with a front off of the East Coast, to grow, and to move to the north and east. The first yellow flags were a lot of moving parts and growing. Then, there is a set of aspects that put up more warning flags. There is the need to get water from the warmer-than-normal ocean, transport that water, and convert it to rain and snow. These are aspects of modeling that are difficult to represent and more different to link together.

Within the model, there are events occurring on different measures (scales) of space and time. The evaporation of water is represented in the models in areas on the Earth’s surface that are a few kilometers on their sides. The actual evaporation occurs in much smaller representative areas and depends on many unrepresented details of the Earth’s surface. The evaporation, the transport, and the conversion of water from liquid to vapor, from vapor to water, ice and snow, must be organized into moving and growing storms whose geographical extent is from 10 to 100 times larger. We want to know the transition line between rain, sleet and snow. Then, after all of these elements of a storm are collected together and forecast into the future, we ask the model to give us an answer that distinguishes Manhattan from Queens from Hauppauge. We want answers separated by smaller distances than the smallest distances that the models represent. The expectations are not in realistic alignment with possibility. There are too many things that have to come together in the 24-48 hours of the forecast to justify the hyperbole of super, historic and unprecedented.

Weather and climate models are amazing and powerful tools. They help us think about what the weather and climate will do. They help us think about how to prepare. They also have intrinsic, sometime irreducible limitations. With regard to this weather forecast, if a model represents the surface of the Earth with patches of surface than are 10 km on the side, then the uncertainty associated with a particular weather event is more like 50 to 100 km (Recent effective resolution paper). Within that range of uncertainty, the forecast of the 2015 Northeast blizzard was spot on.

Weather and climate models are powerful and dispassionate tools. They have no control over how we take that information, determine knowledge content, describe that knowledge, react to that knowledge and use that knowledge. There are those trained in interpretation of forecasts and the prediction of weather events. There are those trained in the identification of vulnerabilities and assessment of risk. There are those trained in response to perceived risk and in response to realized risk. There are those trained in communication, and those trained in capturing audience. Increasingly, we allow our communication to be framed by those experts in capturing audience; we watch stories flame in news cycles that are rife with inaccuracy and incompleteness. We allow the foibles of communication to damage the chain of expertise for making and using forecasts.

This weekend Dean Smith died. Dean Smith has a larger-than-life iconography in sport, society and life. Smith was notorious for causing chaos at the end of basketball games when Carolina was trailing. In that chaos was opportunity. Weather, climate and the relationship of weather and climate play out in public, where there are many chattering voices looking for attention and audience – mine included. The desire to predict, for rightness and for attention motivates us to take distinguishing positions that differentiate us from others. This is chaotic. Then there are those in the climate-change conversation who are deliberately chaotic. As scientists claiming to advocate knowledge-based decisions, we must understand that we step into this world of natural and manufactured chaos. There are things we do repeatedly, record marking and event attribution amongst them, which help fuel the chaos, and obscure what is important about climate change.

r
About the Blogs
These blogs are a compilation of Dr. Jeff Masters,
Dr. Ricky Rood, and Angela Fritz on the topic of climate change, including science, events, politics and policy, and opinion.
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