Damage from sever weather in Missouri shows a different pattern than does damage nationwide. As Figure 1 shows, the cost of damage from hazardous weather events in Missouri spiked in 2007, then really spiked in 2011. Since then, it has returned to a comparatively low level. The bulk of the damage in 2011 was from 2 tornado outbreaks. One hit the St. Louis area, damaging Lamber Field. The second devastated Joplin, killing 158, injuring 1,150, and causing damage estimated at $2.8 billion. The damages in 2007 came primarily from two winter storms, one early in the year, one late. In both cases, hundreds of thousands were without power, and traffic accidents spiked.
In 2015 Missouri saw an increase in weather-related damage, primarily due to the flooding that struck between Christmas and New Years that year. There was similar flooding this year in April, so 2017 will likely see a similar increase.
Figure 2 shows deaths and injuries in Missouri from hazardous weather. Deaths are in blue and should be read on the left vertical axis. Injuries are in red and should be read on the right vertical axis. The large number of injuries and deaths in 2011 were primarily from the Joplin tornado. In 2006 and 2007, injuries spiked, but fatalities did not. The injuries mostly represented non-fatal auto accidents from winter ice storms. The fatalities in 1999 resulted from a tornado outbreak.
The Missouri data covers fewer years than the national data discussed in my previous post. It also covers all hazardous weather, in contrast to the national data, which covered billion dollar weather disasters.
While the national data shows a clear trend towards more big weather disasters, Missouri’s data does not. The Missouri data seems to reflect the kind of disaster that occurred and where it occurred. Tornadoes, if they hit developed areas, cause injuries, deaths, and lots of damage. Floods cause fewer injuries and deaths; damage can be significant, but it is limited to the floodplain of the river that flooded. Ice storms affect widespread areas; damages come mostly through loss of the electrical grid and car crashes, which cause many injuries, but fewer deaths.
Office of Climate, Water, and Weather Services, National Weather Service. 2016. Natural Hazard Statistics. Data downloaded 9/11/2017 from http://www.nws.noaa.gov/om/hazstats.shtml#.
InflationData.com. 2016. Historical Consumer Price Index (CPI-U) Data. Data downloaded 2/10/16 from http://inflationdata.com/Inflation/Consumer_Price_Index/HistoricalCPI.aspx?reloaded=true.
Missouri State Emergency Management Agency. Declared Disasters in Missouri. Viewed online 9/12/2017 at https://sema.dps.mo.gov/maps_and_disasters/disasters.
Descriptions of specific weather events, if they are large and significant, can be found on the websites of the Federal Emergency Management Administration, the Missouri State Emergency Management Agency, and local weather forecast offices. However, in my experience, the best descriptions are often on Wikipedia.
The number of severe storms is increasing, and so is their intensity.
In the previous post I noted that Hurricane Harvey was one in a series of storms that have devastated Houston, and indeed, the country as a whole. I asked what is going on, and whether it has always been this way.
The National Centers for Environmental Information tracks weather disasters that cause over $1 billion in damages. Figure 1 shows how many there have been each year going back to 1980. The number varies from year-to-year, but over time there has been a significant increase – there weren’t any in 1987, but in 2011 there were 16. Through July 7, 2017, roughly half the year, there have been 9.
(Click on chart for larger view.)
In the chart, the colors represent different types of weather disasters. Storms are divided into 3 categories: winter storms, which involve ice and snow, tropical cyclones (like Hurricane Harvey or Tropical Storm Irene), and severe storms. This last category includes thunderstorms and tornadoes, as well as severe rain events like the ones that caused flooding in Missouri in December 2015 and April 2017. You can see that the increased number of billion-dollar disasters has come from an increase in the number of severe storms. It has not come from tropical storms or winter storms.
Figure 2 shows the damage cost from billion-dollar weather disasters each year. The damage cost is adjusted for inflation. The chart shows that there are many years when the total cost is below $25 billion. However, there are also years where the amount of damage spikes. The year with the largest damage was 2005, when Hurricane Katrina devastated New Orleans and a wide swath of the Gulf Coast, and damage topped $213 billion. That’s quite a chunk of change. The second highest cost occurred in 2012, when Hurricane Sandy came ashore in New York. This year, 2017, only includes damage up to July 7, so it doesn’t include Hurricane Harvey or Irma. I have seen news stories that the cost of damage from Hurricane Harvey may reach $150 billion, and Irma will add billions more. By the time the year is done, the damage cost is likely to be the highest in history.
Figure 3 shows the number of billion dollar weather disasters by type (through 7/7/2017). Since 1980, there have been a total of 212. Severe storms have accounted for 42% of the events.
Figure 4 shows the total costs of billion dollar weather disasters by type (through 7/7/2017). Since 1980 costs have totaled $1.24 trillion dollars, and tropical cyclones have accounted for about 47% of the total cost. Though they constitute the largest number of events, severe storms account for only 16% of the cost of damages. That is because such storms, while severe, affect relatively small areas. Tropical storms and droughts, on the other hand, affect much larger areas.
All of the highest cost years have occurred since 2004. The data is inflation-adjusted, so that should not be the reason. One possible reason not related to the weather is that there are more people living in harms way – the population living along the coast has grown, and sprawl has caused more of the landscape to be covered with development, increasing the likelihood that a severe storm will hit something and damage it. For instance, in 1920 the population of Miami-Dade County (the location of the City of Miami) was 42,753 (that’s right, less than 50,000). But in 2010 it was 2,507,362. In 1992, when Hurricane Andrew devastated Homestead, a small community southwest of Miami, the area between Miami and Homestead was mostly open agricultural fields. Today, just 15 years later, it has filled-in, and is one continuous urban area. This story has been repeated all along the coasts of America, and in many inland areas as well. (See here.)
But I think that’s only part of the story. The number of tropical storms striking the U.S. may not have increased, but their intensity has. Figure 6 shows the intensity of tropical storms in different regions of the world over time. LMI stands for the lifetime maximum intensity of the wind in a storm, in meters per second. The lines represent quantiles. The 0.9 line (pinkish-purple) means that 90% of all storms that year were less intense than that value. The 0.8 line (light blue) means that 80% of all storms were less intense than that value, and so on. The authors dropped trend lines on the chart for each quantile. In the North Atlantic, storms have increased in intensity a lot. Those are the storms that strike the East Coast and Gulf Coast of the United States.
Other kinds of heavy precipitation events are also on the rise, as I reported here. Figure 7 repeats a chart from that post showing the trend over time.
Scientists project that climate change will cause an increase in storm intensity and in heavy rain events. It seems that this is not a prediction for the future, it is already happening. One cannot say that any individual storm is caused by climate change, but storms like Hurricane Harvey, Tropical Storm Irene, and the April storm in Missouri are already “more common,” and are likely to be even more “more common” in the future.
GlobalChange.gov. Broadcase_Trends-in-heavy-precip_V2. National Climate Assessment 2014. Downloads, Graphics (Broadcast). Downloaded 11/13/2016 from http://nca2014.globalchange.gov/downloads.
Kossin, James, Timothy Olander, and Kenneth Knapp. 2013. Trend Analysis with a New Global Record of Tropical Cyclone Intensity. Journal of Climate, 26, 9960-9976.
Miami Design Preservation League. Collins Ave. at 63rd Street in 1925.Downloaded 9/8/2017 from https://www.pinterest.com/pin/189714203027788727.
NOAA National Centers for Environmental Information (NCEI). U.S. Billion-Dollar Weather and Climate Disasters (2017). https://www.ncdc.noaa.gov/billions.
Wikipedia. Miami-Dade County, Florida. Viewed online 9/8/2017 at https://en.wikipedia.org/wiki/Miami-Dade_County,_Florida#2010_U.S._Census.
Hurricane Harvey caused record flooding in Houston. Those poor people!
Most of you know about the terrible disaster that Hurrican Harvey caused in Houston, TX. The disaster will inevitably be compared to Hurricane Katrina and the flood that struck New Orleans. In both cases, a major city was flooded by a hurricane. Houston, however, is a metropolitan area with a population of about 6.3 million people, while New Orleans is a metropolitan area with a population of about 1.3 million. That means that Houston is almost 5 times as large.
New Orleans flooded so catastrophically because much of the city is below sea level. The levies broke, the ocean poured through, and the low areas filled up with water just like a bathtub would. Coastal Texas is a flat, low-lying area, some of which was swamp or marshland before being developed. It is not below sea level, however. Houston flooded because Hurricane Harvey dumped prodigious amounts of rain on the city – more than 4 feet of rain in some areas. The water couldn’t run off fast enough, and flooding occurred. The tragedy has been well covered by all of the national news sources, so I have contented myself with a single photograph of the flooding in Port Arthur, a small city about 100 miles northeast of Houston. (Figure 1) This blog focuses not on individual events, but on trends and on the big picture.
(Click on photo for larger view.)
Houston has been hit repeatedly by tropical storms and hurricanes. From 1836 to 1936, the city suffered through 16 major floods, with the water level reaching as high as 40 feet in one of them. Since 1935, there have been 8 more. In 2001, Tropical Storm Allison dumped up to 35 inches of rain on Houston over 5 days, resulting in flooding that damaged over 73,000 homes and caused $5 billion in property damage (see Figure 2). In 2008, Hurricane Ike passed directly over the city, breaking out windows in downtown skyscrapers and wiping out electricity to some customers for over a month. Over the Memorial Day Holiday in 2015, rain of up to 11 inches over 24 hours drenched Houston, flooding thousands of homes. In April 2016 (last year), a trough of rain parked over the city, and over 24 hours, 17 inches of rain fell. They had to rescue 1,800 people from the floods, but even so 8 died and 1,144 homes were inundated.
But flooding is not limited to Houston. In April of this year, flooding in Missouri and Arkansas caused $1.7 billion in damages. In February, flooding in California caused $1.5 billion in damages, including Oroville Dam (see here). In October, 2016, Hurricane Matthew churned along the Atlantic Coast causing damage. In August, 2016, Louisiana received 20-30 inches of rain from a stationary storm, causing $10.3 billion in damages. And a December 2015 storm brought record flooding to Missouri and tornadoes to Texas, causing 50 deaths and $2.5 billion in damages. The list goes on and on.
UPDATE: As of 9/8/2017, three more tropical storms have formed in the Atlantic Ocean: Hurricane Irma, a Catagory 5 hurricane (the largest category), passed over several Caribbean islands causing terrible damage (see Figure 3). As I write, it is bearing down on Florida. How bad will it be? We don’t know; it has diminished to a Category 4 hurricane, but it is wider than the Florida Peninsula is, and it is currently forecast to travel south to north right up the entire peninsula. Tropical Storm Jose is gaining strength in the mid-Atlantic, threatening many of the same islands that were just devastated by Irma, though it is forecast to turn north. And Hurricane Katia has formed just north of the Yucatan Peninsula, and is expected to come ashore north of Veracruz, Mexico.
What is happening? Has it always been this way, or is there more very damaging weather than there used to be? The next post will look at the national trend, and the post after that will look at the trend in Missouri.
Gerb van Es, Dutch Department of Defense. Aerial Photo Shows the Damage of hurrican Irma in Phillipsburg, on the Dutch portion of the Caribbean Island of Sint Maarten. Downloaded 9/8/2017 from https://www.caymancompass.com/2017/09/07/enormous-catastrophe-st-martin-reeling-from-hurricane-damage.
Harris County Flood Control District. Harris County’s Flooding History. Viewed online 8/30/2017 at https://www.hcfcd.org/flooding-floodplains/harris-countys-flooding-history.
Harris County Flood Control District. Tropical Storm Allison. Viewed online 8/30/2017 at https://www.hcfcd.org/storm-center/tropical-storm-allison-2001.
NOAA National Centers for Environmental Information (NCEI) U.S. Billion-Dollar Weather and Climate Disasters (2017). https://www.ncdc.noaa.gov/billions.
South Carolina National Guard. 8/31/2017. Image #170831-Z-AH923-081. Downloaded 9/8/2017 from https://commons.wikimedia.org/w/index.php?curid=62096178.
Wikipedia. April 2016 United States Storm Complex. Viewed online 8/30/2017 at https://www.hcfcd.org/storm-center/tropical-storm-allison-2001.
Wikipedia. Houston. Viewed online 8/30/2017 at https://en.wikipedia.org/wiki/Houston.
Wikipedia. New Orleans. Viewed online 8/30/2017 at https://en.wikipedia.org/wiki/Houston.
Despite the wet winter in 2017, climate change will pose severe challenges to California’s future water supply.
In the last post I reported that Gov. Brown has declared California’s drought emergency officially over. The state has plenty of water for the next year. This post explores the implications of this wet winter for California’s long-term water status.
I first looked at this topic in a 13-post series that ran during the summer of 2015. The series starts here. It contains a lot of information about California’s water supply and consumption. I concluded that at some point in the not-too-distant future California would experience a significant permanent water deficit. The #1 cause of the deficit would be climate change, which is projected to result in a significant reduction in the size of California’s snowcap. The #2 cause would be population increase. I performed the analysis myself because I could find no sources that did anything similar. I’m not going to repeat that analysis in this post. Rather, I’m going to report a couple of new reports that confirm the concerns I had in 2015.
Figure 1 illustrates the problem California faces. Almost all of California’s precipitation falls during the winter. Some of it gets temporarily “locked up” as snowpack on the Sierra Nevada mountains. Demand for water, however, peaks during the summer. California has many man-made reservoirs that release water during the summer and fall, and the state depends on the melting snowpack to recharge the man-made reservoirs as water is drawn from them. In Figure 1, the blue line represents runoff and the red line represents water demand. You can see that moving the date of maximum runoff earlier in the year increases the amount of water that cannot be captured into storage (yellow area). It has to be dumped; see the post on Oroville Dam to see what happens if the volume of water being dumped gets too high. It increases the amount of water that must be released from storage in the summer and fall. The amount released is now larger than the amount of inflow the reservoir receives, resulting in an increased water deficit (the blue area represents water received, the green area represents water discharged equal to the size of the blue area, and the red area represents the deficit). There is a water deficit in average years, but it is small, and a winter with slightly above average precipitation can make up the deficit. Moving maximum runoff earlier in the year increases the size of the deficit; now only a much wetter year can recharge the reservoirs.
Figure 2 includes two charts. The first chart shows the percentage of precipitation in California that occurred as rain from 1948-2012. If precipitation occurs as rain, it is not snow and can’t add to the snowpack. On the chart, the black horizontal line is the mean percentage across all years. Red columns represent years with above average percentage of rain, the blue columns below average. There is variation between years, but you can see that the red columns cluster to the right while blue columns cluster to the left. That means that on average an increasing percentage of precipitation is falling as rain. Thus, on average, unless annual precipitation undergoes a sustained increase (which hasn’t happened and is not projected), California’s snowpack will shrink, because what once was snow is now rain.
The second chart in Figure 2 shows runoff measured on the Sacramento River. The red line represents the 50-year period from 1906-1955, while the blue line represents the 52-year period from 1956-2007. This is the specific problem that was discussed conceptually in Figure 1. You can see that runoff has moved earlier in the year by about a month.
Why is more precipitation falling as rain rather than snow, and why is melt occurring earlier? Because of increased temperature. Winter is when the snow falls in California, and it is when the state receives the bulk of its precipitation. Figure 3 shows that the average winter temperature (December – March) has increased more than 2°F. In addition, if you look at Figure 3 carefully, you can see that the rate of temperature increase accelerated somewhere around 1980. The runoff chart in Figure 2 chunks the data into only 2 groups, each about 50 years long. Because of the acceleration in the increase in temperature, I believe that if they had chunked the data into 3 groups, each about 33 years long, the change towards earlier snowmelt would have been even greater than the one shown.
How dire is the threat is to California’s snowpack? It depends on which climate projection is used. The projected effects of climate change depend very much on how humankind responds to the threat. If we greatly reduce our GHG emissions immediately, the climate will warm less; if we don’t, it will warm more.
Figure 4 shows the historical size of the California snowpack plus 2 projections. The middle map show the projected size of the snow pack if warming is less. The map on the right shows its size if warming is more. You can see that, even under the low warming scenario, a loss of 48% of the snowpack is projected. Under the high warming scenario, a 65% loss of the snowpack is projected. These projections are for the end of the century. In my original series, I estimated the loss of snowpack at 40% by mid-century. That is not too far off from the high warming scenario. And I have to say, the evidence suggests that so far the world is operating under the high warming scenario, possibly, even worse.
Surface water is not the only source on which California depends. California withdraws significant amounts of water from underground aquifers, especially in (but not limited to) the agricultural areas of the Central Valley. Aquifers can be compared to underground lakes, but don’t think of them as being like a big, hollow cave in which there is a concentrated, pure body of water. Rather, think of them as regions of porous ground, such as gravel or sand. In between the pieces of gravel or sand is space, and that space can hold water. Below and on the sides are rocks or clay that are impervious to water, which allow the water to be held in the aquifer.
So long as the aquifer is charged with water, this is a situation that can last for thousands of years. If, however, water is pumped out without being replaced, then nothing occupies the spaces between the pieces of gravel or sand. If that occurs, the weight of the ground over the aquifer can compress the aquifer, reducing the amount of space available between the pieces of sand and gravel, reducing the capacity of the aquifer to hold water. When this occurs, it sometimes shows up as subsidence on the surface. In California, it is primarily the snowpack that feeds the aquifers. If a significant amount of the snowpack is lost, it will be less able to recharge the aquifers, and they will undergo increased compaction.
As noted in my original series, significant subsidence has already occurred over California’s aquifers. More seems to be occurring every year. A recent study attempted to quantify the amount of water storage capacity being lost to compaction. The study covered the years 2007-2010, so it didn’t even include the recent severe drought (2007, 2008, and 2009 were dry years, but 2010 was 9th wettest in the record). The study covered only a small portion of the south end of the Central Valley Aquifer, yet it found that during those 4 years significant permanent subsidence had occurred (see Figure 5), resulting in a total loss of 748 million cubic meters of water storage, an amount roughly equal to 9% of the groundwater pumping that occurs in the study area. If this ratio held going forward, it would mean that for every 44.4 gallons of water pumped out each year, about 1 gallon of aquifer storage would be lost.
During the recent drought many newspaper articles reported that there had been a sharp increase in the number of wells being drilled in the Central Valley, and that the depth of the wells had also significantly increased. This suggests an increase in the rate at which the water table is being lowered, which would lead to an increased rate of compaction. As the study notes, this is a loss that cannot be replenished; aquifer storage lost to compaction is gone forever.
Dry periods become more devastating when they occur during hot periods. One reason the recent drought in California was so devastating was because it was a hot drought. A recent study found that climate change has already raised the temperature in the state (as in Figure 3 above), and will continue to raise it further, to the point that every dry year is likely to be a hot drought. The report concludes that anthropogenic warming has substantially increased the risk of severe impacts on human and natural systems, such as reduced snowpack, increased wildfire risk, acute water shortages, critical groundwater overdraft, and species extinction.
The bottom line here is that we are talking about the effects of climate change. Climate means average patterns over long periods of time – 30 years at minimum. The current wet period represents only 1 winter. Just as one swallow doesn’t make a summer, so one wet winter doesn’t make a climate trend. For that matter, neither do 5 dry years. However, California’s increase in temperature is a long-term change that does make a climate trend, and every indication suggests it will only increase more.
My conclusion is that this wet winter not withstanding, the concerns I voiced in 2015 over California’s water supply remain valid. As time passes, California will face increasing challenges meeting the demand for water (see here). The state will be unable to secure large new sources of surface water or ground water (see here), and will have to construct large, expensive desalination plants (see here). There will be sufficient water to supply human consumption if it is properly allocated (see here), but water available to agriculture will be reduced, resulting in a decline in California’s agricultural economy (see here). That loss, plus the cost of the desalination plants, will impact California’s economy (see here), as well as the food supply for the entire country.
[In the above paragraph I have referenced several of the posts in my 2015 series Drought in California. If you are interested in the topic, you should read the series sequentially, beginning with Drought in California Part 1: Introduction.]
California Department of Water Resources. 2015. California Climate Science and Data for Water Resources Management. Downloaded 4/6/2017 from http://www.water.ca.gov/climatechange/docs/CA_Climate_Science_and_Data_Final_Release_June_2015.pdf.
Diffenbaugh, Noah, Daniel Swain, and Danielle Touma. 2015. “Anthropogenic Warming Has Increased Drought Risk in California.” Proceedings of the National Academy of Sciences. Downloaded 3/30/2017 from http://www.pnas.org/content/112/13/3931.
National Centers for Environmental Information. “California, Average Temperature, December-March, 1896-2016” Graph generated and downloaded 4/13/2017 at https://www.ncdc.noaa.gov/cag/time-series/us.
Smith, R.G., R. Kinght, J. Chen, J.A. Reeves, H.A. Zebker, T. Farr, and Z. Liu. 2016. “Estimating the Permanent Loss of Groundwater Storage in the Southern San Joaquin Valley, California.” Water Resources Research, American Geophysical Union. 10.1002/2016WRO19861. Downloaded 3/30/2017 from http://onlinelibrary.wiley.com/doi/10.1002/2016WR019861/full.
Gov. Jerry Brown officially declared California’s drought emergency over on Friday, April 7. It was a fitting ending to one of the worst episodes in California’s drought-laden history.
Or was it? The next two posts update California’s water situation. This one focuses on the current short-term situation. The next one focuses on the future, with an eye toward the future impact of climate change. I have personal reasons for following California’s water situation – I have family living there. But in addition, California is the most populous state in the Union, it has the largest economy of any state, and the state grows a ridiculously large fraction of our food. What happens in California affects us here in Missouri.
Is the short-term drought truly over? Yes, I think so. The vast majority of California’s precipitation falls during the winter, and the snowpack that builds up in the Sierra Nevada Mountains serves as California’s largest “reservoir.” As it melts, it not only releases water that represents about 30% of the state’s water supply, but it also feeds water into the underground aquifers that provide groundwater to much of the state. Thus, the size of the snowpack is the most important factor in determining California’s water status. California measures the water content of the snowpack electronically and manually. The measurements around April 1 are considered the most important, as that is when the snowpack is typically at its largest. Figure 1 shows the report for this year. Statewide, the water content of the snowpack was 164% of average for the date, almost 2/3 larger than average. The water content was significantly above average in all three regions of the snowpack, North, Central, and South.
I follow the snow report at Mammoth Mountain Ski Resort to provide a specific example of the snow conditions. Figure 2 shows that through March, Mammoth received over 500 inches of snow, one of the highest totals in the record going back to 1969-70. The column for 2016-17 has very large blue and orange sections, indicating that the majority of the snow fell in January and February. Figure 3 confirms the impression. It charts the amount of snowfall at Mammoth during each month of the 2016-17 snow season, and compares it to the average for that month across all years. You can see that both January and February were monster snow months, especially January. By March, snowfall had already fallen below average. I wouldn’t make too much of this fact, one month doesn’t make a trend.
California also stores water in man-made reservoirs. Figure 4 show the condition of 12 especially important ones on March 31. Most were above their historical average for that date, and many were approaching their maximum capacity. Those who follow this blog know that the Oroville Reservoir actually received so much water that it damaged both the main and emergency spillways, threatening collapse of the dam and requiring evacuation of thousands of people down stream. (See here.)
In addition, Southern California receives the lion’s share of water drawn from the Colorado River, thus the status of Lake Mead, the largest reservoir on the Colorado, is important to the state. A study in 2008 found that there was a 50% chance the reservoir would go dry by 2021. On March 31, Lake Mead was at 1088.26 feet above sea level. (This doesn’t mean there were that many feet of water in the reservoir, Hoover Dam isn’t that tall. Rather, it represents how many feet above sea level the surface of the water was. Lake Mead’s maximum depth is 532 feet.) The current level represents 41.38% of capacity. Figure 5 shows the level of the lake over time. You can see that the line tends to go up with the spring snowmelt, and down during the rest of the year. This year it is up very slightly year-over-year, but the trend has been relentlessly down since 2000.
The conclusion seems inescapable: for this year at least, California has plenty of water. The short-term drought is over. One year doesn’t make a climate trend, however. In the next post I will consider the implications of this wet winter for California’s water situation going into the future.
Barnett, Tim, and David Pierce. 2008. “When Will Lake Mead Go Dry?” Water Resources Research, 44, W03201. Retrieved online at http://www.image.ucar.edu/idag/Papers/PapersIDAGsubtask2.4/Barnett1.pdf.
CA.GOV. Governor Brown Lifts Drought Emergency, Retains Prohibition on Wasteful Practices. Viewed online 4/10/2017 at https://www.gov.ca.gov/home.php.
California Data Exchange Center. Conditions for Major Reservoirs: 31-Mar-2017. Viewed online at http://cdec.water.ca.gov/cdecapp/resapp/getResGraphsMain.action.
California Department of Water Resources. Snow Water Equivalents (inches) for 3/30/2017. Viewed online 3/31/2017 at http://cdec.water.ca.gov/cgi-progs/snowsurvey_sno/DLYSWEQ.
Mammoth Mountain Ski Resort. Snow Conditions and Weather, Extended Snow History. Data downloaded 4/2/2017 from http://www.mammothmountain.com/winter/mountain-information/mountain-information/snow-conditions-and-weather.
2016 was an above average year for precipitation in Missouri and across the United States.
In 2016, precipitation across the Continental United States averaged 31.70 inches. That is above average, but not a record. Figure 1 shows the precipitation trend over time. The green line represents measured precipitation, the blue line represents the linear trend over time, and the black line represents the average yearly precipitation over the reference period (1901-2000). The trend suggests that precipitation is increasing, and that the United States receives, on average, about 2 inches more precipitation per year than it did in 1895.
Some parts of the country receive more precipitation, others less. In addition to the trend, we want to see is how various regions of the country fared compared to usual. Figure 2 shows 2016 precipitation anomalies for climate divisions across the Continental United States. On the map, green represents above average precipitation, while yellow, red, and purple represent below average.
Regions of the Pacific Northwest, Texas/Louisiana, Minnesota/Wisconsin, and the Mid-Atlantic Coast received rainfall much above average. The Mid-Atlantic Coast was impacted by 7 tropical storms (!), but none of the other regions were. Louisiana was the site of massive flooding in August that was related to an extraordinary heavy rainfall event, but not a tropical storm. (See here for my post on heavy rainfall events.)
Dry areas included Oklahoma, portions of the Northeast, and a large area centered near Atlanta, GA. This last area received as much as 18 inches of precipitation less than normal, and it has entered a drought that is graded as “Extreme” by the U.S. Drought Monitor.
Meanwhile, precipitation in the Pacific Northwest has brought much of that area out of short-term drought, and a recent set of storms hold promise for the California snowpack. Mammoth Mountain (a ski resort in the Central Sierra Nevadas) is running about 4% ahead of the October-January total for last year, and there are still 2+ weeks left in January.
Parts of California, however, were so far behind that they haven’t yet resolved the long-term drought situation. This is particularly true for a region of mid-coastal California, from about Big Sur down to Santa Barbara. This area remains in an “Exceptional” drought, and as of 12/20/2016, the Gibralter Reservoir was completely empty, and the Cachuma Reservoir was down to 8% of capacity. San Diego relies on these two reservoirs for 82% of its water supply. As I write, it is raining today in Santa Barbara, and since January 1, it has rained about 2.1 inches more than average. Hopefully, even this most stubborn remnant of the drought will finally break.
Figure 3 shows annual precipitation in Missouri over time. Statewide, Missouri received 0.55 inches less precipitation than average, basically an average year. The trend, however, suggests that over time precipitation is increasing across the state at the rate of 0.24 inches per decade.
Looking at Figure 2 shows that precipitation varied by region of the state. The northwestern and southeastern portions of the state received above average precipitation, while the rest of the state received below average. In particular, Southwest Missouri, the area around Springfield, Branson, and Joplin, was on the edge of the dry region centered on Oklahoma, and it received 4.3 inches less than average.
For the period 1895-2016, no region of the country shows a strong trend toward decreased precipitation. The Northeast, the Ohio Valley, the Upper Midwest, and the South all show significant trends towards increased precipitation.
City of Santa Barbara. Drought Information. Viewed online 1/10/2017 at http://www.santabarbaraca.gov/gov/depts/pw/resources/system/docs/default.asp
National Drought Mitigation Center. U.S. Drought Monitor for 1/3/2017. Viewed online 1/10/2017 at http://droughtmonitor.unl.edu.
NOAA Los Angeles/Oxnard Weather Forecast Office. Climatological Report (Daily) for January 11, 2017. Viewed online 1/12/2017 at http://w2.weather.gov/climate/index.php?wfo=lox.
NOAA National Centers for Environmental information, Climate at a Glance: U.S. Time Series, Average Temperature, published January 2017, retrieved on January 9, 2017 from http://www.ncdc.noaa.gov/cag.
In the United States, 2016 was the second hottest year on record, replacing 2015, which is now the third hottest.
Weather data for 2016 has been posted on the Climate at a Glance data portal operated by the National Centers for Environmental Information. Figure 1 shows average temperature trend for the contiguous 48 states. The purple line represents the yearly average, the blue line represents the trend over time, and the black line represents the average temperature over the entire reference period (1901-2000).
The average temperature for 2016 was 54.91°F, some 2.89°F above the mean, the second warmest year in the record. The warmest year was 2012 at 55.28°F. The third warmest was 2015 at 54.40°F. There is a lot of variability from year-to-year, but the trend is clearly upward, especially since about 1980.
Figure 2 shows the trend in the average daily maximum temperature (red line), the average daily minimum temperature (blue line), and the average daily average temperature (orange line). I have dropped a dashed linear trend line on each.
If you look at the trend lines carefully, you can see that, while all three are increasing, the trend for minimum daily temperature is steepest, followed by daily average temperature, with the trend for daily maximum being least steep. Though they are not shown on the chart, the equations for the trend lines confirms the visual impression: the average daily minimum temperature is increasing faster than the daily maximum temperature. This finding is consistent with projections for climate change: as the temperature warms, the atmosphere can hold more humidity. The humidity reduces the amount of cooling that occurs at night.
In Missouri, the average temperature was 57.4°F, the fifth highest reading in the record. The highest reading occurred in 2012. Figure 3 shows the Missouri temperature trends. The red line at the top shows the average daily maximum temperature, the orange line in the middle shows the average daily average temperature, and the blue line at the bottom shows the average daily minimum temperature. The dashed lines show the trends.
The trend lines show that the national pattern applies in Missouri: minimum daily temperature is increasing most rapidly, followed by daily average temperature, then daily maximum temperature. The change in Missouri is less than the average nationwide change, and the reason is, again, humidity. Missouri is a humid state, and it takes more energy to change the temperature here than it does in a dry state.
Because I have been following the water situation in California, I will note that the average temperature there in 2016 was 60.2°F, the third highest since record keeping began. The highest on record occurred in 2014, and the second highest in 2015. Thus, it has been a really warm 3 years in California.
To summarize, 2016 was warmer than average. Across the entire contiguous United States, it was the second warmest year in the record, while in Missouri it was the fifth warmest.
I’ll look at precipitation during 2016 in the next post.
NOAA National Centers for Environmental information, Climate at a Glance: U.S. Time Series, Average Temperature, published January 2017, retrieved on January 9, 2017 from http://www.ncdc.noaa.gov/cag.
If you have been watching the national news, you know that California has had record precipitation for the winter so far. There has been so much rain that one of the state’s biggest reservoirs, Lake Oroville, has exceeded its capacity. Water flowing through the emergency spillway has eroded portions of the dam, threatening a dam collapse that would kill thousands and wipe out communities below the dam. Emergency efforts are underway to repair the dam.
Following are two photos that show just how badly the dam has been damaged. The photos are a bit hard to interpret, but here’s what I think they show: water overtopped the dam into the emergency spillway in amounts that the spillway was not designed to handle. In Figure 1, the water is no longer overtopping the dam, but a huge section of the dam face has been badly damaged. Several channels have been carved down the face of the dam. Figure 2 shows water surging down the damaged main spillway. The spillway is the concrete structure at left. You can see that the water isn’t flowing in it, but rather down a rogue channel that the water has cut in the face of the dam. This actually occurred 2 days after the photo in Figure 1, as the California Department of Water Resources dumped water out of the lake in anticipation of large inflows from a new storm.
It sure seems like the surface water drought in California has been broken. The most important snow survey of the year (and often the final one) occurs on or about April 1. So I’m going to wait for that date before I do an analysis of how the wet winter has changed their water situation. Hopefully, at that point there will be enough data to allow an analysis that goes beyond the headlines and looks at long-term implications.
Kolke, Dale. 2017. DK_Oro_Spillway_damage-4109_02_15_2017.jpg. California Department of Water Resources > Galleries > Dams > Oroville Dam > Oroville Spillway Damage. Downloaded 2/21/17 from http://pixel-ca-dwr.photoshelter.com/galleries/C0000OxvlgXg3yfg/G00003YCcmDTx48Y/Oroville-Spillway-Damage.
Grow, Kelly. 2017. KG_oroville_damage-1 2868_02_20_2017.jpg. California Department of Water Resources > Galleries > Dams > Oroville Dam > Oroville Spillway Damage. Downloaded 2/21/17 from http://pixel-ca-dwr.photoshelter.com/galleries/C0000OxvlgXg3yfg/G00003YCcmDTx48Y/Oroville-Spillway-Damage.
2016 was even hotter than 2015!
Data released by NASA reveals that the average global temperature in 2016 was even hotter than in 2015, and by a substantial margin. The data is shown in Figure 1. 2014 was a record, then 2015 was a new record, and now 2016 is a new record: this marks the first time in the data maintained by NASA that the world has set three consecutive records. The data indicates that the temperature was at record highs during every month of the year.
In 2016, global surface temperature was 0.12°C warmer than in 2015. In 2016, the temperature was .99°C warmer than during the reference period, from 1951-1980, and about 2.0°C warmer than the late 19th Century.
Figure 2 shows a map of global temperature anomalies. In terms of heavily populated areas, portions of the United States, Canada, Russia, and Brazil were especially warm. But in truth, the real pattern here is that the farther north you go, the more severe the warming.
The NASA report is based on satellite measurements of temperature over both land and sea. In general, satellite measurement is quite accurate. The report does not address the many other climate variables that are addressed in the State of the Climate report published by the American Meteorological Association. That report, however, takes many months to prepare. In the previous post, I reported on the most recent State of the Climate report, which concerns 2015, not 2016.
NASA Goddard Institute for Space Studies. GISS Surface Temperature Analysis: Global Maps from GHCN v3 Data. Downloaded 1/18/2017 from https://data.giss.nasa.gov/gistemp/maps.
NASA Goddard Institute for Space Studies. GISS Surface Temperature Analysis: Analysis Graphs and Plots. Downloaded 1/19/2017 from https://data.giss.nasa.gov/gistemp/graphs.
2015 was the hottest year worldwide since record-keeping began. The previous hottest year was 2014.
2015 was the hottest year worldwide since record-keeping began in 1900, according to the State of the Climate in 2015 report by the American Meteorological Society. This is a report that came out in August, 2016, and I’m just catching up to it now. I will summarize a few of the many findings.
Figure 1 shows how much 2015 temperatures around the globe varied from the average temperature for that location (reference years 1981-2010). The yellow and red areas were warmer than average, the blue areas cooler. White represents areas for which there is not enough data to make a characterization. You can see that the map has many more yellow and red areas than blue. The previous record was set the year before, and 2015 was 0.13 – 0.18°C warmer. That is a large jump.
Figure 2 shows the trend in global temperatures from 1880 to 2015. The top two graphs represent different analyses of temperature over both land and ocean, the middle two graphs represent different analyses of temperature over land only, and the bottom two represent different analyses of temperature over ocean only. An inspection of the charts shows considerable year-to-year variation, but all of them show a continuing trend towards warmer temperature. Climate change deniers have been making much of a multi-year pause in the increase in surface temperature at the beginning of the 21st Century. Climate scientist have pointed out that this pause was illusory, as it represented a period during which heat was being shunted from the surface to the depths of the ocean faster than usual, not an actual pause in warming. It now seems that surface temperature has resumed its upward march: 2014 and 2015 show up on the charts as a quite large spike upward.
One of the ways global warming has its effect is by increasing the number of warm days, defined as “number of days above the seasonal 90th percentile of daily maximum temperatures over the 1961-1990 base period.” (Blunden and Arndt, 2016, p. S19) Figure 3 shows the map. You can see that there are large blobs of red over Australia, Southeast Asia, China, Siberia, Europe, South Africa, eastern Greenland, and most of North America. That means that all these regions had an above average number of warm days, in most cases by a lot (+30 days or more).
Extreme days are important. In the summer a “warm” day might indicate that it was extremely hot, which is hazardous. During the winter, on the other hand, it might indicate that the day was above freezing.
The map of warm days for 2015 looks quite similar to the map for 2014 (here): many of the same areas were involved.
There is a great deal more information in the report that is beyond the scope of this blog. For those interested in meteorology and climatology, it would make interesting reading.
I’m writing this post in early January, 2017. United States climate data for 2016 should post-up on Climate at a Glance during January, so hopefully by the time this post goes live, I’ll be able to follow up with information about the USA and Missouri.
Blunden, Jessica and Derek Arndt (eds.) 2016. “State of the Climate in 2015.” Bulletin of the American Meteorological Society, 97 (8) Special Supplement. Downloaded 1/8/17 from https://www.ametsoc.org/ams/index.cfm/publications/bulletin-of-the-american-meteorological-society-bams/state-of-the-climate.