We’re sorry, but we will not be posting updates to this blog during the government shutdown. Also, all public NASA activities and events are cancelled or postponed until further notice. Rest assured that we will be back as soon as possible! We hope that you will stick with us and we promise more great imagery when we return. Please note that we will not be moderating or posting comments until the shutdown is over.
See you on the other side,
Kevin, Mike, Adam, Holli, Jesse, Rob, and Paul
The Earth Observatory Team
+Warming of the climate system is unequivocal, and since the 1950s, many of the observed changes are unprecedented over decades to millennia. The atmosphere and ocean have warmed, the amounts of snow and ice have diminished, sea level has risen, and the concentrations of greenhouse gases have increased. Read more about global warming.
+Each of the last three decades has been successively warmer at the Earth’s surface than any preceding decade since 1850. In the Northern Hemisphere, 1983–2012 was likely the warmest 30-year period of the last 1400 years. See maps showing global temperature trends.
+Ocean warming dominates the increase in energy stored in the climate system, accounting for more than 90% of the energy accumulated between 1971 and 2010 (high confidence). It is virtually certain that the upper ocean (0−700 m) warmed from 1971 to 2010, and it likely warmed between the 1870s and 1971. Read more about Earth’s energy budget.
+Over the last two decades, the Greenland and Antarctic ice sheets have been losing mass, glaciers have continued to shrink almost worldwide, and Arctic sea ice and Northern Hemisphere spring snow cover have continued to decrease in extent (high confidence). Read more about Arctic and Antarctic sea ice.
+The rate of sea level rise since the mid-19th century has been larger than the mean rate during the previous two millennia (high confidence). Over the period 1901–2010, global mean sea level rose by 0.19 [0.17 to 0.21] m. Read more about sea level rise.
+The atmospheric concentrations of carbon dioxide (CO2), methane, and nitrous oxide have increased to levels unprecedented in at least the last 800,000 years. CO2 concentrations have increased by 40% since pre-industrial times, primarily from fossil fuel emissions and secondarily from net land use change emissions. The ocean has absorbed about 30% of the emitted anthropogenic carbon dioxide, causing ocean acidification. Read more about the greenhouse effect.
+Total radiative forcing is positive, and has led to an uptake of energy by the climate system. The largest contribution to total radiative forcing is caused by the increase in the atmospheric concentration of CO2 since 1750. Read more about radiative forcing.
+Climate models have improved since the AR4. Models reproduce observed continental-scale surface temperature patterns and trends over many decades, including the more rapid warming since the mid-20th century and the cooling immediately following large volcanic eruptions (very high confidence). Read more about climate models.
+Observational and model studies of temperature change, climate feedbacks and changes in the Earth’s energy budget together provide confidence in the magnitude of global warming in response to past and future forcing. Read more about Earth’s energy budget.
+Human influence has been detected in warming of the atmosphere and the ocean, in changes in the global water cycle, in reductions in snow and ice, in global mean sea level rise, and in changes in some climate extremes. This evidence for human influence has grown since AR4. It is extremely likely that human influence has been the dominant cause of the observed warming since the mid-20th century. Read more about the human influence on climate.
+Continued emissions of greenhouse gases will cause further warming and changes in all components of the climate system. Limiting climate change will require substantial and sustained reductions of greenhouse gas emissions. Read more about greenhouse gases.
+Global surface temperature change for the end of the 21st century is likely to exceed 1.5°C relative to 1850 to 1900 for all RCP scenarios except RCP2.6. It is likely to exceed 2°C for RCP6.0 and RCP8.5, and more likely than not to exceed 2°C for RCP4.5. Read more about global surface temperatures.
+Changes in the global water cycle in response to the warming over the 21st century will not be uniform. The contrast in precipitation between wet and dry regions and between wet and dry seasons will increase, although there may be regional exceptions. Read more about the water cycle.
+It is very likely that the Arctic sea ice cover will continue to shrink and thin and that Northern Hemisphere spring snow cover will decrease during the 21st century as global mean surface temperature rises. Global glacier volume will further decrease. Read more about sea ice.
+Global mean sea level will continue to rise during the 21st century. Under all RCP scenarios the rate of sea level rise will very likely exceed that observed during 1971–2010 due to increased ocean warming and increased loss of mass from glaciers and ice sheets. Read more about sea surface temperature.
+Climate change will affect carbon cycle processes in a way that will exacerbate the increase of CO2 in the atmosphere (high confidence). Further uptake of carbon by the ocean will increase ocean acidification. Read more about the ocean’s carbon balance.
+Cumulative emissions of CO2 largely determine global mean surface warming by the late 21st century and beyond. Most aspects of climate change will persist for many centuries even if emissions of CO2 are stopped. This represents a substantial multi-century climate change commitment created by past, present and future emissions of CO2. Read more about carbon dioxide.
Tropical cyclone “heat engines” extract heat from the ocean’s surface through evaporation and convert a portion of that energy into destructive winds that circle under the eyewall of the storm. All tropical cyclones have heat engines, but several features detected by TRMM suggested that Usagi’s was running particularly efficiently. Radars almost always see eyewalls in strong tropical cyclones, for instance, but they are rarely as symmetrical as Usagi’s is in the visualization shown above. NASA Goddard Space Flight Center researcher Owen Kelley produced the visualization based on TRMM data from the Precipitation Measurement Missions science team at NASA and from the Japan Aerospace Exploration Agency (JAXA).
In the 3D portion of the image, heavy precipitation is shown in dark red. Light precipitation is gray, green, yellow or light red, with the color reflecting how high the storm has lofted the rain production (higher than 8.5 kilometers is green; above 11.5 kilometers is yellow; and higher than 14 kilometers is red). Note that the underlying image, which shows the temperature of cloud tops, uses a different color scale. In it, cool cloud tops are pink and white, medium temperature cloud tops are gray and blue, and warm cloud tops are dark gray and black.
Even the heavy precipitation at the base of the eyewall is fairly symmetric, which is somewhat unusual according to Kelley. Tropical cyclone eyewalls that are this symmetric are called “annular,” and they have a tendency to maintain their intensity for longer periods than tropical cyclones with more lopsided eyewalls. At two locations in the inner eyewall, updrafts were strong enough to produce hot towers—features that are associated with strengthening cyclones. A few hours after TRMM collected the data visualized here, Usagi intensified briefly into a category 5 storm, the highest category on the scale.
Yesterday’s Image of the Day — Ocean Revealed — elicited an interesting response from Norman Kuring, a NASA oceanographer who frequently contributes to the Earth Observatory. He notes:
“There have indeed been a number of studies that exploit sunglint for ocean research since Paul Scully-Power made his statement. However, I disagree with the follow-on sentence that, “his observation holds true for satellite observations today.” While sunglint does reveal some information about the ocean beneath, for visible radiometry sensors it usually obscures more than it reveals.”
“We in the ocean-color community often bemoan the fact that the MODIS instruments and VIIRS do not tilt to avoid the worst of the glint field. SeaWiFS, which was primarily an ocean mission, tilted, and the upcoming ocean radiometer on PACE is also planned to be tiltable to avoid the worst of the glint.”
Good point, Norman. Sunglint hides the telltale shades of blue and green that point to phytoplankton growth in the ocean’s surface waters. Here’s a good example, originally published on the Earth Observatory in 2007.
Notice how the bright sunglint obscures the color on the top and right side of the image. (NASA’s Ocean Color web site provides another good example with a more detailed description.) It’s no wonder that oceanographers like Norman cringe at the thought of sunglint in ocean images.
Wildfires follow a simple but dangerous equation: Hotter, dryer conditions + more people in the world = a greater likelihood of ferocious wildfires threatening lives and property.
Fires in the western United States are burning earlier, longer and with more intensity, as shown by a decades-long record from ground surveys and NASA satellites. How much of this is due to climate change? And how do scientists see this trend developing in the coming decades, as temperatures rise, seasons shift, and precipitation patterns change?
Join researchers online at 1 p.m. EDT (10 a.m. PDT) on Friday, Aug. 9, for a NASA Google+ Hangout that will explore these questions. The Hangout will feature:
Doug Morton, research scientist at NASA’s Goddard Space Flight Center
Bill Patzert, research scientist at NASA’s Jet Propulsion Laboratory
Elizabeth Reinhardt, national program leader for fire research, research and development, Office of the Climate Change Advisor, U.S. Forest Service
The panelists will take questions from the press and the public during the Hangout. Submit questions on Google+, YouTube, Twitter, Facebook or other social media channels in advance and during the event using the hashtag #NASAFire. The URL for the hangout is https://plus.google.com/events/c6qkg3u1bbgvc81smsrqb84okcc
You can also find some background and imagery on wildfires here on the Earth Observatory.
When astronomer and Slate blogger Phil Plait fired up the image processing software on his computer down on Earth, he enhanced the brightness on Nyberg’s photo so that Jupiter and Mercury show up quite nicely. (See the enhanced image below.) Read more about the remarkable photograph on the Bad Astronomy blog.
Periodically, Earth Observatory answers reader questions on this blog. Here’s a recent note from Manny J of New York City:
“I recall that starting on May 15, 2013, the cold did not leave [New York]. In fact, it still felt like winter because it refused to warm up. Then came June 2013, with the sky overcast each and every day, with the humidity very high, hardly any sun except for an occasional peeping through. In fact as of June 30, 2013, there was no summer as summer used to be. The weather pattern was such that I had never seen anything like it. Do you know why?”
We asked Gavin Schmidt, deputy chief of NASA’s Goddard Institute for Space Studies (GISS) and a NYC resident, what he thought:
“The seasonal weather pattern in any particular location is very sensitive to the chaotic dynamics in the atmosphere. Our ability to attribute those changes to either ocean temperature patterns or external drivers is quite limited, and so we can’t provide an answer that can satisfactorily address this question. Things that we can say are caused (statistically) are generally on larger spatial scales and longer time scales.”
In recent years, many readers have asked Earth Observatory if a particular spell of crazy weather is a result of global warming. As Gavin pointed out and many others have explained, weather events and climate are different things. Climate is what you expect to happen, and weather is what actually happens on a day-to-day, week-to-week time scale. There is inherent chaos and unpredictable variability in weather. Climate, on the other hand, is a matter of trends and long views. What might the season or year look like when compared to the averages of many years? Is it getting warmer or cooler, wetter or drier? Can that be explained by some physical process?
Above: temperature anomalies for June 2013, as calculated by NASA GISS
As we explained in a feature story earlier this spring, the behavior of storms is growing more erratic. Other research has shown that heat waves have become more frequent and more likely to break records. This video below shows how the number of deviations from normal — the number of extreme heating or cooling events — has shifted toward more extreme highs and fewer lows.
While Manny and other New Yorkers had an unorthodox June, much of the rest of the United States and the world baked. According the NOAA National Climatic Data Center and meteorologist-blogger Jeff Masters of Weather Underground, June 2013 was the fifth warmest June on record. July 2013 also was shaping up to be quite hot just about everywhere.
On June 19, 2013, the U.S. Geological Survey officially decommissioned Landsat 5 after an astonishing 29 years of operation. The satellite’s longevity was recognized by the Guinness Book of World Records, which dubbed Landsat 5 as the longest-operating Earth observation satellite.
I recently listened to Dr. Steve Covington — the flight systems manager for Landsat 5 since 2001 — recount some of the lucky circumstances and creative engineering that kept the satellite operating for nearly three decades. (The talk will be posted on the Library of Congress web site in the near future.) Here are some of the highlights.
Lucky circumstance 1: Landsat 5 had a twin, Landsat 4, which showed problems with its power system once it was in orbit. Those problems let engineers adjust Landsat 5 before it launched on March 1, 1984.
Lucky circumstance 2: Landsat 5 was equipped with a large auxiliary fuel tank designed to let the satellite fly down from its orbit to a lower orbit where astronauts could retrieve and repair it. The polar-orbiting space shuttle program that would enable these on-orbit repairs never got off the ground, and this left Landsat 5 with a whole lot of extra fuel. Mission operators used the fuel to extend the mission across decades.
Creative Engineering 1: In January 2005, Landsat 5’s primary solar array drive failed, and months later, in November, the backup drive failed. This key component turned the solar array to face the Sun straight on whenever the satellite was on the sunlit side of the Earth. Without the drive, the solar array was stuck in a single position, limiting the amount of energy it generated to power the instruments and spacecraft.
The failure of the drives looked to be a mission-ending event, since the Landsat 5’s batteries couldn’t be recharged sufficiently to continue science operations. But mission operation engineers came up with a novel solution: If the solar array couldn’t move, they would move the entire spacecraft. Before the satellite came across Earth’s shadow into the sunlight, they pitched the satellite to face the Sun. The satellite faced down again to acquire data, and then, approaching the shadow again, pitched out to face the Sun. This dance gave the satellite just enough extra Sun exposure to keep the batteries charged and execute its imaging duties.
Creative Engineering 2: Landsat 5 had four pathways for sending data to the ground: two communication links with relay satellites, and two direct downlinks to ground stations. The last of these failed in 2012, preventing the satellite from sending data from its primary instrument (the Thematic Mapper) to the ground. The secondary instrument, the Multispectral Scanner (MSS) had been turned off in 1995. Mission operations engineers realized that the communication links used by MSS were still good, and the mission could continue if the MSS still worked. Seventeen years after turning the instrument off, engineers powered it back on, and amazingly, it worked. This allowed Landsat 5 to acquire one more year of data until Landsat 8 was ready to take its place in early 2013.
One of the wonderful things about working for the Earth Observatory is that we often get first crack at examining imagery from satellites new and old. It’s been especially exciting to look at data from Landsat 8, a joint U.S. Geological Survey and NASA mission launched in February 2013.
But with new things comes new challenges. We’ve had some odd problems with the very intense memory demands of Landsat 8 imagery, for example. And when I saw the image below, I thought for sure I had stumbled on a processing error.
Oh dear. Look at that ripple pattern along the river banks. Superficially, it looks a lot like a software processing error. New code I wrote: my error, right? In fact, at first glance, it looked a lot like Landsat data of a decade or so ago when the source files were being distributed with nearest-neighbor resampling–a technique used in remapping and resizing data which limits interactions between adjacent measures, something often useful in science measurements, but which causes jagged-looking edges. Since this was not the first time my code had done something unexpected, it was the obvious first place to look for the cause. The software failed me! Again!
However, a quick glance through the data files showed that, whatever was going on, it was coming from the source data: the same rippling showed up in all the bands. Ha! Someone else’s software had failed!
Because Landsat 8 is so new, it is easy to assume maybe I was not the only one having occasional processing problems with old software on new data. There was one more check I should have done before contacting customer service at USGS, but…
…I didn’t think of it. If you see something odd in imagery, it is always good to check reality. In this case, a quick zoomed-in view in Google Earth (as shown here) would have informed me that the jagged edges along the banks of the river in the imagery are real jagged edges along the banks of the river.
In hindsight, there were other clues. Notice that the jagged features are present in some places and not others. And notice that the rippled pattern along the banks bends and curves with the flow of the river. A processing artifact might only show up on very strongly contrasting features (the boundary between land and water here, for example), but would most likely be aligned consistently through the image. It wouldn’t appear and disappear like it does here, and it would probably be more regular. It would probably distort in the same direction every time it happened.
In the end, it turns out that all the new systems were working just fine and there really is a very oddly shaped series of features along the banks of the Elbe River near Wittenberg, presumably to stablize the banks of the river and control sediment flow.
But there’s not much they can do in the face of severe flooding.
Today’s guest post is from Kate Ramsayer of the NASA Earth Science News Team. Kate wrote the caption for today’s Image of the Day about El Paso and the mountains of data collected by Landsat over four decades.
When the first Landsat satellite — originally called the Earth Resources Technology Satellite (ERTS) — launched in 1972, it was no small feat to visualize the data it sent back and to conduct research with it.
“When ERTS was first launched, there was one cathode ray tube in the country that could take in the digital data and display an image,” said Jeff Masek, Landsat project scientist at NASA Goddard.
In the early years, satellite observations of the light reflected off of Earth were transmitted to receiving stations and mailed to processing centers. Computers translated the image data into photographic prints or transparencies that could be placed on light tables for interpretation. Alternatively, computers translated the numbers in each pixel into alpha-numeric symbols that were printed on large reams of paper. Analysts, often graduate students, could then color-in the symbols with crayon or magic markers. Standing on ladders over the colored-in data, they’d try to visualize the landscape represented by the maps.
“Things were pretty primitive in those days,” Masek said. “People say, ‘Why didn’t they produce a global land cover map in those first few years?’ They were lucky to be able to look at one image for a Ph.D. dissertation.”