Sentences with phrase «like sea surface temperature»

More subtle effects are seen from variables like sea surface temperature and net primary production.

I wonder what would happen if the same approach was applied to other climate metrics, like sea surface temperature, water vapor feedback strength, and precipitation - evaporation changes.

If the heat input is not entirely from insolation then the problem is like the sea surface temperatures, a lot deeper.

Not exact matches

While natural climate variations like El Niño do affect the frequency and severity of heat waves from one year to the next, the study suggests the increases are mainly linked to long - term changes in sea surface temperatures.

Beyond human activity, tropical sea surface temperatures further back in time are affected by volcanic eruptions, changes in the intensity of sunlight and natural events like El Niño.

So this effect could either be the result of natural variability in Earth's climate, or yet another effect of carbon dioxide and other greenhouse gases like water vapor trapping more heat and thus warming sea - surface temperatures.

... [It will be] like a sea - surface temperature map, except it's whale occurrence.

The Atlantic Multidecadal Oscillation is related to sea surface temperatures in the North Atlantic Ocean and, like El Niño, it affects weather far away.

Other scientists at Goddard are investigating ways to forecast the ebbs and flows of nutrients using the center's supercomputers, incorporating data like winds, sea surface temperatures, air pressures and more.

«It would be like trying to predict El Niño with a sophisticated atmospheric model, but with the Sea Surface Temperatures taken from external, independent projections by, for example, the United Nations,» said Kalnay.

There are strong competing effects such as changes in the large - scale atmospheric circulation, sea surface temperature changes like El Niño and La Niña and the dynamics of westerly storm tracks that all interact at the mid-latitudes,» said Stanford co-author Matthew Winnick who contributed to the study with fellow doctoral student Daniel Ibarra.

Sea surface temperature data since 1882 document large El Niño - like patterns following four out of five big eruptions: Santa María (Guatemala) in October 1902, Mount Agung (Indonesia) in March 1963, El Chichón (Mexico) in April 1982 and Pinatubo in June 1991.

The study stops short of attributing California's latest drought to changes in Arctic sea ice, partly because there are other phenomena that play a role, like warm sea surface temperatures and changes to the Pacific Decadal Oscillation, an atmospheric climate pattern that typically shifts every 20 to 30 years.

A well - known issue with LGM proxies is that the most abundant type of proxy data, using the species composition of tiny marine organisms called foraminifera, probably underestimates sea surface cooling over vast stretches of the tropical oceans; other methods like alkenone and Mg / Ca ratios give colder temperatures (but aren't all coherent either).

Because it is far from the Sun, Titan is extremely cold (surface temperature of about minus 178 Celsius (minus 289 Fahrenheit), allowing a hydrocarbon rain that may form gasoline - like seas.

A subset of Earth System Models (ESMs) project that El Niño - like conditions will progressively increase in coming decades as sea - surface temperatures in the tropical Pacific warm, implying increased drought and forest dieback in the Amazon.

Like almost all historical climate data, ship - board sea surface temperatures (SST) were not collected with long term climate trends in mind.

One thing I would have liked to see in the paper is a quantitative side - by - side comparison of sea - surface temperatures and upper ocean heat content; all the paper says is that only «a small amount of cooling is observed at the surface, although much less than the cooling at depth» though they do report that it is consistent with 2 - yr cooling SST trend — but again, no actual data analysis of the SST trend is reported.

Re 9 wili — I know of a paper suggesting, as I recall, that enhanced «backradiation» (downward radiation reaching the surface emitted by the air / clouds) contributed more to Arctic amplification specifically in the cold part of the year (just to be clear, backradiation should generally increase with any warming (aside from greenhouse feedbacks) and more so with a warming due to an increase in the greenhouse effect (including feedbacks like water vapor and, if positive, clouds, though regional changes in water vapor and clouds can go against the global trend); otherwise it was always my understanding that the albedo feedback was key (while sea ice decreases so far have been more a summer phenomenon (when it would be warmer to begin with), the heat capacity of the sea prevents much temperature response, but there is a greater build up of heat from the albedo feedback, and this is released in the cold part of the year when ice forms later or would have formed or would have been thicker; the seasonal effect of reduced winter snow cover decreasing at those latitudes which still recieve sunlight in the winter would not be so delayed).

Seems to me the debate about AGHG global warming and increasing TC frequency / intensity / duration boils down to the fact that as sea surface temperatures, as well as deeper water temperatures rise, the wallop of any TC over warmer seas without mitigating circumstances like wind sheer and dry air off land masses entrained in the cyclone will likely be much more devastating.

F. Engelbeen's claim that he only looked at land temperature trends, while Johannessen e.a. mainly looked at sea surface temperatures and ice cover is a Tech Central Station like.

For example, temperature changes on sea surfaces can signal widespread weather shifts like El Niño.

In the case of ORAS4, this includes ocean temperature measurements from bathythermographs and the Argo buoys, and other types of data like sea surface height and surface temperatures.

As a result, directly comparing the Sea Surface Temperature data from the early 20th century to the current Sea Surface Temperature data is like «comparing apples and oranges» — there have been too many changes in the data sources for such comparisons to have much meaning.

------------------------------------ And here's what the proxies vs. the highly adjusted instrumental data that have been hopelessly corrupted by removing thousands of rural stations and keeping urban stations, moving rural sites to airports, «mostly made up» SH sea surface temperatures, cooling down the 1930s and 1940s artificially to remove 0.5 C from the early 20th century warming... look like.

The bottom right map shows results from models in which things like greenhouse gases, sea surface temperatures, and sea ice were allowed to change as they have in the real world due to human activities.

Some day I'll figure out why the climate science community insists on using abstract forms of sea surface temperature data as indices, like the PDO, when detrending the sea surface temperatures of the KOE (which dominate the North Pacific) would provide the same basic information (only inverted) and would be less confusing for most persons.

However, during La Niña Modoki the anomaly of the sea surface temperature (SST) in the eastern Pacific isn't affected by cooling but by warming just like western equatorial Pacific, while a cold anomaly affects the central equatorial Pacific (Niño 3.4).

Sea surface heights are influenced by ocean temperatures and winds, and so in turn reflect the overarching conditions of ocean regions, including patterns like El Niño and La Niña.

I would classify a topic like «Uncertainty in historical sea surface temperatures» as cutting edge requiring access to recently published primary scientific literature.

Let me try to rephrase the ENSO - PDO relationship so that you can understand it: ENSO creates the PDO spatial pattern in sea surface temperature anomalies, which is why the PDO is called an ENSO - like pattern.

It is not simply detrended sea surface temperature anomaly data like the AMO.The PDO data is the standardized leading principal component of the sea surface temperatures of the North Pacific, north of 20N, after global sea surface temperatures are subtracted from the sea surface temperatures of each 5 × 5 deg grid.

In a study last year, the U.S. Climate Change Science Program indicated that an increase in sea - surface temperatures would lead to a proliferation of ocean bacteria species like Vibrio vulnificus and Vibrio parahaemolyticus that cause seafood - borne diseases.

When its windy, ice calms the waves like a peninsula, above the ice pack there is colder air, the pack cools sea surface temperatures and a huge pack creates a drier sky environment.

The best way to envision the relation between ENSO and precipitation over East Africa is to regard the Indian Ocean as a mirror of the Pacific Ocean sea surface temperature anomalies [much like the Western Hemisphere Warm Pool creates such a SST mirror with the Atlantic Ocean too]: during a La Niña episode, waters in the eastern Pacific are relatively cool as strong trade winds blow the tropically Sun - warmed waters far towards the west.

Something like albedo might explain the 1,500 - year cycle without a two - state mechanism; the D - O flips might arise from an abrupt atmospheric reorganization triggered by accumulating regional differences in sea surface temperatures.

The new atlas could also improve understanding of climate phenomena like the Atlantic Multi-decadal Oscillation, a variation in North Atlantic sea - surface temperatures that hasn't been tracked long enough to tell if it is a transitory event, forced by human intervention in the climate system, or a natural long - term oscillation.

Over these shorter periods, there are many modes of climate variability, usually involving semi-structured oscillations in sea surface temperatures, like the El Niño - Southern Oscillation, the Pacific Decadal Oscillation, the Arctic Oscillation, and so on.

The ups and downs, pauses and accelerations come from surface air temperatures being a consequence of sea surface temperatures, which are variable over decades due to ocean currents, overturning - ie things like ENSO, PDO.

It looks like some sort of hybrid between AR4 projections for tropical sea temperature increase and global average surface temperature rise.

It looks like the sub-sea permafrost is failing due to warmer ocean temperatures and allowing methane to escape; because the Siberian Sea is very shallow the methane isn't oxidized as it travels to the surface.

To me it looks like this shift will be the «team's» new tactic to keep the notion of global warming alive, especially if the pause in warming (or even slight cooling) of the «globally and annually averaged land and sea surface temperature» lasts another few decades.

But when that ocean is hot — and at the moment sea surface temperatures off the Northeast are five degrees higher than normal — a storm like Sandy can lurch north longer and stronger, drawing huge quantities of moisture into its clouds, and then dumping them ashore.

In his presentation, Gerry Bell, Like Lautenbacher, associated conditions since 1995 to «multi-decadal signal along with warmer than normal sea surface temperatures.»

However, ocean temperatures have warmed almost everywhere on the planet, with 0.5 ºC being the global mean rise of sea surface temperature, hence Trenberth's reasonable estimate that this much is the contribution from global forcings like CO2.

One NASA oceanographer told Scientific American that the world's seas, not surface temperatures, should be the current barometer of climate change because their temperatures are going up «like gangbusters.»

Specifically, key parameters of the Human System, such as fertility, health, migration, economic inequality, unemployment, GDP per capita, resource use per capita, and emissions per capita, must depend on the dynamic variables of the Human — Earth coupled system.26 Not including these feedbacks would be like trying to make El Niño predictions using dynamic atmospheric models but with sea surface temperatures as an external input based on future projections independently produced (e.g., by the UN) without feedbacks.

Figure 6 shows the global land surface air temperature plus sea surface temperature anomalies (average of GISS LOTI, HADCRUT4 and NCDC datasets, like The Escalator) before, during and after the 1997/98 El Niño.