For example, Kosaka and Xie showed than when the El Niño - related changes in Pacific ocean temperature are entered into a model, it not only reproduced the global surface warming over the past 15 years but it also accurately reproduced regional and
seasonal changes in surface temperatures.
Not exact matches
This seems to be associated with particular patterns of
change in sea
surface temperature in the Atlantic and Pacific oceans, a teleconnection which is well - captured
in climate models on
seasonal timescales.
The lapse rate within the troposphere is largely determined by convection, which redistributes any
changes in radiative heating or cooling within the troposphere +
surface so that all levels tend to shift
temperature similarly (with some regional / latitudinal, diurnal, and
seasonal exceptions, and some exceptions for various transient weather events).
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).
Type 3 downscaling is applied, for example, for
seasonal forecasts where slowly
changing anomalies
in the
surface forcing (such as sea
surface temperature) provide real - world information to constrain the downscaling results.
The initial
changes in temperature during this period are explained by
changes in the Earth's orbit around the sun, which affects the amount of
seasonal sunlight reaching the Earth's
surface.
Due to the much higher heat capacity of soil relative to air and the thermal insulation provided by vegetation and
surface soil layers,
seasonal changes in soil
temperature deep
in the ground are much less than and lag significantly behind
seasonal changes in overlying air
temperature.
The amplitude of
seasonal changes in soil
temperature on either side of the mean earth
temperature depends on the type of soil and depth below the ground
surface.
The scatter diagrams described and presented on these pages depict projected
changes in seasonal surface air
temperature and precipitation for three 30 - year periods (2010 - 2039, 2040 - 2069 and 2070 - 2099) relative to the baseline period 1961 - 1990
in 32 sub-continental scale regions (see below).
Scatter plot of simulated springtime Δαs / ΔTs values
in climate
change (ordinate) vs simulated springtime Δαs / ΔTs values
in the
seasonal cycle (abscissa)
in transient climate
change experiments with 17 AOGCMs used
in this report (Δαs and Ts are
surface albedo and
surface air
temperature, respectively).
Given the intimate connection between river water and widespread alluvial aquifers it is clear that there must be stong
seasonal change in «shallow groundwater»
temperature many metres below the
surface.