Patrick T. Brown

Top‐of‐atmosphere radiative contribution to unforced decadal global temperature variability in climate models

Much recent work has focused on unforced global mean surface air temperature (T) variability associated with the efficiency of heat transport into the deep ocean. Here the relationship between unforced variability in T and the Earths top-of-atmosphere (TOA) energy balance is explored in preindustrial control runs of the Coupled Model Intercomparison Project Phase 5 multimodel ensemble. It is found that large decadal scale variations in T tend to be significantly enhanced by the net energy flux at the TOA. This indicates that unforced decadal variability in T is not only caused by a redistribution of heat within the climate system but can also be associated with unforced changes in the total amount of heat in the climate system. It is found that the net TOA radiation imbalances result mostly from changes in albedo associated with the Interdecadal Pacific Oscillation that temporarily counteracts the climate systems outgoing longwave (i.e., Stefan-Boltzmann) response to T change.

The necessity of cloud feedback for a basin‐scale Atlantic Multidecadal Oscillation

The Atlantic Multidecadal Oscillation (AMO), characterized by basin-scale multidecadal variability in North Atlantic sea surface temperatures (SSTs), has traditionally been interpreted as the surface signature of variability in oceanic heat convergence (OHC) associated with the Atlantic Meridional Overturning Circulation (AMOC). This view has been challenged by recent studies that show that AMOC variability is not simultaneously meridionally coherent over the North Atlantic and that AMOC-induced low-frequency variability of OHC is weak in the tropical North Atlantic. Here we present modeling evidence that the AMO-related SST variability over the extratropical North Atlantic results directly from anomalous OHC associated with the AMOC but that the emergence of the coherent multidecadal SST variability over the tropical North Atlantic requires cloud feedback. Our study identifies atmospheric processes as a necessary component for the existence of a basin-scale AMO, thus amending the canonical view that the AMOC-AMO connection is solely attributable to oceanic processes.

Regions of significant influence on unforced global mean surface air temperature variability in climate models

We document the geographic regions where local variability is most associated with unforced global mean surface air temperature (GMT) variability in Coupled Model Intercomparison Project Phase 5 coupled global climate models (GCMs) at both the subdecadal and interdecadal timescales. For this purpose, Regions of Significant Influence on GMT are defined as locations that have a statistically significant correlation between local surface air temperature (SAT) and GMT (with a regression slope greater than 1), and where local SAT variation leads GMT variation in time. In both GCMs and observations, subdecadal timescale GMT variability is most associated with SAT variation over the eastern equatorial Pacific. At the interdecadal timescale, GMT variability is also linked with SAT variation over the Pacific in many GCMs, but the particular spatial patterns are GCM dependent, and several GCMs indicate a primary association between GMT and SAT over the Southern Ocean. We find that it is difficult to validate GCM behavior at the interdecadal timescale because the pattern derived from observations is highly depended on the method used to remove the forced variability from the record. The magnitude of observed GMT variability is near the ensemble median at the subdecadal timescale but well above the median at the interdecadal timescale. GCMs with a stronger subdecadal relationship between GMT and SAT over the Pacific tend to have more variable subdecadal GMT while GCMs with a stronger interdecadal relationship between GMT and SAT over parts of the Southern Ocean tend to have more variable GMT.

Unforced surface air temperature variability and its contrasting relationship with the anomalous TOA energy flux at local and global spatial scales

AbstractUnforced global mean surface air temperature () is stable in the long term primarily because warm anomalies are associated with enhanced outgoing longwave radiation () to space and thus a negative net radiative energy flux (, positive downward) at the top of the atmosphere (TOA). However, it is shown here that, with the exception of high latitudinal and specific continental regions, warm unforced surface air temperature anomalies at the local spatial scale [T(θ, ϕ), where (θ, ϕ) = (latitude, longitude)] tend to be associated with anomalously positive N(θ, ϕ). It is revealed that this occurs mainly because warm T(θ, ϕ) anomalies are accompanied by anomalously low surface albedo near sea ice margins and over high altitudes, low cloud albedo over much of the middle and low latitudes, and a large water vapor greenhouse effect over the deep Indo-Pacific.It is shown here that the negative versus relationship arises because warm anomalies are associated with large divergence of atmospheric energy transpo...

Comparing the model-simulated global warming signal to observations using empirical estimates of unforced noise.

The comparison of observed global mean surface air temperature (GMT) change to the mean change simulated by climate models has received much public and scientific attention. For a given global warming signal produced by a climate model ensemble, there exists an envelope of GMT values representing the range of possible unforced states of the climate system (the Envelope of Unforced Noise; EUN). Typically, the EUN is derived from climate models themselves, but climate models might not accurately simulate the correct characteristics of unforced GMT variability. Here, we simulate a new, empirical, EUN that is based on instrumental and reconstructed surface temperature records. We compare the forced GMT signal produced by climate models to observations while noting the range of GMT values provided by the empirical EUN. We find that the empirical EUN is wide enough so that the interdecadal variability in the rate of global warming over the 20th century does not necessarily require corresponding variability in the rate-of-increase of the forced signal. The empirical EUN also indicates that the reduced GMT warming over the past decade or so is still consistent with a middle emission scenarios forced signal, but is likely inconsistent with the steepest emission scenarios forced signal.

Time and tide: analysis of sea level time series

A number of recent papers have examined sea level data, both local tide gauge records and regional/global averages, to estimate not only how fast sea level is rising but how the rate has changed over time, i.e. its pattern of acceleration and deceleration. In addition, a number of claims of cyclic/quasi-periodic variations have been proposed. However, many of these papers contain technical problems which call their results into question. In particular, the issue of autocorrelation is often ignored, and even when it is addressed its impact has sometimes been misinterpreted. Autocorrelation does more than just affect the standard errors of regression analysis, it can also make the spectrum of a noise process distinctly “red” and therefore be highly suggestive of low-frequency periodic or pseudo-periodic behavior when none is present. If any analysis is applied which acts as a band-pass filter, it can further exaggerate the illusion of oscillatory behavior. These issues are highlighted in a small number of recent papers, in order to improve the quality of future work on this subject.

Evaluating Modeled Intra- to Multidecadal Climate Variability Using Running Mann-Whitney Z Statistics

An analysis method previously used to detect observed intra- to multidecadal (IMD) climate regimes was adapted to compare observed and modeled IMD climate variations. Pending the availability of the more appropriate phase 5 Coupled Model Intercomparison Project (CMIP-5) simulations, the method is demonstrated using CMIP-3 model simulations. Although the CMIP-3 experimental design will almost certainly prevent these model runs from reproducing features of historical IMD climate variability, these simulations allow for the demonstration of the method and illustrate how the models and observations disagree. This method samples a time series’s data rankings over moving time windows, converts those ranking sets to a Mann‐Whitney U statistic, and then normalizes the U statistic into a Z statistic. By detecting optimally significant IMD ranking regimes of arbitrary onset and varying duration, this process generates time series of Z values that are an adaptively low-passed and normalized transformation of the original time series. Principal component (PC) analysis of the Z series derived from observed annual temperatures at 92 U.S. grid locations during 1919‐2008 shows two dominant modes: a PC1 mode with cool temperatures before the late 1960s and warm temperatures after the mid-1980s, and a PC2 mode indicating a multidecadal temperature cycle over the Southeast. Using a graphic analysis of a Z error metric that compares modeled and observed Z series,thethreeCMIP-3modelsimulationstestedhereareshowntoreproducethePC1modebutnotthePC2 mode. By providing a way to compare grid-level IMD climate response patterns in observed and modeled data, this method can play a useful diagnostic role in future model development and decadal climate forecasting.

Change in the magnitude and mechanisms of global temperature variability with warming

Natural unforced variability in global mean surface air temperature (GMST) can mask or exaggerate human-caused global warming, and thus a complete understanding of this variability is highly desirable. Significant progress has been made in elucidating the magnitude and physical origins of present-day unforced GMST variability, but it has remained unclear how such variability may change as the climate warms. Here we present modeling evidence that indicates that the magnitude of low-frequency GMST variability is likely to decline in a warmer climate and that its generating mechanisms may be fundamentally altered. In particular, a warmer climate results in lower albedo at high latitudes, which yields a weaker albedo feedback on unforced GMST variability. These results imply that unforced GMST variability is dependent on the background climatological conditions, and thus climate model control simulations run under perpetual preindustrial conditions may have only limited relevance for understanding the unforced GMST variability of the future.

Spread in the magnitude of climate model interdecadal global temperature variability traced to disagreements over high‐latitude oceans

Unforced variability in global mean surface air temperature can obscure or exaggerate global warming on interdecadal timescales, thus understanding both the magnitude and generating mechanisms of such variability is of critical importance for both attribution studies as well as decadal climate prediction. Coupled atmosphere-ocean general circulation models (climate models) simulate a wide range of magnitudes of unforced interdecadal variability in global mean surface air temperature (UITglobal), hampering efforts to quantify the influence of UITglobal on contemporary global temperature trends. Recently, a preliminary consensus has emerged that unforced interdecadal variability in local surface temperatures (UITlocal) over the tropical Pacific Ocean are particularly influential on UITglobal. Therefore, a reasonable hypothesis might be that the large spread in the magnitude of UITglobal across climate models can be explained by the spread in the magnitude of simulated tropical Pacific UITlocal. Here we show that this hypothesis is mostly false. Instead, the spread in the magnitude of UITglobal is linked much more strongly to the spread in the magnitude of UITlocal over high-latitude regions characterized by significant variability in oceanic convection, sea ice concentration, and energy flux at both the surface and the top of the atmosphere (TOA). Thus, efforts to constrain the climate model produced range of UITglobal magnitude would be best served by focusing on the simulation of air-sea interaction at high latitudes.