David W. J. Thompson’s research while affiliated with Colorado State University and other places

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Publications (125)


Relationships between forced and unforced climate feedbacks. Each background shading zone corresponds to the feedback component indicated on the x‐axis. Bars indicate (institute‐weighted) inter‐model linear regression coefficients. Pale and dark shading indicate inter‐model regressions across the CMIP5 and CMIP6 ensembles, respectively. Gray, blue, and pink shading indicate inter‐model regressions against internal variability feedbacks using the full forced response (years 1–150), early forced response (years 1–20), and late forced response (years 21–150), respectively. Thin whiskers (thick whiskers) indicate the 95% (50%) uncertainty bounds for the regression coefficients according to two‐sided student's t‐tests.
Local contributions to inter‐model cloud feedback regressions and surface temperature change. The first and second columns indicate results for the CMIP5 and CMIP6 ensembles, respectively. The third column shows zonal‐average differences between the first two columns. The upper panels indicate spatial decompositions of the cloud radiative effect feedback regression coefficients from Figure 1. Global averages of the upper first column (a, d) and the upper second column (b, e) are equivalent to bars from Figures 1B and 1C (respectively). The first and second rows show decompositions for the early (year 0–20) and late (year 21–150) forced responses to quadrupled CO2, respectively. The lower panels indicate (institute‐weighted) average surface temperature change. The third row shows local temperature departures associated with internal variability in global‐average temperature (g, h). The fourth and fifth rows show local temperature departures from the global‐average early (i, j) and late (k, l) forced responses, respectively. Stippling indicates regions excluded from the spatial projections (see text).
Emergent constraints on forced climate feedbacks using observed internal variability. The top row indicates constraints on the forced cloud radiative effect feedback. The bottom row indicates constraints on the total (net) forced climate feedback. The columns indicate results for the CMIP5 and CMIP6 ensembles, respectively. Gray markers indicate forced and internal climate feedbacks for individual models. Gray lines and shading indicate (institute‐weighted) inter‐model linear regressions and their 95% uncertainty bounds. The size of each marker is proportional to its weight in the regression (see text). Blue lines and shading indicate the mean and t‐distributed 95% uncertainty bounds for the observational estimate of the corresponding internal variability feedback (see text). Pink lines and shading indicate the mean and 95% uncertainty bounds for the constrained estimate of the late forced climate feedback, accounting for both observational and regression uncertainty (see text). Horizontal gray dotted and dashed lines indicate (respectively) the mean and t‐distributed 95% uncertainty bounds for the unconstrained forced feedbacks (i.e., y‐coordinates of the gray markers). Lower right annotations indicate the percentage of (institute‐weighted) variance in the forced feedbacks explained by each regression (i.e., the coefficient of determination r2 ${r}^{2}$). Upper left annotations indicate the amount that each emergent constraint reduces inter‐model spread in the response (i.e., the pink shading width minus the distance between the dashed gray lines). Positive values indicate unsuccessful constraints and are highlighted with red. The darker bands of blue and pink shading indicate the uncertainty associated with equivalent observational feedbacks derived from a hypothetical 50‐year observing period instead of the true 292‐month (≈24‐year) period.
Links Between Internal Variability and Forced Climate Feedbacks: The Importance of Patterns of Temperature Variability and Change
  • Article
  • Full-text available

December 2024

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51 Reads

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David W. J. Thompson

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Maria Rugenstein

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Understanding the relationships between internal variability and forced climate feedbacks is key for using observations to constrain future climate change. Here we probe and interpret the differences in these relationships between the climate change projections provided by the CMIP5 and CMIP6 experiment ensembles. We find that internal variability feedbacks better predict forced feedbacks in CMIP6 relative to CMIP5 by over 50%, and that the increased predictability derives primarily from the slow (>20 years) response to climate change. A key novel result is that the increased predictability is consistent with the higher resemblance between the patterns of internal and forced temperature changes in CMIP6, which suggests temperature pattern effects play a key role in predicting forced climate feedbacks. Despite the increased predictability, emergent constraints provided by observed internal variability are weak and largely unchanged from CMIP5 to CMIP6 due to the shortness of the observational record.

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Signature of the western boundary currents in local climate variability

October 2024

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269 Reads

Nature

The western boundary currents are characterized by narrow, intense ocean jets and are among the most energetic phenomena in the world ocean. The importance of the western boundary currents to the mean climate is well established: they transport vast quantities of heat from the subtropics to the midlatitudes¹, and they govern the structure of the climatological mean surface winds2–6, precipitation4–6 and extratropical storm tracks7–13. Their importance to climate variability is much less clear, as the tropospheric response to extratropical sea surface temperature (SST) variability is generally modest relative to the internal variability in the midlatitude atmosphere12–14. Here we exploit novel local analyses based on high-spatial-resolution data to demonstrate that SST variability in the western boundary currents has a more robust signature in climate variability than has been indicated in previous work. Our results indicate that warm SST anomalies in the major boundary currents of both hemispheres are associated with a distinct signature of locally enhanced precipitation and rising motion anomalies that extend throughout the depth of the troposphere. The tropospheric signature closely mirrors that of ocean dynamical processes in the boundary currents. Thus, the findings indicate a distinct and robust pathway through which extratropical ocean dynamical processes influence local climate variability. The observational relationships are also reproducible in Earth system model simulations but only when the simulations are run at high spatial resolution.



Daily temperature for recent extreme heat events. Panels (a, c, and e) show standardized temperature anomalies on 29 June 2021, 19 July 2022, and 18 July 2023. Panels (b, d, and f) show the daily averaged temperatures in 2021, 2022, and 2023 for the locations with the most extreme temperature on the days shown in panels (a, c, and e), respectively. Locations are indicated by green circles in the left column and centered at (50.5°N; 127.75°W), (53.75°N; 0.5°W), and (37.25°N; 1.25°E). The black lines in the right column show the long‐term mean; the dashed and dotted gray lines indicate the 2s and 4s bands around the mean; the light gray lines are the daily averaged temperatures for all other years in the period 1979–2023.
Influence of skewness and kurtosis on local and hemispheric incidence of heat events. (a) Contours: theoretical percent of days that temperature anomalies exceed +4s if they follow a Pearson distribution with skewness and kurtosis indicated on the axes. Shading: observed percent of days when local temperature anomalies exceeded +4s with respect to the 1991–2020 climatology. Results are calculated for all grid points in the Northern Hemisphere midlatitudes (30°N–70°N) and interpolated using Delaunay triangulation. Gray regions on the plot indicate values of skewness and kurtosis that are not found at any grid point. (b) Contours: theoretical percent of days that a temperature anomaly will exceed +4s in at least one of 100 independent time series if they follow a Pearson distribution with skewness and kurtosis indicated on the axes. Note that contours in panel (a) are for a single time series, and that contours in panel (b) are for 100 independent time series (there are roughly 100 spatial degrees of freedom in the Northern Hemisphere midlatitude temperature field). Shading: observed number of grid points in the Northern Hemisphere midlatitudes within a given skewness and kurtosis range using a bin size of 0.02 × 0.02. Black numbers indicate the total number of grid points that fall between the indicated probability contours.
Time evolution of the incidence of extreme heat events over the Northern Hemisphere midlatitudes. Results are summed over successive decades, with the x‐axes noting the starting year of each decade. Left column: (a) Percent of days in each decade that experienced an extreme heat event at least one location. (b) Average number of days between extreme heat events. (c) Percent of the Northern Hemisphere that experienced an extreme heat event on at least one day in each decade. Horizontal dashed lines denote the average over all decades in the base period 1991–2020. Gray shading show 95% confidence bounds computed by resampling with replacement. Middle column: Same as the left column, but for the incidence of heat waves based on detrended temperature anomalies. Right column: Black lines and gray shading are reproduced from the left column. Red lines indicate changes in extreme heat events found by allowing the mean temperature to change at each grid point but holding all other aspects of the temperature data fixed to a reference decade. Results for decades prior to 2013 are based on observed trends over 1979–2022; results for decades after 2013 show changes that will arise if the observed trends continue over the next four decades. The 95% confidence bounds are found by resampling the reference decade used in the analysis. See text for details.
Comparing Local Versus Hemispheric Perspectives of Extreme Heat Events

December 2023

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205 Reads

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1 Citation

Plain Language Summary Extreme events can be studied from local and large‐scale perspectives. The two perspectives provide different insights into the likelihood of extreme events. For example, several notable recent heat waves in the Northern Hemisphere exceeded four standard deviations about the long‐term climatology. Locally, such events are expected less than once every century. But based on high spatial resolution temperature data, such events occur somewhere in the Northern Hemisphere roughly once every 10 days. The increased likelihood of extreme heat events when summed over the hemisphere is not well represented by normal statistics because it is strongly dependent on the shapes of the temperature distributions. The large effective sample size afforded by the hemispheric perspective is important, as it provides a robust estimate of the influence of climate change on the frequency of occurrence of heat events. The hemispheric perspective confirms previous findings that long‐term trends in extreme heat events summed over the Northern Hemisphere can be explained by recent increases in mean temperature.


The Atmospheric General Circulation

May 2023

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313 Reads

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5 Citations

An engaging, comprehensive, richly illustrated textbook about the atmospheric general circulation, written by leading researchers in the field. The book elucidates the pervasive role of atmospheric dynamics in the Earth System, interprets the structure and evolution of atmospheric motions across a range of space and time scales in terms of fundamental theoretical principles, and includes relevant historical background and tutorials on research methodology. The book includes over 300 exercises and is accompanied by extensive online resources, including solutions manuals, an animations library, and an introduction to online visualization and analysis tools. This textbook is suitable as a textbook for advanced undergraduate and graduate level courses in atmospheric sciences and geosciences curricula and as a reference textbook for researchers.


Exceptional stratospheric contribution to human fingerprints on atmospheric temperature

May 2023

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201 Reads

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28 Citations

Proceedings of the National Academy of Sciences

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Stephen Po-Chedley

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Lilong Zhao

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[...]

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Karl E Taylor

In 1967, scientists used a simple climate model to predict that human-caused increases in atmospheric CO2 should warm Earth's troposphere and cool the stratosphere. This important signature of anthropogenic climate change has been documented in weather balloon and satellite temperature measurements extending from near-surface to the lower stratosphere. Stratospheric cooling has also been confirmed in the mid to upper stratosphere, a layer extending from roughly 25 to 50 km above the Earth's surface (S25 - 50). To date, however, S25 - 50 temperatures have not been used in pattern-based attribution studies of anthropogenic climate change. Here, we perform such a "fingerprint" study with satellite-derived patterns of temperature change that extend from the lower troposphere to the upper stratosphere. Including S25 - 50 information increases signal-to-noise ratios by a factor of five, markedly enhancing fingerprint detectability. Key features of this global-scale human fingerprint include stratospheric cooling and tropospheric warming at all latitudes, with stratospheric cooling amplifying with height. In contrast, the dominant modes of internal variability in S25 - 50 have smaller-scale temperature changes and lack uniform sign. These pronounced spatial differences between S25 - 50 signal and noise patterns are accompanied by large cooling of S25 - 50 (1 to 2[Formula: see text]C over 1986 to 2022) and low S25 - 50 noise levels. Our results explain why extending "vertical fingerprinting" to the mid to upper stratosphere yields incontrovertible evidence of human effects on the thermal structure of Earth's atmosphere.


The Key Role of Cloud-Climate Coupling in Extratropical Sea Surface Temperature Variability

January 2023

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28 Reads

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6 Citations

Journal of Climate

Cloud radiative effects have long been known to play a key role in governing the mean climate. In recent years, it has become clear that they also contribute to climate variability in the tropics. Here we build on recent work and probe the role of cloud radiative effects in extratropical sea surface temperature (SST) variability. The impact of cloud radiative effects on climate variability is explored in ‘cloud-locking’ simulations run on an Earth System Model. The method involves comparing the output from two climate simulations: one in which clouds are coupled to atmospheric dynamic and thermodynamic processes, and another in which clouds are prescribed and thus decoupled from them. The results reveal that cloud-climate coupling leads to widespread increases in the amplitudes of extratropical SST variability from monthly to decadal timescales. Notably, it leads to ~40-100% increases in the amplitude of monthly to decadal variability over both the North Atlantic and North Pacific oceans. These increases are consistent with the ‘reddening’ of cloud shortwave radiative effects that arises when clouds respond to the dynamic and thermodynamic state of the atmosphere. The results suggest that a notable fraction of observed Northern Hemisphere SST variability - including that associated with North Pacific and North Atlantic decadal variability - is due to cloud-climate coupling.



Phase Unlocking and the Modulation of Tropopause‐Level Trace Gas Advection by the Quasibiennial Oscillation

November 2022

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55 Reads

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3 Citations

Open questions about the modulation of near‐surface trace gas variability by stratosphere‐troposphere tracer transport complicate efforts to identify anthropogenic sources of gases such as CFC‐11 and N2O and disentangle them from dynamical influences. In this study, we explore one model's modulation of lower stratospheric tracer advection by the quasi‐biennial oscillation (QBO) of stratospheric equatorial zonal‐mean zonal winds at 50 hPa. We assess instances of coherent modulation versus disruption through phase unlocking with the seasonal cycle in the model and in observations. We quantify modeled advective contributions to the temporal rate of change of stratospheric CFC‐11 and N2O at extratropical and high‐latitudes by calculating a transformed Eulerian mean (TEM) budget across isentropic surfaces from a 10‐member WACCM4 ensemble simulation. We find that positive interannual variability in seasonal tracer advection generally occurs in the easterly QBO phase, as in previous work, and briefly discuss physical mechanisms. Individual simulations of the 10‐member ensemble display phase‐unlocking disruptions from this general pattern due to seasonally varying synchronizations between the model's repeating 28‐month QBO cycle and the 12‐month seasonal cycle. We find that phase locking and unlocking patterns of tracer advection calculations inferred from observations fall within the envelope of the ensemble member results. Our study bolsters evidence for variability in the interannual stratospheric dynamical influence of CFC‐11 near‐surface concentrations by assessing the QBO modulation of lower stratospheric advection via synchronization with the annual cycle. It identifies a likely cause of variations in the QBO influence on tropospheric abundances.


Time series of zonal‐mean stratospheric aerosol extinction, ozone concentrations, and geopotential height anomalies during 2020–2021. Results are shown at the 100 hPa level (Panels (a) and (b) are shown at the 70 hPa level in Figure S1). The cross and dot indicate the Australian bushfires of early 2020 and the April 2021 eruption of La Soufriere, respectively. Aerosol extinction (A, 10⁻³ km⁻¹) and ozone concentrations (B, ppmv) are derived from the Ozone Mapping and Profiler Suite Limb Profiler instrument. Geopotential heights (C, in geopotential meters; gpm) are derived from ERA5. Anomalies are calculated with respect to the base period 2012–2019 (omitting 2015 due to the eruption of Calbuco). The results are smoothed with an 11‐point (11‐degree by 11‐day) running mean filter.
Time series of area‐mean stratospheric aerosol extinction, ozone concentrations, and polar cap geopotential height anomalies. Ozone Mapping and Profiler Suite Limb Profiler aerosol extinction data (A, 10⁻³ km⁻¹) are averaged over 30–90°, ozone concentrations (B, ppmv) are averaged over 50–90°, and geopotential anomalies (C, normalized) are averaged over 60–90°. White contour lines are spaced at −0.6, −0.8, −1.0… ppmv for the ozone anomalies and ±2, 3, 4… gpm for the geopotential anomalies. Black lines in the top panel mark the onset day of the Australian bushfires and the La Soufriere eruption. Regions within the troposphere or with a relatively small number (<200) of observations are masked out. The results are smoothed with an 11‐day running mean filter. Anomalies are calculated with respect to the base period 2012–2019 (omitting 2015 due to the eruption of Calbuco).
Surface climate anomalies during the 2020 and 2021 seasons. Monthly mean anomalies in (a, b) geopotential height at 500 hPa (gpm) in the SH (c–f) 2m‐air temperature and the 850 hPa flow over (c, d) the Antarctic and (e, f) Australia. Results are shown for the periods of (a, c, e) December–January in 2020/21 and (b, d, f) November–January in 2021/22. Anomalies are calculated with respect to the base period 2012–2019 (omitting 2015 due to the eruption of Calbuco).
Scatter plots of total column ozone derived from the NASA Ozone Watch averaged over October to November (abscissa) versus (a) Ozone Mapping and Profiler Suite total column stratospheric aerosol extinction averaged over October to November, ERA5 polar cap geopotential height at (b) 100 hPa averaged over November to December and (C) 500 hPa averaged over November to January. The aerosol extinction data are averaged 30°–90°; ozone concentrations are averaged 63°–90°; and geopotential heights are averaged 60°–90°. Selected years with high aerosol loadings are indicated by the top colorbar; other years are indicated by the bottom colorbar. Anomalies are calculated with respect to the base period 2012–2019 (omitting 2015 due to the eruption of Calbuco).
Histograms of daily mean, Ozone Mapping and Profiler Suite total column stratospheric aerosol extinction, NASA Ozone Watch total column ozone, and ERA5 geopotential height anomalies at indicated levels. Results are derived from all days during October–November for aerosol extinction and total column ozone, November–December for 100 hPa height, November–January for 500 hPa height. The aerosol extinction data are averaged 30°–90°; ozone concentrations are averaged 63°–90°; and geopotential heights are averaged 60°–90°. Colored bars denote days during 2020 and 2021; gray bars denote days during all other years in the available record. The PDFs are normalized to the same height; the number of days used to construct the PDFs is indicated on the plots. Anomalies are calculated with respect to the base period 2012–2019 (omitting 2015 due to the eruption of Calbuco).
Climate Impacts and Potential Drivers of the Unprecedented Antarctic Ozone Holes of 2020 and 2021

May 2022

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129 Reads

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37 Citations

Plain Language Summary The Antarctic ozone hole is characterized by dramatic decreases in stratospheric ozone during the austral spring months. The ozone hole is expected to recover over the next few decades in response to the phasing out of ozone‐depleting substances. However, the latter months of 2020 and 2021 were marked by two of the largest Antarctic ozone holes on record, which raises questions about their origins and climate impacts. Here we provide novel evidence that supports the hypothesis that the ozone holes were influenced by two extraordinary events: the Australian wildfires of early 2020 and the eruption of La Soufriere in 2021. We further reveal that both ozone holes were associated with changes in Southern Hemisphere surface climate consistent with the established climate impacts of Antarctic ozone depletion. Together, the results provide suggestive evidence that injections of both wildfire smoke and volcanic emissions into the stratosphere can lead to hemispheric‐scale changes in surface climate.


Citations (86)


... Despite this large body of work, it remains unclear whether we are observing amplified warming of hot extremes. We a priori expect the signal, if present, to be relatively small because the primary drivers of historical trends in observed (32,33) and projected (34,35) heat extremes are trends in the mean or the median, although the signal is nevertheless important to identify given the nonlinear impact of high temperatures (36). Prior work has primarily asked whether extremes are warming at a different rate from the middle of the distribution at the local level (22,31,32,(37)(38)(39), and these local trends will have a large contribution from unforced internal variability, even on multidecadal timescales. ...

Reference:

The pace of change of summertime temperature extremes
Comparing Local Versus Hemispheric Perspectives of Extreme Heat Events

... The old research question regarding the nature and cause of the Northern Annular Mode has until now been tackled by adopting pressure coordinates, assuming quasi-geostrophic balance and evaluating the effect of eddies on the zonal-mean state of the atmosphere in terms of meridional fluxes of momentum and heat, and so-called Eliassen-Palm fluxes. See, for example, the recent book by Wallace et al. (2023). By adopting isentropic coordinates and by not taking balance for granted, this and a companion paper offer a different perspective on the same research question. ...

The Atmospheric General Circulation
  • Citing Book
  • May 2023

... Long-term cooling trends have been observed in the stratosphere at least for the past 40 years, which are primarily due to the increase of greenhouse gases with modulations by evolving ozone changes (e.g. Steiner et al., 2020b and the references therein; Santer et al., 2023). As explained in Sections 1 and 2, several homogenized radiosonde data sets are usually used in trend 375 studies (e.g. ...

Exceptional stratospheric contribution to human fingerprints on atmospheric temperature

Proceedings of the National Academy of Sciences

... The relative stationarity of the low-cloud cover until about 2015 (Figs. 2f and 3c) speaks against short-term variability, but longer-term variability associated for example with the Atlantic Multidecadal Variability (AMV; 5, 47) could contribute to the observed trends, also given that ocean surface warming can reduce low-cloud cover (35,48,49). ...

The Key Role of Cloud-Climate Coupling in Extratropical Sea Surface Temperature Variability
  • Citing Article
  • January 2023

Journal of Climate

... These occur with irregular patterns as soon as something is changed in the applied parameterizations. To test the reason for this, a simulation randomly perturbing the initial temperature of REF on the order of 10 −14 K, as done in previous work with CESM (Kay et al., 2015;Shah et al., 2022;Stone et al., 2019), led to similar tropospheric changes of these species, see Figure S3 in Supporting Information S1 for ozone. Thus, these changes are apparently a result of dynamical changes, which originate from intermediate solutions at the smaller chemistry time step when applying the chemistry sub-stepping and which then change the trace gas concentrations in the model. ...

Phase Unlocking and the Modulation of Tropopause‐Level Trace Gas Advection by the Quasibiennial Oscillation

... However, the zonal wind differences between low and high SIC winters are generally not statistically significant. Other sources of interannual variability, such as the El Nino-Southern Oscillation (Stone et al., 2021) or the QBO (Rao et al., 2023), also influence SH springtime stratospheretroposphere coupling, so that detecting the influence of sea ice fluctuations may be obscured, particularly given sampling limitations in the short satellite record. Therefore, to isolate the atmospheric circulation response to SIC interannual variability, we turn to the two large ensemble experiments described in Section 2. ...

On the Southern Hemisphere Stratospheric Response to ENSO and Its Impacts on Tropospheric Circulation
  • Citing Article
  • March 2022

Journal of Climate

... Ozone is one of the key molecular species in atmospheric chemistry and radiative processes with an impact on climate, ecosystems and human health. 1,2 Besides well-known issues related to the protective role of stratospheric ozone, 3,4 tropospheric O 3 is one of the greenhouse gases that impacts the atmospheric energy budget and can act as a toxic pollutant. 2,5,6 Its atmospheric distribution is monitored in ground-based, balloon-borne, and satellite measurements [7][8][9] (and references therein) by retrieval methods using spectral analyses. ...

Climate Impacts and Potential Drivers of the Unprecedented Antarctic Ozone Holes of 2020 and 2021

... There is constant material circulation and energy exchange between land and ocean [37]. Several marine ecosystem functions in the sea area adjacent to Jiangsu Province serve the land; similarly, terrestrial ecosystems serve the ocean. ...

Observed Linkages Between the Atmospheric Circulation and Oceanic‐Forced Sea‐Surface Temperature Variability in the Western North Pacific

... Importantly, features of deep convection start to be explicitly resolved at kilometre-scale resolutions. This does not only improve the local representation of the diurnal cycle, convective organization, and the propagation of convective storms (Prein et al., 2015;Satoh et al., 2019;Schär et al., 2020) but can also impact the large-scale circulation (Gao et al., 2023). Ultimately, the replacement of parametrizations by explicitly resolved atmospheric dynamics is also expected to narrow the still large uncertainty range of cloud-related feedbacks and thus climate sensitivity (Bony et al., 2015;Stevens et al., 2016). ...

Long-range prediction and the stratosphere

... Continuing efforts since then have been made to extend the model and improve our understanding of the air-sea interaction. Research along this line includes Cayan (1992), Barsugli and Battisti (1998), Frankignoul et al. (1998), von Storch (2000, Wu et al. (2006), Kirtman et al. (2012), Li et al. (2017), Bishop et al. (2017), Small et al. (2019), and Patrizio and Thompson (2022), to name a few. ...

Understanding the Role of Ocean Dynamics in Midlatitude Sea Surface Temperature Variability Using a Simple Stochastic Climate Model

Journal of Climate