Sea Level Pressure Variability Research Articles

Atmospheric Precursors of Skillful SST Prediction in the Northeast Pacific

Abstract Forecasts of sea surface temperature anomalies (SSTAs) provide essential information to stakeholders of marine resources in coastal ecosystems, such as the California Current Large Marine Ecosystem (CCLME), at management-relevant monthly-to-annual time scales. Diagnosing dynamical sources of predictability and the mechanisms differentiating skill among forecasts is required for verification and improvement in operational forecasting systems. Using retrospective forecasts (1982–2020) from a four-member subset of the North American Multi-Model Ensemble (NMME), we evaluate the conditional skill of SSTA forecasts in the CCLME at monthly resolution for lead times up to 10.5 months. Forecasts from ensemble members with relatively small SSTA errors at shorter lead times retain higher skill at longer lead times, with the most substantial and long-lasting increases for forecasts initialized in the fall and early spring. The “best” low-error SSTA forecasts are characterized by increased skill in the prediction of North Pacific atmospheric circulation [sea level pressure (SLP) and 200-hPa geopotential height] the month prior to the evaluation of SSTA errors in the CCLME and exhibit more realistic progressions of anomalous SLP. The Pacific meridional mode (PMM) emerges as a diagnostic of skillful North Pacific atmosphere–ocean coupling, as forecasts that correctly simulate the PMM and its associated SLP variability increase the SSTA prediction skill in the CCLME in the fall through spring. Predictable coupled ocean–atmosphere modes provide a target for enhancing predictability with early detection of the onset of a deterministic progression emerging from stochastic atmospheric variability. Significance Statement Global forecast systems provide near-term climate predictions that inform the management of marine resources, such as those of the California Current Large Marine Ecosystem. In this study, we probe the processes which lead forecasts to succeed or fail at predicting sea surface temperatures in the California Current at seasonal time scales among retrospective forecasts from the North American Multimodel Ensemble. We demonstrate that forecasts which best simulate sea surface temperatures at the earliest lead times sustain advantages in forecast skill and find that correctly simulating extratropical atmospheric circulation increases the predictive skill of sea surface temperatures in the northeast Pacific in the following lead times. Our results offer North Pacific atmospheric circulation as a target for forecast model improvement that would additionally enhance ocean forecasts.

The Coastal Sea‐Level Response to Wind Stress in the Middle Atlantic Bight

AbstractAnalysis of 40 years of tide gauge data and reanalysis wind stresses from the Middle Atlantic Bight (MAB) indicate that along‐shelf wind stresses are a dominant driver of coastal dynamic sea level (sea level plus atmospheric pressure) variability at daily to yearly time scales. The sea‐level response to along‐shelf wind stress varies substantially along the coast and is accurately reproduced by a steady, barotropic, depth‐averaged model (Csanady, 1978, https://doi.org/10.1175/1520‐0485(1978)008<0047:tatw>2.0.co;2, Arrested Topographic Wave). The model indicates that the sea‐level response in the MAB depends primarily on the along‐shelf distribution of the along‐shelf wind stress, the Coriolis frequency, the bottom drag coefficient, and the cross‐shelf bottom slope. The along‐shelf wind stress varies along the MAB shelf due primarily to changes in the shelf orientation. The sea‐level response depends on both the local and upstream (in the sense of Kelvin wave propagation) along‐shelf wind stresses. Consequently, sea‐level variability at daily, monthly and yearly time scales along much of the central MAB coast is more strongly driven by upstream winds along the southern New England shelf than by local winds along the central MAB shelf. The residual coastal sea‐level variability, after removing the wind‐driven response and the trend, is roughly uniform along the MAB coast. The along‐coast average of the residual sea level at monthly and yearly time scales is caused by variations in shelf water densities primarily associated with the large annual cycle in water temperature and interannual variations in salinity.

Subseasonal variability of sea level pressure and its influence on snowpack over mid-high-latitude Eurasia during boreal winter

The atmospheric circulation significantly influences the snowpack over mid-high-latitude Eurasia. This study examines the characteristics of the leading subseasonal variability mode of boreal winter sea level pressure (SLP) with 20-80-day period and its relationship with snowpack over mid-high-latitude Eurasia, using the fifth generation of European Center for Medium-Range Weather Forecasts (ECMWF) reanalysis (ERA5) data and different snowpack datasets. The SLP leading mode, characterized by a monopole pattern with a strong surface anomalous high centered near the Ural Mountains, exhibits a barotropic structure and extends from the surface to the tropopause. Above SLP and geopotential height anomalies propagate southeastward from the Barents-Kara Sea to East Asia. This leading SLP mode contributes to surface air temperature (SAT) and snowfall circulation anomalies over mid-high-latitude Eurasia. The latter two both directly influence on snowpack anomalies in situ. Over high latitude region, snowfall circulation anomaly is the dominant factor to control the snow depth anomaly. Over middle latitude region, both SAT and snowfall circulation anomalies lead to the snowpack anomaly. Furthermore, the response of snow depth to the leading subseaonal SLP mode occurs 2–5 days earlier than the response of snow cover to the same mode over middle latitude region. In addition, it is suggested that the Arctic Oscillation (AO), East Atlantic/West Russia (EAWR) and Polar/Eurasia (PEU) pattern may contribute to the development of the leading SLP mode and subsequently influence snowpack anomalies.

The South Atlantic Dipole via multichannel singular spectrum analysis

This study analyzes coupled atmosphere–ocean variability in the South Atlantic Ocean. To do so, we characterize the spatio-temporal variability of annual mean sea-surface temperature (SST) and sea-level pressure (SLP) using Multichannel Singular Spectrum Analysis (M-SSA). We applied M-SSA to ERA5 reanalysis data (1959–2022) of South Atlantic SST and SLP, both individually and jointly, and identified a nonlinear trend, as well as two climate oscillations. The leading oscillation, with a period of 13 years, consists of a basin-wide southwest–northeast dipole and is observed both in the individual variables and in the coupled analysis. This mode is reminiscent of the already known South Atlantic Dipole, and it is probably related to the Pacific Decadal Oscillation and to El Niño–Southern Oscillation in the Pacific Ocean. The second oscillation has a 5-year period and also displays a dipolar structure. The main difference between the spatial structure of the decadal, 13-year, and the interannual, 5-year mode is that, in the first one, the SST cold tongue region in the southeast Atlantic’s Cape Basin is included in the pole closer to the equator. Together, these two oscillatory modes, along with the trend, capture almost 40% of the total interannual variability of the SST and SLP fields, and of their co-variability. These results provide further insights into the spatio-temporal evolution of SST and SLP variability in the South Atlantic, in particular as it relates to the South Atlantic Dipole and its predictability.

Mid-Pliocene not analogous to high-CO2 climate when considering Northern Hemisphere winter variability

Abstract. In this study, we address the question of whether the mid-Pliocene climate can act as an analogue for a future warm climate with elevated CO2 concentrations, specifically regarding Northern Hemisphere winter variability. We use a set of sensitivity simulations with the global coupled climate model CESM1.0.5 (CCSM4-Utr), which is part of the PlioMIP2 model ensemble, to separate the response to a CO2 doubling and to mid-Pliocene boundary conditions other than CO2. In the CO2 doubling simulation, the Aleutian low deepens, and the Pacific–North American pattern (PNA) strengthens. In response to the mid-Pliocene boundary conditions, sea-level pressure variance decreases over the North Pacific, the PNA becomes weaker and the North Pacific Oscillation (NPO) becomes the dominant mode of variability. The mid-Pliocene simulation shows a weak North Pacific jet stream that is less variable in intensity but has a high level of variation in jet latitude, consistent with a dominant NPO and indicating that North Pacific atmospheric dynamics become more North Atlantic-like. We demonstrate that the weakening of the Aleutian low, and subsequent relative dominance of the NPO over the PNA, is related to shifts in tropical Pacific convection. Variability in the North Atlantic shows little variation between all simulations. The opposite response in North Pacific winter variability to elevated CO2 or mid-Pliocene boundary conditions demonstrates that the mid-Pliocene climate cannot serve as a future analogue in this regard.

A Mechanism for the Summer Monsoon Precipitation Variability Over Northwest India Driven by Moisture Deficit Transport

AbstractA large reservoir of saturation deficit air is known to exist over the northern Arabian Sea and the adjoining land regions during the peak of Indian summer monsoon (ISM). The strengthening of monsoon low‐level jet (LLJ) in the northern parts of the Arabian Sea during the break phase of ISM helps in transporting this dry air toward northwestern India. Here, we show that, a weakening (strengthening) of the zonal flow over the northern Arabian Sea can reduce (enhance) the influx of the unsaturated air to the Northwest India and thereby enhance (reduce) precipitation there. The variability in the zonal flow over the northern Arabian Sea is a direct geostrophic response to the variability in the meridional pressure gradient over the Northwest India. The interannual variability in the mean sea level pressure over the region explains the inter‐annual variability of ISM precipitation during July–August over northwestern India. The contribution of El Niño Southern Oscillation in the interannual variability of precipitation over this region is not significant.

Signal‐to‐noise errors in free‐running atmospheric simulations and their dependence on model resolution

AbstractEnsemble forecasts have been shown to better predict observed Atlantic climate variability than that of their own ensemble members. This phenomenon—termed the signal‐to‐noise paradox—is found to be widespread across models, timescales, and climate variables, and has wide implications. The signal‐to‐noise paradox can be interpreted as forecasts underestimating the amplitude of predictable signals on seasonal‐to‐decadal timescales. The cause of this remains unknown. Here, we examine sea level pressure variability from a very large multi‐model ensemble of uninitialized atmosphere‐only simulations, focusing on boreal winter. To assess signal‐to‐noise errors, the ratio of predictable components (RPC) is examined globally, as well as for regional climate indices: the North Atlantic Oscillation, Arctic Oscillation, Southern Annular Mode, and an Arctic index. Our analyses reveal significant correlations between the multi‐model ensemble‐mean and observations over large portions of the globe, particularly the tropics, North Atlantic, and North Pacific. However, RPC values greater than one are apparent over many extratropical regions and in all four climate indices. Higher‐resolution models produce greater observation‐model correlations and greater RPC values than lower‐resolution models in all four climate indices. We find that signal‐to‐noise errors emerge more clearly at higher resolution, but the amplitudes of predictable signals do not increase with resolution, at least across the range of resolutions considered here. Our results suggest that free‐running atmospheric models underestimate predictable signals in the absence of sea surface temperature biases, implying that signal‐to‐noise errors originate in the atmosphere or in ocean–atmosphere coupling.

A regional attentive empirical orthogonal function analysis: An application to North Atlantic Oscillation

AbstractEmpirical orthogonal function (EOF) analysis is widely adopted for identifying spatial patterns in regular latitude‐longitude gridded geographical data. However, a standard EOF analysis could underestimate variances from low latitudes due to the increasing grid cell areas when moving toward the equator. A broadly adopted compensating approach is the area‐weighted EOF, where the grid data are multiplied by a factor proportional to the grid area, thereby forcing each datum to represent identical areas. In this article, we revisit the area‐weighting scheme and discuss its potential drawbacks. In particular, we show that along with compensating the unequal areas, another unaddressed issue is which region of the data is more relevant to our focused problem. We propose a regional attentive EOF (RA‐EOF) method, which resolves area‐compensation and region selection simultaneously. We conduct case studies of the North Atlantic Oscillation (NAO) analysis and perform RA‐EOF to the sea level pressure variability in the North Atlantic sector. Experiments show that our method evidently detects the NAO pattern in the leading mode of sea level pressure variability and suggests the southwestward movement of the southern action centre of NAO during the summers. Our findings clarify the ambiguity about the summer NAO in previous studies. The proposed methodology provides a potent instrument for discerning the spatial distribution and analysing the temporal variability of atmospheric teleconnections and oscillations, particularly in cases characterized by weak signal strength.

Revisiting the Relationship between the North Pacific High and Upwelling Winds along the West Coast of North America in the Present and Future Climate

Abstract The wind-driven circulation is an important driver of upwelling in the California Current System, a key factor in maintaining a productive ecosystem. In summer, the North Pacific high (NPH) dominates the atmospheric circulation, including the nearshore winds. The impact of the NPH on the surface winds along the North American west coast during summer is examined using the ECMWF Reanalysis v5 (ERA5) and the Community Earth System Model version 1 (CESM1) large ensemble of simulations. The strength, latitude, and longitude of the sea level pressure (SLP) and subsidence at 500 hPa are used to assess the NPH and its variability. While both the surface high pressure cell and subsidence are related to the interannual variability of the surface winds over the North Pacific, the strength of subsidence has a much larger effect on the coastal winds than the variability in SLP. Based on the mean of the 40 CESM simulations, future changes in upwelling also more strongly coincide with changes in subsidence than in SLP. Subsidence and southward upwelling-favorable winds increase off the Canadian coast, with the reverse occurring off the U.S. West Coast, by the end of the twenty-first century. In particular, the intermember correlation between the changes in the nearshore surface winds and the 500-hPa pressure vertical velocity reaches 0.75 and 0.87 in the southern and northern portions of the northeast Pacific, respectively. The effect of the subsidence on upwelling winds in the future is confirmed by the CESM2 large ensemble.

Decoupling of Arctic variability from the North Pacific in a warmer climate

The sea level pressure variability in the North Pacific modulates the climate of the Arctic and surrounding continents, substantially impacting ecosystems and indigenous communities. Our analysis based on data from the CESM2 Large Ensemble and different Model Intercomparison Project datasets reveals that the interannual variability of Arctic surface air temperature (SAT) gradually decouples from the contemporaneous atmospheric conditions over the North Pacific as external forcing increases in intensity in the future. Future projections show that the North Pacific-Arctic relationship during the fall season consistently weakens in magnitude until the end of this century, and in the 22nd and 23rd centuries, the relationship is negligible throughout the year. We show that under increased greenhouse gas emissions, the regional heat fluxes extensively control the Arctic temperature variability, and the strength of the projected North Pacific-Arctic relationship is strongly dependent on the Arctic sea ice extent. Our results suggest that under future warming, a strong coupling of Arctic SAT with the underlying ocean and a weakening of the meridional pressure gradient driven by an enhanced rate of sea ice retreat will weaken the interannual footprint of North Pacific variability on Arctic SAT. Therefore, we propose that the alarming rate of sea-ice decline over recent decades and projected in the near future could accelerate the rate of decoupling. Further, we suggest that mitigation strategies for the Arctic should focus on regional mechanisms operating on interannual and seasonal timescales.

Spatio-temporal long-term evaluations of the mean sea level pressure, sea level change, and sea surface temperature over two enclosed seas

This study aims to examine the temporal and spatial variability of mean sea level pressure (MSLP) and to determine the relationship between MSLP and the oceanic data, such as sea surface temperature (SST), and sea level anomaly (SLA). The long-term and decadal averages, long-term trends, and their statistical significance levels were evaluated in the eastern Mediterranean and Black seas as enclosed sea examples. In the Black Sea, the western part was exposed to higher MSLP accompanied by relatively low sea level rise compared to the eastern part of the sea. In the eastern Black Sea, significant sea level rise was detected, where the MSLP was low due to the inverse barometer (IB) effect. In the eastern Mediterranean Sea, MSLP was significantly decreased eastward and was accompanied by relatively high sea level rise compared to other parts of the basin. The highest MSLP was found in the Aegean Sea, where the sea level rise was relatively low. In recent years, significant warming tendency in SST triggers a significant decreasing trend in MSLP and the rising tendency in sea level over the eastern Mediterranean and Black seas.

The modelled climatic response to the 18.6-year lunar nodal cycle and its role in decadal temperature trends

Abstract. The 18.6-year lunar nodal cycle arises from variations in the angle of the Moon's orbital plane. Previous work has linked the nodal cycle to climate but has been limited by either the length of observations analysed or geographical regions considered in model simulations of the pre-industrial period. Here we examine the global effect of the lunar nodal cycle in multi-centennial climate model simulations of the pre-industrial period. We find cyclic signals in global and regional surface air temperature (with amplitudes of around 0.1 K) and in ocean heat uptake and ocean heat content. The timing of anomalies of global surface air temperature and heat uptake is consistent with the so-called slowdown in global warming in the first decade of the 21st century. The lunar nodal cycle causes variations in mean sea level pressure exceeding 0.5 hPa in the Nordic Seas region, thus affecting the North Atlantic Oscillation during boreal winter. Our results suggest that the contribution of the lunar nodal cycle to global temperature should be negative in the mid-2020s before becoming positive again in the early 2030s, reducing the uncertainty in time at which projected global temperature reaches 1.5 ∘C above pre-industrial levels.

On the Nature and Origin of Atmospheric Annual and Semi-Annual Oscillations

This paper proposes a joint analysis of variations of global sea-level pressure (SLP) and of Earth’s rotation (RP), expressed as the coordinates of the rotation pole (m1, m2) and length of day (lod). We retain iterative singular spectrum analysis (iSSA) as the main tool to extract the trend, periods, and quasi periods in the data time series. SLP components are a weak trend, seven quasi-periodic or periodic components (∼130, 90, 50, 22, 15, 4, 1.8 years), an annual cycle, and its first three harmonics. These periods are characteristic of the space-time evolution of the Earth’s rotation axis and are present in many characteristic features of solar and terrestrial physics. The amplitudes of the annual SLP component and its three first harmonics decrease from 93 hPa for the annual to 21 hPa for the third harmonic. In contrast, the components with pseudo-periods longer than a year range between 0.2 and 0.5 hPa. We focus mainly on the annual and, to a lesser extent, the semi-annual components. The annual RP and SLP components have a phase lag of 152 days (half the Euler period). Maps of the first three components of SLP (that together comprise 85% of the data variance) reveal interesting symmetries. The trend is very stable and forms a triskeles structure that can be modeled as Taylor–Couette flow of mode 3. The annual component is characterized by a large negative anomaly extending over Eurasia in the NH summer (and the opposite in the NH winter) and three large positive anomalies over Australia and the southern tips of South America and South Africa in the SH spring (and the opposite in the SH autumn), forming a triskeles. The semi-annual component is characterized by three positive anomalies (an irregular triskeles) in the NH spring and autumn (and the opposite in the NH summer and winter), and in the SH spring and autumn by a strong stable pattern consisting of three large negative anomalies forming a clear triskeles within the 40–60∘ annulus formed by the southern oceans. A large positive anomaly centered over Antarctica, with its maximum displaced toward Australia, and a smaller one centered over Southern Africa, complement the pattern. Analysis of iSSA components of global sea level pressure shows a rather simple spatial distribution with the principal forcing factor being changes in parameters of the Earth’s rotation pole and velocity. The flow can probably best be modeled as a set of coaxial cylinders arranged in groups of three (triskeles) or four and controlled by Earth topography and continent/ocean boundaries. Flow patterns suggested by maps of the three main iSSA components of SLP (trend, annual, and semi-annual) are suggestive of Taylor–Couette flow. The envelopes of the annual components of SLP and RP are offset by four decades, and there are indications that causality is present in that changes in Earth rotation axis lead force pressure variations.

Developing and evaluating week 2 and weeks 3-4 outlook tools for extratropical storminess

Extratropical cyclones give rise to most of the high impact weather in the mid-to high-latitudes during the cool seasons, including heavy precipitation and strong winds. Thus it is important for stakeholders to be informed of approaching periods of increased or decreased cyclone activity. While individual cyclone tracks can be predicted out to about a week or so, from week 2 on, statistics summarizing cyclone activity, or storminess, are more useful. Storminess can be defined based on Lagrangian cyclone tracking or by Eulerian variance statistics. The outlook includes a combination of both methods. Lagrangian cyclone tracks provide information about where cyclones pass through and are more intuitive to users, while Eulerian variance statistics have been shown to be highly correlated with cyclone-related weather and are expected to be more predictable given that they are not as noisy. In this paper, we evaluate a storminess outlook tool developed based on dynamical model forecasts in the week-2 and weeks 3-4 time ranges. The outlook uses two 6-hourly subseasonal ensemble forecasts–the Global Ensemble Forecast System version 12 (GEFSv12), and the coupled Climate Forecast System version 2 (CFSv2). Hindcasts and operational forecasts from 1999–2016 are used to assess the prediction skill. Our results show that the GEFSv12 and CFSv2 combined ensemble has higher skill than either individual ensemble. The combined ensemble shows some skill in predicting cyclone amplitude and frequency out to weeks 3-4, with highest skill in winter, and lowest skill in summer. Models also show some skill in predicting the statistics of deep cyclones for week 2. The prediction skills for an Eulerian sea level pressure variance storminess metric is significantly higher than those for Lagrangian track statistics. Our results also show that GEFSv12 performs better than its predecessor GEFSv11. Correlations between the storminess indices and surface weather, including precipitation and high winds, are examined. A publicly accessible web page has been developed to display the subseasonal predictions in real time. The web page also contains information on climatology and forecast verification to enable users to make more informed use of the outlook.

Spatio-temporal variability of mean wave energy flux in the Caribbean Sea

Mean wave energy flux (hereinafter WEF) is assessed in the Caribbean Sea from a 60-year (1958–2017) wave hindcast. We use a novel approach, based on neural networks, to identify coherent regions of WEF and their association with different climate patterns. This method allows for a better evaluation of the underlying dynamics behind seasonal and inter-annual WEF variability, including the effect induced by the latitudinal migration of the Intertropical Convergence Zone (ITCZ) and the influence of El Niño-Southern Oscillation (ENSO) events. Results show regional differences in WEF variability likely due to both intensification and migration of the ITCZ. WEF exhibits a strong semi-seasonal signal in areas of the continental shelf, with maxima reached in January and June, in agreement with the known sea surface temperature and sea-level pressure variability patterns. At larger scales, WEF shows a significant correlation with the Oceanic Niño Index (ONI, which is the primary index for tracking the ocean part of ENSO climate pattern), depicting positive values in the central and western sides of the basin and negative ones at the eastern side.

Network connectivity between the winter Arctic Oscillation and summer sea ice in CMIP6 models and observations

Abstract. The indirect effect of winter Arctic Oscillation (AO) events on the following summer Arctic sea ice extent suggests an inherent winter-to-summer mechanism for sea ice predictability. On the other hand, operational regional summer sea ice forecasts in a large number of coupled climate models show a considerable drop in predictive skill for forecasts initialised prior to the date of melt onset in spring, suggesting that some drivers of sea ice variability on longer timescales may not be well represented in these models. To this end, we introduce an unsupervised learning approach based on cluster analysis and complex networks to establish how well the latest generation of coupled climate models participating in phase 6 of the World Climate Research Programme Coupled Model Intercomparison Project (CMIP6) are able to reflect the spatio-temporal patterns of variability in Northern Hemisphere winter sea-level pressure and Arctic summer sea ice concentration over the period 1979–2020, relative to ERA5 atmospheric reanalysis and satellite-derived sea ice observations, respectively. Two specific global metrics are introduced as ways to compare patterns of variability between models and observations/reanalysis: the adjusted Rand index – a method for comparing spatial patterns of variability – and a network distance metric – a method for comparing the degree of connectivity between two geographic regions. We find that CMIP6 models generally reflect the spatial pattern of variability in the AO relatively well, although they overestimate the magnitude of sea-level pressure variability over the north-western Pacific Ocean and underestimate the variability over northern Africa and southern Europe. They also underestimate the importance of regions such as the Beaufort, East Siberian, and Laptev seas in explaining pan-Arctic summer sea ice area variability, which we hypothesise is due to regional biases in sea ice thickness. Finally, observations show that historically, winter AO events (negatively) covary strongly with summer sea ice concentration in the eastern Pacific sector of the Arctic, although now under a thinning ice regime, both the eastern and western Pacific sectors exhibit similar behaviour. CMIP6 models however do not show this transition on average, which may hinder their ability to make skilful seasonal to inter-annual predictions of summer sea ice.

Interdecadal Variation of the Antarctic Circumpolar Wave Based on the 20CRV3 Dataset

As a large-scale ocean–atmosphere coupling system in the Southern Hemisphere, the Antarctic Circumpolar Wave (ACW) greatly impacts the global climate. However, the interdecadal variation of the ACW has rarely been studied due to the lack of long-term data. In this research, the latest 20th Century Reanalysis Version 3 dataset is used to analyze the interdecadal variations of sea level pressure (SLP) and sea surface temperature (SST) signals in the ACW during 1836–2015. The results indicate that the ACW has not always been present in the recent 180 years, and it has remarkable interdecadal variations. Specifically, the ACW was hard to distinguish before the 1870s. The SLP anomalies propagated eastwards over the South Pacific and South Atlantic during part of the 1880s–1940s. The SST anomalies also have an eastward propagation in the 1880s–1960s. The most active period of the SLP signal is in the 1950s–1990s, while that of the SST signal is in the 1980s–1990s. The ACW has not been significant since the 21st century. The interdecadal variation of the SLP may be related to the variations of the long-term Southern Annular Mode and Pacific-South American pattern, while the interdecadal variation of the SST is more associated with the ENSO.

Atmospheric Forcing of the Pacific Meridional Mode: Tropical Pacific‐Driven Versus Internal Variability

AbstractThe Pacific Meridional Mode (PMM) impacts tropical Pacific sea surface temperature variations, which in turn affect the PMM through the excited atmospheric teleconnections. Previous studies linked this loop to the tropical Pacific‐excited North Pacific Oscillation (NPO; the second empirical mode of North Pacific sea level pressure variability), while a recent study proposed the linkage to the excited Aleutian low (AL) variability (the first empirical mode). Unraveling their relative importance for the loop is thus crucial for better understanding subtropical‐tropical interactions. Here, using tropical Pacific pacemaker experiments we show that tropical Pacific‐forced AL variability is tied to the loop, while the tropical Pacific‐forced NPO does not effectively induce PMM variability, hence not being in the loop. Our study emphasizes the role of tropical Pacific‐forced AL variability in the PMM‐tropical Pacific interaction, which should be paid more attention in future studies.

Influence of Sea Level Pressure on Inter-Annual Rainfall Variability in Northern Senegal in the Context of Climate Change

This study examines the inter-annual variability of rainfall and Mean Sea Level Pressure (MSLP) over west Africa based on analysis of the Global Precipitation Climatology Project (GPCP) and National Center for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) Reanalysis respectively. An interconnection is found in this region, between Mean Sea Level Pressure (MSLP) anomaly (over Azores and St. Helena High) and monthly mean precipitation during summer (June to September: JJAS). We also found that over northern Senegal (15°N - 17°N; 17°W - 13°W) the SLP to the north is strong; the wind converges at 200 hPa corresponding to the position of the African Easterly Jet (AEJ) the rotational wind 700 hPa (corresponding to the position of the African Easterly Jet (AEJ) coming from the north-east is negative. In this region, the precipitation is related to the SLP to the north with the opposite sign. The Empirical Orthogonal Functions (EOF) of SLP is also presented, including the mean spectrum of precipitation and pressures to the north (15°N - 40°N and 50°W - 25°W) and south (40°S - 10°S and 40°W - 0°E). The dominant EOF of Sea Level Pressures north and south of the Atlantic Ocean for GPCP represents about 62.2% and 69.4% of the variance, respectively. The second and third EOFs of the pressure to the north account for 24.0% and 6.5% respectively. The second and third EOFs of the pressure to the south represent 12.5% and 8.9% respectively. Wet years in the north of Senegal were associated with anomalous low-pressure areas over the north Atlantic Ocean as opposed to the dry years which exhibited an anomalous high-pressure area in the same region. On the other hand, over the South Atlantic, an opposition is noted. The wavelet analysis method is applied to the SLP showings to the north, south and precipitation in our study area. The indices prove to be very consistent, especially during intervals of high variance.

Are the Different Eddy Metrics Quantifying the Winter North Pacific Storm Track Consistent With Each Other?

AbstractHistorical simulations from twenty‐nine Coupled Model Intercomparison Project Phase 6 (CMIP6) models are used to investigate the consistency among different eddy metrics characterizing the winter North Pacific storm track (WNPST). All CMIP6 models can reproduce the basic climatological characteristics of the WNPST. Results show that, out of the metrics studies, only the upper‐tropospheric filtered meridional wind variance () is significantly correlated with the model grid spacing. The climatological amplitudes of different eddy metrics are consistent with each other, except for the consistency between the upper‐tropospheric and lower‐tropospheric meridional eddy heat flux and that between the middle‐tropospheric eddy kinetic energy and filtered sea level pressure variance (). The strength trends of different eddy metrics are consistent with each other except for upper‐tropospheric and . The meridional migration trends are consistent among different eddy metrics excluding . Given that the sensitivity to horizontal resolution, climatological amplitude, strength trend and meridional migration trend of different Eulerian eddy metrics may exhibit inconsistency, the use of multiple eddy metrics to increase the reliability of the results is suggested.