Mean Sea Level Pressure Difference Research Articles

Characteristics of Ocean Waves in the Southern Ocean and Seasonal Prediction of Difficulty for the Vessels Crossing the Westerlies

In this study, the European Centre for Medium-Range Weather Forecasts reanalysis v5 (ERA5) wave height reanalysis data and sea-level pressure data from two seasonal prediction systems were used to study the wave characteristics of the Southern Ocean and the seasonal prediction of difficulty for the vessels crossing the westerlies. The results show that significant wave height, extreme wave height, and extreme wave processes were all much stronger in austral winter than in austral summer, making it more difficult for vessels to cross the westerlies in winter. Furthermore, the difficulty of crossing the westerlies has increased over the last 40 years, except in areas east of South America. We found that the monthly frequency of crossing the westerlies between 100° E and 75° W could be accurately estimated point by point using the monthly mean sea-level pressure difference between 30° S and 65° S. With a 1-month lead, the multi-model forecasts gave a fairly accurate forecast of such sea-level pressure difference signal between 150° E to 60° W for target months from May to December. Based on these assessments, we could estimate the difficulty of crossing the westerlies in some specific months in advance using a seasonal prediction system. We also found that the seasonal prediction system produced inaccurate predictions of sea-level pressure at high latitudes, which is the main barrier to further accurately estimating the difficulty of crossing the westerlies. These findings may provide support for predicting difficulty for the vessels crossing the westerlies with a 1-month lead and can provide planning for the route and the allocation of material reserves.

Study of the climatic teleconnection between the Siberian high and maritime continent warm pool

This paper attempts to establish a method for analysing the relationship between the polar and equatorial climate of the Northern Hemisphere. The Arctic Oscillation (AO) is known to have no direct relationship with the monsoon over the Maritime Continent (MC). Thus, an index called the Siberian High(SH)–Maritime Continent(MC) Index (SHMCI) is developed to represent the mean sea level pressure difference between the SH and the warm pool over the MC. This index indicates a strong link with the monsoon circulation. A positive (strong) value of the SHMCI is associated with strong meridional winds and intense and frequent cold surge events over the South China Sea. The correlation between the AO index and the SHMCI is -0.39, which is medium but statistically significant; however, it is not sufficiently conclusive to infer direct correlation. Nevertheless, the SHMCI can be used as a tool to relate the AO with the monsoon over the MC because of the influence demonstrated by the AO towards the SH. Further analysis on the convergence and divergence anomalies over the MC reveals an impact discernible only from the SHMCI. This implies that the SHMCI manifests clearly the relationship between the Arctic and equatorial climate.

Ensemble Sensitivity Tools for Assessing Extratropical Cyclone Intensity and Track Predictability

Abstract This paper applies ensemble sensitivity analysis to a U.S. East Coast snowstorm on 26–28 December 2010 in a way that may be beneficial for an operational forecaster to better understand the forecast uncertainties. Sensitivity using the principal components of the leading empirical orthogonal functions (EOFs) on the 50-member European Centre for Medium-Range Weather Forecasts (ECMWF) ensemble identifies the sensitive regions and weather systems at earlier times associated with the cyclone intensity and track uncertainty separately. The 5.5-day forecast cyclone intensity uncertainty in the ECMWF ensemble is associated with trough and ridge systems over the northeastern Pacific and central United States, respectively, while the track uncertainty is associated with a short-wave trough over the southern Great Plains. Sensitivity based on the ensemble mean sea level pressure difference between two run cycles also suggests that the track's shift between the two cycles is linked with the initial errors in the short-wave trough over the southern Great Plains. The sensitivity approach is run forward in time using forward ensemble regression based on short-range forecast errors, which further confirms that the short-term error over the southern plains trough was associated with the shift in cyclone position between the two forecast cycles. A coherent Rossby wave packet originated from the central North Pacific 6 days before this snowstorm event. The sensitivity signals behave like a wave packet and exhibit the same group velocity of ~29° longitude per day, indicating that Rossby wave packets may have also amplified uncertainty in both the cyclone amplitude and track forecast.

Estimating sea ice area flux across the Canadian Arctic Archipelago using enhanced AMSR‐E

Enhanced resolution Advanced Microwave Scanning Radiometer (AMSR‐E) imagery is used to estimate daily sea ice area fluxes between the Canadian Arctic Archipelago and the Arctic Ocean and Baffin Bay for the period September 2002 to June 2007. Over the period, Amundsen Gulf and M'Clure Strait exported 54 × 103 km2 of sea ice area or roughly 77 km3 of sea ice volume each year into the Arctic Ocean. Export/import into the Arctic Ocean through the Queen Elizabeth Islands is small and uncertain since no estimates for July and August could be made due to atmospheric attenuation of the microwave signal. Lancaster Sound exported 68 × 103 km2 of sea ice area or roughly 102 km3 of ice volume into Baffin Bay. This produced a net loss of sea ice area of about 122 × 103 km2 or roughly 174 km3 a−1 which is presumed to be generated from within the Archipelago itself mainly through the stationary and transient polynyas and leads that form each winter. Daily ice area fluxes for Amundsen Gulf (AG) and Lancaster Sound (LS) were as high as ±2500 km2 d−1 and were event driven depending on synoptic scale atmospheric circulation and the mobility of the sea ice. Mean sea level pressure difference across each gate is moderately correlated with daily sea ice area fluxes despite the fact that free ice drift conditions are not always met in the region. Cross‐gradient and daily sea ice area flux for Lancaster Sound show a large number of counter gradient ice flux occurrences suggesting that local mesoscale winds (nongeostrophic) and perhaps ocean currents play a role in transporting sea ice through this gate. Monthly ice fluxes for the AG and MS gate were positively correlated with the AO index indicating that a strong Beaufort Sea high pressure and gyre correspond to more export into the Beaufort Sea. Monthly fluxes for the LS gate were positively correlated with the NAO index indicating that strong southerly atmospheric circulation over Baffin Bay increases ice export into Baffin Bay from Lancaster Sound.

Internal variability in a 1000-yr control simulation with the coupled climate model ECHO-G — II. El Niño Southern Oscillation and North Atlantic Oscillation

A 1000-yr control simulation (CTL) performed with the atmosphere’ocean global climate model ECHO-G is analysed with regard to the El Niño Southern Oscillation (ENSO) and North Atlantic Oscillation (NAO), the two major natural climatic variabilities, in comparison with observations and other model simulations. The ENSO-related sea surface temperature climate and its seasonal cycle in the tropical Pacific and a single Intertropical Convergence Zone in the eastern tropical Pacific are simulated reasonably, and the ENSO phase-locking to the annual cycle and the subsurface ocean behaviour related to equatorial wave dynamics are also reproduced well. The simulated amplitude of the ENSO signal is however too large and its occurrence is too regular and frequent. Also, the observed westward propagation of zonal wind stress over the equatorial Pacific is not captured by the model. Nevertheless, the ENSO-related teleconnection patterns of near-surface temperature (T2m), precipitation (PCP) and mean sea level pressure (MSLP) are reproduced realistically.The NAO index, defined as the MSLP difference between Gibraltar and Iceland, has a ‘white’ noise spectrum similar to that of the detrended index obtained from observed data. The correlation and regression patterns of T2m, PCP and MSLP with the NAO index are also successfully simulated. However, the model overestimates the warming over the North Pacific in the high index phase of the NAO, a feature it shares with other coupled models. This might be associated with an enhanced Atlantic’Pacific teleconnection, which is hardly seen in the observations. A detection analysis of the NAO index shows that the observed recent 40–60 yr trend cannot be explained by the model’s internal variability while the recent 20–30 yr trend occurs with a more than 1% chance in ECHO-G CTL.

Trends in the Southern Annular Mode from Observations and Reanalyses

Several papers have described a significant trend toward the positive phase of the Southern Hemisphere annular mode (SAM) in recent decades. The SAM is the dominant mode of atmospheric variability in the Southern Hemisphere (SH) so such a change implies a major shift in the broadscale climate of this hemisphere. However, the majority of these studies have used NCEP‐NCAR reanalysis (NNR) data, which are known to have spurious negative trends in SH high-latitude pressure. Thus, given that the SAM describes the relative atmospheric anomalies at mid- and high southern latitudes, these errors in the NNR data have the potential to invalidate the published findings on changes in the SAM. Therefore, it is important that a ‘‘true’’ benchmark of trends in the SAM is available against which future climate scenarios as revealed through climate models can be examined. In this paper this issue is addressed by employing an empirical definition of the SAM so that station data can be utilized to evaluate true temporal changes: six stations are used to calculate a proxy zonal mean sea level pressure (MSLP) at both 408 and 658S during 1958‐2000. The observed increase in the difference in zonal MSLP between 408 (increasing) and 658S (decreasing) is shown to be statistically significant, with the trend being most pronounced since the mid-1970s. However, it is demonstrated that calculated trends in the MSLP difference between 408 and 658S and the SAM itself are exaggerated by a factor of 3 and 2, respectively, in the NNR. The SH high-latitude errors in the early part of this reanalysis are greatest in winter as are subsequent improvements. As a result, the NNR shows the greatest seasonal trend in the SAM to be in the austral winter, in marked contrast to observational data, which reveal the largest real increase to be in summer. Equivalent data from two ECMWF reanalyses, including part of the new ERA-40 reanalysis, are also examined. It is demonstrated that ERA-40 provides an improved representation of SH high-latitude atmospheric circulation variability that can be used with high confidence at least as far back as 1973—and is therefore ideal for examining the recent trend in the SAM—and with more confidence than the NNR right back to 1958.

LONG-TERM FLUCTUATION CHARACTERISTICS OF SOUTHERN OSCILLATION

Southern Oscillation (SO) is an atmospheric see-saw phenomenon in tropical Pacific sea level pressure between the eastern and western hemispheres associated with the El Nino and La Nina oceanographic features. The oscillation can be characterized by Southern Oscillation Index (SOI) which is derived from values of the monthly mean sea level pressure difference between Tahiti and Darwin, Australia. The impacts of SO on climate are widespread and extend far beyond the tropical Pacific, a phenomenon known as teleconnection.In this study, long-term fluctuation characteristics of SO are presented as guidance when using SOI for other analyses. The results show SO intensity (i. e., cross-correlation of Tahiti and Darwin pres sure deviations) is increasing almost constantly since around 1900. The reasons of increase of SO intensity are also investigated statistically in detail.

STATISTICAL CHARACTERISTICS OF SOUTHERN OSCILLATION INDEX AND ITS BAROMETRIC PRESSURE DATA

The impacts of Southern Oscillation (SO) on climate are widespread and extend far beyond the tropical Pacific, a phenomenon known as teleconnection. The oscillation can be characterized by Southern Oscillation Index (SOI) which is derived from values of the monthly mean sea level pressure difference between Tahiti and Darwin, Australia. Its best-known extreme is the El Nifio event.In this study, general statistical characteristics of SOI and the data from which it is derived (i.e. mean sea level pressure data at Tahiti and Darwin) are presented as guidance when using SOI for other analyses.The characteristics include the availability of the barometric pressure data, statistics of monthly pressure data, correlation of SO intensity, frequency analysis of SOI by magnitude and by month (January- December), duration properties of SOI by run analysis.

Spectral comparison of ENSO and stratospheric zonal winds

The 12-monthly running means of stratospheric low latitude zonal winds at 10, 15, 20, 30, 40, 50, 70 mb, Southern Oscillation Index represented by Tahiti - Darwin atmospheric mean sea level pressure difference (T - D) and equatorial eastern Pacific sea surface temperature (SST) were subjected to maximum entropy spectral analysis for the whole period 1953-1995 as also for its portions. The SST and (T - D) had similar periodicities, as expected, the majormost at ca. 4.5 years and other smaller ones in the quasi-biennial and quasi-triennial regions. The stratospheric winds had the most prominent periodicity at ca. 2.17 years (26 months) in the early years, which changed to ca. 2.22 years (26.5 months) in the middle and ca. 2.50 years (30 months) in recent years, and had other minor periodicities. Some of the wind periodicities matched some of the SST, (T - D) periodicities during some intervals, indicating possible partially common origins and/or mutual influences.

Post monsoon tropical cyclone activity in the north Indian Ocean in relation to the El Nion / southern Oscillation phenomenon

In this paper the relationship between post monsoon (Oct-Dec) tropical cyclone activity in the north Indian Ocean and El Nino Southern Oscillation (ENSO) is discussed. The study uses a 83-year {1901-1983) time series or number of storm days for preliminary analysis. On an average the number of storm days during El Nina year is not departed from the normal. Usin9 the 48-year. (1935-1982) time series of number of storm days correlations were calculated with southern oscillation index (mean sea level pressure difference between Tahiti and Darwin) before, during and after the season: A weak negative correlation is seen between the storm activity and SOI before the season. Stability of correlations is examined by recalculating correlations using four 12-year data subsets. Magnitude of correlations is found to vary significantly in the subsets.
 
 There is no appreciable difference between the strike rate (number of storm crossing the coast/total number of storms) per El Nina year and strike rate per non El Nina year. There is no marked shift in the area of formation of storms during El Nino years from the climatologically favourable area:

The Synoptic-Climatological Characteristics of Heavy Rainfalls in the Region of Pacific Ocean of Tohoku District

The appearance-distribution of heavy rainfalls (above 50 mm per day) in the region of Pacific Ocean side of Tohoku district is analysed synoptic-climatologically. The main results obtained are as follows;1) The heavy rainfalls in warm season tend to appear in the eastern (coastal) region of Tohoku district. This tendency is more obvious as the maximum amount in rainfall-area is larger.2) The heavy rainfalls in the western and central regions are mianly due to the front, thunderstorm and northwesterly monsoon. On the other hand, those in the eastern (coastal) region are mainly due to the typhoons and subtropical cyclones. Regarding the latter, almost every case (80-90%) having the maximum rainfall-amount more than 100 mm per day is due to the typhoon or subtropical cyclone.3) The larger the daily mean sea-level pressure difference (Δp) between Nemuro and Choshi, the more frequently thd heavy rainfalls (above 100 mm per day) appear in the eastern region.4) The fact mentioned in 2) is more obvious in the eastern (coastal) region when positive Δp is larger, and in the western and central regions when negative Δp is larger.5) The annual variation of frequency of heavy rainfalls in an area with the size of a prefecture corresponds to that of precipitable water. This relation, however, is not obvious in smaller regions covering a half or one third of a prefecture, because the heavy rainfall areas are dislocated according to synoptic condition specially in summer and in winter.