scholarly journals Identification and Climatology of Southern Hemisphere Mobile Fronts in a Modern Reanalysis

2012 ◽  
Vol 25 (6) ◽  
pp. 1945-1962 ◽  
Author(s):  
Ian Simmonds ◽  
Kevin Keay ◽  
John Arthur Tristram Bye
Keyword(s):  
Indian Ocean ◽  
Southern Hemisphere ◽  
Opposite Sign ◽  
Latitude Belt ◽  
Weather Forecasts ◽  
Weather And Climate ◽  
Medium Range ◽  
Semiannual Variation ◽  
The Indian Ocean ◽  
The Mean

Abstract Presented here is an objective approach to identify, characterize, and track Southern Hemisphere mobile fronts in hemispheric analyses of relatively modest resolution, such as reanalyses. Among the principles in its design were that it should be based on broadscale synoptic considerations and be as simple and easily understood as possible. The resulting Eulerian scheme has been applied to the European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA)–Interim and a climatology of frontal characteristics, at both the 10-m and 850-hPa levels, derived for the period 1 January 1989–28 February 2009. The knowledge of the character of these features is central to understanding weather and climate over the hemisphere. In both summer and winter the latitude belt 40°–60°S hosts the highest frequency of frontal points, but there are significant zonal asymmetries within this band. The climatology reveals that the longest fronts are in the Indian Ocean where mean lengths exceed 2000 km. The mean frontal intensity over the hemisphere tends to be greater at 850 hPa than at 10 m, and greater in winter than in summer. The frontal intensity also shows its maximum in the Indian Ocean. In the mean, the meridional tilt of these fronts is northwest–southeast over much of the midlatitudes and subtropics, and increases with latitude toward the equator. The tilts are of overwhelmingly opposite sign in the coastal Antarctic and subantarctic regions. Broadly speaking, the number of fronts and their mean length and mean intensity exhibit maxima in winter in the midlatitudes (30°–50°S), but show a sizeable semiannual variation (maxima in fall and spring) during the year at higher latitudes.

scholarly journals Triggering the Indian Ocean Dipole from the Southern Hemisphere

2021 ◽  
Author(s):  
Lian-Yi Zhang ◽  
Yan Du ◽  
Wenju Cai ◽  
Zesheng Chen ◽  
Tomoki Tozuka ◽  
...  
Keyword(s):  
Indian Ocean ◽  
Southern Hemisphere ◽  
Indian Ocean Dipole ◽  
Southern Oscillation ◽  
Southern Annular Mode ◽  
Triggering Mechanism ◽  
Phase Development ◽  
The Indian Ocean ◽  
High System ◽  
The Tropics

<p>This study identifies a new triggering mechanism of the Indian Ocean Dipole (IOD) from the Southern Hemisphere. This mechanism is independent from the El Niño/Southern Oscillation (ENSO) and tends to induce the IOD before its canonical peak season. The joint effects of this mechanism and ENSO may explain different lifetimes and strengths of the IOD. During its positive phase, development of sea surface temperature cold anomalies commences in the southern Indian Ocean, accompanied by an anomalous subtropical high system and anomalous southeasterly winds. The eastward movement of these anomalies enhances the monsoon off Sumatra-Java during May-August, leading to an early positive IOD onset. The pressure variability in the subtropical area is related with the Southern Annular Mode, suggesting a teleconnection between high-latitude and mid-latitude climate that can further affect the tropics. To include the subtropical signals may help model prediction of the IOD event.</p>

scholarly journals Scientific motivation for ADM/Aeolus mission

2018 ◽  
Vol 176 ◽  
pp. 02008
Author(s):  
Erland Källén
Keyword(s):  
Weather Forecast ◽  
Weather Forecasts ◽  
Weather And Climate ◽  
Medium Range ◽  
Forecast Models ◽  
Tropical Areas ◽  
Global Coverage ◽  
Wind Lidar ◽  
Wind Profiles

The ADM/Aeolus wind lidar mission will provide a global coverage of atmospheric wind profiles. Atmospheric wind observations are required for initiating weather forecast models and for predicting and monitoring long term climate change. Improved knowledge of the global wind field is widely recognised as fundamental to advancing the understanding and prediction of weather and climate. In particular over tropical areas there is a need for better wind data leading to improved medium range (3-10 days) weather forecasts over the whole globe.

scholarly journals Relations between Annular Modes and the Mean State: Southern Hemisphere Winter

2007 ◽  
Vol 64 (9) ◽  
pp. 3328-3339 ◽  
Author(s):  
Francis Codron
Keyword(s):  
Southern Hemisphere ◽  
Low Frequency ◽  
Stationary Waves ◽  
Annular Modes ◽  
The Pacific ◽  
Latitudinal Shift ◽  
The Indian Ocean ◽  
The Mean ◽  
Hemisphere Winter ◽  
Mean State

Abstract In a zonally symmetric climatology with a single eddy-driven jet, such as prevails in the Southern Hemisphere summer, the midlatitude variability is dominated by fluctuations of the jet around its mean position, as described by the Southern Hemisphere annular mode (SAM). To study whether this result holds for a zonally asymmetric climatology, the observed variability of the Southern Hemisphere winter is analyzed. The mean state in this case is characterized by relatively weak stationary waves; yet there exist significant zonal variations in the mean strength and meridional structure of the subtropical jet stream. As in summer, the winter SAM signature is annular in shape and the corresponding wind anomalies are dipolar; but it is associated with two different behaviors of the eddy-driven jet in different longitudinal ranges. Over the Indian Ocean, the SAM is associated primarily with a latitudinal shift of the jet around its mean position. Over the Pacific sector, it is instead characterized by a seesaw in the wind speed between two distinct latitudes, corresponding to the positions of the midlatitude and subtropical jets. Composites of eddy forcing and baroclinicity over both sectors appear consistent with the two different behaviors. As in the zonal-mean case, high-frequency eddies both force and maintain the low-frequency wind anomalies associated with the SAM. The positive feedback by eddies is, however, not local: changes in the eddy forcing are influenced most strongly by zonal wind anomalies located upstream.

Seasonal variations in the Indian Ocean along 110°E. III. Chlorophylls a and c

1969 ◽  
Vol 20 (1) ◽  
pp. 55 ◽  
Author(s):  
GF Humphrey ◽  
JD Kerr
Keyword(s):  
Regression Analysis ◽  
Indian Ocean ◽  
Water Column ◽  
Chlorophyll A ◽  
Seasonal Variations ◽  
The Indian Ocean ◽  
The Mean

The mean concentrations for all samples analysed were 0.17 �g/l for chlorophyll a and 0.22 �g/I. for chlorophyll c; there were 27 mg/m² of a and 35 mg/m² of c in the water column to 150 m. June-August gave the highest values. The model depth at which concentrations were greatest was 75 m. Diagrams of regression surfaces fitted to the results are given. Regression analysis showed that depth, latitude, and season affected the concentration of chlorophylls; latitude and season affected the column amount of chlorophylls.

New Methods for Data Storage of Model Output from Ensemble Simulations

2019 ◽  
Vol 147 (2) ◽  
pp. 677-689 ◽  
Author(s):  
Peter D. Düben ◽  
Martin Leutbecher ◽  
Peter Bauer
Keyword(s):  
Data Storage ◽  
Climate Modeling ◽  
Model Resolution ◽  
Ensemble Spread ◽  
Ensemble Forecasts ◽  
Weather Forecasts ◽  
Ensemble Simulations ◽  
New Methods ◽  
Weather And Climate ◽  
Medium Range

Abstract Data storage and data processing generate significant cost for weather and climate modeling centers. The volume of data that needs to be stored and data that are disseminated to end users increases with increasing model resolution and the use of larger forecast ensembles. If precision of data is reduced, cost can be reduced accordingly. In this paper, three new methods to allow a reduction in precision with minimal loss of information are suggested and tested. Two of these methods rely on the similarities between ensemble members in ensemble forecasts. Therefore, precision will be high at the beginning of forecasts when ensemble members are more similar, to provide sufficient distinction, and decrease with increasing ensemble spread. To keep precision high for predictable situations and low elsewhere appears to be a useful approach to optimize data storage in weather forecasts. All methods are tested with data of operational weather forecasts of the European Centre for Medium-Range Weather Forecasts.

scholarly journals Northern and southern hemisphere controls on seasonal sea surface temperatures in the Indian Ocean during the last deglaciation

2013 ◽  
Vol 28 (4) ◽  
pp. 619-632 ◽  
Author(s):  
Yiming V. Wang ◽  
Guillaume Leduc ◽  
Marcus Regenberg ◽  
Nils Andersen ◽  
Thomas Larsen ◽  
...  
Keyword(s):  
Indian Ocean ◽  
Southern Hemisphere ◽  
Sea Surface ◽  
Sea Surface Temperatures ◽  
Last Deglaciation ◽  
Surface Temperatures ◽  
The Indian Ocean ◽  
The Last Deglaciation

scholarly journals Trend Detection of Wave Parameters along the Italian Seas

Water ◽  
2021 ◽  
Vol 13 (12) ◽  
pp. 1634
Author(s):  
Tommaso Caloiero ◽  
Francesco Aristodemo
Keyword(s):  
Kendall Test ◽  
Trend Detection ◽  
Wave Power ◽  
Mean Values ◽  
Significance Level ◽  
Weather Forecasts ◽  
Wave Energy Converters ◽  
Wave Parameters ◽  
Medium Range ◽  
The Mean

In this paper, trend detection of wave parameters such as significant wave height, energy period, and wave power along the Italian seas was carried out. To this purpose, wave time series in the period 1979–2018 taken from the global atmospheric reanalysis ERA-Interim by European Center for Medium-Range Weather Forecasts (ECMWF) were considered. Choosing a significance level equal to 90%, the use of the Mann–Kendall test allowed estimating ongoing trends on the mean values evaluated at yearly and seasonal scale. Furthermore, the assessment of the magnitude of the increase/decrease of the wave parameters was performed through the Theil–Sen estimator. The obtained results underlined that the mean values of the considered wave parameters were characterized by a high occurrence of positive trends in the different Italian seas. The findings of this study could have implications for studies of coastal flooding, shoreline variations, and port operations, and for the assessment of the performances of Wave Energy Converters.

scholarly journals Annual, Seasonal, and Interannual Variability of Air–Sea Heat Fluxes in the Indian Ocean

2007 ◽  
Vol 20 (13) ◽  
pp. 3190-3209 ◽  
Author(s):  
Lisan Yu ◽  
Xiangze Jin ◽  
Robert A. Weller
Keyword(s):  
Heat Flux ◽  
Indian Ocean ◽  
Interannual Variability ◽  
Seasonal Cycle ◽  
Arabian Sea ◽  
Heat Fluxes ◽  
The Other ◽  
Net Heat Flux ◽  
The Indian Ocean ◽  
The Mean

Abstract This study investigated the accuracy and physical representation of air–sea surface heat flux estimates for the Indian Ocean on annual, seasonal, and interannual time scales. Six heat flux products were analyzed, including the newly developed latent and sensible heat fluxes from the Objectively Analyzed Air–Sea Heat Fluxes (OAFlux) project and net shortwave and longwave radiation results from the International Satellite Cloud Climatology Project (ISCCP), the heat flux analysis from the Southampton Oceanography Centre (SOC), the National Centers for Environmental Prediction reanalysis 1 (NCEP1) and reanalysis-2 (NCEP2) datasets, and the European Centre for Medium-Range Weather Forecasts operational (ECMWF-OP) and 40-yr Re-Analysis (ERA-40) products. This paper presents the analysis of the six products in depicting the mean, the seasonal cycle, and the interannual variability of the net heat flux into the ocean. Two time series of in situ flux measurements, one taken from a 1-yr Arabian Sea Experiment field program and the other from a 1-month Joint Air–Sea Monsoon Interaction Experiment (JASMINE) field program in the Bay of Bengal were used to evaluate the statistical properties of the flux products over the measurement periods. The consistency between the six products on seasonal and interannual time scales was investigated using a standard deviation analysis and a physically based correlation analysis. The study has three findings. First of all, large differences exist in the mean value of the six heat flux products. Part of the differences may be attributable to the bias in the numerical weather prediction (NWP) models that underestimates the net heat flux into the Indian Ocean. Along the JASMINE ship tracks, the four NWP modeled mean fluxes all have a sign opposite to the observations, with NCEP1 being underestimated by 53 W m−2 (the least biased) and ECMWF-OP by 108 W m−2 (the most biased). At the Arabian Sea buoy site, the NWP mean fluxes also have an underestimation bias, with the smallest bias of 26 W m−2 (ERA-40) and the largest bias of 69 W m−2 (NCEP1). On the other hand, the OAFlux+ISCCP has the best comparison at both measurement sites. Second, the bias effect changes with the time scale. Despite the fact that the mean is biased significantly, there is no major bias in the seasonal cycle of all the products except for ECMWF-OP. The latter does not have a fixed mean due to the frequent updates of the model platform. Finally, among the four products (OAFlux+ISCCP, ERA-40, NCEP1, and NCEP2) that can be used for studying interannual variability, OAFlux+ISCCP and ERA-40 Qnet have good consistency as judged from both statistical and physical measures. NCEP1 shows broad agreement with the two products, with varying details. By comparison, NCEP2 is the least representative of the Qnet variabilities over the basin scale.

scholarly journals Interaction between the MJO and Polar Circulations

2013 ◽  
Vol 26 (11) ◽  
pp. 3562-3574 ◽  
Author(s):  
Maria Flatau ◽  
Young-Joon Kim
Keyword(s):  
Indian Ocean ◽  
Southern Hemisphere ◽  
Warm Season ◽  
Cold Season ◽  
The Arctic ◽  
Boreal Winter ◽  
Annular Modes ◽  
The Indian Ocean ◽  
The Arctic Oscillation ◽  
The Tropics

Abstract A tropical–polar connection and its seasonal dependence are examined using the real-time multivariate Madden–Julian oscillation (MJO) (RMM) index and daily indices for the annular modes, the Arctic Oscillation (AO) and the Antarctic Oscillation (AAO). On the intraseasonal time scale, the MJO appears to force the annular modes in both hemispheres. On this scale, during the cold season, the convection in the Indian Ocean precedes the increase of the AO/AAO. Interestingly, during the boreal winter (Southern Hemisphere warm season), strong MJOs in the Indian Ocean are related to a decrease of the AAO index, and AO/AAO tendencies are out of phase. On the longer time scales, a persistent AO/AAO anomaly appears to influence the convection in the tropical belt and impact the distribution of MJO-preferred phases. It is shown that this may be a result of the sea surface temperature (SST) changes related to a persistent AO, with cooling over the Indian Ocean and warming over Indonesia. In the Southern Hemisphere, the SST anomalies are to some extent also related to a persistent AAO pattern, but this relationship is much weaker and appears only during the Southern Hemisphere cold season. On the basis of these results, a mechanism involving the air–sea interaction in the tropics is suggested as a possible link between persistent AO and convective activity in the Indian Ocean and western Pacific.

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