The sea level pressure field can be computed from sea surface winds retrieved from satellite microwave scatterometer measurements, based on variational assimilation in combination with a regularization method given in...The sea level pressure field can be computed from sea surface winds retrieved from satellite microwave scatterometer measurements, based on variational assimilation in combination with a regularization method given in part I of this paper. First, the validity of the new method is proved with a simulation experiment. Then, a new processing procedure for the sea level pressure retrieval is built by combining the geostrophic wind, which is computed from the scatterometer 10-meter wind using the University of Washington planetary boundary layer model using this method. Finally, the feasibility of the method is proved using an actual case study.展开更多
A new method of constructing a sea level pressure field from satellite microwave scatterometer measurements is presented. It is based on variational assimilation in combination with a regularization method using geost...A new method of constructing a sea level pressure field from satellite microwave scatterometer measurements is presented. It is based on variational assimilation in combination with a regularization method using geostrophic vorticity to construct a sea level pressure field from scatterometer data that are given in this paper, which offers a new idea for the application of scatterometer measurements. Firstly, the geostrophic vorticity from the scatterometer data is computed to construct the observation field, and the vorticity field in an area and the sea level pressure on the borders are assimilated. Secondly, the gradient of sea level pressure (semi-norm) is used as the stable functional to educe the adjoint system, the adjoint boundary condition and the gradient of the cost functional in which a weight parameter is introduced for the harmony of the system and the Tikhonov regularization techniques in inverse problem are used to overcome the ill-posedness of the assimilation. Finally, the iteration method of the sea level pressure field is developed.展开更多
A comparison of sea level pressure(SLP)trends in a subset of seven Coupled Model Intercomparison Project(CMIP)phase 5 general circulation models(GCM),namely decadal simulations with CCSM4,CanCM4,MPI-ESM-LR,FGOALS-g2,M...A comparison of sea level pressure(SLP)trends in a subset of seven Coupled Model Intercomparison Project(CMIP)phase 5 general circulation models(GCM),namely decadal simulations with CCSM4,CanCM4,MPI-ESM-LR,FGOALS-g2,MIROC4h,MIROC5,and MRICGCM3,to their CMIP3 counterparts reveals an unrealistically strong forecast skill in CMIP3 models for trend predictions for 2001e2011 when using the 1979e2000 period to train the forecast.Boreal-winter SLP trends over five high-,mid-,and low-latitude zones were calculated over the 1979e2000 initialization period for each ensemble member and then ranked based on their performance relative to HadSLP2 observations.The same method is used to rank the ensemble members during the 2001e2011 period.In CMIP3,17 out of 38 ensemble members retain their rank in the 2001e2011 hindcast period and 3 retain the neighboring rank.However,numbers are much lower in more recent CMIP5 decadal predictions over the similar 2001e2010 period when using the 1981e2000 period as initialization with the same number of ensembles.Different periods were used for CMIP3 and CMIP5 because although the 1979e2000 initialization is widely used for CMIP3,CMIP5 decadal predictions are only available for 30-year periods.The conclusion to consider the forecast skill in CMIP3 predictions during 2001e2011 as unrealistic is corroborated by comparisons to earlier periods from the 1960s to the 1980s in both CMIP3 and CMIP5 simulations.Thus,although the 2001e2011 CMIP3 predictions show statistically significant forecast skill,this skill should be treated as a spurious result that is unlikely to be reproduced by newer more accurate GCMs.展开更多
This study investigates the impact of uncertainty in initial conditions on 24-h sea-level pressure predictions near 0509 Typhoon Matsa by using conditional nonlinear optimal perturbation (CNOP).The CNOP is calculated ...This study investigates the impact of uncertainty in initial conditions on 24-h sea-level pressure predictions near 0509 Typhoon Matsa by using conditional nonlinear optimal perturbation (CNOP).The CNOP is calculated by using a newly proposed fast algorithm.The model used is the Global/Regional Assimilation and PrEdiction System (GRAPES).The sensitivity of the 24-h predictions is studied in terms of horizontal and vertical ranges and also in terms of different initial state variables.To study the sensitivity of 24-h sea-level pressure predictions to different initial state variables,four functions are given as metrics to find the sensitive initial locations.The results show that the main prediction errors come from initial uncertainty on the levels below 200 hPa and at the region south of about 37.6°N,with more sensitivity to initial winds than to other initial state variables.展开更多
This study examines the inter-annual variability of rainfall and Mean Sea Level Pressure (</span><span style="font-family:Verdana;">M</span><span style="font-family:Verdana;"&g...This study examines the inter-annual variability of rainfall and Mean Sea Level Pressure (</span><span style="font-family:Verdana;">M</span><span style="font-family:Verdana;">SLP) over west Africa based on analysis of the Global Precipitation</span><span style="font-family:""><span style="font-family:Verdana;"> 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</span><span style="white-space:nowrap;font-family:Verdana;">°</span><span style="font-family:Verdana;">N</span></span><span style="font-family:""> </span><span style="font-family:Verdana;">-</span><span style="font-family:""> </span><span style="font-family:""><span style="font-family:Verdana;">17</span><span style="white-space:nowrap;font-family:Verdana;">°</span><span style="font-family:Verdana;">N;17</span><span style="white-space:nowrap;font-family:Verdana;">°</span><span style="font-family:Verdana;">W</span></span><span style="font-family:""> </span><span style="font-family:Verdana;">-</span><span style="font-family:""> </span><span style="font-family:""><span style="font-family:Verdana;">13</span><span style="white-space:nowrap;font-family:Verdana;">°</span><span style="font-family:Verdana;"></span><span style="font-family:Verdana;">W) the SLP to the north is strong;the wind converges at 200</span></span><span style="font-family:""> </span><span style="font-family:Verdana;">hPa corresponding to the position of the African Easterly Jet (AEJ) the rotational wind 700</span><span style="font-family:""> </span><span style="font-family:""><span style="font-family:Verdana;">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</span><span style="white-space:nowrap;font-family:Verdana;">°</span><span style="font-family:Verdana;">N</span></span><span style="font-family:""> </span><span style="font-family:Verdana;">-</span><span style="font-family:""> </span><span style="font-family:""><span style="font-family:Verdana;">40</span><span style="white-space:nowrap;font-family:Verdana;">°</span><span style="font-family:Verdana;">N and 50</span><span style="white-space:nowrap;font-family:Verdana;">°</span><span style="font-family:Verdana;">W</span></span><span style="font-family:""> </span><span style="font-family:Verdana;">-</span><span style="font-family:""> </span><span style="font-family:""><span style="font-family:Verdana;">25</span><span style="white-space:nowrap;font-family:Verdana;">°</span><span style="font-family:Verdana;">W) and south (40</span><span style="white-space:nowrap;font-family:Verdana;">°</span><span style="font-family:Verdana;">S</span></span><span style="font-family:""> </span><span style="font-family:Verdana;">-</span><span style="font-family:""> </span><span style="font-family:""><span style="font-family:Verdana;">10</span><span style="white-space:nowrap;font-family:Verdana;">°</span><span style="font-family:Verdana;">S and 40</span><span style="white-space:nowrap;font-family:Verdana;">°</span><span style="font-family:Verdana;">W</span></span><span style="font-family:""> </span><span style="font-family:Verdana;">-</span><span style="font-family:""> </span><span style="font-family:""><span style="font-family:Verdana;">0</span><span style="white-space:nowrap;font-family:Verdana;">°</span><span style="font-family:Verdana;">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.展开更多
Based on the analysis of sea level, air temperature, sea surface temperature(SST), air pressure and wind data during 1980-2013, the causes of seasonal sea level anomalies in the coastal region of the East China Sea...Based on the analysis of sea level, air temperature, sea surface temperature(SST), air pressure and wind data during 1980-2013, the causes of seasonal sea level anomalies in the coastal region of the East China Sea(ECS) are investigated. The research results show:(1) sea level along the coastal region of the ECS takes on strong seasonal variation. The annual range is 30-45 cm, larger in the north than in the south. From north to south, the phase of sea level changes from 140° to 231°, with a difference of nearly 3 months.(2) Monthly mean sea level(MSL)anomalies often occur from August to next February along the coast region of the ECS. The number of sea level anomalies is at most from January to February and from August to October, showing a growing trend in recent years.(3) Anomalous wind field is an important factor to affect the sea level variation in the coastal region of the ECS. Monthly MSL anomaly is closely related to wind field anomaly and air pressure field anomaly. Wind-driven current is essentially consistent with sea surface height. In August 2012, the sea surface heights at the coastal stations driven by wind field have contributed 50%-80% of MSL anomalies.(4) The annual variations for sea level,SST and air temperature along the coastal region of the ECS are mainly caused by solar radiation with a period of12 months. But the correlation coefficients of sea level anomalies with SST anomalies and air temperature anomalies are all less than 0.1.(5) Seasonal sea level variations contain the long-term trends and all kinds of periodic changes. Sea level oscillations vary in different seasons in the coastal region of the ECS. In winter and spring, the oscillation of 4-7 a related to El Ni?o is stronger and its amplitude exceeds 2 cm. In summer and autumn, the oscillations of 2-3 a and quasi 9 a are most significant, and their amplitudes also exceed 2 cm. The height of sea level is lifted up when the different oscillations superposed. On the other hand, the height of sea level is fallen down.展开更多
Based on sea level, air temperature, sea surface temperature(SST), air pressure and wind data during 1980–2014,this paper uses Morlet wavelet transform, Estuarine Coastal Ocean Model(ECOM) and so on to investigat...Based on sea level, air temperature, sea surface temperature(SST), air pressure and wind data during 1980–2014,this paper uses Morlet wavelet transform, Estuarine Coastal Ocean Model(ECOM) and so on to investigate the characteristics and possible causes of seasonal sea level anomalies along the South China Sea(SCS) coast. The research results show that:(1) Seasonal sea level anomalies often occur from January to February and from June to October. The frequency of sea level anomalies is the most in August, showing a growing trend in recent years. In addition, the occurring frequency of negative sea level anomaly accounts for 50% of the total abnormal number.(2) The seasonal sea level anomalies are closely related to ENSO events. The negative anomalies always occurred during the El Ni?o events, while the positive anomalies occurred during the La Ni?a(late El Ni?o) events. In addition, the seasonal sea level oscillation periods of 4–7 a associated with ENSO are the strongest in winter, with the amplitude over 2 cm.(3) Abnormal wind is an important factor to affect the seasonal sea level anomalies in the coastal region of the SCS. Wind-driven sea level height(SSH) is basically consistent with the seasonal sea level anomalies. Moreover, the influence of the tropical cyclone in the coastal region of the SCS is concentrated in summer and autumn, contributing to the seasonal sea level anomalies.(4) Seasonal variations of sea level, SST and air temperature are basically consistent along the coast of the SCS, but the seasonal sea level anomalies have no much correlation with the SST and air temperature.展开更多
Every region around the globe has its unique climatic conditions which are set based on different orographic constant and atmospheric dynamic features. These features posses’ variability on different time scales. Det...Every region around the globe has its unique climatic conditions which are set based on different orographic constant and atmospheric dynamic features. These features posses’ variability on different time scales. Determining the local sea level change based on terrestrial non-tidal, short-term variability is complicated. Some internal mechanisms of ocean are also taking place along with the external physical ones. We show that variability at Sindh-Baluchistan coastal belt can be greatly explained via dimensional indices of the position and intensity of the atmospheric center of action (COAs). This technique has already proved its usefulness at number of location especially in Northern Atlantic. It takes into account the changes in the atmospheric pressure which is exerted on the sea surface influencing the variability in sea level on seasonal scale and on inter-annual basis. As warming causes thermal expansion of water it also causes changes in atmospheric circulation. Both of these processes affect the sea level variability on their respective time scales. Atmospheric being the quicker one of the two to pass on the effect is also more influential to explain the variability in local sea level. In this attempt the COA approach is used to assess the impact of low pressure on local sea levels.展开更多
Extratropical cyclones are critical weather systems that affect large-scale weather and climate changes at mid-high latitudes.However,prior research shows that there are still great difficulties in predicting extratro...Extratropical cyclones are critical weather systems that affect large-scale weather and climate changes at mid-high latitudes.However,prior research shows that there are still great difficulties in predicting extratropical cyclones for occurrence,frequency,and position.In this study,mean sea level pressure(MSLP)data from the European Centre for Medium-Range Weather Forecasts(ECMWF)reanalysis(ERA5)are used to calculate the variance statistics of the MSLP to reveal extratropical cyclone activity(ECA).Based on the analysis of the change characteristics of ECA in the Northern Hemisphere,the intrinsic link between ECA in the Northern Hemisphere and Arctic sea ice is explored.The results show that the maximum ECA mainly occurs in winter over the mid-high latitudes in the Northern Hemisphere.The maximum ECA changes in the North Pacific and the North Atlantic,which are the largest variations in the Northern Hemisphere,are independent of each other,and their mechanisms may be different.Furthermore,MSLP is a significant physical variable that affects ECA.The North Atlantic Oscillation(NAO)and North Pacific Index(NPI)are significant indices that impact ECA in the North Atlantic and North Pacific,respectively.The innovation of this paper is to explore the relationship between the activity of extratropical cyclones in the Northern Hemisphere and the abnormal changes in Arctic sea ice for the first time.The mechanism is that the abnormal changes in summer-autumn and winter Arctic sea ice lead to the phase transition of the NPI and NAO,respectively,and then cause the occurrence of ECA in the North Pacific and North Atlantic,respectively.Arctic sea ice plays a crucial role in the ECA in the Northern Hemisphere by influencing the polar vortex and westerly jets.This is the first exploration of ECAs in the Northern Hemisphere using Arctic sea ice,which can provide some references for the in-depth study and prediction of ECAs in the Northern Hemisphere.展开更多
In the present study, the authors investigated the relationship between the Arctic Oscillation (AO) and the high-frequency variability of daily sea level pressures in the Northern Hemisphere in winter (November throug...In the present study, the authors investigated the relationship between the Arctic Oscillation (AO) and the high-frequency variability of daily sea level pressures in the Northern Hemisphere in winter (November through March), using NCEP/NCAR reanalysis datasets for the time period of 1948/49-2000/01. High-frequency signals are defined as those with timescales shorter than three weeks and measured in terms of variance, for each winter for each grid. The correlations between monthly mean AO index and high-frequency variance are conducted. A predominant feature is that several regional centers with high correlation show up in the middle to high latitudes. Significant areas include mid- to high-latitude Asia centered at Siberia, northern Europe and the middle-latitude North Atlantic east of northern Africa. Their strong correlations can also be confirmed by the singular value decomposition analysis of covariance between mean SLP and high-frequency variance. This indicates that the relationship of AO with daily Sea Level Pressure (SLP) is confined to some specific regions in association with the inherent atmospheric dynamics. In middle-latitude Asia, there is a significant (at the 95% level) trend of variance of-2.26% (10 yr)-1. Another region that displays a strong trend is the northwestern Pacific with a significant rate of change of 0.80% (10 yr)-1. If the winter of 1948/49, an apparent outlier, is excluded, a steady linear trend of +1.51% (10 yr)-1 shows up in northern Europe. The variance probability density functions (PDFs) are found to change in association with different AO phases. The changes corresponding to high and low AO phases, however, are asymmetric in these regions. Some regions such as northern Europe display much stronger changes in high AO years, whereas some other regions such as Siberia show a stronger connection to low AO conditions. These features are supported by ECMWF reanalysis data. However, the dynamical mechanisms involved in the AO-high frequency SLP variance connection have not been well understood, and this needs further study.展开更多
The interannual and interdecadal varinbility of the Siberian High (SH) and the Aleutian Low (AL) from aspects of strength and location for the past one hundred years as well as their possible relations with temperatur...The interannual and interdecadal varinbility of the Siberian High (SH) and the Aleutian Low (AL) from aspects of strength and location for the past one hundred years as well as their possible relations with temperature changes over China's Mainland are investigated. The data sets used are the historical sea level pressure for 1871-1995 and surface air temperature (SAT) over China in the last 100 years. The results show that the SAT in different regions over China, central strength of the SH and the AL, the south-reaching latitude of the 1030 hPa contour of the SH and the pressure gradient between the SH and the AL experienced two obvious changes during this period. One occurred in the 1920s, with a more prominent one in the 1980s. These variations are closely linked with the change of winter temperature over China in the interdecadal timescale. In the last 50 years, there is a remarkable interannual correlation between the strength of Active Centers of Atmosphere (Acas) and the winter temperature of northern and eastern regions in China. The abrupt change of Acas in the 1980s is consistent with the rising of the SAT in China. Since the late 1980s, the atmospheric circulation is experiencing a remarkable modulation, which may cause the interdecadal transition of warming trend.展开更多
The spatial variation of sea surface temperature anomalies(SSTA) in the North Pacific Ocean during winter is investigated using the EOF decomposition method.The first two main modes of SSTA are associated with Pacific...The spatial variation of sea surface temperature anomalies(SSTA) in the North Pacific Ocean during winter is investigated using the EOF decomposition method.The first two main modes of SSTA are associated with Pacific Decadal Oscillation(PDO) mode and North Pacific Gyre Oscillation(NPGO) mode,respectively.Moreover,the first mode(PDO) is switched to the second mode(NPGO),a dominant mode after mid-1980.The mechanism of the modes' transition is analyzed.As the two oceanic modes are forced by the Aleutian Low(AL) and North Pacific Oscillation(NPO) modes,the AR-1 model is further used to examine the possible effect and mechanism of AL and NPO in generating the PDO and NPGO.The results show that compared to the NPO,the AL plays a more important role in generating the NPGO mode since the 1970s.Likewise,both the AL and NPO affect the PDO mode since the 1980s.展开更多
The paper is to depict the major structures of the Northern Hemispheric summer sealevel pressure (SLP), 500 hPa height (H 500) and 500 hPa ridge-and-trough (RAT) field during1951-1980. The 1960s’ jump was found in th...The paper is to depict the major structures of the Northern Hemispheric summer sealevel pressure (SLP), 500 hPa height (H 500) and 500 hPa ridge-and-trough (RAT) field during1951-1980. The 1960s’ jump was found in the major signal of each field as well as inthe series of many circulation parameters. The major part of the H 500 change was the heightlowering over the most of the Hemisphere during the 1960s, corresponding well to the sur-face temperature change. The SLP and RAT changed in a way similar to that of the rainfallchange, with regard to the southwest-to-northeast zonal structure in the geographical distri-butions of the major signals of all the three fields. The relationship between the changes ofsome circulation parameters and the regional rainfall is discussed.展开更多
An EOF analysis was performed to investigate the variations of sea surface temperature (SST) of Pacific and Indian Oceans.Result shows that the distribution of SST anomaly exhibits a distinct anticorrelation pattern b...An EOF analysis was performed to investigate the variations of sea surface temperature (SST) of Pacific and Indian Oceans.Result shows that the distribution of SST anomaly exhibits a distinct anticorrelation pattern between Northwest and Southeast Pacific,as well as between Northwest Pacific and the Arabian Sea.It also shows that the sea level pressure (SLP) anomaly between North Pacific and North Indian Oceans is of a seesaw pattern,which we named the North Paci- fic and North Indian Ocean Oscillation (PIO).Such a phenomenon is closely correlated with the cold summer in East Asia.展开更多
Atmospheric reanalysis data are an important data source for studying weather and climate systems.The sea surface wind and sea level pressure observations measured from a real-time buoy system deployed in Kenya’s off...Atmospheric reanalysis data are an important data source for studying weather and climate systems.The sea surface wind and sea level pressure observations measured from a real-time buoy system deployed in Kenya’s offshore area in 2019 conducted jointly by Chinese and Kenyan scientists were used to evaluate the performance of the major high-frequency atmospheric reanalysis products in the western Indian Ocean region.Compared with observations,the sea level pressure field could be accurately simulated using the atmospheric reanalysis data.However,significant discrepancies existed between the surface wind reanalysis data,especially between meridional wind and the observational data.Most of the data provide a complete understanding of sea level pressure,except for the Japanese 55-year Reanalysis data,which hold a significant system bias.The Modern-Era Reanalysis for Research and Applications,Version-2,provides an improved description of all datasets.All the reanalysis datasets for zonal wind underestimate the strength during the study period.Among reanalysis data,NCEP-DOE Atmospheric Model Intercomparison Project reanalysis data presents an inaccurate description due to the worst correlation with the observations.For meridional wind,most reanalysis datasets underestimate the variance,while the European Centre for Medium-Range Weather Forecasts Atmospheric Composition Reanalysis 4 has a larger variance than the observations.In addition to the original data comparison,the diurnal variability of sea level pressure and surface wind are also assessed,and the result indicates that the diurnal variations have a significant gap between observation and reanalysis data.This study indicates that the current high-frequency reanalysis data still have disadvantages when describing the atmospheric parameters in the Western Indian Ocean region.展开更多
The throughflow in the Canadian Arctic Archipelago(CAA)had a significant impact on the North Atlantic Ocean with the Arctic climate change.The findings of physical mechanisms driving the throughflow in the CAA differe...The throughflow in the Canadian Arctic Archipelago(CAA)had a significant impact on the North Atlantic Ocean with the Arctic climate change.The findings of physical mechanisms driving the throughflow in the CAA differed and few studies about the impact of sea level pressure(SLP)on the CAA throughflow were made.A high-resolution ice-ocean coupled Arctic Ocean Finite-Volume Community Ocean Model(AO-FVCOM)was used over the period 1978-2016 to examine the interannual and seasonal variability of the outflows in the CAA and the mechanism of SLP in driving the variation of the CAA throughflow quantitively.The simulated volume transport through Davis Strait,Nares Strait,Lancaster Sound and Jones Sound showed consistent increasing trends over 1978-2016 and the larger flux in winter and spring than in summer and fall.The variation of volume transport through Nares Strait contributed more than Lancaster and Jones Sound to the variation through Davis Strait.Five process-oriented experiments were made to further explore the role of SLP in setting up and controlling the sea surface height(SSH)difference and thus the throughflow transport in the CAA.The SLP was a primary forcing to control the SSH difference and the outflow transport compared with the wind forcing.The memory of the SSH to the SLP was short and an equilibrium state could be reached if the SLP varied with time.The upstream and downstream SLP difference,however,made a slight direct contribution to driving the volume transport of the CAA throughflow.In addition to the external forcing of SLP and wind,the variability of the CAA outflow was also influenced by the variability of the inflow/outflow and SSH on boundaries connected to the Pacific and Atlantic Oceans.The choice of SLP datasets from CORE-v2,ECMWF and NCEP was sensitive to the simulated uncertainty of volume transport.展开更多
This study aims to examine the atmospheric conditions characterising fog phenomena on the Senegalese coast focusing on two specific instances that occurred on April 3 and April 30,2023.These events were detected by th...This study aims to examine the atmospheric conditions characterising fog phenomena on the Senegalese coast focusing on two specific instances that occurred on April 3 and April 30,2023.These events were detected by the LIDAR Ceilometer installed at LPAOSF/ESP/UCAD and confirmed on the METARs of the meteorological stations at Dakar and Diass airports.The LIDAR’s backscatter signal showed that the fog of April 3 started around midnight with a vertical extension at 100 m altitude and dissipated around 10 a.m.The April 30 event characterized by a good vertical extension from the surface up to 300 m above sea level,was triggered just after 2 a.m.and lasted around 3 hours.The results showed that a decrease in temperature,accompanied by an increase in humidity and light wind,is favorable for the triggering and persistence of fog.Sea Level Pressure(SLP)anomaly fields show two distinct configurations.The April 3 event was characterized by a zonal dipole of SLP anomalies between the Sahara and the northern Senegalese coast,while the April 30 event was characterized by a meridional dipole between the Sahara and the Gulf of Guinea area as far as the equatorial Atlantic.A weakening of the pressure around the study area was observed in both cases,allowing moisture advection to favor the onset of fog.The hovmoller diagrams of relative humidity and wind show that a good vertical extension of humidity associated with a westerly wind in the lower layers plays an important role in the formation and persistence of fog.The presence of dry air associated with a weak easterly wind in the middle layers could explain the low vertical extension of the fog on April 3.A strong wind in the lower layers would be responsible for the premature dissipation of the April 30 fog.展开更多
基金Project supported by the National Natural Science Foundation of China (Grant No. 41175025)
文摘The sea level pressure field can be computed from sea surface winds retrieved from satellite microwave scatterometer measurements, based on variational assimilation in combination with a regularization method given in part I of this paper. First, the validity of the new method is proved with a simulation experiment. Then, a new processing procedure for the sea level pressure retrieval is built by combining the geostrophic wind, which is computed from the scatterometer 10-meter wind using the University of Washington planetary boundary layer model using this method. Finally, the feasibility of the method is proved using an actual case study.
基金supported by the National Natural Science Foundation of China(Grant No.41175025)
文摘A new method of constructing a sea level pressure field from satellite microwave scatterometer measurements is presented. It is based on variational assimilation in combination with a regularization method using geostrophic vorticity to construct a sea level pressure field from scatterometer data that are given in this paper, which offers a new idea for the application of scatterometer measurements. Firstly, the geostrophic vorticity from the scatterometer data is computed to construct the observation field, and the vorticity field in an area and the sea level pressure on the borders are assimilated. Secondly, the gradient of sea level pressure (semi-norm) is used as the stable functional to educe the adjoint system, the adjoint boundary condition and the gradient of the cost functional in which a weight parameter is introduced for the harmony of the system and the Tikhonov regularization techniques in inverse problem are used to overcome the ill-posedness of the assimilation. Finally, the iteration method of the sea level pressure field is developed.
基金Support for this study was provided by the U.S.National Science Foundation(1029711),the U.S.National Aeronautics and Space Administration(14-CMAC14-0010),and the George R.and Orpha Gibson Foundation at the University of Minnesota.
文摘A comparison of sea level pressure(SLP)trends in a subset of seven Coupled Model Intercomparison Project(CMIP)phase 5 general circulation models(GCM),namely decadal simulations with CCSM4,CanCM4,MPI-ESM-LR,FGOALS-g2,MIROC4h,MIROC5,and MRICGCM3,to their CMIP3 counterparts reveals an unrealistically strong forecast skill in CMIP3 models for trend predictions for 2001e2011 when using the 1979e2000 period to train the forecast.Boreal-winter SLP trends over five high-,mid-,and low-latitude zones were calculated over the 1979e2000 initialization period for each ensemble member and then ranked based on their performance relative to HadSLP2 observations.The same method is used to rank the ensemble members during the 2001e2011 period.In CMIP3,17 out of 38 ensemble members retain their rank in the 2001e2011 hindcast period and 3 retain the neighboring rank.However,numbers are much lower in more recent CMIP5 decadal predictions over the similar 2001e2010 period when using the 1981e2000 period as initialization with the same number of ensembles.Different periods were used for CMIP3 and CMIP5 because although the 1979e2000 initialization is widely used for CMIP3,CMIP5 decadal predictions are only available for 30-year periods.The conclusion to consider the forecast skill in CMIP3 predictions during 2001e2011 as unrealistic is corroborated by comparisons to earlier periods from the 1960s to the 1980s in both CMIP3 and CMIP5 simulations.Thus,although the 2001e2011 CMIP3 predictions show statistically significant forecast skill,this skill should be treated as a spurious result that is unlikely to be reproduced by newer more accurate GCMs.
基金jointly supported by the National Basic Research Program of China (973 Program,Grant No.2005CB321703)the Science Fund for Creative Research Groups of the National Natural Science Foundation of China (Grant No.40821092)
文摘This study investigates the impact of uncertainty in initial conditions on 24-h sea-level pressure predictions near 0509 Typhoon Matsa by using conditional nonlinear optimal perturbation (CNOP).The CNOP is calculated by using a newly proposed fast algorithm.The model used is the Global/Regional Assimilation and PrEdiction System (GRAPES).The sensitivity of the 24-h predictions is studied in terms of horizontal and vertical ranges and also in terms of different initial state variables.To study the sensitivity of 24-h sea-level pressure predictions to different initial state variables,four functions are given as metrics to find the sensitive initial locations.The results show that the main prediction errors come from initial uncertainty on the levels below 200 hPa and at the region south of about 37.6°N,with more sensitivity to initial winds than to other initial state variables.
文摘This study examines the inter-annual variability of rainfall and Mean Sea Level Pressure (</span><span style="font-family:Verdana;">M</span><span style="font-family:Verdana;">SLP) over west Africa based on analysis of the Global Precipitation</span><span style="font-family:""><span style="font-family:Verdana;"> 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</span><span style="white-space:nowrap;font-family:Verdana;">°</span><span style="font-family:Verdana;">N</span></span><span style="font-family:""> </span><span style="font-family:Verdana;">-</span><span style="font-family:""> </span><span style="font-family:""><span style="font-family:Verdana;">17</span><span style="white-space:nowrap;font-family:Verdana;">°</span><span style="font-family:Verdana;">N;17</span><span style="white-space:nowrap;font-family:Verdana;">°</span><span style="font-family:Verdana;">W</span></span><span style="font-family:""> </span><span style="font-family:Verdana;">-</span><span style="font-family:""> </span><span style="font-family:""><span style="font-family:Verdana;">13</span><span style="white-space:nowrap;font-family:Verdana;">°</span><span style="font-family:Verdana;"></span><span style="font-family:Verdana;">W) the SLP to the north is strong;the wind converges at 200</span></span><span style="font-family:""> </span><span style="font-family:Verdana;">hPa corresponding to the position of the African Easterly Jet (AEJ) the rotational wind 700</span><span style="font-family:""> </span><span style="font-family:""><span style="font-family:Verdana;">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</span><span style="white-space:nowrap;font-family:Verdana;">°</span><span style="font-family:Verdana;">N</span></span><span style="font-family:""> </span><span style="font-family:Verdana;">-</span><span style="font-family:""> </span><span style="font-family:""><span style="font-family:Verdana;">40</span><span style="white-space:nowrap;font-family:Verdana;">°</span><span style="font-family:Verdana;">N and 50</span><span style="white-space:nowrap;font-family:Verdana;">°</span><span style="font-family:Verdana;">W</span></span><span style="font-family:""> </span><span style="font-family:Verdana;">-</span><span style="font-family:""> </span><span style="font-family:""><span style="font-family:Verdana;">25</span><span style="white-space:nowrap;font-family:Verdana;">°</span><span style="font-family:Verdana;">W) and south (40</span><span style="white-space:nowrap;font-family:Verdana;">°</span><span style="font-family:Verdana;">S</span></span><span style="font-family:""> </span><span style="font-family:Verdana;">-</span><span style="font-family:""> </span><span style="font-family:""><span style="font-family:Verdana;">10</span><span style="white-space:nowrap;font-family:Verdana;">°</span><span style="font-family:Verdana;">S and 40</span><span style="white-space:nowrap;font-family:Verdana;">°</span><span style="font-family:Verdana;">W</span></span><span style="font-family:""> </span><span style="font-family:Verdana;">-</span><span style="font-family:""> </span><span style="font-family:""><span style="font-family:Verdana;">0</span><span style="white-space:nowrap;font-family:Verdana;">°</span><span style="font-family:Verdana;">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.
基金The Project of Global Change and Air-Sea Interaction under Contract No.GASI-03-01-01-09
文摘Based on the analysis of sea level, air temperature, sea surface temperature(SST), air pressure and wind data during 1980-2013, the causes of seasonal sea level anomalies in the coastal region of the East China Sea(ECS) are investigated. The research results show:(1) sea level along the coastal region of the ECS takes on strong seasonal variation. The annual range is 30-45 cm, larger in the north than in the south. From north to south, the phase of sea level changes from 140° to 231°, with a difference of nearly 3 months.(2) Monthly mean sea level(MSL)anomalies often occur from August to next February along the coast region of the ECS. The number of sea level anomalies is at most from January to February and from August to October, showing a growing trend in recent years.(3) Anomalous wind field is an important factor to affect the sea level variation in the coastal region of the ECS. Monthly MSL anomaly is closely related to wind field anomaly and air pressure field anomaly. Wind-driven current is essentially consistent with sea surface height. In August 2012, the sea surface heights at the coastal stations driven by wind field have contributed 50%-80% of MSL anomalies.(4) The annual variations for sea level,SST and air temperature along the coastal region of the ECS are mainly caused by solar radiation with a period of12 months. But the correlation coefficients of sea level anomalies with SST anomalies and air temperature anomalies are all less than 0.1.(5) Seasonal sea level variations contain the long-term trends and all kinds of periodic changes. Sea level oscillations vary in different seasons in the coastal region of the ECS. In winter and spring, the oscillation of 4-7 a related to El Ni?o is stronger and its amplitude exceeds 2 cm. In summer and autumn, the oscillations of 2-3 a and quasi 9 a are most significant, and their amplitudes also exceed 2 cm. The height of sea level is lifted up when the different oscillations superposed. On the other hand, the height of sea level is fallen down.
基金The National Key Research and Development Program of China under contract No.2016YFC1402610
文摘Based on sea level, air temperature, sea surface temperature(SST), air pressure and wind data during 1980–2014,this paper uses Morlet wavelet transform, Estuarine Coastal Ocean Model(ECOM) and so on to investigate the characteristics and possible causes of seasonal sea level anomalies along the South China Sea(SCS) coast. The research results show that:(1) Seasonal sea level anomalies often occur from January to February and from June to October. The frequency of sea level anomalies is the most in August, showing a growing trend in recent years. In addition, the occurring frequency of negative sea level anomaly accounts for 50% of the total abnormal number.(2) The seasonal sea level anomalies are closely related to ENSO events. The negative anomalies always occurred during the El Ni?o events, while the positive anomalies occurred during the La Ni?a(late El Ni?o) events. In addition, the seasonal sea level oscillation periods of 4–7 a associated with ENSO are the strongest in winter, with the amplitude over 2 cm.(3) Abnormal wind is an important factor to affect the seasonal sea level anomalies in the coastal region of the SCS. Wind-driven sea level height(SSH) is basically consistent with the seasonal sea level anomalies. Moreover, the influence of the tropical cyclone in the coastal region of the SCS is concentrated in summer and autumn, contributing to the seasonal sea level anomalies.(4) Seasonal variations of sea level, SST and air temperature are basically consistent along the coast of the SCS, but the seasonal sea level anomalies have no much correlation with the SST and air temperature.
文摘Every region around the globe has its unique climatic conditions which are set based on different orographic constant and atmospheric dynamic features. These features posses’ variability on different time scales. Determining the local sea level change based on terrestrial non-tidal, short-term variability is complicated. Some internal mechanisms of ocean are also taking place along with the external physical ones. We show that variability at Sindh-Baluchistan coastal belt can be greatly explained via dimensional indices of the position and intensity of the atmospheric center of action (COAs). This technique has already proved its usefulness at number of location especially in Northern Atlantic. It takes into account the changes in the atmospheric pressure which is exerted on the sea surface influencing the variability in sea level on seasonal scale and on inter-annual basis. As warming causes thermal expansion of water it also causes changes in atmospheric circulation. Both of these processes affect the sea level variability on their respective time scales. Atmospheric being the quicker one of the two to pass on the effect is also more influential to explain the variability in local sea level. In this attempt the COA approach is used to assess the impact of low pressure on local sea levels.
基金The National Key Research and Development Program of China under contract No.2022YFF0802002.
文摘Extratropical cyclones are critical weather systems that affect large-scale weather and climate changes at mid-high latitudes.However,prior research shows that there are still great difficulties in predicting extratropical cyclones for occurrence,frequency,and position.In this study,mean sea level pressure(MSLP)data from the European Centre for Medium-Range Weather Forecasts(ECMWF)reanalysis(ERA5)are used to calculate the variance statistics of the MSLP to reveal extratropical cyclone activity(ECA).Based on the analysis of the change characteristics of ECA in the Northern Hemisphere,the intrinsic link between ECA in the Northern Hemisphere and Arctic sea ice is explored.The results show that the maximum ECA mainly occurs in winter over the mid-high latitudes in the Northern Hemisphere.The maximum ECA changes in the North Pacific and the North Atlantic,which are the largest variations in the Northern Hemisphere,are independent of each other,and their mechanisms may be different.Furthermore,MSLP is a significant physical variable that affects ECA.The North Atlantic Oscillation(NAO)and North Pacific Index(NPI)are significant indices that impact ECA in the North Atlantic and North Pacific,respectively.The innovation of this paper is to explore the relationship between the activity of extratropical cyclones in the Northern Hemisphere and the abnormal changes in Arctic sea ice for the first time.The mechanism is that the abnormal changes in summer-autumn and winter Arctic sea ice lead to the phase transition of the NPI and NAO,respectively,and then cause the occurrence of ECA in the North Pacific and North Atlantic,respectively.Arctic sea ice plays a crucial role in the ECA in the Northern Hemisphere by influencing the polar vortex and westerly jets.This is the first exploration of ECAs in the Northern Hemisphere using Arctic sea ice,which can provide some references for the in-depth study and prediction of ECAs in the Northern Hemisphere.
文摘In the present study, the authors investigated the relationship between the Arctic Oscillation (AO) and the high-frequency variability of daily sea level pressures in the Northern Hemisphere in winter (November through March), using NCEP/NCAR reanalysis datasets for the time period of 1948/49-2000/01. High-frequency signals are defined as those with timescales shorter than three weeks and measured in terms of variance, for each winter for each grid. The correlations between monthly mean AO index and high-frequency variance are conducted. A predominant feature is that several regional centers with high correlation show up in the middle to high latitudes. Significant areas include mid- to high-latitude Asia centered at Siberia, northern Europe and the middle-latitude North Atlantic east of northern Africa. Their strong correlations can also be confirmed by the singular value decomposition analysis of covariance between mean SLP and high-frequency variance. This indicates that the relationship of AO with daily Sea Level Pressure (SLP) is confined to some specific regions in association with the inherent atmospheric dynamics. In middle-latitude Asia, there is a significant (at the 95% level) trend of variance of-2.26% (10 yr)-1. Another region that displays a strong trend is the northwestern Pacific with a significant rate of change of 0.80% (10 yr)-1. If the winter of 1948/49, an apparent outlier, is excluded, a steady linear trend of +1.51% (10 yr)-1 shows up in northern Europe. The variance probability density functions (PDFs) are found to change in association with different AO phases. The changes corresponding to high and low AO phases, however, are asymmetric in these regions. Some regions such as northern Europe display much stronger changes in high AO years, whereas some other regions such as Siberia show a stronger connection to low AO conditions. These features are supported by ECMWF reanalysis data. However, the dynamical mechanisms involved in the AO-high frequency SLP variance connection have not been well understood, and this needs further study.
基金the National Key Program for Developing Basic Sciences in China(No.G 1999043405) NSFC 49975023.
文摘The interannual and interdecadal varinbility of the Siberian High (SH) and the Aleutian Low (AL) from aspects of strength and location for the past one hundred years as well as their possible relations with temperature changes over China's Mainland are investigated. The data sets used are the historical sea level pressure for 1871-1995 and surface air temperature (SAT) over China in the last 100 years. The results show that the SAT in different regions over China, central strength of the SH and the AL, the south-reaching latitude of the 1030 hPa contour of the SH and the pressure gradient between the SH and the AL experienced two obvious changes during this period. One occurred in the 1920s, with a more prominent one in the 1980s. These variations are closely linked with the change of winter temperature over China in the interdecadal timescale. In the last 50 years, there is a remarkable interannual correlation between the strength of Active Centers of Atmosphere (Acas) and the winter temperature of northern and eastern regions in China. The abrupt change of Acas in the 1980s is consistent with the rising of the SAT in China. Since the late 1980s, the atmospheric circulation is experiencing a remarkable modulation, which may cause the interdecadal transition of warming trend.
基金Basic Research Program of National Natural Science Foundation of China (2007CB411800)
文摘The spatial variation of sea surface temperature anomalies(SSTA) in the North Pacific Ocean during winter is investigated using the EOF decomposition method.The first two main modes of SSTA are associated with Pacific Decadal Oscillation(PDO) mode and North Pacific Gyre Oscillation(NPGO) mode,respectively.Moreover,the first mode(PDO) is switched to the second mode(NPGO),a dominant mode after mid-1980.The mechanism of the modes' transition is analyzed.As the two oceanic modes are forced by the Aleutian Low(AL) and North Pacific Oscillation(NPO) modes,the AR-1 model is further used to examine the possible effect and mechanism of AL and NPO in generating the PDO and NPGO.The results show that compared to the NPO,the AL plays a more important role in generating the NPGO mode since the 1970s.Likewise,both the AL and NPO affect the PDO mode since the 1980s.
文摘The paper is to depict the major structures of the Northern Hemispheric summer sealevel pressure (SLP), 500 hPa height (H 500) and 500 hPa ridge-and-trough (RAT) field during1951-1980. The 1960s’ jump was found in the major signal of each field as well as inthe series of many circulation parameters. The major part of the H 500 change was the heightlowering over the most of the Hemisphere during the 1960s, corresponding well to the sur-face temperature change. The SLP and RAT changed in a way similar to that of the rainfallchange, with regard to the southwest-to-northeast zonal structure in the geographical distri-butions of the major signals of all the three fields. The relationship between the changes ofsome circulation parameters and the regional rainfall is discussed.
文摘An EOF analysis was performed to investigate the variations of sea surface temperature (SST) of Pacific and Indian Oceans.Result shows that the distribution of SST anomaly exhibits a distinct anticorrelation pattern between Northwest and Southeast Pacific,as well as between Northwest Pacific and the Arabian Sea.It also shows that the sea level pressure (SLP) anomaly between North Pacific and North Indian Oceans is of a seesaw pattern,which we named the North Paci- fic and North Indian Ocean Oscillation (PIO).Such a phenomenon is closely correlated with the cold summer in East Asia.
基金supported by the Global Change and Air-Sea Interaction Program(No.GASI-04-QYQH-03)the Taishan Scholars Program of Shandong Province(No.tsqn 201909165)+3 种基金the National Natural Science Foundation of China(No.41876028)the Global Change and Air-Sea Interaction Program(No.GASI-01-WIND-STwin)the Shandong Science and Technology Foundation(No.2013GRC 31504)the Marine S&T Fund of Shandong Province for Pilot National Laboratory for Marine Science and Technology(Qingdao)(No.2022QNLM010103-3).
文摘Atmospheric reanalysis data are an important data source for studying weather and climate systems.The sea surface wind and sea level pressure observations measured from a real-time buoy system deployed in Kenya’s offshore area in 2019 conducted jointly by Chinese and Kenyan scientists were used to evaluate the performance of the major high-frequency atmospheric reanalysis products in the western Indian Ocean region.Compared with observations,the sea level pressure field could be accurately simulated using the atmospheric reanalysis data.However,significant discrepancies existed between the surface wind reanalysis data,especially between meridional wind and the observational data.Most of the data provide a complete understanding of sea level pressure,except for the Japanese 55-year Reanalysis data,which hold a significant system bias.The Modern-Era Reanalysis for Research and Applications,Version-2,provides an improved description of all datasets.All the reanalysis datasets for zonal wind underestimate the strength during the study period.Among reanalysis data,NCEP-DOE Atmospheric Model Intercomparison Project reanalysis data presents an inaccurate description due to the worst correlation with the observations.For meridional wind,most reanalysis datasets underestimate the variance,while the European Centre for Medium-Range Weather Forecasts Atmospheric Composition Reanalysis 4 has a larger variance than the observations.In addition to the original data comparison,the diurnal variability of sea level pressure and surface wind are also assessed,and the result indicates that the diurnal variations have a significant gap between observation and reanalysis data.This study indicates that the current high-frequency reanalysis data still have disadvantages when describing the atmospheric parameters in the Western Indian Ocean region.
基金the National Key Research and Development Program of China(2019YFA0607000)the National Natural Science Foundation of China(41706210)for Yu Zhang+3 种基金the U.S.A National Science Foundation(PLR-1603000)for Chang-Sheng Chenthe Innovation Group Project of Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai)(311021009)for Dan-Ya Xuthe National Natural Science Foundation of China(42076238)for Wei-Zeng ShaoShanghai Pujiang Program(19PJ1404300)for Liang Chang.
文摘The throughflow in the Canadian Arctic Archipelago(CAA)had a significant impact on the North Atlantic Ocean with the Arctic climate change.The findings of physical mechanisms driving the throughflow in the CAA differed and few studies about the impact of sea level pressure(SLP)on the CAA throughflow were made.A high-resolution ice-ocean coupled Arctic Ocean Finite-Volume Community Ocean Model(AO-FVCOM)was used over the period 1978-2016 to examine the interannual and seasonal variability of the outflows in the CAA and the mechanism of SLP in driving the variation of the CAA throughflow quantitively.The simulated volume transport through Davis Strait,Nares Strait,Lancaster Sound and Jones Sound showed consistent increasing trends over 1978-2016 and the larger flux in winter and spring than in summer and fall.The variation of volume transport through Nares Strait contributed more than Lancaster and Jones Sound to the variation through Davis Strait.Five process-oriented experiments were made to further explore the role of SLP in setting up and controlling the sea surface height(SSH)difference and thus the throughflow transport in the CAA.The SLP was a primary forcing to control the SSH difference and the outflow transport compared with the wind forcing.The memory of the SSH to the SLP was short and an equilibrium state could be reached if the SLP varied with time.The upstream and downstream SLP difference,however,made a slight direct contribution to driving the volume transport of the CAA throughflow.In addition to the external forcing of SLP and wind,the variability of the CAA outflow was also influenced by the variability of the inflow/outflow and SSH on boundaries connected to the Pacific and Atlantic Oceans.The choice of SLP datasets from CORE-v2,ECMWF and NCEP was sensitive to the simulated uncertainty of volume transport.
文摘This study aims to examine the atmospheric conditions characterising fog phenomena on the Senegalese coast focusing on two specific instances that occurred on April 3 and April 30,2023.These events were detected by the LIDAR Ceilometer installed at LPAOSF/ESP/UCAD and confirmed on the METARs of the meteorological stations at Dakar and Diass airports.The LIDAR’s backscatter signal showed that the fog of April 3 started around midnight with a vertical extension at 100 m altitude and dissipated around 10 a.m.The April 30 event characterized by a good vertical extension from the surface up to 300 m above sea level,was triggered just after 2 a.m.and lasted around 3 hours.The results showed that a decrease in temperature,accompanied by an increase in humidity and light wind,is favorable for the triggering and persistence of fog.Sea Level Pressure(SLP)anomaly fields show two distinct configurations.The April 3 event was characterized by a zonal dipole of SLP anomalies between the Sahara and the northern Senegalese coast,while the April 30 event was characterized by a meridional dipole between the Sahara and the Gulf of Guinea area as far as the equatorial Atlantic.A weakening of the pressure around the study area was observed in both cases,allowing moisture advection to favor the onset of fog.The hovmoller diagrams of relative humidity and wind show that a good vertical extension of humidity associated with a westerly wind in the lower layers plays an important role in the formation and persistence of fog.The presence of dry air associated with a weak easterly wind in the middle layers could explain the low vertical extension of the fog on April 3.A strong wind in the lower layers would be responsible for the premature dissipation of the April 30 fog.