Correlation Of Anomalies Research Articles

Regional magnetic and gravity anomaly correlations of the Southern Tyrrhenian Sea

The complex magnetic and gravity anomaly fields of the Southern Tyrrhenian Sea provide a record of the complicated properties and evolution of the underlying crust. Geologic interpretation of these anomalies is hindered by the effects of anomaly superposition and source ambiguity inherent to potential field analysis. A common approach to minimizing interpretational ambiguities is to consider analyses of anomaly correlations. Spectral correlation filters are used to separate positively and negatively correlated anomaly features based on the correlation coefficient given by the cosine of the phase difference between common wavenumber components. This procedure is applied to reduced-to-pole magnetic and first vertical derivative gravity anomalies for mapping correlative crustal magnetization and density contrasts. Adding and subtracting the standardized outputs of the filters yield summed (SLFI) and differenced (DLFI) local favorability indices that, respectively highlight positive and negative feature correlations in the anomaly data sets. Correlative maxima mainly reflect volcanic structures, and secondarily intrusive bodies and pre-Tortonian carbonates of the Maghrebian chain and the basement rocks of the Sardinia eastern margin. Correlative minima mostly mark sediment-filled peri-Tyrrhenian structural basins related to the Pliocene extensional tectonics, and intra-slope marine depressions related to post-Pliocene and still-active compressional tectonics off Northern Sicily. Prominent inverse anomaly correlations mainly reflect crustal features around the southern margin of the Tyrrhenian Sea that include higher density, lower magnetization pelagic-to-terrigenous and flysch-type nappes of the Sicilian-Maghrebian chain, as well as lower density, higher magnetization sediments filling depressions of the chain, and syn-rift sediments of Southeastern Sardinia.

Interannual variations in the total ozone, stratospheric dynamics, extratropical SST anomalies and predictions of abnormal winters in Eurasia

Analysis of the monthly mean interannual variations in the total ozone (TO), zonal stratospheric circulation, three-dimensional Eliassen–Palm (EP) fluxes and their correlations with the surface air temperature (SAT) and sea surface temperature (SST) anomalies in the North Pacific and North Atlantic was carried out. Interannual TO variations are strongly connected with those of the zonal wind in the lower stratosphere during the winter. A strong upward propagation of planetary waves from the troposphere to the stratosphere over northern Eurasia and a weak downward propagation in Labrador and South Greenland regions are indicated. There are large differences in the interaction of the zonal mean circulation and wave processes between early winter (November–December) and mid-to-late winter (January–March). Amplification of the penetration into the stratosphere of planetary waves in December is strongly associated with changes in the stratospheric dynamics in January, creating the ‘preconditions’ for the appearance of stratospheric warming. We show that the ‘stratospheric bridge’, with a strengthening of the downward propagation of the vertical EP flux over the North Atlantic, is being formed for years with a strong polar vortex. Simultaneous correlations of the stratospheric circulation variations with the Southern Oscillation Index show its small linkage with the stratospheric dynamics in the Arctic. However, there are significant correlations of the extratropical SST anomalies in the North Pacific and the North Atlantic with the interannual variations in the stratospheric dynamics. We demonstrate that the TO changes over the UK in January can be a good predictor of the anomalous cold/warm winters in distinct regions of Eurasia in February. The TO and other stratospheric predictors can be used for extended-range forecasting of extreme winters in Eurasia. Possible mechanisms for stratosphere–troposphere coupling and its link to the extratropical SST anomalies are discussed.

Magnetic anomalies near Apollinaris Patera and the Medusae Fossae Formation in Lucus Planum, Mars

The nature of strong martian crustal field sources is investigated by mapping and modeling of Mars Global Surveyor magnetometer data near Apollinaris Patera, a previously proposed volcanic source, supplemented by large-scale correlative studies. Regional mapping yields evidence for positive correlations of orbital anomalies with both Apollinaris Patera and Lucus Planum, a nearby probable extrusive pyroclastic flow deposit that is mapped as part of the Medusae Fossae Formation. Iterative forward modeling of the Apollinaris Patera magnetic anomaly assuming a source model consisting of one or more uniformly magnetized near-surface disks indicates that the source is centered approximately on the construct with a scale size several times larger and comparable to that of the Apollinaris Patera free-air gravity anomaly. A significantly lower rms deviation is obtained using a two-disk model that favors a concentration of magnetization near the construct itself. Estimates for the dipole moment per unit area of the Lucus Planum source together with maximum thicknesses of ∼3 km based on topographic and radar sounding data lead to an estimated minimum magnetization intensity of ∼50 A/m within the pyroclastic deposits. Intensities of this magnitude are similar to those obtained experimentally for Fe-rich Mars analog basalts that cooled in an oxidizing (high fO 2) environment in the presence of a strong (⩾10 μT) surface field. Further evidence for the need for an oxidizing environment is provided by a broad spatial correlation of the locations of phyllosilicate exposures identified to date using Mars Express OMEGA data with areas containing strong crustal magnetic fields and valley networks in the Noachian-aged southern highlands. This indicates that the presence of liquid water, which is a major crustal oxidant, was an important factor in the formation of strong magnetic sources. The evidence discussed here for magnetic sources associated with relatively young volcanic units suggests that a martian dynamo existed during the late Noachian/early Hesperian, after the last major basin-forming impacts and the formation of the northern lowlands.

Spring predictability barrier of ENSO events from the perspective of an ensemble prediction system

Based on an ENSO (El Niño-Southern Oscillation) ensemble prediction system (EPS), the seasonal variations in the predictability of ENSO are examined in both a deterministic and a probabilistic sense. For the deterministic prediction skills, the skills of the ensemble-mean are sensitive to the month in which the forecast was initiated. The anomaly correlations decrease rapidly during the Northern Hemisphere (NH) spring, and the root mean square (RMS) errors have the largest values and the fastest growth rates initialized before and during the NH spring. However, the probabilistic predictions based on the verification methods of the relative operating character (ROC) curve and area both show that there are no strong seasonal variations for the two extreme (warm and cold) ENSO events. For the near-normal events, the seasonal variations of the probabilistic skills are much more obvious, and the ROC areas of the ensemble forecasts made in the spring are clearly smaller than those of the ensemble forecasts that began during other seasons. At the same time, the probabilistic prediction skills of the EPS for all three events that only consider the initial perturbations are also clearly sensitive to the initial months. This was indicated by the fact that the most rapid decrease of the ROC area skill occurs as the hindcasts proceed through the spring season. A further signal-to-noise ratio analysis reveals that potential sources of the predictability barrier in the probabilistic skills for the EPS are namely that the spring is the period when stochastic initial error effects can be expected to strongly degrade forecast skill, and that small predicted signals can render the system noisier by further limiting the predictability. However, reasonable considerations of the model-error perturbations during the ensemble forecast process can alleviate the barrier caused by initial uncertainties through coordinately simulating the seasonal variations of the forecast uncertainty in order to significantly improve the probabilistic prediction skills and then to disorder the seasonal predictability related to the SPB.

Radon Monitoring in Soil Gas and Ground Water for Earthquake Prediction Studies in North West Himalayas, India

Continuous monitoring of soil gas radon at Sarol and the daily monitoring of radon concentration in water at Banikhet is carried out in Chamba valley of North West Himalayas, India “a well known seismic zone” to study the correlation of radon anomalies in relation to seismic activities of the region. Radon monitoring in soil gas was carried out by using Barasol probe manufactured by Algade France and the radon content in water was recorded using RAD7 radon monitoring system of Durridge Company, USA. The effect of meteorological parameters viz. temperature and pressure on soil gas radon emission has been studied. Correlation coefficient has been calculated between radon in soil gas, soil temperature and soil pressure. The radon anomalies observed in the region have been correlated with the seismic events in the magnitude range 2.2 to 5.0 recorded by Wadia Institute of Himalayan Geology Dehradun in NW Himalayan. Empirical equations between earthquake magnitude, epicentral distance and precursor time were examined, and respective constants were determined.

Possible causes for the persistence barrier of SSTA in the South China Sea and the vicinity of Indonesia

The persistence barrier refers to the lag correlation of sea surface temperature anomalies (SSTA) showing a rapid and significant decline in a specific season, regardless of the starting month. This implies that there is a decrease in forecast skill for SSTA in this specific season. This paper investigates the possible causes for the persistence barrier of SSTA in the South China Sea (SCS) and its adjacent regions from the perspective of interannual-interdecadal time scales. The results show that the persistence barrier of SSTA exists not only in the SCS, but also in the vicinity of Indonesia south of the equator. The SCS barrier occurs around October-November, while the occurrence of the barrier in the Indonesia region is around November-December. For these two regions, the occurrence of the persistence barrier is closely associated with the interdecadal variability of SSTA, as well as the interannual variability. The persistence barriers in the SCS and the Indonesia region do not exist alone if the interdecadal variability is not considered, because SSTA have a short memory of less than 4 months, regardless of the starting month. Moreover, the influence of the interdecadal variability of SSTA on the persistence barrier of SSTA in the SCS and the Indonesia region may be associated with SSTA in the Indian Ocean and the western Pacific, but is not closely associated with the Pacific Decadal Oscillation. However, compared with the spring persistence barrier (SPB) of ENSO, the close relationship between the persistence barriers in the SCS and the Indonesia region and the interdecadal variability is unique, since the ENSO SPB is not significantly affected by such variability. In addition, although the persistence barriers in both the SCS and the Indonesia region are quite obvious in strong ENSO cases, the interdecadal variability of SSTA also plays a non-negligible role in this relationship.

Earthquake precursory studies in Kangra valley of North West Himalayas, India, with special emphasis on radon emission

The continuous soil gas radon monitoring is carried out at Palampur and the daily monitoring of radon concentration in water is carried out at Dharamshala region of Kangra valley of North West Himalayas, India, a seismic zone V, to study the correlation of radon anomalies in relation to seismic activities. In this study, radon monitoring in soil was carried out by using barasol probe manufactured by Algade France, whereas the radon content in water was recorded using RAD 7 radon monitoring system of Durridge Company USA. The effect of meteorological parameters viz. temperature, pressure, wind velocity, rainfall, and humidity on radon emission has been studied. The seasonal average value and standard deviation of radon in soil and water is calculated to find the radon anomaly to minimize the effect of meteorological parameters on radon emission. The radon anomalies observed in the region have been correlated with the seismic events of M≥2 reported by Wadia Institute of Himalayas Geology Dehradoon and Indian Meteorological Department, New Delhi in NW Himalayas within 250 km distance from the monitoring stations.

A Five-Year Record of Summer Melt on Eurasian Arctic Ice Caps

Abstract Climatologies and annual anomaly patterns (2000–04) of melt season duration and dates of melt onset/freeze-up on Eurasian Arctic ice masses were derived from Quick Scatterometer (QuikSCAT) backscatter data. Severnaya Zemlya, Russia, has later melt onset, earlier freeze-up, and shorter melt seasons than Svalbard, Norway/Novaya Zemlya, Russia. In all three archipelagos 2001 was the longest melt season and 2000 was the shortest. Anomalously long (short) melt seasons on Svalbard were associated with negative (positive) sea ice concentration anomalies along the north coast in June and August. Annual mean melt duration was strongly correlated with the mean (June + August) NCEP–NCAR reanalysis 850-hPa air temperature, allowing reconstruction of melt durations for the period of 1948–2005. The 2000–04 pentad had the second or third longest mean melt duration of all pentads in the 1950–2004 epoch, while the 1950–54 pentad probably had the longest. Integration of these results with previous results from Greenland and the Canadian Arctic identifies 2002 as the longest melt season in the 2000–04 period across the Arctic as a whole, and 2001 as the shortest. Correlation of melt duration anomalies for 19 discrete regions identifies seven spatially coherent areas of the Arctic with common patterns of variability in annual melt duration.

A Two-Season Impact Study of NOAA Polar-Orbiting Satellites in the NCEP Global Data Assimilation System

Abstract Observing system experiments (OSEs) during two seasons are used to quantify the important contributions made to forecast quality from the use of the National Oceanic and Atmospheric Administration’s (NOAA) polar-orbiting satellites. The impact is measured by comparing the analysis and forecast results from an assimilation–forecast system using one NOAA polar-orbiting satellite with results from using two and three polar-orbiting satellites in complementary orbits. The assimilation–forecast system used for these experiments is the National Centers for Environmental Prediction (NCEP) Global Data Assimilation System–Global Forecast System (GDAS–GFS). The case studies chosen consist of periods during January–February and August–September 2003. Differences between the forecasts are accumulated over the two seasons and are analyzed to demonstrate the impact of these satellites. Anomaly correlations (ACs) and geographical forecasts (FIs) are evaluated for all experimental runs during both seasons. The anomaly correlations are generated using the standard NCEP verification software suite and cover the polar regions (60°–90°) and midlatitudes (20°–80°) of each hemisphere. The rms error for 850- and 200-hPa wind vector differences are shown for the tropical region (20°N–20°S). The geographical distribution of forecast impact on geopotential heights, relative humidity, precipitable water, and the u component of wind are also examined. The results demonstrate that the successive addition of each NOAA polar-orbiting satellite increases forecast quality. The use of three NOAA polar-orbiting satellites generally provides the largest improvement to the anomaly correlation scores in the polar and midlatitude regions. Improvements to the anomaly correlation scores are also realized from the use of two NOAA polar-orbiting satellites over only one. The forecast improvements from two satellites are generally smaller than if using three satellites, consistent with the increase in areal coverage obtained with the third satellite.

Korrelation zwischen Risikogenvarianten für Schizophrenie und Hirnstrukturanomalien

The specific etiologies of schizophrenia are largely unknown. Genetic predisposition constitutes an important, however, not exclusive risk factor for the development of schizophrenia. In recent years, a number of candidate genes were identified and have been consistently replicated. Magnetic resonance imaging studies have characterized structural changes in brain morphology, such as ventricular enlargement or volume reduction of the medial temporal structures and the superior temporal gyrus. Several studies have found correlations between gene variants and changes of brain morphology in schizophrenia patients and healthy controls. In this review, publications examining correlations of schizophrenia susceptibility gene polymorphisms and structural brain anomalies in patients and healthy controls are described. An overview and a critical reflection of the current research are outlined. The results of genome-wide studies will soon provide a multitude of additional schizophrenia susceptibility genes. If and to what extent these genes exert an influence on the brain structure in the healthy and the diseased, can be clarified by gene structure correlations. Given the many possible gene-gene and gene-environment interactions, most variants will probably not show simple interactions with sizable effects.

Contribution of stratospheric ozone to the interannual variability of tropospheric ozone in the northern extratropics

We examined the role of variability in the input of stratospheric ozone on the interannual variability of tropospheric ozone in the northern extratropics using correlations of monthly ozone anomalies for the lower stratosphere and the troposphere. We used output from a multiyear simulation of the NASA Goddard Space Flight Center (GSFC) Chemistry and Transport Model (CTM), and evaluated model results using ozonesonde data. The GSFC CTM explicitly calculates stratospheric ozone and simulates separate tracers of stratospheric and tropospheric ozone (O3‐strat and O3‐trop, respectively). The climatological seasonal cycle of ozone shows that O3‐strat contributes significantly to the spring maximum of ozone at 500 hPa, ∼40% at high latitudes and ∼30% at midlatitudes. We find large regional differences in the correlation of ozone in the lower stratosphere and troposphere in the model that are supported by the ozonesonde data. Highest correlations are found from the eastern Atlantic to Europe, from the eastern Pacific to the western United States, and over the polar regions, in winter‐spring. This spatial pattern is due to the input of O3‐strat into the troposphere. The distribution and time lag of the correlations (highest with no lag for midlatitudes and a 1–2 month lag for polar regions) are consistent with the dynamical indicators of stratosphere‐troposphere exchange (STE), such as storm tracks in the midlatitudes and slow descending motion in the polar region. Our simple approach can be widely applied to diagnose the effect of STE on tropospheric ozone.

Spatial correlation of the aeromagnetic anomalies and seismogenic faults in the Marmara region, NW Turkey

Previous investigations into the deep structure of the Marmara Sea region revealed an existence of a rigid barrier located at the centre of the Marmara Sea. Thus, the North Anatolian Fault (NAF) was divided into three segments to the west of this barrier. Seismological records of two 5 year periods (1998–2002 and 2003–2007) indicate a decrease of seismic activity on and around this barrier. It was previously shown if the fault movement reaches to magma its fractures are filled with magmatic material causing magnetic anomalies. In this study, advance processing methods are utilized to observe the spatial correlation between the aeromagnetic anomalies and the faults of the Marmara region. These are the reduction to the pole transformation (RTP) and second vertical derivative (SVD) methods. In particular, SVD map shows alignments which can be correlated with the faults. These faults are the Northern Boundary, Yalova, Armutlu, Imrali and Edincik faults. Length of the Northern Boundary Fault (NBF) is about 50–60 km. Thus, this fault would not produce strong earthquakes. The Edincik Fault extends from east to the west and bends through WSW. The length of this fault in connection with the Imrali, Armutlu and Yalova faults in the east exceeds 300 km and named the Main Fault Zone (MFZ) by the authors of this study. These faults as a whole may produce strong earthquakes. Some seismic gaps are observed along with the Imrali and Edincik faults from the earthquake distribution records of two 5 year periods (1998–2002 and 2003–2007). As a conclusion, there are high-potentials of strong earthquake occurrences in these regions.

Spatial analysis of stream power using GIS: SLk anomaly maps

AbstractThe stream length‐gradient index (SL) shows the variation in stream power along river reaches. This index is very sensitive to changes in channel slope, thus allowing the evaluation of recent tectonic activity and/or rock resistance. Nevertheless, the comparison of SL values from rivers of different length is biased due to the manner in which the index is formulated, thus making correlations of SL anomalies along different rivers difficult. Therefore, when undertaking a comparison of SL values of rivers of different lengths, a normalization factor must be used. The graded river gradient (K) has already been used in some studies to normalize the SL index. In this work, we explore the relationships between the graded river gradient (K), the SL index and the stream power, proposing the use of a re‐named SLk index, which enables the comparison of variable‐length rivers, as well as the drawing of SLk anomaly maps. We present here a GIS‐based procedure to generate SLk maps and to identify SLk anomalies. In order to verify the advantages of this methodology, we compared an SLk map of the NE border of the Granada basin with both simple river profile–knickpoint identification and with an SL map. The results show that the SLk map supplies good results with defined anomalies and suitably reflects the main tectonic and lithological features of the study area. Copyright © 2008 John Wiley & Sons, Ltd.

Snow Cover Characteristics over the Main Russian River Basins as Represented by Reanalyses and Measured Data

Abstract Snow water equivalents (SWE) produced by the National Centers for Environmental Prediction–U.S. Department of Energy (NCEP–DOE) and 40-yr European Centre for Medium-Range Weather Forecasts (ERA-40) reanalyses and snow depths (SD) produced by the 25-yr Japanese “JRA-25” reanalysis over the main Russian river basins for 1979–2000 were examined against measured data. The analysis included comparisons of mean basin values and correlation of anomalies, as well as seasonal and interannual variabilities and trends. ERA-40 generally provided better estimates of mean SWE values for river basins than did the NCEP–DOE reanalysis. Mean SD values from the JRA-25 reanalysis were systematically underestimated. The best correlations among the anomalies were given by ERA-40, followed by JRA-25. All reanalyses reproduced seasonal variability well, although the differences in absolute values varied substantially. The highest differences were typically connected with the snowmelt period (April and May). Interannual variability confirmed the errors of ERA-40 and JRA-25 in 1992–94 and 1979–83, respectively. Otherwise, the reproduction of the interannual variability of SWE and SD was reasonable. Strong biases in SD data from JRA-25 that decrease with time induce artificial positive trends. Significant underestimations of SWE data by ERA-40 for 1991–94 influenced the values of the trends. NCEP–DOE reasonably represented the trend found in measured data. In general, the highest discrepancies between measured and reanalysis data were found for the northern European and eastern Asian rivers (Pechora, Lena, and Amur). The assessment of the quality of SWE and SD reanalysis data can help potential users in the selection of a particular reanalysis as being appropriate to the purpose of their studies.

Testing Climate Models Using Thermal Infrared Spectra

Abstract An approach to test climate models with observations is presented. In this approach, it is possible to directly observe the longwave feedbacks of the climate system in time series of annual average outgoing longwave spectra. Tropospheric temperature, stratospheric temperature, water vapor, and carbon dioxide have clear and distinctive signatures in the infrared spectrum, and it is possible to detect trends of these signals unambiguously from trends in the outgoing longwave spectrum by optimal detection techniques. This approach is applied to clear-sky data in the tropics simulated from the output of an ensemble of climate models. Estimates of the water vapor–longwave feedback by this approach agree to within estimated errors with truth, and it is likely that an uncertainty of 50% can be obtained in 20 yr of a continuous time series. The correlation of tropospheric temperature and water vapor anomalies can provide a constraint on the water vapor–longwave feedback to 5% uncertainty in 20 yr, or 7% in 10 yr. Thus, it should be possible to place a strong constraint on climate models, which currently show a range of 30% in the water vapor–longwave feedback, in just 10 yr. These results may not hold in the presence of clouds, however, and so it may be necessary to supplement time series of outgoing longwave spectra with GPS radio occultation data, which are insensitive to clouds.

Correlation of GSO satellite anomalies with space weather data

This work summarizes the main results of our studies at the ISRO cell of IIT-Mumbai, on the relationship between space weather and geostationary satellite anomalies. We point out that the essence of the problem is to understand quantitatively the relationships between changes in space weather at the Sun (S) and the dayside Lagrangian point (L1) on the one hand, and on the other hand the electron/proton fluxes and magnetic field changes at the geostationary altitude (G). Electromagnetic and cosmic ray changes at the Earth surface (E) are also related to the field and particle changes observed at G. We have evolved prediction programs for satellite anomalies based on proton events on the Sun, the solar wind speeds measured at L1, and the 2MeV electron flux enhancements observed at G. The probabilities and time lags of the occurrence of satellite anomalies are also governed by whether the ‘shock’ in solar wind and IMF parameters detected at L1 is of a ‘sharp’ or a ‘diffuse’ type. From a comparative study of the two years 2005 and 2006 with very different space weather conditions, we find that the type and number of anomalies is (1) clearly governed by the magnitude of the interplanetary electric field Esw, and hence by the IMF B and (2) by the number of proton events on the Sun. We are currently exploring the role played by the ratio of 2MeV electrons to the >1MeV protons, both at G, in the occurrence of satellite anomalies.

A Two-Season Impact Study of Four Satellite Data Types and Rawinsonde Data in the NCEP Global Data Assimilation System

Abstract Extended-length observing system experiments (OSEs) during two seasons are used to quantify the contributions made to forecast quality by conventional rawinsonde data and four types of remotely sensed satellite data. The impact is measured by comparing the analysis and forecast results from an assimilation–forecast system using all data types with those excluding a particular observing system. The impact of the particular observing system is assessed by comparing the forecast results over extended periods. For these observing system experiments, forecast results are compared through 168 h for periods covering more than a month during both the summer and winter seasons of each hemisphere. The assimilation–forecast system used for these experiments is the National Centers for Environmental Prediction (NCEP) Global Data Assimilation System (GDAS) and the Global Forecast System (GFS). The case studies chosen consist of periods during January–February 2003 and August–September 2003. During these periods, a T254L64 layer version of NCEP’s global spectral model was used. The control run utilized all data types routinely assimilated in the GDAS. The experimental runs individually denied data from the Advanced Microwave Sounding Unit (AMSU), the High-Resolution Infrared Radiation Sounder (HIRS), geostationary satellite atmospheric motion vectors (GEO winds), in situ rawinsondes (raobs), and surface winds derived from the Quick Scatterometer (QuikSCAT). Differences between the control and denial experiment forecasts are accumulated over the two 45-day periods and are analyzed to demonstrate the impact of these data types. Anomaly correlations (ACs), forecast impacts (FIs), and hurricane track forecasts are evaluated for all experimental runs during both seasons. The anomaly correlations used the standard NCEP software suite and are partitioned into subsections covering the polar caps (60°–90°) and midlatitudes (20°–80°) of each hemisphere and the tropical region (20°N–20°S). Anomaly correlations of geopotential heights are shown at several pressure levels in the polar regions and midlatitudes. The root-mean-square error (RMSE) for 850- and 200-hPa wind vector differences are shown for the tropical region. The geographical distributions of forecast impacts on geopotential heights are also examined. The influence these data types have on tropical cyclone track forecasts are shown for both the Atlantic and Pacific basins and again are computed using standard algorithms developed and maintained at NCEP. The results demonstrate a positive impact from all data types with AMSU and rawinsonde data providing the largest anomaly correlation improvements in all zonal regions examined. Smaller forecast improvements are noticed from each of the other data types. In the Atlantic basin, each of the four satellite data types provides nearly equal improvement to the tropical cyclone track forecasts; however, GEO winds provide the largest improvement to track forecasts in the Pacific basin.

A trajectory‐based estimate of the tropospheric ozone column using the residual method

We estimate the tropospheric column ozone using a forward trajectory model to increase the horizontal resolution of the Aura Microwave Limb Sounder (MLS) derived stratospheric column ozone. Subtracting the MLS stratospheric column from Ozone Monitoring Instrument total column measurements gives the trajectory enhanced tropospheric ozone residual (TTOR). Because of different tropopause definitions, we validate the basic residual technique by computing the 200‐hPa‐to‐surface column and comparing it to the same product from ozonesondes and Tropospheric Emission Spectrometer measurements. Comparisons show good agreement in the tropics and reasonable agreement at middle latitudes, but there is a persistent low bias in the TTOR that may be due to a slight high bias in MLS stratospheric column. With the improved stratospheric column resolution, we note a strong correlation of extratropical tropospheric ozone column anomalies with probable troposphere‐stratosphere exchange events or folds. The folds can be identified by their colocation with strong horizontal tropopause gradients. TTOR anomalies due to folds may be mistaken for pollution events since folds often occur in the Atlantic and Pacific pollution corridors. We also compare the 200‐hPa‐to‐surface column with Global Modeling Initiative chemical model estimates of the same quantity. While the tropical comparisons are good, we note that chemical model variations in 200‐hPa‐to‐surface column at middle latitudes are much smaller than seen in the TTOR.

Tropical cyclone genesis potential index in climate models

The potential for tropical cyclogenesis in a given ocean basin during its active season has been represented by genesis potential indices, empirically determined functions of large-scale environmental variables which influence tropical cyclone (TC) genesis. Here we examine the ability of some of today’s atmospheric climate models, forced with historical observedSSTover a multidecadal hindcast period, to reproduce observed values and patterns of one such genesis potential index (GP), as well as whether the GP in a given model is a good predictor of the number of TCs generated by that model. The effect of the horizontal resolution of a climate model on its GP is explored.The five analysed models are capable of reproducing the observed seasonal phasing of GP in a given region, but most of them them have a higher GP than observed. Each model has its own unique relationship between climatological GP and climatological TC number; a larger climatological GP in one model compared to others does not imply that that model has a larger climatological number of TCs. The differences among the models in the climatology of TC number thus appear to be related primarily to differences in the dynamics of the simulated storms themselves, rather than to differences in the simulated large-scale environment for genesis. The correlation of interannual anomalies in GP and number of TCs in a given basin also differs significantly from one model to the next.Experiments using the ECHAM5 model at different horizontal resolutions indicate that as resolution increases, model GP also tends to increase. Most of this increase is realized between T42 and T63.

Assimilation of ozone profiles from the Improved Limb Atmospheric Spectrometer‐II: Study of Antarctic ozone

Ozone data from the Improved Limb Atmospheric Spectrometer‐II (ILAS‐II) were included in addition to other satellite observations in the ozone assimilation system at the Global Modeling and Assimilation Office (GMAO) of NASA/Goddard. The control run assimilated data from NOAA 16 Solar Backscatter Ultraviolet/2 (SBUV/2) and Polar Ozone and Aerosol Measurement III (POAM III) instruments. Persistent impacts over Antarctica and transient impacts over northern middle and high latitudes are seen from April to October 2003, when ILAS‐II provided good coverage. The largest improvements with respect to independent ozone sonde data are seen over the South Pole station. Ozone analyses and forecasts from the assimilation of SBUV/2, POAM III and ILAS‐II data are used to investigate the transport of ozone to southern middle latitudes following the breakup of the Antarctic vortex. The quality of analyses and forecasts is evaluated by comparison with independent Stratospheric Aerosol and Gas Experiment III (SAGE III) ozone data near 46°S. Anomaly correlations between SAGE III data and forecasts are improved at 70 hPa when occultation data are included.