This study aims at increasing our understanding of the regional wind climate in Sweden. Spatial and temporal patterns of the surface winds are presented for the years 1999-2000. Annual mean wind speeds range between 2 and 5 m/s with high values at exposed mountainous sites and on islands off the coast. Combining wind speed and direction into mean wind velocities shows that flow conditions are stronger and more coherent in space in southern Sweden than in central and northern Sweden. The spatial scale, defined as the distance between stations when the correlation for wind speed drops to similar to 0.37, was determined by pairwise correlations between all possible station pairs. Scales range from 38 to 530 km for wind speed and from 40 to 830 km for wind direction depending on the region. They tend to be smaller in central and northern Sweden, where the more pronounced relief has a larger influence on the local wind conditions. The strength and the timing of the annual and diurnal wind speed cycle have been estimated for each station. Amplitudes of the annual cycle are greater at exposed sites and correlate generally well with annual mean wind speeds. Monthly mean wind speeds peak in winter in southern Sweden, but peak in other seasons in the remaining regions. In winter, weaker pressure gradients over northern Sweden and surface-near temperature inversions contribute to weaker surface winds. Diurnal cycles vary in strength between summer and winter. Compared to the last normal climate period (1961-1990), 1999-2000 is characterized by the increased occurrence of westerly and southerly geostrophic flow. Copyright (C) 2005 Royal Meteorological Society.

A new test for the detection of linear trends of arbitrary length in normally distributed time series is developed. With this test it is possible to detect and estimate gradual changes of the mean value in a candidate series compared with a homogeneous reference series. The test is intended for studies of artificial relative trends in climatological time series, e.g. an increasing urban heat island effect. The basic structure of the new test is similar to that of a widely used test for abrupt changes, the standard normal homogeneity test. The test for abrupt changes is found to remain unaltered after an important generalization.

Extra-tropical cyclone frequency and intensity are Currently under intense scrutiny because of the destruction recent windstorms have brought to Europe, and because they are a major meridional heat transport mechanism that may respond to differential latitudinal warming trends. Several studies using reanalysis data covering the second half of the 20th century Suggest increasing storm intensity in the northeastern Atlantic and European sector. Fewer analyses cover a longer time period but show different trends or point towards the dominance of interdecadal variability instead of ally clear trends. Hence, it is relevant to analyse cyclone variability over as long a period as possible. In this Study, we analyse interdecadal variability in cyclone activity over northwestern Europe back to AD 1780 by combining information from eight storminess indices applied in all Eulerian framework. These indices, including four new approaches towards gauging cyclone activity, use the series of thrice-daily sea level pressure observations at Lund and Stockholm. We find pronounced interdecadal variability in cyclonic activity but no significant overall consistent long-term trend. The major interdecadal-scale variability common to all indices is in good agreement with geostrophic wind reconstructions for NE Atlantic and NW Europe, and with variations in the North Atlantic oscillation (NAO). Our results show that the reanalysis studies cover a time period chiefly coinciding with a marked, but not exceptional in our 225-year perspective, positive variation in the regional cyclone activity that has more recently reversed. Because of the interdecadal variations, a near-centennial time perspective is needed when analysing variations in extra-tropical cyclone activity and the associated weather conditions over northwestern Europe. Copyright (C) 2009 Royal Meteorological Society

The reconstructed surface air pressure series from Lund, southern Sweden, covers the period 1780-1997 and comprises mon than 234000 valid observations (three observations per day), i.e. > 98% of all possible observation occasions. For the Early Instrumental Period (EIP; 1780-1860) data were digitised from the original records. For most of the Modern Instrumental Period (MIP; 1861-) a series was compiled from various databases containing instrument corrected data. During EIP, the series of raw monthly means show several substantial inhomogeneities. With the aid of a detailed reconstruction of the station history, it was possible to remove almost all inhomogeneities during EIP by applying the correct instrument corrections (for barometer temperature, to standard gravity and to mean sea-level pressure) to the series of original observations. In particular, corrections for the temperature and altitude of the barometer eliminated several inhomogeneities. A prerequisite for applying these corrections is the availability of high-resolution data (actual raw observations or daily averages). Further homogenisation was attained by intercomparison of the monthly mean pressure with acknowledged homogeneous series (mainly the UKMO monthly grid, station records from Copenhagen and Edinburgh). Statistical tests of homogeneity showed that no substantial inhomogeneities remain in the final version. The modern part of the final monthly pressure series largely follows that of the southern Baltic Sea region. Furthermore, it shows relatively high pressure during spring (MAM) in the period 1780-1820, which was paralleled by severe wind erosion in southern Scandinavia during this time. Relatively high pressure throughout the year is also notable during a period of precipitation deficit in 1970s. Copyright (C) 1999 Royal Meteorological Society.

: This study investigates the impacts of climate change scenario on summer heat waves’ (HWs) and winter cold spells’ (CSs) characteristics for 12 locations over the Iberian Peninsula (IP). These characteristics are duration, recovery factor and intensity. Two future time slices of the chosen scenario are studied, namely, the periods 2046–2065 and 2081–2100 which are compared with a reference climate for the recent-past (1986–2005). The RCP8.5 greenhouse gas emission scenario is considered. The minimum and maximum daily temperature were obtained for these periods through regional model simulations using the Weather and Research Forecast (WRF) model forced with the MPI-ESM-LR model. The model was validated against EOBS and SPAIN02 datasets. The model shows 90th/10th percentile temperature (i.e. thresholds to identify HW/CS) biases. Therefore, HW/CS numbers and properties were evaluated using the model’s respective thresholds. HW/CS numbers and characteristics were also compared between the model and EOBS derived data. Probability density functions (PDFs) of the duration, recovery factor and intensity show significant changes in the mean and variance for the summer HWs. Differences, between future and recent-past climate in the extremes are evaluated by the 95th percentile which show an increase in the duration and intensity of the HWs for the future time slices. Very few CSs were detectable in the mid-term future (2046–2065) and none in the long-term future (2080–2100), except for Barcelona. For most locations, the CS for the future are of smaller duration and intensity. The PDF of the recovery factor suggests smaller absolute differences between the minimum and maximum temperature during winter which is also confirmed by the percentile analysis. The increase in the duration and intensity of HWs is greater in the long-term future than in the mid-term future, pointing for a warmer IP with more and longer HWs towards the end of the XXI century

An intercomparison of three regional climate models (RCMs) (PRECIS-HadRM3P, RCA4, and RegCM4) was performed over the Coordinated Regional Dynamical Experiment (CORDEX)-Central America, Caribbean, and Mexico (CAM) domain to determine their ability to reproduce observed temperature and precipitation trends during 1980-2010. Particular emphasis was given to the North American monsoon (NAM) and the mid-summer drought (MSD) regions. The three RCMs show negative (positive) temperature (precipitation) biases over the mountains, where observations have more problems due to poor data coverage. Observations from the Climate Research Unit (CRU) and ERA-Interim show a generalized warming over the domain. The most significant warming trend (>= 0.34 degrees C/decade) is observed in the NAM, which is moderately captured by the three RCMs, but with less intensity; each decade from 1970 to 2016 has become warmer than the previous ones, especially during the summer (mean and extremes); this warming appears partially related to the positive Atlantic Multidecadal Oscillation (+AMO). CRU, GPCP, and CHIRPS show significant decreases of precipitation (less than -15%/decade) in parts of the southwest United States and northwestern Mexico, including the NAM, and a positive trend (5-10%/decade) in June-September in eastern Mexico, the MSD region, and northern South America, but longer trends (1950-2017) are not statistically significant. RCMs are able to moderately simulate some of the recent trends, especially in winter. In spite of their mean biases, the RCMs are able to adequately simulate inter-annual and seasonal variations. Wet (warm) periods in regions affected by the MSD are significantly correlated with the +AMO and La Nina events (+AMO and El Nino). Summer precipitation trends from GPCP show opposite signs to those of CRU and CHIRPS over the Mexican coasts of the southern Gulf of Mexico, the Yucatan Peninsula, and Cuba, possibly due to data limitations and differences in grid resolutions.

The output of four regional climate models (RCMs) from the Coordinated Regional Climate Downscaling Experiment (CORDEX)-North America (NA) region was analysed for the 1990-2008 period, with particular interest on the mechanisms associated with wet and dry years over the North American Monsoon (NAM) core region. All RCMs (RCA3.5, HadGEM3-RA, REMO, and RegCM4) were forced by the ERA-Interim reanalysis. Model precipitation was compared against several observational gridded data sets at different time scales. Most RCMs capture well the annual cycle of precipitation and outperform ERA-Interim, which is drier than the observations. RCMs underestimate (overestimate) the precipitation over the coastal plains (mountains) and have some problems to reproduce the interannual variability of the monsoon. To further investigate this, two extreme summers that showed the largest consistency among observations and RCMs were chosen: one wet (1990) and one dry (2005). The impact of the passage of tropical cyclones, the size of the Western Hemisphere Warm Pool (WHWP), the Intertropical Convergence Zone (ITCZ) position, and the initial intensity of the land-sea thermal contrast (LSTC) were analysed. During the wet year, the LSTC was stronger than the 2005 dry monsoon season and there were a larger number of hurricanes near the Gulf of California, the WHWP was more extended, and the ITCZ was located in a more northerly position than in 2005. All these processes contributed to a wetter NAM season. During the dry year, the LSTC was weaker, with a later onset, probably due to a previous very wet winter. The inverse precipitation relationship between winter and summer in the monsoon region was well captured by most of the RCMs. RegCM4 showed the largest biases and HadGEM3-RA the smallest ones.

The southern Mexico and Central America (SMCA) region shows a dominant well-defined precipitation annual cycle. The rainy season usually begins in May and ends in October, with a relatively dry period in July and August known as the mid-summer drought (MSD); notable exceptions are the Caribbean coast of Honduras and Costa Rica. This MSD phenomenon is expected to be affected as the SMCA experiences an enhanced differential warming between the Pacific and Atlantic Oceans (PO-AO) towards the end of the 21st century. Previous studies have suggested that this differential warming will induce a strengthening of the westward Caribbean low-level jet (CLLJ) and that this heightened CLLJ will shift precipitation westwards, falling on the PO instead that within the SMCA region causing a severe drought. In this work we examine this scenario with a new model, the Rossby Center Regional Climate Model (RCA4), for the COordinated Regional climate Downscaling EXperiment (CORDEX) Central America domain, forced with different general circulation models (GCMs) and for different representative concentration paths (RCPs). We consider 25-year periods as "present conditions" (1981-2005) and "future scenario" (2071-2095), focusing on the "extended summer" season (May-October). Results suggest that in the future the spatial extension of the MSD will decrease and that in certain areas the MSD will be more intense but less frequent compared to present conditions. Also, the oceanic differential warming, the intensification of the CLLJ, and the reduction in regional precipitation in the future scenario, suggested by previous works, were verified in this study.

We examine the ability of an ensemble of 10 Regional Climate Models (RCMs), driven by ERA-Interim reanalysis, in skillfully reproducing key features of present-day precipitation and temperature (1990-2008) over West Africa. We explore a wide range of time scales spanning seasonal climatologies, annual cycles and interannual variability, and a number of spatial scales covering the Sahel, the Gulf of Guinea and the entire West Africa. We find that the RCMs show acceptable performance in simulating the spatial distribution of the main precipitation and temperature features. The occurrence of the West African Monsoon jump, the intensification and northward shift of the Saharan Heat Low (SHL), during the course of the year, are shown to be realistic in most RCMs. They also capture the mean annual cycle of precipitation and temperature, including, single and double-peaked rainy seasons, in terms of timing and amplitude over the homogeneous sub-regions. However, we should emphasize that the RCMs exhibit some biases, which vary considerably in both magnitude and spatial extent from model to model. The interannual variability of seasonal anomalies is best reproduced in temperature rather than precipitation. The ensemble mean considerably improves the skill of most of the individual RCMs. This highlights the importance of performing multi-model assessment in properly estimating the response of the West African climate to global warming at seasonal, annual and interannual time scales.

Efforts to intercompare many existing circulation type classification (CTC) methods have found no consistency in their outcomes. Therefore, when confronted with a task to classify atmospheric circulation types, it is difficult to find clear guidelines. This study explores the ways of increasing consistency between existing methods and obtaining physically meaningful and practically useful results. By applying a range of CTC methods to sea-level pressure fields over a Scandinavian domain, it is shown that CTC methods using the same similarity measure (pattern correlation (CORR) or Euclidean distance (DIST)) have higher consistency. It is further shown that CTC outcomes can be tailored towards specific user requirements by properly manipulating the input data. Using unprocessed input data in DIST-based CTC methods frequently results in classes containing physically inconsistent members because the classification procedure is obfuscated by circulation-irrelevant information in the data. Using spatially standardized data in DIST-based methods leads to considerably improved agreement with CORR-based methods and brings high physical consistency within the individual classes. However, standardizing the input data removes too much of the circulation-relevant information and results in no clear improvement in partitioning dependent variables such as precipitation. Best performance is achieved with DIST-based methods using the input data with the spatial mean removed. This simple procedure focuses the CTC methods to use only the circulation-relevant information and hence results both in physically consistent classes and in optimally performing partitioning of dependent variables. Consequently, the recommended guideline would be to use DIST-based methods with spatial-mean-removed input data as the generally most effective classification approach.

To estimate daily catchment precipitation from point observations there is a need to understand the spatial pattern, particularly in mountainous regions. One of the most important processes occurring there is orographic enhancement, which is affected by, among other things, wind speed and wind direction. The objective of this paper was to investigate whether the relationship between precipitation, airflow and topography could be described by statistical relationships using data easily available in an operational environment. The purpose was to establish a statistical model to describe basic patterns Of precipitation distribution. This model, if successful, can he used to account for the topographical influence in precipitation interpolation schemes. A statistical analysis was carried out to define the most relevant variables, and, based on that analysis, a regression model was established through stepwise regression. Some 15 years of precipitation data front 370 stations in Sweden were used for the analysis. The geostrophic wind, computed from pressure observations, was assumed to represent the airflow at the relevant altitude. Precipitation data for each station were divided into 48 classes representing different wind directions and wind speeds. Among the variables selected, the single most important one was found to be the location of a station with respect to a mountain range. On the upwind side, precipitation increased with increasing wind speed. On the leeward side there was less variation in precipitation, and wind speed did not affect the precipitation amounts to the same degree. For ascending air, slope multiplied by wind speed was another important factor. The effect of slope was enhanced close to the coast, and reduced for mountain valleys with upwind barriers. The stepwise procedure led to a regression model that also included the meridional and zonal wind components. Their inclusion might indicate the importance of air mass characteristics not explicitly accounted for. Copyright (C) 2003 Royal Meteorological Society.

Results from a satellite-based method to compile regional cloud climatologies covering the Scandinavian region are presented. Systematic processing of multispectral image data from the NOAA Advanced Very High Resolution Radiometer (AVHRR) instrument has been utilized to provide monthly cloud climatologies covering the period 1991-2000. Considerable local-scale variation of cloud amounts was found in the region. The inland Baltic Sea and adjacent land areas exhibited a large-amplitude annual cycle in cloudiness (high cloud amounts in winter, low cloud amounts in summer) whereas a weak-amplitude reversed annual cycle (high cloud amounts with a weak maximum in summer) was found for the Scandinavian mountain range. As a contrast, conditions over the Norwegian Sea showed high and almost unchanged cloud amounts during the course of the year. Some interesting exceptions to these patterns were also seen locally. The quality of the satellite-derived cloud climatology was examined through comparisons with climatologies derived from surface cloud observations, from the International Satellite Cloud Climatology Project (ISCCP) and from the European Centre for Medium-range Weather Forecasts ERA-40 data set. In general, cloud amount deviations from surface observations were smaller than 10% except for some individual winter months, when the separability between clouds and snow-covered cold land surfaces is often poor. The ISCCP data set showed a weaker annual cycle in cloudiness, generally caused by higher summer-time cloud amounts in the region. Very good agreement was found with the ERA-40 data set, especially for the summer season. However, ERA-40 showed higher cloud amounts than SCANDIA and ISCCP during the winter season. The derived cloud climatology is affected by errors due to temporal AVHRR sensor degradation, but they appear to be small for this particular study. The data set is proposed as a valuable data set for validation of cloud description in numerical weather prediction and regional climate simulation models. Copyright (C) 2003 Royal Meteorological Society.

Homogeneity tests of long seasonal temperature series from Sweden, Denmark, Finland, and Norway indicate that homogeneous series are rare and that an abrupt change of the relative mean level is a much more common type of nonhomogeneity than a gradual change. Furthermore, negative shifts were 20% more common than positive shifts. Homogenized temperature anomaly series that were constructed for six 5 degrees latitude x 5 degrees longitude grid boxes indicate that the temporal pattern of temperture changes has been similar in different parts of Sweden since 1861. The annual mean temperature over Sweden was found to have increased by 0.68 degrees C from the period 1861-1890 to 1965-1994. The corresponding changes for the seasons were: +0.18 degrees C (winter), +1.40 (spring), +0.42 (summer) and +0.60 (autumn). A direct comparson shows that non-homogeneities in the temperature series from individual grid boxes in a global data set can be as large as the total changes observed. We estimate that a 95 per cent confidence interval for the error, due to non-homogeneous long station records, in estimates of hemispheric temperature changes over land regions since the period 1861-1890 is +/-0.1 degrees C for the Northern Hemisphere and the globe and +/-0.25 degrees C for the Southern Hemisphere. For a region consisting of about five grid boxes, this error is +/-0.5 degrees C. The large non-homogeneities in individual grid-box series in the global data set is partly a consequence of the fact that homogeneous climate data are not always easily available for the open research community. We urge that efforts are made to improve this situation.

Temperature series from Stockholm and Uppsala in southern Sweden indicate that summers from the mid-18th century until around 1860 were, on average, warmer than the 1961-90 mean. The station histories suggest that the early observations could have been positively biased, for example because of insufficient radiation protection. We investigate if independent support for warm summers in the early period can be obtained from other climate variables. Using stepwise multiple regression analysis we investigate nine potential predictor variables: six air circulation indices, precipitation, air pressure and cloud amount. Three of these variables - cloud amount (the most important one), meridional geostrophic wind, and air pressure - together explain 65% of the June-August temperature variance in the calibration period 1873-2000. Application of the regression relationship back to 1780 shows that the model is equally successful in predicting year-to-year temperature variability before 1873 as it is in the calibration period, whereas the low-frequency component is poorly reconstructed in the early period. This reduced skill is primarily due to poorer data quality of the predictor variables in the early period, in particular the cloud amount series. The observed decadal mean temperatures during 1780-1860 are found to be above the upper limit of a 95% confidence interval that accounts for uncertainties both in the regression relationship and in the cloud amount series. We conclude that the observed temperatures before around 1860 are, therefore, most likely positively biased. The size of this bias cannot be accurately determined from the evidence used here, but seems to be about 0.7-0.8degreesC for both stations. A comparison with long instrumental temperature series from central Europe suggests a slightly smaller bias (0.5-0.6degreesC). For more accurate assessment of the Stockholm and Uppsala temperatures, we recommend that extensive homogeneity testing of other long northern European temperature series are undertaken. Copyright (C) 2003 Royal Meteorological Society.

Precipitation is one of the most important atmospheric variables to assess, particularly in the context of climate change. This study evaluates future changes in precipitation over the Iberian Peninsula (IP) under the RCP8.5 scenario. Changes are assessed for two future climate periods namely (2046-2065) and (2081-2100), relative to a recent reference climate (1986-2005). Here we introduce the concept of precipitation episodes (PEs) and estimate their statistical properties for the present climate and, their changes for future climate scenarios. PEs are defined by considering a full range of durations as well as intensities. This constitutes a novel approach to estimate changes with relevance, for example, for water resources applications. The climate simulations are performed with the Weather Research and Forecast (WRF) model. These are compared with an ensemble of other similar simulations from the Coordinated Downscaling Experiment initiative. This was done to evaluate the performance of the WRF model and also to estimate uncertainty of the derived future projections. Since models may present systematic errors, results from all simulations were previously bias corrected relative to observations using the same quantile mapping method. Under climate change, a great part of the region is expected to experience reduced annual precipitation of approximately 20-40% and reaching 80% in summer by the end of the XXI century. For the PEs, a large reduction in the average number of days and duration of all types of PEs is expected across all seasons and regions. The average intensity of episodes is projected to increase in winter and spring and decrease in summer. These results imply that climate change will likely influence precipitation and precipitation extremes in the 21st century, mostly in southern areas. These, together with projected warming may amplify desertification already taking place in the southern regions of the IP and cause stresses to water resources.

Long-term in situ observations are widely used in a variety of climate analyses. Unfortunately, most decade- to century-scale time series of atmospheric data have been adversely impacted by inhomogeneities caused by, for example, changes in instrumentation, station moves, changes in the local environment such as urbanization, or the introduction of different observing practices like a new formula for calculating mean daily temperature or different observation times. If these inhomogeneities are not accounted for properly, the results of climate analyses using these data on be erroneous. Over the last decade, many climatologists have put a great deal of effort into developing techniques to identify inhomogeneities and adjust climatic time series to compensate for the biases produced by the inhomogeneities. It is important for users of homogeneity-adjusted data to understand how the data were adjusted and what impacts these adjustments are likely to make on their analyses. And it is important for developers of homogeneity-adjusted data sets to compare readily the different techniques most commonly used today. Therefore, this paper reviews the methods and techniques developed for homogeneity adjustments and describes many different approaches and philosophies involved in adjusting in situ climate data. (C) 1998 Royal Meteorological Society.

Global warming is likely to cause a progressive drought increase in some regions, but how population and natural resources will be affected is still underexplored. This study focuses on global population and land-use (forests, croplands, pastures) exposure to meteorological drought hazard in the 21st century, expressed as frequency and severity of drought events. As input, we use a large ensemble of climate simulations from the Coordinated Regional Climate Downscaling Experiment, population projections from the NASA-SEDAC dataset, and land-use projections from the Land-Use Harmonization 2 project for 1981-2100. The exposure to drought hazard is presented for five SSPs (SSP1-SSP5) at four Global Warming Levels (GWLs, from 1.5 to 4 degrees C). Results show that considering only Standardized Precipitation Index (SPI; based on precipitation), the combination SSP3-GWL4 projects the largest fraction of the global population (14%) to experience an increase in drought frequency and severity (vs. 1981-2010), with this value increasing to 60% if temperature is considered (indirectly included in the Standardized Precipitation-Evapotranspiration Index, SPEI). With SPEI, considering the highest GWL for each SSP, 8 (for SSP2, SSP4, and SSP5) and 11 (SSP3) billion people, that is, more than 90%, will be affected by at least one unprecedented drought. For SSP5 (fossil-fuelled development) at GWL 4 degrees C, approximately 2 center dot 10(6) km(2) of forests and croplands (respectively, 6 and 11%) and 1.5 center dot 10(6) km(2) of pastures (19%) will be exposed to increased drought frequency and severity according to SPI, but for SPEI, this extent will rise to 17 center dot 10(6) km(2) of forests (49%), 6 center dot 10(6) km(2) of pastures (78%), and 12 center dot 10(6) km(2) of croplands (67%), with mid-latitudes being the most affected areas. The projected likely increase of drought frequency and severity significantly increases population and land-use exposure to drought, even at low GWLs, thus extensive mitigation and adaptation efforts are needed to avoid the most severe impacts of climate change.

An air transport climatology is derived for subtropical southern Africa (Africa south of 15 degrees S) by classifying daily synoptic situations into predominant circulation types. The annual variation of these provides the basis for determining month-by-month transport. Percentage zonal transport in easterly and westerly directions, levels of transport, and times of transit are derived from forward trajectory analyses using European Centre for Medium-range Weather Forecasts (ECMWF) data for a 7-year period. It is shown that semi-permanent subtropical continental anticyclones, transient mid-latitude ridging anticyclones and midlatitude westerly disturbances produce major transport into the south-western Indian Ocean in the Natal plume. Only quasistationary tropical easterly waves result in appreciable transport into the tropical South Atlantic Ocean in the Angolan plume. Total transport is a function of circulation type and frequency, as well as plume dimensions. Transport in continental highs follows an annual cycle reaching peak values in excess of 70 per cent in winter. That in easterly waves also exhibits an annual cycle, but one peaking in summer, when up to 55 per cent transport may occur in north-western regions. Transport in ridging highs and westerly perturbations is much less and occurs throughout the year, with a slight tendency to peak in spring. Recirculation of air is shown to be considerable when anticyclonic conditions prevail. Monthly, seasonal, and annual mass fluxes over and out of southern Africa are determined from transport fields, frequency of occurrence of circulation types and from measurements of aerosol concentrations. An annual mass flux of aerosols some 134 Mtons is generated over the subcontinent. About 60 Mtons year(-1) are deposited, and approximately 29 Mtons year(-1) are exported westward over the Atlantic Ocean and 45 Mtons year(-1) eastward over the Indian Ocean. Twenty-six million tons of the 74 Mtons of aerosols exported annually to the adjacent oceans on each coast are a product of recirculation. Deposition within 10 degrees latitude of the coast is nearly 10 times greater on the east than on the west coast.