Monthly Anomalies Research Articles

Effects of macro-circulation on local climatic conditions of plant development

Agricultural or ecological impact studies, related to future climate changes, require highly resolved meteorological input data both in space and time. Since present climate models can not fulfill this requirement, gaps between the necessary and available resolution, are filled by downscaling. A possible way to downscale GCM-output fields into regional climate scenarios can be to consider the changes in the frequency distribution of model-generated macro-circulation types and to combine them with conditional climatology of each macro-type. This approach can be successful, if a great part of local climate anomalies is connected to frequency anomalies of the macro-types. To test this assumption, a diagnostic method for separation of the local climate anomalies into circulation and non-circulation (physical) factors, allowing a mixed term, is developed, applying the subjective classification of pressure patterns by Péczely (1957). Results for monthly and seasonal anomalies of precipitation and temperature are presented for Debrecen, Hungary (47°N, 21°E). The investigated period is 30 years from 1966 to 1995. The main feature of the results is the secondary role of the macro-circulation factor. This conclusion is formulated from the comparison of contributions by these terms to moderate and extreme anomalies; to the standard deviation and to long-term variations; and also from the correlation between the three terms and their sum, i.e. the monthly anomaly. It is impossible, however, to consider this circulation term as the maximum information contained by a series of macro-types, because the succession of macro-types and conditional relation of the local weather on different days of a given type is not taken into account by the given separation. On the other hand, the circulation term exhibits fair statistical relation to the physical term and also to the whole anomaly in many cases, which is promising considering further improvement of this approach to downscaling based on frequency of macro-synoptic types.

An assessment of three alternatives to linear trends for characterizing global atmospheric temperature changes

Historical changes in global atmospheric temperature are typically estimated using simple linear trends. This paper considers three alternative simple statistical models, each involving breakpoints (abrupt changes): a flat steps model, in which all changes occur abruptly; a piecewise linear model; and a sloped steps model, incorporating both abrupt changes and slopes during the periods between breakpoints. First‐ and second‐order autoregressive models are used in combination with each of the above. Goodness of fit of the models is evaluated using the Schwarz Bayesian Information Criterion. These models are applied to the instrumental record of global monthly temperature anomalies at the surface and to the radiosonde and satellite records for the troposphere and stratosphere. The alternative models often provide a better fit to the observations than the simple linear model. Typically the two top‐performing models have very close values of the Schwarz Bayesian Information Criterion. Usually the two models have the same basic form and the same net temperature change but with a different choice of autoregressive model. However, in some cases the best fits are from two different basic models, yielding different net temperature changes and suggesting different interpretations of the nature of those changes. For the surface data during 1900–2002 the sloped steps and piecewise linear models offer the best fits. Results for tropospheric data suggest that it is reasonable to consider most of the warming during 1958–2001 to have occurred at the time of the abrupt climate regime shift in 1977. Two fundamentally different, but equally valid, descriptions of stratospheric cooling were found: gradual linear change versus more abrupt ratcheting down of temperature concentrated in postvolcanic periods (∼2 years after eruption). Because models incorporating abrupt changes can be as explanatory as simple linear trends, we suggest consideration of these alternatives in climate change detection and attribution studies.

Hydrographic and transport variability on the Halifax section

Archived data and geostrophic computations are used to examine variability in hydrographic properties and along‐shelf transport on the Scotian Shelf, with focus on the Halifax section and a decadal‐scale hydrographic anomaly during the late 1950s and early/mid 1960s. The long‐term annual cycle shows strong seasonal variations in baroclinic transport on the inner shelf and at the shelf edge, and an associated steric change in adjusted sea level (ASL) at Halifax. Regional wind‐forcing and barotropic currents make smaller contributions to the annual cycle in ASL. In contrast, regional wind‐forcing contributes about 40% of the ASL variability for periods of 6–30 days. Hydrographic sections indicate that the 1950s/1960s anomaly arose from episodic extensions of Labrador Slope Water along the shelf edge followed by on‐shelf intrusions, primarily during the fall‐spring periods of 1958–1959 and 1963–1964. It ended with excursions of Warm Slope Water into the region in 1967–1968. An analysis of monthly temperature anomalies indicates that slope temperatures can account for 50% of the variance of deep shelf temperatures 3–6 months later. Correlations between the hydrographic and baroclinic transport variations indicate increased southwestward flow associated with lower temperatures and salinities, but no evidence was found for large local current events at the onset and termination times of the 1950s/1960s anomaly. Positive correlations between wind‐adjusted ASL and steric anomalies point to the potential for sea level being helpful in monitoring baroclinic transport variability.

Possible Change of Extratropical Cyclone Activity due to Enhanced Greenhouse Gases and Sulfate Aerosols—Study with a High-Resolution AGCM

To investigate the possible impacts of enhanced greenhouse gases and sulfate aerosols on extratropical cyclone activity, two 20-yr time-slice experiments—the control run and the global warming run—are performed with a high-resolution AGCM (T106) of the Japan Meteorological Agency. In the control run, the atmosphere is forced by the observed SST and sea ice of 1979–98 and present-day CO2 and sulfate aerosol concentrations. In the global warming run, the atmosphere is forced by the observed SST and sea ice of 1979–98 plus the monthly mean anomalies of SST and sea ice at about the year 2050 obtained from a transient climate change experiment with the Geophysical Fluid Dynamics Laboratory (GFDL) coupled ocean–atmosphere model with a low resolution of R15. The equivalent amounts of CO2 and sulfate aerosol concentrations at about the year 2050 as used in the GFDL R15 model are prescribed. First, the performance of the high-resolution AGCM (T106) in reproducing the extratropical cyclone activity of both hemispheres in the control run is examined—by comparing the cyclone activities simulated in the AGCM and those analyzed from the NCEP–NCAR reanalysis data of the same period from 1979 to 1998. An objective cyclone identification and tracking algorithm is used to analyze the cyclone activity. The results show that the model can reproduce the cyclone activity reasonably well. Second, the possible change in cyclone activity due to enhanced greenhouse gases and sulfate aerosols is examined. The main results are summarized as follows. 1) The total cyclone density (number of cyclones in a 4.5° × 4.5° area per season) tends to decrease significantly in the midlatitudes of both of the Northern and Southern Hemispheres during the December–January–February (DJF) and June–July–August (JJA) seasons. The decrease of cyclone density in the midlatitudes of both of the Northern and Southern Hemispheres in the DJF season is about 7%. In the JJA season, the decreases of cyclone density in the Northern and Southern Hemispheres' midlatitudes are about 3% and 10%, respectively. 2) Although weak and medium-strength cyclones decrease, the density of strong cyclones increases by more than 20% in the Northern Hemisphere in JJA and in the Southern Hemisphere in both DJF and JJA. 3) The density of strong cyclones in the Northern Hemisphere summer (JJA) increases over the eastern coasts of Asia and North America. In the Southern Hemisphere, the density of strong cyclones increases over the circumpolar regions around Antarctica in both summer (DJF) and winter (JJA) seasons. The density of strong cyclones also increases over the southeastern coasts of South Africa and South America. Finally, the possible reasons for the change in cyclone activity due to enhanced greenhouse gases and sulfate aerosols are examined. It is shown that the changes in the extratropical cyclone activity are closely linked to the changes in the baroclinicity in the lower troposphere, which are mainly related to the changes in the horizontal and vertical temperature distributions in the atmosphere due to enhanced greenhouse gases and sulfate aerosols. It is shown that, in the Northern Hemisphere midlatitudes, the decrease of baroclinicity is mainly caused by the decrease of meridional temperature gradient, while in the Southern Hemisphere midlatitudes, the decrease of baroclinicity is mainly caused by the increase of static stability caused by the enhanced greenhouse gases and sulfate aerosols.

Forced Rossby wave in the northern South China Sea

Time-longitude diagrams of monthly anomalies of TOPEX/Poseidon sea surface height (SSH), Levitus steric height, COADS wind stress curl, as well as meridional surface wind averaged over the northern South China Sea (SCS) from 18° to 22°N, exhibit a coherent westward phase propagation, with a westward propagation speed of about 5 cm s −1. The consistency between oceanic and atmospheric variables indicates that there is a forced Rossby wave in the northern SCS. The horizontal patterns of monthly SSH anomalies from observations and model sensitivity experiments show that the forced Rossby wave, originating to the northwest off Luzon Island, actually propagates west-northwestward towards the Guangdong coast because of zonal migration of the meridional surface wind. The winter Luzon Cold Eddy (LCE), which has been found from field observations, can be identified as a forced Rossby wave with a negative SSH anomaly in winter. It corresponds to strong upwelling and a negative temperature anomaly. Sensitivity experiments show that the wind forcing controls the generation of the LCE, while the Kuroshio is of minor importance.

Embedding sea surface temperature anomalies into the stock recruitment relationship of red mullet (<i>Mullus barbatus</i> L. 1758) in the Strait of Sicily

SUMMARY: In the Strait of Sicily, red mullet (Mullus barbatus L. 1758) is one of the most important resources for the bottom trawlers exploiting the shelf fishing grounds. At present, the younger age groups (groups 0-1) represent most of the catches. In order to give more effective advice for fisheries management in the area, this paper is aimed at further investigating the stock-recruitment relationship for red mullet by including environmental information. Indices of the mean abundance of red mullet older than 1 year (spawners) and younger (recruits) were obtained from autumn trawl survey samples by analyzing the length-frequency distributions. Sea surface temperature (SST), expressed as the average monthly anomalies over the period from May to September (referring to 1961-90 climatology), was considered as a proxy for oceanographic processes affecting recruitment. An exploratory analysis was performed using three stock-recruitment relationships (Cushing, Ricker and Beverton-Holt), with and without the effect of SST. The best fit (R 2 =0.80) was obtained with a Ricker modified curve (lnR = ln(70.17113) + lnS ‐ 0.063812S + 0.060544(S · E)), including SST anomalies in July and August as a masking factor. Results showed that, for a given spawning stock level, higher recruitment levels corresponded to warmer than average SST in early life stages.

지구환경 변화와 관련된 한국 연근해 해양 이상변동

Oceanographic features around Korean waters related to the global change were studied by analysis of the longterm variation of water temperature, dissolved oxygen, sea level of the surface layer with 1<TEX>$^{\circ}C$</TEX> temperature, spatial position of the subpolar front in the East Sea/Japan Sea (the East sea hereafter) and the Wolf Sunspot Number. With the global warming, the temperature of Korean waters has been increased 0.5∼1.0<TEX>$^{\circ}C$</TEX> for 33years (1968∼2000). In case of the dissolved oxygen in the East Sea has been decreased 0.46<TEX>$m\ell$</TEX>/<TEX>$\ell$</TEX>. Year to year vertical fluctuations of the monthly anomalies of the surface layer with 1<TEX>$^{\circ}C$</TEX>water in the East Sea have predominant periods with 15years as the longterm variation of Arctic climate, 12 and 18years as the El Nino-Southern Oscillation. Spatial position of the subpolar front in the East Sea moved to northern part of the sea from the southern part of the sea with the increasing sea surface temperature. The relationship between the number of Wolf Sunspot and the anomalies of sea surface temperature was very closer after the late of 1980s than those before the early of 1980s in Korean waters.

Mesospheric ozone response to changes in water vapor

Observations made by the Upper Atmosphere Research Satellite (UARS) now extend in time for almost a decade and allow for an improved understanding of seasonal and interannual variations of middle atmospheric minor constituents. In particular, measurements of mesospheric ozone and water vapor made by the UARS Halogen Occultation Experiment (HALOE) reveal significant seasonal and decadal variability. At midlatitudes, the observed variation in water vapor is primarily an annual cycle that peaks in summertime driven by changes in the residual circulation. In contrast to earlier satellite observations, HALOE ozone sunset observations also have an annual cycle that is anticorrelated with the water vapor cycle. The anticorrelation is a consequence of water vapor photolysis producing hydrogen species that destroy ozone. However, HALOE sunrise observations of ozone show no seasonal cycle. Analysis of monthly anomalies between 1991 and 2001 show a long‐term water vapor increase of approximately 1%/year. The observed response of ozone depends on altitude and time of day and is strongly negative (up to −4%/year) for sunset observations around 80 km. Again, the response of ozone at sunrise is minimal. Sensitivity tests using a three‐dimensional global chemical transport model show good agreement with the observations and confirm that the observed decrease in sunset ozone is a response to increasing water vapor.

Development and validation of a high-resolution monthly gridded temperature and precipitation data set for Switzerland (1951-2000)

A 5 km gridded temperature and precipitation data set was constructed for the topo- graphically complex region of Switzerland in the European Alps. The data set consists of 1961-1990 mean fields for monthly mean temperature (T -- ) and monthly total precipitation (P -- ), plus monthly anomaly fields ∆T and ∆P for 1951-2000. All data are point estimates and come with extensive statis- tics on interpolation errors as a function of geographical location, elevation and time of the year. A novel interpolation method was employed that accounted for possible orographic effects at different spatial scales and allowed for regionally and seasonally varying relief-climate relationships. The accuracy of the interpolations was quantified by means of cross-validation. The proposed method was found to be superior to linear regression employing elevation as the only predictor for P- , and better than inverse distance weighting (IDW) interpolation for September to February ∆T. It was worse than IDW interpolation for springtime ∆T and for March to September ∆P. The areal mean cross-validation errors obtained for the new method were generally close to zero. The annually averaged mean absolute error for T -- was 0.6°C and for P- it was 10.5 mm mo -1 (or 11%). The average proportion of temporal variance explained by the cross-validated monthly 1951-2000 station time series was 89% for ∆T and 81% for ∆P. The average proportion of spatial variance of the monthly anomaly fields explained was 13% for ∆T and 40% for ∆P. The largest cross-validation errors were generally found at regions of lower station density in south-southeast Switzerland and at elevations above ~2000 m above sea level. All error variances showed distinct annual cycles. The ∆T and ∆P fields and the derived trend fields showed substantial small-scale variability, which was not well reproduced and deserves further study. The individual gridpoint estimates should therefore be interpreted with care.

Global-scale Trend Estimation for Temperature and Precipitation

the spatial variability with an explicit treatment of elevation. Seeon~L Combining this mean field with the grids of monthly anomalies relative to the standarld pormal period of ( 1 96 1-1990). [New et al 1999] which depends more on the large-scale circulation pattem than physiographic control and therefore require less extensive network to bc described [New et al. 2000] . This approach have the advantages of using the more extensive network of stations giving nonnal in comparison to time series, and the use of elevation as a

Macroscale water fluxes 1. Quantifying errors in the estimation of basin mean precipitation

Developments in analysis and modeling of continental water and energy balances are hindered by the limited availability and quality of observational data. The lack of information on error characteristics of basin water supply is an especially serious limitation. Here we describe the development and testing of methods for quantifying several errors in basin mean precipitation, both in the long‐term mean and in the monthly and annual anomalies. To quantify errors in the long‐term mean, two error indices are developed and tested with positive results. The first provides an estimate of the variance of the spatial sampling error of long‐term basin mean precipitation obtained from a gauge network, in the absence of orographic effects; this estimate is obtained by use only of the gauge records. The second gives a simple estimate of the basin mean orographic bias as a function of the topographic structure of the basin and the locations of gauges therein. Neither index requires restrictive statistical assumptions (such as spatial homogeneity) about the precipitation process. Adjustments of precipitation for gauge bias and estimates of the adjustment errors are made by applying results of a previous study. Additionally, standard correlation‐based methods are applied for the quantification of spatial sampling errors in the estimation of monthly and annual values of basin mean precipitation. These methods also perform well, as indicated by network subsampling tests in densely gauged basins. The methods are developed and applied with data for 175 large (median area of 51,000 km2) river basins of the world for which contemporaneous, continuous (missing fewer than 2% of data values), long‐term (median record length of 54 years) river discharge records are also available. Spatial coverage of the resulting river basin data set is greatest in the middle latitudes, though many basins are located in the tropics and the high latitudes, and the data set spans the major climatic and vegetation zones of the world. This new data set can be applied in diagnostic and theoretical studies of water balance of large basins and in the evaluation of performance of global models of land water balance.

The Influence of ENSO in the Flows of the Upper Paraná River of South America over the Past 100 Years

Abstract The Upper Parana River is the main tributary of the La Plata River basin, the second largest in South America, contributing with an annual mean flow of 12 000 m3 s−1 to more than one-half of the total water flowing in the La Plata River system. The Parana River has a relevant importance in the region for transportation and hydroelectricity generation. This paper studies the influence of ENSO on the monthly flows measured at Posadas (27°23′S, 55°53′W) during the period of 1901–97. The original data are converted into standardized monthly anomalies, and the annual cycle is removed. Two data subsets are generated: a first group includes the years of warm ENSO events, or El Nino, and the second group includes the years of cold ENSO events, or La Nina. The elements of the subsets are composites of 24 consecutive months starting in January of the year when the ENSO event begins and ending in December of the following year. The results show that the averaged flows observed during El Nino events are alwa...

The sensitivity of subannual and intraseasonal tropical variability to model ocean mixed layer depth

The influence of air‐sea interaction on subannual and intraseasonal tropical variability is explored through analysis of three long simulations of the Commonwealth Scientific and Industrial Research Organisation atmospheric general circulation model (GCM) with differing ocean specifications: a coupled ocean GCM, a simple 50‐m mixed layer model, or climatological sea surface temperatures (SST); together with 50‐year simulations with mixed layer depths of 10 m and 20 m. The analysis focuses initially on a signal similar to a Madden‐Julian Oscillation (MJO) contained in the first two empirical orthogonal functions (EOF) of monthly anomalies of tropical 807‐hPa winds in January in the coupled model. Time‐lag regression is used to demonstrate that these patterns propagate eastward, although at only half the speed of the MJO, and induce perturbations to the Australian monsoon. The specified SST model shows no such propagation. Similar results are then obtained using daily data filtered to retain subannual periods. The eastward propagation speed is faster in the shallower mixed layer cases, with the 10‐m case producing speeds close to observations. In the interactive models, surface energy fluxes force SST anomalies propagating ahead of the EOF convergence. These fluxes are largely consistent with evaporation perturbed by wind anomalies to the monsoon westerlies, augmented by solar radiation. The SST anomalies then further perturb the winds, as is confirmed by a separate SST perturbation experiment. From the examination of other seasons, it is seen that air‐sea interaction generally enhances the amplitude of the MJO‐like patterns. It also enhances their eastward propagation along westerly wind bands. Analysis of zonal wave number one winds confirms the strong sensitivity to mixed layer depth in the amplitude and period of the eastward propagating component, particularly during September through February. The results suggest that air‐sea interaction may be important to the MJO, provided that the SSTs are sufficiently responsive to the atmospheric patterns.

Statistical Modeling of Monthly Anomalies of Atmospheric Precipitations for the Region of the Ukraine and Black Sea

The data array accumulated for the period 1946–1995 is used to select the most significant predictor of monthly anomalies of precipitation in the region of the Ukraine and Black Sea, namely, a large-scale circulation in a sector covering the North Atlantic and Europe. Three large-scale predictors (geopotential at a level of 500 GPa, sea-level pressure, and the difference between the geopotentials at levels of 500 and 1000 GPa) give almost identical results: their correlation with anomalies of precipitation is equal to 0.7–0.8 in winter and 0.4–0.5 in summer. The predominant mechanism of the influence of circulation on precipitations at low frequencies is the response of the trajectories of European cyclones to changes in the upper-tropospheric jet currents in the Atlantic-European sector described as the superposition of the North-Atlantic oscillation and the Eurasian mode. The decomposition of the fields of precipitations and circulation in the eigenmodes of the canonical correlation analysis opens a possibility of direct computation of the monthly average fields of precipitations for the entire territory of the Ukraine and Black Sea region according to the large-scale geopotential fields.

An analysis of simulated and observed global mean near-surface air temperature anomalies from 1979 to 1999: trends and attribution of causes

The 1979–1999 response of the climate system to variations in solar spectral irradiance is estimated by comparing the global averaged surface temperature anomalies simulated by a 2-D energy balance climate model to observed temperature anomalies. We perform a multiple regression of southern oscillation index and the individual model responses to solar irradiance variations, stratospheric and tropospheric aerosol loading, stratospheric ozone trends, and greenhouse gases onto each of five near-surface temperature anomaly data sets. We estimate the observed difference in global mean near-surface air temperature attributable to the solar irradiance difference between solar maximum and solar minimum to be between 0.06 and 0.11 K, and that 1.1–3.8% of the total variance in monthly mean near-surface air temperature data is attributable to variations in solar spectral irradiance. For the five temperature data sets used in our analysis, the trends in raw monthly mean temperature anomaly data have a large range, spanning a factor of 3 from 0.06 to 0.17 K/decade. However, our analysis suggests that trends in monthly temperature anomalies attributable to the combination of greenhouse gas, stratospheric ozone, and tropospheric sulfate aerosol variations are much more consistent among data sets, ranging from 0.16 to 0.24 K/decade. Our model results suggest that roughly half of the warming from greenhouse gases is cancelled by the cooling from changes in stratospheric ozone. Tropospheric sulfate aerosol loading in the present day atmosphere contributes significantly to the net radiative forcing of the present day climate system. However, because the change in magnitude and latitudinal distribution of tropospheric sulfate aerosol has been small over the past 20 years, the change in the direct radiative forcing attributable to changes in aerosol loading over this time is also small.

Using the Special Sensor Microwave Imager to Monitor Surface Wetness

The frequencies flown on the Special Sensor Microwave Imager (SSM/I) are sensitive to liquid water near the earth’s surface. These frequencies are primarily atmospheric window channels, which receive the majority of their radiation from the surface. Liquid water near the surface depresses the emissivity as a function of wavelength. The relationship between brightness temperatures at different frequencies is used to dynamically derive the amount of liquid water in each SSM/I observation at 1/38 resolution. These data are averaged at 18 resolution throughout the globe for each month during the period of 1992‐97, and the 6-yr monthly means and the monthly anomalies of the wetness index are computed from this base period. To quantify the relationship between precipitation and surface wetness, these anomalies are compared with precipitation anomalies derived from the Global Precipitation Climate Program. The analysis was performed for six agricultural regions across six continents. There is generally a good correspondence between the two variables. The correlation generally increases when the wetness index is compared with precipitation anomalies accumulated over a 2-month period. These results indicate that the wetness index has a strong correspondence to the upper layer of the soil moisture in many cultivated areas of the world. The region in southeastern Australia had the best relationship, with a correlation coefficient of 0.76. The Sahel, France, and Argentina showed that the wetness index had memory of precipitation anomalies from the previous months. The memory is shorter for southeastern Australia and central China. The weakest correlations occurred over the southeastern United States, where the surface is covered by dense vegetation. The unique signal, strengths, and weaknesses of the wetness index in each of the six study regions are discussed.

An East Coast Winter Storm Climatology

A climatology of East Coast winter storms (ECWS) was developed using an automated procedure. This routine was used along with the NCEP–NCAR reanalysis dataset (1948, 1951–97) to identify storms over the October–April winter season. An array of statistical analyses was used to empirically analyze the interannual variability of these cyclones. To be classified as an ECWS, an area of low pressure was required to have a closed circulation, be located along the east coast of the United States (within the quadrilateral bounded at 45°N by 65° and 70°W and at 30°N by 75° and 85°W), show general movement from the south-southwest to the north-northeast, and contain winds greater than 10.3 m s−1 (20 kt) for at least one time period (6 h). Storms meeting the above criteria were also required to have a closed circulation and be located within the quadrilateral during one additional 6-h period (not necessarily consecutive with the first). On average, 12 ECWS occurred per season with a maximum in January. Significant trends in storm frequency over the 46-yr period beginning in 1951 are not evident. However, a marginally significant (α = 0.10) increase in average storm minimum pressure is noted. Spectral analysis of the ECWS time series shows significant cycles with periods of 2.3, 2.8, 3.4, 4.8, and 10.2 yr, which are in agreement with documented periodicities in joint Atlantic SST and sea level pressure data. Average monthly ECWS frequency anomalies are significantly higher during El Niño months when compared to neutral months over the October–April storm season. ECWS show little or no change in frequency anomalies during La Niña months.

New Zealand wave climate from satellite observations

Wave data derived from radar altimeters carried on four satellite missions are combined into a wave climatology for New Zealand waters. These data provide extensive observations of wave conditions around New Zealand, where the paucity of measurements has previously hindered definition of the wave climate. The data span the period 1985 to the present with the exception of a 2‐year gap in 1989–91. The spatial distribution of the long‐term mean of significant wave heights (SWH) indicates a strong latitudinal variation in the south‐west Pacific, with values of over 4 m at latitudes of 50–60°S and under 2.5 m towards the tropics. The shadowing of New Zealand is quite marked; a result of the dominant contribution of south‐westerly wave events. The annual range of the mean SWH also varies over the region; within 0.6 m in the north and 1.3 m in the south. A principal component analysis of the monthly anomalies in mean SWH identifies spatial patterns of variation. Some components vary with the local wind more than others suggesting that some anomalies are associated with wind sea and some with swell. Some patterns also appear to vary with the Southern Oscillation Index and can be related to the wind anomalies associated with El Nino events. Frequency distributions of SWH are also determined, and it is noted that in the north of the region the spatial pattern of the high waves differs considerably from the means.

Coupled Rossby Waves in the Indian Ocean on Interannual Timescales

Abstract Gridded fields of TOPEX/Poseidon sea level height (SLH) from 1993 to 1998 and National Centers for Environmental Prediction sea surface temperature (SST) and meridional surface wind (MSW) anomalies from 1970 to 1998 are used to examine coupled Rossby waves in the Indian Ocean from 10°S to 30°S. Time–longitude diagrams of monthly SLH, SST, and MSW anomalies yield significant peak spectral energy density in propagation wavenumber–frequency spectra for westward propagating waves of >2 yr period and >4000 km wavelength. Subsequent low-pass filtering of SLH, SST, and MSW anomalies for these interannual timescales >2 yr finds them propagating westward over the Indian Ocean in fixed phase with one another at speeds significantly less (0.04–0.07 m s−1) than first-mode baroclinic Rossby waves, taking 3 to 4 years to cross the basin. These coupled Rossby waves display weak beta refraction patterns in all three variables. Significant squared coherence between interannual SLH and SST (SST and MSW) anomalies ...

Comparison of Tropospheric Temperatures from Radiosondes and Satellites: 1979–98

A comprehensive comparison is made between two tropospheric temperature datasets over the period 1979–98: the most recent and substantially revised (version d) microwave sounding unit (MSU) channel 2 data retrievals, and a gridded radiosonde analysis provided by the Hadley Centre of the U.K. Meteorological Office. The latter is vertically weighted to approximate the deep layer temperatures measured by the satellite data. At individual grid points, there is good overall agreement among monthly anomalies, especially over the Northern Hemisphere continents where the climate signal is large, although monthly root-mean-square (rms) differences typically exceed 0.6°C. Over the Tropics, correlations are lower and rms differences can be as large as the standard deviations of monthly anomalies. Differences in the gridpoint variances are significant at many locations, which presumably reflects sources of noise in one or both measurement systems. It is often argued for climate purposes that temperature anomalies are...