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Two-year-long simulations of the atmosphere and ocean by the Commonwealth Scientific and Industrial Research Organisation's (CSIRO) Climate Analysis Forecast Ensemble (CAFE) modelling system are analysed, with a focus on Indo-Pacific sea surface temperature (SST) climate drivers and their teleconnection to Australian rainfall. The simulations are 11-member ensemble forecasts (strictly, hindcasts) initiated each month from 2002 to 2015, supplemented by a 100-year-long control simulation. Using correlations r between seasonal and annual means, it is shown that the links between the interannual variations of All-Australia precipitation (AApr) and the standard driver indices, together with the Pacific-Indian Dipole (PID), are mostly similar to those derived from observational data. The vertically integrated meridional flux of moisture towards northern Australia is linked to both the SSTs and AApr. Correlations between ensemble averages and observations are used as a measure of forecast skill, calculated for each start month and for lead time after start. Positive correlations hold over the first year for much of the low-latitude Pacific and for the drivers. The forecasts become more skillful than persistence, with r for PID averaging 0.3 higher over lead times of 7–13 months. The forecast of seasonal AApr has moderate to good correlations (r 0.4–0.8) for seasons centred on September–February. This is largely consistent with skill in both the flux and in the SST drivers. Correlations are also good for 1-year and 2-year means. This apparent skill is currently being explored using a new larger suite of CAFE forecasts.

The CSIRO Climate retrospective Analysis and Forecast Ensemble system: version 1 (CAFE60v1) provides a large (96 member) ensemble retrospective analysis of the global climate system from 1960 to present with sufficiently many realizations and at spatio-temporal resolutions suitable to enable probabilistic climate studies. Using a variant of the ensemble Kalman filter, 96 climate state estimates are generated over the most recent six decades. These state estimates are constrained by monthly mean ocean, atmosphere and sea ice observations such that their trajectories track the observed state while enabling estimation of the uncertainties in the approximations to the retrospective mean climate over recent decades. For the atmosphere, we evaluate CAFE60v1 in comparison to empirical indices of the major climate teleconnections and blocking with various reanalysis products. Estimates of the large scale ocean structure, transports and biogeochemistry are compared to those derived from gridded observational products and climate model projections (CMIP). Sea ice (extent, concentration and variability) and land surface (precipitation and surface air temperatures) are also compared to a variety of model and observational products. Our results show that CAFE60v1 is a useful, comprehensive and unique data resource for studying internal climate variability and predictability, including the recent climate response to anthropogenic forcing on multi-year to decadal time scales.

Recent studies have shown that regardless of model configuration, skill in predicting El Niño–Southern Oscillation (ENSO), in terms of target month and forecast lead time, remains largely dependent on the temporal characteristics of the boreal spring predictability barrier. Continuing the 2019 study by O’Kane et al., we compare multiyear ensemble ENSO forecasts from the Climate Analysis Forecast Ensemble (CAFE) to ensemble forecasts from state-of-the-art dynamical coupled models in the North American Multimodel Ensemble (NMME) project. The CAFE initial perturbations are targeted such that they are specific to tropical Pacific thermocline variability. With respect to individual NMME forecasts and multimodel ensemble averages, the CAFE forecasts reveal improvements in skill when predicting ENSO at lead times greater than 6 months, in particular when predictability is most strongly limited by the boreal spring barrier. Initial forecast perturbations generated exclusively as disturbances in the equatorial Pacific thermocline are shown to improve the forecast skill at longer lead times in terms of anomaly correlation and the random walk sign test. Our results indicate that augmenting current initialization methods with initial perturbations targeting instabilities specific to the tropical Pacific thermocline may improve long-range ENSO prediction.

Atmospheric moisture is perturbed during ENSO variation, as can be quantified using regression with ENSO indices. Seasonal and annual anomalies of the water column, horizontal moisture flux, surface evaporation, rainfall, and other basic variables, associated with the sea-surface temperature indices NINO34 and Pacific-Indian Dipole are evaluated from ERA5 reanalyses over 1980-2019. The skill in the corresponding regression coefficients (at one standard deviation) from historical climate simulations by the ten (only) CMIP6 models for which the vertically integrated flux was submitted is assessed, subject to the statistical uncertainty in ENSO from 40-year series. The ten-model mean fields are encouragingly realistic, although ENSO anomalies in the equatorial Pacific extend farther westward. The future change for the period 2040-2079 under the SSP585 scenario of rising greenhouse gases is evaluated. There is generally little change in the standard deviation in the two indices or in the SST and wind anomalies. The water column, moisture flux, and rainfall anomalies tend to be amplified in the low latitudes, but with limited change in the teleconnections to higher latitudes. The climatological changes in rainfall and moisture flux resemble those of ENSO in the tropical Indo-Pacific, in part linked to a small positive shift in both the indices. Elsewhere, widespread increases in water column, evaporation, midlatitude surface pressure, and, of course, temperature are not ENSO-like. Implications for the reliability of future projected means and variability will be considered. An obvious recommendation is that the vertically integrated moisture fluxes be routinely output by climate models and be a requested variable in future CMIPs.

The changes in precipitation simulated by the 40-model CMIP5 ensemble for the Asia-Pacific region are assessed, focusing on the two periods 1986–2005 and 2080–2099 under the RCP8.5 scenario. The frequency distributions of both daily and monthly mean rain rates at model grid points in each of four seasons are considered. In spatial averages for the land domain and seven selected regions, there is both an increase in the frequency of dry days and a shift towards heavier rain. Three 20-year seasonal aggregate statistics, the mean, the top decile of monthly amounts, and top percentile of daily amounts are assessed. The percentage changes over land are on average 4% higher for monthly extremes than for the mean, and a further 10% higher for the daily extremes. Over Australia and central Indonesia in some seasons the mean decreases but daily extremes increase. In much of Asia the daily extremes increase by 30% or more. For these statistics, there is a range across the ensemble that can often be linked to a pattern of sea surface temperature change that is quantified by a Pacific-Indian Dipole (or difference, PID) index. Correlations with both mean and extreme rain are highly negative over Australia and Indonesia and moderately positive over parts of south and east Asia in some seasons. The mechanism for this is explored through additional simulations and links with water vapour path. The results provide some understanding of the range of projections of future rainfall change based on the CMIP5 results, with some potential for narrowing it.

Motivated by the wide range of projections of regional rainfall (or precipitation, pr) based on the CMIP5 ensemble of global climate models, we investigate the atmospheric moisture budget of idealized rising‐CO2 (1pctCO2) simulations from 10 models submitted to CMIP6. We use the new CMIP6 standard variables, the vertically integrated eastward and northward moisture flux, and provide a multi‐model assessment of these, their convergence (conv), along with water vapour path (prw). Seasonal climatologies of a 20‐year base climate for pr, prw, flux, and conv match well those from the ECMWF's Reanalysis 5. In addition, composites ‘H’ of quantities for months in the top decile of monthly rainfall, calculated at each model grid point, produce a field of heavy rainfall, on average double that of the mean. Spatial correlation coefficients (r) between the pr and conv fields are typically .7 in each season. This rises to .9 for the corresponding H fields, due to the important link between moisture convergence and heavy rainfall. Fields of standardized change (Δ), or change per degree of global warming, were calculated. The ensemble‐mean Δpr is only weakly correlated with the base climate pr, and likewise for conv. However, the prw change is highly correlated with the base prw, pointing to the importance of the “thermodynamic” change in that variable. Globally, the net Δconv is highly correlated with Δpr, around .9. This rises to .95 for the heavy‐rain composites. Relationships between changes in pr and other components hold at grid points also, when the individual model results are correlated. Clearly, there is a dependence in the change in pr with that in conv, particularly for heavy rainfall. Assessment of a larger ensemble from CMIP6, using the new flux variables, would improve the evaluation of these processes, and potentially allow more confident projections in future rainfall changes.

The current generation of climate models, as represented by phase 5 of the Coupled Model Intercomparison Project (CMIP5), has previously been assessed as having more skill in simulating the observed climate than the previous ensemble from phase 3 of CMIP (CMIP3). Furthermore, the skill of models in reproducing seasonal means of precipitation, temperature, and pressure from two observational datasets, quantified by the nondimensional Arcsin–Mielke skill score, appeared to be influenced by model resolution. The analysis is extended to 42 CMIP5 and 24 CMIP3 models. For the combined skill scores for six continents, averaged over the three variables and four seasons, the correlation with model grid length in the 66-model ensemble is −0.73. Focusing on the comparison with ERA-Interim data at higher resolution and with greater regional detail, correlations are nearly as strong for scores over the ocean domain as for land. For the global domain (excluding the Antarctic cap), the correlation of the overall skill score with grid length is −0.61, and it is nearly as strong for each variable. For most tests the improved averaged score of CMIP5 models relative to those from CMIP3 is largely consistent with their increased resolution. However, the improvement for precipitation and the correlations with length are both smaller if rmse is used as a metric. They are smaller again using the GPCP observational data, as the regional detail from a high-resolution model can lead to larger differences when compared to relatively smooth observational fields.

4OASIS3.2–5 coupling framework. The primary goal of the ACCESS-CM development is to provide the Australian climate community with a new generation fully coupled climate model for climate research, and to participate in phase five of the Coupled Model Inter-comparison Project (CMIP5). This paper describes the ACCESS-CM framework and components, and presents the control climates from two versions of the ACCESS-CM, ACCESS1.0 and ACCESS1.3, together with some fields from the 20 th century historical experiments, as part of model evaluation. While sharing the same ocean sea-ice model (except different setups for a few parameters), ACCESS1.0 and ACCESS1.3 differ from each other in their atmospheric and land surface components: the former is configured with the UK Met Office HadGEM2 (r1.1) atmospheric physics and the Met Office Surface Exchange Scheme land surface model version 2, and the latter with atmospheric physics similar to the UK Met Office Global Atmosphere 1.0 includ ing modifications performed at CAWCR and the CSIRO Community Atmosphere Biosphere Land Exchange land surface model version 1.8. The global average annual mean surface air temperature across the 500-year preindustrial control integrations show a warming drift of 0.35 °C in ACCESS1.0 and 0.04 °C in ACCESS1.3. The overall skills of ACCESS-CM in simulating a set of key climatic fields both globally and over Australia significantly surpass those from the preceding CSIRO Mk3.5 model delivered to the previous coupled model inter-comparison. However, ACCESS-CM, like other CMIP5 models, has deficiencies in various as pects, and these are also discussed.

Simulations of greenhouse-gas-induced climate change from the pre-industrial period to 2100 by the CSIRO (Mark 2, Mark 3), Hadley Centre (HadCM2) and Canadian (CGCM1) coupled atmosphere–ocean general-circulation models are compared with those from mixed-layer ocean (MLO) versions of the models. The effect of additional transient aerosol and ozone forcings in Mark 2 is examined. Some of the variation in the global-mean surface warming of the coupled models can be attributed to the rate of heat uptake by the subsurface ocean. Based on the effective heat-capacity diagnostic, the HadCM2 ocean retards the warming more effectively than the ocean in the other models. Much of the variation between both the coupled and MLO models is due to the differing effective sensitivity (to doubled CO2) of the models. In particular, the rapid warming after 2000 from CGCM1 relates to increasing sensitivity that is largely associated with rising feedback from the snow-free or low latitudes, according to a regional feedback analysis. The Hadley Centre model has a lower global sensitivity than Mark 2, related to the high-latitude feedback. The lowest warming, in both model versions, is from Mark 3, which has relatively low feedbacks. The addition of aerosol forcing is shown to raise the net effective sensitivity in Mark 2. A simple two-region system including horizontal heat transport based on Mark 2 is used to explore the effect of variations in forcings and feedbacks on surface warming at equilibrium. Effective sensitivity can vary by −20% to +70% compared with the standard doubled CO2 case as forcing is confined to either the low- or high-latitude regions. Choosing extreme feedbacks from the other models leads to variation from 2.7 K to 7.2 K. A two-parameter transport model, which allows poleward net flux changes consistent with HadCM2 and Mark 3, demonstrates additional variation in the global sensitivity depending on transport characteristics. Copyright © 2005 Royal Meteorological Society

This study examines the capability of the Commonwealth Scientific and Industrial Research Organisation (CSIRO) climate model in simulating the observed modes of interannual variability of the Southern Hemisphere circulation. Modes of variability in the 500-hPa geopotential height (Z500) field of the following three experiments are examined: 1) a coupled experiment, in which the atmosphere and the ocean are fully coupled, producing El Nino-Southern Oscillation (ENSO) cycles and allowing full air-sea interactions; 2) a mixed layer experiment, in which the atmosphere is coupled to an ocean mixed layer heat equation allowing limited air-sea interactions; and 3) a climatology experiment, in which the atmosphere is forced by an observed SST climatology with a fixed annual cycle, allowing no air-sea interactions. It is found that the observed modes are reasonably simulated in all three experiments, although the amplitude of the model modes is generally smaller than that of the observed. These modes include the high-latitude mode (i.e., the Antarctic Oscillation), the Pacific-South American (PSA) mode, and the wavenumber-3 mode. It is also found that the response of the mid- to high-latitude atmosphere circulation to the model ENSO forcing projects mainly onto the PSA mode. Many features of the PSA mode are similar to those associated with the Pacific-North American mode in the Northern Hemisphere. In response to these Z500 modes, the ocean produces coherent modes of variability, but the oceanic feedback effect appears to be weak. The amplitude of anomalies associated with each mode of the Z500 field in the three experiments shows little difference, suggesting that these Z500 modes can be generated by atmospheric internal dynamics alone, and that the ocean dynamics, air-sea interactions, and ENSO forcing are not essential.

Much of the variance of monthly and zonal mean zonal wind anomalies in the Southern Hemisphere troposphere can be attributed to the vacillation of a barotropic dipole-like “mode.” In four multidecadal simulations of the CSIRO general circulation model, the vacillation is also associated with variations in atmospheric temperature, surface pressure, cloud cover, rainfall, surface, and top-of-atmosphere energy fluxes, surface stresses, and ocean currents. Surface heat fluxes reach 6 W m−2 in composites of months of high value of the vacillation index. In simulations of the model that include either a mixed-layer or general circulation ocean model, these fluxes produce zonal mean SST anomalies, reaching 0.14°C at 45°S, which persist for several months. Ocean dynamics modifies this response, particularly farther south. The atmosphere then responds, although weakly, to these ocean anomalies, as is demonstrated by comparing the interacting-ocean runs with runs where SSTs follow either a climatological a...

A simple energy balance model with two parameters, an effective heat capacity and an effective climate sensitivity, is used to interpret six GCM simulations of greenhouse gas–induced global warming. By allowing the parameters to vary in time, the model can be accurately calibrated for each run. It is found that the sensitivity can be approximated as a constant in each case. However, the effective heat capacity clearly varies, and it is important that the energy equation is formulated appropriately, and thus unlike many such models. For simulations with linear forcing and from a cold start, the capacity is in each case close to that of a homogeneous ocean with depth initially 200 m, but increasing some 4.3 m each year, irrespective of the sensitivity and forcing growth rate. Analytic solutions for this linear capacity function are derived, and these reproduce the GCM runs well, even for cases where the forcing is stabilized after a century or so. The formation of a subsurface maximum in the mean o...

A climate simulation of a limited area model implemented over the Australian region is analyzed for the presence of low pressure systems that have some of the physical characteristics of tropical cyclones. The model is run at a horizontal resolution of 125 km and is nested within a GCM simulation of 10 Januarys. The model simulates those variables that are believed to be important for tropical cyclone formation reasonably well, as evaluated using Gray’s Seasonal Genesis Parameter. Objective criteria are used to detect tropical cyclone-like vortices (TCLVs) in the model. The composite structure of the simulated storms and the life cycle of a typical TCLV are described. Like tropical cyclones, the simulated TCLVs have warm cores, low-level wind maxima, and their tracks and regions of occurrence are similar to those observed for tropical cyclones. In general, the TCLVs simulated by the limited area model are weaker than observed, as determined by a measure of the area-averaged low-level tangential w...

The extent of agreement amongst current global climate models (GCMs) on the global pattern of rainfall change simulated under enhanced greenhouse conditions is assessed. We consider the results of five experiments which use a simple mixed layer ocean formulation and five which use a fully dynamic ocean model (‘coupled experiments’). For many regions of the northern hemisphere there is strong agreement amongst both mixed layer and coupled experiments on the sign of simulated rainfall change. However, in the southern hemisphere there are large, and apparently systematic, differences between the coupled and mixed layer experiments. In particular, whereas the mixed layer experiments agree on simulated rainfall increase in summer in the tropics and subtropics of the Australian sector, the coupled experiments agree (although more weakly) on rainfall decreases. These differences appear to relate to the much reduced warming simulated by the coupled experiments in the high latitudes of the southern hemisphere. However, recent oceanographie evidence suggests that this suppressed warming may be considerably overestimated. We conclude therefore that despite the in-principle advantages of coupled models, it may be too soon to base some regionally specific climate change scenarios solely on the results of coupled experiments.

Gray's seasonal genesis parameter (SGP) is reassessed as a diagnostic quantity for both climatological and single-season tropical cyclogenesis. The SGP applied to global analyses from recent years is able to locate the regions of genesis activity during 1967–86. The SGP based on the climatology of a simulation by the CSIR09 atmospheric model using prescribed ocean temperatures for 1979–88 has similar skill. The SGP applied to single-season means is then assessed as a diagnostic for interannual variation of cyclogenesis. Increased cyclogenesis in the central Pacific during the 1982/83 El Nino coincides with increased SGP. CSIRO9 simulated similar variations in the SGP. Moderate correlations are found between the time series of the observed and inferred simulated cyclogenesis numbers in the central Pacific, eastern North Pacific, and North Atlantic regions during 1979–88. However, elsewhere the correlations were poor.

A synoptic climatological evaluation of the output of the CSIRO nine-level model shows differences from the climatology derived by Kidson from ECMWF analyses for 1980–1988. The model climatology includes more days with winds from the westerly quarter, and fewer anticyclones are found to the south and south-east of New Zealand. The difference in climate between the single and doubled CO2 runs was relatively small using the synoptic classes derived from the ECMWF analyses, and an alternative set of daily classifications was obtained from the model data. Significant differences between the single and doubled CO2 runs were then apparent, particularly in the winter season. The number of highs to the west of New Zealand decreased and both cyclonic and anticyclonic south-west flow on to the country increased. Mean departures in the climatic elements were obtained for days in which a good match was obtained between the model-derived synoptic classes and ECMWF analyses. These suggested that more rain should fall on the south and west of the country with increasing CO2. Relative to the overall warming trend, minimum temperatures may be a little higher in the central and western North Island and maximum temperatures lower in the south of the South Island and higher in the east of the North Island. Bright sunshine may decline slightly, and more wind is expected over the North Island.

The Gray Yearly Genesis Parameter (YGP) is an empirical diagnostic tool used to infer regions in which necessary (but not sufficient) conditions exist for tropical cyclone development. This parameter is used here as a measure of the implied tropical cyclone frequency and area of occurrence in climate simulations generated by a General Circulation Model (GCM). In a simulation of the current climate, the CSIRO9 GCM shows reasonable agreement with the original Gray climatology. The YGP for a doubled CO2 simulation is presented.

On August 20 1991, unusual, hazy clouds were encountered by commercial jet aircraft flying over continental SE Australia. Image data from the AVHRR on board the NOAA satellites have been used to discriminate the clouds from water/ice clouds. The clouds were again observed over Australia by lidar eight days later, presumably after a complete circumnavigation in the zonal winds of the southern mid-latitudes. The lidar measurements revealed a strong scattered signal from a layer situated near 12 km above the surface. The satellite and lidar data indicate that the clouds were of volcanic origin and we suggest that they originated from the Mt Hudson eruptions in Chile. We have used a numerical model to simulate the transport of the volcanic clouds and find good agreement between the projected position of the clouds and observations.

A time-dependent primitive-equation model of the southern hemisphere winter troposphere with an idealized dome-shaped continent centred at 80°S has been used to assess the potential of Antarctica to force stationary waves and to determine the location of the mid-latitude baroclinic storm track. Several integrations of the model for two hundred days were made with the zonal-mean fields fixed at the climatological values. In the time mean of each run an anticyclonic wave response formed over the mountain and a planetary wave propagated into the mid latitudes with substantial amplitude. This suggests that much of the observed stationary asymmetry in the southern, mid and high latitudes may be due to Antarctica. The response to the Antarctic forcing was different in a steady, linear version of the model. However, interaction between the steady waves appears to be of minor importance to the time-mean pattern. Rather, E-vector fields point to a substantial effect of the transients on the pattern. In particular, the low-frequency transients appear to be important in the balance of the time-mean equations near the mountain.

[i] There remains uncertainty in the projected climate change over the 21 st century, in part because of the range of responses to rising greenhouse gas concentrations in current global climate models (GCMs). The representation of potential changes in the form of a probability density function (PDF) is increasingly sought for applications. This article presents a method of estimating PDFs for projections based on the "pattern scaling" technique, which separates the uncertainty in the global mean warming from that in the standardized regional change. A mathematical framework for the problem is developed, which includes a joint probability distribution for the product of these two factors. Several simple approaches are considered for representing the factors by PDFs using GCM results, allowing model weighting. The four-parameter beta distribution is found to provide a smooth PDF that can match the mean and range of GCM results, allowing skewness when appropriate. A beta representation of the range in global warming consistent with the Intergovernmental Panel on Climate Change Fourth Assessment Report is presented. The method is applied to changes in Australian temperature and precipitation, under the A1B scenario of concentrations, using results from 23 GCMs in the CMIP3 database. Statistical results, including percentiles and threshold exceedences, are compared for the case of southern Australian temperature change in summer. For the precipitation example, central Australian winter rainfall, the usual linear scaling assumption produces a net change PDF that extends to unphysically large decreases. This is avoided by assuming an exponential relationship between percentage decreases in rainfall and warming.

[1] The potential change in precipitation due to global warming is studied using five-member ensembles of climate simulations by the CSIRO Mark 2 atmosphere-ocean model for the period 1871–1990 and forward to 2100 under both the Special Report on Emission Scenarios (SRES) A2 (rapid CO2 increase) and B2 (moderate increase) forcing scenarios. The mean surface warming for the period 1961–1990 is 0.3 K. The warming from 1961–1990 to 2071–2100 is 3.5 K under A2, 29% more than for B2, and with a very similar spatial pattern. The daily precipitation (P) frequency distributions for January and July days in these periods are presented, focusing on the A2 case. The distributions for wet days at each point are approximated by the gamma distribution. The global mean P increase of around 6%, in both months, is related to a mean increase in the gamma's scale parameter of 18%, offset by small decreases in the shape parameter and wet day frequency. However, local changes of opposite signs also occur, especially in the tropics. Ensemble averages of 30-year extreme daily precipitation for January and July, and other months, are generally greater for 2071–2100 than for 1961–1990, with an average increase of 14%. Extreme value theory based on the monthly gamma distributions provides a good match to these values. The theory is extended to the annual case. In general, the 1961–1990 extremes peak in the subtropical rainbands in the model, where increases of 10 to 30% are common. Larger relative increases occur in polar regions, and also over northern land in January.

[1] 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.

A barotropic Rossby wave incident to a region of increasing mean flow velocity opposing the wave group velocity undergoes a reversal of direction at a stopping point where the mean flow velocity and local wave group velocities are equal and opposite. Incident wave amplitude increases approaching this stopping point, which may be referred to as a group velocity critical layer, but eventually suffers a decrease along its trajectory so that the reflected wave amplitude and energy tend to zero on approach to a phase velocity critical layer located where the opposing flow vanishes. Some applications of this process to observations of synoptic scale Rossby waves are suggested and an example of the interaction of an incident wave with a barotropic model of the Hadley circulation is presented to illustrate these ideas.