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Rossby wave packets (RWPs) are Rossby waves for which the amplitude has a local maximum and decays to smaller values at larger distances. This review focuses on upper-tropospheric transient RWPs along the midlatitude jet stream. Their central characteristic is the propagation in the zonal direction as well as the transfer of wave energy from one individual trough or ridge to its downstream neighbor, a process called "downstream development." These RWPs sometimes act as long-range precursors to extreme weather and presumably have an influence on the predictability of midlatitude weather systems. The paper reviews research progress in this area with an emphasis on developments during the last 15 years. The current state of knowledge is summarized including a discussion of the RWP life cycle as well as Rossby waveguides. Recent progress in the dynamical understanding of RWPs has been based, in part, on the development of diagnostic methods. These methods include algorithms to identify and track RWPs in an automated manner, which can be used to extract the climatological properties of RWPs. RWP dynamics have traditionally been investigated using the eddy kinetic energy framework; alternative approaches based on potential vorticity and wave activity fluxes are discussed and put into perspective with the more traditional approach. The different diagnostics are compared to each other and the strengths and weaknesses of individual methods are highlighted. A recurrent theme is the role of diabatic processes, which can be a source for forecast errors. Finally, the paper points to important open research questions and suggests avenues for future research. [ABSTRACT FROM AUTHOR]

'Neighborhood approaches' have been used in two primary ways to postprocess and verify high-resolution ensemble output. While the two methods appear deceptively similar, they define events over different spatial scales and yield fields with different interpretations: the first produces probabilities interpreted as likelihood of event occurrence at the grid scale, while the second produces probabilities of event occurrence over spatial scales larger than the grid scale. Unfortunately, some studies have confused the two methods, while others did not acknowledge multiple possibilities of neighborhood approach application and simply stated, 'a neighborhood approach was applied' without supporting details. Thus, this paper reviews applications of neighborhood approaches to convection-allowing ensembles in hopes of clarifying the two methods and their different event definitions. Then, using real data, it is demonstrated how the two approaches can yield statistically significantly different objective conclusions about model performance, underscoring the critical need for thorough descriptions of how neighborhood approaches are implemented and events are defined. The authors conclude by providing some recommendations for application of neighborhood approaches to convection-allowing ensembles. [ABSTRACT FROM AUTHOR]

Using daily rain gauge records for Madagascar and nearby islands, this paper investigates rainfall intraseasonal variability at local and regional scales during the austral summer season (November-February), as well as the respective influences of recurrent convective regimes over the southwest Indian Ocean (SWIO) and the Madden-Julian oscillation (MJO). The results show a general consistency between local-scale rainfall variability in Madagascar and regional-scale features of climate variability. The influence of tropical temperate troughs in their mature phase and/or their easternmost locations is first underlined. The development of such systems over southern Africa and the Mozambique Channel can be considered as precursors for Malagasy wet spells, especially over the southern part of the island. Regional and local effects of the MJO are weaker on average, and only concern the northwest of the island and the north of the Mozambique Channel. MJO and convective regimes are finally shown to explain distinct fractions of regional rainfall variability. [ABSTRACT FROM AUTHOR]

This paper describes work to improve the understanding of the broad range of factors affecting the occurrence of postfire flooding, with emphasis on an event that occurred in the Alpine Shire, Victoria, Australia, in 2003. Analysis and mesoscale modeling of the conditions surrounding the event suggests that the drivers of the extreme rainfall event were above-average precipitable water in the atmosphere, significant values of CAPE, producing strong updrafts within the thunderstorm capable of supporting large quantities of suspended water droplets, and thunderstorm cell regeneration in the same area. However, atmospheric instability was further enhanced by anabatic breezes, above-average boundary layer moisture, and increased surface heating resulting from reduced surface albedo and soil moisture of the recently burned fire surface. Flash flooding resulted, due to 1) the storm cells likely being pulse wet microbursts, 2) cell regeneration over the same area (very little horizontal movement), and 3) the small catchment size. It is likely that a further contributor to the observed flash flood was the reduced infiltration often observed in recently burned catchments; these factors will be explored in a subsequent hydrologic study. It is intended that the mechanisms elucidated in this study will assist in emergency preparedness in the Alpine Shire. Given the warmer conditions expected with near-term anthropogenic climate change for the Alpine Shire, and the concomitant increase in fires, this causal relationship, even for a relatively rare event, has implications for emergency managers and Alpine Shire residents. [ABSTRACT FROM AUTHOR]

Assimilation of salinity into ocean and climate general circulation models is a very important problem. Argo data now provide far more salinity observations than ever before. In addition, a good analysis of salinity over time in ocean reanalyses can give important results for understanding climate change. Here it is shown from the historical ocean database that over large regions of the globe (mainly midlatitudes and lower latitudes) variance of salinity on an isotherm S(T) is often less than variance measured at a particular depth S(z). It is also shown that the dominant temporal variations in S(T) occur more slowly than variations in S(z), based on power spectra from the Bermuda time series. From ocean models it is shown that the horizontal spatial covariance of S(T) often has larger scales than S(z). These observations suggest an assimilation method based on analyzing S(T). An algorithm for assimilating salinity data on isotherms is then presented, and it is shown how this algorithm produces orthogonal salinity increments to those produced during the assimilation of temperature profiles. It is argued that the larger space and time scales can be used for the S(T) assimilation, leading to better use of scarce salinity observations. Results of applying the salinity assimilation algorithm to a single analysis time within the ECMWF seasonal forecasting ocean model are also shown. The separate salinity increments coming from temperature and salinity data are identified, and the independence of these increments is demonstrated. Results of an ocean reanalysis with this method will appear in a future paper. [ABSTRACT FROM AUTHOR]

The characteristics of explosively developing extratropical cyclones in the northwestern Pacific region are analyzed using the global objectively Analyzed dataset (GANAL) provided by the Japan Meteorological Agency (JMA). In the present paper, these cyclones are classified into three types, depending on positions of formation and of rapid development: OJ cyclones originate over the eastern Asian continent and develop over the Sea of Japan or the Sea of Okhotsk; PO-L cyclones are also formed over the Asian continent and develop over the northwestern Pacific Ocean; and PO-O cyclones are formed and develop over the northwestern Pacific Ocean. Statistical analyses suggest that OJ cyclones frequently appeared in late fall and had the smallest deepening rates of the three types; PO-L cyclones had medium deepening rates and frequently occurred in early and late winter; and PO-O cyclones mainly occurred in midwinter and had the largest deepening rates. Two kinds of composite analyses were conducted to understand the structures and the mechanisms of development. The first composite analysis used geographically fixed coordinates. The results suggest that the favorable atmospheric conditions for the development of each type of cyclone are closely connected to the presence and extension of the cold air mass over the Asian continent. In addition, these conditions are closely related to seasonal variations across the area. The other analysis of cyclone mesoscale structure, using cyclone-relative coordinates at the maximum deepening rate, suggests that OJ cyclones had a short-wave, upper-level jet streak and a strong baroclinic zone in the lower level. PO-L cyclones, associated with a zonally stretched jet stream, had a remarkable midlevel baroclinic zone. PO-O cyclones with a strong jet streak also had a distinct baroclinic zone in the midlevel, and a large water vapor budget (precipitation minus evaporation) appeared around the cyclone center. These cyclone structures reflected vorticity, temperature, and moisture advection, that is, larger-scale atmospheric conditions that affected cyclone development. [ABSTRACT FROM AUTHOR]

In July 2021, Typhoon In-Fa (TIF) triggered a significant indirect heavy precipitation event (HPE) in central China and a direct HPE in eastern China. Both these events led to severe disasters. However, the synoptic-scale conditions and the impacts of these HPEs on future estimations of return periods remain poorly understood. Here, we find that the remote HPE that occurred ∼2200 km ahead of TIF over central China was a predecessor rain event (PRE). The PRE unfolded under the equatorward entrance of the upper-level westerly jet. This event, which encouraged divergent and adiabatic outflow in the upper level, subsequently intensified the strength of the upper-level westerly jet. In contrast, the direct HPE in eastern China was due primarily to the long duration and slow movement of TIF. The direct HPE occurred in areas situated less than 200 km from TIF's center and to the left of TIF's propagation trajectory. Anomaly analyses reveal favorable thermodynamic and dynamic conditions and abundant atmospheric moisture that sustained TIF's intensity. A saddle-shaped pressure field in the north of eastern China and peripheral weak steering flow impeded TIF's movement northward. Hydrologically, the inclusion of these two HPEs in the historical record leads to a decrease in the estimated return periods of similar HPEs. Our findings highlight the potential difficulties that HPEs could introduce for the design of hydraulic engineering infrastructure as well as for the disaster mitigation measures required to alleviate future risk, particularly in central China. [ABSTRACT FROM AUTHOR]

For managing climate variability and adapting to climate change, seasonal forecasts are widely produced to inform decision-making. However, seasonal forecasts from global climate models are found to poorly reproduce temperature trends in observations. Furthermore, this problem is not addressed by existing forecast postprocessing methods that are needed to remedy biases and uncertainties in model forecasts. The inability of the forecasts to reproduce the trends severely undermines user confidence in the forecasts. In our previous work, we proposed a new statistical postprocessing model that counteracted departures in trends of model forecasts from observations. Here, we further extend this trend-aware forecast postprocessing methodology to carefully treat the trend uncertainty associated with the sampling variability due to limited data records. This new methodology is validated on forecasting seasonal averages of daily maximum and minimum temperatures for Australia based on the SEAS5 climate model of the European Centre for Medium-Range Weather Forecasts. The resulting postprocessed forecasts are shown to have proper trends embedded, leading to greater accuracy in regions with significant trends. The application of this new forecast postprocessing is expected to boost user confidence in seasonal climate forecasts. [ABSTRACT FROM AUTHOR]

The representation of tropical precipitation is evaluated across three generations of models participating in phases 3, 5, and 6 of the Coupled Model Intercomparison Project (CMIP). Compared to state-of-the-art observations, improvements in tropical precipitation in the CMIP6 models are identified for some metrics, but we find no general improvement in tropical precipitation on different temporal and spatial scales. Our results indicate overall little changes across the CMIP phases for the summer monsoons, the double-ITCZ bias, and the diurnal cycle of tropical precipitation. We find a reduced amount of drizzle events in CMIP6, but tropical precipitation occurs still too frequently. Continuous improvements across the CMIP phases are identified for the number of consecutive dry days, for the representation of modes of variability, namely, the Madden– Julian oscillation and El Niño–Southern Oscillation, and for the trends in dry months in the twentieth century. The observed positive trend in extreme wet months is, however, not captured by any of the CMIP phases, which simulate negative trends for extremely wet months in the twentieth century. The regional biases are larger than a climate change signal one hopes to use the models to identify. Given the pace of climate change as compared to the pace of model improvements to simulate tropical precipitation, we question the past strategy of the development of the present class of global climate models as the mainstay of the scientific response to climate change. We suggest the exploration of alternative approaches such as high-resolution storm-resolving models that can offer better prospects to inform us about how tropical precipitation might change with anthropogenic warming. [ABSTRACT FROM AUTHOR]

Criteria currently employed in algorithms that identify low-level jets (LLJs) in South America utilizing rawinsonde and gridded model data fail to detect an important number of LLJ events. This study discusses shortcomings in the existing approaches for LLJ identification in South America and proposes modifications to the criteria regarding layer depth for LLJ identification and wind direction. Episodes of southerly LLJs, which have received less attention in the La Plata basin, are also included in the investigation. A sensitivity analysis of LLJ detection in South America upon the choice of the criteria applied to a sample period of 15 years (1996-2010) of gridded numerical data from the National Centers for Environmental Prediction (NCEP) Climate Forecast System Reanalysis (CFSR), and to a 20-yr dataset (1996-2015) of actual rawinsondes for the La Plata basin, reveals the benefits of revising the criteria. The modified criteria allow for the characterization of a wider spectrum of LLJs over key regions of South America, such as over the Bolivian-Paraguayan border, Sierras de Córdoba in Argentina, and southern-southeastern Brazil. This wider range of events includes elevated LLJs, mostly with strong zonal components, that account for approximately 20% of the full sample of LLJs identified in the rawinsonde dataset investigated here. The revised criteria have the advantage of retaining the identification of episodes that meet the consecrated definition of the South American LLJ, while at the same time providing an augmented sample of such wind systems. Our results provide further insights into the forcing mechanisms of distinct types of LLJs in South America, ranging from topographic to baroclinic effects. [ABSTRACT FROM AUTHOR]

On 21 January 2009, the warm front of an extensive low pressure system affected U.K. weather. In this work, macroscopic and microphysical characteristics of this warm front are investigated using in situ (optical array probes, temperatures sensors, and radiosondes) and S-band polarimetric radar data from the Aerosol Properties, Processes and Influences on the Earth's Climate-Clouds project. The warm front was associated with a warm conveyor belt, a zone of wind speeds of up to 26 m s-1, which played a key role in the formation of extensive mixed-phase cloud mass by ascending significant liquid water (LWC; ~0.22 g m-3) at a level ~3 km and creating an ideal environment at temperatures ~-5°C for ice multiplication. Then, "generating cells," which formed in the unstable and sheared layer above the warm conveyor belt, influenced the structure of the stratiform cloud layer, dividing it into two types of elongated and slanted ice fall streaks: one depicted by large ZDR values and the other by large ZH values. The different polarimetric characteristics of these ice fall streaks reveal their different microphysical properties, such as the ice habit, concentration, and size. We investigate their evolution, which was affected by the warm conveyor belt, and their impact on the surface precipitation. [ABSTRACT FROM AUTHOR]

Intense tropical cyclones (TCs) generally produce a cloud-free center with calm winds, called the eye. The Automated Rotational Center Hurricane Eye Retrieval (ARCHER) algorithm is used to analyze Hurricane Satellite (HURSAT) B1 infrared satellite imagery data for storms occurring globally from 1982 to 2015. HURSAT B1 data provide 3-hourly observations of TCs. The result is a 34-yr climatology of eye location and size. During that time period, eyes are identified in about 13% of all infrared images and slightly more than half of all storms produced an eye. Those that produce an eye have (on average) 30 h of eye scenes. Hurricane Ioke (1992) had the most eye images (98, which is 12 complete days with an eye). The median wind speed of a system with an eye is 97 kt (50 m s-1) [cf. 35 kt (18 m s-1) for those without an eye]. Eyes are much more frequent in the Northern Hemisphere (particularly in the western Pacific) but eyes are larger in the Southern Hemisphere. The regions where eyes occur are expanding poleward, thus expanding the area at risk of TC-related damage. Also, eye scene occurrence can provide an objective measure of TC activity in place of those based on maximum wind speeds, which can be affected by available observations and forecast agency practices. [ABSTRACT FROM AUTHOR]

This work demonstrates the use of Sobol's sensitivity analysis framework to examine multivariate input-output relationships in dynamical systems. The methodology allows simultaneous exploration of the effect of changes in multiple inputs, and accommodates nonlinear interaction effects among parameters in a computationally affordable way. The concept is illustrated via computation of the sensitivities of atmospheric general circulation model (AGCM)-simulated tropical cyclones to changes in model initial conditions. Specifically, Sobol's variance-based sensitivity analysis is used to examine the response of cyclone intensity, cloud radiative forcing, cloud content, and precipitation rate to changes in initial conditions in an idealized AGCM-simulated tropical cyclone (TC). Control factors of interest include the following: initial vortex size and intensity, environmental sea surface temperature, vertical lapse rate, and midlevel relative humidity. The sensitivity analysis demonstrates systematic increases in TC intensity with increasing sea surface temperature and atmospheric temperature lapse rates, consistent with many previous studies. However, there are nonlinear interactions among control factors that affect the response of the precipitation rate, cloud content, and radiative forcing. In addition, sensitivities to control factors differ significantly when the model is run at different resolution, and coarse-resolution simulations are unable to produce a realistic TC. The results demonstrate the effectiveness of a quantitative sensitivity analysis framework for the exploration of dynamic system responses to perturbations, and have implications for the generation of ensembles. [ABSTRACT FROM AUTHOR]

The subtropical east coast region of Australia is characterized by the frequent occurrence of low pressure systems, known as east coast lows (ECLs). The more intense ECLs can cause severe damage and disruptions to this region. While the term 'east coast low' refers to a broad classification of events, it has been argued that different ECLs can have substantial differences in their nature, being dominated by baroclinic and barotropic processes in different degrees. Here we reexamine two well-known historical ECL case studies under this perspective: the Duck storm of March 2001 and the Pasha Bulker storm of June 2007. Exploiting the cyclone phase space analysis to study the storms' full three-dimensional structure, we show that one storm has features similar to a typical extratropical frontal cyclone, while the other has hybrid tropical-extratropical characteristics. Furthermore, we examine the energetics of the atmosphere in a limited area including both systems for the ECL occurrence times, and show that the two cyclones are associated with different signatures in the energy conversion terms. We argue that the systematic use of the phase space and energetics diagnostics can form the basis for a physically based classification of ECLs, which is important to advance the understanding of ECL risk in a changing climate. [ABSTRACT FROM AUTHOR]

The development of elevated potential instability within the comma head of a continental winter cyclone over the north-central United States is examined using a 63-h Weather Research and Forecasting (WRF) Model simulation. The simulation is first compared to the observed cyclone. The distribution of most unstable convective available potential energy (MUCAPE) within the comma head is then analyzed. The region with positive MUCAPE was based from 2- to 4-km altitude with MUCAPE values up to 93 J kg-1. Backward trajectories from five sublayers within the region of elevated convection in the comma head were calculated to investigate how elevated potential instability developed. Air in the lowest sublayer, the source air for convective cells, originated 63 h earlier near Baja California at elevations between 2.25- and 2.75-km altitude. Air atop the layer where convection occurred originated at altitudes between 9.25 and 9.75 km in the Arctic, 5000 km away from the origin of air in the lowest sublayer. All air in the layer in which convection occurred originated over the Pacific coast of Mexico, the Pacific Ocean, or arctic regions of Canada. Diabatic processes strongly influenced air properties during transit to the comma head. Air underwent radiative cooling, was affected by mixing during passage over mountains, and underwent interactions with clouds and precipitation. Notably, no trajectory followed an isentropic surface during the transit. The changes in thermodynamic properties along the trajectories led to an arrangement of air masses in the comma head that promoted the development of potential instability and elevated convection. [ABSTRACT FROM AUTHOR]

In light of growing interest in data-driven methods for oceanic, atmospheric, and climate sciences, this work focuses on the field of data assimilation and presents the analog data assimilation (AnDA). The proposed framework produces a reconstruction of the system dynamics in a fully data-driven manner where no explicit knowledge of the dynamical model is required. Instead, a representative catalog of trajectories of the system is assumed to be available. Based on this catalog, the analog data assimilation combines the nonparametric sampling of the dynamics using analog forecasting methods with ensemble-based assimilation techniques. This study explores different analog forecasting strategies and derives both ensemble Kalman and particle filtering versions of the proposed analog data assimilation approach. Numerical experiments are examined for two chaotic dynamical systems: the Lorenz-63 and Lorenz-96 systems. The performance of the analog data assimilation is discussed with respect to classical model-driven assimilation. A Matlab toolbox and Python library of the AnDA are provided to help further research building upon the present findings. [ABSTRACT FROM AUTHOR]

The U.S. National Blend of Models provides statistically postprocessed, high-resolution multimodel ensemble guidance, providing National Weather Service forecasters with a calibrated, downscaled starting point for producing digital forecasts. Forecasts of 12-hourly probability of precipitation (POP12) over the contiguous United States are produced as follows: 1) Populate the forecast and analyze cumulative distribution functions (CDFs) to be used later in quantile mapping. Were every grid point processed without benefit of data from other points, 60 days of training data would likely be insufficient for estimating CDFs and adjusting the errors in the forecast. Accordingly, 'supplemental' locations were identified for each grid point, and data from the supplemental locations were used to populate the forecast and analyzed CDFs used in the quantile mapping. 2) Load the real-time U.S. and Environment Canada (now known as Environment and Climate Change Canada) global deterministic and ensemble forecasts, interpolated to ⅛°. 3) Using CDFs from the past 60 days of data, apply a deterministic quantile mapping to the ensemble forecasts. 4) Dress the resulting ensemble with random noise. 5) Generate probabilities from the ensemble relative frequency. 6) Spatially smooth the forecast using a Savitzky-Golay smoother, applying more smoothing in flatter areas. Forecasts of 6-hourly quantitative precipitation (QPF06) are more simply produced as follows: 1) Form a grand ensemble mean, again interpolated to ⅛°. 2) Quantile map the mean forecast using CDFs of the ensemble mean and analyzed distributions. 3) Spatially smooth the field, similar to POP12. Results for spring 2016 are provided, demonstrating that the postprocessing improves POP12 reliability and skill, as well as the deterministic forecast bias, while maintaining sharpness and spatial detail. [ABSTRACT FROM AUTHOR]

A statistical postprocessing method for seasonal forecasts based on temporally and spatially smoothed climate statistics is introduced. The method uses information available from seasonal hindcasts initialized at the beginning of 12 calendar months. The performance of the method is tested within both deterministic and probabilistic frameworks using output from the ensemble of seasonal hindcasts produced by the Canadian Seasonal to Interannual Prediction System for the 30-yr period 1981-2010. Forecast skill improvements are found to be greater when forecast adjustment parameters estimated for individual seasons and at individual grid points are temporally and spatially smoothed. The greatest skill improvements are typically achieved for seasonally invariant parameters while skill improvements due to additional spatial smoothing are modest. [ABSTRACT FROM AUTHOR]

This study analyzes a method of constructing a homogeneous, high-resolution global atmospheric hindcast. Themethod is the spectral nudging technique, which was applied to a state-of-the-art general circulationmodel (ECHAM6, T255L95). Large spatial scales of the global climate model prognostic variables were spectrally nudged toward a reanalysis dataset (NCEP-1, T62L28) for the past few decades. The main idea is the addition of dynamically consistent regional weather details to the coarse-grid NCEP-1 reanalysis. A large number of sensitivity experiments was performed, using different nudging e-folding times, vertical profiles, wavenumbers, and variables. Comparisons with observations and several reanalyses showed a high dependency on the variations of the nudging configuration.At the global scale, the accordance is very high for extratropical regions and lower in the tropics. A wavenumber truncation of 30, a relatively short e-folding time of 50min, and a plateaushaped nudging profile applied only to divergence and vorticity generally yielded the best results. This is one of the first global spectral nudging hindcast studies and the first applying an altitude-dependent profile to selected prognostic variables. Themethod can be applied to reconstructing the history of extreme events such as intense storms within the context of ongoing climate change. [ABSTRACT FROM AUTHOR]

The first multimodel study to estimate the predictability of a boreal sudden stratospheric warming (SSW) is performed using five NWP systems. During the 2012/13 boreal winter, anomalous upward propagating planetary wave activity was observed toward the end of December, which was followed by a rapid deceleration of the westerly circulation around 2 January 2013, and on 7 January 2013 the zonal-mean zonal wind at 60°N and 10 hPa reversed to easterly. This stratospheric dynamical activity was followed by an equatorward shift of the tropospheric jet stream and by a high pressure anomaly over the North Atlantic, which resulted in severe cold conditions in the United Kingdom and northern Europe. In most of the five models, the SSW event was predicted 10 days in advance. However, only some ensemble members in most of the models predicted weakening of westerly wind when the models were initialized 15 days in advance of the SSW. Further dynamical analysis of the SSW shows that this event was characterized by the anomalous planetary wavenumber-1 amplification followed by the anomalous wavenumber-2 amplification in the stratosphere, which resulted in a split vortex occurring between 6 and 8 January 2013. The models have some success in reproducing wavenumber-1 activity when initialized 15 days in advance, but they generally failed to produce the wavenumber-2 activity during the final days of the event. Detailed analysis shows that models have reasonably good skill in forecasting tropospheric blocking features that stimulate wavenumber-2 amplification in the troposphere, but they have limited skill in reproducing wavenumber-2 amplification in the stratosphere. [ABSTRACT FROM AUTHOR]

Cold pools are integral components of squall-line mesoscale convective systems and the West African monsoon, but are poorly represented in operational global models. Observations of 38 cold pools made at Niamey, Niger, during the 2006 African Monsoon Multidisciplinary Analysis (AMMA) campaign (1 June-30 September 2006), are used to generate a seasonal characterization of cold pool properties by quantifying related changes in surface meteorological variables. Cold pools were associated with temperature decreases of 2°-14°C, pressure increases of 0-8 hPa, and wind gusts of 3-22 m s−1. Comparison with published values of similar variables from the U.S. Great Plains showed comparable differences. The leading part of most cold pools had decreased water vapor mixing ratios compared to the environment, with moister air, likely related to precipitation, approximately 30 min behind the gust front. A novel diagnostic used to quantify how consistent observed cold pool temperatures are with saturated or unsaturated descent from midlevels [fractional evaporational energy deficit (FEED)] shows that early season cold pools are consistent with less saturated descents. Early season cold pools were relatively colder, windier, and wetter, consistent with drier midlevels, although this was only statistically significant for the change in moisture. Late season cold pools tended to decrease equivalent potential temperature from the pre-cold pool value, whereas earlier in the season changes were smaller, with more increases. The role of cold pools may therefore change through the season, with early season cold pools more able to feed subsequent convection. [ABSTRACT FROM AUTHOR]

Efforts to improve the prediction accuracy of high-resolution (1-10 km) surface precipitation distribution and variability are of vital importance to local aspects of air pollution, wet deposition, and regional climate. However, precipitation biases and errors can occur at these spatial scales due to uncertainties in initial meteorological conditions and/or grid-scale cloud microphysics schemes. In particular, it is still unclear to what extent a subgrid-scale convection scheme could be modified to bring in scale awareness for improving high-resolution short-term precipitation forecasts in the WRF Model. To address these issues, the authors introduced scale-aware parameterized cloud dynamics for high-resolution forecasts by making several changes to the Kain-Fritsch (KF) convective parameterization scheme in the WRF Model. These changes include subgrid-scale cloud-radiation interactions, a dynamic adjustment time scale, impacts of cloud updraft mass fluxes on grid-scale vertical velocity, and lifting condensation level-based entrainment methodology that includes scale dependency. A series of 48-h retrospective forecasts using a combination of three treatments of convection (KF, updated KF, and the use of no cumulus parameterization), two cloud microphysics schemes, and two types of initial condition datasets were performed over the U.S. southern Great Plains on 9- and 3-km grid spacings during the summers of 2002 and 2010. Results indicate that 1) the source of initial conditions plays a key role in high-resolution precipitation forecasting, and 2) the authors' updated KF scheme greatly alleviates the excessive precipitation at 9-km grid spacing and improves results at 3-km grid spacing as well. Overall, the study found that the updated KF scheme incorporated into a high-resolution model does provide better forecasts for precipitation location and intensity. [ABSTRACT FROM AUTHOR]

As an important global data resource, reanalysis is widely applied for climate impact studies of the past several decades. For the first time, monthly mean temperature and monthly total precipitation derived from the newest generation reanalysis product-the ECMWF twentieth-century reanalysis dataset (ERA-20CM)-is quantitatively evaluated based on probability density functions and 702 meteorological stations during the period of 1960-2009 across China. This study attempts to investigate how well each member ensemble prediction of ERA-20CM performs for different regions. Generally, all ensemble predictions in ERA-20CM are able to recreate the real conditions on a comparable level. More than 90% of the observed probability for temperature and more than 80% of the probabilities for precipitation could be captured by ERA-20CM over China. However, the performance changes significantly from region to region because of different topographical features and climate characteristics. The Tibetan Plateau is the most difficult to model for all member ensembles. The Jianhuai region is the area with the best performance for both temperature and precipitation. Although the best and worst ensembles for temperature and precipitation for each region were selected according to the skill scores, the differences among the 10-member ensemble predictions are negligible. This evaluation would be helpful for the potential users of reanalysis data, such as ERA-20CM for local climate impact assessments in China. [ABSTRACT FROM AUTHOR]

Seasonal rainfall predictions for Australia from the Predictive Ocean Atmosphere Model for Australia (POAMA), version P15b, coupled model seasonal forecast system, which has been run operationally at the Australian Bureau of Meteorology since 2002, are overconfident (too low spread) and only moderately reliable even when forecast accuracy is highest in the austral spring season. The lack of reliability is a major impediment to operational uptake of the coupled model forecasts. Considerable progress has been made to reduce reliability errors with the new version of POAMA2, which makes use of a larger ensemble from three different versions of the model. Although POAMA2 can be considered to be multimodel, its individual models and forecasts are similar as a result of using the same perturbed initial conditions and the same model lineage. Reliability of the POAMA2 forecasts, although improved, remains relatively low. Hence, the authors explore the additional benefit that can be attained using more independent models available in the European Union Ensemble-Based Predictions of Climate Changes and their Impacts (ENSEMBLES) project. Although forecast skill and reliability of seasonal predictions of Australian rainfall are similar for POAMA2 and the ENSEMBLES models, forming a multimodel ensemble using POAMA2 and the ENSEMBLES models is shown to markedly improve reliability of Australian seasonal rainfall forecasts. The benefit of including POAMA2 into this multimodel ensemble is due to the additional information and skill of the independent model, and not just due to an increase in the number of ensemble members. The increased reliability, as well as improved accuracy, of regional rainfall forecasts from this multimodel ensemble system suggests it could be a useful operational prediction system. [ABSTRACT FROM AUTHOR]

High-resolution Weather Research and Forecasting Model (WRF) simulations are used to explore the sensitivity of Great Lakes lake-effect snowfall (LES) to changes in lake ice cover and surface temperature. A control simulation with observed ice cover is compared with three sensitivity tests: complete ice cover, no lake ice, and warmer lake surface temperatures. The spatial pattern of unfrozen lake surfaces determines the placement of LES, and complete ice cover eliminates it. Removal of ice cover and an increase in lake temperatures result in an expansion of the LES area both along and downwind of the lake shore, as well as an increase in snowfall amount. While lake temperatures and phase determine the amount and spatial coverage of LES, the finescale distribution of LES is strongly affected by the interaction between lake surface fluxes, the large-scale flow, and the local lake shore geography and inland topography. As a consequence, the sensitivity of LES to topography and shore geometry differs for lakes with short versus long overwater fetch. These simulations indicate that coarse-resolution models may be able to realistically reproduce the gross features of LES in future climates, but will miss the important local-scale interactions that determine the location and intensity of LES. [ABSTRACT FROM AUTHOR]

The ability to solve the global shallow-water equations with a conforming, variable-resolution mesh is evaluated using standard shallow-water test cases. While the long-term motivation for this study is the creation of a global climate modeling framework capable of resolving different spatial and temporal scales in different regions, the process begins with an analysis of the shallow-water system in order to better understand the strengths and weaknesses of the approach developed herein. The multiresolution meshes are spherical centroidal Voronoi tessellations where a single, user-supplied density function determines the region(s) of fine- and coarse-mesh resolution. The shallow-water system is explored with a suite of meshes ranging from quasi-uniform resolution meshes, where the grid spacing is globally uniform, to highly variable resolution meshes, where the grid spacing varies by a factor of 16 between the fine and coarse regions. The potential vorticity is found to be conserved to within machine precision and the total available energy is conserved to within a time-truncation error. This result holds for the full suite of meshes, ranging from quasi-uniform resolution and highly variable resolution meshes. Based on shallow-water test cases 2 and 5, the primary conclusion of this study is that solution error is controlled primarily by the grid resolution in the coarsest part of the model domain. This conclusion is consistent with results obtained by others. When these variable-resolution meshes are used for the simulation of an unstable zonal jet, the core features of the growing instability are found to be largely unchanged as the variation in the mesh resolution increases. The main differences between the simulations occur outside the region of mesh refinement and these differences are attributed to the additional truncation error that accompanies increases in grid spacing. Overall, the results demonstrate support for this approach as a path toward multiresolution climate system modeling. [ABSTRACT FROM AUTHOR]

The influence of the Madden-Julian oscillation (MJO) over tropical Africa and Atlantic is explored during the Northern Hemisphere summer months. The MJO is assessed by using real-time multivariate MJO (RMM) indices. These indices divide the active convective signal of the MJO into 8 phases. Convection associated with the MJO is enhanced over tropical Africa during RMM phases 8, 1, and 2. Convection becomes suppressed over tropical Africa during the subsequent RMM phases (phases 3-7). African convective signals are associated with westward-propagating equatorial Rossby waves. The MJO modulates African easterly wave (AEW) activity. AEW activity is locally enhanced during RMM phases 1-3 and suppressed during RMM phases 6-8. Enhanced AEW activity occurs during periods of enhanced convection over tropical Africa, consistent with stronger or more frequent triggering of AEWs as well as more growth associated with latent heat release. Enhanced AEW activity occurs during the low-level westerly wind phase of the MJO, which increases the cyclonic shear on the equatorward side of the AEJ, increasing its instability. Atlantic tropical cyclogenesis frequency varies coherently with the MJO. RMM phases 1-3 show the greatest frequency of tropical cyclogenesis events whereas phases 7 and 8 show the least. RMM phase 2 is also the most likely phase to be associated with a train of three or more tropical cyclones over the tropical Atlantic. This observed evolution of tropical cyclogenesis frequency varies coherently with variations in AEW activity and the large-scale environment. [ABSTRACT FROM AUTHOR]

Seasonal forecasting systems, and related systems for decadal prediction, are crucial in the development of adaptation strategies to climate change. However, despite important achievements in this area in the last 10 years, significant levels of skill are only generally found over regions strongly connected with the El Niñño--Southern Oscillation. With the aim of improving the skill of regional climate predictions in tropical and extratropical regions from intraseasonal to interannual time scales, a new Met Office global seasonal forecasting system (GloSea4) has been developed. This new system has been designed to be flexible and easy to upgrade so it can be fully integrated within the Met Office model development infrastructure. Overall, the analysis here shows an improvement of GloSea4 when compared to its predecessor. However, there are exceptions, such as the increased model biases that contribute to degrade the skill of Niñño-3.4 SST forecasts starting in November. Global ENSO teleconnections and Madden--Julian oscillation anomalies are well represented in GloSea4. Remote forcings of the North Atlantic Oscillation by ENSO and the quasi-biennial oscillation are captured albeit the anomalies are weaker than those found in observations. Hindcast length issues and their implications for seasonal forecasting are also discussed. [ABSTRACT FROM AUTHOR]

The statistical feature of occurrence of multiple tropical cyclone (MTC) events in the western North Pacific (WNP) is examined during summer (June--September) for the period of 1979--2006. The number of MTC events ranged from one to eight per year, experiencing a marked interannual variation. The spatial distance between the TCs associated with MTC events is mostly less than 3000 km, which accounts for 73%% of total samples. The longest active phase of an MTC event lasts for nine days, and about 80%% of the MTC events last for five days or less. A composite analysis of active and inactive MTC phases reveals that positive low-level (negative upper-level) vorticity anomalies and enhanced convection and midtropospheric relative humidity are the favorable large-scale conditions for MTC genesis. About 77%% of the MTC events occurred in the region where either the atmospheric intraseasonal (25--70 day) oscillation (ISO) or biweekly (10--20 day) oscillation (BWO) is in a wet phase. The overall occurrence of the MTC events is greatly regulated by the combined large-scale impact of BWO, ISO, and the lower-frequency (90 days or longer) oscillation. On the interannual time scale, the MTC frequency is closely related to the seasonal mean anomalies of 850-hPa vorticity, outgoing longwave radiation (OLR), and 500-hPa humidity fields. The combined ISO and BWO activity is greatly strengthened (weakened) in the WNP region during the MTC active (inactive) years. [ABSTRACT FROM AUTHOR]

A pattern projection downscaling method is applied to predict summer precipitation at 60 stations over Korea. The predictors are multiple variables from the output of six operational dynamical models. The hindcast datasets span a period of 21 yr from 1983 to 2003. A downscaled prediction was made for each model separately within a leave-one-out cross-validation framework. The pattern projection method uses a moving window, which scans globally, in order to seek the most optimal predictor for each station. The final forecast is the average of six model downscaled precipitation forecasts using the best predictors and will be referred to as “DMME.” It is found that DMME significantly improves the prediction skill by correcting the erroneous signs of the rainfall anomalies in coarse-resolution predictions of general circulation models. Although Korea’s precipitation is strongly influenced by local mountainous terrain, DMME performs well at 59 stations with correlation skill significant at the 95% confidence level. The improvement of the prediction skill is attributed to three steps: coupled pattern selection, optimal predictor selection, and the multimodel downscaled precipitation ensemble. This study indicates that the large-scale circulation variables, which are predicted by the current operational dynamical models, if selected, can be used to make skillful predictions of the local precipitation by using appropriate statistical downscaling methods. [ABSTRACT FROM AUTHOR]

Vegetated surfaces, such as grasslands and croplands, constitute a significant portion of the earth’s surface and play an important role in land–atmosphere exchange processes. This study focuses on one important parameter used in describing the exchange of moisture from vegetated surfaces: the minimum canopy resistance (rcmin). This parameter is used in the Jarvis canopy resistance scheme that is incorporated into the Noah and many other land surface models. By using an inverted form of the Jarvis scheme, rcmin is determined from observational data collected during the 2002 International H2O Project (IHOP_2002). The results indicate that rcmin is highly variable both site to site and over diurnal and longer time scales. The mean value at the grassland sites in this study is 96 s m-1 while the mean value for the cropland (winter wheat) sites is one-fourth that value at 24 s m-1. The mean rcmin for all the sites is 72 s m-1 with a standard deviation of 39 s m-1. This variability is due to both the empirical nature of the Jarvis scheme and a combination of changing environmental conditions, such as plant physiology and plant species composition, that are not explicitly considered by the scheme. This variability in rcmin has important implications for land surface modeling where rcmin is often parameterized as a constant. For example, the Noah land surface model parameterizes rcmin for the grasslands and croplands types in this study as 40 s m-1. Tests with the coupled Weather Research and Forecasting (WRF)–Noah model indicate that the using the modified values of rcmin from this study improves the estimates of latent heat flux; the difference between the observed and modeled moisture flux decreased by 50% or more. While land surface models that estimate transpiration using Jarvis-type relationships may be improved by revising the rcmin values for grasslands and croplands, updating the rcmin will not fully account for the variability in rcmin observed in this study. As such, it may be necessary to replace the Jarvis scheme currently used in many land surface and numerical weather prediction models with a physiologically based estimate of the canopy resistance. [ABSTRACT FROM AUTHOR]

A new diagnostic for measuring the ability of atmospheric models to reproduce realistic low-frequency variability is introduced in the context of Held and Suarez’s 1994 proposal for comparing the dynamics of different general circulation models. A simple procedure to compute τ, the e-folding time scale of the annular mode autocorrelation function, is presented. This quantity concisely quantifies the strength of low-frequency variability in a model and is easy to compute in practice. The sensitivity of τ to model numerics is then studied for two dry primitive equation models driven with the Held–Suarez forcings: one pseudospectral and the other finite volume. For both models, τ is found to be unrealistically large when the horizontal resolutions are low, such as those that are often used in studies in which long integrations are needed to analyze model variability on low frequencies. More surprising is that it is found that, for the pseudospectral model, τ is particularly sensitive to vertical resolution, especially with a triangular truncation at wavenumber 42 (a very common resolution choice). At sufficiently high resolution, the annular mode autocorrelation time scale τ in both models appears to converge around values of 20–25 days, suggesting the existence of an intrinsic time scale at which the extratropical jet vacillates in the Held and Suarez system. The importance of τ for computing the correct response of a model to climate change is explicitly demonstrated by perturbing the pseudospectral model with simple torques. The amplitude of the model’s response to external forcing increases as τ increases, as suggested by the fluctuation–dissipation theorem. [ABSTRACT FROM AUTHOR]

This study examines space–time characteristics of seasonal rainfall predictability in a tropical region by analyzing observed data and model simulations over Senegal. Predictability is analyzed in terms of the spatial coherence of observed interannual variability at the station scale, and within-ensemble coherence of general circulation model (GCM) simulations with observed sea surface temperatures (SSTs) prescribed. Seasonal mean rainfall anomalies are decomposed in terms of daily rainfall frequency and daily mean intensity. The observed spatial coherence is computed from a 13-station network of daily rainfall during the July–September season 1961–98 in terms of (i) interannual variability of a standardized anomaly index (i.e., the average of the normalized anomalies of each station), (ii) the external variance (i.e., the fraction of common variance among stations), and (iii) the number of spatiotemporal degrees of freedom. Spatial coherence of interannual anomalies across stations is found to be much stronger for seasonal rainfall amount and daily occurrence frequency, compared with daily mean intensity of rainfall. Combinatorial analysis of the station observations suggests that, for occurrence and seasonal amount, the empirical number of spatial degrees of freedom is largely insensitive to the number of stations considered, and is between 3 and 4 for Senegal. For daily mean intensity, by contrast, each station is found to convey almost independent information, and the number of degrees of freedom would be expected to increase for a denser network of stations. The GCM estimates of potential predictability and skill associated with the SST forcing are found to be remarkably consistent with those inferred from the observed spatial coherence: there is a moderate-to-strong skill at reproducing the interannual variations of seasonal amounts and rainfall occurrence, whereas the skill is weak for the mean intensity of rainfall. Over Senegal during July–September, it is concluded that (i) regional-scale seasonal amount and rainfall occurrence frequency are predictable from SSTs, (ii) daily mean intensity of rainfall is spatially incoherent and largely unpredictable at the regional scale, and (iii) point-score estimates of seasonal rainfall predictability and skill are subject to large sampling variability. [ABSTRACT FROM AUTHOR]

The NCEP–NCAR reanalysis together with the outgoing longwave radiation anomalies (OLRAs) and a gridded daily precipitation over the United States were used to analyze precipitation over California on intraseasonal timescales. The intraseasonal (10–90 days) filtered OLRAs were subjected to singular spectrum analysis, which identifies nonlinear oscillations in noisy time series. There are two dominant oscillatory modes associated with California rainfall with periods near 36–40 and 20–25 days. The 36–40-day mode is related to the Madden–Julian Oscillation (MJO) in the Tropics. Enhanced tropical convection propagates from the western Pacific to the central Pacific. A three-cell pattern with negative OLRAs in California and positive anomalies in the eastern Pacific and the Pacific Northwest starts to develop 4 days later and rainfall starts in California. Anomalies associated with the 20–25-day mode are responsible for alternating wet and dry episodes over California with periods shorter than the timescales of the MJO. The 20–25-day mode is the leading mode in the 7–30-day band and is related to tropical convection in the Pacific. In the extratropics, cloud bands propagate northward along the west coast of North America from the eastern Pacific just north of the ITCZ through California to the Pacific Northwest. The 200-hPa streamfunction anomaly composites associated with the 20–25-day mode reveal a westward propagating wave train dominated by a zonal wavenumber 2. This mode has a spatial structure similar to the traveling pattern described by Branstator. [ABSTRACT FROM AUTHOR]

The technique of piecewise potential vorticity (PV) inversion is used to identify the nondivergent wind fields attributed to upper-, middle-, and lower-tropospheric PV anomalies in addition to the irrotational wind with the goal of diagnosing the respective wind fields’ frontogenetic potentialities. Frontogenesis is diagnosed using a piecewise separation of the Q vector into parts associated with the partitioned wind field. Partitioned geostrophic Q vectors are used to diagnose the vertical motion attributed to the upper-, middle-, and lower-tropospheric PV anomalies. Insight gained from this new diagnostic technique is demonstrated by examining a particular case of extratropical marine cyclogenesis resulting from the interaction of an upper-tropospheric short-wave trough with a surface thermal wave. In the early stages of development, the largest contributor to surface frontogenesis was associated with winds attributed to the lower-tropospheric thermal wave. As the cyclone matured, the contributions of the upper-tropospheric PV and near-surface potential temperature anomalies to surface frontogenesis increased. Winds attributed to the upper-tropospheric PV were frontogenetical north of the thermal ridge axis and frontolytical south of the thermal ridge in the warm sector. The upper-tropospheric PV acted to amplify the thermal ridge while simultaneously narrowing the warm sector. The patterns of geostrophic Q vectors associated with the upper-tropospheric PV suggest that ascent should be favored in the narrowing surface thermal ridge. The contribution to surface frontogenesis due to lower- and middle-tropospheric PV, whose increase is imputed to latent heat release, was variable during the evolution of the cyclone—suggesting that the location of diabatically generated PV anomalies relative to frontal zones can have a significant impact on frontogenesis and associated frontal precipitation distribution. Throughout the evolution of the cyclone, the... [ABSTRACT FROM AUTHOR]

A general digital bandpass filtering procedure is presented whose advantages over other simple filtering methods are 1) versatility in its design, because only a set of three parameters is needed to calculate the filter weights via a simple analytic expression, 2) good performance at the transition band depending on the number of weights considered, and 3) the reduction of the Gibbs oscillations in the pass band of a given raw filter by convolving it with a convergence window. In order to illustrate the method, the filter has been first used to assess the ability of the Météo-France general circulation model ARPEGE to simulate the midtropospheric low-frequency intra-seasonal variability in the Northern Hemisphere. The filter examined here allows one to assess the model drawbacks in different frequency bands. As a second example, the synoptic-scale baroclinic fluctuations in midlatitudes have also been studied. It is shown that the horizontal and vertical structure of these fluctuations does not depend very much on the frequency band up to a period of 10 days, but shows an increase in zonal wavelength as lower-frequency fluctuations are considered. [ABSTRACT FROM AUTHOR]

The CSIRO coupled model has been used in a "transient" greenhouse experiment. This model contains atmospheric, oceanic, comprehensive sea-ice (dynamic/thermodynamic plus leads), and biospheric submodels. The model control run (over 100 years long) employed flux corrections and displayed only a small amount of cooling, mainly at high latitudes. The transient experiment (1% increase in CO2 compounding per annum) gave a 28C warming at time of CO2 doubling. The model displayed a "cold start" effect with a (maximum) value estimated at 0.38C. The warming in the transient run had an asymmetrical response as seen in other coupled models, with the Northern Hemisphere (NH) warming more than the Southern Hemisphere (SH). However, the land surface response in this model is different from some other transient experiments in that there is not a pronounced drying of the midlatitudes in the NH in summer. In the control run the ice model gave realistic ice distributions at both poles, with the NH ice in particular displaying considerable interdecadal variability. In the transient run the ice amount decreased more in the NH than the SH (corresponding with a greater NH warming). The NH ice extent and volume in summer was considerably reduced in depth and extent compared to the control. However, the model ice dynamics and thermodynamics allowed for a successful regrowth of the ice during the winter season to give a coverage comparable to that of the control run, although thinner. During the transient run there is a freshening of the surface salinity in the oceans at high latitudes. In the SH this is caused mainly by increases in precipitation over evaporation. The same is true for the NH, but it is found that there is a similar magnitude contribution to the polar freshening from ice melt and land runoff changes. The freshening in the North Atlantic reduces the strength of the meridional overturning by 35% at time of doubling of CO2 . Other changes... [ABSTRACT FROM AUTHOR]

ABSTRACT Two distinct intraseasonal oscillations (ISO) are found in the tropical ocean atmosphere in the western Pacific region during Tropical Ocean Global Atmosphere Coupled Ocean--Atmosphere Response Experiment (TOGA COARE). The ISO is characterized by cycles of dry--wet phases in the atmosphere due to the passage of Madden-- Julian oscillations, and corresponding warming/shoaling--cooling/deepening cycles in the ocean mixed layer (OML). During the wet phase, 2--3-day disturbances and diurnal variations in the atmosphere are pronounced. During the dry phase, diurnal cycles in sea surface temperature (SST) is much enhanced while the OML is shallow. These multiscale coupled air--sea variations are further investigated with an ocean mixed-layer model forced by the observed surface heat, water, and momentum fluxes. The variations of ocean mixed layer are shown to be crucially dependent on the vertical distribution of solar radiation, that is, diurnal SST variability primarily determined by the absorbed solar radiation in the surface layer (;1 m), and intraseasonal variations determined by penetrating solar radiation below the surface layer. Results further reveal that the accumulative effect of diurnal mixing cycles (solar heating/nocturnal deepening) is essential to maintain a stable temperature stratifi-cation and a realistic evolution of mixed-layer depth and temperature at the intraseasonal scale. The nonlinear response of the ocean mixed layer to the surface heat and momentum fluxes indicates the need to resolve the high-frequency response including diurnal atmospheric radiative--convective processes and ocean mixing pro-cesses in a coupled model to simulate the whole spectrum of multiscale variations within ISOs. [ABSTRACT FROM AUTHOR]