Abstract

Numerical weather, climate, or Earth system models involve the coupling of components. At a broad level, these components can be classified as the resolved fluid dynamics, unresolved fluid dynamical aspects (i.e., those represented by physical parameterizations such as subgrid-scale mixing), and nonfluid dynamical aspects such as radiation and microphysical processes. Typically, each component is developed, at least initially, independently. Once development is mature, the components are coupled to deliver a model of the required complexity. The implementation of the coupling can have a significant impact on the model. As the error associated with each component decreases, the errors introduced by the coupling will eventually dominate. Hence, any improvement in one of the components is unlikely to improve the performance of the overall system. The challenges associated with combining the components to create a coherent model are here termed physics–dynamics coupling. The issue goes beyond the coupling between the parameterizations and the resolved fluid dynamics. This paper highlights recent progress and some of the current challenges. It focuses on three objectives: to illustrate the phenomenology of the coupling problem with references to examples in the literature, to show how the problem can be analyzed, and to create awareness of the issue across the disciplines and specializations. The topics addressed are different ways of advancing full models in time, approaches to understanding the role of the coupling and evaluation of approaches, coupling ocean and atmosphere models, thermodynamic compatibility between model components, and emerging issues such as those that arise as model resolutions increase and/or models use variable resolutions.

Abstract

This paper summarizes advances in research on tropical–polar teleconnections, made roughly over the last decade. Elucidating El Niño–Southern Oscillation (ENSO) impacts on high latitudes has remained an important focus along different lines of inquiry. Tropical to polar connections have also been discovered at the intraseasonal time scale, associated with Madden–Julian oscillations (MJOs). On the time scale of decades, changes in MJO phases can result in temperature and sea ice changes in the polar regions of both hemispheres. Moreover, the long-term changes in SST of the western tropical Pacific, tropical Atlantic, and North Atlantic Ocean have been linked to the rapid winter warming around the Antarctic Peninsula, while SST changes in the central tropical Pacific have been linked to the warming in West Antarctica. Rossby wave trains emanating from the tropics remain the key mechanism for tropical and polar teleconnections from intraseasonal to decadal time scales. ENSO-related tropical SST anomalies affect higher-latitude annular modes by modulating mean zonal winds in both the subtropics and midlatitudes. Recent studies have also revealed the details of the interactions between the Rossby wave and atmospheric circulations in high latitudes. We also review some of the hypothesized connections between the tropics and poles in the past, including times when the climate was fundamentally different from present day especially given a larger-than-present-day global cryosphere. In addition to atmospheric Rossby waves forced from the tropics, large polar temperature changes and amplification, in part associated with variability in orbital configuration and solar irradiance, affected the low–high-latitude connections.

Abstract

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

“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

The Middle East and southwest Asia are a region that is water stressed, societally vulnerable, and prone to severe droughts. Large-scale climate variability, particularly La Niña, appears to play an important role in regionwide droughts, including the two most severe of the last 50 years—1999–2001 and 2007/08—with implications for drought forecasting. Important dynamical factors include orography, thermodynamic influence on vertical motion, storm-track changes, and moisture transport. Vegetation in the region is strongly impacted by drought and may provide an important feedback mechanism. In future projections, drying of the eastern Mediterranean region is a robust feature, as are temperature increases throughout the region, which will affect evaporation and the timing and intensity of snowmelt. Vegetation feedbacks may become more important in a warming climate. There are a wide range of outstanding issues for understanding, monitoring, and predicting drought in the region, including dynamics of the regional storm track, the relative importance of the range of dynamical mechanisms related to drought, the regional coherence of drought, the relationship between synoptic-scale mechanisms and drought, the predictability of vegetation and crop yields, the stability of remote influences, data uncertainty, and the role of temperature. Development of a regional framework for cooperative work and dissemination of information and existing forecasts would speed understanding and make better use of available information.

Abstract

This paper reviews the development of the ensemble Kalman filter (EnKF) for atmospheric data assimilation. Particular attention is devoted to recent advances and current challenges. The distinguishing properties of three well-established variations of the EnKF algorithm are first discussed. Given the limited size of the ensemble and the unavoidable existence of errors whose origin is unknown (i.e., system error), various approaches to localizing the impact of observations and to accounting for these errors have been proposed. However, challenges remain; for example, with regard to localization of multiscale phenomena (both in time and space). For the EnKF in general, but higher-resolution applications in particular, it is desirable to use a short assimilation window. This motivates a focus on approaches for maintaining balance during the EnKF update. Also discussed are limited-area EnKF systems, in particular with regard to the assimilation of radar data and applications to tracking severe storms and tropical cyclones. It seems that relatively less attention has been paid to optimizing EnKF assimilation of satellite radiance observations, the growing volume of which has been instrumental in improving global weather predictions. There is also a tendency at various centers to investigate and implement hybrid systems that take advantage of both the ensemble and the variational data assimilation approaches; this poses additional challenges and it is not clear how it will evolve. It is concluded that, despite more than 10 years of operational experience, there are still many unresolved issues that could benefit from further research.

Contents

• Introduction...4490

• Popular flavors of the EnKF algorithm...4491

  1. General description...4491

  2. Stochastic and deterministic filters...4492

     1. The stochastic filter...4492

     2. The deterministic filter...4492

  3. Sequential or local filters...4493

     1. Sequential ensemble Kalman filters...4493

     2. The local ensemble transform Kalman filter...4494

  4. Extended state vector...4494

  5. Issues for the development of algorithms...4495

• Use of small ensembles...4495

  1. Monte Carlo methods...4495

  2. Validation of reliability...4497

  3. Use of group filters with no inbreeding...4498

  4. Sampling error due to limited ensemble size: The rank problem...4498

  5. Covariance localization...4499

     1. Localization in the sequential filter...4499

     2. Localization in the LETKF...4499

     3. Issues with localization...4500

  6. Summary...4501

• Methods to increase ensemble spread...4501

  1. Covariance inflation...4501

     1. Additive inflation...4501

     2. Multiplicative inflation...4502

     3. Relaxation to prior ensemble information...4502

     4. Issues with inflation...4503

  2. Diffusion and truncation...4503

  3. Error in physical parameterizations...4504

     1. Physical tendency perturbations...4504

     2. Multimodel, multiphysics, and multiparameter approaches...4505

     3. Future directions...4505

  4. Realism of error sources...4506

• Balance and length of the assimilation window...4506

  1. The need for balancing methods...4506

  2. Time-filtering methods...4506

  3. Toward shorter assimilation windows...4507

  4. Reduction of sources of imbalance...4507

• Regional data assimilation...4508

  1. Boundary conditions and consistency across multiple domains...4509

  2. Initialization of the starting ensemble...4510

  3. Preprocessing steps for radar observations...4510

  4. Use of radar observations for convective-scale analyses...4511

  5. Use of radar observations for tropical cyclone analyses...4511

  6. Other issues with respect to LAM data assimilation...4511

• The assimilation of satellite observations...4512

  1. Covariance localization...4512

  2. Data density...4513

  3. Bias-correction procedures...4513

  4. Impact of covariance cycling...4514

  5. Assumptions regarding observational error...4514

  6. Recommendations regarding satellite observations...4515

• Computational aspects...4515

  1. Parameters with an impact on quality...4515

  2. Overview of current parallel algorithms...4516

  3. Evolution of computer architecture...4516

  4. Practical issues...4517

  5. Approaching the gray zone...4518

  6. Summary...4518

• Hybrids with variational and EnKF components...4519

  1. Hybrid background error covariances...4519

  2. E4DVar with the α control variable...4519

  3. Not using linearized models with 4DEnVar...4520

  4. The hybrid gain algorithm...4521

  5. Open issues and recommendations...4521

• Summary and discussion...4521

  1. Stochastic or deterministic filters...4522

  2. The nature of system error...4522

  3. Going beyond the synoptic scales...4522

  4. Satellite observations...4523

  5. Hybrid systems...4523

  6. Future of the EnKF...4523

APPENDIX A...4524

Types of Filter Divergence...4524

1. Classical filter divergence...4524

2. Catastrophic filter divergence...4524

   APPENDIX B...4524

   Systems Available for Download...4524

   References...4525

Abstract

Over the past decade, the number of studies that investigate aerosol–cloud interactions has increased considerably. Although tremendous progress has been made to improve the understanding of basic physical mechanisms of aerosol–cloud interactions and reduce their uncertainties in climate forcing, there is still poor understanding of 1) some of the mechanisms that interact with each other over multiple spatial and temporal scales, 2) the feedbacks between microphysical and dynamical processes and between local-scale processes and large-scale circulations, and 3) the significance of cloud–aerosol interactions on weather systems as well as regional and global climate. This review focuses on recent theoretical studies and important mechanisms on aerosol–cloud interactions and discusses the significances of aerosol impacts on radiative forcing and precipitation extremes associated with different cloud systems. The authors summarize the main obstacles preventing the science from making a leap—for example, the lack of concurrent profile measurements of cloud dynamics, microphysics, and aerosols over a wide region on the observation side and the large variability of cloud microphysics parameterizations resulting in a large spread of modeling results on the modeling side. Therefore, large efforts are needed to escalate understanding. Future directions should focus on obtaining concurrent measurements of aerosol properties and cloud microphysical and dynamic properties over a range of temporal and spatial scales collected over typical climate regimes and closure studies, as well as improving understanding and parameterizations of cloud microphysics such as ice nucleation, mixed-phase properties, and hydrometeor size and fall speed.

Abstract

A synthesis of tornado observations across Europe between 1800 and 2014 is used to produce a pan-European climatology. Based on regional tornado-occurrence datasets and articles published in peer-reviewed journals, the evolution and the major contributions to tornado databases for 30 European countries were analyzed. Between 1800 and 2014, 9563 tornadoes were reported in Europe with an increase from 8 tornadoes per year between 1800 and 1850 to 242 tornadoes per year between 2000 and 2014. The majority of the reports came from northern, western, and southern Europe, and to a lesser extent from eastern Europe where tornado databases were developed after the 1990s. Tornadoes occur throughout the year with a maximum in June–August for most of Europe and in August–November for southern Europe. Tornadoes occur more frequently between 1300 and 1500 UTC over most of Europe and between 0900 and 1100 UTC over southern Europe. Where intensity was known, 74.7% of tornadoes were classified as F0 and F1, 24.5% as F2 and F3, and 0.8% as F4 and F5. Comparing this intensity distribution over Europe with the intensity distribution for tornadoes in the United States shows that tornadoes over western and eastern Europe are more likely to be supercellular tornadoes and those over northern and southern Europe are likely to also include nonsupercellular tornadoes.

Abstract

A great deal of expertise in satellite precipitation estimation has been developed during the Tropical Rainfall Measuring Mission (TRMM) era (1998–2015). The quantification of errors associated with satellite precipitation products (SPPs) is crucial for a correct use of these datasets in hydrological applications, climate studies, and water resources management. This study presents a review of previous work that focused on validating SPPs for liquid precipitation during the TRMM era through comparisons with surface observations, both in terms of mean errors and detection capabilities across different regions of the world. Several SPPs have been considered: TMPA 3B42 (research and real-time products), CPC morphing technique (CMORPH), Global Satellite Mapping of Precipitation (GSMaP; both the near-real-time and the Motion Vector Kalman filter products), PERSIANN, and PERSIANN–Cloud Classification System (PERSIANN-CCS). Topography, seasonality, and climatology were shown to play a role in the SPP’s performance, especially in terms of detection probability and bias. Regions with complex terrain exhibited poor rain detection and magnitude-dependent mean errors; low probability of detection was reported in semiarid areas. Winter seasons, usually associated with lighter rain events, snow, and mixed-phase precipitation, showed larger biases.

Abstract

Underwater cables play vital roles in marine engineering because they provide power and communication connections from the shore to an increasing number of sea installations. To ensure the system is operating reliably and continuously, it is necessary to detect the shapes of underwater cables in real time. However, this task is difficult to accomplish because the underwater cables are located in a dynamic and complicated subsea environment, which can cause changes in position, depth, and visibility.

In this report, the current development of underwater cable shape detection methods, including visual, acoustic, magnetic detection, and multisensor fusion detection, and the advantages and disadvantages are described and analyzed. Furthermore, the disadvantages of these methods are addressed, which, based on survey platforms with high cost, include a long detection period and the failure to reveal emergencies. Then, the need to construct a simple and reliable system to detect the shapes of underwater cables is highlighted, and one possible solution based on bend sensors embedded in underwater cables is discussed.