Global Cloud-resolving Models Research Articles

ASSESSMENT OF THE CUSTOMER RELATIONSHIP MANAGEMENT SOFTWARE MARKET BASED ON A FUNCTIONAL APPROACH

With the ever-increasing importance of effective customer relationship management for businesses, the problem of choosing the right software arises. With the variety of software solutions, it becomes difficult to determine the best option that would meet the specific needs of the enterprise. The rapid development of this sector, coupled with the variety of software products, makes it difficult to find the right solution that meets business needs and allows for effective customer relationship management. A lack of understanding of the customer relationship management software market has led to a failure to utilize its potential. Lack of consensus on the optimal strategies for using CRM systems and limited research in this area require an active search for solutions to optimize customer relationship management. The purpose of the article is to study and analyze the market for customer relationship management software based on a functional approach to identify a promising direction for the development of this sector. The article highlights the capabilities of CRM systems and the basic tasks they solve. An analysis of revenue dynamics in the global market for customer relationship management software is carried out. The forecasted values of revenue in the global customer relationship management software market for 2024-2026 are determined. The key players in the global customer relationship management software market are identified.

Business analytics in CRM: A comparative review of practices in the USA and Africa

In the dynamic landscape of global business, Customer Relationship Management (CRM) has emerged as a crucial strategy for organizations aiming to enhance customer satisfaction and loyalty. This study delves into the realm of Business Analytics (BA) within CRM, examining the diverse practices employed in the USA and Africa. The purpose is to identify similarities, differences, and potential areas for improvement, with the overarching goal of fostering more effective CRM strategies. The American business landscape, characterized by advanced technological infrastructure and matured data analytics capabilities, provides a fertile ground for sophisticated CRM practices. A comprehensive analysis of leading companies in the USA reveals a strong reliance on predictive analytics, machine learning, and artificial intelligence to glean actionable insights from vast datasets. Such approaches empower organizations to personalize customer experiences, optimize marketing strategies, and drive overall business growth. In contrast, the African business environment exhibits unique challenges and opportunities. While certain regions may face infrastructural constraints, innovative CRM practices tailored to local contexts are emerging. This study sheds light on the utilization of mobile technology, social media analytics, and localized data collection methods as crucial tools in the African CRM landscape. These adaptive strategies not only address challenges but also present opportunities for leapfrogging traditional CRM models. The comparative review uncovers key areas of convergence and divergence between the two regions, highlighting the need for a nuanced approach to global CRM strategies. By synthesizing insights from the USA and Africa, organizations can develop a more holistic understanding of effective CRM practices. This research contributes valuable insights to the ongoing discourse on global business analytics, offering a roadmap for organizations to navigate the intricacies of CRM implementation in diverse and dynamic markets.

Asymptotic Matching between Weather and Climate Models

Abstract The Deep Numerical Analysis for Climate (DNA-Climate) is a pilot project to develop an Earth system model on a kilometer-scale horizontal mesh. The acronym “DNA” is based on the analogies between the hierarchical structures of atmospheric phenomena and living organisms. The multiscale structure of clouds and circulations may be analogous to the multiscale structure of cells and organs organized according to the blueprint, deoxyribonucleic acid (DNA). Whereas global cloud-resolving models (CRMs) can produce better solutions on shorter time scales that are decisively governed by the initial conditions, global climate models (GCMs) may generate reliable solutions on longer time scales that are largely determined to balance energy inputs and outputs. Our challenge is to build a physically valid model that consistently bridges the shorter- and longer-time-scale solutions in the intermediate time scales. Research topics of DNA-Climate are configured in consideration of the structural similarity between the climate modeling and the technique of matched asymptotic expansions in mathematics. The central question is whether a single modeling framework using only either global CRM or GCM will work adequately at all time scales of climate, or whether a multiscale modeling framework combining several models, of which each is only valid for limited time scales, will be needed. A multiscale modeling is an attractive framework for advancing climate modeling and would be an intriguing topic to be studied in parallel with global CRMs and GCMs.

Clouds and Convective Self-Aggregation in a Multimodel Ensemble of Radiative-Convective Equilibrium Simulations.

The Radiative‐Convective Equilibrium Model Intercomparison Project (RCEMIP) is an intercomparison of multiple types of numerical models configured in radiative‐convective equilibrium (RCE). RCE is an idealization of the tropical atmosphere that has long been used to study basic questions in climate science. Here, we employ RCE to investigate the role that clouds and convective activity play in determining cloud feedbacks, climate sensitivity, the state of convective aggregation, and the equilibrium climate. RCEMIP is unique among intercomparisons in its inclusion of a wide range of model types, including atmospheric general circulation models (GCMs), single column models (SCMs), cloud‐resolving models (CRMs), large eddy simulations (LES), and global cloud‐resolving models (GCRMs). The first results are presented from the RCEMIP ensemble of more than 30 models. While there are large differences across the RCEMIP ensemble in the representation of mean profiles of temperature, humidity, and cloudiness, in a majority of models anvil clouds rise, warm, and decrease in area coverage in response to an increase in sea surface temperature (SST). Nearly all models exhibit self‐aggregation in large domains and agree that self‐aggregation acts to dry and warm the troposphere, reduce high cloudiness, and increase cooling to space. The degree of self‐aggregation exhibits no clear tendency with warming. There is a wide range of climate sensitivities, but models with parameterized convection tend to have lower climate sensitivities than models with explicit convection. In models with parameterized convection, aggregated simulations have lower climate sensitivities than unaggregated simulations.

Risk Management in Global CRM IT Projects

Global information technology projects are risky with failure rates for customer relationship management information technology (CRM IT) projects estimated to 70 percent. These failures are often due to multiplicity of factors including poor risk management. The project management literature points out four broad types of risks: technical, external, organizational, and other risk factors. Project manager’s basic job, therefore, becomes to manage the risks and ensure that an IT project is steered to completion while meeting the objectives. Unmanaged risks run into chances of failure and ultimately impacting the CRM project and the reputation of the consultant. Payne and Frow’s (2005) advocates the need for a structured study on the information technology implementations of these projects. The objectives of the study are to investigate: how project risks in CRM- IT implementations impact the final outcome and how the risk management process adopted by the IT project manager impacts the final outcome of the project. The research was conducted administering questionnaire to 135 project managers. It was found that project risk impact cost, time, and technical performance and risk management process impacts planning, support of customers as well as top management.

Insights into Atmospheric Predictability through Global Convection-Permitting Model Simulations

Global convection-permitting models enable weather prediction from local to planetary scales and are therefore often expected to transform the weather prediction enterprise. This potential, however, depends on the predictability of the atmosphere, which was explored here through identical twin experiments using the Model for Prediction Across Scales. The simulations were produced on a quasi-uniform 4-km mesh, which allowed the illumination of error growth from convective to global scales. During the first two days, errors grew through moist convection and other mesoscale processes, and the character of the error growth resembled the case of [Formula: see text] turbulence. Between 2 and 13 days, errors grew with the background baroclinic instability, and the character of the error growth mirrored the case of [Formula: see text] turbulence. The existence of an error growth regime with properties similar to [Formula: see text] turbulence confirmed the radical idea of E. N. Lorenz that the atmosphere has a finite limit of predictability, no matter how small the initial error. The global-mean predictability limit of the troposphere was estimated here to be around 2–3 weeks, which is in agreement with previous work. However, scale-dependent predictability limits differed between the divergent and rotational wind component and between vertical levels, indicating that atmospheric predictability is a more complex problem than that of homogeneous, isotropic turbulence. The practical value of global cloud-resolving models is discussed in light of the various aspects of atmospheric predictability.

Radiative–convective equilibrium model intercomparison project

Abstract. RCEMIP, an intercomparison of multiple types of models configured in radiative–convective equilibrium (RCE), is proposed. RCE is an idealization of the climate system in which there is a balance between radiative cooling of the atmosphere and heating by convection. The scientific objectives of RCEMIP are three-fold. First, clouds and climate sensitivity will be investigated in the RCE setting. This includes determining how cloud fraction changes with warming and the role of self-aggregation of convection in climate sensitivity. Second, RCEMIP will quantify the dependence of the degree of convective aggregation and tropical circulation regimes on temperature. Finally, by providing a common baseline, RCEMIP will allow the robustness of the RCE state across the spectrum of models to be assessed, which is essential for interpreting the results found regarding clouds, climate sensitivity, and aggregation, and more generally, determining which features of tropical climate a RCE framework is useful for. A novel aspect and major advantage of RCEMIP is the accessibility of the RCE framework to a variety of models, including cloud-resolving models, general circulation models, global cloud-resolving models, single-column models, and large-eddy simulation models.

Toward unification of the multiscale modeling of the atmosphere

Abstract. As far as the representation of deep moist convection is concerned, only two kinds of model physics are used at present: highly parameterized as in the conventional general circulation models (GCMs) and explicitly simulated as in the cloud-resolving models (CRMs). Ideally, these two kinds of model physics should be unified so that a continuous transition of model physics from one kind to the other takes place as the resolution changes. With such unification, the GCM can converge to a global CRM (GCRM) as the grid size is refined. This paper suggests two possible routes to achieve the unification. ROUTE I continues to follow the parameterization approach, but uses a unified parameterization that is applicable to any horizontal resolutions between those typically used by GCMs and CRMs. It is shown that a key to construct such a unified parameterization is to eliminate the assumption of small fractional area covered by convective clouds, which is commonly used in the conventional cumulus parameterizations either explicitly or implicitly. A preliminary design of the unified parameterization is presented, which demonstrates that such an assumption can be eliminated through a relatively minor modification of the existing mass-flux based parameterizations. Partial evaluations of the unified parameterization are also presented. ROUTE II follows the "multi-scale modeling framework (MMF)" approach, which takes advantage of explicit representation of deep moist convection and associated cloud-scale processes by CRMs. The Quasi-3-D (Q3-D) MMF is an attempt to broaden the applicability of MMF without necessarily using a fully three-dimensional CRM. This is accomplished using a network of cloud-resolving grids with large gaps. An outline of the Q3-D algorithm and highlights of preliminary results are reviewed.

Analyzing the Diffusion of Global Customer Relationship Management: A Cross-Regional Modeling Framework

Most recent research on customer relationship management (CRM) has been restricted to developed economies such as the United States. Researchers have done little to study the growth of CRM in developing markets such as Asia and South America, which are becoming increasingly relevant to business today. With the changing business climate, firms are beginning to embrace the concept of managing customers rather than products. This leads managers down the path of customer centricity, and here lies the relevance of truly global CRM (GCRM). The authors conduct a qualitative study to understand the concept of GCRM and its relevance. Their results quantify the growth of CRM on a global scale using a diffusion modeling framework. The results of the generalized cross-regional diffusion model indicate that there is untapped market potential in the GCRM market, with varying adoption patterns across regions. The authors also propose a conceptual framework to understand the factors that affect cross-regional learning in GCRM adoption. In addition, the study provides insights into implementation and calibration of a GCRM framework and directions for further research.

Unification of the Anelastic and Quasi-Hydrostatic Systems of Equations

Abstract A system of equations is presented that unifies the nonhydrostatic anelastic system and the quasi-hydrostatic compressible system for use in global cloud-resolving models. By using a properly defined quasi-hydrostatic density in the continuity equation, the system is fully compressible for quasi-hydrostatic motion and anelastic for purely nonhydrostatic motion. In this way, the system can cover a wide range of horizontal scales from turbulence to planetary waves while filtering vertically propagating sound waves of all scales. The continuity equation is primarily diagnostic because the time derivative of density is calculated from the thermodynamic (and surface pressure tendency) equations as a correction to the anelastic continuity equation. No reference state is used and no approximations are made in the momentum and thermodynamic equations. An equation that governs the time change of total energy is also derived. Normal-mode analysis on an f plane without the quasigeostrophic approximation and on a midlatitude β plane with the quasigeostrophic approximation is performed to compare the unified system with other systems. It is shown that the unified system reduces the westward retrogression speed of the ultra-long barotropic Rossby waves through the inclusion of horizontal divergence due to compressibility.

A Madden-Julian Oscillation Event Realistically Simulated by a Global Cloud-Resolving Model

A Madden-Julian Oscillation (MJO) is a massive weather event consisting of deep convection coupled with atmospheric circulation, moving slowly eastward over the Indian and Pacific Oceans. Despite its enormous influence on many weather and climate systems worldwide, it has proven very difficult to simulate an MJO because of assumptions about cumulus clouds in global meteorological models. Using a model that allows direct coupling of the atmospheric circulation and clouds, we successfully simulated the slow eastward migration of an MJO event. Topography, the zonal sea surface temperature gradient, and interplay between eastward- and westward-propagating signals controlled the timing of the eastward transition of the convective center. Our results demonstrate the potential making of month-long MJO predictions when global cloud-resolving models with realistic initial conditions are used.

Developing a Global CRM Strategy

While the managerial rationale for adopting customer relationship management (CRM) has been fairly well articulated in the literature, research on strategy development is scant. Moreover, reports of “CRM failures” in the popular business press have done little to inspire confidence. To date, what little research has been conducted in the area of CRM strategy development has been confined to a single country (often the U.S.). Global CRM strategy development issues have yet to be specifically addressed, particularly which elements of CRM strategy should be centralised/decentralised. The present study examines the complexities of global CRM strategy using the case of a leading financial services company. Interviews are conducted in 20 countries. Global Head Office and external IT consultant perspectives are also considered. Our findings confirm that a hybrid approach has wide practical appeal and that subsidiary orientation towards centralisation/decentralisation is moderated by firm/market size and sophistication.

On the Definition of the Cloud Water Content Fluctuations and Its Effects on the Computation of a Second-Order Liquid Water Correlation

Abstract In subgrid-scale condensation schemes of cloud models, the majority of previous authors have relied on results presented in a paper by Bougeault. In the present paper, second-order liquid water correlations are restated that differ from the former paper but are coherent with the corrigendum of Mellor. These differences are explained here through two different underlying definitions of cloud water content fluctuations; they can be summarized by whether or not unsaturated air within a grid box contributes to the eddy flux of the cloud water content. Taking into account the issue mentioned above, the “buoyancy flux” is also derived. Although the full impact of these changes has not been evaluated here, it may become important for future global cloud-resolving climate models.

Issues and Perspectives in Global Customer Relationship Management

Over the past few decades, cross-border business has experienced unparalleled growth. This growth is due to advances in communication and information technologies, privatization and deregulation in emerging economies, and emergence of the global consumer. As the era of globalization continues to manifest through the emergence of global companies, the importance of customer relationship management (CRM) in these companies has become increasingly significant. Global CRM (GCRM) is the strategic application of the processes and practices of CRM by firms operating in multiple countries or by firms serving customers who span multiple countries, which incorporates relevant differences in business practices, competition, regulatory characteristics, country characteristics, and consumer characteristics to CRM strategies to maximize customer value across the global customer portfolio of the firm. In this article, the authors present an overview of the GCRM environment and the challenges in formulation and implementation of CRM across national boundaries as a source of sustained advantage. The authors also provide a conceptual framework for GCRM and recommendations for future research in Global CRM.

Mid-America Parts Company: An E-Commerce Case Study of a Successful International Small-Medium-Sized Enterprise (SME)

ABSTRACT Mid-America Parts Company (MAPC) is a small U.S. firm located in the Midwest specializing in supplying heavy earthmoving equipment parts worldwide. In the mid-1990s the company began to experience challenges maintaining quality assurance while meeting a broad base of global customer parts needs at a profitable level. In the later half of the 1990s, the company initiated the use of a computer-based system to supply parts more efficiently to their customers. After numerous iterations, in 2000, Mid-America Parts Company finally established a customer data entry system that ensured ease of customer use while maintaining quality assurance. An important outcome of these efforts was enhanced customer relationships. This case study describes the company as it has successfully progressed along that path and identifies current issues yet to be addressed including the networking of both suppliers and customers. This paper includes questions related to reinforcing global customer relationship management (CRM) while pressing for the needs of efficiency gained from advanced computer technology. The information has been collected through site visits (2003 and 2004) in addition to traditional information-gathering methods. Although the company name and names of individuals have been changed, the specifics of the case are true as concerns the actual experience of this small-medium-sized enterprise (SME).

Counting the clouds

Cloud processes are very important for the global circulation of the atmosphere. It is now possible, though very expensive, to simulate the global circulation of the atmosphere using a model with resolution fine enough to explicitly represent the larger individual clouds. An impressive preliminary calculation of this type has already been performed by Japanese scientists, using the Earth Simulator. Within the next few years, such global cloud-resolving models (GCRMs) will be applied to weather prediction, and later they will be used in climatechange simulations. The tremendous advantage of GCRMs, relative to conventional lowerresolution global models, is that GCRMs can avoid many of the questionable "parameterizations" used to represent cloud effects in lower-resolution global models. Although cloud microphysics, turbulence, and radiation must still be parameterized in GCRMs, the high resolution of a GCRM simplifies these problems considerably, relative to conventional models. The United States currently has no project to develop a GCRM, although we have both the computer power and the expertise to do it. A research program aimed at development and applications of GCRMs is outlined.