Northern Tales: A Synthesis of MAGS Atmospheric and Hydrometeorological Research

2007 ◽  
Vol 88 (9) ◽  
pp. 1411-1426 ◽  
Author(s):  
K. K. Szeto ◽  
R. E. Stewart ◽  
M. K. Yau ◽  
J. Gyakum
Keyword(s):  
Large Scale ◽  
Water Cycle ◽  
Climate System ◽  
Atmospheric Flows ◽  
Continental Scale ◽  
Weather And Climate ◽  
Scientific Results ◽  
Two Phases ◽  
Key Aspects ◽  
Physical Features

The Mackenzie Global Energy and Water Cycle Experiment (GEWEX) Study (MAGS) is one of the continental-scale experiments approved specifically by GEWEX to better understand and model water and energy cycling at high latitudes. The project has gone through two phases since its inception in 1994 and conclusion in December 2005. Many scientific results have been achieved through MAGS research to advance our understanding of the Mackenzie River basin climate system. This article is a synthesis of its atmospheric research achievements through an integrative description of the basin's climate system, along with highlights of MAGS research that has advanced our knowledge and understanding of various key aspects of the system. In particular, the significance of MAGS research is discussed in the hancing knowledge of the basin's hydroclimate with focuses on i) the large-scale atmospheric processes that control the transport of water and energy into the basin, and ii) the interactions of the large-scale atmospheric flows with physical features of the basin's environment in affecting the weather and climate of the basin.

scholarly journals Weather and Climate Manipulation as an Optimal Control for Adaptive Dynamical Systems

Complexity ◽  
2017 ◽  
Vol 2017 ◽  
pp. 1-12 ◽  
Author(s):  
Sergei A. Soldatenko
Keyword(s):  
Dynamical System ◽  
Optimal Control ◽  
Control Problem ◽  
Large Scale ◽  
Atmospheric Dynamics ◽  
Climate System ◽  
Chaotic Dynamical System ◽  
Weather And Climate ◽  
Earth’S Climate ◽  
Climate Manipulation

The weather and climate manipulation is examined as an optimal control problem for the earth climate system, which is considered as a complex adaptive dynamical system. Weather and climate manipulations are actually amorphous operations. Since their objectives are usually formulated vaguely, the expected results are fairly unpredictable and uncertain. However, weather and climate modification is a purposeful process and, therefore, we can formulate operations to manipulate weather and climate as the optimization problem within the framework of the optimal control theory. The complexity of the earth’s climate system is discussed and illustrated using the simplified low-order coupled chaotic dynamical system. The necessary conditions of optimality are derived for the large-scale atmospheric dynamics. This confirms that even a relatively simplified control problem for the atmospheric dynamics requires significant efforts to obtain the solution.

Information And Map-Made Control With The Functions Of Business Analytics For Urban Management

2019 ◽  
pp. 72-78
Keyword(s):  
Large Scale ◽  
Information Support ◽  
Urban Management ◽  
Business Analytics ◽  
Administrative District ◽  
The North ◽  
Model Of Management ◽  
Complex Development ◽  
Coordination System ◽  
Key Aspects

The key aspects of the process of designing and developing an information and cartographic control tool with business analytics functions for the municipal level of urban management are considered. The review of functionality of the developed tool is given. Examples of its use for the analysis and monitoring of implementation of the program of complex development of territories are given. The importance of application of information support of management and coordination at all levels of management as an integral part of the basic model of management and coordination system of large-scale urban projects of dispersed construction is proved. Information and map-made tool with business intelligence functions was used and was highly appreciated in the preparation of information-analytical and presentation materials of the North-Eastern Administrative District of Moscow. Its use made it possible to significantly optimize the list of activities of the program of integrated development of territories, their priority and timing.

scholarly journals Analog Downscaling of Seasonal Rainfall Forecasts in the Murray Darling Basin

2013 ◽  
Vol 141 (3) ◽  
pp. 1099-1117 ◽  
Author(s):  
Andrew Charles ◽  
Bertrand Timbal ◽  
Elodie Fernandez ◽  
Harry Hendon
Keyword(s):  
General Circulation ◽  
Large Scale ◽  
Seasonal Prediction ◽  
General Circulation Models ◽  
Meridional Wind ◽  
Seasonal Forecasts ◽  
Local Climate ◽  
Continental Scale ◽  
Predictive Skill ◽  
Murray Darling Basin

Abstract Seasonal predictions based on coupled atmosphere–ocean general circulation models (GCMs) provide useful predictions of large-scale circulation but lack the conditioning on topography required for locally relevant prediction. In this study a statistical downscaling model based on meteorological analogs was applied to continental-scale GCM-based seasonal forecasts and high quality historical site observations to generate a set of downscaled precipitation hindcasts at 160 sites in the South Murray Darling Basin region of Australia. Large-scale fields from the Predictive Ocean–Atmosphere Model for Australia (POAMA) 1.5b GCM-based seasonal prediction system are used for analog selection. Correlation analysis indicates modest levels of predictability in the target region for the selected predictor fields. A single best-match analog was found using model sea level pressure, meridional wind, and rainfall fields, with the procedure applied to 3-month-long reforecasts, initialized on the first day of each month from 1980 to 2006, for each model day of 10 ensemble members. Assessment of the total accumulated rainfall and number of rainy days in the 3-month reforecasts shows that the downscaling procedure corrects the local climate variability with no mean effect on predictive skill, resulting in a smaller magnitude error. The amount of total rainfall and number of rain days in the downscaled output is significantly improved over the direct GCM output as measured by the difference in median and tercile thresholds between station observations and downscaled rainfall. Confidence in the downscaled output is enhanced by strong consistency between the large-scale mean of the downscaled and direct GCM precipitation.

scholarly journals Transferability Intercomparison: An Opportunity for New Insight on the Global Water Cycle and Energy Budget

2007 ◽  
Vol 88 (3) ◽  
pp. 375-384 ◽  
Author(s):  
E. S. Takle ◽  
J. Roads ◽  
B. Rockel ◽  
W. J. Gutowski ◽  
R. W. Arritt ◽  
...  
Keyword(s):  
Energy Budget ◽  
Climate Models ◽  
Climate Model ◽  
Water Cycle ◽  
Regional Climate ◽  
Climate Conditions ◽  
Continental Scale ◽  
Global Water Cycle ◽  
Wide Range ◽  
Global Water

A new approach, called transferability intercomparisons, is described for advancing both understanding and modeling of the global water cycle and energy budget. Under this approach, individual regional climate models perform simulations with all modeling parameters and parameterizations held constant over a specific period on several prescribed domains representing different climatic regions. The transferability framework goes beyond previous regional climate model intercomparisons to provide a global method for testing and improving model parameterizations by constraining the simulations within analyzed boundaries for several domains. Transferability intercomparisons expose the limits of our current regional modeling capacity by examining model accuracy on a wide range of climate conditions and realizations. Intercomparison of these individual model experiments provides a means for evaluating strengths and weaknesses of models outside their “home domains” (domain of development and testing). Reference sites that are conducting coordinated measurements under the continental-scale experiments under the Global Energy and Water Cycle Experiment (GEWEX) Hydrometeorology Panel provide data for evaluation of model abilities to simulate specific features of the water and energy cycles. A systematic intercomparison across models and domains more clearly exposes collective biases in the modeling process. By isolating particular regions and processes, regional model transferability intercomparisons can more effectively explore the spatial and temporal heterogeneity of predictability. A general improvement of model ability to simulate diverse climates will provide more confidence that models used for future climate scenarios might be able to simulate conditions on a particular domain that are beyond the range of previously observed climates.

Global scale hydrological modelling at 100 m, 1 h resolution, in Python

2021 ◽  
Author(s):  
Kor de Jong ◽  
Marc van Kreveld ◽  
Debabrata Panja ◽  
Oliver Schmitz ◽  
Derek Karssenberg
Keyword(s):  
Large Scale ◽  
Model Building ◽  
Flow Direction ◽  
Building Blocks ◽  
Global Scale ◽  
Data Availability ◽  
Hydrological Models ◽  
Continental Scale ◽  
Modelling Framework ◽  
Scale Models

<p>Data availability at global scale is increasing exponentially. Although considerable challenges remain regarding the identification of model structure and parameters of continental scale hydrological models, we will soon reach the situation that global scale models could be defined at very high resolutions close to 100 m or less. One of the key challenges is how to make simulations of these ultra-high resolution models tractable ([1]).</p><p>Our research contributes by the development of a model building framework that is specifically designed to distribute calculations over multiple cluster nodes. This framework enables domain experts like hydrologists to develop their own large scale models, using a scripting language like Python, without the need to acquire the skills to develop low-level computer code for parallel and distributed computing.</p><p>We present the design and implementation of this software framework and illustrate its use with a prototype 100 m, 1 h continental scale hydrological model. Our modelling framework ensures that any model built with it is parallelized. This is made possible by providing the model builder with a set of building blocks of models, which are coded in such a manner that parallelization of calculations occurs within and across these building blocks, for any combination of building blocks. There is thus full flexibility on the side of the modeller, without losing performance.</p><p>This breakthrough is made possible by applying a novel approach to the implementation of the model building framework, called asynchronous many-tasks, provided by the HPX C++ software library ([3]). The code in the model building framework expresses spatial operations as large collections of interdependent tasks that can be executed efficiently on individual laptops as well as computer clusters ([2]). Our framework currently includes the most essential operations for building large scale hydrological models, including those for simulating transport of material through a flow direction network. By combining these operations, we rebuilt an existing 100 m, 1 h resolution model, thus far used for simulations of small catchments, requiring limited coding as we only had to replace the computational back end of the existing model. Runs at continental scale on a computer cluster show acceptable strong and weak scaling providing a strong indication that global simulations at this resolution will soon be possible, technically speaking.</p><p>Future work will focus on extending the set of modelling operations and adding scalable I/O, after which existing models that are currently limited in their ability to use the computational resources available to them can be ported to this new environment.</p><p>More information about our modelling framework is at https://lue.computationalgeography.org.</p><p><strong>References</strong></p><p>[1] M. Bierkens. Global hydrology 2015: State, trends, and directions. Water Resources Research, 51(7):4923–4947, 2015.<br>[2] K. de Jong, et al. An environmental modelling framework based on asynchronous many-tasks: scalability and usability. Submitted.<br>[3] H. Kaiser, et al. HPX - The C++ standard library for parallelism and concurrency. Journal of Open Source Software, 5(53):2352, 2020.</p>

Plan for the development of specialized climate forecasting in NEACC

2021 ◽  
pp. 101-111
Author(s):  
S.V. Emelina ◽  
◽  
V.M. Khan ◽  
Keyword(s):  
Large Scale ◽  
Regional Climate ◽  
Optimal Strategies ◽  
Economic Sectors ◽  
Climate Services ◽  
Climate Conditions ◽  
Climate Risks ◽  
The North ◽  
Weather And Climate ◽  
North Eurasia

The possibility of developing specialized seasonal forecasting within the framework of the North Eurasia Climate Centre is discussed. The purpose of these forecasts is to access the impacts of significant large-scale anomalies of meteorological elements on various economic sectors for the timely informing of government services and private businesses to select optimal strategies for planning preventive measures. A brief overview of the groups of climatic risks in the context of the impacts on the socio-economic sphere is given according to the Russian and foreign bibliographic sources. Examples of the activities of some Regional Climate Centers that produce forecast information with an assessment of possible impacts of weather and climate conditions at seasonal scales on various human activities are given. Keywords: climate services, regional climate forums, weather and climate risks, North Eurasia Climate Centre

scholarly journals Herbarium specimens reveal substantial and unexpected variation in phenological sensitivity across the eastern United States

2018 ◽  
Vol 374 (1763) ◽  
pp. 20170394 ◽  
Author(s):  
Daniel S. Park ◽  
Ian Breckheimer ◽  
Alex C. Williams ◽  
Edith Law ◽  
Aaron M. Ellison ◽  
...  
Keyword(s):  
United States ◽  
Climatic Change ◽  
Large Scale ◽  
Critical Role ◽  
Flowering Plant ◽  
Reproductive Phenology ◽  
Herbarium Specimens ◽  
Eastern United States ◽  
Regional Patterns ◽  
Continental Scale

Phenology is a key biological trait that can determine an organism's survival and provides one of the clearest indicators of the effects of recent climatic change. Long time-series observations of plant phenology collected at continental scales could clarify latitudinal and regional patterns of plant responses and illuminate drivers of that variation, but few such datasets exist. Here, we use the web tool CrowdCurio to crowdsource phenological data from over 7000 herbarium specimens representing 30 diverse flowering plant species distributed across the eastern United States. Our results, spanning 120 years and generated from over 2000 crowdsourcers, illustrate numerous aspects of continental-scale plant reproductive phenology. First, they support prior studies that found plant reproductive phenology significantly advances in response to warming, especially for early-flowering species. Second, they reveal that fruiting in populations from warmer, lower latitudes is significantly more phenologically sensitive to temperature than that for populations from colder, higher-latitude regions. Last, we found that variation in phenological sensitivities to climate within species between regions was of similar magnitude to variation between species. Overall, our results suggest that phenological responses to anthropogenic climate change will be heterogeneous within communities and across regions, with large amounts of regional variability driven by local adaptation, phenotypic plasticity and differences in species assemblages. As millions of imaged herbarium specimens become available online, they will play an increasingly critical role in revealing large-scale patterns within assemblages and across continents that ultimately can improve forecasts of the impacts of climatic change on the structure and function of ecosystems. This article is part of the theme issue ‘Biological collections for understanding biodiversity in the Anthropocene’.

scholarly journals Self-Adaptive K-Means Based on a Covering Algorithm

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-16 ◽  
Author(s):  
Yiwen Zhang ◽  
Yuanyuan Zhou ◽  
Xing Guo ◽  
Jintao Wu ◽  
Qiang He ◽  
...  
Keyword(s):  
Large Scale ◽  
Clustering Algorithm ◽  
Real Data ◽  
Second Phase ◽  
Data Sets ◽  
Number Of Clusters ◽  
Large Scale Data ◽  
Long Time ◽  
Two Phases ◽  
Selection Of

The K-means algorithm is one of the ten classic algorithms in the area of data mining and has been studied by researchers in numerous fields for a long time. However, the value of the clustering number k in the K-means algorithm is not always easy to be determined, and the selection of the initial centers is vulnerable to outliers. This paper proposes an improved K-means clustering algorithm called the covering K-means algorithm (C-K-means). The C-K-means algorithm can not only acquire efficient and accurate clustering results but also self-adaptively provide a reasonable numbers of clusters based on the data features. It includes two phases: the initialization of the covering algorithm (CA) and the Lloyd iteration of the K-means. The first phase executes the CA. CA self-organizes and recognizes the number of clusters k based on the similarities in the data, and it requires neither the number of clusters to be prespecified nor the initial centers to be manually selected. Therefore, it has a “blind” feature, that is, k is not preselected. The second phase performs the Lloyd iteration based on the results of the first phase. The C-K-means algorithm combines the advantages of CA and K-means. Experiments are carried out on the Spark platform, and the results verify the good scalability of the C-K-means algorithm. This algorithm can effectively solve the problem of large-scale data clustering. Extensive experiments on real data sets show that the accuracy and efficiency of the C-K-means algorithm outperforms the existing algorithms under both sequential and parallel conditions.

scholarly journals The effect of deforestation on the water cycle in the amazon basin: an attempt reformulate the problem

1985 ◽  
Vol 15 (3-4) ◽  
pp. 307-310 ◽  
Author(s):  
J. R. Gat ◽  
Ε. Matsui ◽  
Ε. Salati
Keyword(s):  
Large Scale ◽  
Amazon Basin ◽  
Water Cycle ◽  
Water Flux ◽  
Atmospheric Stability ◽  
Local Heat ◽  
Physical Geography ◽  
Cloud Formation ◽  
Evaporative Water ◽  
Stability Structure

If widespread deforestation in Amazon results in reduced evaporative water flux, then either a decrease in evaporation is compensated locally by reduced rainfall,or else changed moisture balance expresses itself downwind in the yet undisturbed forest. The question of where rain will occur is crucial. It is suggested that the appearance of clouds and the occurrence of rainout is governed primarily by the interplay of local meteorologic and physical geography parameters with the atmospheric stability structure except for a few well-defined periods when rain is dominated by large scale atmospheric instability. This means that the study of these phenomena (local heat balances,studies on cloud formation mechanism, vertical atmospheric stability, etc.) must be made on the scale of the cloud size, a few tens of kilometers at most.

Multiscale Convective Organization and the YOTC Virtual Global Field Campaign

2012 ◽  
Vol 93 (8) ◽  
pp. 1171-1187 ◽  
Author(s):  
Mitchell W. Moncrieff ◽  
Duane E. Waliser ◽  
Martin J. Miller ◽  
Melvyn A. Shapiro ◽  
Ghassem R. Asrar ◽  
...  
Keyword(s):  
Time Scales ◽  
Climate Models ◽  
Water Cycle ◽  
Building Blocks ◽  
Tropical Convection ◽  
Global Water Cycle ◽  
Weather And Climate ◽  
Impact Phenomena ◽  
Meteorological Systems ◽  
The Tropics

The Year of Tropical Convection (YOTC) project recognizes that major improvements are needed in how the tropics are represented in climate models. Tropical convection is organized into multiscale precipitation systems with an underlying chaotic order. These organized systems act as building blocks for meteorological events at the intersection of weather and climate (time scales up to seasonal). These events affect a large percentage of the world's population. Much of the uncertainty associated with weather and climate derives from incomplete understanding of how meteorological systems on the mesoscale (~1–100 km), synoptic scale (~1,000 km), and planetary scale (~10,000 km) interact with each other. This uncertainty complicates attempts to predict high-impact phenomena associated with the tropical atmosphere, such as tropical cyclones, the Madden–Julian oscillation, convectively coupled tropical waves, and the monsoons. These and other phenomena influence the extratropics by migrating out of the tropics and by the remote effects of planetary waves, including those generated by the MJO. The diurnal and seasonal cycles modulate all of the above. It will be impossible to accurately predict climate on regional scales or to comprehend the variability of the global water cycle in a warmer world without comprehensively addressing tropical convection and its interactions across space and time scales.

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