scholarly journals Helping to Make Sense of Regional Climate Modeling: Professional Development for Scientists and Decision-Makers Anytime, Anywhere

2016 ◽  
Vol 97 (7) ◽  
pp. 1173-1185 ◽  
Author(s):  
Peter J. Walton ◽  
Morgan B. Yarker ◽  
Michel D. S. Mesquita ◽  
Friederike E. L. Otto
Keyword(s):  
Professional Development ◽  
High Resolution ◽  
Climate Models ◽  
Online Courses ◽  
Climate Modeling ◽  
Regional Climate ◽  
Climate Science ◽  
Regional Climate Modeling ◽  
Decision Makers ◽  
E Learning

Abstract Globally, decision-makers are increasingly using high-resolution climate models to support policy and planning; however, many of these users do not have the knowledge needed to use them appropriately. This problem is compounded by not having access to quality learning opportunities to better understand how to apply the models and interpret results. This paper discusses and proposes an educational framework based on two independent online courses on regional climate modeling, which addresses the accessibility issue and provides guidance to climate science professors, researchers, and institutions who want to create their own online courses. The role of e-learning as an educational tool is well documented, highlighting the benefits of improved personal efficiency through “anywhere, anytime” learning with the flexibility to support professional development across different sectors. In addition, improved global Internet means increased accessibility. However, e-learning’s function as a tool to support understanding of atmospheric physics and high-resolution climate modeling has not been widely discussed. To date, few courses, if any, support understanding that takes full advantage of e-learning best practices. There is a growing need for climate literacy to help inform decision-making on a range of scales, from individual households to corporate CEOs. And while there is a plethora of climate information online, educational theory suggests that people need to be guided in how to convert this information into applicable knowledge. Here, we present how the experience of the courses we designed and ran independent of each other, both engaging learners with better understanding benefits and limitations of regional climate modeling, lead to a framework of designing e-learning for climate modeling.

Using Social Media to Improve Peer Dialogue in an Online Course About Regional Climate Modeling

2018 ◽  
Vol 8 (4) ◽  
pp. 1-21 ◽  
Author(s):  
Morgan B. Yarker ◽  
Michel D.S. Mesquita
Keyword(s):  
Social Media ◽  
Information Exchange ◽  
Online Courses ◽  
Climate Modeling ◽  
Global Climate ◽  
Regional Climate ◽  
Regional Climate Modeling ◽  
Effective Learning ◽  
Classroom Dialogue ◽  
E Learning

Recent technology advancements provide worldwide information exchange that has been invaluable for the scientific community, particularly for issues surrounding global climate change. Many online learning spaces have developed which are often repositories of information rather than a space of knowledge construction. Classroom dialogue is shown to be an important component for effective learning, therefore it should be developed online as well. This article explores how social media can support dialogue in e-learning. Interactions were studied in two online courses about regional climate modeling. The first used traditional forums and the other promoted a Facebook group for online interactions. Qualitative results indicate that the Facebook group showed improvement because elements of dialogue began to emerge, including open-ended questions and episodes of peer discussion. Quantitative findings suggest the Facebook interactions were perceived as more informal and participants posted, responded, and interacted with their peers more significantly than traditional forums.

scholarly journals The Ongoing Need for High-Resolution Regional Climate Models: Process Understanding and Stakeholder Information

2020 ◽  
Vol 101 (5) ◽  
pp. E664-E683 ◽  
Author(s):  
W. J. Gutowski ◽  
P. A. Ullrich ◽  
A. Hall ◽  
L. R. Leung ◽  
T. A. O’Brien ◽  
...  
Keyword(s):  
High Resolution ◽  
Climate Models ◽  
Climate Modeling ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Heavy Precipitation ◽  
Regional Climate Modeling ◽  
Urban Heat Islands ◽  
Global Models ◽  
Strong Winds

ABSTRACT Regional climate modeling addresses our need to understand and simulate climatic processes and phenomena unresolved in global models. This paper highlights examples of current approaches to and innovative uses of regional climate modeling that deepen understanding of the climate system. High-resolution models are generally more skillful in simulating extremes, such as heavy precipitation, strong winds, and severe storms. In addition, research has shown that fine-scale features such as mountains, coastlines, lakes, irrigation, land use, and urban heat islands can substantially influence a region’s climate and its response to changing forcings. Regional climate simulations explicitly simulating convection are now being performed, providing an opportunity to illuminate new physical behavior that previously was represented by parameterizations with large uncertainties. Regional and global models are both advancing toward higher resolution, as computational capacity increases. However, the resolution and ensemble size necessary to produce a sufficient statistical sample of these processes in global models has proven too costly for contemporary supercomputing systems. Regional climate models are thus indispensable tools that complement global models for understanding physical processes governing regional climate variability and change. The deeper understanding of regional climate processes also benefits stakeholders and policymakers who need physically robust, high-resolution climate information to guide societal responses to changing climate. Key scientific questions that will continue to require regional climate models, and opportunities are emerging for addressing those questions.

Generating long-term high-resolution land-use change datasets for regional climate modeling in CORDEX domains

2021 ◽  
Author(s):  
Peter Hoffmann ◽  
Diana Rechid ◽  
Vanessa Reinhart ◽  
Christina Asmus ◽  
Edouard L. Davin ◽  
...  
Keyword(s):  
Land Use ◽  
High Resolution ◽  
Land Use Change ◽  
Land Cover ◽  
Climate Modeling ◽  
Regional Climate ◽  
Regional Climate Modeling ◽  
Local Scale ◽  
Modeling Studies

<p>Land-use and land cover (LULC) are continuously changing due to environmental changes and anthropogenic activities. Many observational and modeling studies show that LULC changes are important drivers altering land surface feedbacks and land-atmosphere exchange processes that have substantial impact on climate on the regional and local scale. Yet, most long-term regional climate modeling studies do not account for these changes. Therefore, within the WCRP CORDEX Flagship Pilot Study LUCAS (Land Use Change Across Scales) a new workflow was developed to generate high-resolution annual land cover change time series based on past reconstructions and future projections. First, the high-resolution global land cover dataset ESA-CCI LC (~300 m resolution) is aggregated and converted to a 0.1° resolution, fractional plant functional type (PFT) dataset. Second, the land use change information from the land-use harmonized dataset (LUH2), provided at 0.25° resolution as input for CMIP6 experiments, is translated into PFT changes employing a newly developed land use translator (LUT). The new LUT was first applied to the EURO-CORDEX domain. The resulting LULC maps for past and future - the LUCAS LUC dataset - can be applied as land use forcing to the next generation RCM simulations for downscaling CMIP6 by the EURO-CORDEX community and in the framework of FPS LUCAS. The dataset includes land cover and land management practices changes important for the regional and local scale such as urbanization and irrigation. The LUCAS LUC workflow is applied to further CORDEX domains, such as Australasia and North America. The resulting past and future land cover changes will be presented, and challenges regarding the application of the new workflow to different regions will be addressed. In addition, issues related to the implementation of the dataset into different RCMs will be discussed.</p>

scholarly journals Regional Climate Modeling over South America: A Review

2013 ◽  
Vol 2013 ◽  
pp. 1-13 ◽  
Author(s):  
Silvina A. Solman
Keyword(s):  
Climate Change ◽  
South America ◽  
Climate Models ◽  
Climate Modeling ◽  
Regional Climate ◽  
Regional Climate Change ◽  
Regional Climate Models ◽  
Regional Climate Modeling ◽  
South American ◽  
Sensitivity Studies

This review summarizes the progress achieved on regional climate modeling activities over South America since the early efforts at the beginning of the 2000s until now. During the last 10 years, simulations with regional climate models (RCMs) have been performed for several purposes over the region. Early efforts were mainly focused on sensitivity studies to both physical mechanisms and technical aspects of RCMs. The last developments were focused mainly on providing high-resolution information on regional climate change. This paper describes the most outstanding contributions from the isolated efforts to the ongoing coordinated RCM activities in the framework of the CORDEX initiative, which represents a major endeavor to produce ensemble climate change projections at regional scales and allows exploring the associated range of uncertainties. The remaining challenges in modeling South American climate features are also discussed.

scholarly journals Deriving user-informed climate information from climate model ensemble results

2017 ◽  
Vol 14 ◽  
pp. 261-269 ◽  
Author(s):  
Heike Huebener ◽  
Peter Hoffmann ◽  
Klaus Keuler ◽  
Susanne Pfeifer ◽  
Hans Ramthun ◽  
...  
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
Climate Modeling ◽  
Research Output ◽  
Model Simulation ◽  
Regional Climate ◽  
Regional Climate Modeling ◽  
Climate Impact ◽  
Final Project ◽  
User Workshop

Abstract. Communication between providers and users of climate model simulation results still needs to be improved. In the German regional climate modeling project ReKliEs-De a midterm user workshop was conducted to allow the intended users of the project results to assess the preliminary results and to streamline the final project results to their needs. The user feedback highlighted, in particular, the still considerable gap between climate research output and user-tailored input for climate impact research. Two major requests from the user community addressed the selection of sub-ensembles and some condensed, easy to understand information on the strengths and weaknesses of the climate models involved in the project.

Regional Climate Modeling for the Baltic Sea Region

2020 ◽  
Author(s):  
Erik Kjellström ◽  
Ole Bøssing Christensen
Keyword(s):  
Climate Change ◽  
Baltic Sea ◽  
Climate Models ◽  
Climate Modeling ◽  
Regional Climate ◽  
Regional Climate Modeling ◽  
Sea Surface ◽  
The Baltic Sea ◽  
Baltic Sea Region ◽  
The Baltic

Regional climate models (RCMs) are commonly used to provide detailed regional to local information for climate change assessments, impact studies, and work on climate change adaptation. The Baltic Sea region is well suited for RCM evaluation due to its complexity and good availability of observations. Evaluation of RCM performance over the Baltic Sea region suggests that: • Given appropriate boundary conditions, RCMs can reproduce many aspects of the climate in the Baltic Sea region. • High resolution improves the ability of RCMs to simulate significant processes in a realistic way. • When forced by global climate models (GCMs) with errors in their representation of the large-scale atmospheric circulation and/or sea surface conditions, performance of RCMs deteriorates. • Compared to GCMs, RCMs can add value on the regional scale, related to both the atmosphere and other parts of the climate system, such as the Baltic Sea, if appropriate coupled regional model systems are used. Future directions for regional climate modeling in the Baltic Sea region would involve testing and applying even more high-resolution, convection permitting, models to generally better represent climate features like heavy precipitation extremes. Also, phenomena more specific to the Baltic Sea region are expected to benefit from higher resolution (these include, for example, convective snowbands over the sea in winter). Continued work on better describing the fully coupled regional climate system involving the atmosphere and its interaction with the sea surface and land areas is also foreseen as beneficial. In this respect, atmospheric aerosols are important components that deserve more attention.

Improving the Simulation of Large Lakes in Regional Climate Modeling: Two-Way Lake–Atmosphere Coupling with a 3D Hydrodynamic Model of the Great Lakes

2017 ◽  
Vol 30 (5) ◽  
pp. 1605-1627 ◽  
Author(s):  
Pengfei Xue ◽  
Jeremy S. Pal ◽  
Xinyu Ye ◽  
John D. Lenters ◽  
Chenfu Huang ◽  
...  
Keyword(s):  
Great Lakes ◽  
Climate Models ◽  
Climate Modeling ◽  
Thermal Structure ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Regional Climate Modeling ◽  
Spatiotemporal Variability ◽  
Lake Ice ◽  
Large Lakes

Abstract Accurate representations of lake–ice–atmosphere interactions in regional climate modeling remain one of the most critical and unresolved issues for understanding large-lake ecosystems and their watersheds. To date, the representation of the Great Lakes two-way interactions in regional climate models is achieved with one-dimensional (1D) lake models applied at the atmospheric model lake grid points distributed spatially across a 2D domain. While some progress has been made in refining 1D lake model processes, such models are fundamentally incapable of realistically resolving a number of physical processes in the Great Lakes. In this study, a two-way coupled 3D lake-ice–climate modeling system [Great Lakes–Atmosphere Regional Model (GLARM)] is developed to improve the simulation of large lakes in regional climate models and accurately resolve the hydroclimatic interactions. Model results are compared to a wide variety of observational data and demonstrate the unique skill of the coupled 3D modeling system in reproducing trends and variability in the Great Lakes regional climate, as well as in capturing the physical characteristics of the Great Lakes by fully resolving the lake hydrodynamics. Simulations of the climatology and spatiotemporal variability of lake thermal structure and ice are significantly improved over previous coupled, 1D simulations. At seasonal and annual time scales, differences in model results are primarily observed for variables that are directly affected by lake surface temperature (e.g., evaporation, precipitation, sensible heat flux) while no significant differences are found in other atmospheric variables (e.g., solar radiation, cloud cover). Underlying physical mechanisms for the simulation improvements using GLARM are also discussed.

scholarly journals Characterization of vegetation fraction estimated using spot-vegetation NDVI data for regional climate modeling in India

MAUSAM ◽  
2021 ◽  
Vol 57 (4) ◽  
pp. 669-674
Author(s):  
S. R. OZA ◽  
R. P. SINGH ◽  
V. K. DADHWAL
Keyword(s):  
Climate Models ◽  
Climate Modeling ◽  
Regional Climate ◽  
Regional Climate Modeling ◽  
Data Sets ◽  
Data Set ◽  
Vegetation Fraction ◽  
Noaa Avhrr ◽  
Significant Difference ◽  
Important Input

lkj & ,e- ,e- 5 tSls eslksLdsy tyok;q fun’kksZa }kjk ouLifr ¼oh- ,Q-½ dh lwpuk nsus dk dk;Z egRoiw.kZ gSA fun’kZu ¼ekWMfyax½ esa lkekU; :Ik ls lcls vf/kd iz;qDr dh xbZ tyok;q laca/kh ekfld oh- ,Q-  gSA oh- ,Q- dh lwpuk,¡ ,u- vks- ,- ,- & ,- oh- ,p- vkj- vkj-  ,u- Mh- oh- vkbZ- HkweaMyh; vk¡dM+k lsVksa dk mi;ksx djrs gq, xqVesu vkSj bXukVkso ¼1988½ ¼th- vkbZ-½ }kjk rS;kj dh xbZ gSA bl 'kks/k&i= esa Hkkjrh; {ks= ds vizSy 1998 ls uoacj 2003 dh vof/k ds LikWV& ost+hVs’ku 10 fnolh; fefJr ,u- Mh- oh- vkbZ- ds mRiknksa dk mi;ksx djrs gq, 1 fd- eh- ds oh- ,Q- ds vk¡dM+k lsV rS;kj djus ds ckjs esa crk;k x;k gSA LikWV&osthVs’ku ds 0 % vkSj 100 % dh  oh- ,Q- ls laca) ,u- Mh- oh- vkbZ- dh laosnd fof’k"V izHkkolhek,¡ th- vkbZ- ds 0-04 vkSj 0-52 dh rqyuk esa Øe’k: 0-04 vkSj 0-804 ikbZ xbZaA th- vkbZ- ds tyok;q laca/kh oh- ,Q ds lkFk izkIr fd, x, oh- ,Q ds vk¡dM+ksa dh rqyuk dh xbZ gSA rhu v{kka’kh; {ks=ksa ¼<16] 16&24] > 24½ ds fy, oh- ,Q- ds fo’ys"k.k ls th- vkbZ- ls 15 % rd dh fHkUurkvksa dk irk pyk gSA o"kkZ&vk/kkfjr Ñf"k okys {ks= esa mYys[kuh; fHkUurk dk irk pyk gSA oh- ,Q- ls izkIr fd, x, ekSleh vkSj o"kZ&izfro"kZ dh fHkUurkvksa ds ifj.kkeksa ij fopkj&foe’kZ fd;k x;k  gSA  Vegetation fraction (VF) is an important input in mesoscale climate models, such as MM5. The most commonly used VF inputs in modeling is the climatic monthly VF generated by Gutman and Ignatov (1998)  (GI) using NOAA-AVHRR NDVI global data sets. This paper reports the generation of 1 km VF data set using SPOT-VEGETATION 10-day composite NDVI products from April 1998 to November 2003 for the Indian region. Sensor-specific thresholds of NDVI associated with 0% and 100% VF for SPOT-VEGETATION were found to be 0.04 and 0.804, respectively, in contrast to 0.04 and 0.52 of GI. Comparison of derived VF with climatic VF of GI was carried out.  Analysis of VF for three latitudinal zones (<16, 16-24, >24) indicated the differences up to 15 percent from GI.  Significant difference was observed for the area having rain-fed agriculture. Results of the seasonal and year-to-year variations of derived VF are discussed.

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