Academic literature on the topic 'High-resolution Regional Climate Model'
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Journal articles on the topic "High-resolution Regional Climate Model"
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Meissner, Cathérine Schädler, Hans-Jürgen Feldmann Panitz, and Christoph Kottmeier. "High-resolution sensitivity studies with the regional climate model COSMO-CLM." Meteorologische Zeitschrift 18, no. 5 (October 1, 2009): 543–57. http://dx.doi.org/10.1127/0941-2948/2009/0400.
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Suklitsch, Martin, Andreas Gobiet, Armin Leuprecht, and Christoph Frei. "High Resolution Sensitivity Studies with the Regional Climate Model CCLM in the Alpine Region." Meteorologische Zeitschrift 17, no. 4 (August 25, 2008): 467–76. http://dx.doi.org/10.1127/0941-2948/2008/0308.
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Mendoza, Pablo A., Balaji Rajagopalan, Martyn P. Clark, Kyoko Ikeda, and Roy M. Rasmussen. "Statistical Postprocessing of High-Resolution Regional Climate Model Output." Monthly Weather Review 143, no. 5 (May 1, 2015): 1533–53. http://dx.doi.org/10.1175/mwr-d-14-00159.1.
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Abstract Statistical postprocessing techniques have become essential tools for downscaling large-scale information to the point scale, and also for providing a better probabilistic characterization of hydrometeorological variables in simulation and forecasting applications at both short and long time scales. In this paper, the authors assess the utility of statistical postprocessing methods for generating probabilistic estimates of daily precipitation totals, using deterministic high-resolution outputs obtained with the Weather Research and Forecasting (WRF) Model. After a preliminary assessment of WRF simulations over a historical period, the performance of three postprocessing techniques is compared: multinomial logistic regression (MnLR), quantile regression (QR), and Bayesian model averaging (BMA)—all of which use WRF outputs as potential predictors. Results demonstrate that the WRF Model has skill in reproducing observed precipitation events, especially during fall/winter. Furthermore, it is shown that the spatial distribution of skill obtained from statistical postprocessing is closely linked with the quality of WRF precipitation outputs. A detailed comparison of statistical precipitation postprocessing approaches reveals that, although the poorest performance was obtained using MnLR, there is not an overall best technique. While QR should be preferred if skill (i.e., small probability forecast errors) and reliability (i.e., match between forecast probabilities and observed frequencies) are target properties, BMA is recommended in cases when discrimination (i.e., prediction of occurrence versus nonoccurrence) and statistical consistency (i.e., equiprobability of the observations within their ensemble distributions) are desired. Based on the results obtained here, the authors believe that future research should explore frameworks reconciling hierarchical Bayesian models with the use of the extreme value theory for high precipitation events.
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Berg, P., H. Feldmann, and H. J. Panitz. "Bias correction of high resolution regional climate model data." Journal of Hydrology 448-449 (July 2012): 80–92. http://dx.doi.org/10.1016/j.jhydrol.2012.04.026.
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Drost, Frank, James Renwick, B. Bhaskaran, Hilary Oliver, and James McGregor. "Simulation of New Zealand's climate using a high-resolution nested regional climate model." International Journal of Climatology 27, no. 9 (2007): 1153–69. http://dx.doi.org/10.1002/joc.1461.
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Wagner, Sven, Peter Berg, Gerd Schädler, and Harald Kunstmann. "High resolution regional climate model simulations for Germany: Part II—projected climate changes." Climate Dynamics 40, no. 1-2 (September 13, 2012): 415–27. http://dx.doi.org/10.1007/s00382-012-1510-1.
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Jadmiko, Syamsu Dwi, and Akhmad Faqih. "Dynamical Downscaling Luaran Global Climate Model (GCM) Menggunakan Model REGCM3 untuk Proyeksi Curah Hujan di Kabupaten Indramayu." Agromet 28, no. 1 (February 8, 2018): 9. http://dx.doi.org/10.29244/j.agromet.28.1.9-16.
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Future rainfall projection can be predicted by using Global Climate Model (GCM). In spite of low resolution, we are not able specifically to describe a local or regional information. Therefore, we applied downscaling technique of GCM output using Regional Climate Model (RCM). In this case, Regional Climate Model version 3 (RegCM3) is used to accomplish this purpose. RegCM3 is regional climate model which atmospheric properties are calculated by solving equations of motion and thermodynamics. Thus, RegCM3 is also called as dynamic downscaling model. RegCM3 has reliable capability to evaluate local or regional climate in high spatial resolution up to 10 × 10 km. In this study, dynamically downscaling techniques was applied to produce high spatial resolution (20 × 20 km) from GCM EH5OM output which commonly has rough spatial resolution (1.875<sup>o</sup> × 1.875<sup>o</sup>). Simulation show that future rainfall in Indramayu is relatively decreased compared to the baseline condition. Decreased rainfall generally occurs during the dry season (July-June-August/JJA) in a range 10-20%. Study of extreme daily rainfall indicates that there is no significant increase or decrease value.
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Demory, Marie-Estelle, Ségolène Berthou, Jesús Fernández, Silje L. Sørland, Roman Brogli, Malcolm J. Roberts, Urs Beyerle, et al. "European daily precipitation according to EURO-CORDEX regional climate models (RCMs) and high-resolution global climate models (GCMs) from the High-Resolution Model Intercomparison Project (HighResMIP)." Geoscientific Model Development 13, no. 11 (November 11, 2020): 5485–506. http://dx.doi.org/10.5194/gmd-13-5485-2020.
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Abstract. In this study, we evaluate a set of high-resolution (25–50 km horizontal grid spacing) global climate models (GCMs) from the High-Resolution Model Intercomparison Project (HighResMIP), developed as part of the EU-funded PRIMAVERA (Process-based climate simulation: Advances in high resolution modelling and European climate risk assessment) project, and from the EURO-CORDEX (Coordinated Regional Climate Downscaling Experiment) regional climate models (RCMs) (12–50 km horizontal grid spacing) over a European domain. It is the first time that an assessment of regional climate information using ensembles of both GCMs and RCMs at similar horizontal resolutions has been possible. The focus of the evaluation is on the distribution of daily precipitation at a 50 km scale under current climate conditions. Both the GCM and RCM ensembles are evaluated against high-quality gridded observations in terms of spatial resolution and station density. We show that both ensembles outperform GCMs from the 5th Coupled Model Intercomparison Project (CMIP5), which cannot capture the regional-scale precipitation distribution properly because of their coarse resolutions. PRIMAVERA GCMs generally simulate precipitation distributions within the range of EURO-CORDEX RCMs. Both ensembles perform better in summer and autumn in most European regions but tend to overestimate precipitation in winter and spring. PRIMAVERA shows improvements in the latter by reducing moderate-precipitation rate biases over central and western Europe. The spatial distribution of mean precipitation is also improved in PRIMAVERA. Finally, heavy precipitation simulated by PRIMAVERA agrees better with observations in most regions and seasons, while CORDEX overestimates precipitation extremes. However, uncertainty exists in the observations due to a potential undercatch error, especially during heavy-precipitation events. The analyses also confirm previous findings that, although the spatial representation of precipitation is improved, the effect of increasing resolution from 50 to 12 km horizontal grid spacing in EURO-CORDEX daily precipitation distributions is, in comparison, small in most regions and seasons outside mountainous regions and coastal regions. Our results show that both high-resolution GCMs and CORDEX RCMs provide adequate information to end users at a 50 km scale.
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Walter, Andreas, Klaus Keuler, Daniela Jacob, Richard Knoche, Alexander Block, Sven Kotlarski, Gerhard Müller-Westermeier, Diana Rechid, and Wilfried Ahrens. "A high resolution reference data set of German wind velocity 19512001 and comparison with regional climate model results." Meteorologische Zeitschrift 15, no. 6 (December 20, 2006): 585–96. http://dx.doi.org/10.1127/0941-2948/2006/0162.
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Wang, Xiuquan, Guohe Huang, Qianguo Lin, and Jinliang Liu. "High-Resolution Probabilistic Projections of Temperature Changes over Ontario, Canada." Journal of Climate 27, no. 14 (July 10, 2014): 5259–84. http://dx.doi.org/10.1175/jcli-d-13-00717.1.
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Abstract Planning of mitigation and adaptation strategies to a changing climate can benefit from a good understanding of climate change impacts on human life and local society, which leads to an increasing requirement for reliable projections of future climate change at regional scales. This paper presents an ensemble of high-resolution regional climate simulations for the province of Ontario, Canada, developed with the Providing Regional Climates for Impacts Studies (PRECIS) modeling system. A Bayesian statistical model is proposed through an advance to the method proposed by Tebaldi et al. for generating probabilistic projections of temperature changes at gridpoint scale by treating the unknown quantities of interest as random variables to quantify their uncertainties in a statistical way. Observations for present climate and simulations from the ensemble are fed into the statistical model to derive posterior distributions of all the uncertain quantities through a Markov chain Monte Carlo (MCMC) sampling algorithm. Detailed analyses at 12 selected weather stations are conducted to investigate the practical significance of the proposed statistical model. Following that, maps of projected temperature changes at different probability levels are presented to help understand the spatial patterns across the entire province. The analysis shows that there is likely to be a significant warming trend throughout the twenty-first century. It also suggests that people in Ontario are very likely to suffer a change greater than 2°C to mean temperature in the forthcoming decades and very unlikely to suffer a change greater than 10°C to the end of this century.
Dissertations / Theses on the topic "High-resolution Regional Climate Model"
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Pal, Sujan, and Sujan Pal. "Application of High-Resolution Regional Climate Model Product in Climate and Weather Research." Thesis, The University of Arizona, 2017. http://hdl.handle.net/10150/624093.
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Accurate regional and local scale information about seasonal climate variability and its impact on water availability is important in many practical applications like agriculture, water resource planning, long term decision making etc. Presently, the primary source for real-time seasonal climate forecast comes from the CPC within the NOAA-NCEP which uses its model forecast component (CFSv2) of North American Multi-Model Ensemble (NMME). But it has been observed that in comparison to the cool season, the level of skill in warm season seasonal forecasts of precipitation produced by the NMME is much lower (Kirtman et al. 2014) due to the poor climatological representation of warm season convective precipitation. To fully realise the potential in improving warm season seasonal forecasts using a dynamical modeling approach requires dynamical downscaling of NMME models to better improve their representation of convective precipitation at a convective-permitting (3km) grid. A decade-long CFSR (the reanalysis product of CFS) data is dynamically downscaled using WRF to demonstrate the value added of convective permitting modeling in the representation of mean and extreme warm season precipitation over the Southwest United States. The study shows evidence that the use of regional model adds value to the reanalyses in terms to better special and temporal representation which is also consistent with previous studies and appears to be an important initial step towards seasonal to subseasonal (S2S) forecasting.
Empirical observations show that the structure and size of tropical cyclones (TCs) have dramatic impacts at landfall, including wind damage and storm surge. A better understanding of how the large-scale environment affects TC size and size change might be helpful in the predictions of the TC environment to infer how the TC size might change close to landfall. This study investigates the influence of environmental factors on TC size expansions using numerical simulations. Two periods of size change are investigated one in Hurricane Katrina (2005) as it moved through the Gulf of Mexico and one in Igor (2010) as it begins to undergo extratropical transition. Size changes are evaluated using the North Atlantic Hurricane Database second generation (HURDAT2) data set, which contains the maximum radial extent of the 64-, 50- and 34-kt wind in four quadrants. The average 34-kt wind radius (R34) is used as an indicator of the size of the TC. For the purposes of this study, the environment of a TC is investigated if the wind field either expanded or contracted in size at least 15 n mi radially in a 12-hour period. The regional model used is WRF-ARW. The results found from the simulation of Hurricane Katrina support previous results that increased surface fluxes and higher moisture availability is conducive to TC wind expansion and that as the moisture is depleted, the expansion of the wind field is no longer supported. In the case of Hurricane Igor, the influences of the midlatitude westerlies was evident in the increasing deep vertical wind shear, which is known to be detrimental to TC structure and intensity when strong enough.
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Meissner, Cathérine. "High-resolution sensitivity studies with the regional climate model COSMO-CLM." Karlsruhe Univ.-Verl. Karlsruhe, 2008. http://d-nb.info/992844436/04.
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Meyer, Jonathan D. D. "Modeling and Projection of the North American Monsoon Using a High-Resolution Regional Climate Model." DigitalCommons@USU, 2017. https://digitalcommons.usu.edu/etd/5802.
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This dissertation aims to better understand how various climate modeling approaches affect the fidelity of the North American Monsoon (NAM), as well as the sensitivity of the future state of the NAM under a global warming scenario. Here, we improved over current fully-coupled general circulation models (GCM), which struggle to fully resolve the controlling dynamics responsible for the development and maintenance of the NAM. To accomplish this, we dynamically downscaled a GCM with a regional climate model (RCM). The advantage here being a higher model resolution that improves the representation of processes on scales beyond that which GCMs can resolve. However, as all RCM applications are subject to the transference of biases inherent to the parent GCM, this study developed and evaluated a process to reduce these biases. Pertaining to both precipitation and the various controlling dynamics of the NAM, we found simulations driven by these bias-corrected forcing conditions performed moderately better across a 32-year historical climatology than simulations driven by the original GCM data.
Current GCM consensus suggests future tropospheric warming associated with increased radiative forcing as greenhouse gas concentrations increase will suppress the NAM convective environment through greater atmospheric stability. This mechanism yields later onset dates and a generally drier season, but a slight increase to the intensity during July-August. After comparing downscaled simulations forced with original and corrected forcing conditions, we argue that the role of unresolved GCM surface features such as changes to the Gulf of California evaporation lead to a more convective environment. Even when downscaling the original GCM data with known biases, the inclusion of these surface features altered and in some cases reversed GCM trends throughout the southwest United States. This reversal towards a wetter NAM is further magnified in future bias-corrected simulations, which suggest (1) fewer average number of dry days by the end of the 21st century (2) onset occurring up to two to three weeks earlier than the historical average, and (3) more extreme daily precipitation values. However, consistent across each GCM and RCM model is the increase in inter-annual variability, suggesting greater susceptibility to drought conditions in the future.
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Karmacharya, Jagadishwor. "Climate processes over the Himalaya : the added value from high resolution regional climate modelling." Thesis, University of Oxford, 2014. http://ora.ox.ac.uk/objects/uuid:a8cec5ba-b837-49c0-abd4-62c26d71dffd.
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The Himalaya plays a vital role in shaping the hydro-climate of South Asia and beyond, but their climate has not yet been monitored and modelled as well as some other regions. As the summer monsoon is the dominant climate system over South Asia, including the Himalaya, realistic simulation of the South Asian summer monsoon (SASM) should be a prerequisite for the satisfactory simulation of the Himalayan climate. The present research tests the assumption that higher resolution modelling will provide improved representation of the SASM, both regionally and over the Himalaya region. The first part of this research assesses the strength and stability of the temporal relationships between the monsoon rainfall indices (MRIs) and the large-scale monsoon circulation indices (MCIs), as a precursor to using such indices for model evaluation. The remainder of the thesis evaluates model performance in simulating various characteristics of SASM, mainly with regard to precipitation. In particular, the sensitivity of a regional climate model (RCM) simulation to domain size and added value of high resolution RCM simulation are evaluated. For this purpose, the Hadley Centre unified model - HadGEM is utilized in its regional and, in few instances, global configurations. The RCM simulations are performed at 0.44° and 0.11° horizontal resolutions and they are forced by the ERA interim dataset. Results show that i) the MRI-MCI relationship exhibits considerable low-frequency variability, ii) RCM simulation of SASM, particularly precipitation, shows sensitivity to domain size and simulation with a moderately sized domain that partially excludes bias prone equatorial Indian ocean outperform those with larger domains, iii) high resolution RCM simulation adds value in many aspects of SASM precipitation, including the seasonal mean, relative frequency distribution, extremes, and active and break monsoon composites, but the improvements are generally seen over the Indo-Gangetic plain rather than the Himalaya. The findings promote use of a high resolution RCM over a moderate sized domain (~ 25,000,000 sq. km) for the realistic simulation of SASM, but the study needs to be repeated with multiple realizations and different RCMs before arriving at a robust conclusion.
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Meißner, Cathérine [Verfasser], and C. [Akademischer Betreuer] Kottmeier. "High-resolution sensitivity studies with the regional climate model COSMO-CLM / Cathérine Meißner ; Betreuer: C. Kottmeier." Karlsruhe : KIT Scientific Publishing, 2008. http://d-nb.info/1185225358/34.
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Liang, Ju. "Validation and projection of Tropical Cyclone activity over the western North Pacific using a high resolution regional climate model." Thesis, University of Reading, 2017. http://centaur.reading.ac.uk/75270/.
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TCs have caused death and great economic loss every year across the coastal area of the western North Pacific (WNP). Therefore it is important to improve the understanding of the climatology of TCs over this region and their modulation by natural climate variability and large-scale circulation systems. It is also important to improve our ability to predict possible changes in TC activity over the WNP under climate change conditions. The most appropriate approach to study this is to use numerical models. However, high model resolution is required to resolve the complex physical structure of TCs so that realistic climatologies of TCs can be produced. In this thesis, regional climate model (RCM) simulations, from the Unified Model of the UK Met Office (MetUM) with resolutions of 25 and 12km and two different dynamical cores, are used to project the future change in TC activity over Vietnam, Philippines and the South China Sea (SCS). These simulations are driven by data from the ERA-Interim reanalysis for the period 1990-2005 and the HadGEM2-ES global climate model covering the historical period (1961-2005) and a future period (2069-2099) under two IPCC greenhouse gas emission scenarios (RCP4.5 and RCP8.5) to investigate the impact of anthropogenic warming on TCs in the study region. An objective algorithm is used to identify and track the simulated TCs. First, the ability of the RCM to simulate TCs and their associated large-scale environments, for a current climate period of 1990-2005, with different model resolutions is evaluated. For the period of 1961-2005, the downscaled HadGEM2-ES simulations are also used to evaluate the model's ability to reproduce the modulation of TC activity associated with El Nino/Southern Oscillation (ENSO). Both the 25 km and 12 km models can reasonably simulate the TC activity over the SCS compared with the observed TCs. The associated large-scale environments are found to be simulated correctly compared with the ERA-Interim reanalysis. The observed weakened TC activity during El Nino events is also captured by the downscaled HadGEM2-ES. Compared with the 25 km model, the 12 km model has a better ability to simulate the large-scale environments and generally improves the simulation of the spatial distribution and structure of TCs. Improved simulated TC-ENSO response (in terms of TC frequency, track density, intensity, structure and associated large-scale environments) is also found in the 12 km model. However, the 12 km model does not produce stronger 10-m maximum wind speeds of TCs compared with the 25km model. For the projections towards the end of the 21st century, the downscaled HadGEM2-ES at both 25 km and 12 km resolution present an insignificant decrease in TC frequency with rates of -0.001 per year and -0.007 per year for RCP4.5 and RCP8.5 respectively. The Had2-25km projection shows a more than 3% increase of the intense (10 m wind speed >35 mS-1) TCs over the South China Sea, while weak TCs (wind speed >25 ms-1) decrease by 10% under RCP8.5. Also, both the RCMs simulate a seasonal shift of TC activity in a warming climate, with an increase in TCs during winter related to the more favourable large-scale conditions and a decrease in TCs is projected in summer.
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Schaaf, Benjamin [Verfasser], and Hans von [Akademischer Betreuer] Storch. "Added Value and regional effects in the multidecadal trends of a very high-resolution regional climate long-term model simulation at the coasts of Northern Germany / Benjamin Schaaf ; Betreuer: Hans von Storch." Hamburg : Staats- und Universitätsbibliothek Hamburg, 2018. http://d-nb.info/1163394319/34.
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Caillaud, Cecile. "Sensibilité climatique des systèmes précipitants intenses : approche par la modélisation climatique à très haute résolution sur le nord-ouest de la Méditerranée." Electronic Thesis or Diss., Toulouse, INPT, 2023. http://www.theses.fr/2023INPT0111.
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Les épisodes méditerranéens qui concernent chaque automne le nord-ouest de la Méditerranée sont des événements de précipitation extrême à fort impact. L'étude de leur évolution aux échelles climatiques revêt donc une grande importance et constitue encore un défi pour la communauté de modélisation du climat. Depuis quelques années, il est possible d’utiliser des modèles régionaux de climat à résolution kilométrique (Convection-Permitting Regional Climate Models ou CP-RCMs, 1-3 km) dont la convection profonde est simulée de manière explicite. Ces modèles permettent de se rapprocher des échelles spatio-temporelles en jeu et ouvrent de nouvelles perspectives en termes d'analyse. Cette thèse a pour objectif de déterminer la réponse des épisodes méditerranéens du nord-ouest de la Méditerranée au changement climatique d’origine humaine, en s'appuyant sur cette nouvelle génération de modèles de climat associée à une approche orientée objet. Le suivi des systèmes fortement précipitants est appliqué à la fois aux jeux de données d'observation, aux simulations réalisées avec le CP-RCM CNRM-AROME et aux simulations du premier ensemble de CP-RCMs disponible dans le cadre du programme international CORDEX FPS Convection sur un domaine commun couvrant le nord-ouest de la Méditerranée. La première partie de cette thèse est consacrée à l’évaluation des performances des CP-RCMs par comparaison à des données d’observation de référence à haute résolution. La valeur ajoutée des CP-RCMs par rapport aux modèles régionaux à résolution plus grossière (12-15 km) est démontrée pour les extrêmes de précipitation, en particulier au pas de temps horaire. L’approche objet permet également de montrer que, malgré quelques biais résiduels, les CP-RCMs sont capables de représenter correctement les principales propriétés des systèmes fortement précipitants, que ce soit en termes de nombre et de positionnement sur l'ensemble du domaine, ou en termes de durée, d'intensité, de surface, de volume, de vitesse et de sévérité sur le pourtour méditerranéen français où les observations permettent d’évaluer finement ces propriétés. La bonne performance de ces modèles permet de renforcer la confiance en leurs projections futures. La deuxième partie s’intéresse à l’évolution future des épisodes méditerranéens avec l’approche objet appliquée aux simulations milieu et fin de siècle de l’ensemble de CP-RCMs en mode scénario pour étudier les changements des propriétés des systèmes fortement précipitants dans un climat plus chaud. En fin de siècle et selon un scénario de fortes émissions, certains changements se retrouvent dans la plupart des simulations et peuvent être qualifiés de robustes. Ainsi, une augmentation de la fréquence des systèmes fortement précipitants de l’automne dans une grande partie du domaine, en particulier du centre de l'Italie au nord des Balkans, accompagne un doublement des zones touchées par ces événements. Sur la région méditerranéenne française, les modèles s’accordent sur une augmentation d'intensité, de surface et de volume des systèmes précipitants. Toutefois, même avec cette nouvelle génération de modèles, d'importantes incertitudes persistent, notamment pour les changements de fréquence dans le sud-est de la France, probablement dus à des différences dans les conditions synoptiques imposées par les modèles forceurs des CP-RCMs. De même, l’ensemble projette une large gamme de changements possibles dans les propriétés des systèmes, en particulier pour les plus intenses et y compris lorsqu’on normalise par le réchauffement régional correspondant. Si les CP-RCMs sont les outils de modélisation adaptés pour l'étude des extrêmes de précipitation, les efforts doivent être poursuivis pour produire des ensembles plus larges, mieux construits et probablement complétés par des méthodes d'apprentissage machine, afin d’apporter des informations climatiques utiles aux échelles pertinentes pour les politiques d’adaptationThe Mediterranean Heavy Precipitation Events (HPEs) that affect the northwestern Mediterranean every fall are high-impact weather events. The study of their evolution on climate scales is therefore of great importance and remains a challenge for the climate modelling community. For some years now, it has been possible to use kilometre-scale regional climate models (Convection- Permitting Regional Climate Models or CP-RCMs, 1-3 km) in which deep convection is explicitly simulated. These models make it possible to get closer to the spatio-temporal scales involved and open up new perspectives in terms of analysis. The aim of this thesis is to determine the response of northwestern Mediterranean HPEs to human-induced climate change, using this new generation of climate models combined with an object-oriented approach. The tracking of heavy precipitation systems is applied to observational datasets, to simulations carried out with the CNRM-AROME CP-RCM and to simulations of the first ensemble of CP-RCMs available as part of the international CORDEX FPS Convection programme over a common domain covering the north-western Mediterranean. The first part of this thesis is devoted to evaluating the performance of CP-RCMs in comparison with high-resolution reference observation data. The added value of CP-RCM compared with regional models with coarser resolution (12-15 km) is demonstrated for precipitation extremes, particularly at hourly time steps. The object-oriented approach also shows that, despite a few residual biases, CP-RCMs are capable of correctly representing the principal properties of heavy precipitation systems, both in terms of number and position over the entire domain, and in terms of duration, intensity, surface area, volume, speed and severity over the French Mediterranean, where observations enable these properties to be assessed in detail. The good performance of these models lends greater confidence to their future projections. The second part focuses on the future evolution of Mediterranean HPEs using the object-oriented approach applied to mid and end-of-century simulations of the CP-RCMs ensemble in scenario mode to study changes in the properties of heavy precipitation systems in a warmer climate. At the end of the century, and according to a scenario of high emissions, certain changes are found in most of the simulations and can be described as robust. For example, an increase in the frequency of fall heavy precipitation systems over a large part of the domain, particularly from central Italy to the northern Balkans, is accompanied by a doubling of the areas affected by these events. Over the French Mediterranean region, the models agree on an increase in the intensity, surface area and volume of precipitating systems. However, even with this new generation of models, significant uncertainties remain, particularly for changes in frequency over southeastern France, probably due to differences in the synoptic conditions imposed by the CP-RCMs driving models. Similarly, the ensemble projects a wide range of possible changes in the properties of systems, particularly for the most intense ones and even when standardised by the corresponding regional warming. While CP-RCMs are the appropriate modelling tools for studying precipitation extremes, efforts must be continued to produce larger, better constructed ensembles, probably supplemented by machine learning methods, in order to provide useful climate information at scales relevant to adaptation policies
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Rulewski, Stenberg Louis. "High frequency rainfall data disaggregation with a random cascade model : Identifying regional differences in hyetographs in Sweden." Thesis, Uppsala universitet, Institutionen för geovetenskaper, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-434661.
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The field of urban hydrology is in need of high temporal resolution data series in order to effectively model and analyse existing and future trends in extreme precipitation. When high resolution data sets are, for any number of reasons, not available for a given location, the technique of disaggregation using a random cascade model can be applied. Previous studies have demonstrated the relevance of random cascades in the context of rainfall data disaggregation with temporal resolutions usually down to 1 hour. In this study, an attempt at disaggregation to a resolution of 1 minute was made. Using newly disaggregated rainfall data for different regions in Sweden, the possibility of clustering rain events into separate regional hyetographs was investigated. The random cascade model was calibrated using existing municipal rainfall data with a temporal resolution of 1 minute, in order to disaggregate continuous 15 minutes data series provided by the Swedish Meteorological and Hydrological Institute (SMHI). The disaggregation process was then performed in multiple stochastic realisations, in order to correct the uncertainties inherent to the random cascade model. The disaggregation results were assessed by comparing them with calibration data: two main rainfall parameters, EV and ED, were analysed by determining their behaviours and distribution. The possibility of transfering calibration parameters from one station to another was also assessed in a similar manner, again by studying EV & ED for different scenarios. Finally, hyetographs were clustered, compared and contrasted, in order to ascertain previously theorized differences between regions. This research showed the feasibility of applying a random cascade model to very high temporal resolutions in Sweden, while replicating rainfall characteristics from the calibration data quite well. The analysis of the spatial transferability of calibration parameters yielded inconclusive results, as rainfall characteristics were preserved in some cases but failed in others. Lastly, distinct regional differences in hyetographs were noted, but no clear conclusions could be drawn owing to the delimitations of this study.Inom småskalig hydrologisk modellering finns det idag ett behov av dataserier med hög tidsupplösning för att effektivt kunna modellera och analysera både aktuella och kommande trender hos extrema regnhändelser. När högupplösta dataserier är otillgängliga vid en önskad mätplats kan disaggregering med hjälp av en slumpmässig kaskadmodell tillämpas. Tidigare forskning har visat att kaskadmodeller är användbara för disaggregering av regndata med en tidsupplösning av 1 timme. I denna studie disaggregerades dataserier med syftet att uppnå en tidsupplösningav av 1 minut. För att kunna analysera eventuella skillnader mellan regioner klustrades även hyetografer med de framtagna dataserierna. Den slumpmässiga kaskadmodellen kalibrerades med befintlig kommunal data med en tidsupplösning på 1 minut, för att sedan kunna disaggregera 15 minuters data från SMHIs databaser. Disaggregeringen genomfördes i ett antal olika stokastiska realisationer för att kunna ta hänsyn till, och korrigera, de inneboende osäkerheterna i den slumpmässiga kaskadmodellen. Disaggregeringsresultaten bedömdes genom en jämförelse med kalibreringsdata: två regnegenskaper, regnvaraktighet (ED) och regnvolym (EV), analyserades för att kunna bestämma derasfördelningar och beteenden. Kalibreringsparametrarnas överförbarhet analyserades också med hjälp av ED & EV för olika scenarier. Slutligen klustrades hyetografer för att fastställa potentiella skillnader mellan regioner. Studien påvisade möjligheten att använda en slumpmässig kaskadmodell till höga tidsupplösningar i Sverige. Modellen lyckades återskapa regnegenskaper från kalibreringsdata vid disaggregeringen. Möjligheten att överföra kalibreringsparametrar från en station till en annan visade sig dock inte vara helt övertygande: regnegenskaper återskapades endast i vissa fall, men inte i samtliga. Slutligen konstaterades regionala skillnader i hyetografer, men tydliga slutsatser kunde inte dras på grund av underliggande begränsningar med studien.
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Osima, Sarah Emerald. "Understanding a high resolution regional climate model's ability in simulating tropical East Africa climate variability and change." Doctoral thesis, University of Cape Town, 2015. http://hdl.handle.net/11427/16716.
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Includes bibliographical referencesThe main aim of this thesis is to investigate the potential benefits of increasing resolution in regional climate models in the simulation of climate variability and change over East Africa. This study is based on two high resolution regional climate simulations with a horizontal resolution of 50km and 10km, respectively. These represent present day climate and a projection of future climate change over East Africa. The regional climate model (RCM) used here is HIRHAM5, which is driven by the global circulation model (ECHAM5). Downscaled ECHAM5 output is used to drive the 50km HIRHAM5 simulation for the period 1950-2100, and output from this simulation is used to drive the 10km simulation for three time slices: 1980-1999, representative for present-day climate and two time slices for near future (2046-2065) and far future (2080- 2099), respectively. HIRHAM5 is evaluated with respect to the observed mean climatologies of rainfall, surface temperature and surface winds over East Africa, and representations of the observed annual cycles and inter-annual variability of rainfall and surface temperature. This study utilizes reanalysis and observational datasets: a hindcast of HIRHAM5 forced with ERA Interim, as well as two observation datasets for temperature and rainfall. Since reanalyses aim to make "best use" of all available observations by making a physically consistent representation continuous in time and space, and since there is a paucity of observations over many parts of Africa, the ERAI reanalysis is also used as a best estimate for model evaluation. Additionally, for evaluation of the bimodal nature of East Africa's rainfall, especially over Tanzania, three stations run by the Tanzania Meteorological Agency were used. The model data used in th is evaluation ranges from 1980 to 2006 iv HIRHAM5 demonstrates reasonable skill in the reproduction of observed patterns of mean climatology of rainfall, surface temperature and winds over East Africa. Moreover, the patterns of annual cycles of rainfall and surface temperature in the bimodal nature of East Africa are well represented. Furthermore, the model showed reasonable skill in the representation of the inter- annual variability and ENSO signals as suggested by the observation. Despite these strengths, HIRHAM5 shows some shortcomings. One weakness of the model is the simulation of the magnitude of a given variable over a specific region. For example, HIRHAM5 driven by ERAI underestimates rainfall and overestimates surface temperature over the entire domain of East Africa. The higher resolution HIRHAM5 (10km resolution) overestimates rainfall over high ground. The model bias could be due in part to the inadequacy of the observation networks in East Africa, represented in this thesis by the CRU and FEWS datasets. However, these two datasets draw on some different sources and neither do they have the same resolution. FEWS is a high resolution data (0.1 o ) gridded satellite-derived precipitation estimate covering the entire African continent while CRU datasets is a relatively low resolution (0.5 o ) dataset based on rain gauge monthly precipitation only; in addition , near surface temperature is also available. As no reliable wind observations exist, wind data was taken from the ERA-Interim reanalysis. The different observational datasets do not agree particularly well, which impedes evaluating the quality of the HIRHAM5 simulations, in particular the high resolution one. So while the higher resolution HIRHAM5 appears to be generally reliable, caution must be exercised in formulating conclusions from the results, especially over high ground and remote areas without adequate observation data. Under these constraints, the results suggest HIRHAM5 may be useful for assessing climate variability and change over East Africa. A weakness of the analysis presented here is that only one combination of GCM and RCM could be investigated in depth due to computer and time constraints. Therefore the results presented here, if used in application for climate change adaptation, should be considered in conjunction with a broader suite of data, such from the CORDEX programme. This has potential to increase the reliability of information about climate variability and change at a regional to local level necessary for impact assessment.
Books on the topic "High-resolution Regional Climate Model"
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Meissner, Cathérine. High-resolution sensitivity studies with the regional climate model COSMO-CLM. Karlsruhe: Univ.-Verl. Karlsruhe, 2008.
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Crane, Robert G. Regional climate change predictions from the Goddard Institute for Space Studies high resolution GCM. University Park, Pa: Pennsylvania State University, Dept. of Geography and the Earth System Science Center, 1990.
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Dorn, Wolfgang. Natürliche Klimavariationen der Arktis in einem regionalen hochauflösenden Atmosphärenmodell =: Natural climate variations of the Arctic in a regional high-resolution atmosphere model. Bremerhaven: Alfred-Wegener-Institut für Polar- und Meeresforschung, 2002.
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Crane, Robert G. Regional climate change predictions from the Goddard Institute for Space Studies high resolution GCM: Final report, NASA grant NAG 5-1133, May 1989 - October 1991. [Washington, D.C: National Aeronautics and Space Administration, 1990.
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W, Zack John, Karyampudi V. Mohan, and United States. National Aeronautics and Space Administration., eds. Development of high resolution simulations of the atmospheric environment using the MASS model. Hampton, Va: MESO Inc., 1990.
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Service, Canadian Forest, and Rocky Mountain Research Station (Fort Collins, Colo.), eds. High resolution interpolation of climate scenarios for the conterminous USA and Alaska derived from general circulation model simulations. Fort Collins, CO: U.S. Dept. of Agriculture, Forest Service, Rocky Mountain Research Station, 2011.
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Gao, Yanhong, and Deliang Chen. Modeling of Regional Climate over the Tibetan Plateau. Oxford University Press, 2017. http://dx.doi.org/10.1093/acrefore/9780190228620.013.591.
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The modeling of climate over the Tibetan Plateau (TP) started with the introduction of Global Climate Models (GCMs) in the 1950s. Since then, GCMs have been developed to simulate atmospheric dynamics and eventually the climate system. As the highest and widest international plateau, the strong orographic forcing caused by the TP and its impact on general circulation rather than regional climate was initially the focus. Later, with growing awareness of the incapability of GCMs to depict regional or local-scale atmospheric processes over the heterogeneous ground, coupled with the importance of this information for local decision-making, regional climate models (RCMs) were established in the 1970s. Dynamic and thermodynamic influences of the TP on the East and South Asia summer monsoon have since been widely investigated by model. Besides the heterogeneity in topography, impacts of land cover heterogeneity and change on regional climate were widely modeled through sensitivity experiments.In recent decades, the TP has experienced a greater warming than the global average and those for similar latitudes. GCMs project a global pattern where the wet gets wetter and the dry gets drier. The climate regime over the TP covers the extreme arid regions from the northwest to the semi-humid region in the southeast. The increased warming over the TP compared to the global average raises a number of questions. What are the regional dryness/wetness changes over the TP? What is the mechanism of the responses of regional changes to global warming? To answer these questions, several dynamical downscaling models (DDMs) using RCMs focusing on the TP have recently been conducted and high-resolution data sets generated. All DDM studies demonstrated that this process-based approach, despite its limitations, can improve understandings of the processes that lead to precipitation on the TP. Observation and global land data assimilation systems both present more wetting in the northwestern arid/semi-arid regions than the southeastern humid/semi-humid regions. The DDM was found to better capture the observed elevation dependent warming over the TP. In addition, the long-term high-resolution climate simulation was found to better capture the spatial pattern of precipitation and P-E (precipitation minus evapotranspiration) changes than the best available global reanalysis. This facilitates new and substantial findings regarding the role of dynamical, thermodynamics, and transient eddies in P-E changes reflected in observed changes in major river basins fed by runoff from the TP. The DDM was found to add value regarding snowfall retrieval, precipitation frequency, and orographic precipitation.Although these advantages in the DDM over the TP are evidenced, there are unavoidable facts to be aware of. Firstly, there are still many discrepancies that exist in the up-to-date models. Any uncertainty in the model’s physics or in the land information from remote sensing and the forcing could result in uncertainties in simulation results. Secondly, the question remains of what is the appropriate resolution for resolving the TP’s heterogeneity. Thirdly, it is a challenge to include human activities in the climate models, although this is deemed necessary for future earth science. All-embracing further efforts are expected to improve regional climate models over the TP.
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Cook, Kerry H. Climate Change Scenarios and African Climate Change. Oxford University Press, 2018. http://dx.doi.org/10.1093/acrefore/9780190228620.013.545.
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Accurate projections of climate change under increasing atmospheric greenhouse gas levels are needed to evaluate the environmental cost of anthropogenic emissions, and to guide mitigation efforts. These projections are nowhere more important than Africa, with its high dependence on rain-fed agriculture and, in many regions, limited resources for adaptation. Climate models provide our best method for climate prediction but there are uncertainties in projections, especially on regional space scale. In Africa, limitations of observational networks add to this uncertainty since a crucial step in improving model projections is comparisons with observations. Exceeding uncertainties associated with climate model simulation are uncertainties due to projections of future emissions of CO2 and other greenhouse gases. Humanity’s choices in emissions pathways will have profound effects on climate, especially after the mid-century.The African Sahel is a transition zone characterized by strong meridional precipitation and temperature gradients. Over West Africa, the Sahel marks the northernmost extent of the West African monsoon system. The region’s climate is known to be sensitive to sea surface temperatures, both regional and global, as well as to land surface conditions. Increasing atmospheric greenhouse gases are already causing amplified warming over the Sahara Desert and, consequently, increased rainfall in parts of the Sahel. Climate model projections indicate that much of this increased rainfall will be delivered in the form of more intense storm systems.The complicated and highly regional precipitation regimes of East Africa present a challenge for climate modeling. Within roughly 5º of latitude of the equator, rainfall is delivered in two seasons—the long rains in the spring, and the short rains in the fall. Regional climate model projections suggest that the long rains will weaken under greenhouse gas forcing, and the short rains season will extend farther into the winter months. Observations indicate that the long rains are already weakening.Changes in seasonal rainfall over parts of subtropical southern Africa are observed, with repercussions and challenges for agriculture and water availability. Some elements of these observed changes are captured in model simulations of greenhouse gas-induced climate change, especially an early demise of the rainy season. The projected changes are quite regional, however, and more high-resolution study is needed. In addition, there has been very limited study of climate change in the Congo Basin and across northern Africa. Continued efforts to understand and predict climate using higher-resolution simulation must be sustained to better understand observed and projected changes in the physical processes that support African precipitation systems as well as the teleconnections that communicate remote forcings into the continent.
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Goswami, B. N., and Soumi Chakravorty. Dynamics of the Indian Summer Monsoon Climate. Oxford University Press, 2017. http://dx.doi.org/10.1093/acrefore/9780190228620.013.613.
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Lifeline for about one-sixth of the world’s population in the subcontinent, the Indian summer monsoon (ISM) is an integral part of the annual cycle of the winds (reversal of winds with seasons), coupled with a strong annual cycle of precipitation (wet summer and dry winter). For over a century, high socioeconomic impacts of ISM rainfall (ISMR) in the region have driven scientists to attempt to predict the year-to-year variations of ISM rainfall. A remarkably stable phenomenon, making its appearance every year without fail, the ISM climate exhibits a rather small year-to-year variation (the standard deviation of the seasonal mean being 10% of the long-term mean), but it has proven to be an extremely challenging system to predict. Even the most skillful, sophisticated models are barely useful with skill significantly below the potential limit on predictability. Understanding what drives the mean ISM climate and its variability on different timescales is, therefore, critical to advancing skills in predicting the monsoon. A conceptual ISM model helps explain what maintains not only the mean ISM but also its variability on interannual and longer timescales.The annual ISM precipitation cycle can be described as a manifestation of the seasonal migration of the intertropical convergence zone (ITCZ) or the zonally oriented cloud (rain) band characterized by a sudden “onset.” The other important feature of ISM is the deep overturning meridional (regional Hadley circulation) that is associated with it, driven primarily by the latent heat release associated with the ISM (ITCZ) precipitation. The dynamics of the monsoon climate, therefore, is an extension of the dynamics of the ITCZ. The classical land–sea surface temperature gradient model of ISM may explain the seasonal reversal of the surface winds, but it fails to explain the onset and the deep vertical structure of the ISM circulation. While the surface temperature over land cools after the onset, reversing the north–south surface temperature gradient and making it inadequate to sustain the monsoon after onset, it is the tropospheric temperature gradient that becomes positive at the time of onset and remains strongly positive thereafter, maintaining the monsoon. The change in sign of the tropospheric temperature (TT) gradient is dynamically responsible for a symmetric instability, leading to the onset and subsequent northward progression of the ITCZ. The unified ISM model in terms of the TT gradient provides a platform to understand the drivers of ISM variability by identifying processes that affect TT in the north and the south and influence the gradient.The predictability of the seasonal mean ISM is limited by interactions of the annual cycle and higher frequency monsoon variability within the season. The monsoon intraseasonal oscillation (MISO) has a seminal role in influencing the seasonal mean and its interannual variability. While ISM climate on long timescales (e.g., multimillennium) largely follows the solar forcing, on shorter timescales the ISM variability is governed by the internal dynamics arising from ocean–atmosphere–land interactions, regional as well as remote, together with teleconnections with other climate modes. Also important is the role of anthropogenic forcing, such as the greenhouse gases and aerosols versus the natural multidecadal variability in the context of the recent six-decade long decreasing trend of ISM rainfall.
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Busuioc, Aristita, and Alexandru Dumitrescu. Empirical-Statistical Downscaling: Nonlinear Statistical Downscaling. Oxford University Press, 2018. http://dx.doi.org/10.1093/acrefore/9780190228620.013.770.
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This is an advance summary of a forthcoming article in the Oxford Research Encyclopedia of Climate Science. Please check back later for the full article.The concept of statistical downscaling or empirical-statistical downscaling became a distinct and important scientific approach in climate science in recent decades, when the climate change issue and assessment of climate change impact on various social and natural systems have become international challenges. Global climate models are the best tools for estimating future climate conditions. Even if improvements can be made in state-of-the art global climate models, in terms of spatial resolution and their performance in simulation of climate characteristics, they are still skillful only in reproducing large-scale feature of climate variability, such as global mean temperature or various circulation patterns (e.g., the North Atlantic Oscillation). However, these models are not able to provide reliable information on local climate characteristics (mean temperature, total precipitation), especially on extreme weather and climate events. The main reason for this failure is the influence of local geographical features on the local climate, as well as other factors related to surrounding large-scale conditions, the influence of which cannot be correctly taken into consideration by the current dynamical global models.Impact models, such as hydrological and crop models, need high resolution information on various climate parameters on the scale of a river basin or a farm, scales that are not available from the usual global climate models. Downscaling techniques produce regional climate information on finer scale, from global climate change scenarios, based on the assumption that there is a systematic link between the large-scale and local climate. Two types of downscaling approaches are known: a) dynamical downscaling is based on regional climate models nested in a global climate model; and b) statistical downscaling is based on developing statistical relationships between large-scale atmospheric variables (predictors), available from global climate models, and observed local-scale variables of interest (predictands).Various types of empirical-statistical downscaling approaches can be placed approximately in linear and nonlinear groupings. The empirical-statistical downscaling techniques focus more on details related to the nonlinear models—their validation, strengths, and weaknesses—in comparison to linear models or the mixed models combining the linear and nonlinear approaches. Stochastic models can be applied to daily and sub-daily precipitation in Romania, with a comparison to dynamical downscaling. Conditional stochastic models are generally specific for daily or sub-daily precipitation as predictand.A complex validation of the nonlinear statistical downscaling models, selection of the large-scale predictors, model ability to reproduce historical trends, extreme events, and the uncertainty related to future downscaled changes are important issues. A better estimation of the uncertainty related to downscaled climate change projections can be achieved by using ensembles of more global climate models as drivers, including their ability to simulate the input in downscaling models. Comparison between future statistical downscaled climate signals and those derived from dynamical downscaling driven by the same global model, including a complex validation of the regional climate models, gives a measure of the reliability of downscaled regional climate changes.
Book chapters on the topic "High-resolution Regional Climate Model"
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Panitz, H. J., G. Fosser, R. Sasse, K. Sedlmeier, S. Mieruch, M. Breil, H. Feldmann, and G. Schädler. "High Resolution Climate Modeling with the CCLM Regional Model." In High Performance Computing in Science and Engineering ‘13, 511–27. Cham: Springer International Publishing, 2013. http://dx.doi.org/10.1007/978-3-319-02165-2_35.
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Yoshizaki, Masanori, Chiashi Muroi, Hisaki Eito, Sachie Kanada, Yasutaka Wakazuki, and Akihiro Hashimoto. "Simulations of Forecast and Climate Modes Using Non-Hydrostatic Regional Models." In High Resolution Numerical Modelling of the Atmosphere and Ocean, 129–39. New York, NY: Springer New York, 2008. http://dx.doi.org/10.1007/978-0-387-49791-4_8.
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Mystakidis, S., P. Zanis, C. Dogras, E. Katragkou, I. Pytharoulis, D. Melas, E. Anadranistakis, and H. Feidas. "Optimization of a Regional Climate Model for High Resolution Simulations over Greece." In Advances in Meteorology, Climatology and Atmospheric Physics, 623–29. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-29172-2_89.
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Panitz, H. J., G. Schädler, M. Breil, S. Mieruch, H. Feldmann, K. Sedlmeier, N. Laube, and M. Uhlig. "High Resolution Climate Modelling with the CCLM Regional Model for Europe and Africa." In High Performance Computing in Science and Engineering ‘14, 561–74. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-10810-0_37.
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Vazquez, Ruben, Ivan Parras-Berrocal, William Cabos, Dmitry V. Sein, Rafael Mañanes, Juan I. Perez, and Alfredo Izquierdo. "Climate Evaluation of a High-Resolution Regional Model over the Canary Current Upwelling System." In Lecture Notes in Computer Science, 240–52. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-22747-0_19.
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Teske, Sven, Jaysson Guerrero Orbe, Jihane Assaf, Souran Chatterjee, Benedek Kiss, and Diana Ürge-Vorsatz. "Methodology." In Achieving the Paris Climate Agreement Goals, 25–59. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-99177-7_3.
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AbstractThe OneEarth Climate Model (OECM), its background, and program architecture are described. How the OECM is broken down into two independent modules to calculate demand and supply is explored. The basic program logic of the MATLAB-based bottom-up demand module, with high technical resolution, is described for various sectors, including the input and output parameters. The description includes numerous figures and tables for both demand and supply modules. The sub-sectors used for the OECM 1.5 °C pathway are listed, including outputs and the areas of use.The second part of the chapter documents the high-efficiency building (HEB) model of the Central European University, which was used for the global and regional bottom-up analyses of the building sector. Its methodology, including the programme architecture, the workflow, and the equations used, is provided.
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Wijaya, I. Putu Krishna, Peeranan Towashiraporn, Anish Joshi, Susantha Jayasinghe, Anggraini Dewi, and Md Nurul Alam. "Climate Change-Induced Regional Landslide Hazard and Exposure Assessment for Aiding Climate Resilient Road Infrastructure Planning: A Case Study in Bagmati and Madhesh Provinces, Nepal." In Progress in Landslide Research and Technology, Volume 1 Issue 1, 2022, 175–84. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-16898-7_12.
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AbstractNepal’s hilly and mountainous regions are highly susceptible to landslides triggered by extreme precipitations. The prevalence of such landslides has increased due to climate change-induced extreme hydro-meteorological conditions. These recurring landslides have significantly impacted the road transport infrastructure, which is the economic lifeline for cities and socio-economic mobility of rural communities in the hilly and mountainous regions of the country. This study modelled extreme rainfall scenarios for the current 1976–2005 baseline and future horizons of 2030, 2050, and 2080 to develop high-resolution 1 km × 1 km mean precipitation datasets under RCP4.5 and RCP8.5. Based on these extreme precipitation scenarios, we developed high-resolution landslide hazard models adopting integrated weighted index by combining the Frequency Ratio (FR) and Analytical Hierarchical Process (AHP) methods using multi-variate factors. The multi-variate factors included three terrain parameters—slope, aspect, and elevation; two soil parameters—lithology and soil type; two Euclidean distance parameters from the likely sources—distance from the lineaments and distance from the stream/river; an anthropogenic parameter—land use; and the climate parameter—the mean annual rainfall for four-time horizons and two RCPs. These parameters were spatially modelled and combined using the weighted overlay method to generate a landslide hazard model. As demonstration case studies, the landslide hazard models were developed for Bagmati and Madhesh provinces. The models were validated using the Receiver Operating Characteristic curve (ROC) approach, which showed a satisfactory 81–86% accuracy in the study area. Spatial exposure analysis of the road network assets under the Strategic Road Network (SRN) was completed for seven landslide hazard scenarios. In both Bagmati and Madhesh provinces, the exposure analysis showed that the proportion of road sections exposed to landslide hazard significantly increases for the future climate change scenarios compared to the current baseline scenario.
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Panitz, H. J., G. Schädler, M. Breil, S. Mieruch, H. Feldmann, K. Sedlmeier, N. Laube, and M. Uhlig. "Application of the Regional Climate Model CCLM for Studies on Urban Climate Change in Stuttgart and Decadal Climate Prediction in Europe and Africa." In High Performance Computing in Science and Engineering ´15, 593–606. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-24633-8_38.
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Macelloni, Myrta Maria, Elisabetta Corte, Andrea Ajmar, Alberto Cina, Fabio Giulio Tonolo, Paolo Felice Maschio, and Isabella Nicole Pisoni. "Multi-platform, Multi-scale and Multi-temporal 4D Glacier Monitoring. The Rutor Glacier Case Study." In Geomatics for Green and Digital Transition, 392–404. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-17439-1_29.
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AbstractAt present most alpine glaciers are not in equilibrium with the current climate, as a result they are undergoing a dramatic mass loss. Monitoring glacial variations is crucial to assess the consequences of climate change on the territory. In this work different geomatics techniques are exploited to measure and monitor the Rutor glacier over the years. In this study two different techniques were adopted to generate 3 digital surface models (DSMs): aerial and satellite photogrammetry. Two photogrammetric aerial surveys were carried out: at the end of the hydrological year 2019/20 and at the end of the following hydrological year. Additionally, a very high-resolution satellite stereo pair, acquired by the Pléiades-1A platform in 2017, was processed to assess whether satellite images can be applied to extract the 3D surface of the Rutor glacier. In order to evaluate the Rutor glacier mass-balance throughout the years several reference points were positioned and measured before the 2021 aerial flight. Thanks to the presence of the materialized points the 2021 model is considered as the ‘Reference Model’ against which subsequent models can be compared for glacier analysis. This model was validated by means of a comparison with the authoritative Regional DSM based on LiDAR surveys. In alpine glaciers, the positioning of artificial square cross target in time invariant areas is crucial to enable a multitemporal 4D analysis. The use of very high-resolution satellite imagery allows large areas to be mapped in 3D, but with lower accuracies proportionally decreasing with respect to slope and exposure.
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Engelbrecht, Francois A., Jessica Steinkopf, Jonathan Padavatan, and Guy F. Midgley. "Projections of Future Climate Change in Southern Africa and the Potential for Regional Tipping Points." In Sustainability of Southern African Ecosystems under Global Change, 169–90. Cham: Springer International Publishing, 2024. http://dx.doi.org/10.1007/978-3-031-10948-5_7.
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AbstractSouthern Africa is a climate change hotspot with projected warming and drying trends amplifying stresses in a naturally warm, dry and water-stressed region. Despite model-projected uncertainty in rainfall change over the eastern escarpment of South Africa, strong model agreement in projections indicates that southern African is likely to become generally drier. Sharply increased regional warming and associated strong reductions in soil-moisture availability and increases in heat-waves and high fire-danger days are virtually certain under low mitigation futures. Changes are detectible in observed climate trends for the last few decades, including regional warming, drying in both the summer and winter rainfall regions, and increases in intense rainfall events. The southern African climate is at risk of tipping into a new regime, with unprecedented impacts, such as day-zero drought in the Gauteng province of South Africa, collapse of the maize and cattle industries, heat-waves of unprecedented intensity and southward shifts in intense tropical cyclone landfalls. Many of these adverse changes could be avoided if the Paris Accord’s global goal were to be achieved, but research is urgently required to quantify the probabilities of such tipping points in relation to future levels of global warming. Adaptation planning is an urgent regional priority.
Conference papers on the topic "High-resolution Regional Climate Model"
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Anwar, Samy Ashraf, Zeinab Salah, Wael Khald, and Ashraf Saber Zakey. "Projecting the Potential Evapotranspiration of Egypt Using a High-Resolution Regional Climate Model (RegCM4)." In ECAS 2022. Basel Switzerland: MDPI, 2022. http://dx.doi.org/10.3390/ecas2022-12841.
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Mašek, Ján. "Climate configuration of the model ALADIN at CHMI." In První konference PERUN. Český hydrometeorologický ústav, 2023. http://dx.doi.org/10.59984/978-80-7653-063-8.06.
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For operational weather forecast at CHMI we use the ALARO configuration of the numerical system ALADIN with horizontal resolution 2.3km. It is so-called convection permitting model. The goal of presented work was to evaluate potential of operational ALARO configuration used for Central Europe, and apply it with minimal changes for baseline regional climate simulations realized within the PERUN project. Tests following the so-called big brother experimental protocol were performed, demonstrating ability of the regional model to add short scales missing in the boundary conditions from driving model ESM2-1 in the region of interest over Czech territory, even though the resolution of driving model is more than order of magnitude coarser. Further it was verified that in the computational domain synoptic scales are sufficiently controlled by lateral boundary conditions. Thanks to this, consistency with driving global scenario is ensured even without use of spectral nudging. Such approach enables to fully profit from high resolution of the regional model, when internal variability generated by convective or orographic circulations is not artificially restricted.
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Bhattacharya, Tanmoyee, Deepak Khare, and Manohar Arora. "Hydrologic Impact assessment of glaciated BEAS river basin using High Resolution Climate Simulations from CORDEX Regional Climate Models." In 2019 International Conference on Intelligent Computing and Remote Sensing (ICICRS). IEEE, 2019. http://dx.doi.org/10.1109/icicrs46726.2019.9555850.
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Anwar, Samy Ashraf, and Irida Lazić. "Estimating the Potential Evapotranspiration of Egypt Using a Regional Climate Model and a High-Resolution Reanalysis Dataset." In ECWS-7 2023. Basel Switzerland: MDPI, 2023. http://dx.doi.org/10.3390/ecws-7-14253.
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"High resolution regional climate model simulations available through the ACECRC Climate Futures team: What we have and how they can be used." In 22nd International Congress on Modelling and Simulation. Modelling and Simulation Society of Australia and New Zealand (MSSANZ), Inc., 2017. http://dx.doi.org/10.36334/modsim.2017.h11.remenyi.
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Mostafa, Sally Mahmoud, Samy Ashraf Anwar, Ashraf Saber Zakey, and Mohamed Magdy Abdel Wahab. "Bias-Correcting the Maximum and Minimum Air Temperatures of Egypt Using a High-Resolution Regional Climate Model (RegCM4)." In ASEC 2022. Basel Switzerland: MDPI, 2022. http://dx.doi.org/10.3390/asec2022-13852.
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Holtanová, Eva, and Tomáš Halenka. "Assessment of uncertainty of the PERUN climate change scenarios." In První konference PERUN. Český hydrometeorologický ústav, 2023. http://dx.doi.org/10.59984/978-80-7653-063-8.04.
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The main source of data about possible future climate change over the Czech Republic studied within the project PERUN is a series of Aladin-CLIMATE/CZ model simulations driven by the global climate model CNRM-ESM2-1. Other available model simulations, in particular the CMIP5 and CMIP6 global climate models, Euro-CORDEX regional climate models, and other new simulations at high horizontal resolution, will be used to estimate the uncertainties in the climate change scenarios. This paper presents examples of such uncertainty analysis.
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Anwar, Samy Ashraf. "Simulating Daily Soil Temperature in Egypt Using a High-Resolution Regional Climate Model: Sensitivity to Soil Moisture and Temperature Initial Conditions." In ASEC 2023. Basel Switzerland: MDPI, 2023. http://dx.doi.org/10.3390/asec2023-15368.
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Wang, Lei, Tao Feng, Zehn Cai, Xunjian Xu, Li Li, and Zhou Jian. "Dynamic prediction of ice disaster in Hunan power grid in the late January of 2022 using a high resolution regional climate model." In 2022 China International Conference on Electricity Distribution (CICED). IEEE, 2022. http://dx.doi.org/10.1109/ciced56215.2022.9929030.
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CAIAN, Mihaela, Crina RADU, and Georgeta BANDOC. "Changes in Breeze Warmest Summers for the Romanian Black Sea Coast in Climate Scenarios for the Time Horizon 2050." In Air and Water – Components of the Environment 2021 Conference Proceedings. Casa Cărţii de Ştiinţă, 2021. http://dx.doi.org/10.24193/awc2021_14.
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The study aims to analyze and compare the mean sea level pressure field to show the changes in the breeze regime in the coastal area of Romania in the current climate and the one projected in climate scenarios. The mechanism and variability of the breeze cell (intensity, location, frequency, persistence) are analyzed and compared for extreme conditions of warmest summers (July) during the two climatic intervals: 1971- 2000 respectively for the RCP4.5 2021-2050 scenario. The high-resolution climate is simulated using the RegCMv4.5 regional climate model at 5 km resolution, coupled with the global EC-Earth model. These dynamical downscaling methods were performed for the first time for Romania in ANM (Meteo Romania) during the AZURE-Microsoft project (2018), aiming to refine the scale of the global climate scenarios to allow process analysis. The mechanism of changes is analyzed with the interaction between regional-scale conditions and large-scale dynamic factors. The results indicate changes in the frequency of intense events and the spatial development of the breeze cell, with a time-mean intensification of both sea and land breezes and, a greater spatial advance in the area mainly during the day. Large scale-dynamics changes in interaction with the breeze circulation lead to an anticyclonic rotation under a warmer climate of the coupled circulation that induces a shift to the South-West of the cell, with a possible impact on the location of the associated precipitation. Regarding timing, a time-delay in the sea breeze occurrence (smaller pressure gradients persist longer due to warmer sea surface temperature), together with enhanced cell intensity, later on, makes the event appear as a more abrupt or extreme one. The results of the study provide potentially important input for further analysis of projected impacts of the breeze circulation on the regional climate.
Reports on the topic "High-resolution Regional Climate Model"
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Cassano, John. Collaborative Research: Towards Advanced Understanding and Predictive Capability of Climate Change in the Arctic Using a High-Resolution Regional Arctic Climate Model. Office of Scientific and Technical Information (OSTI), June 2013. http://dx.doi.org/10.2172/1086625.
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Gutowski, William J. COLLABORATIVE RESEARCH: TOWARDS ADVANCED UNDERSTANDING AND PREDICTIVE CAPABILITY OF CLIMATE CHANGE IN THE ARCTIC USING A HIGH-RESOLUTION REGIONAL ARCTIC CLIMATE SYSTEM MODEL. Office of Scientific and Technical Information (OSTI), February 2013. http://dx.doi.org/10.2172/1062533.
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Lettenmaier, Dennis P. Collaborative Research: Towards Advanced Understanding and Predictive Capability of Climate Change in the Arctic using a High-Resolution Regional Arctic Climate System Model. Office of Scientific and Technical Information (OSTI), April 2013. http://dx.doi.org/10.2172/1072967.
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Keller, David P., Neha Mehendale, and Tronje P. Kemena. Analysis (report) of high- resolution modelling of efficacy, and regional impacts of selected ocean NETs close to the deployment sites. OceanNets, November 2023. http://dx.doi.org/10.3289/oceannets_d4.3_v1.
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Many recent ocean modelling studies have demonstrated the added value of enhanced horizontal resolution, although it comes at a high computational cost. However, few modeling studies of ocean-based CDR have been done at high resolution. Here we assess the effects of model resolution on two simulated ocean-based CDR methods, unequilibrated ocean alkalinity enhancement (OAE) and the direct marine capture (DMC) of CO2 from seawater (with assumed permanent storage), in experiments with the FOCI Earth system model. To do this we utilized two FOCI configurations, one with a 1/2° ocean resolution and the other with a 1/10° ocean nest in the N. Atlantic. Both configurations were run in a series of “paired” experiments with identical climate forcing and CDR deployments. We show that model resolution does appear to matter when simulating OAE and DMC. For OAE, parameterization of physical processes in the coarse resolution version of the model appears to overestimate how long alkalized waters stay in contact with the atmosphere and where they are transported. This results in large differences in OAE efficacy with almost twice as much carbon sequestered when the model resolution is coarse. For the DMC simulations, at one site there were clear differences in the compensating CO2 flux induced by DIC removal, which was again higher with a coarse resolution, while at the other site variability was high and differences were difficult to determine. At both DMC sites there were clear differences in circulation with the two model resolutions, and thus on downstream biogeochemistry. We suggest that well resolving ocean physics may be necessary to best calculate unequilibrated OAE and DMC efficacies and side effects. These results should be confirmed using other models and with different resolutions.
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Aalto, Juha, and Ari Venäläinen, eds. Climate change and forest management affect forest fire risk in Fennoscandia. Finnish Meteorological Institute, June 2021. http://dx.doi.org/10.35614/isbn.9789523361355.
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Forest and wildland fires are a natural part of ecosystems worldwide, but large fires in particular can cause societal, economic and ecological disruption. Fires are an important source of greenhouse gases and black carbon that can further amplify and accelerate climate change. In recent years, large forest fires in Sweden demonstrate that the issue should also be considered in other parts of Fennoscandia. This final report of the project “Forest fires in Fennoscandia under changing climate and forest cover (IBA ForestFires)” funded by the Ministry for Foreign Affairs of Finland, synthesises current knowledge of the occurrence, monitoring, modelling and suppression of forest fires in Fennoscandia. The report also focuses on elaborating the role of forest fires as a source of black carbon (BC) emissions over the Arctic and discussing the importance of international collaboration in tackling forest fires. The report explains the factors regulating fire ignition, spread and intensity in Fennoscandian conditions. It highlights that the climate in Fennoscandia is characterised by large inter-annual variability, which is reflected in forest fire risk. Here, the majority of forest fires are caused by human activities such as careless handling of fire and ignitions related to forest harvesting. In addition to weather and climate, fuel characteristics in forests influence fire ignition, intensity and spread. In the report, long-term fire statistics are presented for Finland, Sweden and the Republic of Karelia. The statistics indicate that the amount of annually burnt forest has decreased in Fennoscandia. However, with the exception of recent large fires in Sweden, during the past 25 years the annually burnt area and number of fires have been fairly stable, which is mainly due to effective fire mitigation. Land surface models were used to investigate how climate change and forest management can influence forest fires in the future. The simulations were conducted using different regional climate models and greenhouse gas emission scenarios. Simulations, extending to 2100, indicate that forest fire risk is likely to increase over the coming decades. The report also highlights that globally, forest fires are a significant source of BC in the Arctic, having adverse health effects and further amplifying climate warming. However, simulations made using an atmospheric dispersion model indicate that the impact of forest fires in Fennoscandia on the environment and air quality is relatively minor and highly seasonal. Efficient forest fire mitigation requires the development of forest fire detection tools including satellites and drones, high spatial resolution modelling of fire risk and fire spreading that account for detailed terrain and weather information. Moreover, increasing the general preparedness and operational efficiency of firefighting is highly important. Forest fires are a large challenge requiring multidisciplinary research and close cooperation between the various administrative operators, e.g. rescue services, weather services, forest organisations and forest owners is required at both the national and international level.
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Maltrud, Mathew E. High Resolution Fully Coupled Climate Simulations for Investigation of Regional Interactions. Office of Scientific and Technical Information (OSTI), April 2014. http://dx.doi.org/10.2172/1129818.
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Thoma, David. Landscape phenology, vegetation condition, and relations with climate at Canyonlands National Park, 2000–2019. Edited by Alice Wondrak Biel. National Park Service, June 2023. http://dx.doi.org/10.36967/2299619.
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Quantitatively linking satellite observations of vegetation condition and climate data over time provides insight to climate influences on primary production, phenology (timing of growth), and sensitivity of vegetation to weather and longer-term patterns of weather referred to as climate. This in turn provides a basis for understanding potential climate impacts to vegetation—and the potential to anticipate cascading ecological effects—such as impacts to forage, habitat, fire potential, and erosion—as climate changes in the future. This report provides baseline information about vegetation production and condition over time at Canyonlands National Park (NP), as derived from satellite remote sensing. Its objective is to demonstrate methods of analysis, share findings, and document historic climate exposure and sensitivity of vegetation to weather and climate as a driver of vegetation change. This report represents a quantitative foundation of vegetation–climate relationships on an annual timestep. The methods can be modified to finer temporal resolution and other spatial scales if further analyses are needed to inform park planning and management. The knowledge provided in this report can inform vulnerability assessments for Climate Smart Conservation planning by park managers. Patterns of pivot points and responses can serve as a guide to anticipate what, where, when, and why vegetation change may occur. For this analysis, vegetation alliance groups were derived from vegetation-map polygons (Von Loh et al. 2007) by lumping vegetation types expected to respond similarly to climate. Relationships between vegetation production and phenology were evaluated for each alliance map unit larger than a satellite pixel (~300 × 300 m). We used a water-balance model to characterize the climate experienced by plants. Water balance translates temperature and precipitation into more biophysically relevant climate metrics, such as soil moisture and drought stress, that are often more strongly correlated with vegetation condition than temperature or precipitation are. By accounting for the interactions between temperature, precipitation, and site characteristics, water balance helps make regional climate assessments relevant to local scales. The results provide a foundation for interpreting weather and climate as a driver of changes in primary production over a 20-year period at the polygon and alliance-group scale. Additionally, they demonstrate how vegetation type and site characteristics, such as soil properties, slope, and aspect, interact with climate at local scales to determine trends in vegetation condition. This report quantitatively defines critical water needs of vegetation and identifies which alliance types, in which locations, may be most susceptible to climate-change impacts in the future. Finally, this report explains how findings can be used in the Climate Smart Conservation framework, with scenario planning, to help manage park resources through transitions imposed by climate change.
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Thoma, David. Landscape phenology, vegetation condition, and relations with climate at Capitol Reef National Park, 2000–2019. Edited by Alice Wondrak Biel. National Park Service, March 2023. http://dx.doi.org/10.36967/2297289.
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Quantitatively linking satellite observations of vegetation condition and climate data over time provides insight to climate influences on primary production, phenology (timing of growth), and sensitivity of vegetation to weather and longer-term patterns of weather referred to as climate. This in turn provides a basis for understanding potential climate impacts to vegetation—and the potential to anticipate cascading ecological effects, such as impacts to forage, habitat, fire potential, and erosion, as climate changes in the future. This report provides baseline information about vegetation production and condition over time at Capitol Reef National Park (NP), as derived from satellite remote sensing. Its objective is to demonstrate methods of analysis, share findings, and document historic climate exposure and sensitivity of vegetation to weather and climate as a driver of vegetation change. This report represents a quantitative foundation of vegetation–climate relationships on an annual timestep. The methods can be modified to finer temporal resolution and other spatial scales if further analyses are needed to inform park planning and management. The knowledge provided in this report can inform vulnerability assessments for Climate Smart Conservation planning by park managers. Patterns of pivot points and responses can serve as a guide to anticipate what, where, when, and why vegetation change may occur. For this analysis, vegetation alliance groups were derived from vegetation-map polygons (Von Loh et al. 2007) by lumping vegetation types expected to respond similarly to climate. Relationships between vegetation production and phenology were evaluated for each alliance map unit larger than a satellite pixel (~300 × 300 m). We used a water-balance model to characterize the climate experienced by plants. Water balance translates temperature and precipitation into more biophysically relevant climate metrics, such as soil moisture and drought stress, that are often more strongly correlated with vegetation condition than temperature or precipitation are. By accounting for the interactions between temperature, precipitation, and site characteristics, water balance helps make regional climate assessments relevant to local scales. The results provide a foundation for interpreting weather and climate as a driver of changes in primary production over a 20-year period at the polygon and alliance-group scale. Additionally, they demonstrate how vegetation type and site characteristics, such as soil properties, slope, and aspect, interact with climate at local scales to determine trends in vegetation condition. This report quantitatively defines critical water needs of vegetation and identifies which alliance types, in which locations, may be most susceptible to climate-change impacts in the future. Finally, this report explains how findings can be used in the Climate Smart Conservation framework, with scenario planning, to help manage park resources through transitions imposed by climate change.
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Schunk, Robert W. USU Gauss-Markov Model: High Resolution Regional Capability and Support for AFWA. Fort Belvoir, VA: Defense Technical Information Center, September 2006. http://dx.doi.org/10.21236/ada613100.
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Robert E. Dickinson. Lane Processes in a High Resolution Community Climate Model with Sub-Grid Scale Prameterizations. Office of Scientific and Technical Information (OSTI), December 1997. http://dx.doi.org/10.2172/840811.
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