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1
Pham, Trang Van, Christian Steger, Burkhardt Rockel, Klaus Keuler, Ingo Kirchner, Mariano Mertens, Daniel Rieger, Günther Zängl, and Barbara Früh. "ICON in Climate Limited-area Mode (ICON release version 2.6.1): a new regional climate model." Geoscientific Model Development 14, no. 2 (February 18, 2021): 985–1005. http://dx.doi.org/10.5194/gmd-14-985-2021.
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Abstract. For the first time, the Limited-Area Mode of the new ICON (Icosahedral Nonhydrostatic) weather and climate model has been used for a continuous long-term regional climate simulation over Europe. Built upon the Limited-Area Mode of ICON (ICON-LAM), ICON-CLM (ICON in Climate Limited-area Mode, hereafter ICON-CLM, available in ICON release version 2.6.1) is an adaptation for climate applications. A first version of ICON-CLM is now available and has already been integrated into a starter package (ICON-CLM_SP_beta1). The starter package provides users with a technical infrastructure that facilitates long-term simulations as well as model evaluation and test routines. ICON-CLM and ICON-CLM_SP were successfully installed and tested on two different computing systems. Tests with different domain decompositions showed bit-identical results, and no systematic outstanding differences were found in the results with different model time steps. ICON-CLM was also able to reproduce the large-scale atmospheric information from the global driving model. Comparison was done between ICON-CLM and the COnsortium for Small-scale MOdeling (COSMO)-CLM (the recommended model configuration by the CLM-Community) performance. For that, an evaluation run of ICON-CLM with ERA-Interim boundary conditions was carried out with the setup similar to the COSMO-CLM recommended optimal setup. ICON-CLM results showed biases in the same range as those of COSMO-CLM for all evaluated surface variables. While this COSMO-CLM simulation was carried out with the latest model version which has been developed and was carefully tuned for climate simulations on the European domain, ICON-CLM was not tuned yet. Nevertheless, ICON-CLM showed a better performance for air temperature and its daily extremes, and slightly better performance for total cloud cover. For precipitation and mean sea level pressure, COSMO-CLM was closer to observations than ICON-CLM. However, as ICON-CLM is still in the early stage of development, there is still much room for improvement.
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Thompson, D. W. J. "Regional Climate Impacts of the Northern Hemisphere Annular Mode." Science 293, no. 5527 (July 6, 2001): 85–89. http://dx.doi.org/10.1126/science.1058958.
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Pietikäinen, J. P., D. O'Donnell, C. Teichmann, U. Karstens, S. Pfeifer, J. Kazil, R. Podzun, et al. "The regional aerosol-climate model REMO-HAM." Geoscientific Model Development Discussions 5, no. 1 (March 26, 2012): 737–79. http://dx.doi.org/10.5194/gmdd-5-737-2012.
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Abstract. REMO-HAM is a new regional aerosol-climate model. It is based on the REMO regional climate model and includes all of the major aerosol processes. The structure for aerosol is similar to the global aerosol-climate model ECHAM5-HAM, for example the aerosol module HAM-M7 has been coupled with a two-moment stratiform cloud scheme. In this work, we have evaluated the model and compared the results against ECHAM5-HAM and measurements. Four different measurement sites was chosen for the comparison of total number concentrations, size distributions and gas phase sulfur dioxide concentrations: Hyytiälä in Finland, Melpitz in Germany, Mace Head in Ireland and Jungfraujoch in Switzerland. REMO-HAM is run with two different resolutions: 50×50 km2 and 10×10 km2. Based on our simulations, REMO-HAM can represent the measured values reasonably well. The total number concentrations are slightly underestimated, which is probably due to the missing boundary layer nucleation and online secondary organic aerosol model. The differences in the total number concentrations between REMO-HAM and ECHAM5-HAM can be mainly explained by the difference in the nucleation mode. From the meteorological point of view, REMO-HAM represents the precipitation fields and 2 m temperature profile very well compared to measurement. Overall, we have shown that REMO-HAM is a functional aerosol-climate model, which will be used in further studies.
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Pietikäinen, J. P., D. O'Donnell, C. Teichmann, U. Karstens, S. Pfeifer, J. Kazil, R. Podzun, et al. "The regional aerosol-climate model REMO-HAM." Geoscientific Model Development 5, no. 6 (November 1, 2012): 1323–39. http://dx.doi.org/10.5194/gmd-5-1323-2012.
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Abstract. REMO-HAM is a new regional aerosol-climate model. It is based on the REMO regional climate model and includes most of the major aerosol processes. The structure for aerosol is similar to the global aerosol-climate model ECHAM5-HAM, for example the aerosol module HAM is coupled with a two-moment stratiform cloud scheme. On the other hand, REMO-HAM does not include an online coupled aerosol-radiation nor a secondary organic aerosol module. In this work, we evaluate the model and compare the results against ECHAM5-HAM and measurements. Four different measurement sites were chosen for the comparison of total number concentrations, size distributions and gas phase sulfur dioxide concentrations: Hyytiälä in Finland, Melpitz in Germany, Mace Head in Ireland and Jungfraujoch in Switzerland. REMO-HAM is run with two different resolutions: 50 × 50 km2 and 10 × 10 km2. Based on our simulations, REMO-HAM is in reasonable agreement with the measured values. The differences in the total number concentrations between REMO-HAM and ECHAM5-HAM can be mainly explained by the difference in the nucleation mode. Since we did not use activation nor kinetic nucleation for the boundary layer, the total number concentrations are somewhat underestimated. From the meteorological point of view, REMO-HAM represents the precipitation fields and 2 m temperature profile very well compared to measurement. Overall, we show that REMO-HAM is a functional aerosol-climate model, which will be used in further studies.
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Liu, Xinlei. "A New Machine Learning Algorithm for Regional Low-Carbon Economic Development Analysis Based on Data Mining." Journal of Function Spaces 2022 (August 25, 2022): 1–8. http://dx.doi.org/10.1155/2022/5692666.
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The development of information technology such as the continuous improvement of mobile Internet infrastructure and the performance of computers has made it easy to process and share information. The huge market demand for location-based information services provides huge impetus to the generation and development of mobile terminal positioning technology. Generally speaking, the main causes of climate change can be summarized into two categories: natural climate fluctuations and the impact of human activities which is a major measure taken by China to actively respond to climate change. This is a successful approach to actively explore the rapid development of China’s industrialization and urbanization, which not only develops the economy and improves people’s livelihood but also responds to climate change and reduces carbon intensity. Firstly, this paper mainly is aimed at the connotation of regional low-carbon economic development mode, studying the basic mode of regional low-carbon economic development, and analyzing the characteristics and applicable conditions of each mode. Secondly, based on the machine learning algorithm of data mining, the main mode selection of regional low-carbon economic development is discussed. Thirdly and finally, when choosing the regional low-carbon economic development mode, comprehensive consideration should be given to the economic development basis, energy structure, resource characteristics, industrial status, development mode, geographic location, and other factors. This paper studies the basic conditions and applicable conditions of regional economic development models. The conclusion shows that from the perspective of regional economic evolution, low-carbon economy can be regarded as the decarbonization process of economic development. It is an economic form combining its own characteristics and an inevitable requirement for the transformation of regional economy from other economic models to low-carbon economic models. And other factors of Selection of regional economic development foundation, energy structure, resource characteristics, industrial status, development mode, geographical location, were also discussed.
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Coburn, Jacob, and S. C. Pryor. "Differential Credibility of Climate Modes in CMIP6." Journal of Climate 34, no. 20 (October 2021): 8145–64. http://dx.doi.org/10.1175/jcli-d-21-0359.1.
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AbstractThis work quantitatively evaluates the fidelity with which the northern annular mode (NAM), southern annular mode (SAM), Pacific–North American pattern (PNA), El Niño–Southern Oscillation (ENSO), Pacific decadal oscillation (PDO), Atlantic multidecadal oscillation (AMO), and the first-order mode interactions are represented in Earth system model (ESM) output from the CMIP6 archive. Several skill metrics are used as part of a differential credibility assessment (DCA) of both spatial and temporal characteristics of the modes across ESMs, ESM families, and specific ESM realizations relative to ERA5. The spatial patterns and probability distributions are generally well represented but skill scores that measure the degree to which the frequencies of maximum variance are captured are consistently lower for most ESMs and climate modes. Substantial variability in skill scores manifests across realizations from individual ESMs for the PNA and oceanic modes. Further, the ESMs consistently overestimate the strength of the NAM–PNA first-order interaction and underestimate the NAM–AMO connection. These results suggest that the choice of ESM and ESM realizations will continue to play a critical role in determining climate projections at the global and regional scale at least in the near term.
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Zhang, Mingyue, Merja H. Tölle, Eva Hartmann, Elena Xoplaki, and Jürg Luterbacher. "A Sensitivity Assessment of COSMO-CLM to Different Land Cover Schemes in Convection-Permitting Climate Simulations over Europe." Atmosphere 12, no. 12 (November 29, 2021): 1595. http://dx.doi.org/10.3390/atmos12121595.
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The question of how sensitive the regional and local climates are to different land cover maps and fractions is important, as land cover affects the atmospheric circulation via its influence on heat, moisture, and momentum transfer, as well as the chemical composition of the atmosphere. In this study, we used three independent land cover data sets, GlobCover 2009, GLC2000 and ESACCI-LC, as the lower boundary of the regional climate model COSMO-CLM (Consortium for Small Scale Modeling in Climate Mode, v5.0-clm15) to perform convection-permitting regional climate simulations over the large part of Europe covering the years 1999 and 2000 at a 0.0275° horizontal resolution. We studied how the sensitivity of the impacts on regional and local climates is represented by different land cover maps and fractions, especially between warm (summer) and cold (winter) seasons. We show that the simulated regional climate is sensitive to different land cover maps and fractions. The simulated temperature and observational data are generally in good agreement, though with differences between the seasons. In comparison to winter, the summer simulations are more heterogeneous across the study region. The largest deviation is found for the alpine area (−3 to +3 °C), which might be among different reasons due to different classification systems in land cover maps and orographical aspects in the COSMO-CLM model. The leaf area index and plant cover also showed different responses based on various land cover types, especially over the area with high vegetation coverage. While relating the differences of land cover fractions and the COSMO-CLM simulation results (the leaf area index, and plant coverage) respectively, the differences in land cover fractions did not necessarily lead to corresponding bias in the simulation results. We finally provide a comparative analysis of how sensitive the simulation outputs (temperature, leaf area index, plant cover) are related to different land cover maps and fractions. The different regional representations of COSMO-CLM indicate that the soil moisture, atmospheric circulation, evaporative demand, elevation, and snow cover schemes need to be considered in the regional climate simulation with a high horizontal resolution.
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Messié, Monique, and Francisco Chavez. "Global Modes of Sea Surface Temperature Variability in Relation to Regional Climate Indices." Journal of Climate 24, no. 16 (August 15, 2011): 4314–31. http://dx.doi.org/10.1175/2011jcli3941.1.
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Abstract A century-long EOF analysis of global sea surface temperature (SST) was carried out and the first six modes, independent by construction, were found to be associated with well-known regional climate phenomena: the El Niño–Southern Oscillation (ENSO), the Atlantic multidecadal oscillation (AMO), the Pacific decadal oscillation (PDO), the North Pacific Gyre Oscillation (NPGO), El Niño Modoki, and the Atlantic El Niño. Four of the six global modes are dominated by Pacific changes, the other two (M2 and M6) being associated with the AMO and Atlantic El Niño, respectively. The principal component time series of the ENSO (M1) and North Pacific (M3) modes are coherent at time scales >10 yr, and their interaction results in the traditional PDO pattern and the dominant mode of Pacific multidecadal variability. The M3 and PDO time series are well correlated, but the EOFs have different spatial patterns. The fourth mode (M4) has been strengthening since the 1950s and is related to the NPGO but also to El Niño Modoki, especially at the decadal scale. The fifth global mode (M5) is also spatially and temporally correlated to El Niño Modoki. The Pacific SST modes are further related to atmospheric forcing and the circulation of the North Pacific subpolar and subtropical gyres.
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Doi, Takeshi, Chaoxia Yuan, Swadhin K. Behera, and Toshio Yamagata. "Predictability of the California Niño/Niña*." Journal of Climate 28, no. 18 (September 11, 2015): 7237–49. http://dx.doi.org/10.1175/jcli-d-15-0112.1.
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Abstract Predictability of a recently discovered regional coupled climate mode called the California Niño (Niña) off Baja California and California is explored using a seasonal prediction system based on the Scale Interaction Experiment-Frontier, version 1 (SINTEX-F1) coupled ocean–atmosphere general circulation model. Because of the skillful prediction of basin-scale El Niño (La Niña), the California Niño (Niña) that co-occurs with El Niño (La Niña) with a peak in boreal winter is found to be predictable at least a couple of seasons ahead. On the other hand, the regional coupled phenomenon peaking in boreal summer without co-occurrence with El Niño (La Niña) is difficult to predict. The difficulty in predicting such an intrinsic regional climate phenomenon may be due to model deficiency in resolving the regional air–sea–land positive feedback processes. The model may also underestimate coastal Kelvin waves with a small offshore scale, which may play an important role in the generation of the California Niño/Niña. It may be improved by increasing horizontal resolution of the ocean component of the coupled model. The present study may provide a guideline to improve seasonal prediction of regional climate modes for important industrial as well as social applications.
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Ge, Yan, and Gavin Gong. "North American Snow Depth and Climate Teleconnection Patterns." Journal of Climate 22, no. 2 (January 15, 2009): 217–33. http://dx.doi.org/10.1175/2008jcli2124.1.
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Abstract Snow–atmosphere relationships have been studied for nearly half a century, but the primary focus has been on snow extent variability, largely because of the relative scarcity of snow depth data. A recently released North American snow depth dataset, with extensive spatial coverage and multidecadal temporal duration, provides a new opportunity to compare snow depth–climate relationships with snow extent–climate relationships over North America. Robust concurrent lead and lag correlations are observed between snow depth and two major climate modes, the Pacific decadal oscillation (PDO) and the Pacific–North America (PNA) pattern, across North America and throughout the snow season. In contrast, snow extent exhibits a less coherent relationship with PDO and PNA except in late spring, which can be interpreted as a residual of the snow depth–climate mode relationship. A regional signature for the snow depth–PDO/PNA relationship is also identified, centered over interior central-western North America. Smaller scales mask the regional effect of PDO and PNA because of local snow depth variability, while larger continental scales exceed the regional domain of the climate mode teleconnections. Overall these results suggest that North American snow depth variability may have greater climatic causes and consequences than snow extent. Physical mechanisms that may be responsible for the observed snow depth–climate teleconnection patterns such as the surface energy balance, moisture transport, and atmospheric flow regimes are briefly discussed.
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Verdon-Kidd, D., and A. S. Kiem. "On the relationship between large-scale climate modes and regional synoptic patterns that drive Victorian rainfall." Hydrology and Earth System Sciences Discussions 5, no. 5 (October 10, 2008): 2791–815. http://dx.doi.org/10.5194/hessd-5-2791-2008.
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Abstract. In this paper regional (synoptic) and large-scale climate drivers of rainfall are investigated for Victoria, Australia. A non-linear classification methodology known as self-organizing maps (SOM) is used to identify 20 key regional synoptic patterns, which are shown to capture a range of significant synoptic features known to influence the climate of the region. Rainfall distributions are assigned to each of the 20 patterns for nine rainfall stations located across Victoria, resulting in a clear distinction between wet and dry synoptic types at each station. The influence of large-scale climate modes on the frequency and timing of the regional synoptic patterns is also investigated. This analysis revealed that phase changes in the El Niño Southern Oscillation (ENSO), the Southern Annular Mode (SAM) and/or Indian Ocean Dipole (IOD) are associated with a shift in the relative frequency of wet and dry synoptic types. Importantly, these results highlight the potential to utilise the link between the regional synoptic patterns derived in this study and large-scale climate modes to improve rainfall forecasting for Victoria, both in the short- (i.e. seasonal) and long-term (i.e. decadal/multi-decadal scale). In addition, the regional and large-scale climate drivers identified in this study provide a benchmark by which the performance of Global Climate Models (GCMs) may be assessed.
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Castro, Christopher L., Roger A. Pielke, Jimmy O. Adegoke, Siegfried D. Schubert, and Phillip J. Pegion. "Investigation of the Summer Climate of the Contiguous United States and Mexico Using the Regional Atmospheric Modeling System (RAMS). Part II: Model Climate Variability." Journal of Climate 20, no. 15 (August 1, 2007): 3866–87. http://dx.doi.org/10.1175/jcli4212.1.
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Abstract Summer simulations over the contiguous United States and Mexico with the Regional Atmospheric Modeling System (RAMS) dynamically downscaling the NCEP–NCAR Reanalysis I for the period 1950–2002 (described in Part I of the study) are evaluated with respect to the three dominant modes of global SST. Two of these modes are associated with the statistically significant, naturally occurring interannual and interdecadal variability in the Pacific. The remaining mode corresponds to the recent warming of tropical sea surface temperatures. Time-evolving teleconnections associated with Pacific SSTs delay or accelerate the evolution of the North American monsoon. At the period of maximum teleconnectivity in late June and early July, there is an opposite relationship between precipitation in the core monsoon region and the central United States. Use of a regional climate model (RCM) is essential to capture this variability because of its representation of the diurnal cycle of convective rainfall. The RCM also captures the observed long-term changes in Mexican summer rainfall and suggests that these changes are due in part to the recent increase in eastern Pacific SST off the Mexican coast. To establish the physical linkage to remote SST forcing, additional RAMS seasonal weather prediction mode simulations were performed and these results are briefly discussed. In order for RCMs to be successful in a seasonal weather prediction mode for the summer season, it is required that the GCM provide a reasonable representation of the teleconnections and have a climatology that is comparable to a global atmospheric reanalysis.
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Busuioc, Aristita, Hans von Storch, and Reiner Schnur. "Verification of GCM-Generated Regional Seasonal Precipitation for Current Climate and of Statistical Downscaling Estimates under Changing Climate Conditions." Journal of Climate 12, no. 1 (January 1, 1999): 258–72. http://dx.doi.org/10.1175/1520-0442-12.1.258.
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Abstract Empirical downscaling procedures relate large-scale atmospheric features with local features such as station rainfall in order to facilitate local scenarios of climate change. The purpose of the present paper is twofold: first, a downscaling technique is used as a diagnostic tool to verify the performance of climate models on the regional scale; second, a technique is proposed for verifying the validity of empirical downscaling procedures in climate change applications. The case considered is regional seasonal precipitation in Romania. The downscaling model is a regression based on canonical correlation analysis between observed station precipitation and European-scale sea level pressure (SLP). The climate models considered here are the T21 and T42 versions of the Hamburg ECHAM3 atmospheric GCM run in “time-slice” mode. The climate change scenario refers to the expected time of doubled carbon dioxide concentrations around the year 2050. The downscaling model is skillful for all seasons except spring. The general features of the large-scale SLP variability are reproduced fairly well by both GCMs in all seasons. The climate models reproduce the empirically determined precipitation–SLP link in winter, whereas the observed link is only partially captured for the other seasons. Thus, these models may be considered skillful with respect to regional precipitation during winter, and partially during the other seasons. Generally, applications of statistical downscaling to climate change scenarios have been based on the assumption that the empirical link between the large-scale and regional parameters remains valid under a changed climate. In this study, a rationale is proposed for this assumption by showing the consistency of the 2 × CO2 GCM scenarios in winter, derived directly from the gridpoint data, with the regional scenarios obtained through empirical downscaling. Since the skill of the GCMs in regional terms is already established, it is concluded that the downscaling technique is adequate for describing climatically changing regional and local conditions, at least for precipitation in Romania during winter.
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Rauthe, Monika, and Heiko Paeth. "Relative Importance of Northern Hemisphere Circulation Modes in Predicting Regional Climate Change." Journal of Climate 17, no. 21 (November 1, 2004): 4180–89. http://dx.doi.org/10.1175/jcli3140.1.
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Abstract The Northern Hemisphere annular mode (NAM), North Atlantic Oscillation (NAO), and Aleutian low (AL) are known to be the most prominent components of Northern Hemisphere (NH) near-surface climate variability. In a tremendous number of studies, the impact of these circulation features on regional climate has been demonstrated. More recently, research has gone into the connection between the NAO and NAM and into the physical meaning of the latter. However, the relevance of those circulation modes for climatological issues may also be inferred from another nondynamical point of view: their statistical relationship to various climate parameters. This study comprises two steps: 1) qualifying and quantifying the relative importance of NH circulation modes with respect to twentieth-century near-surface temperature and precipitation, using stepwise multiple regression with cross validation; and 2) using predictor–predictand relationships to access the contributions of each circulation mode to regional climate change in the middle of the twenty-first century, given multimodel predictions of the circulation modes' responses to increasing greenhouse gas (GHG) and sulfate aerosol (SUL) concentrations. Altogether, the NAM, NAO, and AL account locally for up to 75% of the total interannual temperature and rainfall variability over NH continents. Over the major part of the NH, the NAM appears to be the most important predictor. In some parts of the North Atlantic, temperature and rainfall are more closely linked to the NAO, while the North Pacific is clearly dominated by the AL dynamics. In general, the NAO and AL have a more regionally confined influence. Climate change experiments mostly predict an intensification of the NAM and AL under GHG+SUL forcing, while the NAO response is much less consistent with different models and generally undergoes no long-term changes. This leads to substantial contributions to temperature and rainfall anomalies, especially over the NH landmasses. Temperature changes amount to ±1 K over large parts of Russia, North America, and the North Pacific. The major precipitation changes occur over the North Pacific, the North Atlantic, and Scandinavia. This circulation-induced contribution accounts for a considerable part of total expected change in these regions. Given its distinct trend, the NAM plays the main role, except over the Pacific Ocean and North America, where the AL is driving regional climate anomalies. Thus, whether physically relevant or not, the NAM is an appropriate statistical indicator of NH regional climate change.
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Feng, Junshu, and Peng Wang. "Analysis on Electrification Development Mode from a Global Perspective." E3S Web of Conferences 165 (2020): 06043. http://dx.doi.org/10.1051/e3sconf/202016506043.
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In the context of a global response to climate change, the key to the future low-carbon energy transition is “electricity-cantered”, which makes use of renewable energy. This paper studied the typical modes of improving electrification from a global perspective, including clean energy driving mode, industry upgrading driving mode, regional resource integrated planning mode, power grid-led mode and inclusive mode for all. The research can provide options of electrification development in different regions all over the world.
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Verdon-Kidd, D. C., and A. S. Kiem. "On the relationship between large-scale climate modes and regional synoptic patterns that drive Victorian rainfall." Hydrology and Earth System Sciences 13, no. 4 (April 7, 2009): 467–79. http://dx.doi.org/10.5194/hess-13-467-2009.
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Abstract. In this paper regional (synoptic) and large-scale climate drivers of rainfall are investigated for Victoria, Australia. A non-linear classification methodology known as self-organizing maps (SOM) is used to identify 20 key regional synoptic patterns, which are shown to capture a range of significant synoptic features known to influence the climate of the region. Rainfall distributions are assigned to each of the 20 patterns for nine rainfall stations located across Victoria, resulting in a clear distinction between wet and dry synoptic types at each station. The influence of large-scale climate modes on the frequency and timing of the regional synoptic patterns is also investigated. This analysis revealed that phase changes in the El Niño Southern Oscillation (ENSO), the Indian Ocean Dipole (IOD) and/or the Southern Annular Mode (SAM) are associated with a shift in the relative frequency of wet and dry synoptic types on an annual to inter-annual timescale. In addition, the relative frequency of synoptic types is shown to vary on a multi-decadal timescale, associated with changes in the Inter-decadal Pacific Oscillation (IPO). Importantly, these results highlight the potential to utilise the link between the regional synoptic patterns derived in this study and large-scale climate modes to improve rainfall forecasting for Victoria, both in the short- (i.e. seasonal) and long-term (i.e. decadal/multi-decadal scale). In addition, the regional and large-scale climate drivers identified in this study provide a benchmark by which the performance of Global Climate Models (GCMs) may be assessed.
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Shepherd, Tristan, Jacob J. Coburn, Rebecca J. Barthelmie, and Sara C. Pryor. "Exploring ENSO-Induced Anomalies over North America in Historical and Future Climate Simulations That Use HadGEM2-ESM Output to Drive WRF." Climate 10, no. 8 (August 10, 2022): 117. http://dx.doi.org/10.3390/cli10080117.
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Projected changes to the El Niño Southern Oscillation (ENSO) climate mode have been explored using global Earth system models (ESMs). Regional expressions of such changes have yet to be fully advanced and may require the use of regional downscaling. Here, we employ regional climate modeling (RCM) using the Weather Research and Forecasting (WRF) model at convection-permitting resolution and nested in output from the HadGEM2 ESM. We quantify ENSO teleconnections to temperature and precipitation anomalies in historical and future climate scenarios over eastern North America. Two paired simulations are run, a strong El Niño (positive ENSO phase) and a weak La Niña (negative ENSO phase), for the historical and future years. The HadGEM2 direct output and HadGEM2-WRF simulation output are compared to the anomalies derived from the NOAA ENSO Climate Normals dataset. The near-surface temperature and precipitation differences by ENSO phase, as represented by the HadGEM2-WRF historical simulations, show a poor degree of association with the NOAA ENSO Climate Normals, in part because of the large biases in the HadGEM2 model. Downscaling with the WRF model does improve the agreement with the observations, and large discrepancies remain. The model chain HadGEM2-WRF reverses the sign of the ENSO phase response over eastern North America under simulations of the future climate with high greenhouse gas forcing, but due to the poor agreement with the NOAA ENSO Climate Normals it is difficult to assign confidence to this prediction.
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McKinnon, Karen A., and Clara Deser. "Internal Variability and Regional Climate Trends in an Observational Large Ensemble." Journal of Climate 31, no. 17 (September 2018): 6783–802. http://dx.doi.org/10.1175/jcli-d-17-0901.1.
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Recent observed climate trends result from a combination of external radiative forcing and internally generated variability. To better contextualize these trends and forecast future ones, it is necessary to properly model the spatiotemporal properties of the internal variability. Here, a statistical model is developed for terrestrial temperature and precipitation, and global sea level pressure, based upon monthly gridded observational datasets that span 1921–2014. The model is used to generate a synthetic ensemble, each member of which has a unique sequence of internal variability but with statistical properties similar to the observational record. This synthetic ensemble is combined with estimates of the externally forced response from climate models to produce an observational large ensemble (OBS-LE). The 1000 members of the OBS-LE display considerable diversity in their 50-yr regional climate trends, indicative of the importance of internal variability on multidecadal time scales. For example, unforced atmospheric circulation trends associated with the northern annular mode can induce winter temperature trends over Eurasia that are comparable in magnitude to the forced trend over the past 50 years. Similarly, the contribution of internal variability to winter precipitation trends is large across most of the globe, leading to substantial regional uncertainties in the amplitude and, in some cases, the sign of the 50-yr trend. The OBS-LE provides a real-world counterpart to initial-condition model ensembles. The approach could be expanded to using paleo-proxy data to simulate longer-term variability.
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Thiery, Wim, Edouard L. Davin, Hans-Jürgen Panitz, Matthias Demuzere, Stef Lhermitte, and Nicole van Lipzig. "The Impact of the African Great Lakes on the Regional Climate." Journal of Climate 28, no. 10 (May 12, 2015): 4061–85. http://dx.doi.org/10.1175/jcli-d-14-00565.1.
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Abstract Although the African Great Lakes are important regulators for the East African climate, their influence on atmospheric dynamics and the regional hydrological cycle remains poorly understood. This study aims to assess this impact by comparing a regional climate model simulation that resolves individual lakes and explicitly computes lake temperatures to a simulation without lakes. The Consortium for Small-Scale Modelling model in climate mode (COSMO-CLM) coupled to the Freshwater Lake model (FLake) and Community Land Model (CLM) is used to dynamically downscale a simulation from the African Coordinated Regional Downscaling Experiment (CORDEX-Africa) to 7-km grid spacing for the period of 1999–2008. Evaluation of the model reveals good performance compared to both in situ and satellite observations, especially for spatiotemporal variability of lake surface temperatures (0.68-K bias), and precipitation (−116 mm yr−1 or 8% bias). Model integrations indicate that the four major African Great Lakes almost double the annual precipitation amounts over their surface but hardly exert any influence on precipitation beyond their shores. Except for Lake Kivu, the largest lakes also cool the annual near-surface air by −0.6 to −0.9 K on average, this time with pronounced downwind influence. The lake-induced cooling happens during daytime, when the lakes absorb incoming solar radiation and inhibit upward turbulent heat transport. At night, when this heat is released, the lakes warm the near-surface air. Furthermore, Lake Victoria has a profound influence on atmospheric dynamics and stability, as it induces circular airflow with over-lake convective inhibition during daytime and the reversed pattern at night. Overall, this study shows the added value of resolving individual lakes and realistically representing lake surface temperatures for climate studies in this region.
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Li, Jie, Wan Ying Qu, Fang Wang, and Wan Zhen Li. "Research and Analysis on the Heating Energy Consumption of Urban Residents in Hot Summer and Cold Winter Area of China." Applied Mechanics and Materials 587-589 (July 2014): 299–303. http://dx.doi.org/10.4028/www.scientific.net/amm.587-589.299.
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The paper analyzes the energy-saving mode in hot summer and cold winter area through simulating and comparing the unique climate conditions and energy-using mode in this region, which are different from the northern heating areas. In hot summer and cold summer areas, the current per unit area value of heating electricity is low in urban residences, but it is based on the low heating temperature value and intermittent heating approach, and the energy consumption grows with the development of economy and the improvement of people's living standard. According to the regional climate characteristics and living mode, the decentralized efficient heating modes based on various pumps should be developed instead of central heating or central heating and cooling system.
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Fiddes, Sonya L., Matthew T. Woodhouse, Todd P. Lane, and Robyn Schofield. "Coral-reef-derived dimethyl sulfide and the climatic impact of the loss of coral reefs." Atmospheric Chemistry and Physics 21, no. 8 (April 20, 2021): 5883–903. http://dx.doi.org/10.5194/acp-21-5883-2021.
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Abstract. Dimethyl sulfide (DMS) is a naturally occurring aerosol precursor gas which plays an important role in the global sulfur budget, aerosol formation and climate. While DMS is produced predominantly by phytoplankton, recent observational literature has suggested that corals and their symbionts produce a comparable amount of DMS, which is unaccounted for in models. It has further been hypothesised that the coral reef source of DMS may modulate regional climate. This hypothesis presents a particular concern given the current threat to coral reefs under anthropogenic climate change. In this paper, a global climate model with online chemistry and aerosol is used to explore the influence of coral-reef-derived DMS on atmospheric composition and climate. A simple representation of coral-reef-derived DMS is developed and added to a common DMS surface water climatology, resulting in an additional flux of 0.3 Tg yr−1 S, or 1.7 % of the global sulfur flux from DMS. By comparing the differences between both nudged and free-running ensemble simulations with and without coral-reef-derived DMS, the influence of coral-reef-derived DMS on regional climate is quantified. In the Maritime Continent–Australian region, where the highest density of coral reefs exists, a small decrease in nucleation- and Aitken-mode aerosol number concentration and mass is found when coral reef DMS emissions are removed from the system. However, these small responses are found to have no robust effect on regional climate via direct and indirect aerosol effects. This work emphasises the complexities of the aerosol–climate system, and the limitations of current modelling capabilities are highlighted, in particular surrounding convective responses to changes in aerosol. In conclusion, we find no robust evidence that coral-reef-derived DMS influences global and regional climate.
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Merrifield, Anna L., Lukas Brunner, Ruth Lorenz, Vincent Humphrey, and Reto Knutti. "Climate model Selection by Independence, Performance, and Spread (ClimSIPS v1.0.1) for regional applications." Geoscientific Model Development 16, no. 16 (August 23, 2023): 4715–47. http://dx.doi.org/10.5194/gmd-16-4715-2023.
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Abstract. As the number of models in Coupled Model Intercomparison Project (CMIP) archives increase from generation to generation, there is a pressing need for guidance on how to interpret and best use the abundance of newly available climate information. Users of the latest CMIP6 seeking to draw conclusions about model agreement must contend with an “ensemble of opportunity” containing similar models that appear under different names. Those who used the previous CMIP5 as a basis for downstream applications must filter through hundreds of new CMIP6 simulations to find several best suited to their region, season, and climate horizon of interest. Here we present methods to address both issues, model dependence and model subselection, to help users previously anchored in CMIP5 to navigate CMIP6 and multi-model ensembles in general. In Part I, we refine a definition of model dependence based on climate output, initially employed in Climate model Weighting by Independence and Performance (ClimWIP), to designate discrete model families within CMIP5 and CMIP6. We show that the increased presence of model families in CMIP6 bolsters the upper mode of the ensemble's bimodal effective equilibrium climate sensitivity (ECS) distribution. Accounting for the mismatch in representation between model families and individual model runs shifts the CMIP6 ECS median and 75th percentile down by 0.43 ∘C, achieving better alignment with CMIP5's ECS distribution. In Part II, we present a new approach to model subselection based on cost function minimization, Climate model Selection by Independence, Performance, and Spread (ClimSIPS). ClimSIPS selects sets of CMIP models based on the relative importance a user ascribes to model independence (as defined in Part I), model performance, and ensemble spread in projected climate outcome. We demonstrate ClimSIPS by selecting sets of three to five models from CMIP6 for European applications, evaluating the performance from the agreement with the observed mean climate and the spread in outcome from the projected mid-century change in surface air temperature and precipitation. To accommodate different use cases, we explore two ways to represent models with multiple members in ClimSIPS, first, by ensemble mean and, second, by an individual ensemble member that maximizes mid-century change diversity within the CMIP overall. Because different combinations of models are selected by the cost function for different balances of independence, performance, and spread priority, we present all selected subsets in ternary contour “subselection triangles” and guide users with recommendations based on further qualitative selection standards. ClimSIPS represents a novel framework to select models in an informed, efficient, and transparent manner and addresses the growing need for guidance and simple tools, so those seeking climate services can navigate the increasingly complex CMIP landscape.
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Camara, Moctar, Ibrahima Diba, and Arona Diedhiou. "Effects of Land Cover Changes on Compound Extremes over West Africa Using the Regional Climate Model RegCM4." Atmosphere 13, no. 3 (March 5, 2022): 421. http://dx.doi.org/10.3390/atmos13030421.
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This study aims to characterize the impacts of the Sahel–Sahara interface reforestation on compound extremes in the Sahel region during the West African monsoon season (June–July–August–September, JJAS). For this purpose, we performed a simulation with the standard version of the RegCM4 model, and another simulation with the altered version of the same model, taking into account the incorporated forest. Results show that reforestation may strongly influence the frequency of individual extreme events (dry and warm days) by decreasing them over and off the reforested zone. The reduction in these extreme dry and warm days may be due partly to the strengthening of the atmospheric moisture content over most parts of the West African domain and the weakening of the sensible heat flux south of 16° N. The analysis also shows an increase in extreme wet days over and off the reforested zone, which could be associated partly with the strengthening of evapotranspiration over most parts of the West African domain, including the reforested area. The analysis of compound extremes shows a strong occurrence of the compound dry/warm mode over the northern Sahel for both runs, probably due to the weak precipitation recorded in this zone. Both experiments also simulated a strong compound wet/warm mode occurrence over the Sahel due to a high rainfall occurrence over this region. When comparing both runs, the impact of the reforestation was to decrease (increase) the compound extreme dry/warm (wet/warm) mode over the reforested zone. The dry/warm mode decrease is consistent with that of individual extreme dry and warm days, while the compound wet/warm mode increase may be driven by that of the extreme wet days. Finally, when considering the seasonal cycle, the dry/warm mode exhibits a more substantial decrease in the beginning (June–July, JJ) than during the peak of the West African summer monsoon season (August–September, AS). Moreover, reforestation similarly affects the compound wet/warm mode in JJ and AS by increasing it in the reforested region and decreasing it over the Southern Sahel (south of 15° N). This work suggests that reforestation may be a good solution for West African policymakers to mitigate climate change over the region and to develop better strategies for water resource management.
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Lohmann, G., A. Wackerbarth, P. M. Langebroek, M. Werner, J. Fohlmeister, D. Scholz, and A. Mangini. "Simulated European stalagmite record and its relation to a quasi-decadal climate mode." Climate of the Past 9, no. 1 (January 21, 2013): 89–98. http://dx.doi.org/10.5194/cp-9-89-2013.
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Abstract. A synthetic stalagmite δ18O record for the Bunker Cave (51° N, 7° E) is constructed using a combined climate–stalagmite modelling approach where we combine an atmospheric circulation model equipped with water isotopes and a model simulating stalagmite calcite δ18O values. Mixing processes in the soil and karst above the cave represent a natural low-pass filter of the speleothem climate archive. Stalagmite δ18O values at Bunker Cave lag the regional surface climate by 3–4 yr. The power spectrum of the simulated speleothem calcite δ18O record has a pronounced peak at quasi-decadal time scale, which is associated with a large-scale climate variability pattern in the North Atlantic. Our modelling study suggests that stalagmite records from Bunker Cave are representative for large-scale teleconnections and can be used to obtain information about the North Atlantic and its decadal variability.
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Gudoshava, Masilin, and Fredrick H. M. Semazzi. "Customization and Validation of a Regional Climate Model Using Satellite Data Over East Africa." Atmosphere 10, no. 6 (June 10, 2019): 317. http://dx.doi.org/10.3390/atmos10060317.
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This study focused on the customization of the fourth generation International Center for Theoretical Physics Regional Climate Model version 4.4 and its ability to reproduce the mean climate and most dominant modes of variability over East Africa. The simulations were performed at a spatial resolution of 25 km for the period 1998–2013. The model was driven by ERA-Interim reanalysis. The customization focus was on cumulus and microphysics schemes during the Short Rains for the year 2000. The best physics combinations were then utilized for the validation studies. The East Africa region and Lake Victoria Basin region are adapted to carry out empirical orthogonal function analysis, during the Short and Long Rains. Tropical Rainfall Measuring Mission data was utilized in the validation of the model. The first mode of variability from the model and observational data during the Short Rains was associated with the warming of the Pacific Ocean and the sea surface temperature gradients over the Indian Ocean. During the Long rains, the inter-annual rainfall variability over the Lake Victoria region was associated with the sea surface temperature anomaly over the Indian Ocean and for the East Africa region the associations were weak. The drivers during the Long Rains over East Africa region were then further investigated by splitting the season to the March–April and May periods. The March–April period was positively correlated to the West Pacific and Indian Ocean dipole index, while May was associated with the Quasi-Biennial Oscillation. In conclusion, although the model can reproduce the dominant modes of variability as in the observational data sets during the Short Rains, skill was lower during the Long Rains.
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Wang, Libo, Murray MacKay, Ross Brown, Paul Bartlett, Richard Harvey, and Alexandre Langlois. "Application of Satellite Data for Evaluating the Cold Climate Performance of the Canadian Regional Climate Model over Québec, Canada." Journal of Hydrometeorology 15, no. 2 (April 1, 2014): 614–30. http://dx.doi.org/10.1175/jhm-d-13-086.1.
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Abstract This study evaluates key aspects of the snow cover, cloud cover, and radiation budget simulated by the Canadian Regional Climate Model, version 4 (CRCM4), coupled with two versions of the Canadian Land Surface Scheme (CLASS). CRCM4 coupled with CLASS version 2.7 has been used operationally at Ouranos since 2006, while, more recently, CRCM4 has been coupled experimentally with CLASS 3.5, which includes a number of improvements to the representation of snow cover processes. The simulations showed evidence of a systematic cold temperature bias. Evaluation of cloud cover and radiation fluxes with satellite data suggests this bias is related to insufficient cloud radiative forcing from a combination of underestimated cloud cover, excessive cloud albedo, and too low cloud emissivity in the model. This cold bias is reinforced by a positive snow albedo feedback manifest through earlier snow cover onset in the fall and early winter period. Snow albedo was found to be very sensitive to the treatment of albedo refresh but insignificantly influenced by the partitioning of solid precipitation in CLASS. This study demonstrates that atmospheric forcing can exert a significant impact on the simulation of snow cover and surface albedo. The results highlight the need to evaluate parameterizations in land surface models designed for climate models in fully coupled mode.
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Berckmans, Julie, Olivier Giot, Rozemien De Troch, Rafiq Hamdi, Reinhart Ceulemans, and Piet Termonia. "Reinitialised versus continuous regional climate simulations using ALARO-0 coupled to the land surface model SURFEXv5." Geoscientific Model Development 10, no. 1 (January 16, 2017): 223–38. http://dx.doi.org/10.5194/gmd-10-223-2017.
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Abstract. Dynamical downscaling in a continuous approach using initial and boundary conditions from a reanalysis or a global climate model is a common method for simulating the regional climate. The simulation potential can be improved by applying an alternative approach of reinitialising the atmosphere, combined with either a daily reinitialised or a continuous land surface. We evaluated the dependence of the simulation potential on the running mode of the regional climate model ALARO coupled to the land surface model Météo-France SURFace EXternalisée (SURFEX), and driven by the ERA-Interim reanalysis. Three types of downscaling simulations were carried out for a 10-year period from 1991 to 2000, over a western European domain at 20 km horizontal resolution: (1) a continuous simulation of both the atmosphere and the land surface, (2) a simulation with daily reinitialisations for both the atmosphere and the land surface and (3) a simulation with daily reinitialisations of the atmosphere while the land surface is kept continuous. The results showed that the daily reinitialisation of the atmosphere improved the simulation of the 2 m temperature for all seasons. It revealed a neutral impact on the daily precipitation totals during winter, but the results were improved for the summer when the land surface was kept continuous. The behaviour of the three model configurations varied among different climatic regimes. Their seasonal cycle for the 2 m temperature and daily precipitation totals was very similar for a Mediterranean climate, but more variable for temperate and continental climate regimes. Commonly, the summer climate is characterised by strong interactions between the atmosphere and the land surface. The results for summer demonstrated that the use of a daily reinitialised atmosphere improved the representation of the partitioning of the surface energy fluxes. Therefore, we recommend using the alternative approach of the daily reinitialisation of the atmosphere for the simulation of the regional climate.
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DuchÊne, François, Bert Van Schaeybroeck, Steven Caluwaerts, Rozemien De Troch, Rafiq Hamdi, and Piet Termonia. "A Statistical–Dynamical Methodology to Downscale Regional Climate Projections to Urban Scale." Journal of Applied Meteorology and Climatology 59, no. 6 (June 2020): 1109–23. http://dx.doi.org/10.1175/jamc-d-19-0104.1.
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AbstractThe demand of city planners for quantitative information on the impact of climate change on the urban environment is increasing. However, such information is usually extracted from decadelong climate projections generated with global or regional climate models (RCMs). Because of their coarse resolution and unsuitable physical parameterization, however, their model output is not adequate to be used at city scale. A full dynamical downscaling to city level, on the other hand, is computationally too expensive for climatological time scales. A statistical–dynamical computationally inexpensive method is therefore proposed that approximates well the behavior of the full dynamical downscaling approach. The approach downscales RCM simulations using the combination of an RCM at high resolution (H-RES) and a land surface model (LSM). The method involves the setup of a database of urban signatures by running an H-RES RCM with and without urban parameterization for a relatively short period. Using an analog approach, these signatures are first selectively added to the long-term RCM data, which are then used as forcing for an LSM using an urban parameterization in a stand-alone mode. A comparison with a full dynamical downscaling approach is presented for the city of Brussels, Belgium, for 30 summers with the combined ALADIN–AROME model (ALARO-0) coupled to the Surface Externalisée model (SURFEX) as H-RES RCM and SURFEX as LSM. The average bias of the nocturnal urban heat island during heat waves is vanishingly small, and the RMSE is strongly reduced. Not only is the statistical–dynamical approach able to correct the heat-wave number and intensities, it can also improve intervariable correlations and multivariate and temporally correlated indices, such as Humidex.
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Akkermans, Tom, Wim Thiery, and Nicole P. M. Van Lipzig. "The Regional Climate Impact of a Realistic Future Deforestation Scenario in the Congo Basin." Journal of Climate 27, no. 7 (March 26, 2014): 2714–34. http://dx.doi.org/10.1175/jcli-d-13-00361.1.
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Abstract The demand for agricultural land in the Congo basin is expected to yield substantial deforestation over the coming decades. Although several studies exist on the climatological impact of deforestation in the Congo basin, deforestation scenarios that are implemented in climate models are generally crude. This study aims to refine current impact assessments by removing the primary forest according to an existing spatially explicit scenario, and replacing it by successional vegetation typically observed for the Congo basin. This is done within the Consortium for Small-Scale Modeling (COSMO) model in climate mode (COSMO-CLM), a regional climate model at 25-km grid spacing coupled to a state-of-the-art soil–vegetation–atmosphere transfer scheme (Community Land Model). An evaluation of the model shows good performance compared to in situ and satellite observations. Model integrations indicate that the deforestation, expected for the middle of the twenty-first century, induces a warming of about 0.7°C. This is about half the greenhouse gas–induced surface warming in this region, given an intermediate emission scenario (A1B) with COSMO-CLM driven by the ECHAM5 global climate model. This shows the necessity of taking into account deforestation to obtain realistic future climate projections. The deforestation-induced warming can be attributed to reduced evaporation, but this effect is mitigated by increased albedo and increased sensible heat loss to the atmosphere. Precipitation is also affected: as a consequence of surface warming resulting from deforestation, a regional heat low develops over the rain forest region. Resulting low-level convergence causes a redistribution of moisture in the boundary layer and a stabilization of the atmospheric column, thereby reducing convection intensity and hence precipitation by 5%–10% in the region of the heat low.
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Séférian, R., L. Bopp, D. Swingedouw, and J. Servonnat. "Dynamical and biogeochemical control on the decadal variability of ocean carbon fluxes." Earth System Dynamics 4, no. 1 (April 9, 2013): 109–27. http://dx.doi.org/10.5194/esd-4-109-2013.
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Abstract. Several recent observation-based studies suggest that ocean anthropogenic carbon uptake has slowed down due to the impact of anthropogenic forced climate change. However, it remains unclear whether detected changes over the recent time period can be attributed to anthropogenic climate change or rather to natural climate variability (internal plus naturally forced variability) alone. One large uncertainty arises from the lack of knowledge on ocean carbon flux natural variability at the decadal time scales. To gain more insights into decadal time scales, we have examined the internal variability of ocean carbon fluxes in a 1000 yr long preindustrial simulation performed with the Earth System Model IPSL-CM5A-LR. Our analysis shows that ocean carbon fluxes exhibit low-frequency oscillations that emerge from their year-to-year variability in the North Atlantic, the North Pacific, and the Southern Ocean. In our model, a 20 yr mode of variability in the North Atlantic air-sea carbon flux is driven by sea surface temperature variability and accounts for ~40% of the interannual regional variance. The North Pacific and the Southern Ocean carbon fluxes are also characterised by decadal to multi-decadal modes of variability (10 to 50 yr) that account for 20–40% of the interannual regional variance. These modes are driven by the vertical supply of dissolved inorganic carbon through the variability of Ekman-induced upwelling and deep-mixing events. Differences in drivers of regional modes of variability stem from the coupling between ocean dynamics variability and the ocean carbon distribution, which is set by large-scale secular ocean circulation.
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Séférian, R., L. Bopp, D. Swingedouw, and J. Servonnat. "Dynamical and biogeochemical control on the decadal variability of ocean carbon fluxes." Earth System Dynamics Discussions 3, no. 2 (December 21, 2012): 1347–89. http://dx.doi.org/10.5194/esdd-3-1347-2012.
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Abstract. Several recent observation-based studies suggest that ocean anthropogenic carbon uptake has slowed down due to the impact of anthropogenic forced climate change. However, it remains unclear if detected changes over the recent time period can really be attributed to anthropogenic climate change or to natural climate variability (internal plus naturally forced variability). One large uncertainty arises from the lack of knowledge on ocean carbon flux natural variability at the decadal time scales. To gain more insights into decadal time scales, we have examined the internal variability of ocean carbon fluxes in a 1000-yr long preindustrial simulation performed with the Earth System Model IPSL-CM5A-LR. Our analysis shows that ocean carbon fluxes exhibit low-frequency oscillations that emerge from their year-to-year variability in the North Atlantic, the North Pacific, and the Southern Ocean. In our model, a 20-yr mode of variability in the North Atlantic air-sea carbon flux is driven by sea surface temperature variability and accounts for ~40% of the interannual regional variance. The North Pacific and the Southern Ocean carbon fluxes are also characterized by decadal to multi-decadal modes of variability (10 to 50 yr) that account for 30–40% of the interannual regional variance. But these modes are driven by the vertical supply of dissolved inorganic carbon through the variability of Ekman-induced upwelling and deep-mixing events. Differences in drivers of regional modes of variability stem from the coupling between ocean dynamics variability and the ocean carbon distribution, which is set by large-scale secular ocean circulation.
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Royston, Sam, Rory J. Bingham, and Jonathan L. Bamber. "Attributing decadal climate variability in coastal sea-level trends." Ocean Science 18, no. 4 (July 27, 2022): 1093–107. http://dx.doi.org/10.5194/os-18-1093-2022.
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Abstract. Decadal sea-level variability masks longer-term changes due to natural and anthropogenic drivers in short-duration records and increases uncertainty in trend and acceleration estimates. When making regional coastal management and adaptation decisions, it is important to understand the drivers of these changes to account for periods of reduced or enhanced sea-level change. The variance in decadal sea-level trends about the global mean is quantified and mapped around the global coastlines of the Atlantic, Pacific, and Indian oceans from historical CMIP6 runs and a high-resolution ocean model forced by reanalysis data. We reconstruct coastal, sea-level trends via linear relationships with climate mode and oceanographic indices. Using this approach, more than one-third of the variability in decadal sea-level trends can be explained by climate indices at 24.6 % to 73.1 % of grid cells located within 25 km of a coast in the Atlantic, Pacific, and Indian oceans. At 10.9 % of the world's coastline, climate variability explains over two-thirds of the decadal sea-level trend. By investigating the steric, manometric, and gravitational components of sea-level trend independently, it is apparent that much of the coastal ocean variability is dominated by the manometric signal, the consequence of the open-ocean steric signal propagating onto the continental shelf. Additionally, decadal variability in the gravitational, rotational, and solid-Earth deformation (GRD) signal should not be ignored in the total. There are locations such as the Persian Gulf and African west coast where decadal sea-level variability is historically small that are susceptible to future changes in hydrology and/or ice mass changes that drive intensified regional GRD sea-level change above the global mean. The magnitude of variance explainable by climate modes quantified in this study indicates an enhanced uncertainty in projections of short- to mid-term regional sea-level trend.
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Feser, Frauke, and Hans von Storch. "A Dynamical Downscaling Case Study for Typhoons in Southeast Asia Using a Regional Climate Model." Monthly Weather Review 136, no. 5 (May 1, 2008): 1806–15. http://dx.doi.org/10.1175/2007mwr2207.1.
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Abstract This study explores the possibility of reconstructing the weather of Southeast Asia for the last decades using an atmospheric regional climate model, the Climate version of the Lokal-Modell (CLM). For this purpose global National Centers for Environmental Prediction–National Center for Atmospheric Research (NCEP–NCAR) reanalyses data were dynamically downscaled to 50 km and in a double-nesting approach to 18-km grid distance. To prevent the regional model from deviating significantly from the reanalyses with respect to large-scale circulation and large-scale weather phenomena, a spectral nudging technique was used. The performance of this technique in dealing with Southeast Asian typhoons is now examined by considering an ensemble of one simulated typhoon case. This analysis is new insofar as it deals with simulations done in the climate mode (so that any skill of reproducing the typhoon is not related to details of initial conditions), is done in ensemble mode (the same development is described by several simulations), and is done with a spectral nudging constraint (so that the observed large-scale state is enforced in the model domain). This case indicates that tropical storms that are coarsely described by the reanalyses are correctly identified and tracked; considerably deeper core pressure and higher wind speeds are simulated compared to the driving reanalyses. When the regional atmospheric model is run without spectral nudging, significant intraensemble variability occurs; also additional, nonobserved typhoons form. Thus, the insufficiency of lateral boundary conditions alone for determining the details of the dynamic developments in the interior becomes very clear. The same lateral boundary conditions are consistent with different developments in the interior. Several sensitivity experiments were performed concerning varied grid distances, different initial starting dates of the simulations, and changed spectral nudging parameters.
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Tian, Gui Liang, Xing Bo Sun, and Xi Wu. "Research on Virtual-Water Futures Based on Food Safety." Advanced Materials Research 1010-1012 (August 2014): 1980–84. http://dx.doi.org/10.4028/www.scientific.net/amr.1010-1012.1980.
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Global climate disasters happen frequent, agricultural production has led to great instability. The drought disasters are the most serious in these climate disasters. However, agricultural water shortage areas lack of response mechanism to drought disasters. To resist these sudden drought events and uncertainties, this paper has designed a mode of operation of virtual water futures. Then, we analyze the procession of the virtual water futures balancing generalized regional water, as well as elaborated virtual water futures how to hedge the grain yield loss risk. At last, we conclude that virtual water is an effective supplement for agricultural water, agricultural virtual water futures hedging can protect the region's food supply and reduce agricultural losses.
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Yu, Shu, Shuangshuang Zhang, and Takaya Yuizono. "Exploring the Influences of Innovation Climate and Resource Endowments through Two Types of University–Industry Collaborative Activities on Regional Sustainable Development." Sustainability 13, no. 14 (July 6, 2021): 7559. http://dx.doi.org/10.3390/su13147559.
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“Innovation driven” is the proper term for promoting regional sustainable development under the general goal of national high-quality development. University–industry collaboration (UIC) has become an important innovation resource for regional sustainable development. The study aims to analyze the influencing factors and mediating mechanisms of university–industry collaboration scientific and technological (S&T) and business activities oriented for regional sustainable development in 30 provinces in China (excluding Tibet). Specifically, we used the partial least squares (PLS) structural equation modeling method to test the effects of innovation climate and resource endowments on regional sustainable development through two mode pathways of university–industry collaboration activities. The results show that the innovation climate and resource endowments significantly affect UIC in scientific and technological innovation activities, and then affect the regional economic development and human capital. UIC S&T innovation activities play positive mediating roles in promoting regional sustainable development. In addition, the innovation climate does not significantly impact the business activities of UIC. Therefore, region can get a greater sustainable development through UIC S&T innovation activities than business activities. Much more UIC S&T activities can improve the economic development, human capital, and environmental conditions in the region.
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Heinemann, Günther. "Assessment of Regional Climate Model Simulations of the Katabatic Boundary Layer Structure over Greenland." Atmosphere 11, no. 6 (June 1, 2020): 571. http://dx.doi.org/10.3390/atmos11060571.
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The parameterization of the boundary layer is a challenge for regional climate models of the Arctic. In particular, the stable boundary layer (SBL) over Greenland, being the main driver for substantial katabatic winds over the slopes, is simulated differently by different regional climate models or using different parameterizations of the same model. However, verification data sets with high-resolution profiles of the katabatic wind are rare. In the present paper, detailed aircraft measurements of profiles in the katabatic wind and automatic weather station data during the experiment KABEG (Katabatic wind and boundary-layer front experiment around Greenland) in April and May 1997 are used for the verification of the regional climate model COSMO-CLM (CCLM) nested in ERA-Interim reanalyses. CCLM is used in a forecast mode for the whole Arctic with 15 km resolution and is run in the standard configuration of SBL parameterization and with modified SBL parameterization. In the modified version, turbulent kinetic energy (TKE) production and the transfer coefficients for turbulent fluxes in the SBL are reduced, leading to higher stability of the SBL. This leads to a more realistic representation of the daily temperature cycle and of the SBL structure in terms of temperature and wind profiles for the lowest 200 m.
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Amri, Khairul, and Fayakun Satria. "IMPACT OF CLIMATE ANOMALY ON CATCH COMPOSITION OF NERITIC TUNA IN SUNDA STRAIT." Indonesian Fisheries Research Journal 19, no. 2 (December 31, 2013): 61. http://dx.doi.org/10.15578/ifrj.19.2.2013.61-72.
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Tongkol komo/kawakawa (<em>Euthynnus affinis</em>) and tenggiri (<em>Scomberomerus guttatus</em>) are commonly caught by mini purseiners operated in Sunda Straits and landed in Labuan, West Java. This species inhabits coastal water and has preference staying in relatively warm water. Oceanography parameters commonly influencing the distribution of Euthynnus affinis are temperature, current, and salinity. The oceanography of Sunda Strait is influenced by water masses coming from the north that mainly originated from the Java Sea and water masses from the south mainly originated from Indian Ocean. The internal oceanography of Sunda Strait is also influenced by upwelling and monsoon as regional climate anomaly (ENSO and Indian Ocean Dipole Mode). This paper describes the influence of Dipole Mode (positive and negative event) and ENSO (El- Nino/La-Nina) to the catch dynamics of neritic tuna particularly in Sunda Straits waters. The results shown that regional climate anomaly influenced neritic tuna catch and its composition. The catches Euthynnus affinis in phase negative dipole mode or La-Nina were higher and dominated the catch composition of pelagic fishes of Sunda Strait. Similar situation also is showen by Scomberomorus commerson.
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Matsueda, M., A. Weisheimer, and T. N. Palmer. "Calibrating Climate Change Time-Slice Projections with Estimates of Seasonal Forecast Reliability." Journal of Climate 29, no. 10 (May 10, 2016): 3831–40. http://dx.doi.org/10.1175/jcli-d-15-0087.1.
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Abstract In earlier work, it was proposed that the reliability of climate change projections, particularly of regional rainfall, could be improved if such projections were calibrated using quantitative measures of reliability obtained by running the same model in seasonal forecast mode. This proposal is tested for fast atmospheric processes (such as clouds and convection) by considering output from versions of the same atmospheric general circulation model run at two different resolutions and forced with prescribed sea surface temperatures and sea ice. Here output from the high-resolution version of the model is treated as a proxy for truth. The reason for using this approach is simply that the twenty-first-century climate change signal is not yet known and, hence, no climate change projections can be verified using observations. Quantitative assessments of reliability of the low-resolution model, run in seasonal hindcast mode, are used to calibrate climate change time-slice projections made with the same low-resolution model. Results show that the calibrated climate change probabilities are closer to the proxy truth than the uncalibrated probabilities. Given that seasonal forecasts are performed operationally already at several centers around the world, in a seamless forecast system they provide a resource that can be used without cost to help calibrate climate change projections and make them more reliable for users.
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Coburn, Jacob, and Sara C. Pryor. "Evolution of the Internal Climate Modes under Future Warming." Journal of Climate 36, no. 2 (January 15, 2023): 511–29. http://dx.doi.org/10.1175/jcli-d-22-0200.1.
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Abstract Climate modes play an important role in weather and climate variability over multiple spatial and temporal scales. This research assesses Earth system model (ESM) projections of the spatiotemporal characteristics of key internal climate modes (NAM, SAM, PNA, ENSO, PDO, and AMO) under high (SSP585) and low (SSP126) radiative forcing scenarios and contextualizes those projections using historical fidelity. Time series analyses are used to assess trends and mode phase characteristics are summarized for the historical period and for the end of the twenty-first century. Spatial patterns are compared to infer morphological changes. Shifts in the power spectra are used to examine changes in variability at subannual, interannual, and interdecadal scales. Changes in time-lagged correlations are used to capture the evolution of first-order interactions. While differences in historical skill are predominantly ESM dependent, changing mode characteristics in a warmer climate also exhibit variability between individual ensemble realizations. NAM, SAM, and ENSO tend to evolve toward increased prevalence of the positive phase up to 2100 across the multimodel ensemble while the PNA and PDO exhibit little trend but increasing phase intensity. AMO characteristics are shown to depend on the method used to remove the external signal. ESMs that show higher historical fidelity tend to show more modest changes in those modes under global nonstationarity. Changes in mode interactions are found to be highly ESM dependent but exhibit broadly similar behavior to historical relationships. These findings have implications for our understanding of internal variability and make clear that the choice of ESM, and even the ESM realization, matters for applications of climate projections. Significance Statement Internal modes of variability are important to understand due to their impact on local, regional, and global weather and climate patterns. Future climate changes will not only be affected by the variability arising from these modes, but the modes will themselves change in response to the changing climate. Spatial and temporal aspects of the modes are assessed from projections of future climate and related to how well they are captured in the historical climate. This yields some measure of confidence in the changes exhibited by the models. In most cases, when historically skillful models exhibit changes that are different from those produced by less skillful models, they tend to produce more modest changes. These results, as well as the variability between model outcomes, mean decisions on which ESM to use for projections of the future climate matter significantly.
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Li, Gen, Shang-Ping Xie, and Yan Du. "Climate Model Errors over the South Indian Ocean Thermocline Dome and Their Effect on the Basin Mode of Interannual Variability*." Journal of Climate 28, no. 8 (April 7, 2015): 3093–98. http://dx.doi.org/10.1175/jcli-d-14-00810.1.
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Abstract An open-ocean thermocline dome south of the equator is a striking feature of the Indian Ocean (IO) as a result of equatorial westerly winds. Over the thermocline dome, the El Niño–forced Rossby waves help sustain the IO basin (IOB) mode and offer climate predictability for the IO and surrounding countries. This study shows that a common equatorial easterly wind bias, by forcing a westward-propagating downwelling Rossby wave in the southern IO, induces too deep a thermocline dome over the southwestern IO (SWIO) in state-of-the-art climate models. Such a deep SWIO thermocline weakens the influence of subsurface variability on sea surface temperature (SST), reducing the IOB amplitude and possibly limiting the models’ skill of regional climate prediction. To the extent that the equatorial easterly wind bias originates from errors of the South Asian summer monsoon, improving the monsoon simulation can lead to substantial improvements in simulating and predicting interannual variability in the IO.
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Trusilova, Kristina, Barbara Früh, Susanne Brienen, Andreas Walter, Valéry Masson, Grégoire Pigeon, and Paul Becker. "Implementation of an Urban Parameterization Scheme into the Regional Climate Model COSMO-CLM." Journal of Applied Meteorology and Climatology 52, no. 10 (October 2013): 2296–311. http://dx.doi.org/10.1175/jamc-d-12-0209.1.
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AbstractAs the nonhydrostatic regional model of the Consortium for Small-Scale Modelling in Climate Mode (COSMO-CLM) is increasingly employed for studying the effects of urbanization on the environment, the authors extend its surface-layer parameterization by the Town Energy Budget (TEB) parameterization using the “tile approach” for a single urban class. The new implementation COSMO-CLM+TEB is used for a 1-yr reanalysis-driven simulation over Europe at a spatial resolution of 0.11° (~12 km) and over the area of Berlin at a spatial resolution of 0.025° (~2.8 km) for evaluating the new coupled model. The results on the coarse spatial resolution of 0.11° show that the standard and the new models provide 2-m temperature and daily precipitation fields that differ only slightly by from −0.1 to +0.2 K per season and ±0.1 mm day−1, respectively, with very similar statistical distributions. This indicates only a negligibly small effect of the urban parameterization on the model's climatology. Therefore, it is suggested that an urban parameterization may be omitted in model simulations on this scale. On the spatial resolution of 0.025° the model COSMO-CLM+TEB is able to better represent the magnitude of the urban heat island in Berlin than the standard model COSMO-CLM. This finding shows the importance of using the parameterization for urban land in the model simulations on fine spatial scales. It is also suggested that models could benefit from resolving multiple urban land use classes to better simulate the spatial variability of urban temperatures for large metropolitan areas on spatial scales below ~3 km.
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Hasler, N., R. Avissar, and G. E. Liston. "Issues in Simulating the Annual Precipitation of a Semiarid Region in Central Spain." Journal of Hydrometeorology 6, no. 4 (August 1, 2005): 409–22. http://dx.doi.org/10.1175/jhm418.1.
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Abstract Running regional climate models at a high resolution may improve their ability to simulate regional precipitation patterns, making them suitable for studying the impact of human-induced land-cover changes on hydrometeorology. The performance of the Regional Atmospheric Modeling System (RAMS) run in the high-resolution climate mode (4-km grid mesh) has been tested over a small domain in a semiarid region in central Spain. Three 1-yr simulations representing dry, intermediate, and wet conditions were compared to observations collected in 35 rain gauges. The model captured general spatiotemporal features of precipitation, such as the timing of precipitation events and approximate location of storms. A high correlation (0.82) between monthly domain-averaged observed and modeled precipitation was obtained. However, the model had a systematic dry bias, averaging −0.29 mm day−1, equivalent to 26% of annual rainfall. The small domain size, chosen because of computational limits, induced strong lateral boundary forcing, which, combined with uncertainty in NCEP relative humidity fields, was a likely cause for this dry bias.
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Sloyan, Bernadette M., and Igor V. Kamenkovich. "Simulation of Subantarctic Mode and Antarctic Intermediate Waters in Climate Models." Journal of Climate 20, no. 20 (October 15, 2007): 5061–80. http://dx.doi.org/10.1175/jcli4295.1.
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Abstract The Southern Ocean’s Subantarctic Mode Water (SAMW) and Antarctic Intermediate Water (AAIW) are two globally significant upper-ocean water masses that circulate in all Southern Hemisphere subtropical gyres and cross the equator to enter the North Pacific and North Atlantic Oceans. Simulations of SAMW and AAIW for the twentieth century in eight climate models [GFDL-CM2.1, CCSM3, CNRM-CM3, MIROC3.2(medres), MIROC3.2(hires), MRI-CGCM2.3.2, CSIRO-Mk3.0, and UKMO-HadCM3] that provided their output in support of the Intergovernmental Panel on Climate Change’s Fourth Assessment Report (IPCC AR4) have been compared to the Commonwealth Scientific and Industrial Research Organisation (CSIRO) Atlas of Regional Seas. The climate models, except for UKMO-HadCM3, CSIRO-Mk3.0, and MRI-CGCM2.3.2, provide a reasonable simulation of SAMW and AAIW isopycnal temperature and salinity in the Southern Ocean. Many models simulate the potential vorticity minimum layer and salinity minimum layer of SAMW and AAIW, respectively. However, the simulated SAMW layer is generally thinner and at lighter densities than observed. All climate models display a limited equatorward extension of SAMW and AAIW north of the Antarctic Circumpolar Current. Errors in the simulation of SAMW and AAIW property characteristics are likely to be due to a combination of many errors in the climate models, including simulation of wind and buoyancy forcing, inadequate representation of subgrid-scale mixing processes in the Southern Ocean, and midlatitude diapycnal mixing parameterizations.
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Sun, Dongyong, Hongbo Zhang, and Zhihui Guo. "Complexity Analysis of Precipitation and Runoff Series Based on Approximate Entropy and Extreme-Point Symmetric Mode Decomposition." Water 10, no. 10 (October 4, 2018): 1388. http://dx.doi.org/10.3390/w10101388.
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Many regional hydrological regime changes are complex under the influences of climate change and human activities, which make it difficult to understand the regional or basin al hydrological status. To investigate the complexity of precipitation and the runoff time series from 1960 to 2012 in the Jing River Basin on different time scales, approximate entropy, a Bayesian approach and extreme-point symmetric mode decomposition were employed. The results show that the complexity of annual precipitation and runoff has decreased since the 1990sand that the change occurred in 1995. The Intrinsic Mode Function (IMF)-6 component decomposed by extreme-point symmetric mode decomposition of monthly precipitation and runoff was consistent with precipitation and runoff. The IMF-6 component of monthly precipitation closely followed the 10-year cycle of change, and it has an obvious correlation with sunspots. The correlation coefficient is 0.6, representing a positive correlation before 1995 and a negative correlation after 1995. However, the IMF-6 component of monthly runoff does not have a significant correlation with sunspots, and the correlation coefficient is only 0.41, which indicates that climate change is not the dominant factor of runoff change. Approximate entropy is an effective analytical method for complexity, and furthermore, it can be decomposed by extreme-point symmetric mode decomposition to obtain the physical process of the sequences at different time scales, which helps us to understand the background of climate change and human activity in the process of precipitation and runoff.
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Tarasyuk, Nina, and Mаryana Hanushchak. "Mode of atmospheric connection of soil Volynes in the modern climate condition." Visnyk of the Lviv University. Series Geography, no. 51 (December 27, 2017): 322–30. http://dx.doi.org/10.30970/vgg.2017.51.8894.
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The article a nalyzes in detail the dynamics of atmospheric precipitation for the entire instrumental period of observations in the territory of the Volyn region at six meteorological stations. The deviation in the parameters of the amount of precipitation in the long-term regime and the climate norm are revealed. For the entire period of observations in the region, the annual amount of precipitation is characterized by significant fluctuations. The highest precipitation was recorded in 2008 (779 mm), the smallest – in 1961 (319 mm). The differences of atmospheric moisture in recent years have been analyzed. It is established that under the conditions of hemodern climates ince the mid-80s of the twentieth century the rehas been a steady in crease in the annual amount of precipitation throughout the Volyn region, which leads to a change in the environmental environment of the formation of the water regime of soils of different granulometric composition. Atmospheric precipitation is a source of replenish men to moisture in the soil, causing water availability of plants. The amount of atmospheric precipitation and the mode of their fallout are of ten the cause of unfavourable conditions in crop production, horticulture, and forestry. Conditions of atmospheric humidification in the vegetation period are characterized. The changes in the amount of precipitation during the growing season in different time slices are analyzed based on the data of instrumental observations and published data of the late 50 of the last century and the beginning of the 21 century in the Agro-climatic reference books. Hydrothermal coefficient of Selyaninov is calculated and its spatial and temporal differences are established. For the first time, the manifestation of climatic changes in the study area and the regional features of the dynamics of atmospheric humidification are shown. The increase in the annual amount of precipitation and its distribution in the warm period of the year in creases the risks of intensifying soil degradation, and therefore the research can be widely used in the study of changes inwater regime and the determination of moisture sources in the soils of the Volyn region. There sultsof the study will be useful for the practice of plant growing and horti culture in agriculture, as well as for forestry, protected areas, which are the canters for the conservation of Polissya biodiversity. Key words: precipitation, long-term dynamics, global and regional climate changes, vegetation period, hydrothermal coefficient of Selyaninov, dry period duration.
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Udy, Danielle G., Tessa R. Vance, Anthony S. Kiem, Neil J. Holbrook, and Mark A. J. Curran. "Links between Large-Scale Modes of Climate Variability and Synoptic Weather Patterns in the Southern Indian Ocean." Journal of Climate 34, no. 3 (February 2021): 883–99. http://dx.doi.org/10.1175/jcli-d-20-0297.1.
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AbstractWeather systems in the southern Indian Ocean (SIO) drive synoptic-scale precipitation variability in East Antarctica and southern Australia. Improved understanding of these dynamical linkages is beneficial to diagnose long-term climate changes from climate proxy records as well as informing regional weather and climate forecasts. Self-organizing maps (SOMs) are used to group daily 500-hPa geopotential height (z500; ERA-Interim) anomalies into nine regional synoptic types based on their dominant patterns over the SIO (30°–75°S, 40°–180°E) from January 1979 to October 2018. The pattern anomalies represented include four meridional, three mixed meridional–zonal, one zonal, and one transitional node. The frequency of the meridional nodes shows limited association with the phase of the southern annular mode (SAM), especially during September–November. The zonal and mixed patterns were nevertheless strongly and significantly correlated with SAM, although the regional synoptic representation of SAM+ conditions was not zonally symmetric and was represented by three separate nodes. We recommend consideration of how different synoptic conditions vary the atmospheric representation of SAM+ in any given season in the SIO. These different types of SAM+ mean a hemispheric index fails to capture the regional variability in surface weather conditions that is primarily driven by the synoptic variability rather than the absolute polarity of the SAM.
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Chin, Kah Seng, and Kok Weng Tan. "Evaluation of SRE Scenarios for Penang, Selangor and Johor in Peninsular Malaysia using PRECIS Regional Climate Model (RCM)." E3S Web of Conferences 65 (2018): 05020. http://dx.doi.org/10.1051/e3sconf/20186505020.
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Climate change is unambiguous as there is much evidence from around the world showing that changes have already occurred. This phenomenon is in response to an array of human activities, notably the release of greenhouse gases; an understanding of the rate, mode and scale of this change is now of literally vital importance to society. Researchers utilize climate models to study the dynamics of our changing climate and also to make future projections. Climate models are basic representation of many interactions within the Earth’s climate which includes the atmosphere, land surface, oceans and ice. These models are typically quantitative in nature and range from simple depictions of the climate to very complex ones. In this present study, downscaled PRECIS regional climate models (RCMs) were used to project the average minimum and average maximum temperatures and average precipitation for Penang, Selangor and Johor in Peninsular Malaysia. The RCM projections for these three states were developed based on ECHAM4 A2 and ECHAM5 A1B scenarios for the years 1980 to 2069 and ECHAM4 B2 scenario for the years 2010 to 2069. Bias correction will be applied to the simulated historical data to remove common systematic model errors. Historical observation data of monthly average minimum and maximum temperatures and monthly average rainfall from the Malaysian Meteorological Department (MMD) will be used in the bias correction. Finally, a RCM scenario which matches with the historical observation data of the three states for future projections will be recommended.
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Holz, Andrés, Juan Paritsis, Ignacio A. Mundo, Thomas T. Veblen, Thomas Kitzberger, Grant J. Williamson, Ezequiel Aráoz, et al. "Southern Annular Mode drives multicentury wildfire activity in southern South America." Proceedings of the National Academy of Sciences 114, no. 36 (August 21, 2017): 9552–57. http://dx.doi.org/10.1073/pnas.1705168114.
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The Southern Annular Mode (SAM) is the main driver of climate variability at mid to high latitudes in the Southern Hemisphere, affecting wildfire activity, which in turn pollutes the air and contributes to human health problems and mortality, and potentially provides strong feedback to the climate system through emissions and land cover changes. Here we report the largest Southern Hemisphere network of annually resolved tree ring fire histories, consisting of 1,767 fire-scarred trees from 97 sites (from 22 °S to 54 °S) in southern South America (SAS), to quantify the coupling of SAM and regional wildfire variability using recently created multicentury proxy indices of SAM for the years 1531–2010 AD. We show that at interannual time scales, as well as at multidecadal time scales across 37–54 °S, latitudinal gradient elevated wildfire activity is synchronous with positive phases of the SAM over the years 1665–1995. Positive phases of the SAM are associated primarily with warm conditions in these biomass-rich forests, in which widespread fire activity depends on fuel desiccation. Climate modeling studies indicate that greenhouse gases will force SAM into its positive phase even if stratospheric ozone returns to normal levels, so that climate conditions conducive to widespread fire activity in SAS will continue throughout the 21st century.
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Liess, Stefan, Arjun Kumar, Peter K. Snyder, Jaya Kawale, Karsten Steinhaeuser, Frederick H. M. Semazzi, Auroop R. Ganguly, Nagiza F. Samatova, and Vipin Kumar. "Different Modes of Variability over the Tasman Sea: Implications for Regional Climate*." Journal of Climate 27, no. 22 (November 4, 2014): 8466–86. http://dx.doi.org/10.1175/jcli-d-13-00713.1.
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Abstract A new approach is used to detect atmospheric teleconnections without being bound by orthogonality (such as empirical orthogonal functions). This method employs negative correlations in a global dataset to detect potential teleconnections. One teleconnection occurs between the Tasman Sea and the Southern Ocean. It is related to El Niño–Southern Oscillation (ENSO), the Indian Ocean dipole (IOD), and the southern annular mode (SAM). This teleconnection is significantly correlated with SAM during austral summer, fall, and winter, with IOD during spring, and with ENSO in summer. It can thus be described as a hybrid between these modes. Given previously found relationships between IOD and ENSO, and IOD’s proximity to the teleconnection centers, correlations to IOD are generally stronger than to ENSO. Increasing pressure over the Tasman Sea leads to higher (lower) surface temperature over eastern Australia (the southwestern Pacific) in all seasons and is related to reduced surface temperature over Wilkes Land and Adélie Land in Antarctica during fall and winter. Precipitation responses are generally negative over New Zealand. For one standard deviation of the teleconnection index, precipitation anomalies are positive over Australia in fall, negative over southern Australia in winter and spring, and negative over eastern Australia in summer. When doubling the threshold, the size of the anomalous high-pressure center increases and annual precipitation anomalies are negative over southeastern Australia and northern New Zealand. Eliassen–Palm fluxes quantify the seasonal dependence of SAM, ENSO, and IOD influences. Analysis of the dynamical interactions between these teleconnection patterns can improve prediction of seasonal temperature and precipitation patterns in Australia and New Zealand.
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Thomalla, S. J., N. Fauchereau, S. Swart, and P. M. S. Monteiro. "Regional scale characteristics of the seasonal cycle of chlorophyll in the Southern Ocean." Biogeosciences Discussions 8, no. 3 (May 13, 2011): 4763–804. http://dx.doi.org/10.5194/bgd-8-4763-2011.
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Abstract. The seasonal cycle is the mode that couples climate forcing to ecosystem production. A better understanding of the regional characteristics of the seasonal cycle addresses an important gap in our understanding of the sensitivity of the biological pump to climate change. The regional characteristics of the seasonal cycle of phytoplankton biomass in the Southern Ocean were examined in terms of the timing of the bloom initiation, its amplitude, regional scale variability and the importance of the climatological seasonal cycle in explaining the overall variance. The study highlighted important differences between the spatial distribution of satellite observed phytoplankton biomass and the more dynamically linked characteristics of the seasonal cycle. The seasonal cycle was consequently defined into four broad zonal regions; the subtropical zone (STZ), the transition zone (TZ), the Antarctic circumpolar zone (ACZ) and the marginal ice zone (MIZ). Defining the Southern Ocean according to the characteristics of its seasonal cycle provides a more dynamic understanding of ocean productivity based on underlying physical drivers rather than climatological biomass. The response of the biology to the underlying physics of the different seasonal zones resulted in an additional classification of four regions based on the extent of interannual seasonal phase locking and the amplitude of the integrated seasonal biomass. This characterisation contributes to an improved understanding of regional sensitivity to climate forcing potentially allowing more robust predictions of long term climate trends.