scholarly journals Summer Land–Atmosphere Coupling Strength over the United States: Results from the Regional Climate Model RegCM4–CLM3.5

2013 ◽  
Vol 14 (3) ◽  
pp. 946-962 ◽  
Author(s):  
Rui Mei ◽  
Guiling Wang ◽  
Huanghe Gu
Keyword(s):  
United States ◽  
Soil Moisture ◽  
Regional Climate Model ◽  
Coupling Strength ◽  
Time Scale ◽  
Climate Model ◽  
Regional Climate ◽  
The United States ◽  
Regional Model ◽  
Forecast Skill

Abstract This study investigates the land–atmosphere coupling strength during summer over the United States using the Regional Climate Model version 4 (RegCM4)–Community Land Model version 3.5 (CLM3.5). First, a 10-yr simulation driven with reanalysis lateral boundary conditions (LBCs) is conducted to evaluate the model performance. The model is then used to quantify the land–atmosphere coupling strength, predictability, and added forecast skill (for precipitation and 2-m air temperature) attributed to realistic land surface initialization following the Global Land–Atmosphere Coupling Experiment (GLACE) approaches. Similar to previous GLACE results using global climate models (GCMs), GLACE-type experiments with RegCM4 identify the central United States as a region of strong land–atmosphere coupling, with soil moisture–temperature coupling being stronger than soil moisture–precipitation coupling, and confirm that realistic soil moisture initialization is more promising in improving temperature forecasts than precipitation forecasts. At a 1–15-day lead, the added forecast skill reflects predictability (or land–atmosphere coupling strength) indicating that that model can capture the realistic land–atmosphere coupling at a short time scale. However, at a 16–30-day lead, predictability cannot translate to added forecast skill, implying that the coupling at the longer time scale may not be represented well in the model. In addition, comparison of results from GLACE2-type experiments with RegCM4 driven by reanalysis LBCs and those driven by GCM LBCs suggest that the intrinsic land–atmosphere coupling strength within the regional model is the dominant factor for the added forecast skill at a 1–15-day lead, while the impact of LBCs from the GCM may play a dominant role in determining the signal of added forecast skill in the regional model at a 16–30-day lead. It demonstrates the complexities of using regional climate model for GLACE-type studies.

Estimations of Hazardous Convective Weather in the United States Using Dynamical Downscaling

2014 ◽  
Vol 27 (17) ◽  
pp. 6581-6589 ◽  
Author(s):  
Vittorio A. Gensini ◽  
Thomas L. Mote
Keyword(s):  
United States ◽  
High Resolution ◽  
Climate Model ◽  
Dynamical Downscaling ◽  
Global Climate Model ◽  
Regional Climate ◽  
The United States ◽  
Regional Model ◽  
Severe Weather ◽  
Convective Weather

Abstract High-resolution (4 km; hourly) regional climate modeling is utilized to resolve March–May hazardous convective weather east of the U.S. Continental Divide for a historical climate period (1980–90). A hazardous convective weather model proxy is used to depict occurrences of tornadoes, damaging thunderstorm wind gusts, and large hail at hourly intervals during the period of record. Through dynamical downscaling, the regional climate model does an admirable job of replicating the seasonal spatial shifts of hazardous convective weather occurrence during the months examined. Additionally, the interannual variability and diurnal progression of observed severe weather reports closely mimic cycles produced by the regional model. While this methodology has been tested in previous research, this is the first study to use coarse-resolution global climate model data to force a high-resolution regional model with continuous seasonal integration in the United States for purposes of resolving severe convection. Overall, it is recommended that dynamical downscaling play an integral role in measuring climatological distributions of severe weather, both in historical and future climates.

Sensitivities of isoprene emissions to soil moisture and impacts on surface ozone levels as simulated over the Euro-Mediterranean region by the regional climate model RegCM4.7chem-CLM4.5-MEGAN2.1

2021 ◽  
Author(s):  
Susanna Strada ◽  
Andrea Pozzer ◽  
Graziano Giuliani ◽  
Erika Coppola ◽  
Fabien Solmon ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Water Stress ◽  
Regional Climate Model ◽  
Mediterranean Region ◽  
Control Experiment ◽  
Climate Model ◽  
Surface Ozone ◽  
Regional Climate ◽  
Activity Factor ◽  
Ozone Levels

<p>In response to changes in environmental conditions (e.g., temperature, radiation, soil moisture), plants emit biogenic volatile organic compounds (BVOCs). In the large family of BVOCs, isoprene dominates and plays an important role in atmospheric chemistry. Once released in the atmosphere, isoprene influences levels of ozone, thus affecting both climate and air quality. In turn, climate change may alter isoprene emissions by increasing the occurrence and intensity of severe thermal and water stresses that alter plant functioning. To better constrain the evolution of isoprene emissions under future climates, it is critical to reduce the uncertainties in global and regional estimates of isoprene under present climate. Part of these uncertainties is related to the impact of water stress on isoprene. Recently, the BVOC emission model MEGAN has adopted a more sophisticated soil moisture activity factor γ<sub>sm</sub> which does not only account, as previously, for soil moisture available to plants but also links isoprene emissions to photosynthesis and plant water stress.</p><p>To assess the effects of soil moisture on isoprene emissions and, lastly, on ozone levels in the Euro-Mediterranean region, we use the regional climate model RegCM4.7, coupled to the land surface model CLM4.5, MEGAN2.1 and a chemistry module (RegCM4.7chem-CLM4.5-MEGAN2.1). We have performed a control experiment over 1987-2016 (with a 5-yr spin-up) at a horizontal resolution of 0.22°. Model output from the control experiment is used to initialize RegCM4.7chem-CLM4.5-MEGAN2.1 for the 10 most dry/wet summers (May-August) selected referring to the 1970-2016 precipitation climatology. Each May-August experiment is run with the old and with the new MEGAN soil moisture activity factor γ<sub>sm</sub>.  The results are then compared with a simulation whit no soil moisture activity factor. Both activity factors γ<sub>sm</sub> reduce isoprene emissions under water deficit.</p><p>During dry summers, the old soil moisture activity factor reduces isoprene emissions homogeneously over the model domain by nearly 100%, while ozone levels decrease by around 10%. When the new γ<sub>sm </sub>is used,<sub></sub>isoprene emissions are reduced with a patchy pattern by 10-20%, while ground-surface ozone levels diminish homogeneously by few percent over the southern part of the model domain.</p>

scholarly journals Regional Climate Model Evaluation System powered by Apache Open Climate Workbench v1.3.0: an enabling tool for facilitating regional climate studies

2018 ◽  
Author(s):  
Huikyo Lee ◽  
Alexander Goodman ◽  
Lewis McGibbney ◽  
Duane Waliser ◽  
Jinwon Kim ◽  
...  
Keyword(s):  
Regional Climate Model ◽  
Model Evaluation ◽  
Evaluation System ◽  
Climate Models ◽  
Performance Metrics ◽  
Climate Model ◽  
Regional Climate ◽  
The United States ◽  
Climate Data ◽  
Climate Model Evaluation

Abstract. The Regional Climate Model Evaluation System (RCMES) is an enabling tool of the National Aeronautics and Space Administration to support the United States National Climate Assessment. As a comprehensive system for evaluating climate models on regional and continental scales using observational datasets from a variety of sources, RCMES is designed to yield information on the performance of climate models and guide their improvement. Here we present a user-oriented document describing the latest version of RCMES, its development process and future plans for improvements. The main objective of RCMES is to facilitate the climate model evaluation process at regional scales. RCMES provides a framework for performing systematic evaluations of climate simulations, such as those from the Coordinated Regional Climate Downscaling Experiment (CORDEX), using in-situ observations as well as satellite and reanalysis data products. The main components of RCMES are: 1) a database of observations widely used for climate model evaluation, 2) various data loaders to import climate models and observations in different formats, 3) a versatile processor to subset and regrid the loaded datasets, 4) performance metrics designed to assess and quantify model skill, 5) plotting routines to visualize the performance metrics, 6) a toolkit for statistically downscaling climate model simulations, and 7) two installation packages to maximize convenience of users without Python skills. RCMES website is maintained up to date with brief explanation of these components. Although there are other open-source software (OSS) toolkits that facilitate analysis and evaluation of climate models, there is a need for climate scientists to participate in the development and customization of OSS to study regional climate change. To establish infrastructure and to ensure software sustainability, development of RCMES is an open, publicly accessible process enabled by leveraging the Apache Software Foundation's OSS library, Apache Open Climate Workbench (OCW). The OCW software that powers RCMES includes a Python OSS library for common climate model evaluation tasks as well as a set of user-friendly interfaces for quickly configuring a model evaluation task. OCW also allows users to build their own climate data analysis tools, such as the statistical downscaling toolkit provided as a part of RCMES.

scholarly journals Diagnosing Land–Atmosphere Interaction from a Regional Climate Model Simulation over West Africa

2010 ◽  
Vol 11 (2) ◽  
pp. 467-481 ◽  
Author(s):  
Bart J. J. M. van den Hurk ◽  
Erik van Meijgaard
Keyword(s):  
Soil Moisture ◽  
Regional Climate Model ◽  
Climate Model ◽  
Hydrological Cycle ◽  
Regional Climate ◽  
West African ◽  
The West ◽  
Near Surface ◽  
Monsoon Area ◽  
Atmosphere Interaction

Abstract Land–atmosphere interaction at climatological time scales in a large area that includes the West African Sahel has been explicitly explored in a regional climate model (RegCM) simulation using a range of diagnostics. First, areas and seasons of strong land–atmosphere interaction were diagnosed from the requirement of a combined significant correlation between soil moisture, evaporation, and the recycling ratio. The northern edge of the West African monsoon area during June–August (JJA) and an area just north of the equator (Central African Republic) during March–May (MAM) were identified. Further analysis in these regions focused on the seasonal cycle of the lifting condensation level (LCL) and the convective triggering potential (CTP), and the sensitivity of CTP and near-surface dewpoint depressions HIlow to anomalous soil moisture. From these analyses, it is apparent that atmospheric mechanisms impose a strong constraint on the effect of soil moisture on the regional hydrological cycle.

scholarly journals Regional climate model experiments to investigate the Asian monsoon in the Late Miocene

2011 ◽  
Vol 7 (3) ◽  
pp. 847-868 ◽  
Author(s):  
H. Tang ◽  
A. Micheels ◽  
J. Eronen ◽  
M. Fortelius
Keyword(s):  
Tibetan Plateau ◽  
Regional Climate Model ◽  
Late Miocene ◽  
Asian Monsoon ◽  
Climate Model ◽  
Regional Climate ◽  
Northern China ◽  
Regional Model ◽  
Monsoon Climate ◽  
Northern Tibetan Plateau

Abstract. The Late Miocene (11.6–5.3 Ma) is a crucial period in the history of the Asian monsoon. Significant changes in the Asian climate regime have been documented for this period, which saw the formation of the modern Asian monsoon system. However, the spatiotemporal structure of these changes is still ambiguous, and the associated mechanisms are debated. Here, we present a simulation of the average state of the Asian monsoon climate for the Tortonian (11–7 Ma) using the regional climate model CCLM3.2. We employ relatively high spatial resolution (1° × 1°) and adapt the physical boundary conditions such as topography, land-sea distribution and vegetation in the regional model to represent the Late Miocene. As climatological forcing, the output of a Tortonian run with a fully-coupled atmosphere-ocean general circulation model is used. Our regional Tortonian run shows a stronger-than-present East Asian winter monsoon wind as a result of the enhanced mid-latitude westerly wind of our global forcing and the lowered present-day northern Tibetan Plateau in the regional model. The summer monsoon circulation is generally weakened in our regional Tortonian run compared to today. However, the changes of summer monsoon precipitation exhibit major regional differences. Precipitation decreases in northern China and northern India, but increases in southern China, the western coast and the southern tip of India. This can be attributed to the changes in both the regional topography (e.g. the lower northern Tibetan Plateau) and the global climate conditions (e.g. the higher sea surface temperature). The spread of dry summer conditions over northern China and northern Pakistan in our Tortonian run further implies that the monsoonal climate may not have been fully established in these regions in the Tortonian. Compared with the global model, the high resolution regional model highlights the spatial differences of the Asian monsoon climate in the Tortonian, and better characterizes the convective activity and its response to regional topographical changes. It therefore provides a useful and compared to global models, a complementary tool to improve our understanding of the Asian monsoon evolution in the Late Miocene.

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