scholarly journals Explicit Convection and Scale-Aware Cumulus Parameterizations: High-Resolution Simulations over Areas of Different Topography in Germany

2018 ◽  
Vol 146 (6) ◽  
pp. 1925-1944 ◽  
Author(s):  
Andreas Wagner ◽  
Dominikus Heinzeller ◽  
Sven Wagner ◽  
Thomas Rummler ◽  
Harald Kunstmann
Keyword(s):  
High Resolution ◽  
Land Surface ◽  
Climate Model ◽  
Regional Climate ◽  
Surface Characteristics ◽  
Radar Data ◽  
Explicit Calculation ◽  
Climate Model Simulations ◽  
Convection Parameterization ◽  
The Impact

An increase in the spatial resolution of regional climate model simulations improves the representation of land surface characteristics and may allow the explicit calculation of important physical processes such as convection. The present study investigates further potential benefits with respect to precipitation, based on a small ensemble of high-resolution simulations with WRF with grid spacings up to 1 km. The skill of each experiment is evaluated regarding the temporal and spatial performance of the simulation of precipitation of one year over both a mountainous region in southwestern Germany and a mainly flat region in northern Germany. This study allows us to differentiate between the impact of grid spacing, topography, and convection parameterization. Furthermore, the performance of a state-of-the-art convection parameterization scheme in the gray zone of convection is evaluated against an explicit calculation of convection only. Our evaluation demonstrates the following: high-resolution simulations (5 and 1 km) are generally able to represent the diurnal cycle, structure, and intensity distribution of precipitation, when compared to observational datasets such as radar data and interpolated station data. The influence of the improved representation of the topography at higher resolution (1 km) becomes apparent in complex terrain, where the localization of precipitation maxima is more accurate, although these maxima are overestimated. In flat areas, differences in spatial evaluations arise between simulations with parameterized and explicitly calculated convection, whereas smaller grid spacings (1 km vs 5 km) show hardly any impact on precipitation results.

scholarly journals Land surface albedo and vegetation feedbacks enhanced the millennium drought in south-east Australia

2017 ◽  
Vol 21 (1) ◽  
pp. 409-422 ◽  
Author(s):  
Jason P. Evans ◽  
Xianhong Meng ◽  
Matthew F. McCabe
Keyword(s):  
Land Surface ◽  
Climate Model ◽  
Southern Oscillation ◽  
Regional Climate ◽  
Surface Characteristics ◽  
Surface Precipitation ◽  
Vegetation Fraction ◽  
Vegetation Feedbacks ◽  
Millennium Drought ◽  
Precipitation Anomalies

Abstract. In this study, we have examined the ability of a regional climate model (RCM) to simulate the extended drought that occurred throughout the period of 2002 through 2007 in south-east Australia. In particular, the ability to reproduce the two drought peaks in 2002 and 2006 was investigated. Overall, the RCM was found to reproduce both the temporal and the spatial structure of the drought-related precipitation anomalies quite well, despite using climatological seasonal surface characteristics such as vegetation fraction and albedo. This result concurs with previous studies that found that about two-thirds of the precipitation decline can be attributed to the El Niño–Southern Oscillation (ENSO). Simulation experiments that allowed the vegetation fraction and albedo to vary as observed illustrated that the intensity of the drought was underestimated by about 10 % when using climatological surface characteristics. These results suggest that in terms of drought development, capturing the feedbacks related to vegetation and albedo changes may be as important as capturing the soil moisture–precipitation feedback. In order to improve our modelling of multi-year droughts, the challenge is to capture all these related surface changes simultaneously, and provide a comprehensive description of land surface–precipitation feedback during the droughts development.

Projected climate change over Kuwait simulated using a WRF high resolution regional climate model

2020 ◽  
Author(s):  
Hussain Alsarraf
Keyword(s):  
Climate Change ◽  
High Resolution ◽  
Regional Climate Model ◽  
Arabian Peninsula ◽  
Climate Model ◽  
Regional Climate ◽  
Dynamic Downscaling ◽  
Model Simulations ◽  
Average Maximum ◽  
The Impact

<p>The purpose of this study is to examine the impact of climate change on the changes on summer surface temperatures between present (2000-2010) and future (2050-2060) over the Arabian Peninsula and Kuwait. In this study, the influence of climate change in the Arabian Peninsula and especially in Kuwait was investigated by high resolution (36, 12, and 4 km grid spacing) dynamic downscaling from the Community Climate System Model CCSM4 using the WRF Weather Research and Forecasting model. The downscaling results were first validated by comparing National Centers for Environmental Prediction NCEP model outputs with the observational data. The global climate change dynamic downscaling model was run using WRF regional climate model simulations (2000-2010) and future projections (2050-2060). The influence of climate change in the Arabian Peninsula can be projected from the differences between the two period’s model simulations. The regional model simulations of the average maximum surface temperature in summertime predicted an increase from 1◦C to 3 ◦C over the summertime in Kuwait by midcentury.</p><p><strong> </strong></p>

High resolution regional climate model simulations for Germany: part I—validation

2012 ◽  
Vol 40 (1-2) ◽  
pp. 401-414 ◽  
Author(s):  
Peter Berg ◽  
Sven Wagner ◽  
Harald Kunstmann ◽  
Gerd Schädler
Keyword(s):  
High Resolution ◽  
Regional Climate Model ◽  
Climate Model ◽  
Regional Climate ◽  
Model Simulations ◽  
Climate Model Simulations

scholarly journals Numerical Study of the Interaction between Oasis and Urban Areas within an Arid Mountains-Desert System in Xinjiang, China

Atmosphere ◽  
2020 ◽  
Vol 11 (1) ◽  
pp. 85
Author(s):  
Peng Cai ◽  
Rafiq Hamdi ◽  
Huili He ◽  
Geping Luo ◽  
Jin Wang ◽  
...  
Keyword(s):  
Land Surface ◽  
Urban Areas ◽  
Climate Model ◽  
Numerical Study ◽  
Urban Expansion ◽  
Regional Climate ◽  
Maximum Effect ◽  
Local Circulation ◽  
Urban Rural ◽  
The Impact

The rapid oasis expansion and urbanization that occurred in Xinjiang province (China) in the last decades have greatly modified the land surface energy balance and influenced the local circulation under the arid mountains-plain background system. In this study, we first evaluated the ALARO regional climate model coupled to the land surface scheme SURFEX at 4 km resolution using 53 national climatological stations and 5 automatic weather stations. We found that the model correctly simulates daily and hourly variation of 2 m temperature and relative humidity. A 4-day clear sky period has been chosen to study both local atmospheric circulations and their mutual interaction. Observations and simulations both show that a low-level divergence over oasis appears between 19:00 and 21:00 Beijing Time when the background mountain-plain wind system is weak. The model simulates a synergistic interaction between the oasis-desert breeze and urban-rural breeze from 16:00 until 22:00 with a maximum effect at 20:00 when the downdraft over oasis (updraft over urban) areas increases by 0.8 (0.4) Pa/s. The results show that the oasis expansion decreases the nocturnal urban heat island in the city of Urumqi by 0.8 °C, while the impact of urban expansion on the oasis cold island is negligible.

scholarly journals An observation-constrained multi-physics WRF ensemble for simulating European mega heat waves

2015 ◽  
Vol 8 (7) ◽  
pp. 2285-2298 ◽  
Author(s):  
A. I. Stegehuis ◽  
R. Vautard ◽  
P. Ciais ◽  
A. J. Teuling ◽  
D. G. Miralles ◽  
...  
Keyword(s):  
Heat Wave ◽  
Land Surface ◽  
Western Europe ◽  
Climate Models ◽  
Climate Model ◽  
Heat Waves ◽  
Regional Climate ◽  
Shortwave Radiation ◽  
Cold Bias ◽  
The Impact

Abstract. Many climate models have difficulties in properly reproducing climate extremes, such as heat wave conditions. Here we use the Weather Research and Forecasting (WRF) regional climate model with a large combination of different atmospheric physics schemes, in combination with the NOAH land-surface scheme, with the goal of detecting the most sensitive physics and identifying those that appear most suitable for simulating the heat wave events of 2003 in western Europe and 2010 in Russia. In total, 55 out of 216 simulations combining different atmospheric physical schemes have a temperature bias smaller than 1 °C during the heat wave episodes, the majority of simulations showing a cold bias of on average 2–3 °C. Conversely, precipitation is mostly overestimated prior to heat waves, and shortwave radiation is slightly overestimated. Convection is found to be the most sensitive atmospheric physical process impacting simulated heat wave temperature across four different convection schemes in the simulation ensemble. Based on these comparisons, we design a reduced ensemble of five well performing and diverse scheme configurations, which may be used in the future to perform heat wave analysis and to investigate the impact of climate change during summer in Europe.

Impact of regional climate model input and soil map resolution on projected winter wheat production in SW Germany

2020 ◽  
Author(s):  
Sebastian Gayler ◽  
Rajina Bajracharya ◽  
Tobias Weber ◽  
Thilo Streck
Keyword(s):  
High Resolution ◽  
Climate Model ◽  
Regional Climate ◽  
Regional Scale ◽  
Grid Cell ◽  
Small Scale ◽  
Climate Projections ◽  
Soil Map ◽  
Soil Information ◽  
The Impact

<p>Agricultural ecosystem models, driven by climate projections and fed with soil information and plausible management scenarios are frequently used tools to predict future developments in agricultural landscapes. On the regional scale, the required soil parameters must be derived from soil maps that are available in different spatial resolutions, ranging from grid cell sizes of 50 m up to 1 km and more. The typical spatial resolution of regional climate projections is currently around 12 km. Given the small-scale heterogeneity in soil properties, using the most accurate soil representation could be important for predictions of crop growth. However, simulations with very highly resolved soil data requires greater computing time and higher effort for data organization and storage. Moreover, the higher resolution may not necessarily lead to better simulations due to redundant information of the land surface and because the impact of climate forcing could dominate over the effect of soil variability. This leads to the question if the use of high-resolution soil data leads to significantly different predictions of future yields and grain protein trends compared to simulations in which soil data is adapted to the resolution of the climate input.</p><p>This study investigated the impact of weather and soil input on simulated crop growth in an intensively used agricultural region in Southwest Germany. For all areas classified as ‘arable land’ (CLC10), winter wheat growth was simulated over a 44-year period (2006 to 2050) using weather projections from three regional climate models and soil information at two spatial resolutions. The simulations were performed with the model system Expert-N 5.0, where the crop model Gecros was combined with the Richards equation and the CN turnover module of the model Daisy. Soil hydraulic parameters as well as initial values of soil organic matter pools were estimated from BK50 soil map information on soil texture and soil organic matter content, using pedo-transfer functions and SOM pool fractionation following Bruun and Jensen (2002). The coarser soil map is derived from BK50 soil map (50m x 50m) by selecting only the dominant soil type in a 12km × 12km grid to be representative for that grid cell. The crop model was calibrated with field data of crop phenology, leaf area, biomass, yield and crop nitrogen, which were collected at a research station within the study area between 2009 and 2018.</p><p>The predicted increase in temperatures during the growing season correlated with earlier maturity, lower yields and a higher grain protein content. The regional mean values varied by +/- 0.5 t/ha or +/-0.3 percentage points of protein content depending to the climate model used. On the regional scale, the simulated trends remained unchanged using high-resolution or coarse resolution soil data. However, there are strong differences in both the forecasted averages and the distribution of forecasts, as the coarser resolution captures neither the small-scale heterogeneity nor the average of the high-resolution results.</p>

Modeling the effects and feedbacks of irrigation on the regional climate in Northern Italy

2020 ◽  
Author(s):  
Christina Asmus ◽  
Peter Hoffmann ◽  
Diana Rechid ◽  
Jürgen Böhner
Keyword(s):  
Land Cover ◽  
Land Surface ◽  
Climate Model ◽  
Regional Climate ◽  
Sensitivity Study ◽  
Moist Convection ◽  
Moisture Fluxes ◽  
Spatiotemporal Behavior ◽  
Italian Model ◽  
The Impact

<p><span>Large parts of the earth’s land surface are modified by humans. Since the land surface and the atmosphere are constantly in energy exchange and in interactions with each other, anthropogenic modifications of the land’s surface can lead to effects on the climate. The objective of this study is to quantify and investigate the effects and feedbacks of irrigation on the local to regional climate. Irrigation is a land use practice, which does not change the land cover type but changes the biophysical properties of the land’s surface and the soil and thus alters energy and moisture fluxes. These local to regional process responses, detectable in different meteorological variables, are investigated using the regional climate model REMO. High resolution simulations at convection permitting scales will be performed in order to particularly investigate irrigation effects on the spatiotemporal behavior of moist convection. Newly developed parameterizations of different types of irrigation are tested on the example of a northern Italian model domain, where cropland and rice paddies are the dominating land cover. The focus of the sensitivity study is on the impact of the parameterizations on the surface moisture and energy balance as well as on heavy rainfall events. </span></p>

scholarly journals Very high resolution regional climate model simulations over Greenland: Identifying added value

2012 ◽  
Vol 117 (D2) ◽  
pp. n/a-n/a ◽  
Author(s):  
Philippe Lucas-Picher ◽  
Maria Wulff-Nielsen ◽  
Jens H. Christensen ◽  
Guðfinna Aðalgeirsdóttir ◽  
Ruth Mottram ◽  
...  
Keyword(s):  
High Resolution ◽  
Regional Climate Model ◽  
Climate Model ◽  
Regional Climate ◽  
Added Value ◽  
Model Simulations ◽  
Climate Model Simulations ◽  
Very High
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