scholarly journals On the Influence of Vegetation Cover Changes and Vegetation-Runoff Systems on the Simulated Summer Potential Evapotranspiration of Tropical Africa Using RegCM4

2021 ◽  
Author(s):  
Samy A. Anwar ◽  
Ossénatou Mamadou ◽  
Ismaila Diallo ◽  
Mouhamadou Bamba Sylla
Keyword(s):  
Soil Moisture ◽  
Vegetation Cover ◽  
Climate Model ◽  
Potential Evapotranspiration ◽  
Regional Climate ◽  
Boreal Summer ◽  
Climatic Research Unit ◽  
Tropical Africa ◽  
Infiltration Capacity ◽  
Community Land Model

AbstractThe community land model version 4.5 provides two ways for treating the vegetation cover changes (a static versus an interactive) and two runoff schemes for tracking the soil moisture changes. In this study, we examined the sensitivity of the simulated boreal summer potential evapotranspiration (PET) to the aforementioned options using a regional climate model. Three different experiments with each one covering 16 years have been performed. The two runoff schemes were designated as SIMTOP (TOP) and variable infiltration capacity (VIC). Both runoff schemes were coupled to the carbon–nitrogen (CN) module, thus the vegetation status can be influenced by soil moisture changes. Results show that vegetation cover changes alone affect considerably the simulated 2-m mean air temperature (T2M). However, they do not affect the global incident solar radiation (RSDS) and PET. Conversely to the vegetation cover changes alone, the vegetation-runoff systems affect both the T2M and RSDS. Therefore, they considerably affect the simulated PET. Also, the CN-VIC overestimates the PET more than the CN-TOP compared to the Climatic Research Unit observational dataset. In comparison with the static vegetation case and CN-VIC, the CN-TOP shows the least bias of the simulated PET. Overall, our results show that the vegetation-runoff system is relevant in constraining the PET, though the CN-TOP can be recommended for future studies concerning the PET of tropical Africa.

scholarly journals Modeling the Dynamic Vegetation–Climate System over China Using a Coupled Regional Model

2018 ◽  
Vol 31 (15) ◽  
pp. 6027-6049 ◽  
Author(s):  
Ying Shi ◽  
Miao Yu ◽  
Amir Erfanian ◽  
Guiling Wang
Keyword(s):  
Vegetation Cover ◽  
Climate Model ◽  
Regional Climate ◽  
Reanalysis Data ◽  
Plant Phenology ◽  
Wind Fields ◽  
Area Index ◽  
Fractional Coverage ◽  
Community Land Model ◽  
Temperature And Precipitation

Using the Regional Climate Model (RegCM) coupled with the Community Land Model (CLM) including modules of carbon–nitrogen cycling (CN) and vegetation dynamics (DV), this study evaluates the performance of the model with different capacity of representing vegetation processes in simulating the present-day climate over China based on three 21-yr simulations driven with boundary conditions from the ERA-Interim reanalysis data during 1989–2009. For each plant functional type (PFT), the plant pheonology, density, and fractional coverage in RegCM-CLM are all prescribed as static from year to year; RegCM-CLM-CN prescribes static fractional coverage but predicts plant phenology and density, and RegCM-CLM-CN-DV predicts plant phenology, density, and fractional coverage. Compared against the observational data, all three simulations reproduce the present-day climate well, including the wind fields, temperature and precipitation seasonal cycles, extremes, and interannual variabilities. Relative to RegCM-CLM, both RegCM-CLM-CN and RegCM-CLM-CN-DV perform better in simulating the interannual variability of temperature and spatial distribution of mean precipitation, but produce larger biases in the mean temperature field. RegCM-CLM-CN overestimates leaf area index (LAI), which enhances the cold biases and alleviates the dry biases found in RegCM-CLM. RegCM-CLM-CN-DV underestimates vegetation cover and/or stature, and hence overestimates surface albedo, which enhances the wintertime cold and dry biases found in RegM-CLM. During summer, RegCM-CLM-CN-DV overestimates LAI in south and east China, which enhances the cold biases through increased evaporative cooling; in the west where evaporation is low, the albedo effect of the underestimated vegetation cover is still dominant, leading to enhanced cold biases relative to RegCM-CLM.

Hydrological evaluation of high-resolution precipitation estimates from the WRF model in the Third Pole river basins

2021 ◽  
Author(s):  
He Sun ◽  
Fengge Su ◽  
Zhihua He ◽  
Tinghai Ou ◽  
Deliang Chen ◽  
...  
Keyword(s):  
Land Surface ◽  
Large Scale ◽  
Hydrological Modeling ◽  
Climate Model ◽  
Regional Climate ◽  
Wrf Model ◽  
Infiltration Capacity ◽  
Flood Prediction ◽  
Daily Streamflow ◽  
Precipitation Estimates

AbstractIn this study, two sets of precipitation estimates based on the regional Weather Research and Forecasting model (WRF) –the high Asia refined analysis (HAR) and outputs with a 9 km resolution from WRF (WRF-9km) are evaluated at both basin and point scales, and their potential hydrological utilities are investigated by driving the Variable Infiltration Capacity (VIC) large-scale land surface hydrological model in seven Third Pole (TP) basins. The regional climate model (RCM) tends to overestimate the gauge-based estimates by 20–95% in annual means among the selected basins. Relative to the gauge observations, the RCM precipitation estimates can accurately detect daily precipitation events of varying intensities (with absolute bias < 3 mm). The WRF-9km exhibits a high potential for hydrological application in the monsoon-dominated basins in the southeastern TP (with NSE of 0.7–0.9 and bias of -11% to 3%), while the HAR performs well in the upper Indus (UI) and upper Brahmaputra (UB) basins (with NSE of 0.6 and bias of -15% to -9%). Both the RCM precipitation estimates can accurately capture the magnitudes of low and moderate daily streamflow, but show limited capabilities in flood prediction in most of the TP basins. This study provides a comprehensive evaluation of the strength and limitation of RCMs precipitation in hydrological modeling in the TP with complex terrains and sparse gauge observations.

scholarly journals Summer drought in Switzerland 1981‒2020: Events, trends and drivers

2021 ◽  
Author(s):  
Simon C. Scherrer ◽  
Christoph Spirig ◽  
Martin Hirschi ◽  
Felix Maurer ◽  
Sven Kotlarski
Keyword(s):  
Regional Climate Model ◽  
Soil Water ◽  
Climate Model ◽  
Potential Evapotranspiration ◽  
Meteorological Data ◽  
Regional Climate ◽  
Reanalysis Data ◽  
Summer Drought ◽  
Temperature And Precipitation ◽  
Temperature Scaling

&lt;p&gt;The Alpine region has recently experienced several dry summers with negative impacts on the economy, society and ecology. Here, soil water, evapotranspiration and meteorological data from several observational and model-based data sources is used to assess events, trends and drivers of summer drought in Switzerland in the period 1981&amp;#8210;2020. 2003 and 2018 are identified as the driest summers followed by somewhat weaker drought conditions in 2020, 2015 and 2011. We find clear evidence for an increasing summer drying in Switzerland. The observed climatic water balance (-39.2&amp;#160;mm/decade) and 0-1 m soil water from reanalysis (ERA5-Land: -4.7&amp;#160;mm/decade; ERA5: -7.2&amp;#160;mm/decade) show a clear tendency towards summer drying with decreasing trends in most months. Increasing evapotranspiration (potential evapotranspiration: +21.0&amp;#160;mm/decade; ERA5-Land actual evapotranspiration: +15.1&amp;#160;mm/decade) is identified as important driver which scales excellently (+4 to +7%/K) with the observed strong warming of about 2&amp;#176;C. An insignificant decrease in precipitation further enhanced the tendency towards drier conditions. Most simulations of the EURO-CORDEX regional climate model ensemble underestimate the changes in summer drying. They underestimate both, the observed recent summer warming and the small decrease in precipitation. The changes in temperature and precipitation are negatively correlated, i.e. simulations with stronger warming tend to show (weak) decreases in precipitation. However, most simulations and the reanalysis overestimate the correlation between temperature and precipitation and the precipitation-temperature scaling on the interannual time scale. Our results emphasize that the analysis of the regional summer drought evolution and its drivers remains challenging especially with regional climate model data but considerable uncertainties also exist in reanalysis data sets.&lt;/p&gt;

scholarly journals Projected effects of vegetation feedback on drought characteristics of West Africa using a coupled regional land–vegetation–climate model

2019 ◽  
Author(s):  
Muhammad Shafqat Mehboob ◽  
Yeonjoo Kim ◽  
Jaehyeong Lee ◽  
Myoung-Jin Um ◽  
Amir Erfanian ◽  
...  
Keyword(s):  
West Africa ◽  
Vegetation Dynamics ◽  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Global Climate Models ◽  
Congo Basin ◽  
Area Index ◽  
Vegetation Feedback ◽  
Community Land Model

Abstract. This study investigates the projected effect of vegetation feedback on drought conditions in West Africa using a regional climate model coupled to the National Center for Atmospheric Research Community Land Model, the carbon-nitrogen (CN) module, and the dynamic vegetation (DV) module (RegCM-CLM-CN-DV). The role of vegetation feedback is examined based on simulations with and without the DV module. Simulations from four different global climate models are used as lateral boundary conditions (LBCs) for historical and future periods (i.e., historical: 1981–2000; future: 2081–2100). With utilizing the Standardized Precipitation Evapotranspiration Index (SPEI), we quantify the duration, frequency, and severity of droughts over the focal regions of the Sahel, the Gulf of Guinea, and the Congo Basin. With the vegetation dynamics being considered, future droughts become more prolonged and enhanced over the Sahel, whereas for the Guinea Gulf and Congo Basin, the trend is opposite. Additionally, we show that simulated annual leaf greenness (i.e., the Leaf Area Index) well-correlates with annual minimum SPEI, particularly over the Sahel, which is a transition zone, where the feedback between land-atmosphere is relatively strong. Furthermore, we note that our findings based on the ensemble mean are varying, but consistent among three different LBCs except for one LBC. Our results signify the importance of vegetation dynamics in predicting future droughts in West Africa, where the biosphere and atmosphere interactions play an important role in the regional climate setup.

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

&lt;p&gt;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 &amp;#947;&lt;sub&gt;sm&lt;/sub&gt; which does not only account, as previously, for soil moisture available to plants but also links isoprene emissions to photosynthesis and plant water stress.&lt;/p&gt;&lt;p&gt;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&amp;#176;. 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 &amp;#947;&lt;sub&gt;sm&lt;/sub&gt;.&amp;#160; The results are then compared with a simulation whit no soil moisture activity factor. Both activity factors &amp;#947;&lt;sub&gt;sm&lt;/sub&gt; reduce isoprene emissions under water deficit.&lt;/p&gt;&lt;p&gt;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 &amp;#947;&lt;sub&gt;sm &lt;/sub&gt;is used,&lt;sub&gt;&lt;/sub&gt;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.&lt;/p&gt;

Response of Seasonal Simulations of a Regional Climate Model to High-Frequency Variability of Soil Moisture during the Summers of 1988 and 1993

2007 ◽  
Vol 8 (4) ◽  
pp. 738-757 ◽  
Author(s):  
Song Yang ◽  
S-H. Yoo ◽  
R. Yang ◽  
K. E. Mitchell ◽  
H. van den Dool ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Water Vapor ◽  
Diurnal Cycle ◽  
High Frequency ◽  
Large Scale ◽  
Climate Model ◽  
Regional Climate ◽  
Water Vapor Transport ◽  
Diurnal Variability ◽  
High Frequency Variability

Abstract This study employs the NCEP Eta Regional Climate Model to investigate the response of the model’s seasonal simulations of summer precipitation to high-frequency variability of soil moisture. Specifically, it focuses on the response of model precipitation and temperature over the U.S. Midwest and Southeast to imposed changes in the diurnal and synoptic variability of soil moisture in 1988 and 1993. High-frequency variability of soil moisture increases (decreases) precipitation in the 1988 drought (1993 flood) year in the central and southern-tier states, except along the Gulf Coast, but causes smaller changes in precipitation along the northern-tier states. The diurnal variability and synoptic variability of soil moisture produce similar patterns of precipitation change, indicating the importance of the diurnal cycle of land surface process. The increase (decrease) in precipitation is generally accompanied by a decrease (increase) in surface and lower-tropospheric temperatures, and the changes in precipitation and temperature are attributed to both the local effect of evaporation feedback and the remote influence of large-scale water vapor transport. The precipitation increase and temperature decrease in 1988 are accompanied by an increase in local evaporation and, more importantly, by an increase in the large-scale water vapor convergence into the Midwest and Southeast. Analogous but opposite-sign behavior occurs in 1993 (compared to 1988) in changes in precipitation, temperature, soil moisture, evaporation, and large-scale water vapor transport. Results also indicate that, in regions where the model simulates the diurnal cycle of soil moisture reasonably well, including this diurnal cycle in the simulations improves model performance. However, no notable improvement in model precipitation can be found in regions where the model fails to realistically simulate the diurnal variability of soil moisture.

scholarly journals Improving Climate Sensitivity of Deep Lakes within a Regional Climate Model and Its Impact on Simulated Climate

2014 ◽  
Vol 27 (8) ◽  
pp. 2886-2911 ◽  
Author(s):  
Val Bennington ◽  
Michael Notaro ◽  
Kathleen D. Holman
Keyword(s):  
Regional Climate Model ◽  
Interannual Variability ◽  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Global Climate Models ◽  
Deep Lakes ◽  
Community Land Model ◽  
Lake Model ◽  
Lake Temperature

Abstract Regional climate models aim to improve local climate simulations by resolving topography, vegetation, and land use at a finer resolution than global climate models. Lakes, particularly large and deep lakes, are local features that significantly alter regional climate. The Hostetler lake model, a version of which is currently used in the Community Land Model, performs poorly in deep lakes when coupled to the regional climate of the International Centre for Theoretical Physics (ICTP) Regional Climate Model, version 4 (RegCM4). Within the default RegCM4 model, the lake fails to properly stratify, stifling the model’s ability to capture interannual variability in lake temperature and ice cover. Here, the authors improve modeled lake stratification and eddy diffusivity while correcting errors in the ice model. The resulting simulated lake shows improved stratification and interannual variability in lake ice and temperature. The lack of circulation and explicit mixing continues to stifle the model’s ability to simulate lake mixing events and variability in timing of stratification and destratification. The changes to modeled lake conditions alter seasonal means in sea level pressure, temperature, and low-level winds in the entire model domain, highlighting the importance of lake model selection and improvement for coupled simulations. Interestingly, changes to winter and spring snow cover and albedo impact spring warming. Unsurprisingly, regional climate variability is not significantly altered by an increase in lake temperature variability.

A Preliminary Study on the Relationship between Vegetation Cover and Regional Climate Change in Jiangsu Area of China

2013 ◽  
Vol 448-453 ◽  
pp. 916-922
Author(s):  
Yan Rong Yang ◽  
Zhe Kong ◽  
Chun Ming Liu
Keyword(s):  
Climate Change ◽  
Vegetation Cover ◽  
Vegetation Index ◽  
Climate Model ◽  
Regional Climate ◽  
Precipitation Amount ◽  
Regional Climate Change ◽  
Research Field ◽  
Research Fields ◽  
The Relationship

The relationship between vegetation cover and climate change is one of the most important research fields in global change. Herein Jiangsu province and thereabout in China is chosen to be the research field. Under the support of observations from normalized differential vegetation index (NDVI) during years from 1998 to 2008 and corresponding benchmark weather stations, the relationship between vegetation and climate change had been analyzed combined with simulations from regional climate model RegCM3, in perspectives of point vegetation cover amount and area vegetation cover type respectively. Conclusions are: (1) Points observations showed that NDVI had positive correlation with annual total precipitation and negative correlation with annual average temperature. (2) Area simulations showed that two different vegetation types in south and north Jiangsu almost had same 8warming value, but the incremental annual precipitation amount is more significant in south Jiangsu.

scholarly journals Diagnosing the Strength of Land–Atmosphere Coupling at Subseasonal to Seasonal Time Scales in Asia

2014 ◽  
Vol 15 (1) ◽  
pp. 320-339 ◽  
Author(s):  
Di Liu ◽  
Guiling Wang ◽  
Rui Mei ◽  
Zhongbo Yu ◽  
Huanghe Gu
Keyword(s):  
Soil Moisture ◽  
Time Scales ◽  
Climate Model ◽  
Regional Climate ◽  
Precipitation Amount ◽  
Data Sources ◽  
Conditional Correlation ◽  
Global Land ◽  
Land Data Assimilation System ◽  
The Impact

Abstract This paper focuses on diagnosing the strength of soil moisture–atmosphere coupling at subseasonal to seasonal time scales over Asia using two different approaches: the conditional correlation approach [applied to the Global Land Data Assimilation System (GLDAS) data, the Climate Forecast System Reanalysis (CFSR) data, and output from the regional climate model, version 4 (RegCM4)] and the Global Land–Atmosphere Coupling Experiment (GLACE) approach applied to the RegCM4. The conditional correlation indicators derived from the model output and the two observational/reanalysis datasets agree fairly well with each other in the spatial pattern of the land–atmosphere coupling signal, although the signal in CFSR data is stronger and spatially more extensive than the GLDAS data and the RegCM4 output. Based on the impact of soil moisture on 2-m air temperature, the land–atmosphere coupling hotspots common to all three data sources include the Indochina region in spring and summer, the India region in summer and fall, and north-northeastern China and southwestern Siberia in summer. For precipitation, all data sources produce a weak and spatially scattered signal, indicating the lack of any strong coupling between soil moisture and precipitation, for both precipitation amount and frequency. Both the GLACE approach and the conditional correlation approach (applied to all three data sources) identify evaporation and evaporative fraction as important links for the coupling between soil moisture and precipitation/temperature. Results on soil moisture–temperature coupling strength from the GLACE-type experiment using RegCM4 are in good agreement with those from the conditional correlation analysis applied to output from the same model, despite substantial differences between the two approaches in the terrestrial segment of the land–atmosphere coupling.

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