scholarly journals How Well Does Mpas-atmosphere Simulate the Characteristics of the Botswana High?

Author(s):  
Molulaqhooa Linda Maoyi ◽  
Babatunde Joseph Abiodun

Abstract The Botswana High is a prominent mid-tropospheric system that modulates rainfall over subtropical southern Africa, but the capability of a Global Climate Model (GCM) to reproduce it remains unknown. This study examines the capability of a GCM with quasi-uniform resolution (Model Prediction Across Scales, hereafter MPAS) in simulating the characteristics of the Botswana High. The MPAS is applied to simulate the global climate at 240km quasi-uniform resolution over the globe for the period 1980-2010. The model results are validated against gridded observation dataset (Climate Research Unit, CRU), satellite dataset (Global Precipitation Climatology Project, GPCP), and reanalysis datasets (Climate Forecast System Reanalysis, CFSR; the National Oceanic and Atmospheric Administration, NOAA; and the European Centre for Medium-Range Weather Forecasts version 5, ERA5). In general, MPAS replicates all the essential features in the climatology of temperature, rainfall, 500 hPa geopotential height and vertical motion over southern Africa, reproduces the spatial and temporal variation of the Botswana High, and captures the influence of the Botswana High on droughts and deep convections over the sub-continent. In addition, the model reproduces well the anomalies in vertical motion over subtropical southern Africa during +ve and -ve phases of the Botswana High. However, the model struggles to reproduce the precipitation pattern associated with the positive and native modes of Botswana high. The results of this study have an application in understanding the characteristics of Botswana High and in improving MPAS for seasonal forecasting over southern Africa.

2021 ◽  
Author(s):  
Zhongfeng Xu ◽  
Ying Han ◽  
Chi-Yung Tam ◽  
Zong-Liang Yang ◽  
Congbin Fu

Abstract Dynamical downscaling is the most widely used physics-based approach to obtaining fine-scale weather and climate information. However, traditional dynamical downscaling approaches are often degraded by biases in the large-scale forcing. To improve the confidence in future projection of regional climate, we used a novel bias-corrected global climate model (GCM) dataset to drive a regional climate model (RCM) over the period for 1980–2014. The dynamical downscaling simulations driven by the original GCM dataset (MPI-ESM1-2-HR model) (hereafter WRF_GCM), the bias-corrected GCM (hereafter WRF_GCMbc) are validated against that driven by the European Centre for Medium-Range Weather Forecasts Reanalysis 5 dataset (hereafter WRF_ERA5), respectively. The results suggest that, compared with the WRF_GCM, the WRF_GCMbc shows a 50–90% reduction in RMSEs of the climatological mean of downscaled variables (e.g. temperature, precipitation, wind, relative humidity). Similarly, the WRF_GCMbc also shows improved performance in simulating the interannual variability of downscaled variables. The RMSEs of interannual variances of downscaled variables are reduced by 30–60%. An EOF analysis suggests that the WRF_GCMbc can successfully reproduce the dominant tri-pole mode in the interannual summer precipitation variations observed over eastern China as opposed to the mono-pole precipitation pattern simulated by the WRF_GCM. Such improvements are primarily caused by the correct simulation of the location of the western North Pacific subtropical high by the WRF_GCMbc due to the GCM bias correction.


2021 ◽  
Author(s):  
Patrick Peter ◽  
Sigrun Matthes ◽  
Christine Frömming ◽  
Volker Grewe

<p>Air transport has for a long time been linked to environmental issues like pollution, noise and climate change. While CO2 emissions are the main focus in public discussions, non-CO2 emissions of aviation may have a similar impact on the climate as aviation's carbon dioxide, e.g. contrail cirrus, nitrogen oxides or aviation induced cloudiness. While the effects of CO2 on climate are independent of location and situation during release, non-CO2 effects such as contrail formation vary depending on meteorological background. Previous studies investigated the influence of different weather situations on aviation’s climate change contribution, identifying climate sensitive regions and generating data products which enable air traffic management (ATM) to plan for climate optimized trajectories.</p> <p>The research presented here focuses on the further development of methods to determine the sensitivity of the atmosphere to aviation emissions with respect to climate effects in order to determine climate optimized aircraft trajectories. While previous studies focused on characterizing the North Atlantic Flight Corridor region, this study aims to extend the geographic scope by performing Lagrangian simulations in a global climate model EMAC for the northern hemispheric extratropical regions and tropical latitudes. This study addresses how realistically the physical conditions and processes for contrail formation and life cycle are represented in the upper troposphere and lower stratosphere by comparing them to airborne observations (HALO measurement campaign, CARIBIC/IAGOS scheduled flight measurements), examining key variables such as temperature or humidity. Direct comparison of model data with observations using clusters of data provides insight into the extent to which systematic biases exist that are relevant to the climate effects of contrails. We perform this comparison for different vertical resolutions to assess which vertical resolution in the EMAC model is well suited for studying contrail formation. Together with this model evaluation using aircraft measurements, the overall concept for studying the life cycle of contrails in the modular global climate model EMAC is introduced. Hereby, the concept for the development of a MET service that can be provided to ATM to evaluate contrail formation and its impact on the climate along planned aircraft trajectories is presented.</p> <p>Within the ClimOP collaborative project, we can investigate which physical processes determine the effects of contrails on climate and study their spatial and temporal variation. In addition, these climate change functions enable case studies that assess the impact of contrails on climate along trajectories and use alternative trajectories that avoid these regions of the atmosphere that have the potential to form contrails with a large radiative effect.</p> <p>This study is part of the ClimOP project and has received funding from European Union’s Horizon 2020 Research and Innovation Programme under Grant Agreement N° 875503 (ClimOP) and from the SESAR Joint Undertaking under grant agreements No 699395 (FlyATM4E). </p>


2021 ◽  
Author(s):  
Molulaqhooa Linda Maoyi ◽  
Babatunde Joseph Abiodun

Abstract The Botswana High is an important component of the regional atmospheric circulation during austral spring, summer and autumn. While the high tends to be stronger during El Niño and weaker during La Niña, its direct response to El Niño Southern Oscillation (ENSO) remains unknown. To that end, a variable resolution global climate model (Model Prediction Across Scales version 7, hereafter MPAS) is applied with relatively high resolution (48 km grid spacing) over southern Africa and a coarser resolution (240 km grid spacing) over the rest of the globe for the study period 1980–2010. The first model experiment uses observed SSTs everywhere during the study period, while the second experiment uses observed SSTs everywhere except over the Pacific Ocean, where monthly climatological SSTs are imposed. The model results were validated against satellite data (Global Precipitation Climatology Project, GPCP), reanalysis datasets (Climate Forecast System Reanalysis, CFSR; European Centre for Medium-Range Weather Forecasts version 5, ERA5). The results of the study show that the MPAS model gives a credible simulation of the temporal variability of the Botswana High, the seasonal rainfall and 500 hPa geopotential heights over southern Africa. In the absence of ENSO forcing, the amplitude of the Botswana High variability reduces but the signal of the variability remains. Hence, this study shows that ENSO enhances the strength of the Botswana High but does not aid in the formation of the Botswana High.


1996 ◽  
Author(s):  
Larry Bergman ◽  
J. Gary ◽  
Burt Edelson ◽  
Neil Helm ◽  
Judith Cohen ◽  
...  

2010 ◽  
Vol 10 (14) ◽  
pp. 6527-6536 ◽  
Author(s):  
M. A. Brunke ◽  
S. P. de Szoeke ◽  
P. Zuidema ◽  
X. Zeng

Abstract. Here, liquid water path (LWP), cloud fraction, cloud top height, and cloud base height retrieved by a suite of A-train satellite instruments (the CPR aboard CloudSat, CALIOP aboard CALIPSO, and MODIS aboard Aqua) are compared to ship observations from research cruises made in 2001 and 2003–2007 into the stratus/stratocumulus deck over the southeast Pacific Ocean. It is found that CloudSat radar-only LWP is generally too high over this region and the CloudSat/CALIPSO cloud bases are too low. This results in a relationship (LWP~h9) between CloudSat LWP and CALIPSO cloud thickness (h) that is very different from the adiabatic relationship (LWP~h2) from in situ observations. Such biases can be reduced if LWPs suspected to be contaminated by precipitation are eliminated, as determined by the maximum radar reflectivity Zmax>−15 dBZ in the apparent lower half of the cloud, and if cloud bases are determined based upon the adiabatically-determined cloud thickness (h~LWP1/2). Furthermore, comparing results from a global model (CAM3.1) to ship observations reveals that, while the simulated LWP is quite reasonable, the model cloud is too thick and too low, allowing the model to have LWPs that are almost independent of h. This model can also obtain a reasonable diurnal cycle in LWP and cloud fraction at a location roughly in the centre of this region (20° S, 85° W) but has an opposite diurnal cycle to those observed aboard ship at a location closer to the coast (20° S, 75° W). The diurnal cycle at the latter location is slightly improved in the newest version of the model (CAM4). However, the simulated clouds remain too thick and too low, as cloud bases are usually at or near the surface.


2009 ◽  
Vol 29 (1) ◽  
pp. 94-101 ◽  
Author(s):  
Heiko Goelzer ◽  
Anders Levermann ◽  
Stefan Rahmstorf

2012 ◽  
Vol 43 (3) ◽  
pp. 215-230 ◽  
Author(s):  
Manish Kumar Goyal ◽  
C. S. P. Ojha

We investigate the performance of existing state-of-the-art rule induction and tree algorithms, namely Single Conjunctive Rule Learner, Decision Table, M5 Model Tree, Decision Stump and REPTree. Downscaling models are developed using these algorithms to obtain projections of mean monthly precipitation to lake-basin scale in an arid region in India. The effectiveness of these algorithms is evaluated through application to downscale the predictand for the Lake Pichola region in Rajasthan state in India, which is considered to be a climatically sensitive region. The predictor variables are extracted from (1) the National Centre for Environmental Prediction (NCEP) reanalysis dataset for the period 1948–2000 and (2) the simulations from the third-generation Canadian Coupled Global Climate Model (CGCM3) for emission scenarios A1B, A2, B1 and COMMIT for the period 2001–2100. M5 Model Tree algorithm was found to yield better performance among all other learning techniques explored in the present study. The precipitation is projected to increase in future for A2 and A1B scenarios, whereas it is least for B1 and COMMIT scenarios using predictors.


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