Reducing the Uncertainties of Climate Projections: High-Resolution Climate Modeling of Aerosol and Climate Interactions on the Regional Scale Using COSMO-ART: Interaction of Mineral Dust with Atmospheric Radiation over West-Africa

2016 ◽  
pp. 601-607
Author(s):  
Bernhard Vogel ◽  
Hans-Juergen Panitz ◽  
Heike Vogel
Keyword(s):  
High Resolution ◽  
West Africa ◽  
Mineral Dust ◽  
Climate Modeling ◽  
Regional Scale ◽  
Atmospheric Radiation ◽  
Climate Projections ◽  
Climate Interactions

scholarly journals Radiative forcing associated with a springtime case of Bodélé and Sudan dust transport over West Africa

2010 ◽  
Vol 10 (4) ◽  
pp. 8811-8858 ◽  
Author(s):  
C. Lemaître ◽  
C. Flamant ◽  
J. Cuesta ◽  
J.-C. Raut ◽  
P. Chazette ◽  
...  
Keyword(s):  
West Africa ◽  
Heating Rate ◽  
Radiative Forcing ◽  
Mineral Dust ◽  
Regional Scale ◽  
Longwave Radiation ◽  
Heating Rates ◽  
Dust Layer ◽  
In Situ Observations

Abstract. The radiative forcing due to mineral dust over West Africa is investigated using the radiative code STREAMER, as well as remote sensing and in situ observations gathered during the African Monsoon Multidisciplinary Analysis Special Observing Period (AMMA SOP). We focus on two days (13 and 14 June 2006) of an intense and long-lasting episode of dust being lifted in remote sources in Chad and Sudan and transported across West Africa in the African easterly jet region, during which airborne operations were conducted at the regional scale, from the southern fringes of the Sahara to the Gulf of Guinea. Profiles of heating rates are computed from airborne LEANDRE 2 and space-borne CALIOP lidar observations using two mineral dust model constrained by airborne in situ data and ground-based sunphotometer obtained during the campaign. Complementary space-borne observations (from MODIS) and in-situ observations such as dropsondes are also used to take into account a realistic infrared contribution of the water vapour. We investigate the variability of the heating rate on the vertical within a dust plume, as well as the contribution of longwave radiation to the heating rate and the radiative forcing of dust during the nighttime. The sensitivity of the so-derived heating rate is also analyzed for some key variables for which the associated uncertainties are quite large. During daytime, the warming associated with the presence of dust was found to be between 1.5 K day−1 and 4 K day−1, on average, depending on altitude and latitude. Strong warming (i.e. heating rates as high as 8 K day−1) was also observed locally in some limited part of the dust plumes. Obviously, during nighttime much smaller values of heating/cooling are retrieved (less than ±1 K day−1) but large enough to modify the low tropospheric equilibrium. Furthermore, cooling is observed as the result of the longwave forcing in the dust layer, while warming is observed below the dust layer, in the monsoon layer.

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>

scholarly journals Radiative heating rates profiles associated with a springtime case of Bodélé and Sudan dust transport over West Africa

2010 ◽  
Vol 10 (17) ◽  
pp. 8131-8150 ◽  
Author(s):  
C. Lemaître ◽  
C. Flamant ◽  
J. Cuesta ◽  
J.-C. Raut ◽  
P. Chazette ◽  
...  
Keyword(s):  
West Africa ◽  
Heating Rate ◽  
Mineral Dust ◽  
Regional Scale ◽  
Longwave Radiation ◽  
Radiative Heating ◽  
Heating Rates ◽  
Dust Layer ◽  
In Situ Observations

Abstract. The radiative heating rate due to mineral dust over West Africa is investigated using the radiative code STREAMER, as well as remote sensing and in situ observations gathered during the African Monsoon Multidisciplinary Analysis Special Observing Period (AMMA SOP). We focus on two days (13 and 14 June 2006) of an intense and long lasting episode of dust being lifted in remote sources in Chad and Sudan and transported across West Africa in the African easterly jet region, during which airborne operations were conducted at the regional scale, from the southern fringes of the Sahara to the Gulf of Guinea. Profiles of heating rates are computed from airborne LEANDRE 2 (Lidar Embarqué pour l'étude de l'Atmosphère: Nuages Dynamique, Rayonnement et cycle de l'Eau) and space-borne CALIOP (Cloud Aerosol Lidar and Infrared Pathfinder Satellite Observations) lidar observations using two mineral dust model constrained by airborne in situ data and ground-based sunphotometer obtained during the campaign. Complementary spaceborne observations (from the Moderate-resolution Imaging Spectroradiometer-MODIS) and in-situ observations such as dropsondes are also used to take into account the infrared contribution of the water vapour. We investigate the variability of the heating rate on the vertical within a dust plume, as well as the contribution of both shortwave and longwave radiation to the heating rate and the radiative heating rate profiles of dust during daytime and nighttime. The sensitivity of the so-derived heating rate is also analyzed for some key variables for which the associated uncertainties may be large. During daytime, the warming associated with the presence of dust was found to be between 1.5 K day−1 and 4 K day−1, on average, depending on altitude and latitude. Strong warming (i.e. heating rates as high as 8 K day−1) was also observed locally in some limited part of the dust plumes. The uncertainty on the heating rate retrievals in the optically thickest part of the dust plume was estimated to be between 0.5 and 1.4 K day−1. During nighttime much smaller values of heating/cooling are retrieved (less than ±1 K day−1). Furthermore, cooling is observed as the result of the longwave forcing in the dust layer, while warming is observed below the dust layer, in the monsoon layer.

scholarly journals Temporal variability of mineral dust concentrations over West Africa: analyses of a pluriannual monitoring from the AMMA Sahelian Dust Transect

2010 ◽  
Vol 10 (18) ◽  
pp. 8899-8915 ◽  
Author(s):  
B. Marticorena ◽  
B. Chatenet ◽  
J. L. Rajot ◽  
S. Traoré ◽  
M. Coulibaly ◽  
...  
Keyword(s):  
West Africa ◽  
Rainy Season ◽  
Seasonal Cycle ◽  
Mineral Dust ◽  
General Pattern ◽  
Regional Scale ◽  
Surface Wind ◽  
Dry Season ◽  
Dust Concentration ◽  
Saharan Dust

Abstract. The Sahelian belt is known to be a region where atmospheric levels of suspended mineral dust are among the highest observed on Earth. In the framework of the AMMA (African Monsoon Multidisciplinary Analysis) International Program, a transect of 3 ground based stations, the "Sahelian Dust Transect" (SDT), has been deployed in order to obtain quantitative information on the mineral dust content and its variability over the Sahel. The three stations, namely Banizoumbou (Niger), Cinzana (Mali) and M'Bour (Senegal) are aligned around 14° N along the east-westward main pathway of the Saharan and Sahelian dust towards the Atlantic Ocean. We discuss data collected between January 2006 and December 2008 to investigate the main characteristics of the mineral dust concentration over West Africa and their connection with the dominant meteorological situations. The succession of the dry season during which the Sahel is under the influence of the dry Harmattan wind and the wet season induced by the entrance of the monsoon flow is clearly identified from the basic meteorological parameters (air temperature and moisture, wind direction). Atmospheric dust concentrations at the three stations exhibit a similar seasonal cycle, with a monthly maximum during the dry season and a minimum occurring during the rainy season, indicating that the general pattern of dust concentration is similar at regional scale. This seasonal cycle of the dust concentrations is not phased with the seasonal cycle of surface wind velocity locally measured, suggesting that it is mainly controlled by Saharan dust transport. Local dust emissions induced by strong surface winds are responsible for the occurrence of extremely high daily concentrations observed at the beginning of the rainy season. A decrease in the dust concentration is observed when moving from Niger to Senegal.

scholarly journals Temporal variability of mineral dust concentrations over West Africa: analyses of a pluriannual monitoring from the AMMA Sahelian Dust Transect

2010 ◽  
Vol 10 (3) ◽  
pp. 8051-8101 ◽  
Author(s):  
B. Marticorena ◽  
B. Chatenet ◽  
J. L. Rajot ◽  
S. Traoré ◽  
M. Coulibaly ◽  
...  
Keyword(s):  
West Africa ◽  
Rainy Season ◽  
Seasonal Cycle ◽  
Mineral Dust ◽  
General Pattern ◽  
Regional Scale ◽  
Surface Wind ◽  
Dry Season ◽  
Dust Concentration ◽  
Dust Content

Abstract. The Sahelian belt is known to be a region where the mineral dust content is among the highest observed on Earth. In the framework of the AMMA (African Monsoon Multidisciplinary Analysis) International Program, a transect of 3 ground based stations, the "Sahelian Dust Transect" (SDT), has been deployed in order to obtain quantitative information on the mineral dust content and its variability over the Sahel. The three stations, namely Banizoumbou (Niger), Cinzana (Mali) and M'Bour (Senegal) are aligned around 14° N along the east-west main pathway of the Saharan and Sahelian dust towards the Atlantic Ocean. We discuss data collected between January 2006 and December 2008 to investigate the main characteristics of the mineral dust concentration over West Africa and their connection with the dominant meteorological situations. The succession of the dry season during which the Sahel is under the influence of the dry Harmattan wind and the wet season induced by the entrance of the monsoon flow is clearly identified from the basic meteorological parameters (air temperature and moisture, wind direction). Atmospheric dust concentrations at the three stations exhibit a similar seasonal cycle, with a monthly maximum during the dry season and a minimum occurring during the rainy season, indicating that the general pattern of dust concentration is similar at regional scale. This seasonal cycle of the dust concentrations is not phased with the seasonal cycle of surface wind velocity suggesting that it is mainly controlled by Saharan dust transport. A decrease in the dust concentration is observed when moving from Niger to Senegal. However, local dust emissions induced by strong surface winds are responsible for the occurrence of extremely high daily concentrations observed at the beginning of the rainy season.

scholarly journals Spatial Distribution of Permafrost in the Xing’an Mountains of Northeast China from 2001 to 2018

Land ◽  
2021 ◽  
Vol 10 (11) ◽  
pp. 1127
Author(s):  
Yanyu Zhang ◽  
Shuying Zang ◽  
Miao Li ◽  
Xiangjin Shen ◽  
Yue Lin
Keyword(s):  
High Resolution ◽  
Land Surface ◽  
Northeast China ◽  
Climate Modeling ◽  
Regional Scale ◽  
Engineering Application ◽  
Ground Surface ◽  
Remote Sensing Data ◽  
Surface Characteristics ◽  
Significant Difference

Permafrost is a key element of the cryosphere and sensitive to climate change. High-resolution permafrost map is important to environmental assessment, climate modeling, and engineering application. In this study, to estimate high-resolution Xing’an permafrost map (up to 1 km2), we employed the surface frost number (SFN) model and ground temperature at the top of permafrost (TTOP) model for the 2001–2018 period, driven by remote sensing data sets (land surface temperature and land cover). Based on the comparison of the modeling results, it was found that there was no significant difference between the two models. The performances of the SFN model and TTOP model were evaluated by using a published permafrost map. Based on statistical analysis, both the SFN model and TTOP model efficiently estimated the permafrost distribution in Northeast China. The extent of Xing’an permafrost distribution simulated by the SFN model and TTOP model were 6.88 × 105 km2 and 6.81 × 105 km2, respectively. Ground-surface characteristics were introduced into the permafrost models to improve the performance of models. The results provided a basic reference for permafrost distribution research at the regional scale.

scholarly journals Comparison of regional characteristics of land precipitation climatology projected by an MRI-AGCM multi-cumulus scheme and multi-SST ensemble with CMIP5 multi-model ensemble projections

2020 ◽  
Vol 7 (1) ◽  
Author(s):  
Rui Ito ◽  
Tosiyuki Nakaegawa ◽  
Izuru Takayabu
Keyword(s):  
Climate Change ◽  
High Resolution ◽  
General Circulation ◽  
Annual Precipitation ◽  
Cmip5 Models ◽  
Climate Projections ◽  
The Tibetan Plateau ◽  
Model Ensemble ◽  
Uncertainty Range ◽  
High Performing

AbstractEnsembles of climate change projections created by general circulation models (GCMs) with high resolution are increasingly needed to develop adaptation strategies for regional climate change. The Meteorological Research Institute atmospheric GCM version 3.2 (MRI-AGCM3.2), which is listed in the Coupled Model Intercomparison Project phase 5 (CMIP5), has been typically run with resolutions of 60 km and 20 km. Ensembles of MRI-AGCM3.2 consist of members with multiple cumulus convection schemes and different patterns of future sea surface temperature, and are utilized together with their downscaled data; however, the limited size of the high-resolution ensemble may lead to undesirable biases and uncertainty in future climate projections that will limit its appropriateness and effectiveness for studies on climate change and impact assessments. In this study, to develop a comprehensive understanding of the regional precipitation simulated with MRI-AGCM3.2, we investigate how well MRI-AGCM3.2 simulates the present-day regional precipitation around the globe and compare the uncertainty in future precipitation changes and the change projection itself between MRI-AGCM3.2 and the CMIP5 multiple atmosphere–ocean coupled GCM (AOGCM) ensemble. MRI-AGCM3.2 reduces the bias of the regional mean precipitation obtained with the high-performing CMIP5 models, with a reduction of approximately 20% in the bias over the Tibetan Plateau through East Asia and Australia. When 26 global land regions are considered, MRI-AGCM3.2 simulates the spatial pattern and the regional mean realistically in more regions than the individual CMIP5 models. As for the future projections, in 20 of the 26 regions, the sign of annual precipitation change is identical between the 50th percentiles of the MRI-AGCM3.2 ensemble and the CMIP5 multi-model ensemble. In the other six regions around the tropical South Pacific, the differences in modeling with and without atmosphere–ocean coupling may affect the projections. The uncertainty in future changes in annual precipitation from MRI-AGCM3.2 partially overlaps the maximum–minimum uncertainty range from the full ensemble of the CMIP5 models in all regions. Moreover, on average over individual regions, the projections from MRI-AGCM3.2 spread over roughly 0.8 of the uncertainty range from the high-performing CMIP5 models compared to 0.4 of the range of the full ensemble.

scholarly journals New Approach for Bias Correction and Stochastic Downscaling of Future Projections for Daily Mean Temperatures to a High-Resolution Grid

2019 ◽  
Vol 58 (12) ◽  
pp. 2617-2632 ◽  
Author(s):  
Qifen Yuan ◽  
Thordis L. Thorarinsdottir ◽  
Stein Beldring ◽  
Wai Kwok Wong ◽  
Shaochun Huang ◽  
...  
Keyword(s):  
High Resolution ◽  
Bias Correction ◽  
Climate Models ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Climate Change Signal ◽  
Climate Projections ◽  
Data Product ◽  
Temporal Features ◽  
Stochastic Downscaling

AbstractIn applications of climate information, coarse-resolution climate projections commonly need to be downscaled to a finer grid. One challenge of this requirement is the modeling of subgrid variability and the spatial and temporal dependence at the finer scale. Here, a postprocessing procedure for temperature projections is proposed that addresses this challenge. The procedure employs statistical bias correction and stochastic downscaling in two steps. In the first step, errors that are related to spatial and temporal features of the first two moments of the temperature distribution at model scale are identified and corrected. Second, residual space–time dependence at the finer scale is analyzed using a statistical model, from which realizations are generated and then combined with an appropriate climate change signal to form the downscaled projection fields. Using a high-resolution observational gridded data product, the proposed approach is applied in a case study in which projections of two regional climate models from the Coordinated Downscaling Experiment–European Domain (EURO-CORDEX) ensemble are bias corrected and downscaled to a 1 km × 1 km grid in the Trøndelag area of Norway. A cross-validation study shows that the proposed procedure generates results that better reflect the marginal distributional properties of the data product and have better consistency in space and time when compared with empirical quantile mapping.

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