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- Author or Editor: K. Krishna x
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Performance of the WRF Model for Surface Wind Prediction around QatarAbstract
The performance of the Weather Research and Forecasting (WRF) Model is examined for the region around Qatar in the context of surface winds. The wind fields around this peninsula can be complicated owing to its small size, to a complex pattern of land and sea breezes influenced by the prevailing shamal winds, and to its dry and arid nature. Modeled winds are verified with data from 19 land stations and two offshore buoys. A comparison with these data shows that nonlocal planetary boundary layer (PBL) schemes generally perform better than local schemes over land stations during the daytime, when convective conditions prevail; at nighttime, over land and over water, both schemes yield similar results. Among other parameters, modifications to standard USGS land-use descriptors were necessary to reduce model errors. The RMSE values are comparable to those reported elsewhere. Simulated winds, when used with a wave model, result in wave heights comparable to buoy measurements. Furthermore, WRF results, confirmed by data, show that at times sea breezes develop from both coasts, leading to convergence in the middle of the country; at other times, the large-scale wind impedes the formation of sea breezes on one or both coasts. Simulations also indicate greater land/sea-breeze activity in the summer than in the winter. Differences in the diurnal evolution of surface winds over land and water are found to be related to differences in the boundary layer stability. Overall, the results indicate that the WRF Model as configured here yields reliable simulations and can be used for various practical applications.
Abstract
The performance of the Weather Research and Forecasting (WRF) Model is examined for the region around Qatar in the context of surface winds. The wind fields around this peninsula can be complicated owing to its small size, to a complex pattern of land and sea breezes influenced by the prevailing shamal winds, and to its dry and arid nature. Modeled winds are verified with data from 19 land stations and two offshore buoys. A comparison with these data shows that nonlocal planetary boundary layer (PBL) schemes generally perform better than local schemes over land stations during the daytime, when convective conditions prevail; at nighttime, over land and over water, both schemes yield similar results. Among other parameters, modifications to standard USGS land-use descriptors were necessary to reduce model errors. The RMSE values are comparable to those reported elsewhere. Simulated winds, when used with a wave model, result in wave heights comparable to buoy measurements. Furthermore, WRF results, confirmed by data, show that at times sea breezes develop from both coasts, leading to convergence in the middle of the country; at other times, the large-scale wind impedes the formation of sea breezes on one or both coasts. Simulations also indicate greater land/sea-breeze activity in the summer than in the winter. Differences in the diurnal evolution of surface winds over land and water are found to be related to differences in the boundary layer stability. Overall, the results indicate that the WRF Model as configured here yields reliable simulations and can be used for various practical applications.
Investigating the Applicability of a Global Average Calibration Line for Ambient Size-Resolved Cloud Condensation Nuclei (CCN) Measurements: A Technical NoteAbstract
Aerosol–cloud–precipitation interaction represents the largest uncertainty in climate change’s current and future understanding. Therefore, aerosol properties affecting the cloud and precipitation formation and their accurate estimation is a first step in developing improved parameterizations for the prognostic climate models. Over the last couple of decades, a commercially available Cloud Condensation Nuclei Counter (CCNC) has been deployed in the field and laboratory for characterizing CCN properties of ambient or atmospherically relevant laboratory-generated aerosols. However, most of the CCN measurements performed in the field are often compounded with the erroneous estimation of CCN concentration and other parameters due to a lack of robust and accurate CCNC calibration. CCNC is not a plug-and-play instrument and requires prudent calibration and operation, to avoid erroneous data and added parameterization uncertainties. In this work, we propose and demonstrate the usability of a global calibration equation derived from CCNC calibration experiments from 8 contrasting global environments. Significant correlation was observed between the global calibration and each of the 16 individual experiments. A significant improvement in the correlation was observed when the calibration experiments were separated for high-altitude measurements. Using these equations, we further derived the effective hygroscopicity parameter and found lower relative uncertainty in the hygroscopicity parameter at higher effective supersaturation. Our results signify that altitude-based pressure change could be of importance for accurate calibration at high-altitude locations. Our results are consistent with previous studies emphasizing the criticality of the accurate CCN calibration for the lower supersaturations.
Abstract
Aerosol–cloud–precipitation interaction represents the largest uncertainty in climate change’s current and future understanding. Therefore, aerosol properties affecting the cloud and precipitation formation and their accurate estimation is a first step in developing improved parameterizations for the prognostic climate models. Over the last couple of decades, a commercially available Cloud Condensation Nuclei Counter (CCNC) has been deployed in the field and laboratory for characterizing CCN properties of ambient or atmospherically relevant laboratory-generated aerosols. However, most of the CCN measurements performed in the field are often compounded with the erroneous estimation of CCN concentration and other parameters due to a lack of robust and accurate CCNC calibration. CCNC is not a plug-and-play instrument and requires prudent calibration and operation, to avoid erroneous data and added parameterization uncertainties. In this work, we propose and demonstrate the usability of a global calibration equation derived from CCNC calibration experiments from 8 contrasting global environments. Significant correlation was observed between the global calibration and each of the 16 individual experiments. A significant improvement in the correlation was observed when the calibration experiments were separated for high-altitude measurements. Using these equations, we further derived the effective hygroscopicity parameter and found lower relative uncertainty in the hygroscopicity parameter at higher effective supersaturation. Our results signify that altitude-based pressure change could be of importance for accurate calibration at high-altitude locations. Our results are consistent with previous studies emphasizing the criticality of the accurate CCN calibration for the lower supersaturations.
Abstract
Ocean state forecast (OSF) along ship routes (OAS) is an advisory service of the Indian National Centre for Ocean Information Services (INCOIS) of the Earth System Science Organization (ESSO) that helps mariners to ensure safe navigation in the Indian Ocean in all seasons as well as in extreme conditions. As there are many users who solely depend on this service for their decision making, it is very important to ensure the reliability and accuracy of the service using the available in situ and satellite observations. This study evaluates the significant wave height (Hs) along the ship track in the Indian Ocean using the ship-mounted wave height meter (SWHM) on board the Oceanographic Research Vessel Sagar Nidhi, and the Cryosat-2 and Jason altimeters. Reliability of the SWHM is confirmed by comparing with collocated buoy and altimeter observations. The comparison along the ship routes using the SWHM shows very good agreement (correlation coefficient > 0.80) in all three oceanic regimes, [the tropical northern Indian Ocean (TNIO), the tropical southern Indian Ocean (TSIO), and extratropical southern Indian Ocean (ETSI)] with respect to the forecasts with a lead time of 48 h. However, the analysis shows ~10% overestimation of forecasted significant wave height in the low wave heights, especially in the TNIO. The forecast is found very reliable and accurate for the three regions during June–September with a higher correlation coefficient (average = 0.88) and a lower scatter index (average = 15%). During other months, overestimation (bias) of lower Hs is visible in the TNIO.
Abstract
Ocean state forecast (OSF) along ship routes (OAS) is an advisory service of the Indian National Centre for Ocean Information Services (INCOIS) of the Earth System Science Organization (ESSO) that helps mariners to ensure safe navigation in the Indian Ocean in all seasons as well as in extreme conditions. As there are many users who solely depend on this service for their decision making, it is very important to ensure the reliability and accuracy of the service using the available in situ and satellite observations. This study evaluates the significant wave height (Hs) along the ship track in the Indian Ocean using the ship-mounted wave height meter (SWHM) on board the Oceanographic Research Vessel Sagar Nidhi, and the Cryosat-2 and Jason altimeters. Reliability of the SWHM is confirmed by comparing with collocated buoy and altimeter observations. The comparison along the ship routes using the SWHM shows very good agreement (correlation coefficient > 0.80) in all three oceanic regimes, [the tropical northern Indian Ocean (TNIO), the tropical southern Indian Ocean (TSIO), and extratropical southern Indian Ocean (ETSI)] with respect to the forecasts with a lead time of 48 h. However, the analysis shows ~10% overestimation of forecasted significant wave height in the low wave heights, especially in the TNIO. The forecast is found very reliable and accurate for the three regions during June–September with a higher correlation coefficient (average = 0.88) and a lower scatter index (average = 15%). During other months, overestimation (bias) of lower Hs is visible in the TNIO.
Community Global Observing System Simulation Experiment (OSSE) Package (CGOP): Description and UsageAbstract
A modular extensible framework for conducting observing system simulation experiments (OSSEs) has been developed with the goals of 1) supporting decision-makers with quantitative assessments of proposed observing systems investments, 2) supporting readiness for new sensors, 3) enhancing collaboration across the community by making the most up-to-date OSSE components accessible, and 4) advancing the theory and practical application of OSSEs. This first implementation, the Community Global OSSE Package (CGOP), is for short- to medium-range global numerical weather prediction applications. The CGOP is based on a new mesoscale global nature run produced by NASA using the 7-km cubed sphere version of the Goddard Earth Observing System, version 5 (GEOS-5), atmospheric general circulation model and the January 2015 operational version of the NOAA global data assimilation (DA) system. CGOP includes procedures to simulate the full suite of observing systems used operationally in the global DA system, including conventional in situ, satellite-based radiance, and radio occultation observations. The methodology of adding a new proposed observation type is documented and illustrated with examples of current interest. The CGOP is designed to evolve, both to improve its realism and to keep pace with the advance of operational systems.
Abstract
A modular extensible framework for conducting observing system simulation experiments (OSSEs) has been developed with the goals of 1) supporting decision-makers with quantitative assessments of proposed observing systems investments, 2) supporting readiness for new sensors, 3) enhancing collaboration across the community by making the most up-to-date OSSE components accessible, and 4) advancing the theory and practical application of OSSEs. This first implementation, the Community Global OSSE Package (CGOP), is for short- to medium-range global numerical weather prediction applications. The CGOP is based on a new mesoscale global nature run produced by NASA using the 7-km cubed sphere version of the Goddard Earth Observing System, version 5 (GEOS-5), atmospheric general circulation model and the January 2015 operational version of the NOAA global data assimilation (DA) system. CGOP includes procedures to simulate the full suite of observing systems used operationally in the global DA system, including conventional in situ, satellite-based radiance, and radio occultation observations. The methodology of adding a new proposed observation type is documented and illustrated with examples of current interest. The CGOP is designed to evolve, both to improve its realism and to keep pace with the advance of operational systems.
