Craig Schwartz, Glen Romine, Kathryn Fossell, Ryan Sobash, Morris Weisman<\/p>\n\n\n\n
https:\/\/doi.org\/10.1175\/MWR-D-16-0410.1<\/a><\/p>\n\n\n\n\n\t\t\t\n\t\t\t\t\n\t\t\t<\/svg>\n\t\t<\/button><\/figure><\/div>\n\n\n\n<\/p>\n\n\n\nAbstract<\/h4>\n\n\n\nPrecipitation forecasts from convection-allowing ensembles with 3- and 1-km horizontal grid spacing were evaluated between 15 May and 15 June 2013 over central and eastern portions of the United States. Probabilistic forecasts produced from 10- and 30-member, 3-km ensembles were consistently better than forecasts from individual 1-km ensemble members. However, 10-member, 1-km probabilistic forecasts usually were best, especially over the first 12 h and at rainfall rates \u2265 5.0 mm h\u22121<\/sup> at later times. Further object-based investigation revealed that better 1-km forecasts at heavier rainfall rates were associated with more accurate placement of mesoscale convective systems compared to 3-km forecasts. The collective results indicate promise for 1-km ensembles once computational resources can support their operational implementation.<\/p>\n\n\n\n\n\n\n\nEvaluation of the High-Resolution Rapid Refresh (HRRR) model using near-surface meteorological and flux observations from northern Alabama<\/h3>\n\n\n\nTemple Lee, Michael Buban, David Turner, Tilden Meyers, Bruce Baker<\/p>\n\n\n\nhttps:\/\/doi.org\/10.1175\/WAF-D-18-0184.1<\/a><\/p>\n\n\n\n\n\t\t\t\n\t\t\t\t\n\t\t\t<\/svg>\n\t\t<\/button><\/figure><\/div>\n\n\n\nAbstract<\/h4>\n\n\n\nThe High-Resolution Rapid Refresh (HRRR) model became operational at the National Centers for Environmental Prediction (NCEP) in 2014 but the HRRR\u2019s performance over certain regions of the coterminous United States has not been well studied. In the present study, we evaluated how well version 2 of the HRRR, which became operational at NCEP in August 2016, simulates the near-surface meteorological fields and the surface energy balance at two locations in northern Alabama. We evaluated the 1-, 3-, 6-, 12-, and 18-h HRRR forecasts, as well as the HRRR\u2019s initial conditions (i.e., the 0-h initial fields) using meteorological and flux observations obtained from two 10-m micrometeorological towers installed near Belle Mina and Cullman, Alabama. During the 8-month model evaluation period, from 1 September 2016 to 30 April 2017, we found that the HRRR accurately simulated the observations of near-surface air and dewpoint temperature (R<\/em>2<\/sup> > 0.95). When comparing the HRRR output with the observed sensible, latent, and ground heat flux at both sites, we found that the agreement was weaker (R<\/em>2<\/sup> \u2248 0.7), and the root-mean-square errors were much larger than those found for the near-surface meteorological variables. These findings help motivate the need for additional work to improve the representation of surface fluxes and their coupling to the atmosphere in future versions of the HRRR to be more physically realistic.<\/p>\n\n\n\n\n\n\n\nThe Use of High-Resolution Sounding Data to Evaluate and Optimize Nonlocal PBL Schemes for Simulating the Slightly Stable Upper Convective Boundary Layer<\/h3>\n\n\n\nXiao-Ming Hu, Ming Xue, Xiaolan Li<\/p>\n\n\n\nhttps:\/\/doi.org\/10.1175\/MWR-D-19-0085.1<\/a><\/p>\n\n\n\n\n\t\t\t\n\t\t\t\t\n\t\t\t<\/svg>\n\t\t<\/button><\/figure><\/div>\n\n\n\nAbstract<\/h4>\n\n\n\nSince the 1950s, a countergradient flux term has been added to some K<\/em>-profile-based first-order PBL schemes, allowing them to simulate the slightly statically stable upper part of the convective boundary layer (CBL) observed in a limited number of aircraft soundings. There is, however, substantial uncertainty in inferring detailed CBL structure, particularly the level of neutral stability (z<\/em>n<\/em><\/sub>), from such a limited number of soundings. In this study, composite profiles of potential temperature are derived from multiyear early afternoon radiosonde data over Beijing, China. The CBLs become slightly stable above z<\/em>n<\/em><\/sub> ~ 0.31\u20130.33z<\/em>i<\/em><\/sub>, where z<\/em>i<\/em><\/sub> is the CBL depth. These composite profiles are used to evaluate two K<\/em>-profile PBL schemes, the Yonsei University (YSU) and Shin\u2013Hong (SH) schemes, and to optimize the latter through parameter calibration. In one-dimensional simulations using the WRF Model, YSU simulates a stable CBL above z<\/em>n<\/em><\/sub> ~ 0.24z<\/em>i<\/em><\/sub>, while default SH simulates a thick superadiabatic lower CBL with z<\/em>n<\/em><\/sub> ~ 0.45z<\/em>i<\/em><\/sub>. Experiments with the analytic solution of a K<\/em>-profile PBL model show that adjusting the countergradient flux profile leads to significant changes in the thermal structure of CBL, informing the calibration of SH. The SH scheme replaces the countergradient heat flux term in its predecessor YSU scheme with a three-layer nonlocal heating profile, with f<\/em>nl<\/sub> specifying the peak value and z*SL specifying the height of this peak value. Increasing f<\/em>nl<\/sub> to 1.1 lowers z<\/em>n<\/em><\/sub>, but to too low a value, while simultaneously increasing z*SL to 0.4 leads to a more appropriate z<\/em>n<\/em><\/sub> ~ 0.36z<\/em>i<\/em><\/sub>. The calibrated SH scheme performs better than YSU and default SH for real CBLs.<\/p>\n\n\n\n\n\n\n\nSensitivity of WRF simulations with the YSU PBL scheme to the lowest model level height for a sea fog event over the Yellow Sea<\/h3>\n\n\n\nYue Yang, Xiao-Ming Hu, Shanhong Gao, Yongming Wang<\/p>\n\n\n\nhttps:\/\/doi.org\/10.1016\/j.atmosres.2018.09.004<\/a><\/p>\n\n\n\n\n\t\t\t\n\t\t\t\t\n\t\t\t<\/svg>\n\t\t<\/button><\/figure>\n\n\n\nAbstract<\/h4>\n\n\n\nThe lowest model level is the interface of energy and mass exchanging between the surface and planetary boundary layer<\/a> (PBL). Previous studies mostly examined the role of the lowest model level height (z<\/em>1<\/sub>) in simulating the continental PBL processes. The impact of z<\/em>1<\/sub> on simulating marine processes (e.g., sea fog), however, remains unclear. The present study explores the sensitivity of the Weather Research and Forecasting (WRF) model with the Yonsei University (YSU) PBL scheme to z<\/em>1<\/sub> for an advection<\/a> fog event occurred on 27 March 2012 over the Yellow Sea. Seven experiments with various z<\/em>1<\/sub> (28, 22, 14, 8, 4, 1 and 0.4\u202fm) are conducted.<\/p>\n\n\n\nEvaluations for the continental PBL indicate that\u00a0z<\/em>1<\/sub>\u00a0below 8\u202fm is irrational in simulating surface temperature and PBL height over land. However, the model with\u00a0z<\/em>1<\/sub>= 8\u202fm gives the best performance in terms of reproducing sea fog. When\u00a0z<\/em>1<\/sub>\u00a0gets below 8\u202fm, the sea fog occurs too early and the fog area is too small. As\u00a0z<\/em>1<\/sub>\u00a0exceeds 8\u202fm, the fog forms too late and the fog area becomes underestimated. These model sensitivities can be explained by the impact of\u00a0z<\/em>1<\/sub>\u00a0on virtual potential temperature at\u00a0z<\/em>1<\/sub>\u00a0[\u03b8<\/em>v<\/em><\/sub>(z<\/em>1<\/sub>)]. Since the heat capacity of the air in the lowest model layer is proportional to\u00a0z<\/em>1<\/sub>, a lower (higher)\u00a0z<\/em>1<\/sub>\u00a0causes a quicker (slower) response of\u00a0\u03b8<\/em>v<\/em><\/sub>(z<\/em>1<\/sub>) to surface cooling, thus leading to an earlier (later) sea fog formation. After the fog onset, especially for a lower\u00a0z<\/em>1<\/sub>, the variation of\u00a0\u03b8<\/em>v<\/em><\/sub>(z<\/em>1<\/sub>) is dominated by turbulent heating that transports warmer air above to the very shallow lowest model layer, resulting in a lower vertical growth and even earlier dissipation of the sea fog.<\/p>\n\n\n\n\n\n\n\nThe effect of surface drag strength on mesocyclone intensification and tornadogenesis in idealized supercell simulations<\/h3>\n\n\n\nBrett Roberts, Ming Xue, <\/p>\n\n\n\nhttps:\/\/doi.org\/10.1175\/JAS-D-19-0109.1<\/a><\/p>\n\n\n\n\n\t\t\t\n\t\t\t\t\n\t\t\t<\/svg>\n\t\t<\/button><\/figure><\/div>\n\n\n\nAbstract<\/h4>\n\n\n\nA suite of six idealized supercell simulations is performed in which the surface drag coefficient\u00a0C<\/em>d<\/em><\/sub>\u00a0is varied over a range of values from 0 to 0.05 to represent a variety of water and land surfaces. The experiments employ a new technique for enforcing a three-force balance among the pressure gradient, Coriolis, and frictional forces so that the environmental wind profile can remain unchanged throughout the simulation. The initial low-level mesocyclone lowers toward the ground, intensifies, and produces a tornado in all experiments with\u00a0C<\/em>d<\/em><\/sub>\u00a0\u2265 0.002, with the intensification occurring earlier for larger\u00a0C<\/em>d<\/em><\/sub>. In the experiment with\u00a0C<\/em>d<\/em><\/sub>\u00a0= 0, the low-level mesocyclone remains comparatively weak throughout the simulation and does not produce a tornado. Vertical cross sections through the simulated tornadoes reveal an axial downdraft that reaches the ground only in experiments with smaller\u00a0C<\/em>d<\/em><\/sub>, as well as stronger corner flow in experiments with larger\u00a0C<\/em>d<\/em><\/sub>. Material circuits are initialized enclosing the low-level mesocyclone in each experiment and traced backward in time. Circulation budgets for these circuits implicate surface drag acting in the inflow sector of the supercell as having generated important positive circulation, and its relative contribution increases with\u00a0C<\/em>d<\/em><\/sub>. However, the circulation generation is similar in magnitude for the experiments with\u00a0C<\/em>d<\/em><\/sub>\u00a0= 0.02 and 0.05, and the tornado in the latter experiment is weaker. This suggests the possible existence of an optimal range of\u00a0C<\/em>d<\/em><\/sub>\u00a0values for promoting intense tornadoes within our experimental configuration.<\/p>\n\n\n\n\n","protected":false},"excerpt":{"rendered":"Toward 1-km Ensemble Forecasts over Large Domains Craig Schwartz, Glen Romine, Kathryn Fossell, Ryan Sobash, Morris Weisman https:\/\/doi.org\/10.1175\/MWR-D-16-0410.1 Abstract Precipitation forecasts from convection-allowing ensembles with 3- and 1-km horizontal grid… <\/p>\nRead more \u00bb<\/a><\/p>\n","protected":false},"author":129,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-368","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/inside.nssl.noaa.gov\/vsecommunity\/wp-json\/wp\/v2\/pages\/368","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/inside.nssl.noaa.gov\/vsecommunity\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/inside.nssl.noaa.gov\/vsecommunity\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/inside.nssl.noaa.gov\/vsecommunity\/wp-json\/wp\/v2\/users\/129"}],"replies":[{"embeddable":true,"href":"https:\/\/inside.nssl.noaa.gov\/vsecommunity\/wp-json\/wp\/v2\/comments?post=368"}],"version-history":[{"count":6,"href":"https:\/\/inside.nssl.noaa.gov\/vsecommunity\/wp-json\/wp\/v2\/pages\/368\/revisions"}],"predecessor-version":[{"id":438,"href":"https:\/\/inside.nssl.noaa.gov\/vsecommunity\/wp-json\/wp\/v2\/pages\/368\/revisions\/438"}],"wp:attachment":[{"href":"https:\/\/inside.nssl.noaa.gov\/vsecommunity\/wp-json\/wp\/v2\/media?parent=368"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}
<\/p>\n\n\n\n
Precipitation forecasts from convection-allowing ensembles with 3- and 1-km horizontal grid spacing were evaluated between 15 May and 15 June 2013 over central and eastern portions of the United States. Probabilistic forecasts produced from 10- and 30-member, 3-km ensembles were consistently better than forecasts from individual 1-km ensemble members. However, 10-member, 1-km probabilistic forecasts usually were best, especially over the first 12 h and at rainfall rates \u2265 5.0 mm h\u22121<\/sup> at later times. Further object-based investigation revealed that better 1-km forecasts at heavier rainfall rates were associated with more accurate placement of mesoscale convective systems compared to 3-km forecasts. The collective results indicate promise for 1-km ensembles once computational resources can support their operational implementation.<\/p>\n\n\n\n\n\n\n\nEvaluation of the High-Resolution Rapid Refresh (HRRR) model using near-surface meteorological and flux observations from northern Alabama<\/h3>\n\n\n\nTemple Lee, Michael Buban, David Turner, Tilden Meyers, Bruce Baker<\/p>\n\n\n\nhttps:\/\/doi.org\/10.1175\/WAF-D-18-0184.1<\/a><\/p>\n\n\n\n\n\t\t\t\n\t\t\t\t\n\t\t\t<\/svg>\n\t\t<\/button><\/figure><\/div>\n\n\n\nAbstract<\/h4>\n\n\n\nThe High-Resolution Rapid Refresh (HRRR) model became operational at the National Centers for Environmental Prediction (NCEP) in 2014 but the HRRR\u2019s performance over certain regions of the coterminous United States has not been well studied. In the present study, we evaluated how well version 2 of the HRRR, which became operational at NCEP in August 2016, simulates the near-surface meteorological fields and the surface energy balance at two locations in northern Alabama. We evaluated the 1-, 3-, 6-, 12-, and 18-h HRRR forecasts, as well as the HRRR\u2019s initial conditions (i.e., the 0-h initial fields) using meteorological and flux observations obtained from two 10-m micrometeorological towers installed near Belle Mina and Cullman, Alabama. During the 8-month model evaluation period, from 1 September 2016 to 30 April 2017, we found that the HRRR accurately simulated the observations of near-surface air and dewpoint temperature (R<\/em>2<\/sup> > 0.95). When comparing the HRRR output with the observed sensible, latent, and ground heat flux at both sites, we found that the agreement was weaker (R<\/em>2<\/sup> \u2248 0.7), and the root-mean-square errors were much larger than those found for the near-surface meteorological variables. These findings help motivate the need for additional work to improve the representation of surface fluxes and their coupling to the atmosphere in future versions of the HRRR to be more physically realistic.<\/p>\n\n\n\n\n\n\n\nThe Use of High-Resolution Sounding Data to Evaluate and Optimize Nonlocal PBL Schemes for Simulating the Slightly Stable Upper Convective Boundary Layer<\/h3>\n\n\n\nXiao-Ming Hu, Ming Xue, Xiaolan Li<\/p>\n\n\n\nhttps:\/\/doi.org\/10.1175\/MWR-D-19-0085.1<\/a><\/p>\n\n\n\n\n\t\t\t\n\t\t\t\t\n\t\t\t<\/svg>\n\t\t<\/button><\/figure><\/div>\n\n\n\nAbstract<\/h4>\n\n\n\nSince the 1950s, a countergradient flux term has been added to some K<\/em>-profile-based first-order PBL schemes, allowing them to simulate the slightly statically stable upper part of the convective boundary layer (CBL) observed in a limited number of aircraft soundings. There is, however, substantial uncertainty in inferring detailed CBL structure, particularly the level of neutral stability (z<\/em>n<\/em><\/sub>), from such a limited number of soundings. In this study, composite profiles of potential temperature are derived from multiyear early afternoon radiosonde data over Beijing, China. The CBLs become slightly stable above z<\/em>n<\/em><\/sub> ~ 0.31\u20130.33z<\/em>i<\/em><\/sub>, where z<\/em>i<\/em><\/sub> is the CBL depth. These composite profiles are used to evaluate two K<\/em>-profile PBL schemes, the Yonsei University (YSU) and Shin\u2013Hong (SH) schemes, and to optimize the latter through parameter calibration. In one-dimensional simulations using the WRF Model, YSU simulates a stable CBL above z<\/em>n<\/em><\/sub> ~ 0.24z<\/em>i<\/em><\/sub>, while default SH simulates a thick superadiabatic lower CBL with z<\/em>n<\/em><\/sub> ~ 0.45z<\/em>i<\/em><\/sub>. Experiments with the analytic solution of a K<\/em>-profile PBL model show that adjusting the countergradient flux profile leads to significant changes in the thermal structure of CBL, informing the calibration of SH. The SH scheme replaces the countergradient heat flux term in its predecessor YSU scheme with a three-layer nonlocal heating profile, with f<\/em>nl<\/sub> specifying the peak value and z*SL specifying the height of this peak value. Increasing f<\/em>nl<\/sub> to 1.1 lowers z<\/em>n<\/em><\/sub>, but to too low a value, while simultaneously increasing z*SL to 0.4 leads to a more appropriate z<\/em>n<\/em><\/sub> ~ 0.36z<\/em>i<\/em><\/sub>. The calibrated SH scheme performs better than YSU and default SH for real CBLs.<\/p>\n\n\n\n\n\n\n\nSensitivity of WRF simulations with the YSU PBL scheme to the lowest model level height for a sea fog event over the Yellow Sea<\/h3>\n\n\n\nYue Yang, Xiao-Ming Hu, Shanhong Gao, Yongming Wang<\/p>\n\n\n\nhttps:\/\/doi.org\/10.1016\/j.atmosres.2018.09.004<\/a><\/p>\n\n\n\n\n\t\t\t\n\t\t\t\t\n\t\t\t<\/svg>\n\t\t<\/button><\/figure>\n\n\n\nAbstract<\/h4>\n\n\n\nThe lowest model level is the interface of energy and mass exchanging between the surface and planetary boundary layer<\/a> (PBL). Previous studies mostly examined the role of the lowest model level height (z<\/em>1<\/sub>) in simulating the continental PBL processes. The impact of z<\/em>1<\/sub> on simulating marine processes (e.g., sea fog), however, remains unclear. The present study explores the sensitivity of the Weather Research and Forecasting (WRF) model with the Yonsei University (YSU) PBL scheme to z<\/em>1<\/sub> for an advection<\/a> fog event occurred on 27 March 2012 over the Yellow Sea. Seven experiments with various z<\/em>1<\/sub> (28, 22, 14, 8, 4, 1 and 0.4\u202fm) are conducted.<\/p>\n\n\n\nEvaluations for the continental PBL indicate that\u00a0z<\/em>1<\/sub>\u00a0below 8\u202fm is irrational in simulating surface temperature and PBL height over land. However, the model with\u00a0z<\/em>1<\/sub>= 8\u202fm gives the best performance in terms of reproducing sea fog. When\u00a0z<\/em>1<\/sub>\u00a0gets below 8\u202fm, the sea fog occurs too early and the fog area is too small. As\u00a0z<\/em>1<\/sub>\u00a0exceeds 8\u202fm, the fog forms too late and the fog area becomes underestimated. These model sensitivities can be explained by the impact of\u00a0z<\/em>1<\/sub>\u00a0on virtual potential temperature at\u00a0z<\/em>1<\/sub>\u00a0[\u03b8<\/em>v<\/em><\/sub>(z<\/em>1<\/sub>)]. Since the heat capacity of the air in the lowest model layer is proportional to\u00a0z<\/em>1<\/sub>, a lower (higher)\u00a0z<\/em>1<\/sub>\u00a0causes a quicker (slower) response of\u00a0\u03b8<\/em>v<\/em><\/sub>(z<\/em>1<\/sub>) to surface cooling, thus leading to an earlier (later) sea fog formation. After the fog onset, especially for a lower\u00a0z<\/em>1<\/sub>, the variation of\u00a0\u03b8<\/em>v<\/em><\/sub>(z<\/em>1<\/sub>) is dominated by turbulent heating that transports warmer air above to the very shallow lowest model layer, resulting in a lower vertical growth and even earlier dissipation of the sea fog.<\/p>\n\n\n\n\n\n\n\nThe effect of surface drag strength on mesocyclone intensification and tornadogenesis in idealized supercell simulations<\/h3>\n\n\n\nBrett Roberts, Ming Xue, <\/p>\n\n\n\nhttps:\/\/doi.org\/10.1175\/JAS-D-19-0109.1<\/a><\/p>\n\n\n\n\n\t\t\t\n\t\t\t\t\n\t\t\t<\/svg>\n\t\t<\/button><\/figure><\/div>\n\n\n\nAbstract<\/h4>\n\n\n\nA suite of six idealized supercell simulations is performed in which the surface drag coefficient\u00a0C<\/em>d<\/em><\/sub>\u00a0is varied over a range of values from 0 to 0.05 to represent a variety of water and land surfaces. The experiments employ a new technique for enforcing a three-force balance among the pressure gradient, Coriolis, and frictional forces so that the environmental wind profile can remain unchanged throughout the simulation. The initial low-level mesocyclone lowers toward the ground, intensifies, and produces a tornado in all experiments with\u00a0C<\/em>d<\/em><\/sub>\u00a0\u2265 0.002, with the intensification occurring earlier for larger\u00a0C<\/em>d<\/em><\/sub>. In the experiment with\u00a0C<\/em>d<\/em><\/sub>\u00a0= 0, the low-level mesocyclone remains comparatively weak throughout the simulation and does not produce a tornado. Vertical cross sections through the simulated tornadoes reveal an axial downdraft that reaches the ground only in experiments with smaller\u00a0C<\/em>d<\/em><\/sub>, as well as stronger corner flow in experiments with larger\u00a0C<\/em>d<\/em><\/sub>. Material circuits are initialized enclosing the low-level mesocyclone in each experiment and traced backward in time. Circulation budgets for these circuits implicate surface drag acting in the inflow sector of the supercell as having generated important positive circulation, and its relative contribution increases with\u00a0C<\/em>d<\/em><\/sub>. However, the circulation generation is similar in magnitude for the experiments with\u00a0C<\/em>d<\/em><\/sub>\u00a0= 0.02 and 0.05, and the tornado in the latter experiment is weaker. This suggests the possible existence of an optimal range of\u00a0C<\/em>d<\/em><\/sub>\u00a0values for promoting intense tornadoes within our experimental configuration.<\/p>\n\n\n\n\n","protected":false},"excerpt":{"rendered":"Toward 1-km Ensemble Forecasts over Large Domains Craig Schwartz, Glen Romine, Kathryn Fossell, Ryan Sobash, Morris Weisman https:\/\/doi.org\/10.1175\/MWR-D-16-0410.1 Abstract Precipitation forecasts from convection-allowing ensembles with 3- and 1-km horizontal grid… <\/p>\nRead more \u00bb<\/a><\/p>\n","protected":false},"author":129,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-368","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/inside.nssl.noaa.gov\/vsecommunity\/wp-json\/wp\/v2\/pages\/368","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/inside.nssl.noaa.gov\/vsecommunity\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/inside.nssl.noaa.gov\/vsecommunity\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/inside.nssl.noaa.gov\/vsecommunity\/wp-json\/wp\/v2\/users\/129"}],"replies":[{"embeddable":true,"href":"https:\/\/inside.nssl.noaa.gov\/vsecommunity\/wp-json\/wp\/v2\/comments?post=368"}],"version-history":[{"count":6,"href":"https:\/\/inside.nssl.noaa.gov\/vsecommunity\/wp-json\/wp\/v2\/pages\/368\/revisions"}],"predecessor-version":[{"id":438,"href":"https:\/\/inside.nssl.noaa.gov\/vsecommunity\/wp-json\/wp\/v2\/pages\/368\/revisions\/438"}],"wp:attachment":[{"href":"https:\/\/inside.nssl.noaa.gov\/vsecommunity\/wp-json\/wp\/v2\/media?parent=368"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}
Temple Lee, Michael Buban, David Turner, Tilden Meyers, Bruce Baker<\/p>\n\n\n\n
https:\/\/doi.org\/10.1175\/WAF-D-18-0184.1<\/a><\/p>\n\n\n\n\n\t\t\t\n\t\t\t\t\n\t\t\t<\/svg>\n\t\t<\/button><\/figure><\/div>\n\n\n\nAbstract<\/h4>\n\n\n\nThe High-Resolution Rapid Refresh (HRRR) model became operational at the National Centers for Environmental Prediction (NCEP) in 2014 but the HRRR\u2019s performance over certain regions of the coterminous United States has not been well studied. In the present study, we evaluated how well version 2 of the HRRR, which became operational at NCEP in August 2016, simulates the near-surface meteorological fields and the surface energy balance at two locations in northern Alabama. We evaluated the 1-, 3-, 6-, 12-, and 18-h HRRR forecasts, as well as the HRRR\u2019s initial conditions (i.e., the 0-h initial fields) using meteorological and flux observations obtained from two 10-m micrometeorological towers installed near Belle Mina and Cullman, Alabama. During the 8-month model evaluation period, from 1 September 2016 to 30 April 2017, we found that the HRRR accurately simulated the observations of near-surface air and dewpoint temperature (R<\/em>2<\/sup> > 0.95). When comparing the HRRR output with the observed sensible, latent, and ground heat flux at both sites, we found that the agreement was weaker (R<\/em>2<\/sup> \u2248 0.7), and the root-mean-square errors were much larger than those found for the near-surface meteorological variables. These findings help motivate the need for additional work to improve the representation of surface fluxes and their coupling to the atmosphere in future versions of the HRRR to be more physically realistic.<\/p>\n\n\n\n\n\n\n\nThe Use of High-Resolution Sounding Data to Evaluate and Optimize Nonlocal PBL Schemes for Simulating the Slightly Stable Upper Convective Boundary Layer<\/h3>\n\n\n\nXiao-Ming Hu, Ming Xue, Xiaolan Li<\/p>\n\n\n\nhttps:\/\/doi.org\/10.1175\/MWR-D-19-0085.1<\/a><\/p>\n\n\n\n\n\t\t\t\n\t\t\t\t\n\t\t\t<\/svg>\n\t\t<\/button><\/figure><\/div>\n\n\n\nAbstract<\/h4>\n\n\n\nSince the 1950s, a countergradient flux term has been added to some K<\/em>-profile-based first-order PBL schemes, allowing them to simulate the slightly statically stable upper part of the convective boundary layer (CBL) observed in a limited number of aircraft soundings. There is, however, substantial uncertainty in inferring detailed CBL structure, particularly the level of neutral stability (z<\/em>n<\/em><\/sub>), from such a limited number of soundings. In this study, composite profiles of potential temperature are derived from multiyear early afternoon radiosonde data over Beijing, China. The CBLs become slightly stable above z<\/em>n<\/em><\/sub> ~ 0.31\u20130.33z<\/em>i<\/em><\/sub>, where z<\/em>i<\/em><\/sub> is the CBL depth. These composite profiles are used to evaluate two K<\/em>-profile PBL schemes, the Yonsei University (YSU) and Shin\u2013Hong (SH) schemes, and to optimize the latter through parameter calibration. In one-dimensional simulations using the WRF Model, YSU simulates a stable CBL above z<\/em>n<\/em><\/sub> ~ 0.24z<\/em>i<\/em><\/sub>, while default SH simulates a thick superadiabatic lower CBL with z<\/em>n<\/em><\/sub> ~ 0.45z<\/em>i<\/em><\/sub>. Experiments with the analytic solution of a K<\/em>-profile PBL model show that adjusting the countergradient flux profile leads to significant changes in the thermal structure of CBL, informing the calibration of SH. The SH scheme replaces the countergradient heat flux term in its predecessor YSU scheme with a three-layer nonlocal heating profile, with f<\/em>nl<\/sub> specifying the peak value and z*SL specifying the height of this peak value. Increasing f<\/em>nl<\/sub> to 1.1 lowers z<\/em>n<\/em><\/sub>, but to too low a value, while simultaneously increasing z*SL to 0.4 leads to a more appropriate z<\/em>n<\/em><\/sub> ~ 0.36z<\/em>i<\/em><\/sub>. The calibrated SH scheme performs better than YSU and default SH for real CBLs.<\/p>\n\n\n\n\n\n\n\nSensitivity of WRF simulations with the YSU PBL scheme to the lowest model level height for a sea fog event over the Yellow Sea<\/h3>\n\n\n\nYue Yang, Xiao-Ming Hu, Shanhong Gao, Yongming Wang<\/p>\n\n\n\nhttps:\/\/doi.org\/10.1016\/j.atmosres.2018.09.004<\/a><\/p>\n\n\n\n\n\t\t\t\n\t\t\t\t\n\t\t\t<\/svg>\n\t\t<\/button><\/figure>\n\n\n\nAbstract<\/h4>\n\n\n\nThe lowest model level is the interface of energy and mass exchanging between the surface and planetary boundary layer<\/a> (PBL). Previous studies mostly examined the role of the lowest model level height (z<\/em>1<\/sub>) in simulating the continental PBL processes. The impact of z<\/em>1<\/sub> on simulating marine processes (e.g., sea fog), however, remains unclear. The present study explores the sensitivity of the Weather Research and Forecasting (WRF) model with the Yonsei University (YSU) PBL scheme to z<\/em>1<\/sub> for an advection<\/a> fog event occurred on 27 March 2012 over the Yellow Sea. Seven experiments with various z<\/em>1<\/sub> (28, 22, 14, 8, 4, 1 and 0.4\u202fm) are conducted.<\/p>\n\n\n\nEvaluations for the continental PBL indicate that\u00a0z<\/em>1<\/sub>\u00a0below 8\u202fm is irrational in simulating surface temperature and PBL height over land. However, the model with\u00a0z<\/em>1<\/sub>= 8\u202fm gives the best performance in terms of reproducing sea fog. When\u00a0z<\/em>1<\/sub>\u00a0gets below 8\u202fm, the sea fog occurs too early and the fog area is too small. As\u00a0z<\/em>1<\/sub>\u00a0exceeds 8\u202fm, the fog forms too late and the fog area becomes underestimated. These model sensitivities can be explained by the impact of\u00a0z<\/em>1<\/sub>\u00a0on virtual potential temperature at\u00a0z<\/em>1<\/sub>\u00a0[\u03b8<\/em>v<\/em><\/sub>(z<\/em>1<\/sub>)]. Since the heat capacity of the air in the lowest model layer is proportional to\u00a0z<\/em>1<\/sub>, a lower (higher)\u00a0z<\/em>1<\/sub>\u00a0causes a quicker (slower) response of\u00a0\u03b8<\/em>v<\/em><\/sub>(z<\/em>1<\/sub>) to surface cooling, thus leading to an earlier (later) sea fog formation. After the fog onset, especially for a lower\u00a0z<\/em>1<\/sub>, the variation of\u00a0\u03b8<\/em>v<\/em><\/sub>(z<\/em>1<\/sub>) is dominated by turbulent heating that transports warmer air above to the very shallow lowest model layer, resulting in a lower vertical growth and even earlier dissipation of the sea fog.<\/p>\n\n\n\n\n\n\n\nThe effect of surface drag strength on mesocyclone intensification and tornadogenesis in idealized supercell simulations<\/h3>\n\n\n\nBrett Roberts, Ming Xue, <\/p>\n\n\n\nhttps:\/\/doi.org\/10.1175\/JAS-D-19-0109.1<\/a><\/p>\n\n\n\n\n\t\t\t\n\t\t\t\t\n\t\t\t<\/svg>\n\t\t<\/button><\/figure><\/div>\n\n\n\nAbstract<\/h4>\n\n\n\nA suite of six idealized supercell simulations is performed in which the surface drag coefficient\u00a0C<\/em>d<\/em><\/sub>\u00a0is varied over a range of values from 0 to 0.05 to represent a variety of water and land surfaces. The experiments employ a new technique for enforcing a three-force balance among the pressure gradient, Coriolis, and frictional forces so that the environmental wind profile can remain unchanged throughout the simulation. The initial low-level mesocyclone lowers toward the ground, intensifies, and produces a tornado in all experiments with\u00a0C<\/em>d<\/em><\/sub>\u00a0\u2265 0.002, with the intensification occurring earlier for larger\u00a0C<\/em>d<\/em><\/sub>. In the experiment with\u00a0C<\/em>d<\/em><\/sub>\u00a0= 0, the low-level mesocyclone remains comparatively weak throughout the simulation and does not produce a tornado. Vertical cross sections through the simulated tornadoes reveal an axial downdraft that reaches the ground only in experiments with smaller\u00a0C<\/em>d<\/em><\/sub>, as well as stronger corner flow in experiments with larger\u00a0C<\/em>d<\/em><\/sub>. Material circuits are initialized enclosing the low-level mesocyclone in each experiment and traced backward in time. Circulation budgets for these circuits implicate surface drag acting in the inflow sector of the supercell as having generated important positive circulation, and its relative contribution increases with\u00a0C<\/em>d<\/em><\/sub>. However, the circulation generation is similar in magnitude for the experiments with\u00a0C<\/em>d<\/em><\/sub>\u00a0= 0.02 and 0.05, and the tornado in the latter experiment is weaker. This suggests the possible existence of an optimal range of\u00a0C<\/em>d<\/em><\/sub>\u00a0values for promoting intense tornadoes within our experimental configuration.<\/p>\n\n\n\n\n","protected":false},"excerpt":{"rendered":"Toward 1-km Ensemble Forecasts over Large Domains Craig Schwartz, Glen Romine, Kathryn Fossell, Ryan Sobash, Morris Weisman https:\/\/doi.org\/10.1175\/MWR-D-16-0410.1 Abstract Precipitation forecasts from convection-allowing ensembles with 3- and 1-km horizontal grid… <\/p>\nRead more \u00bb<\/a><\/p>\n","protected":false},"author":129,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-368","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/inside.nssl.noaa.gov\/vsecommunity\/wp-json\/wp\/v2\/pages\/368","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/inside.nssl.noaa.gov\/vsecommunity\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/inside.nssl.noaa.gov\/vsecommunity\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/inside.nssl.noaa.gov\/vsecommunity\/wp-json\/wp\/v2\/users\/129"}],"replies":[{"embeddable":true,"href":"https:\/\/inside.nssl.noaa.gov\/vsecommunity\/wp-json\/wp\/v2\/comments?post=368"}],"version-history":[{"count":6,"href":"https:\/\/inside.nssl.noaa.gov\/vsecommunity\/wp-json\/wp\/v2\/pages\/368\/revisions"}],"predecessor-version":[{"id":438,"href":"https:\/\/inside.nssl.noaa.gov\/vsecommunity\/wp-json\/wp\/v2\/pages\/368\/revisions\/438"}],"wp:attachment":[{"href":"https:\/\/inside.nssl.noaa.gov\/vsecommunity\/wp-json\/wp\/v2\/media?parent=368"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}
The High-Resolution Rapid Refresh (HRRR) model became operational at the National Centers for Environmental Prediction (NCEP) in 2014 but the HRRR\u2019s performance over certain regions of the coterminous United States has not been well studied. In the present study, we evaluated how well version 2 of the HRRR, which became operational at NCEP in August 2016, simulates the near-surface meteorological fields and the surface energy balance at two locations in northern Alabama. We evaluated the 1-, 3-, 6-, 12-, and 18-h HRRR forecasts, as well as the HRRR\u2019s initial conditions (i.e., the 0-h initial fields) using meteorological and flux observations obtained from two 10-m micrometeorological towers installed near Belle Mina and Cullman, Alabama. During the 8-month model evaluation period, from 1 September 2016 to 30 April 2017, we found that the HRRR accurately simulated the observations of near-surface air and dewpoint temperature (R<\/em>2<\/sup> > 0.95). When comparing the HRRR output with the observed sensible, latent, and ground heat flux at both sites, we found that the agreement was weaker (R<\/em>2<\/sup> \u2248 0.7), and the root-mean-square errors were much larger than those found for the near-surface meteorological variables. These findings help motivate the need for additional work to improve the representation of surface fluxes and their coupling to the atmosphere in future versions of the HRRR to be more physically realistic.<\/p>\n\n\n\n\n\n\n\nThe Use of High-Resolution Sounding Data to Evaluate and Optimize Nonlocal PBL Schemes for Simulating the Slightly Stable Upper Convective Boundary Layer<\/h3>\n\n\n\nXiao-Ming Hu, Ming Xue, Xiaolan Li<\/p>\n\n\n\nhttps:\/\/doi.org\/10.1175\/MWR-D-19-0085.1<\/a><\/p>\n\n\n\n\n\t\t\t\n\t\t\t\t\n\t\t\t<\/svg>\n\t\t<\/button><\/figure><\/div>\n\n\n\nAbstract<\/h4>\n\n\n\nSince the 1950s, a countergradient flux term has been added to some K<\/em>-profile-based first-order PBL schemes, allowing them to simulate the slightly statically stable upper part of the convective boundary layer (CBL) observed in a limited number of aircraft soundings. There is, however, substantial uncertainty in inferring detailed CBL structure, particularly the level of neutral stability (z<\/em>n<\/em><\/sub>), from such a limited number of soundings. In this study, composite profiles of potential temperature are derived from multiyear early afternoon radiosonde data over Beijing, China. The CBLs become slightly stable above z<\/em>n<\/em><\/sub> ~ 0.31\u20130.33z<\/em>i<\/em><\/sub>, where z<\/em>i<\/em><\/sub> is the CBL depth. These composite profiles are used to evaluate two K<\/em>-profile PBL schemes, the Yonsei University (YSU) and Shin\u2013Hong (SH) schemes, and to optimize the latter through parameter calibration. In one-dimensional simulations using the WRF Model, YSU simulates a stable CBL above z<\/em>n<\/em><\/sub> ~ 0.24z<\/em>i<\/em><\/sub>, while default SH simulates a thick superadiabatic lower CBL with z<\/em>n<\/em><\/sub> ~ 0.45z<\/em>i<\/em><\/sub>. Experiments with the analytic solution of a K<\/em>-profile PBL model show that adjusting the countergradient flux profile leads to significant changes in the thermal structure of CBL, informing the calibration of SH. The SH scheme replaces the countergradient heat flux term in its predecessor YSU scheme with a three-layer nonlocal heating profile, with f<\/em>nl<\/sub> specifying the peak value and z*SL specifying the height of this peak value. Increasing f<\/em>nl<\/sub> to 1.1 lowers z<\/em>n<\/em><\/sub>, but to too low a value, while simultaneously increasing z*SL to 0.4 leads to a more appropriate z<\/em>n<\/em><\/sub> ~ 0.36z<\/em>i<\/em><\/sub>. The calibrated SH scheme performs better than YSU and default SH for real CBLs.<\/p>\n\n\n\n\n\n\n\nSensitivity of WRF simulations with the YSU PBL scheme to the lowest model level height for a sea fog event over the Yellow Sea<\/h3>\n\n\n\nYue Yang, Xiao-Ming Hu, Shanhong Gao, Yongming Wang<\/p>\n\n\n\nhttps:\/\/doi.org\/10.1016\/j.atmosres.2018.09.004<\/a><\/p>\n\n\n\n\n\t\t\t\n\t\t\t\t\n\t\t\t<\/svg>\n\t\t<\/button><\/figure>\n\n\n\nAbstract<\/h4>\n\n\n\nThe lowest model level is the interface of energy and mass exchanging between the surface and planetary boundary layer<\/a> (PBL). Previous studies mostly examined the role of the lowest model level height (z<\/em>1<\/sub>) in simulating the continental PBL processes. The impact of z<\/em>1<\/sub> on simulating marine processes (e.g., sea fog), however, remains unclear. The present study explores the sensitivity of the Weather Research and Forecasting (WRF) model with the Yonsei University (YSU) PBL scheme to z<\/em>1<\/sub> for an advection<\/a> fog event occurred on 27 March 2012 over the Yellow Sea. Seven experiments with various z<\/em>1<\/sub> (28, 22, 14, 8, 4, 1 and 0.4\u202fm) are conducted.<\/p>\n\n\n\nEvaluations for the continental PBL indicate that\u00a0z<\/em>1<\/sub>\u00a0below 8\u202fm is irrational in simulating surface temperature and PBL height over land. However, the model with\u00a0z<\/em>1<\/sub>= 8\u202fm gives the best performance in terms of reproducing sea fog. When\u00a0z<\/em>1<\/sub>\u00a0gets below 8\u202fm, the sea fog occurs too early and the fog area is too small. As\u00a0z<\/em>1<\/sub>\u00a0exceeds 8\u202fm, the fog forms too late and the fog area becomes underestimated. These model sensitivities can be explained by the impact of\u00a0z<\/em>1<\/sub>\u00a0on virtual potential temperature at\u00a0z<\/em>1<\/sub>\u00a0[\u03b8<\/em>v<\/em><\/sub>(z<\/em>1<\/sub>)]. Since the heat capacity of the air in the lowest model layer is proportional to\u00a0z<\/em>1<\/sub>, a lower (higher)\u00a0z<\/em>1<\/sub>\u00a0causes a quicker (slower) response of\u00a0\u03b8<\/em>v<\/em><\/sub>(z<\/em>1<\/sub>) to surface cooling, thus leading to an earlier (later) sea fog formation. After the fog onset, especially for a lower\u00a0z<\/em>1<\/sub>, the variation of\u00a0\u03b8<\/em>v<\/em><\/sub>(z<\/em>1<\/sub>) is dominated by turbulent heating that transports warmer air above to the very shallow lowest model layer, resulting in a lower vertical growth and even earlier dissipation of the sea fog.<\/p>\n\n\n\n\n\n\n\nThe effect of surface drag strength on mesocyclone intensification and tornadogenesis in idealized supercell simulations<\/h3>\n\n\n\nBrett Roberts, Ming Xue, <\/p>\n\n\n\nhttps:\/\/doi.org\/10.1175\/JAS-D-19-0109.1<\/a><\/p>\n\n\n\n\n\t\t\t\n\t\t\t\t\n\t\t\t<\/svg>\n\t\t<\/button><\/figure><\/div>\n\n\n\nAbstract<\/h4>\n\n\n\nA suite of six idealized supercell simulations is performed in which the surface drag coefficient\u00a0C<\/em>d<\/em><\/sub>\u00a0is varied over a range of values from 0 to 0.05 to represent a variety of water and land surfaces. The experiments employ a new technique for enforcing a three-force balance among the pressure gradient, Coriolis, and frictional forces so that the environmental wind profile can remain unchanged throughout the simulation. The initial low-level mesocyclone lowers toward the ground, intensifies, and produces a tornado in all experiments with\u00a0C<\/em>d<\/em><\/sub>\u00a0\u2265 0.002, with the intensification occurring earlier for larger\u00a0C<\/em>d<\/em><\/sub>. In the experiment with\u00a0C<\/em>d<\/em><\/sub>\u00a0= 0, the low-level mesocyclone remains comparatively weak throughout the simulation and does not produce a tornado. Vertical cross sections through the simulated tornadoes reveal an axial downdraft that reaches the ground only in experiments with smaller\u00a0C<\/em>d<\/em><\/sub>, as well as stronger corner flow in experiments with larger\u00a0C<\/em>d<\/em><\/sub>. Material circuits are initialized enclosing the low-level mesocyclone in each experiment and traced backward in time. Circulation budgets for these circuits implicate surface drag acting in the inflow sector of the supercell as having generated important positive circulation, and its relative contribution increases with\u00a0C<\/em>d<\/em><\/sub>. However, the circulation generation is similar in magnitude for the experiments with\u00a0C<\/em>d<\/em><\/sub>\u00a0= 0.02 and 0.05, and the tornado in the latter experiment is weaker. This suggests the possible existence of an optimal range of\u00a0C<\/em>d<\/em><\/sub>\u00a0values for promoting intense tornadoes within our experimental configuration.<\/p>\n\n\n\n\n","protected":false},"excerpt":{"rendered":"Toward 1-km Ensemble Forecasts over Large Domains Craig Schwartz, Glen Romine, Kathryn Fossell, Ryan Sobash, Morris Weisman https:\/\/doi.org\/10.1175\/MWR-D-16-0410.1 Abstract Precipitation forecasts from convection-allowing ensembles with 3- and 1-km horizontal grid… <\/p>\nRead more \u00bb<\/a><\/p>\n","protected":false},"author":129,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-368","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/inside.nssl.noaa.gov\/vsecommunity\/wp-json\/wp\/v2\/pages\/368","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/inside.nssl.noaa.gov\/vsecommunity\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/inside.nssl.noaa.gov\/vsecommunity\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/inside.nssl.noaa.gov\/vsecommunity\/wp-json\/wp\/v2\/users\/129"}],"replies":[{"embeddable":true,"href":"https:\/\/inside.nssl.noaa.gov\/vsecommunity\/wp-json\/wp\/v2\/comments?post=368"}],"version-history":[{"count":6,"href":"https:\/\/inside.nssl.noaa.gov\/vsecommunity\/wp-json\/wp\/v2\/pages\/368\/revisions"}],"predecessor-version":[{"id":438,"href":"https:\/\/inside.nssl.noaa.gov\/vsecommunity\/wp-json\/wp\/v2\/pages\/368\/revisions\/438"}],"wp:attachment":[{"href":"https:\/\/inside.nssl.noaa.gov\/vsecommunity\/wp-json\/wp\/v2\/media?parent=368"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}
Xiao-Ming Hu, Ming Xue, Xiaolan Li<\/p>\n\n\n\n
https:\/\/doi.org\/10.1175\/MWR-D-19-0085.1<\/a><\/p>\n\n\n\n\n\t\t\t\n\t\t\t\t\n\t\t\t<\/svg>\n\t\t<\/button><\/figure><\/div>\n\n\n\nAbstract<\/h4>\n\n\n\nSince the 1950s, a countergradient flux term has been added to some K<\/em>-profile-based first-order PBL schemes, allowing them to simulate the slightly statically stable upper part of the convective boundary layer (CBL) observed in a limited number of aircraft soundings. There is, however, substantial uncertainty in inferring detailed CBL structure, particularly the level of neutral stability (z<\/em>n<\/em><\/sub>), from such a limited number of soundings. In this study, composite profiles of potential temperature are derived from multiyear early afternoon radiosonde data over Beijing, China. The CBLs become slightly stable above z<\/em>n<\/em><\/sub> ~ 0.31\u20130.33z<\/em>i<\/em><\/sub>, where z<\/em>i<\/em><\/sub> is the CBL depth. These composite profiles are used to evaluate two K<\/em>-profile PBL schemes, the Yonsei University (YSU) and Shin\u2013Hong (SH) schemes, and to optimize the latter through parameter calibration. In one-dimensional simulations using the WRF Model, YSU simulates a stable CBL above z<\/em>n<\/em><\/sub> ~ 0.24z<\/em>i<\/em><\/sub>, while default SH simulates a thick superadiabatic lower CBL with z<\/em>n<\/em><\/sub> ~ 0.45z<\/em>i<\/em><\/sub>. Experiments with the analytic solution of a K<\/em>-profile PBL model show that adjusting the countergradient flux profile leads to significant changes in the thermal structure of CBL, informing the calibration of SH. The SH scheme replaces the countergradient heat flux term in its predecessor YSU scheme with a three-layer nonlocal heating profile, with f<\/em>nl<\/sub> specifying the peak value and z*SL specifying the height of this peak value. Increasing f<\/em>nl<\/sub> to 1.1 lowers z<\/em>n<\/em><\/sub>, but to too low a value, while simultaneously increasing z*SL to 0.4 leads to a more appropriate z<\/em>n<\/em><\/sub> ~ 0.36z<\/em>i<\/em><\/sub>. The calibrated SH scheme performs better than YSU and default SH for real CBLs.<\/p>\n\n\n\n\n\n\n\nSensitivity of WRF simulations with the YSU PBL scheme to the lowest model level height for a sea fog event over the Yellow Sea<\/h3>\n\n\n\nYue Yang, Xiao-Ming Hu, Shanhong Gao, Yongming Wang<\/p>\n\n\n\nhttps:\/\/doi.org\/10.1016\/j.atmosres.2018.09.004<\/a><\/p>\n\n\n\n\n\t\t\t\n\t\t\t\t\n\t\t\t<\/svg>\n\t\t<\/button><\/figure>\n\n\n\nAbstract<\/h4>\n\n\n\nThe lowest model level is the interface of energy and mass exchanging between the surface and planetary boundary layer<\/a> (PBL). Previous studies mostly examined the role of the lowest model level height (z<\/em>1<\/sub>) in simulating the continental PBL processes. The impact of z<\/em>1<\/sub> on simulating marine processes (e.g., sea fog), however, remains unclear. The present study explores the sensitivity of the Weather Research and Forecasting (WRF) model with the Yonsei University (YSU) PBL scheme to z<\/em>1<\/sub> for an advection<\/a> fog event occurred on 27 March 2012 over the Yellow Sea. Seven experiments with various z<\/em>1<\/sub> (28, 22, 14, 8, 4, 1 and 0.4\u202fm) are conducted.<\/p>\n\n\n\nEvaluations for the continental PBL indicate that\u00a0z<\/em>1<\/sub>\u00a0below 8\u202fm is irrational in simulating surface temperature and PBL height over land. However, the model with\u00a0z<\/em>1<\/sub>= 8\u202fm gives the best performance in terms of reproducing sea fog. When\u00a0z<\/em>1<\/sub>\u00a0gets below 8\u202fm, the sea fog occurs too early and the fog area is too small. As\u00a0z<\/em>1<\/sub>\u00a0exceeds 8\u202fm, the fog forms too late and the fog area becomes underestimated. These model sensitivities can be explained by the impact of\u00a0z<\/em>1<\/sub>\u00a0on virtual potential temperature at\u00a0z<\/em>1<\/sub>\u00a0[\u03b8<\/em>v<\/em><\/sub>(z<\/em>1<\/sub>)]. Since the heat capacity of the air in the lowest model layer is proportional to\u00a0z<\/em>1<\/sub>, a lower (higher)\u00a0z<\/em>1<\/sub>\u00a0causes a quicker (slower) response of\u00a0\u03b8<\/em>v<\/em><\/sub>(z<\/em>1<\/sub>) to surface cooling, thus leading to an earlier (later) sea fog formation. After the fog onset, especially for a lower\u00a0z<\/em>1<\/sub>, the variation of\u00a0\u03b8<\/em>v<\/em><\/sub>(z<\/em>1<\/sub>) is dominated by turbulent heating that transports warmer air above to the very shallow lowest model layer, resulting in a lower vertical growth and even earlier dissipation of the sea fog.<\/p>\n\n\n\n\n\n\n\nThe effect of surface drag strength on mesocyclone intensification and tornadogenesis in idealized supercell simulations<\/h3>\n\n\n\nBrett Roberts, Ming Xue, <\/p>\n\n\n\nhttps:\/\/doi.org\/10.1175\/JAS-D-19-0109.1<\/a><\/p>\n\n\n\n\n\t\t\t\n\t\t\t\t\n\t\t\t<\/svg>\n\t\t<\/button><\/figure><\/div>\n\n\n\nAbstract<\/h4>\n\n\n\nA suite of six idealized supercell simulations is performed in which the surface drag coefficient\u00a0C<\/em>d<\/em><\/sub>\u00a0is varied over a range of values from 0 to 0.05 to represent a variety of water and land surfaces. The experiments employ a new technique for enforcing a three-force balance among the pressure gradient, Coriolis, and frictional forces so that the environmental wind profile can remain unchanged throughout the simulation. The initial low-level mesocyclone lowers toward the ground, intensifies, and produces a tornado in all experiments with\u00a0C<\/em>d<\/em><\/sub>\u00a0\u2265 0.002, with the intensification occurring earlier for larger\u00a0C<\/em>d<\/em><\/sub>. In the experiment with\u00a0C<\/em>d<\/em><\/sub>\u00a0= 0, the low-level mesocyclone remains comparatively weak throughout the simulation and does not produce a tornado. Vertical cross sections through the simulated tornadoes reveal an axial downdraft that reaches the ground only in experiments with smaller\u00a0C<\/em>d<\/em><\/sub>, as well as stronger corner flow in experiments with larger\u00a0C<\/em>d<\/em><\/sub>. Material circuits are initialized enclosing the low-level mesocyclone in each experiment and traced backward in time. Circulation budgets for these circuits implicate surface drag acting in the inflow sector of the supercell as having generated important positive circulation, and its relative contribution increases with\u00a0C<\/em>d<\/em><\/sub>. However, the circulation generation is similar in magnitude for the experiments with\u00a0C<\/em>d<\/em><\/sub>\u00a0= 0.02 and 0.05, and the tornado in the latter experiment is weaker. This suggests the possible existence of an optimal range of\u00a0C<\/em>d<\/em><\/sub>\u00a0values for promoting intense tornadoes within our experimental configuration.<\/p>\n\n\n\n\n","protected":false},"excerpt":{"rendered":"Toward 1-km Ensemble Forecasts over Large Domains Craig Schwartz, Glen Romine, Kathryn Fossell, Ryan Sobash, Morris Weisman https:\/\/doi.org\/10.1175\/MWR-D-16-0410.1 Abstract Precipitation forecasts from convection-allowing ensembles with 3- and 1-km horizontal grid… <\/p>\nRead more \u00bb<\/a><\/p>\n","protected":false},"author":129,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-368","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/inside.nssl.noaa.gov\/vsecommunity\/wp-json\/wp\/v2\/pages\/368","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/inside.nssl.noaa.gov\/vsecommunity\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/inside.nssl.noaa.gov\/vsecommunity\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/inside.nssl.noaa.gov\/vsecommunity\/wp-json\/wp\/v2\/users\/129"}],"replies":[{"embeddable":true,"href":"https:\/\/inside.nssl.noaa.gov\/vsecommunity\/wp-json\/wp\/v2\/comments?post=368"}],"version-history":[{"count":6,"href":"https:\/\/inside.nssl.noaa.gov\/vsecommunity\/wp-json\/wp\/v2\/pages\/368\/revisions"}],"predecessor-version":[{"id":438,"href":"https:\/\/inside.nssl.noaa.gov\/vsecommunity\/wp-json\/wp\/v2\/pages\/368\/revisions\/438"}],"wp:attachment":[{"href":"https:\/\/inside.nssl.noaa.gov\/vsecommunity\/wp-json\/wp\/v2\/media?parent=368"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}
Since the 1950s, a countergradient flux term has been added to some K<\/em>-profile-based first-order PBL schemes, allowing them to simulate the slightly statically stable upper part of the convective boundary layer (CBL) observed in a limited number of aircraft soundings. There is, however, substantial uncertainty in inferring detailed CBL structure, particularly the level of neutral stability (z<\/em>n<\/em><\/sub>), from such a limited number of soundings. In this study, composite profiles of potential temperature are derived from multiyear early afternoon radiosonde data over Beijing, China. The CBLs become slightly stable above z<\/em>n<\/em><\/sub> ~ 0.31\u20130.33z<\/em>i<\/em><\/sub>, where z<\/em>i<\/em><\/sub> is the CBL depth. These composite profiles are used to evaluate two K<\/em>-profile PBL schemes, the Yonsei University (YSU) and Shin\u2013Hong (SH) schemes, and to optimize the latter through parameter calibration. In one-dimensional simulations using the WRF Model, YSU simulates a stable CBL above z<\/em>n<\/em><\/sub> ~ 0.24z<\/em>i<\/em><\/sub>, while default SH simulates a thick superadiabatic lower CBL with z<\/em>n<\/em><\/sub> ~ 0.45z<\/em>i<\/em><\/sub>. Experiments with the analytic solution of a K<\/em>-profile PBL model show that adjusting the countergradient flux profile leads to significant changes in the thermal structure of CBL, informing the calibration of SH. The SH scheme replaces the countergradient heat flux term in its predecessor YSU scheme with a three-layer nonlocal heating profile, with f<\/em>nl<\/sub> specifying the peak value and z*SL specifying the height of this peak value. Increasing f<\/em>nl<\/sub> to 1.1 lowers z<\/em>n<\/em><\/sub>, but to too low a value, while simultaneously increasing z*SL to 0.4 leads to a more appropriate z<\/em>n<\/em><\/sub> ~ 0.36z<\/em>i<\/em><\/sub>. The calibrated SH scheme performs better than YSU and default SH for real CBLs.<\/p>\n\n\n\n\n\n\n\nSensitivity of WRF simulations with the YSU PBL scheme to the lowest model level height for a sea fog event over the Yellow Sea<\/h3>\n\n\n\nYue Yang, Xiao-Ming Hu, Shanhong Gao, Yongming Wang<\/p>\n\n\n\nhttps:\/\/doi.org\/10.1016\/j.atmosres.2018.09.004<\/a><\/p>\n\n\n\n\n\t\t\t\n\t\t\t\t\n\t\t\t<\/svg>\n\t\t<\/button><\/figure>\n\n\n\nAbstract<\/h4>\n\n\n\nThe lowest model level is the interface of energy and mass exchanging between the surface and planetary boundary layer<\/a> (PBL). Previous studies mostly examined the role of the lowest model level height (z<\/em>1<\/sub>) in simulating the continental PBL processes. The impact of z<\/em>1<\/sub> on simulating marine processes (e.g., sea fog), however, remains unclear. The present study explores the sensitivity of the Weather Research and Forecasting (WRF) model with the Yonsei University (YSU) PBL scheme to z<\/em>1<\/sub> for an advection<\/a> fog event occurred on 27 March 2012 over the Yellow Sea. Seven experiments with various z<\/em>1<\/sub> (28, 22, 14, 8, 4, 1 and 0.4\u202fm) are conducted.<\/p>\n\n\n\nEvaluations for the continental PBL indicate that\u00a0z<\/em>1<\/sub>\u00a0below 8\u202fm is irrational in simulating surface temperature and PBL height over land. However, the model with\u00a0z<\/em>1<\/sub>= 8\u202fm gives the best performance in terms of reproducing sea fog. When\u00a0z<\/em>1<\/sub>\u00a0gets below 8\u202fm, the sea fog occurs too early and the fog area is too small. As\u00a0z<\/em>1<\/sub>\u00a0exceeds 8\u202fm, the fog forms too late and the fog area becomes underestimated. These model sensitivities can be explained by the impact of\u00a0z<\/em>1<\/sub>\u00a0on virtual potential temperature at\u00a0z<\/em>1<\/sub>\u00a0[\u03b8<\/em>v<\/em><\/sub>(z<\/em>1<\/sub>)]. Since the heat capacity of the air in the lowest model layer is proportional to\u00a0z<\/em>1<\/sub>, a lower (higher)\u00a0z<\/em>1<\/sub>\u00a0causes a quicker (slower) response of\u00a0\u03b8<\/em>v<\/em><\/sub>(z<\/em>1<\/sub>) to surface cooling, thus leading to an earlier (later) sea fog formation. After the fog onset, especially for a lower\u00a0z<\/em>1<\/sub>, the variation of\u00a0\u03b8<\/em>v<\/em><\/sub>(z<\/em>1<\/sub>) is dominated by turbulent heating that transports warmer air above to the very shallow lowest model layer, resulting in a lower vertical growth and even earlier dissipation of the sea fog.<\/p>\n\n\n\n\n\n\n\nThe effect of surface drag strength on mesocyclone intensification and tornadogenesis in idealized supercell simulations<\/h3>\n\n\n\nBrett Roberts, Ming Xue, <\/p>\n\n\n\nhttps:\/\/doi.org\/10.1175\/JAS-D-19-0109.1<\/a><\/p>\n\n\n\n\n\t\t\t\n\t\t\t\t\n\t\t\t<\/svg>\n\t\t<\/button><\/figure><\/div>\n\n\n\nAbstract<\/h4>\n\n\n\nA suite of six idealized supercell simulations is performed in which the surface drag coefficient\u00a0C<\/em>d<\/em><\/sub>\u00a0is varied over a range of values from 0 to 0.05 to represent a variety of water and land surfaces. The experiments employ a new technique for enforcing a three-force balance among the pressure gradient, Coriolis, and frictional forces so that the environmental wind profile can remain unchanged throughout the simulation. The initial low-level mesocyclone lowers toward the ground, intensifies, and produces a tornado in all experiments with\u00a0C<\/em>d<\/em><\/sub>\u00a0\u2265 0.002, with the intensification occurring earlier for larger\u00a0C<\/em>d<\/em><\/sub>. In the experiment with\u00a0C<\/em>d<\/em><\/sub>\u00a0= 0, the low-level mesocyclone remains comparatively weak throughout the simulation and does not produce a tornado. Vertical cross sections through the simulated tornadoes reveal an axial downdraft that reaches the ground only in experiments with smaller\u00a0C<\/em>d<\/em><\/sub>, as well as stronger corner flow in experiments with larger\u00a0C<\/em>d<\/em><\/sub>. Material circuits are initialized enclosing the low-level mesocyclone in each experiment and traced backward in time. Circulation budgets for these circuits implicate surface drag acting in the inflow sector of the supercell as having generated important positive circulation, and its relative contribution increases with\u00a0C<\/em>d<\/em><\/sub>. However, the circulation generation is similar in magnitude for the experiments with\u00a0C<\/em>d<\/em><\/sub>\u00a0= 0.02 and 0.05, and the tornado in the latter experiment is weaker. This suggests the possible existence of an optimal range of\u00a0C<\/em>d<\/em><\/sub>\u00a0values for promoting intense tornadoes within our experimental configuration.<\/p>\n\n\n\n\n","protected":false},"excerpt":{"rendered":"Toward 1-km Ensemble Forecasts over Large Domains Craig Schwartz, Glen Romine, Kathryn Fossell, Ryan Sobash, Morris Weisman https:\/\/doi.org\/10.1175\/MWR-D-16-0410.1 Abstract Precipitation forecasts from convection-allowing ensembles with 3- and 1-km horizontal grid… <\/p>\nRead more \u00bb<\/a><\/p>\n","protected":false},"author":129,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-368","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/inside.nssl.noaa.gov\/vsecommunity\/wp-json\/wp\/v2\/pages\/368","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/inside.nssl.noaa.gov\/vsecommunity\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/inside.nssl.noaa.gov\/vsecommunity\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/inside.nssl.noaa.gov\/vsecommunity\/wp-json\/wp\/v2\/users\/129"}],"replies":[{"embeddable":true,"href":"https:\/\/inside.nssl.noaa.gov\/vsecommunity\/wp-json\/wp\/v2\/comments?post=368"}],"version-history":[{"count":6,"href":"https:\/\/inside.nssl.noaa.gov\/vsecommunity\/wp-json\/wp\/v2\/pages\/368\/revisions"}],"predecessor-version":[{"id":438,"href":"https:\/\/inside.nssl.noaa.gov\/vsecommunity\/wp-json\/wp\/v2\/pages\/368\/revisions\/438"}],"wp:attachment":[{"href":"https:\/\/inside.nssl.noaa.gov\/vsecommunity\/wp-json\/wp\/v2\/media?parent=368"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}
Yue Yang, Xiao-Ming Hu, Shanhong Gao, Yongming Wang<\/p>\n\n\n\n
https:\/\/doi.org\/10.1016\/j.atmosres.2018.09.004<\/a><\/p>\n\n\n\n\n\t\t\t\n\t\t\t\t\n\t\t\t<\/svg>\n\t\t<\/button><\/figure>\n\n\n\nAbstract<\/h4>\n\n\n\nThe lowest model level is the interface of energy and mass exchanging between the surface and planetary boundary layer<\/a> (PBL). Previous studies mostly examined the role of the lowest model level height (z<\/em>1<\/sub>) in simulating the continental PBL processes. The impact of z<\/em>1<\/sub> on simulating marine processes (e.g., sea fog), however, remains unclear. The present study explores the sensitivity of the Weather Research and Forecasting (WRF) model with the Yonsei University (YSU) PBL scheme to z<\/em>1<\/sub> for an advection<\/a> fog event occurred on 27 March 2012 over the Yellow Sea. Seven experiments with various z<\/em>1<\/sub> (28, 22, 14, 8, 4, 1 and 0.4\u202fm) are conducted.<\/p>\n\n\n\nEvaluations for the continental PBL indicate that\u00a0z<\/em>1<\/sub>\u00a0below 8\u202fm is irrational in simulating surface temperature and PBL height over land. However, the model with\u00a0z<\/em>1<\/sub>= 8\u202fm gives the best performance in terms of reproducing sea fog. When\u00a0z<\/em>1<\/sub>\u00a0gets below 8\u202fm, the sea fog occurs too early and the fog area is too small. As\u00a0z<\/em>1<\/sub>\u00a0exceeds 8\u202fm, the fog forms too late and the fog area becomes underestimated. These model sensitivities can be explained by the impact of\u00a0z<\/em>1<\/sub>\u00a0on virtual potential temperature at\u00a0z<\/em>1<\/sub>\u00a0[\u03b8<\/em>v<\/em><\/sub>(z<\/em>1<\/sub>)]. Since the heat capacity of the air in the lowest model layer is proportional to\u00a0z<\/em>1<\/sub>, a lower (higher)\u00a0z<\/em>1<\/sub>\u00a0causes a quicker (slower) response of\u00a0\u03b8<\/em>v<\/em><\/sub>(z<\/em>1<\/sub>) to surface cooling, thus leading to an earlier (later) sea fog formation. After the fog onset, especially for a lower\u00a0z<\/em>1<\/sub>, the variation of\u00a0\u03b8<\/em>v<\/em><\/sub>(z<\/em>1<\/sub>) is dominated by turbulent heating that transports warmer air above to the very shallow lowest model layer, resulting in a lower vertical growth and even earlier dissipation of the sea fog.<\/p>\n\n\n\n\n\n\n\nThe effect of surface drag strength on mesocyclone intensification and tornadogenesis in idealized supercell simulations<\/h3>\n\n\n\nBrett Roberts, Ming Xue, <\/p>\n\n\n\nhttps:\/\/doi.org\/10.1175\/JAS-D-19-0109.1<\/a><\/p>\n\n\n\n\n\t\t\t\n\t\t\t\t\n\t\t\t<\/svg>\n\t\t<\/button><\/figure><\/div>\n\n\n\nAbstract<\/h4>\n\n\n\nA suite of six idealized supercell simulations is performed in which the surface drag coefficient\u00a0C<\/em>d<\/em><\/sub>\u00a0is varied over a range of values from 0 to 0.05 to represent a variety of water and land surfaces. The experiments employ a new technique for enforcing a three-force balance among the pressure gradient, Coriolis, and frictional forces so that the environmental wind profile can remain unchanged throughout the simulation. The initial low-level mesocyclone lowers toward the ground, intensifies, and produces a tornado in all experiments with\u00a0C<\/em>d<\/em><\/sub>\u00a0\u2265 0.002, with the intensification occurring earlier for larger\u00a0C<\/em>d<\/em><\/sub>. In the experiment with\u00a0C<\/em>d<\/em><\/sub>\u00a0= 0, the low-level mesocyclone remains comparatively weak throughout the simulation and does not produce a tornado. Vertical cross sections through the simulated tornadoes reveal an axial downdraft that reaches the ground only in experiments with smaller\u00a0C<\/em>d<\/em><\/sub>, as well as stronger corner flow in experiments with larger\u00a0C<\/em>d<\/em><\/sub>. Material circuits are initialized enclosing the low-level mesocyclone in each experiment and traced backward in time. Circulation budgets for these circuits implicate surface drag acting in the inflow sector of the supercell as having generated important positive circulation, and its relative contribution increases with\u00a0C<\/em>d<\/em><\/sub>. However, the circulation generation is similar in magnitude for the experiments with\u00a0C<\/em>d<\/em><\/sub>\u00a0= 0.02 and 0.05, and the tornado in the latter experiment is weaker. This suggests the possible existence of an optimal range of\u00a0C<\/em>d<\/em><\/sub>\u00a0values for promoting intense tornadoes within our experimental configuration.<\/p>\n\n\n\n\n","protected":false},"excerpt":{"rendered":"Toward 1-km Ensemble Forecasts over Large Domains Craig Schwartz, Glen Romine, Kathryn Fossell, Ryan Sobash, Morris Weisman https:\/\/doi.org\/10.1175\/MWR-D-16-0410.1 Abstract Precipitation forecasts from convection-allowing ensembles with 3- and 1-km horizontal grid… <\/p>\nRead more \u00bb<\/a><\/p>\n","protected":false},"author":129,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-368","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/inside.nssl.noaa.gov\/vsecommunity\/wp-json\/wp\/v2\/pages\/368","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/inside.nssl.noaa.gov\/vsecommunity\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/inside.nssl.noaa.gov\/vsecommunity\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/inside.nssl.noaa.gov\/vsecommunity\/wp-json\/wp\/v2\/users\/129"}],"replies":[{"embeddable":true,"href":"https:\/\/inside.nssl.noaa.gov\/vsecommunity\/wp-json\/wp\/v2\/comments?post=368"}],"version-history":[{"count":6,"href":"https:\/\/inside.nssl.noaa.gov\/vsecommunity\/wp-json\/wp\/v2\/pages\/368\/revisions"}],"predecessor-version":[{"id":438,"href":"https:\/\/inside.nssl.noaa.gov\/vsecommunity\/wp-json\/wp\/v2\/pages\/368\/revisions\/438"}],"wp:attachment":[{"href":"https:\/\/inside.nssl.noaa.gov\/vsecommunity\/wp-json\/wp\/v2\/media?parent=368"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}
The lowest model level is the interface of energy and mass exchanging between the surface and planetary boundary layer<\/a> (PBL). Previous studies mostly examined the role of the lowest model level height (z<\/em>1<\/sub>) in simulating the continental PBL processes. The impact of z<\/em>1<\/sub> on simulating marine processes (e.g., sea fog), however, remains unclear. The present study explores the sensitivity of the Weather Research and Forecasting (WRF) model with the Yonsei University (YSU) PBL scheme to z<\/em>1<\/sub> for an advection<\/a> fog event occurred on 27 March 2012 over the Yellow Sea. Seven experiments with various z<\/em>1<\/sub> (28, 22, 14, 8, 4, 1 and 0.4\u202fm) are conducted.<\/p>\n\n\n\nEvaluations for the continental PBL indicate that\u00a0z<\/em>1<\/sub>\u00a0below 8\u202fm is irrational in simulating surface temperature and PBL height over land. However, the model with\u00a0z<\/em>1<\/sub>= 8\u202fm gives the best performance in terms of reproducing sea fog. When\u00a0z<\/em>1<\/sub>\u00a0gets below 8\u202fm, the sea fog occurs too early and the fog area is too small. As\u00a0z<\/em>1<\/sub>\u00a0exceeds 8\u202fm, the fog forms too late and the fog area becomes underestimated. These model sensitivities can be explained by the impact of\u00a0z<\/em>1<\/sub>\u00a0on virtual potential temperature at\u00a0z<\/em>1<\/sub>\u00a0[\u03b8<\/em>v<\/em><\/sub>(z<\/em>1<\/sub>)]. Since the heat capacity of the air in the lowest model layer is proportional to\u00a0z<\/em>1<\/sub>, a lower (higher)\u00a0z<\/em>1<\/sub>\u00a0causes a quicker (slower) response of\u00a0\u03b8<\/em>v<\/em><\/sub>(z<\/em>1<\/sub>) to surface cooling, thus leading to an earlier (later) sea fog formation. After the fog onset, especially for a lower\u00a0z<\/em>1<\/sub>, the variation of\u00a0\u03b8<\/em>v<\/em><\/sub>(z<\/em>1<\/sub>) is dominated by turbulent heating that transports warmer air above to the very shallow lowest model layer, resulting in a lower vertical growth and even earlier dissipation of the sea fog.<\/p>\n\n\n\n\n\n\n\nThe effect of surface drag strength on mesocyclone intensification and tornadogenesis in idealized supercell simulations<\/h3>\n\n\n\nBrett Roberts, Ming Xue, <\/p>\n\n\n\nhttps:\/\/doi.org\/10.1175\/JAS-D-19-0109.1<\/a><\/p>\n\n\n\n\n\t\t\t\n\t\t\t\t\n\t\t\t<\/svg>\n\t\t<\/button><\/figure><\/div>\n\n\n\nAbstract<\/h4>\n\n\n\nA suite of six idealized supercell simulations is performed in which the surface drag coefficient\u00a0C<\/em>d<\/em><\/sub>\u00a0is varied over a range of values from 0 to 0.05 to represent a variety of water and land surfaces. The experiments employ a new technique for enforcing a three-force balance among the pressure gradient, Coriolis, and frictional forces so that the environmental wind profile can remain unchanged throughout the simulation. The initial low-level mesocyclone lowers toward the ground, intensifies, and produces a tornado in all experiments with\u00a0C<\/em>d<\/em><\/sub>\u00a0\u2265 0.002, with the intensification occurring earlier for larger\u00a0C<\/em>d<\/em><\/sub>. In the experiment with\u00a0C<\/em>d<\/em><\/sub>\u00a0= 0, the low-level mesocyclone remains comparatively weak throughout the simulation and does not produce a tornado. Vertical cross sections through the simulated tornadoes reveal an axial downdraft that reaches the ground only in experiments with smaller\u00a0C<\/em>d<\/em><\/sub>, as well as stronger corner flow in experiments with larger\u00a0C<\/em>d<\/em><\/sub>. Material circuits are initialized enclosing the low-level mesocyclone in each experiment and traced backward in time. Circulation budgets for these circuits implicate surface drag acting in the inflow sector of the supercell as having generated important positive circulation, and its relative contribution increases with\u00a0C<\/em>d<\/em><\/sub>. However, the circulation generation is similar in magnitude for the experiments with\u00a0C<\/em>d<\/em><\/sub>\u00a0= 0.02 and 0.05, and the tornado in the latter experiment is weaker. This suggests the possible existence of an optimal range of\u00a0C<\/em>d<\/em><\/sub>\u00a0values for promoting intense tornadoes within our experimental configuration.<\/p>\n\n\n\n\n","protected":false},"excerpt":{"rendered":"Toward 1-km Ensemble Forecasts over Large Domains Craig Schwartz, Glen Romine, Kathryn Fossell, Ryan Sobash, Morris Weisman https:\/\/doi.org\/10.1175\/MWR-D-16-0410.1 Abstract Precipitation forecasts from convection-allowing ensembles with 3- and 1-km horizontal grid… <\/p>\nRead more \u00bb<\/a><\/p>\n","protected":false},"author":129,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-368","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/inside.nssl.noaa.gov\/vsecommunity\/wp-json\/wp\/v2\/pages\/368","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/inside.nssl.noaa.gov\/vsecommunity\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/inside.nssl.noaa.gov\/vsecommunity\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/inside.nssl.noaa.gov\/vsecommunity\/wp-json\/wp\/v2\/users\/129"}],"replies":[{"embeddable":true,"href":"https:\/\/inside.nssl.noaa.gov\/vsecommunity\/wp-json\/wp\/v2\/comments?post=368"}],"version-history":[{"count":6,"href":"https:\/\/inside.nssl.noaa.gov\/vsecommunity\/wp-json\/wp\/v2\/pages\/368\/revisions"}],"predecessor-version":[{"id":438,"href":"https:\/\/inside.nssl.noaa.gov\/vsecommunity\/wp-json\/wp\/v2\/pages\/368\/revisions\/438"}],"wp:attachment":[{"href":"https:\/\/inside.nssl.noaa.gov\/vsecommunity\/wp-json\/wp\/v2\/media?parent=368"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}
Evaluations for the continental PBL indicate that\u00a0z<\/em>1<\/sub>\u00a0below 8\u202fm is irrational in simulating surface temperature and PBL height over land. However, the model with\u00a0z<\/em>1<\/sub>= 8\u202fm gives the best performance in terms of reproducing sea fog. When\u00a0z<\/em>1<\/sub>\u00a0gets below 8\u202fm, the sea fog occurs too early and the fog area is too small. As\u00a0z<\/em>1<\/sub>\u00a0exceeds 8\u202fm, the fog forms too late and the fog area becomes underestimated. These model sensitivities can be explained by the impact of\u00a0z<\/em>1<\/sub>\u00a0on virtual potential temperature at\u00a0z<\/em>1<\/sub>\u00a0[\u03b8<\/em>v<\/em><\/sub>(z<\/em>1<\/sub>)]. Since the heat capacity of the air in the lowest model layer is proportional to\u00a0z<\/em>1<\/sub>, a lower (higher)\u00a0z<\/em>1<\/sub>\u00a0causes a quicker (slower) response of\u00a0\u03b8<\/em>v<\/em><\/sub>(z<\/em>1<\/sub>) to surface cooling, thus leading to an earlier (later) sea fog formation. After the fog onset, especially for a lower\u00a0z<\/em>1<\/sub>, the variation of\u00a0\u03b8<\/em>v<\/em><\/sub>(z<\/em>1<\/sub>) is dominated by turbulent heating that transports warmer air above to the very shallow lowest model layer, resulting in a lower vertical growth and even earlier dissipation of the sea fog.<\/p>\n\n\n\n\n\n\n\nThe effect of surface drag strength on mesocyclone intensification and tornadogenesis in idealized supercell simulations<\/h3>\n\n\n\nBrett Roberts, Ming Xue, <\/p>\n\n\n\nhttps:\/\/doi.org\/10.1175\/JAS-D-19-0109.1<\/a><\/p>\n\n\n\n\n\t\t\t\n\t\t\t\t\n\t\t\t<\/svg>\n\t\t<\/button><\/figure><\/div>\n\n\n\nAbstract<\/h4>\n\n\n\nA suite of six idealized supercell simulations is performed in which the surface drag coefficient\u00a0C<\/em>d<\/em><\/sub>\u00a0is varied over a range of values from 0 to 0.05 to represent a variety of water and land surfaces. The experiments employ a new technique for enforcing a three-force balance among the pressure gradient, Coriolis, and frictional forces so that the environmental wind profile can remain unchanged throughout the simulation. The initial low-level mesocyclone lowers toward the ground, intensifies, and produces a tornado in all experiments with\u00a0C<\/em>d<\/em><\/sub>\u00a0\u2265 0.002, with the intensification occurring earlier for larger\u00a0C<\/em>d<\/em><\/sub>. In the experiment with\u00a0C<\/em>d<\/em><\/sub>\u00a0= 0, the low-level mesocyclone remains comparatively weak throughout the simulation and does not produce a tornado. Vertical cross sections through the simulated tornadoes reveal an axial downdraft that reaches the ground only in experiments with smaller\u00a0C<\/em>d<\/em><\/sub>, as well as stronger corner flow in experiments with larger\u00a0C<\/em>d<\/em><\/sub>. Material circuits are initialized enclosing the low-level mesocyclone in each experiment and traced backward in time. Circulation budgets for these circuits implicate surface drag acting in the inflow sector of the supercell as having generated important positive circulation, and its relative contribution increases with\u00a0C<\/em>d<\/em><\/sub>. However, the circulation generation is similar in magnitude for the experiments with\u00a0C<\/em>d<\/em><\/sub>\u00a0= 0.02 and 0.05, and the tornado in the latter experiment is weaker. This suggests the possible existence of an optimal range of\u00a0C<\/em>d<\/em><\/sub>\u00a0values for promoting intense tornadoes within our experimental configuration.<\/p>\n\n\n\n\n","protected":false},"excerpt":{"rendered":"Toward 1-km Ensemble Forecasts over Large Domains Craig Schwartz, Glen Romine, Kathryn Fossell, Ryan Sobash, Morris Weisman https:\/\/doi.org\/10.1175\/MWR-D-16-0410.1 Abstract Precipitation forecasts from convection-allowing ensembles with 3- and 1-km horizontal grid… <\/p>\nRead more \u00bb<\/a><\/p>\n","protected":false},"author":129,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-368","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/inside.nssl.noaa.gov\/vsecommunity\/wp-json\/wp\/v2\/pages\/368","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/inside.nssl.noaa.gov\/vsecommunity\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/inside.nssl.noaa.gov\/vsecommunity\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/inside.nssl.noaa.gov\/vsecommunity\/wp-json\/wp\/v2\/users\/129"}],"replies":[{"embeddable":true,"href":"https:\/\/inside.nssl.noaa.gov\/vsecommunity\/wp-json\/wp\/v2\/comments?post=368"}],"version-history":[{"count":6,"href":"https:\/\/inside.nssl.noaa.gov\/vsecommunity\/wp-json\/wp\/v2\/pages\/368\/revisions"}],"predecessor-version":[{"id":438,"href":"https:\/\/inside.nssl.noaa.gov\/vsecommunity\/wp-json\/wp\/v2\/pages\/368\/revisions\/438"}],"wp:attachment":[{"href":"https:\/\/inside.nssl.noaa.gov\/vsecommunity\/wp-json\/wp\/v2\/media?parent=368"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}
Brett Roberts, Ming Xue, <\/p>\n\n\n\n
https:\/\/doi.org\/10.1175\/JAS-D-19-0109.1<\/a><\/p>\n\n\n\n\n\t\t\t\n\t\t\t\t\n\t\t\t<\/svg>\n\t\t<\/button><\/figure><\/div>\n\n\n\nAbstract<\/h4>\n\n\n\nA suite of six idealized supercell simulations is performed in which the surface drag coefficient\u00a0C<\/em>d<\/em><\/sub>\u00a0is varied over a range of values from 0 to 0.05 to represent a variety of water and land surfaces. The experiments employ a new technique for enforcing a three-force balance among the pressure gradient, Coriolis, and frictional forces so that the environmental wind profile can remain unchanged throughout the simulation. The initial low-level mesocyclone lowers toward the ground, intensifies, and produces a tornado in all experiments with\u00a0C<\/em>d<\/em><\/sub>\u00a0\u2265 0.002, with the intensification occurring earlier for larger\u00a0C<\/em>d<\/em><\/sub>. In the experiment with\u00a0C<\/em>d<\/em><\/sub>\u00a0= 0, the low-level mesocyclone remains comparatively weak throughout the simulation and does not produce a tornado. Vertical cross sections through the simulated tornadoes reveal an axial downdraft that reaches the ground only in experiments with smaller\u00a0C<\/em>d<\/em><\/sub>, as well as stronger corner flow in experiments with larger\u00a0C<\/em>d<\/em><\/sub>. Material circuits are initialized enclosing the low-level mesocyclone in each experiment and traced backward in time. Circulation budgets for these circuits implicate surface drag acting in the inflow sector of the supercell as having generated important positive circulation, and its relative contribution increases with\u00a0C<\/em>d<\/em><\/sub>. However, the circulation generation is similar in magnitude for the experiments with\u00a0C<\/em>d<\/em><\/sub>\u00a0= 0.02 and 0.05, and the tornado in the latter experiment is weaker. This suggests the possible existence of an optimal range of\u00a0C<\/em>d<\/em><\/sub>\u00a0values for promoting intense tornadoes within our experimental configuration.<\/p>\n\n\n\n\n","protected":false},"excerpt":{"rendered":"Toward 1-km Ensemble Forecasts over Large Domains Craig Schwartz, Glen Romine, Kathryn Fossell, Ryan Sobash, Morris Weisman https:\/\/doi.org\/10.1175\/MWR-D-16-0410.1 Abstract Precipitation forecasts from convection-allowing ensembles with 3- and 1-km horizontal grid… <\/p>\nRead more \u00bb<\/a><\/p>\n","protected":false},"author":129,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-368","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/inside.nssl.noaa.gov\/vsecommunity\/wp-json\/wp\/v2\/pages\/368","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/inside.nssl.noaa.gov\/vsecommunity\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/inside.nssl.noaa.gov\/vsecommunity\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/inside.nssl.noaa.gov\/vsecommunity\/wp-json\/wp\/v2\/users\/129"}],"replies":[{"embeddable":true,"href":"https:\/\/inside.nssl.noaa.gov\/vsecommunity\/wp-json\/wp\/v2\/comments?post=368"}],"version-history":[{"count":6,"href":"https:\/\/inside.nssl.noaa.gov\/vsecommunity\/wp-json\/wp\/v2\/pages\/368\/revisions"}],"predecessor-version":[{"id":438,"href":"https:\/\/inside.nssl.noaa.gov\/vsecommunity\/wp-json\/wp\/v2\/pages\/368\/revisions\/438"}],"wp:attachment":[{"href":"https:\/\/inside.nssl.noaa.gov\/vsecommunity\/wp-json\/wp\/v2\/media?parent=368"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}
A suite of six idealized supercell simulations is performed in which the surface drag coefficient\u00a0C<\/em>d<\/em><\/sub>\u00a0is varied over a range of values from 0 to 0.05 to represent a variety of water and land surfaces. The experiments employ a new technique for enforcing a three-force balance among the pressure gradient, Coriolis, and frictional forces so that the environmental wind profile can remain unchanged throughout the simulation. The initial low-level mesocyclone lowers toward the ground, intensifies, and produces a tornado in all experiments with\u00a0C<\/em>d<\/em><\/sub>\u00a0\u2265 0.002, with the intensification occurring earlier for larger\u00a0C<\/em>d<\/em><\/sub>. In the experiment with\u00a0C<\/em>d<\/em><\/sub>\u00a0= 0, the low-level mesocyclone remains comparatively weak throughout the simulation and does not produce a tornado. Vertical cross sections through the simulated tornadoes reveal an axial downdraft that reaches the ground only in experiments with smaller\u00a0C<\/em>d<\/em><\/sub>, as well as stronger corner flow in experiments with larger\u00a0C<\/em>d<\/em><\/sub>. Material circuits are initialized enclosing the low-level mesocyclone in each experiment and traced backward in time. Circulation budgets for these circuits implicate surface drag acting in the inflow sector of the supercell as having generated important positive circulation, and its relative contribution increases with\u00a0C<\/em>d<\/em><\/sub>. However, the circulation generation is similar in magnitude for the experiments with\u00a0C<\/em>d<\/em><\/sub>\u00a0= 0.02 and 0.05, and the tornado in the latter experiment is weaker. This suggests the possible existence of an optimal range of\u00a0C<\/em>d<\/em><\/sub>\u00a0values for promoting intense tornadoes within our experimental configuration.<\/p>\n\n\n\n\n","protected":false},"excerpt":{"rendered":"Toward 1-km Ensemble Forecasts over Large Domains Craig Schwartz, Glen Romine, Kathryn Fossell, Ryan Sobash, Morris Weisman https:\/\/doi.org\/10.1175\/MWR-D-16-0410.1 Abstract Precipitation forecasts from convection-allowing ensembles with 3- and 1-km horizontal grid… <\/p>\nRead more \u00bb<\/a><\/p>\n","protected":false},"author":129,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-368","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/inside.nssl.noaa.gov\/vsecommunity\/wp-json\/wp\/v2\/pages\/368","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/inside.nssl.noaa.gov\/vsecommunity\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/inside.nssl.noaa.gov\/vsecommunity\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/inside.nssl.noaa.gov\/vsecommunity\/wp-json\/wp\/v2\/users\/129"}],"replies":[{"embeddable":true,"href":"https:\/\/inside.nssl.noaa.gov\/vsecommunity\/wp-json\/wp\/v2\/comments?post=368"}],"version-history":[{"count":6,"href":"https:\/\/inside.nssl.noaa.gov\/vsecommunity\/wp-json\/wp\/v2\/pages\/368\/revisions"}],"predecessor-version":[{"id":438,"href":"https:\/\/inside.nssl.noaa.gov\/vsecommunity\/wp-json\/wp\/v2\/pages\/368\/revisions\/438"}],"wp:attachment":[{"href":"https:\/\/inside.nssl.noaa.gov\/vsecommunity\/wp-json\/wp\/v2\/media?parent=368"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}
Toward 1-km Ensemble Forecasts over Large Domains Craig Schwartz, Glen Romine, Kathryn Fossell, Ryan Sobash, Morris Weisman https:\/\/doi.org\/10.1175\/MWR-D-16-0410.1 Abstract Precipitation forecasts from convection-allowing ensembles with 3- and 1-km horizontal grid… <\/p>\n
Read more \u00bb<\/a><\/p>\n","protected":false},"author":129,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-368","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/inside.nssl.noaa.gov\/vsecommunity\/wp-json\/wp\/v2\/pages\/368","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/inside.nssl.noaa.gov\/vsecommunity\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/inside.nssl.noaa.gov\/vsecommunity\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/inside.nssl.noaa.gov\/vsecommunity\/wp-json\/wp\/v2\/users\/129"}],"replies":[{"embeddable":true,"href":"https:\/\/inside.nssl.noaa.gov\/vsecommunity\/wp-json\/wp\/v2\/comments?post=368"}],"version-history":[{"count":6,"href":"https:\/\/inside.nssl.noaa.gov\/vsecommunity\/wp-json\/wp\/v2\/pages\/368\/revisions"}],"predecessor-version":[{"id":438,"href":"https:\/\/inside.nssl.noaa.gov\/vsecommunity\/wp-json\/wp\/v2\/pages\/368\/revisions\/438"}],"wp:attachment":[{"href":"https:\/\/inside.nssl.noaa.gov\/vsecommunity\/wp-json\/wp\/v2\/media?parent=368"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}
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