Improving short-term numerical weather prediction in the California coastal zone by dynamic initialization of the marine boundary layer

S. M. Leidner, David R. Stauffer, N. L. Seaman

Research output: Contribution to journalArticle

19 Citations (Scopus)

Abstract

Few data are available over the world's oceans to characterize the initial atmospheric state in numerical models. Objective analysis in these regions is largely based on forecast fields obtained from a global model and used as the background ("first guess"). Unfortunately, global models often do not resolve the marine boundary layer (MBL) structure, which is important for simulating stratus clouds, coastal zone circulations, and electromagnetic wave propagation. Furthermore, initialization of the MBL in the coastal zone and data-sparse oceanic regions poses a challenging mesoscale modeling problem. The goal of this study, therefore, is to improve warm-season short-term mesoscale numerical prediction of California coastal zone meteorology by improving the model initial conditions in the coastal zone and offshore data-void regions. Initialization strategies tested include standard static and dynamic techniques and a new marine boundary layer initialization scheme that uses a dynamic initialization based on the remarkably consistent summertime marine-layer climatology of the eastern Pacific Ocean. The model used in this study is the Pennsylvania State University-National Center for Atmospheric Research fifth-generation Mesoscale Model (MM5). Experiments were performed for a typical summertime case (3-4 Aug 1990) to determine an initialization strategy suitable for coastal zone forecasting over the northeast Pacific. The meteorology in this case was dominated by quasi-stationary synoptic-scale high pressure over the ocean. Results from the model experiments were verified using 6-hourly coastal rawinsonde observations and visible range satellite cloud imagery. More accurate initial conditions were obtained by using dynamic initialization compared to static initialization. The most accurate initialization and short-range model forecasts were produced by assimilating a combination of observed data over land and climatological information offshore during the 12-h preforecast period. Through the 24-h forecast period, errors in the coastal zone PBL depth and marine inversion strength were reduced by 65% and 41%, respectively, compared to the static-initialization control experiments. Without proper initialization of the offshore MBL, coastal zone forecasts degraded with time due to the long timescale of physical processes responsible for generating the MBL structure over cold, low-latitude oceans. Therefore, improvement of the model initial conditions in the California coastal zone by assimilation of climatological information offshore in combination with observed conditions near the coast proved to be an effective strategy for increasing short-range forecast accuracy.

Original languageEnglish (US)
Pages (from-to)275-294
Number of pages20
JournalMonthly Weather Review
Volume129
Issue number2
DOIs
StatePublished - Jan 1 2001

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coastal zone
boundary layer
weather
prediction
ocean
meteorology
stratus
experiment
electromagnetic wave
void
wave propagation
climatology
imagery
forecast
timescale
coast
modeling

All Science Journal Classification (ASJC) codes

  • Atmospheric Science

Cite this

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title = "Improving short-term numerical weather prediction in the California coastal zone by dynamic initialization of the marine boundary layer",
abstract = "Few data are available over the world's oceans to characterize the initial atmospheric state in numerical models. Objective analysis in these regions is largely based on forecast fields obtained from a global model and used as the background ({"}first guess{"}). Unfortunately, global models often do not resolve the marine boundary layer (MBL) structure, which is important for simulating stratus clouds, coastal zone circulations, and electromagnetic wave propagation. Furthermore, initialization of the MBL in the coastal zone and data-sparse oceanic regions poses a challenging mesoscale modeling problem. The goal of this study, therefore, is to improve warm-season short-term mesoscale numerical prediction of California coastal zone meteorology by improving the model initial conditions in the coastal zone and offshore data-void regions. Initialization strategies tested include standard static and dynamic techniques and a new marine boundary layer initialization scheme that uses a dynamic initialization based on the remarkably consistent summertime marine-layer climatology of the eastern Pacific Ocean. The model used in this study is the Pennsylvania State University-National Center for Atmospheric Research fifth-generation Mesoscale Model (MM5). Experiments were performed for a typical summertime case (3-4 Aug 1990) to determine an initialization strategy suitable for coastal zone forecasting over the northeast Pacific. The meteorology in this case was dominated by quasi-stationary synoptic-scale high pressure over the ocean. Results from the model experiments were verified using 6-hourly coastal rawinsonde observations and visible range satellite cloud imagery. More accurate initial conditions were obtained by using dynamic initialization compared to static initialization. The most accurate initialization and short-range model forecasts were produced by assimilating a combination of observed data over land and climatological information offshore during the 12-h preforecast period. Through the 24-h forecast period, errors in the coastal zone PBL depth and marine inversion strength were reduced by 65{\%} and 41{\%}, respectively, compared to the static-initialization control experiments. Without proper initialization of the offshore MBL, coastal zone forecasts degraded with time due to the long timescale of physical processes responsible for generating the MBL structure over cold, low-latitude oceans. Therefore, improvement of the model initial conditions in the California coastal zone by assimilation of climatological information offshore in combination with observed conditions near the coast proved to be an effective strategy for increasing short-range forecast accuracy.",
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Improving short-term numerical weather prediction in the California coastal zone by dynamic initialization of the marine boundary layer. / Leidner, S. M.; Stauffer, David R.; Seaman, N. L.

In: Monthly Weather Review, Vol. 129, No. 2, 01.01.2001, p. 275-294.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Improving short-term numerical weather prediction in the California coastal zone by dynamic initialization of the marine boundary layer

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AB - Few data are available over the world's oceans to characterize the initial atmospheric state in numerical models. Objective analysis in these regions is largely based on forecast fields obtained from a global model and used as the background ("first guess"). Unfortunately, global models often do not resolve the marine boundary layer (MBL) structure, which is important for simulating stratus clouds, coastal zone circulations, and electromagnetic wave propagation. Furthermore, initialization of the MBL in the coastal zone and data-sparse oceanic regions poses a challenging mesoscale modeling problem. The goal of this study, therefore, is to improve warm-season short-term mesoscale numerical prediction of California coastal zone meteorology by improving the model initial conditions in the coastal zone and offshore data-void regions. Initialization strategies tested include standard static and dynamic techniques and a new marine boundary layer initialization scheme that uses a dynamic initialization based on the remarkably consistent summertime marine-layer climatology of the eastern Pacific Ocean. The model used in this study is the Pennsylvania State University-National Center for Atmospheric Research fifth-generation Mesoscale Model (MM5). Experiments were performed for a typical summertime case (3-4 Aug 1990) to determine an initialization strategy suitable for coastal zone forecasting over the northeast Pacific. The meteorology in this case was dominated by quasi-stationary synoptic-scale high pressure over the ocean. Results from the model experiments were verified using 6-hourly coastal rawinsonde observations and visible range satellite cloud imagery. More accurate initial conditions were obtained by using dynamic initialization compared to static initialization. The most accurate initialization and short-range model forecasts were produced by assimilating a combination of observed data over land and climatological information offshore during the 12-h preforecast period. Through the 24-h forecast period, errors in the coastal zone PBL depth and marine inversion strength were reduced by 65% and 41%, respectively, compared to the static-initialization control experiments. Without proper initialization of the offshore MBL, coastal zone forecasts degraded with time due to the long timescale of physical processes responsible for generating the MBL structure over cold, low-latitude oceans. Therefore, improvement of the model initial conditions in the California coastal zone by assimilation of climatological information offshore in combination with observed conditions near the coast proved to be an effective strategy for increasing short-range forecast accuracy.

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