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Robert W. Grumbine

Abstract

The sea-ice albedo treatment currently used in the National Meteorological Center Medium Range Forecast Model was a carryover from earlier models. A more modern treatment is shown to improve forecast skill marginally, as measured by height field anomaly correlation, and to improve substantially the surface temperature field in sea-ice regions. The improvement reduces a systematic bias toward warm temperatures in winter and cold temperatures in summer. Even though the ice retreats once the sun rises, accurate sea-ice albedos are important to the forecast problem.

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Robert W. Grumbine

Abstract

Both sea ice forecast models and methods to measure their skill are needed for operational sea ice forecasting. Two simple sea ice models are described and tested here. Four different measures of skill are also tested. The forecasts from the newer sea ice model are found to perform better, regardless of the skill measure used. All four skill measures show essentially the same behavior, in terms of having no dependence on season and being roughly constant. All four measures also agree that there is no decline in skill with time through the 6-day period of forecast.

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David H. Bromwich, Richard I. Cullather, and Robert W. Grumbine

Abstract

Analyses and medium-range numerical weather forecasts produced by the National Centers for Environmental Prediction are evaluated poleward of 50°S during the July 1994 special observing period of the Antarctic First Regional Observing Study of the Troposphere project. Over the Antarctic plateau, the poor representation of the continent’s terrain creates ambiguity in assessing the quality of surface variables. An examination of the vertical temperature profile, however, finds the near-surface temperature inversion strength to be substantially smaller than the observed climatology at the zero forecast hour. This arises from surface temperatures that are warmer than expected. Significant adjustment occurs in a variety of fields over the first few days of the medium-range forecast, which likely results from the initial hour’s suspect temperature profile. A spatially oscillating series of forecast anomalies in the zonally averaged temperature cross section stretches to middle latitudes by day 3. Near-surface and upper-troposphere values are found actually to improve at the South Pole with forecast time, although some fields continue to adjust through day 7. Although the examination presented here does not give a complete diagnosis, differences between observations and analyses suggest deficiencies with the model initial fields have a major role in producing the substantial model drift found. Atmospheric moisture over the continental interior does not change significantly with forecast hour, although the distinct contrast between nearshore and interior conditions lessens with forecast time. A spurious high-latitude wave pattern is found for a variety of variables. The pattern of this distortion remains constant with forecast hour. Over the ocean, large forecast pressure and height differences with analyses are associated with blocking conditions. However, it is unclear whether this results from deficiencies in the forecast model or the meager observational network over the Southern Ocean.

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Keith M. Hines, Robert W. Grumbine, David H. Bromwich, and Richard I. Cullather

Abstract

The surface energy budget in Antarctic latitudes is evaluated for the medium-range numerical weather forecasts produced by the National Centers for Environmental Prediction (NCEP) and for the NCEP–National Center for Atmospheric Research reanalysis project during the winter, spring, and summer special observing periods (SOPs) of the Antarctic First Regional Observing Study of Troposphere project. A significant change in the energy balance resulted from an extensive model update beginning with the forecasts initialized on 11 January 1995 during the summer SOP. Both the forecasts and the reanalysis include significant errors in the surface energy balance over Antarctica. The errors often tend to cancel and thus produce reasonable surface temperature fields. General errors include downward longwave radiation about 30–50 W m−2 too small. Lower than observed cloudiness contributes to this error and to excessive downward shortwave radiation at the surface. The model albedo over Antarctica, about 75%, is lower than that derived from observations, about 81%. During the polar day, errors in net longwave and net shortwave radiation tend to cancel. The energy balance over Antarctica in the reanalysis is, in general, degraded from that of the forecasts.

Seasonal characteristics of the surface energy balance include cooling over East Antarctica and slight warming over West Antarctica during NCEP forecasts for the winter SOP. Wintertime surface warming by downward sensible heat flux is larger than observations by 21–36 W m−2 and tends to balance the excessive longwave cooling at the surface. During the spring SOP, forecast sensible heat flux produces an excessive heating contribution by about 20 W m−2. Latent heat flux during the Antarctic winter for the reanalysis is at least an order of magnitude larger than the very small observed values.

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David Randall, Judith Curry, David Battisti, Gregory Flato, Robert Grumbine, Sirpa Hakkinen, Doug Martinson, Ruth Preller, John Walsh, and John Weatherly

Arctic air masses have direct impacts on the weather and climatic extremes of midlatitude areas such as central North America. Arctic physical processes pose special and very important problems for global atmospheric models used for climate simulation and numerical weather prediction. At present, the observational database is inadequate to support research aimed at overcoming these problems. Three interdependent Arctic field programs now being planned will help to remedy this situation: SHEBA, which will operate an ice camp in the Arctic for a year; ARM, which will supply instruments for use at the SHEBA ice camp and which will also conduct longer-term measurements near Barrow, Alaska; and FIRE, which will conduct one or more aircraft campaigns, in conjunction with remote-sensing investigations focused on the SHEBA ice camp. This paper provides an introductory overview of the physics of the Arctic from the perspective of large-scale modelers, outlines some of the modeling problems that arise in attempting to simulate these processes, and explains how the data to be provided by the three field programs can be used to test and improve large-scale models.

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Fedor Mesinger, Geoff DiMego, Eugenia Kalnay, Kenneth Mitchell, Perry C. Shafran, Wesley Ebisuzaki, Dušan Jović, Jack Woollen, Eric Rogers, Ernesto H. Berbery, Michael B. Ek, Yun Fan, Robert Grumbine, Wayne Higgins, Hong Li, Ying Lin, Geoff Manikin, David Parrish, and Wei Shi

In 1997, during the late stages of production of NCEP–NCAR Global Reanalysis (GR), exploration of a regional reanalysis project was suggested by the GR project's Advisory Committee, “particularly if the RDAS [Regional Data Assimilation System] is significantly better than the global reanalysis at capturing the regional hydrological cycle, the diurnal cycle and other important features of weather and climate variability.” Following a 6-yr development and production effort, NCEP's North American Regional Reanalysis (NARR) project was completed in 2004, and data are now available to the scientific community. Along with the use of the NCEP Eta model and its Data Assimilation System (at 32-km–45-layer resolution with 3-hourly output), the hallmarks of the NARR are the incorporation of hourly assimilation of precipitation, which leverages a comprehensive precipitation analysis effort, the use of a recent version of the Noah land surface model, and the use of numerous other datasets that are additional or improved compared to the GR. Following the practice applied to NCEP's GR, the 25-yr NARR retrospective production period (1979–2003) is augmented by the construction and daily execution of a system for near-real-time continuation of the NARR, known as the Regional Climate Data Assimilation System (R-CDAS). Highlights of the NARR results are presented: precipitation over the continental United States (CONUS), which is seen to be very near the ingested analyzed precipitation; fits of tropospheric temperatures and winds to rawinsonde observations; and fits of 2-m temperatures and 10-m winds to surface station observations. The aforementioned fits are compared to those of the NCEP–Department of Energy (DOE) Global Reanalysis (GR2). Not only have the expectations cited above been fully met, but very substantial improvements in the accuracy of temperatures and winds compared to that of GR2 are achieved throughout the troposphere. Finally, the numerous datasets produced are outlined and information is provided on the data archiving and present data availability.

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Suranjana Saha, Shrinivas Moorthi, Hua-Lu Pan, Xingren Wu, Jiande Wang, Sudhir Nadiga, Patrick Tripp, Robert Kistler, John Woollen, David Behringer, Haixia Liu, Diane Stokes, Robert Grumbine, George Gayno, Jun Wang, Yu-Tai Hou, Hui-ya Chuang, Hann-Ming H. Juang, Joe Sela, Mark Iredell, Russ Treadon, Daryl Kleist, Paul Van Delst, Dennis Keyser, John Derber, Michael Ek, Jesse Meng, Helin Wei, Rongqian Yang, Stephen Lord, Huug van den Dool, Arun Kumar, Wanqiu Wang, Craig Long, Muthuvel Chelliah, Yan Xue, Boyin Huang, Jae-Kyung Schemm, Wesley Ebisuzaki, Roger Lin, Pingping Xie, Mingyue Chen, Shuntai Zhou, Wayne Higgins, Cheng-Zhi Zou, Quanhua Liu, Yong Chen, Yong Han, Lidia Cucurull, Richard W. Reynolds, Glenn Rutledge, and Mitch Goldberg

The NCEP Climate Forecast System Reanalysis (CFSR) was completed for the 31-yr period from 1979 to 2009, in January 2010. The CFSR was designed and executed as a global, high-resolution coupled atmosphere–ocean–land surface–sea ice system to provide the best estimate of the state of these coupled domains over this period. The current CFSR will be extended as an operational, real-time product into the future. New features of the CFSR include 1) coupling of the atmosphere and ocean during the generation of the 6-h guess field, 2) an interactive sea ice model, and 3) assimilation of satellite radiances by the Gridpoint Statistical Interpolation (GSI) scheme over the entire period. The CFSR global atmosphere resolution is ~38 km (T382) with 64 levels extending from the surface to 0.26 hPa. The global ocean's latitudinal spacing is 0.25° at the equator, extending to a global 0.5° beyond the tropics, with 40 levels to a depth of 4737 m. The global land surface model has four soil levels and the global sea ice model has three layers. The CFSR atmospheric model has observed variations in carbon dioxide (CO2) over the 1979–2009 period, together with changes in aerosols and other trace gases and solar variations. Most available in situ and satellite observations were included in the CFSR. Satellite observations were used in radiance form, rather than retrieved values, and were bias corrected with “spin up” runs at full resolution, taking into account variable CO2 concentrations. This procedure enabled the smooth transitions of the climate record resulting from evolutionary changes in the satellite observing system.

CFSR atmospheric, oceanic, and land surface output products are available at an hourly time resolution and a horizontal resolution of 0.5° latitude × 0.5° longitude. The CFSR data will be distributed by the National Climatic Data Center (NCDC) and NCAR. This reanalysis will serve many purposes, including providing the basis for most of the NCEP Climate Prediction Center's operational climate products by defining the mean states of the atmosphere, ocean, land surface, and sea ice over the next 30-yr climate normal (1981–2010); providing initial conditions for historical forecasts that are required to calibrate operational NCEP climate forecasts (from week 2 to 9 months); and providing estimates and diagnoses of the Earth's climate state over the satellite data period for community climate research.

Preliminary analysis of the CFSR output indicates a product that is far superior in most respects to the reanalysis of the mid-1990s. The previous NCEP–NCAR reanalyses have been among the most used NCEP products in history; there is every reason to believe the CFSR will supersede these older products both in scope and quality, because it is higher in time and space resolution, covers the atmosphere, ocean, sea ice, and land, and was executed in a coupled mode with a more modern data assimilation system and forecast model.

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