Coordinated Enhanced Observing Period (CEOP) International Workshop

Bosilovich, Michael G.; Lawford, Rick

doi:10.1175/bams-83-10-1495(2002)083<1495:ceopiw>2.3.co;2

Cited by 17 publications

(14 citation statements)

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“…11c). The TMPA-RT indicated a rainfall occurrence of less than 25%, but the highest accumulaCoordinated Enhanced Observing Period (CEOP) (Bosilovich and Lawford 2002).…”

Section: Results From Long-term Compari-sons Of Satellite-and Model-bmentioning

confidence: 99%

Comparison of Near-Real-Time Precipitation Estimates from Satellite Observations and Numerical Models

Ebert

Janowiak²,

Kidd³

2007

Bull. Amer. Meteor. Soc.

945

735

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The accuracy of daily rainfall estimates from satellite observations and short-range numerical model forecasts is complementary, with satellite estimates performing best in summer and models in winter A ccurate measurements of precipitation on a variety of space and time scales are important not only to weather forecasters and climate scientists, but also to a wide range of decision makers, including hydrologists, agriculturalists, emergency managers, and industrialists. Precipitation measurements provide essential information about the global water cycle and the distribution of the Earth's latent AMERICAN METEOROLOGICAL SOCIETY heating, which has direct effects on the planetary circulation of the atmosphere. However, the historical record of precipitation observations is limited mostly to land areas where rain gauges can be deployed, and measurements from those instruments are sparse over large and meteorologically important regions of the earth, such as over the Amazon and equatorial Africa. Furthermore, precipitation observations over the oceans are limited over most of the historical record to scattered islands and, except for low-lying atolls, the observations from those locations are often not representative of the open ocean because the islands themselves have strong local influences on the precipitation.With the advent of meteorological satellites in the 1970s, scientists developed techniques to estimate precipitation from radiometric observations from satellites, which provide coverage over most of the globe. The first techniques used visible or infrared data to infer precipitation intensity based on the reflectivity of clouds (visible) and from cloud-top temperature (infrared). Both of those types of techniques yield crude estimates of precipitation because the link between cloud properties and precipitation JANUARY 2007 BAPI S" | 47

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“…11c). The TMPA-RT indicated a rainfall occurrence of less than 25%, but the highest accumulaCoordinated Enhanced Observing Period (CEOP) (Bosilovich and Lawford 2002).…”

Section: Results From Long-term Compari-sons Of Satellite-and Model-bmentioning

confidence: 99%

Comparison of Near-Real-Time Precipitation Estimates from Satellite Observations and Numerical Models

Ebert

Janowiak²,

Kidd³

2007

Bull. Amer. Meteor. Soc.

945

735

View full text Add to dashboard Cite

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“…Surface air temperature from in-situ stations is used as independent validation of the approach. Independent in-situ station observations from the Coordinated Enhanced Observing Period (CEOP, Bosilovich and Lawford 2002;Lawford et al 2005) are used to validate the impact on the surface fluxes.…”

Section: Datamentioning

confidence: 99%

“…CEOP was designed as a pilot program to test the scientific community's ability to bring together a variety of global observations in order to better document and simulate water and energy fluxes over land. We will use in-situ point observations from CEOP reference sites and Continental Scale Experiments (CSEs) as independent validations (Bosilovich and Lawford 2002;Koike 2004). In order to compare hourly point observations with our gridded model, we use Model Output Location Time Series (MOLTS), which generate model output from a given point at hourly frequency, matching the station temporal frequency.…”

Section: Datamentioning

confidence: 99%

“…These include several reference sites which have enhanced observing capabilities, such as turbulent fluxes and radiative fluxes. The Coordinated Enhanced Observing Period (CEOP) has compiled, processed and provided further quality control on these observations (Bosilovich and Lawford 2002;Lawford et al 2005). The surface stations and data integration efforts are described in Koike (2004).…”

Section: Energy Budgetsmentioning

confidence: 99%

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Skin Temperature Analysis and Bias Correction in a Coupled Land-Atmosphere Data Assimilation System

Bosilovich

Radakovich

Silva

et al. 2007

Journal of the Meteorological Society of Japan

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In an initial investigation, remotely sensed surface temperature is assimilated into a coupled atmosphere/land global data assimilation system, with explicit accounting for biases in the model state. In this scheme, a incremental bias correction term is introduced in the model's surface energy budget. In its simplest form, the algorithm estimates and corrects a constant time mean bias for each gridpoint; additional benefits are attained with a refined version of the algorithm which allows for a correction of the mean diurnal cycle. The method is validated against the assimilated observations, as well as independent near-surface air temperature observations. In many regions, not accounting for the diurnal cycle of bias caused degradation of the diurnal amplitude of background model air temperature. Energy fluxes collected through the Coordinated Enhanced Observing Period (CEOP) are used to more closely inspect the surface energy budget. In general, sensible heat flux is improved with the surface temperature assimilation, and two stations show a reduction of bias by as much as 30 W m À2 . At the Rondonia station in Amazonia, the Bowen ratio changes direction in an improvement related to the temperature assimilation. However, at many stations the monthly latent heat flux bias is slightly increased. These results show the impact of univariate assimilation of surface temperature observations on the surface energy budget, and suggest the need for multivariate land data assimilation. The results also show the need for independent validation data, especially flux stations in varied climate regimes.

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“…The Tongyu observation site is also one the reference sites of the CEOP (Coordinate Enhanced Observation Period, Bosilovich and Lawford, 2002). The main objectives of this long-term observation are the following.…”

Section: Introductionmentioning

confidence: 99%

Three-year variations of water, energy and CO2 fluxes of cropland and degraded grassland surfaces in a semi-arid area of Northeastern China

Liu

et al. 2008

Adv. Atmos. Sci.

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Based on 3 years of the eddy covariance (EC) observations on degraded grassland and cropland surfaces in a semi-arid area of Tongyu (44 • 25 N, 122• 52 E, 184 m a.s.l.), Northeast China, seasonal and annual variations of water, energy and CO2 fluxes have been investigated. The soil moisture in the thin soil layer (at 0.05, 0.10 and 0.20 m) clearly indicates the pronounced annual wet-dry cycle; the annual cycle is divided into the wet (growing season) and dry seasons (non-growing season). During the growing season (from May to September), the sensible and latent heat fluxes showed a linear dependence on the global solar radiation. However, in the non-growing season, the latent heat flux was always less than 50 W m −2 , while the available energy was dissipated as sensible, rather than latent heat flux. During the growing season in 2003-05, the daily average sensible and latent heat fluxes were larger on the cropland surface than on the degraded grassland surface. The cropland ecosystem absorbed more CO2 than the degraded grassland ecosystem in the growing season in 2003-05. The total evapotranspiration on the cropland was more than the total precipitation, while the total evapotranspiration on the degraded grassland was almost the same as the total annual precipitation in the growing season. The soil moisture had a good correlation with the rainfall in the growing season. Precipitation in the growing season is an important factor on the water and carbon budget in the semi-arid area.Key words: water, energy and flux, semi-arid area, eddy covariance, seasonal and annual variation Citation: Liu, H. Z., G. Tu, C. B. Fu, and L. Q. Shi, 2008: Three-year variations of water, energy and fluxes of cropland and degraded grassland surfaces in a semi-arid area of northeastern China.

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Coordinated Enhanced Observing Period (CEOP) International Workshop

Cited by 17 publications

References 0 publications

Comparison of Near-Real-Time Precipitation Estimates from Satellite Observations and Numerical Models

Comparison of Near-Real-Time Precipitation Estimates from Satellite Observations and Numerical Models

Skin Temperature Analysis and Bias Correction in a Coupled Land-Atmosphere Data Assimilation System

Three-year variations of water, energy and CO2 fluxes of cropland and degraded grassland surfaces in a semi-arid area of Northeastern China

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