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information on critical areas of the state that require monitoring. They guide the selection process to ensure that a site represents a predominant climate regime. Station locations are selected based on several criteria, including NRCS National Benchmark Soils, land ownership (federal, state, county, or university land), whether nonirrigated, whether agricultural in nature, and station security. The first stations to be installed were located in areas that were susceptible to drought. When installed
information on critical areas of the state that require monitoring. They guide the selection process to ensure that a site represents a predominant climate regime. Station locations are selected based on several criteria, including NRCS National Benchmark Soils, land ownership (federal, state, county, or university land), whether nonirrigated, whether agricultural in nature, and station security. The first stations to be installed were located in areas that were susceptible to drought. When installed
1. Introduction Soil moisture is an important component in many hydrologic and land–atmosphere interactions. Anomalous soil moisture conditions on a large scale can lead to droughts or floods ( Delworth and Manabe 1989 , 1993 ), while regional variations can impact the development of the planetary boundary layer ( Zdunkowski et al. 1975 ; Betts and Ball 1995 ), the formation of low-level boundaries or land breezes ( Enger and Tjernstrom 1991 ; Segal and Arritt 1992 ), convective initiation
1. Introduction Soil moisture is an important component in many hydrologic and land–atmosphere interactions. Anomalous soil moisture conditions on a large scale can lead to droughts or floods ( Delworth and Manabe 1989 , 1993 ), while regional variations can impact the development of the planetary boundary layer ( Zdunkowski et al. 1975 ; Betts and Ball 1995 ), the formation of low-level boundaries or land breezes ( Enger and Tjernstrom 1991 ; Segal and Arritt 1992 ), convective initiation
1. Introduction One of the largest uncertainties in global climate models is the representation of how clouds and aerosols influence the earth’s radiation budget (ERB) at the surface, within the atmosphere, and at the top of the atmosphere. Because of the uncertainty in cloud–aerosol–radiation interactions, model predictions of climate change vary widely from one model to the next ( Cess et al. 1990 , 1996 ; Cubasch et al. 2001 ). To improve our understanding of cloud
1. Introduction One of the largest uncertainties in global climate models is the representation of how clouds and aerosols influence the earth’s radiation budget (ERB) at the surface, within the atmosphere, and at the top of the atmosphere. Because of the uncertainty in cloud–aerosol–radiation interactions, model predictions of climate change vary widely from one model to the next ( Cess et al. 1990 , 1996 ; Cubasch et al. 2001 ). To improve our understanding of cloud
, totaling 36 h (0000 UTC on day 1 to 1200 UTC on day 2). The NARR input data have a spatial resolution of 32 km, which is then enhanced by using a series of nested domains within the model. Each domain increases the resolution by a factor of 3, such that the fourth domain, centered over Houston, has a resolution of 1.1 km. To more accurately represent the effects of the urban environment and land surface interactions within the urban environment, the Noah LSM and WRF UCM have been coupled to the ARW
, totaling 36 h (0000 UTC on day 1 to 1200 UTC on day 2). The NARR input data have a spatial resolution of 32 km, which is then enhanced by using a series of nested domains within the model. Each domain increases the resolution by a factor of 3, such that the fourth domain, centered over Houston, has a resolution of 1.1 km. To more accurately represent the effects of the urban environment and land surface interactions within the urban environment, the Noah LSM and WRF UCM have been coupled to the ARW
How Accurate Are Satellite-Derived Surface Solar Radiation Products over Tropical Oceans?that the ISCCP D-series cloud products have a greater uncertainty over ocean than over land. Pinker et al. (2009) also evaluated their global-scale SSR product (UMD/MODIS), which uses the level-3 land and atmosphere products of the Moderate Resolution Imaging Spectroradiometer (MODIS) as inputs, against observations from the same two buoy networks (the PIRATA over the Atlantic and the TAO/TRITON over the Pacific). The results show that the accuracy over the ocean was found to be similar to that
that the ISCCP D-series cloud products have a greater uncertainty over ocean than over land. Pinker et al. (2009) also evaluated their global-scale SSR product (UMD/MODIS), which uses the level-3 land and atmosphere products of the Moderate Resolution Imaging Spectroradiometer (MODIS) as inputs, against observations from the same two buoy networks (the PIRATA over the Atlantic and the TAO/TRITON over the Pacific). The results show that the accuracy over the ocean was found to be similar to that
1. Introduction Land surface characteristics modulate the exchange of mass and energy between the land and atmosphere. While knowledge of the complex interactions between the surface and the atmosphere has increased in recent years, understanding nonlinear feedbacks within the biosphere–atmosphere system remains difficult. A limited number of observations have been available to better understand these feedbacks ( Emanuel et al. 1995 ; Entekhabi et al. 1999 ). Many studies have relied upon
1. Introduction Land surface characteristics modulate the exchange of mass and energy between the land and atmosphere. While knowledge of the complex interactions between the surface and the atmosphere has increased in recent years, understanding nonlinear feedbacks within the biosphere–atmosphere system remains difficult. A limited number of observations have been available to better understand these feedbacks ( Emanuel et al. 1995 ; Entekhabi et al. 1999 ). Many studies have relied upon
troposphere (channels 5–8) and stratosphere (channels 9–14). Channels 18–20, which are centered on the water vapor line at 183.31 GHz, are the prime channels for humidity profile retrievals. Details of the AMSU channels and their characteristics are given in Table 1 . Results in this paper are shown for cases over both land and water using a model for cloud-free atmospheres developed by Rosenkranz (1993) . In the microwave region, the differences can be large due to the low emissivity of water in this
troposphere (channels 5–8) and stratosphere (channels 9–14). Channels 18–20, which are centered on the water vapor line at 183.31 GHz, are the prime channels for humidity profile retrievals. Details of the AMSU channels and their characteristics are given in Table 1 . Results in this paper are shown for cases over both land and water using a model for cloud-free atmospheres developed by Rosenkranz (1993) . In the microwave region, the differences can be large due to the low emissivity of water in this
) ( Grell et al. 1994 ) coupled to the Parameterization for Land–Atmosphere–Cloud Exchange (PLACE) land surface model ( Wetzel and Boone 1995 ). MM5– PLACE case studies will improve understanding of physical–dynamical processes that lead to urban-induced circulations. A new urban land parameterization is currently being integrated into PLACE to more accurately resolve critical urban parameters like roughness length, skin temperature, albedo, leaf area index, and vegetative fraction. This
) ( Grell et al. 1994 ) coupled to the Parameterization for Land–Atmosphere–Cloud Exchange (PLACE) land surface model ( Wetzel and Boone 1995 ). MM5– PLACE case studies will improve understanding of physical–dynamical processes that lead to urban-induced circulations. A new urban land parameterization is currently being integrated into PLACE to more accurately resolve critical urban parameters like roughness length, skin temperature, albedo, leaf area index, and vegetative fraction. This
Community Global Observing System Simulation Experiment (OSSE) Package (CGOP): Perfect Observations Simulation Validationare too high above 700 hPa; 5) precipitation is overestimated over land and in the Pacific intertropical convergence zone (ITCZ); 6) nonprecipitating cloud water amounts in G5NR are high, resulting in too much reflected shortwave radiation at the top of the atmosphere; and 7) G5NR clouds tend to be biased brighter, but they also tend to be biased lower in altitude, both for high and low clouds. Of these findings, difference 1 implies that small scales that give rise to representativeness errors in
are too high above 700 hPa; 5) precipitation is overestimated over land and in the Pacific intertropical convergence zone (ITCZ); 6) nonprecipitating cloud water amounts in G5NR are high, resulting in too much reflected shortwave radiation at the top of the atmosphere; and 7) G5NR clouds tend to be biased brighter, but they also tend to be biased lower in altitude, both for high and low clouds. Of these findings, difference 1 implies that small scales that give rise to representativeness errors in
coastal area in northern Wales (4.5°–3.0°W) more differences are observed. As summarized earlier, this period is characterized by southwesterly winds and this area is leeward of the Welsh mountains. The increase in resolution allows better reproduction of the influence of the orography and higher wind speeds are observed. For Liverpool Bay (3.0°W), atmosphere–land interactions produce a reduction of the wind velocity that is well observed with the increase of the resolution. Over land (3.0°–2.5°W
coastal area in northern Wales (4.5°–3.0°W) more differences are observed. As summarized earlier, this period is characterized by southwesterly winds and this area is leeward of the Welsh mountains. The increase in resolution allows better reproduction of the influence of the orography and higher wind speeds are observed. For Liverpool Bay (3.0°W), atmosphere–land interactions produce a reduction of the wind velocity that is well observed with the increase of the resolution. Over land (3.0°–2.5°W
