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Cooperative Institute for Research in the Atmosphere
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Search CIRA Website x
Colorado State University
  • Home
  • Welcome & About
    • About CIRA
      • Jobs
      • Letter from Christian Kummerow:
      • Map & Directions
      • Organizational Structure
      • Reports
      • Room Schedules
      • Staff Directory
      • Strategic Plan
      • Vision & Mission Statement
    • Themes
      • Climate and Weather Processes
      • Competitive Projects
      • Data Assimilation
      • Data Distributions
      • Education and Outreach
      • Modeling Systems Research
      • NOAA Projects
      • Satellite Algorithm Development, Training and Education
      • Societal and Economic Impact Studies
    • Collaborative Groups
      • Colorado Climate Center
      • National Park Service
      • Regional and Mesoscale Meteorology Branch
  • Teams
    • Colorado Teams:
      • NOAA/Earth System Research Lab (ESRL) – Boulder, CO
      • Air Quality – Fort Collins, CO
      • Atmospheric Science (ATS) – Fort Collins, CO
      • Carbon – Fort Collins, CO
      • CIRA Software Engineering Group (CSEG) – Fort Collins, CO
      • Data Assimilation (DA) – Fort Collins, CO
      • Data Processing Centers (DPC) – Fort Collins, CO
      • Independent – Fort Collins, CO
      • MetSat – Fort Collins, CO
      • Regional and Mesoscale Meteorology Branch (RAMMB) – Fort Collins, CO
      • Training – Fort Collins, CO
      • Tropical Cyclone – Fort Collins, CO
    • Other Location Teams:
      • National Hurricane Center – Miami, FL
      • NESDIS Environmental Applications Team (NEAT) – College Park, MD
      • NWS/Meteorological Development Laboratory (MDL) – Silver Spring, MD
      • NWS/Aviation Weather Center (AWC) – Kansas City, MO
      • Office of Marine and Aviation Operations (OMAO-Training) – Kansas City, MO
  • News & Events
    • News
      • CIRA Administration News
      • Magazines
      • Reports
    • Events
      • Conferences
      • Seminars
  • Research & Publications
  • Imagery & Data
    • Imagery
      • Air Quality Research
        • Improve
        • VIEWS
      • CIRA Algorithm Testbed
      • CIRA Weather Station
      • RAMMB SLIDER
    • Data
      • CloudSat Data Processing Center
      • ECMWF Nature Run
      • RAMSDIS Online
        • GOES-West / GOES-East
        • Synthetic Forecast Imagery
        • Tropical Imagery
        • Suomi NPP VIIRS Imagery
  • Contact Us
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      • Boulder
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  • Search
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Search CIRA Website x
Christman Field Latest Observations
Date Time
MST
Temp
°F
RH
%
DewPt
°F
Wind
mph
Dir
°
Gust
mph
Dir
°
Press
in Hg
Solar
W/m^2
Prec
in
2021-04-19 22:00 20.7 94.8 19.4 3.3 310 3.7 301 0.000 0.1 0.00
2021-04-19 21:55 20.7 94.7 19.4 3.6 301 3.9 303 0.000 0.1 0.00
2021-04-19 21:50 20.7 94.6 19.4 3.5 303 3.8 299 0.000 0.1 0.00
2021-04-19 21:45 20.7 94.7 19.5 3.8 301 4.0 307 0.000 0.1 0.00
2021-04-19 21:40 20.7 94.7 19.5 4.0 311 4.5 311 0.000 0.1 0.00
2021-04-19 21:35 20.7 94.8 19.5 3.7 302 4.1 296 0.000 0.1 0.00
2021-04-19 21:30 20.7 94.9 19.5 3.2 287 3.5 287 0.000 0.1 0.00
2021-04-19 21:25 20.7 94.7 19.4 2.7 293 3.1 294 0.000 0.1 0.00
2021-04-19 21:20 20.7 94.7 19.4 2.9 319 3.5 332 0.000 0.1 0.00
2021-04-19 21:15 20.8 94.6 19.5 2.7 334 3.2 334 0.000 0.1 0.00
2021-04-19 21:10 20.9 94.7 19.6 3.2 332 4.9 339 0.000 0.1 0.00
2021-04-19 21:05 20.9 94.7 19.6 2.4 325 3.5 325 0.000 0.1 0.00
2021-04-19 21:00 20.9 94.7 19.6 2.6 302 3.3 296 0.000 0.1 0.00
2021-04-19 20:55 20.9 94.7 19.6 2.1 325 3.0 319 0.000 0.1 0.00
2021-04-19 20:50 21.0 94.5 19.7 2.2 323 3.6 344 0.000 0.1 0.00
2021-04-19 20:45 21.0 94.5 19.7 3.4 316 5.0 323 0.000 0.1 0.00
2021-04-19 20:40 21.0 94.5 19.7 3.8 322 4.8 324 0.000 0.1 0.00
2021-04-19 20:35 21.0 94.4 19.6 4.0 333 4.8 323 0.000 0.1 0.00
2021-04-19 20:30 21.0 94.6 19.7 4.5 307 6.4 316 0.000 0.1 0.00
2021-04-19 20:25 20.9 94.6 19.6 4.1 311 5.7 336 0.000 0.1 0.00
2021-04-19 20:20 21.0 94.7 19.7 5.0 341 6.6 326 0.000 0.1 0.00
2021-04-19 20:15 20.9 94.8 19.7 4.9 336 5.9 331 0.000 0.1 0.00
2021-04-19 20:10 20.9 94.6 19.6 6.6 332 8.2 337 0.000 0.1 0.00
2021-04-19 20:05 21.0 94.7 19.7 6.9 332 8.8 332 0.000 0.1 0.00
2021-04-19 20:00 21.0 94.5 19.6 9.0 332 11.7 338 0.000 0.1 0.00
2021-04-19 19:55 21.1 94.8 19.9 9.0 337 11.3 339 0.000 0.1 0.00
2021-04-19 19:50 21.2 94.9 19.9 9.4 329 11.2 335 0.000 0.1 0.00
2021-04-19 19:45 21.2 94.9 20.0 8.8 338 11.2 328 0.000 0.1 0.00
2021-04-19 19:40 21.4 95.3 20.2 8.5 323 10.6 321 0.000 0.1 0.00
2021-04-19 19:35 21.4 95.3 20.2 7.4 322 8.8 330 0.000 0.1 0.00
CIRA

Cooperative Institute for Research in the Atmosphere

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Ocean reflectance spectra at the red, near-infrared, and shortwave infrared from highly turbid waters: A study in the Bohai Sea, Yellow Sea, and East China Sea


Normalized water-leaving radiance spectra nLw(λ) at the red, near-infrared (NIR), and shortwave infrared (SWIR) are quantified and characterized in highly turbid waters of the western Pacific using 3 yr (2009–2011) observations from the Moderate Resolution Imaging Spectroradiometer on the satellite Aqua. nLw(645; red), nLw(859; NIR), and nLw(1240; SWIR) were higher in the coastal region and river estuaries, with SWIR nLw(1240) reaching up to ∼ 0.2 mW cm−2 µm−1 sr−1 in Hangzhou Bay during winter. The NIR ocean-reflectance spectral shape represented by the ratio of the normalized water-leaving reflectance ρwN(λ) at the two NIR bands ρwN(748) : ρwN(869) is highly dynamic and region-dependent. The NIR spectral feature associated with the sediment source from the Yellow River and Ancient Yellow River is noticeably different from that of the Yangtze River. There are non-negligible SWIR nLw(1240) contributions for waters with the NIR nLw(859) > ∼ 2.5 mW cm−2 µm−1 sr−1. Estimation of the NIR ocean reflectance with iterative approaches might only be accurate for turbid waters with nLw(859) < ∼ 1.5 mW cm−2 µm−1 sr−1. Thus, the SWIR atmospherics correction algorithm for satellite ocean-color data processing is indispensable to derive accurate nLw(λ) for highly turbid waters. Current existing satellite algorithms for chlorophyll a, diffuse attenuation coefficient at the wavelength of 490 nm (Kd(490)), total suspended matter, and inherent optical properties (IOPs) using nLw(λ) at the red band for coastal waters are limited and can only be applied to turbid waters with nLw(859) < ∼ 1.5 mW cm−2 µm−1 sr−1. Thus, the NIR nLw(λ) measurements are required to characterize water properties for highly turbid waters. Based on the fact that pure water absorption is significantly larger than other absorption components in the NIR wavelengths, we show that it is feasible to analytically derive accurate IOP data for turbid waters with combined satellite-measured visible-NIR nLw(λ) spectra data.

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