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
2019-09-16 14:30 89.2 12.1 30.1 5.1 150 8.7 149 24.728 725.2 0.00
2019-09-16 14:25 89.9 12.0 30.6 6.2 146 9.2 139 24.748 772.6 0.00
2019-09-16 14:20 89.8 12.1 30.6 7.0 122 11.3 134 24.740 770.1 0.00
2019-09-16 14:15 89.8 12.8 32.1 5.5 72 9.3 121 24.763 802.0 0.00
2019-09-16 14:10 90.7 12.3 31.7 7.0 109 11.9 118 24.757 857.0 0.00
2019-09-16 14:05 91.5 11.6 31.0 6.0 121 17.9 179 24.745 887.0 0.00
2019-09-16 14:00 89.5 11.8 29.8 2.4 176 6.1 230 24.738 905.0 0.00
2019-09-16 13:55 88.4 11.8 29.1 6.1 244 8.2 220 24.723 839.0 0.00
2019-09-16 13:50 87.9 12.5 30.1 6.8 264 10.4 233 24.750 679.2 0.00
2019-09-16 13:45 88.4 12.5 30.4 4.6 302 6.7 213 24.752 834.0 0.00
2019-09-16 13:40 88.1 12.5 30.1 4.7 241 8.3 191 24.760 847.0 0.00
2019-09-16 13:35 88.9 12.6 30.9 6.1 135 10.6 141 24.764 883.0 0.00
2019-09-16 13:30 88.8 12.6 30.9 5.5 235 9.6 202 24.766 906.0 0.00
2019-09-16 13:25 89.1 12.1 30.2 4.8 135 7.5 151 24.766 907.0 0.00
2019-09-16 13:20 87.3 12.7 29.9 3.4 151 8.1 136 24.767 790.1 0.00
2019-09-16 13:15 86.4 13.1 30.0 4.5 141 7.0 137 24.768 453.6 0.00
2019-09-16 13:10 85.9 14.2 31.5 3.4 144 7.7 116 24.769 385.8 0.00
2019-09-16 13:05 85.9 12.9 29.2 3.5 78 7.7 93 24.770 329.3 0.00
2019-09-16 13:00 86.2 13.4 30.5 5.3 93 8.7 125 24.771 325.0 0.00
2019-09-16 12:55 87.3 13.2 30.9 5.6 115 8.3 81 24.771 386.8 0.00
2019-09-16 12:50 88.0 12.9 30.8 4.9 82 7.3 82 24.773 818.0 0.00
2019-09-16 12:45 87.2 13.2 30.7 6.1 138 9.1 154 24.774 832.0 0.00
2019-09-16 12:40 86.2 13.6 30.8 6.2 92 10.0 142 24.775 556.3 0.00
2019-09-16 12:35 85.4 13.6 30.1 6.8 124 10.8 126 24.774 452.3 0.00
2019-09-16 12:30 85.4 14.5 31.7 7.3 141 12.1 133 24.773 431.1 0.00
2019-09-16 12:25 85.6 14.2 31.3 8.1 152 11.0 149 24.771 415.6 0.00
2019-09-16 12:20 85.7 13.1 29.3 5.8 119 9.6 127 24.771 494.2 0.00
2019-09-16 12:15 86.6 12.7 29.3 5.6 156 9.8 127 24.775 456.1 0.00
2019-09-16 12:10 87.6 12.9 30.6 7.2 131 10.6 130 24.776 888.0 0.00
2019-09-16 12:05 87.1 13.4 31.1 6.5 151 10.7 164 24.776 875.0 0.00
CIRA

Cooperative Institute for Research in the Atmosphere

Jiang, Lide

Lide Jiang

Job Title:
Research Scientist/Scholar II
Mailing Addresss:
1375 Campus Delivery
Fort Collins, CO 80523-1375
    Publications

    VIIRS ocean color products over global open oceans and turbid coastal/inland waters

    Published Date: 2017
    Published By: Conference

    VIIRS ocean color products over global open oceans and turbid coastal/inland waters

    Published Date: 2018
    Published By: Conference

    VIIRS Mission-long ocean color data reprocessing and demonstration of global ocean color data monitoring tool

    Published Date: 2017
    Published By: Conference

    RSB calibration of SNPP VIIRS using solar diffuser illuminated by scattered light

    Published Date: 2017
    Published By: Conference

    Evaluation of VIIRS ocean color products in open ocean and coastal/inland waters

    Published Date: 2017
    Published By: Conference

    Comparison of GOCI and VIIRS ocean color products in the Western Pacific Region

    Published Date: 2018
    Published By: Conference

    Comparison of GOCI and VIIRS ocean color products in the Western Pacific region

    Published Date: 2017
    Published By: Conference

    Ocean color remote sensing of oceanic respone to passage of tropical cyclones

    Published Date: 2018
    Published By: Conference

    VIIRS-derived ocean color product using imaging bands

    Published Date: 2018
    Published By: Remote Sensing

    An Efficient Approach for VIIRS RDR to SDR Data Processing

    Published Date: 2014
    Published By: IEEE Xplore Digital Library
    The Visible Infrared Imaging Radiometer Suite (VIIRS) Raw Data Records (or Level-0 data) are processed using the current standard Algorithm Development Library (ADL) to produce Sensor Data Records (SDR; or Level-1B data). The ocean color Environmental Data Records (EDR), one of the most important product sets derived from VIIRS, are processed from the SDR of the visible and near-infrared moderate resolution (M) bands. As the ocean color EDR are highly sensitive to the quality of the SDR, the bands from which the EDR data arise must be accurately calibrated. These bands are calibrated on-orbit using the onboard Solar Diffuser, and the derived calibration coefficients are called F-factors. The F-factors used in the forward operational process may have large uncertainty due to various reasons, and thus, to obtain high-quality ocean color EDR, the SDR needs to be regularly reprocessed with improved F-factors. The SDR reprocessing, however, requires tremendous computational power and storage space, which is about 27 TB for one year of ocean-color-related SDR data. In this letter, we present an efficient and robust method for reduction of the computational demand and storage requirement. The method is developed based on the linear relationship between the SDR radiance/reflectance and the F-factors. With this linear relationship, the new SDR radiance/reflectance can be calculated from the original SDR radiance/reflectance and the ratio of the updated and the original F-factors at approximately 100th or less of the original central processing unit requirement. The produced SDR with this new approach fully agrees with those generated using the ADL package. This new approach can also be implemented to directly update the SDR in the EDR data processing, which eliminates the hassle of a huge data storage requirement as well as that of intensive computational demand. This approach may also be applied to other remote sensors for data reprocessing from raw instrument data to science data.