The Intergovernmental Panel on Climate Change (IPCC) Working Group-1 has released its contribution to the 5th Assessment Report, titled "Climate Change 2013: The Physical Science Basis". This contribution concludes that human influence on the climate system is clear and evident in most regions of the globe.
Carl Mears, a long time member of RSS was a contributing author to both Chapter 2 (Observations: Atmosphere and Surface) and to Chapter 9 (Evaluation of Climate Models).
In the many reference sections listed in the report, Remote Sensing Systems was represented by 20 peer-reviewed journal papers (11 as primary authors) cited from 6 RSS scientists. This level of contribution is remarkable from a small company and highlights the significant work performed here at RSS that contributes to greater scientific understanding of the climate.
The following journal papers were cited whose lead authors are scientists at Remote Sensing Systems:
- Mears, C. A., F. J. Wentz, and P. W. Thorne, 2012: Assessing the value of Microwave Sounding Unit-radiosonde comparisons in ascertaining errors in climate data records of tropospheric temperatures. Journal of Geophysical Research-Atmospheres, 117, D19103, doi:10.1029/2012JD017710.
- Wentz, F. J., and L. Ricciardulli, 2011: Comment on "Global trends in wind speed and wave height". Science, 334, 905-905.
- Mears, C. A., F. J. Wentz, P. Thorne, and D. Bernie, 2011: Assessing uncertainty in estimates of atmospheric temperature changes from MSU and AMSU using a Monte-Carlo estimation technique. Journal of Geophysical Research-Atmospheres, 116, D08112, doi:10.1029/2010JD014954.
- Wentz, F. J., and L. Ricciardulli, 2011: Comment on "Global trends in wind speed and wave height". Science, 334, 905-905.
- Mears, C., J. Wang, S. Ho, L. Zhang, and X. Zhou, 2010: Total column water vapor, in State of the Climate in 2009. Bulletin of the American Meteorological Society, D. S. Arndt, M. O. Baringer, and M. R. Johnson, Eds. 91, S29-S31.
- Mears, C. A., and F. J. Wentz, 2009a: Construction of the Remote Sensing Systems V3.2 Atmospheric Temperature Records from the MSU and AMSU Microwave Sounders. Journal of Atmospheric and Oceanic Technology, 26, 1040-1056.
- Mears, C. A., and F. J. Wentz, 2009b: Construction of the RSS V3.2 Lower-Tropospheric Temperature Dataset from the MSU and AMSU Microwave Sounders. Journal of Atmospheric and Oceanic Technology, 26, 1493-1509.
- Mears, C. A., B. D. Santer, F. J. Wentz, K. E. Taylor, and M. F. Wehner, 2007: Relationship between temperature and precipitable water changes over tropical oceans. Geophysical Research Letters, 34, L24709 , doi:10.1029/2007GL031936.
- Wentz, F. J., L. Ricciardulli, K. Hilburn, and C. Mears, 2007: How much more rain will global warming bring? Science, 317, 233-235.
- Gentemann, C., F. Wentz, C. Mears, and D. Smith, 2004: In situ validation of Tropical Rainfall Measuring Mission microwave sea surface temperatures. Journal of Geophysical Research-Oceans, 109, C04021, doi:10.1029/2003JC002092.
- Wentz, F., C. Gentemann, D. Smith, and D. Chelton, 2000: Satellite measurements of sea surface temperature through clouds. Science, 288, 847-850.
Data Products produced by Remote Sensing Systems or Data Products produced by other scientists using RSS data as input are found in many locations throughout the report. The contributions are summarized in the graphic below. Figure references within the below graphic are located in the report.
In the above figure, the following products are identified. How these products relate to Remote Sensing Systems is described.
CCMP Winds: The Cross-Correlated Multi-Platform wind product is created by Atlas et al. and distributed by the NASA Physical Oceanography DAAC. This product uses in situ data, the ECWMF Reanalysis model winds and RSS radiometer and scatterometer winds in a 4D-Var assimilation method to produce 4x/daily winds. The RSS winds are SSM/I (V6), SSMIS (V7), TMI (V4), AMSR-E (V5), WindSat (V7) and QuikSCAT (V3a and V4). [Atlas, R. M., R. N. Hoffman, J. Ardizzone, S. M. Leidner, J. C. Jusem, D. K. Smith and D. Gombos, (2011) A Cross-Calibrated, Multi-Platform Ocean Surface Wind Velocity Product for Meteorological and Oceanographic Applications, Bulletin of the American Meteorological Society, 92(11), 157-174.]
NOAA Sea Winds: The Blended Sea Winds product is created by Zhang et al. and distributed by NOAA National Climate Data Center. This product is created using RSS microwave radiometer and scatterometer winds in an optimal interpolation scheme to produce 4/daily winds. The RSS winds are SSM/I (V6), SSMIS (V7), AMSR-E (V5), TMI (V4), and QuikSCAT (V3a). [Zhang, H.-M., R. W. Reynolds and J. J. Bates, Blended and gridded high resolution global sea surface wind speed and climatology from multiple satellites: 1987 - present, paper presented at American Meteorological Society 2006 Annual Meeting, Atlanta, GA, 2006.]
WHOI OAFlux: The Objectively Analyzed Air-Sea Heat Fluxes dataset is created by Yu and Weller at Woods Hole Oceanographic Institute. The product is created using RSS winds from SSM/I (V6), AMSR-E (V5) and QuikSCAT (V3), in addition to other state variables (SST, air temperature, humidity). They also use the NOAA Optimum Interpolation (OI) 0.25-degree daily SST analysis produced by Reynolds et al. This product incorporates RSS AMSR-E SSTs into the interpolation scheme. [Yu, L., X.Jin, and R.A.Weller (2008), Multidecadal Global Flux Datasets From the Objectively Analyzed Air-Sea Fluxes (OAFlux) Project: Latent and Sensible Heat Fluxes, Ocean Evaporation, and Related Surface Meteorological Variables, Report OA-2008-01, 64pp., Woods Hole Oceanographic Institution, Woods Hole, MA, USA.]
NASA GPCP: The Global Daily Merged Precipitation Analyses of the Global Precipitation Climatology Project is created by Bob Adler et al. at NASA Goddard Space Flight Center. The product incorporates the RSS SSM/I and SSMIS (both V7) brightness temperature data in constructing a remote-sensing based precipitation product available at NOAA NCDC. GPCP is included in AR5 report in several figures (Fig 3.7; Fig 7.6; Fig 7.7; Fig 9.32; Fig 9.38; Fig 9.40; Box 14.1:Fig 1; Fig 14.4). [Huffman, G. J., R. F. Adler, D. T. Bolvin and G. Gu, (2009) Improving the Global Precipitation Record: GPCP Version 2.1., Geophys. Res. Lett., 36, L17808, doi:10.1029/2009GL040000.]
UWISC Cloud Water: This global ocean cloud liquid water path data set was created by Chris O’Dell et al. at University of Wisconsin. The product was constructed using RSS SSM/I, TMI and AMSR-E CLW values from 1988 to 2005. This data set is used in panel b of Figure 7.5. [O'Dell, C., F. J. Wentz and R. Bennartz, (2008) Cloud Liquid Water Path From Satellite-Based Passive Microwave Observations: A New Climatology Over the Global Oceans, Journal of Climate, 21(8), 1721-1739.]
OSU Wind Stress: A Climatology of Global Ocean Winds (COGOW) is constructed by Risien and Chelton at Oregon State University. The RSS scatterometer and AMSR-E SST data are used to produce the data product. [Risien, C. M. and D. B. Chelton, (2006) A Satellite-Derived Climatology of Global Ocean Winds, Remote Sensing of Environment, 105(3), 221-236.]
NSIDC EASE Grid Brightness Temperature Data: RSS MW brightness temperatures are obtained for SSM/I, SSMIS and AMSR-E instruments and used in creating a gridded brightness temperature data set available from NSIDC. This data product is used by many researchers to study sea ice extent. . These EASE-Grid brightness temperatures were used in making Figures 4.1, 4.2, 4.3, 4.4, and 4.6 in Chapter 4, Observations: Cryosphere. Also, the sea ice extent time series in Figure 9.4 used the NSIDC data. [Brodzik, M. J., B. Billingsley, T. Haran, B. Raup, M. H. Savoie. 2012. EASE-Grid 2.0: Incremental but Significant Improvements for Earth–Gridded Data Sets. ISPRS International Journal of Geo–Information 1(1):32-45. doi:10.3390/ijgi1010032. ]
NCDC ERSST: the ERSST v3 data set mentioned in the report incorporates in situ data as well as satellite SSTs (both IR and MW) in the later years. The OI SST product (Reynolds) is used in constructing ERSST. The Reynolds OISST incorporates RSS AMSR-E and WindSat SST data. The ERSST is shown in Figures 11.2, 11.3, 11.4, 11.7 and 14.3. [Banzon, V. F. and R. W. Reynolds, (2013) Use of WindSat to Extend a Microwave-Based Daily Optimum Interpolation Sea Surface Temperature Time Series, Journal of Climate, 26(8), 2557-2562.]
Acronyms