Intercomparison of Integrated Water Vapor Estimates from Multisensors in the Amazonian Region

Water vapor is an atmospheric component of major interest in atmospheric science because it affects the energy budget and plays a key role in several atmospheric processes. The Amazonian region is one of the most humid on the planet, and land use change is able to affect the hydrologic cycle in several areas and consequently to generate severe modifications in the global climate. Within this context, accessing the error associated with atmospheric humidity measurement and the validation of the integrated water vapor (IWV) quantification from different techniques is very important in this region. Using data collected during the Radiation, Cloud, and Climate Interactions in Amazonia during the Dry-to-Wet Transition Season (RACCI/DRY-TO-WET), an experiment carried out in southwestern Amazonia in 2002, this paper presents quality analysis of IWV measurements from RS80 radiosondes, a suite of GPS receivers, an Aerosol Robotic Network (AERONET) solar radiometer, and humidity sounding from the Humidity Sounder for Brazil (HSB) aboard the Aqua satellite. When compared to RS80 IWV values, the root-mean-square (RMS) from the AERONET and GPS results are of the order of 2.7 and 3.8 kg m 2 , respectively. The difference generated between IWV from the GPS receiver and RS80 during the daytime was larger than that of the nighttime period because of the combination of the influence of high ionospheric activity during the RACCI experiment and a daytime drier bias from the RS80.

[1]  P. Clarke.  GPS Satellite Surveying , 2007 .

[2]  I. Shapiro,et al.  Geodesy by radio interferometry: Effects of atmospheric modeling errors on estimates of baseline length , 1985 .

[3]  Masato Shiotani,et al.  Performance of the Meteolabor "Snow White" Chilled-Mirror Hygrometer in the Tropical Troposphere : Comparisons with the Vaisala RS80 A/H-Humicap Sensors , 2003 .

[4]  J. Barnard,et al.  Comparison of columnar water-vapor measurements from solar transmittance methods. , 2001, Applied optics.

[5]  Steven Businger,et al.  GPS Meteorology: Direct Estimation of the Absolute Value of Precipitable Water , 1996 .

[6]  Bjorn Lambrigtsen,et al.  The Humidity Sounder for Brazil - an international partnership , 2003, IEEE Trans. Geosci. Remote. Sens..

[7]  S. Clough,et al.  Dry Bias and Variability in Vaisala RS80-H Radiosondes: The ARM Experience , 2003 .

[8]  David Carlson,et al.  Corrections of Humidity Measurement Errors from the Vaisala RS80 Radiosonde—Application to TOGA COARE Data , 2002 .

[9]  Piers J. Sellers,et al.  Amazonian Deforestation and Regional Climate Change , 1991 .

[10]  Hajime Nakamura,et al.  GPS meteorology project of Japan —Exploring frontiers of geodesy— , 1998 .

[11]  A. Paukkunen,et al.  The accuracy and performance of the new Vaisala RS90 radiosonde in operational use , 2001 .

[12]  Ying-Hwa Kuo,et al.  Assimilation of Precipitable Water Measurements into a Mesoscale Numerical Model , 1993 .

[13]  Christian Rocken,et al.  Near real‐time GPS sensing of atmospheric water vapor , 1997 .

[14]  A. Smirnov,et al.  AERONET-a federated instrument network and data archive for aerosol Characterization , 1998 .

[15]  G. Seeber.  Satellite Geodesy: Foundations, Methods, and Applications , 1993 .

[16]  M. Garstang,et al.  Cloud and rain processes in a biosphere-atmosphere interaction context in the Amazon Region , 2002 .

[17]  Junhong Wang,et al.  Correction for Dry Bias in Vaisala Radiosonde RH Data , 1999 .

[18]  Ragne Emardson,et al.  The systematic behavior of water vapor estimates using four years of GPS observations , 2000, IEEE Trans. Geosci. Remote. Sens..

[19]  E. R. de Paula,et al.  Total electron content at low latitudes and its comparison with the IRI90 , 1994 .

[20]  David B. Parsons,et al.  Thermodynamic and Radiative Impact of the Correction of Sounding Humidity Bias in the Tropics , 2000 .

[21]  J. Pfaendtner,et al.  Inclusion of Special Sensor Microwave/imager (SSM/I) Total Precipitable Water Estimates into the GEOS-1 Data Assimilation System , 1995 .

[22]  Christian Rocken,et al.  Sensing integrated water vapor along GPS ray paths , 1997 .

[23]  T. Herring,et al.  GPS Meteorology: Remote Sensing of Atmospheric Water Vapor Using the Global Positioning System , 1992 .

[24]  Luiz Danilo Damasceno Ferreira,et al.  Application of ionospheric corrections in the equatorial region for L1 GPS users , 2000 .

[25]  Ying-Hwa Kuo,et al.  Variational Assimilation of Precipitable Water Using a Nonhydrostatic Mesoscale Adjoint Model. Part I: Moisture Retrieval and Sensitivity Experiments , 1996 .

[26]  J. Monico,et al.  Analysis of Relative Humidity Sensors at the WMO Radiosonde Intercomparison Experiment in Brazil , 2005 .

[27]  Robert Atlas,et al.  Assimilation of SSM/I-Derived Surface Rainfall and Total Precipitable Water for Improving the GEOS Analysis for Climate Studies , 2000 .

[28]  Veerabhadran Ramanathan,et al.  Observational constraints on non-Lorentzian continuum effects in the near-infrared solar spectrum using ARM ARESE data , 1998 .

[29]  Holger Vömel,et al.  Characterization and correction of relative humidity measurements from Vaisala RS80-A radiosondes at cold temperatures , 2001 .

[30]  Seth I. Gutman,et al.  Developing an Operational, Surface-Based, GPS, Water Vapor Observing System for NOAA: Network Design and Results , 2000 .

[31]  Charles M. Meertens,et al.  TEQC: The Multi-Purpose Toolkit for GPS/GLONASS Data , 1999, GPS Solutions.

[32]  Steven Businger,et al.  GPS Meteorology: Mapping Zenith Wet Delays onto Precipitable Water , 1994 .

[33]  P. Dubuisson,et al.  Estimating the atmospheric water vapor content from multi-filter rotating shadow-band radiometry at São Paulo, Brazil , 2004 .

[34]  Jean-Pierre Aubagnac,et al.  Comparison of Near–Real Time Estimates of Integrated Water Vapor Derived with GPS, Radiosondes, and Microwave Radiometer , 2005 .

[35]  Shepard A. Clough,et al.  The ARM program's water vapor intensive observation periods - Overview, initial accomplishments, and future challenges , 2003 .

[36]  Beat Schmid,et al.  Modeled and empirical approaches for retrieving columnar water vapor from solar transmittance measurements in the 0.72, 0.82, and 0.94 μm absorption bands , 2000 .

[37]  R. Andreoli,et al.  The inclusion of integrated water vapor estimates from AIRS / AMSU and SSM / I sensors into PSAS data assimilation system in the CPTEC , 2006 .

[38]  Philip W. Rosenkranz,et al.  Retrieval of temperature and moisture profiles from AMSU-A and AMSU-B measurements , 2001, IEEE Trans. Geosci. Remote. Sens..

[39]  H. Marel.  Exploitation of Ground Based GPS for Numerical Weather Prediction and Climate Applications in Europe , 2002 .