Junhong Wang

Scientist II
TIIMES - EOL
WCAS

Contact Information:
PO Box 3000, Boulder, CO 80307-3000
Office: FL1 - 2066
Telephone: 303-497-8837
Email: junhong@ucar.edu
Home Page

Project Summary:

Accomplishments for FY07 and plans for FY08: 

Understanding warm-season precipitation diurnal cycle over the U.S. Great Plains from North American Regional Analysis and a regional climate model 

The diurnal cycle of precipitation is large over continents. It provides an excellent test bed for numerical parameterizations such as moist convection and planetary boundary layer schemes in atmospheric models.  In contrast to later afternoon peaks over most land areas, warm-season precipitation in the central U.S. is characterized by a maximum from midnight to early morning, which is mainly a result of the diurnal cycle in precipitation frequency. Previous studies have suggested a number of processes that may contribute to the nocturnal precipitation maximum (NPM). However, the exact underlying processes leading to the NPM are not fully understood. As a result, the NPM is not captured by most global and regional weather and climate models. 

During FY 07, the focus was on preparing a journal paper to summarize the results. The draft manuscript is close to finish. Here is the abstract of the paper.  In this study, we investigate the physical processes that suppress afternoon moist convection and lead to the NPM using data collected during the International H2O Project (IHOP) (May-June 2002) and the North American Regional Reanalysis (NARR) data. The NARR data show good agreement with the radar data on diurnal cycle of precipitation from the Rockies to the Great Plains. The diurnal cycle of CAPE and CIN profiles calculated from 3-hourly radiosonde data shows that the afternoon is most favorable condition for convection initiations with maximum surface CAPE and minimum surface CIN. However, the large-scale subsidence prevents the development of moist convection in the afternoon. The CAPE/CIN profile also shows the second small maximum/minimum at ~500 m in early morning during rainy days, indicating the elevated instability and subsequently elevated convection initiation. The diurnal cycle of U.S. summer precipitation during the IHOP period is simulated by a MM5-based regional climate model (CMM5) using both Grell and Kain-Fritsch cumulus parameterization schemes. Both simulations are able to capture the big rain events during the period. The Grell scheme realistically depicts the NPM over the central Plain and the eastward propagation of convective systems from Rockies to Great Plains. However, the Kain-Fritsch (KF) scheme produces an afternoon precipitation maximum. Both Grell and KF schemes show the large-scale subsidence during daytime. However, the subsidence simulated by the KF scheme is narrower in time and has a maximum at higher altitudes. The maximum surface CAPE in the afternoon in both simulations is only about half of that calculated from the radiosonde data. The simulations do not show the observed elevated instability in early morning. 

During FY08, I will continue to write and revise the paper, and then submit the paper. More analyses might be needed for the paper.

A Global, 2-Hourly Atmospheric Precipitable Water Dataset from GPS Measurement

Water vapor plays a central role in atmospheric radiation, the hydrological cycle and in understanding and predicting global climate change. Therefore, it is vital to advance the understanding of water vapor variability and change, but such advancement is hampered by inadequate observations. Several studies and reports have called for creating global water vapor datasets with sufficient accuracy and temporal resolution, and more importantly long-term stability. None of existing radiosonde, satellite or blended datasets can meet the requirements for the new water vapor datasets. Global GPS measurements of atmospheric precipitable water (PW), however, can meet all of these requirements with an accuracy of < 2 mm, and can be considered as a calibration standard to validate other measurements. Unfortunately, there has been no effort to take advantage of the growing network of global GPS stations to create a global GPS-derived PW dataset. 

During FY07, the paper summarizing the GPS-PW analysis technique, dataset and validations and submitted to JGR was revised, accepted and published in JGR (Wang, J., L. Zhang, A. Dai, T. Van Hove, and J. Van Baelen, 2007: A near-global, 8-year, 2-hourly atmospheric precipitable water dataset from ground-based GPS measurements. J. Geophys. Res., 112, D11107, doi:10.1029/2006JD007529.) In addition, the GPS ZTD product from U.S. Suominet regional network has been obtained and processed using the same technique for the global network. As a result, the GPS-PW data at additional ~200 stations in U.S. for 2003-2006 are added to the global PW dataset.

During FY08, the dataset will continue to be updated when the ZTD data become available. In the mean time, the ZTD products from other non-IGS regional networks, such as Japan and Korean will be processed and added to our global PW dataset to increase the further spatial coverage if they are available. 

Monitoring the quality of global radiosonde humidity record using ground-based GPS measurements

Global radiosonde data represent an increasingly valuable resource for studies of climate change. Unfortunately, the usefulness of radiosonde data for long-term climate monitoring is limited by errors and biases associated with instrument and data processing procedures and by radiosonde changes among stations and with time. The primary goal of this study is to take advantage of increasing volume and maturity of GPS data and more importantly its long-term stability, and use it to monitor the quality of global radiosonde data and potentially improve the long-term radiosonde climate records. A global, 10-year (1997-2006), 2-hourly data set of atmospheric precipitable water (PW) has been produced from ground-based GPS measurements of zenith tropospheric delay (ZTD) and will be updated frequently when the ZTD becomes available.

During FY07, a paper was prepared to summarize the project, submitted to Journal of Climate, revised, and accepted (Wang, J., and L. Zhang, 2007: Systematic errors in global radiosonde precipitable water data from comparisons with ground-based GPS measurements. J. Climate, accepted.) The abstract of this paper is following. A global, ten-year (February 1997 - April 2006), two-hourly data set of atmospheric precipitable water (PW) was produced from ground-based Global Positioning System (GPS) measurements of zenith tropospheric delay (ZTD) at approximately 350 International Global Navigation Satellite Systems (GNSS) Service (IGS) ground stations. A total of 130 pairs of radiosonde and GPS stations are found within 50 km in distance and 100 m in elevation of each other. Fourteen types of radiosondes are launched at these stations, and three types of humidity sensors are used: capacitive polymer, carbon hygristor and goldbeater’s skin. The PW comparison between radiosonde and GPS data reveals three types of systematic errors in the global radiosonde PW data: measurement biases of the fourteen radiosonde types along with their characteristics, long-term temporal inhomogeneity and diurnal sampling errors of once and twice daily radiosonde data. The capacitive polymer generally shows mean dry bias of -1.19 mm (-6.8%). However, the carbon hygristor and goldbeater’s skin hygrometers have mean moist biases of 1.01 mm (3.4%) and 0.76 mm (5.4%), respectively. The protective shield over the humidity sensor boom introduced in late 2000 reduces the PW dry bias from 6.1% and 2.6% in 2000 to 3.9% and -1.14% (wet bias) in 2001 for the Vaisala RS80A and RS80H, respectively. The dry bias in Vaisala sondes has larger magnitudes during the day than at night, especially for RS90 and RS92 with a day-night difference of 5-7%. The time series of monthly mean PW differences between the radiosonde and GPS are able to detect significant changes associated with known radiosonde type changes. Such changes would have a significant impact on the long-term trend estimate. Diurnal sampling errors of twice daily radiosonde data are generally within 2%, but can be as much as 10-15% for the once daily soundings. In conclusion, this study demonstrates that the global GPS-PW data are useful for identifying and quantifying several kinds of systematic errors in global radiosonde PW data. Several recommendations are made for future needs of global radiosonde and GPS networks and data.

During FY08, the project will be expanded to develop correction methods to correct historical radiosonde data based on the comparisons between GPS and radiosonde data.

Diurnal variations of precipitable water on a near-global scale

There exist substantial diurnal variations in atmospheric water vapor, both column-integrated values (i.e., PW) and vertical profiles. The water vapor diurnal variations affect surface and atmospheric longwave radiation and atmospheric absorption of solar radiation. They are also related to many other processes, such as diurnal variations in moist convection and precipitation, surface wind convergence and surface evapotranspiration. Unfortunately, there is a lack of data with high temporal resolution for studying the diurnal cycle of water vapor on the global scale. 

 In FY07, we started to study global PW diurnal variations in details. The PW diurnal cycle is small, but significant. Global, N.H., S.H. annual mean peak-to-peak amplitudes are 0.66, 0.53 and 1.11 mm, respectively. On global and hemispheric average, PW peaks from late afternoon to mid-night. The amplitude of PW diurnal cycle is generally smaller at higher latitudes than the Tropics, varies significantly from station to station, and is the largest in summer. The phase is dominated from noon to mid-night. Seasonal variations of diurnal cycle in different regions are shown. The sub-monthly variability of PW has much larger magnitude than the diurnal cycle. The PW diurnal cycle is poorly represented in the NCEP/NCAR reanalysis in comparison with the observed diurnal cycle. 

During FY08, further analysis will be done to document diurnal variations of PW. By co-relating with other variables observed diurnal cycle of PW will be understood. A journal paper will be prepared to summarize the results.

Comparisons of atmospheric precipitable water between three reanalyses (NCEP/NCAR, ERA-40 and JRA) and ground-based GPS measurements

The reanalysis data have been proved to be very important for a variety of climate and weather research. Thus the validation and evaluation of the reanalysis data are essential for improving its future quality and expanding its applications. The objective of this project is to validate the reanalysis PW data on different time scales by comparing with the 2-hourly GPS PW data with special focus on the diurnal cycle.

Click on picture to view the entire figure.

Figure 1. Comparisons of seasonal variations of PW diurnal anomaly (in mm, color) from GPS (left panel) and NCEP/NCAR reanalysis (right panel) in Europe. The contours show the sub-monthly variability.

During FY07, the GPS-derived PW is compared to the NCEP/NCAR reanalysis from diurnal to interannual time scales in four regions, Europe, Northern Hemisphere (N.H.) Mountains, Darwin and 30°-70°S regions.  The PW diurnal cycle is poorly represented in the NCEP/NCAR reanalysis (Fig. 1). The amplitude of the PW diurnal cycle in the reanalysis is much smaller than that from the GPS dataset. The PW diurnal phase is captured by the reanalysis in Darwin and N.H. Mountains, but not in Europe and the 30°-70°S regions. The seasonal variations of the diurnal cycle are not as strong as that shown by the GPS data. The variability of PW diurnal cycle among stations in each region for the GPS data is much weaker than that among grid boxes for the reanalysis. The diurnal cycle of sub-monthly variability and its seasonal modulations from the reanalysis are generally in agreement with the GPS data. Comparisons of monthly mean PW values from 1997 to 2006 show dry biases in the reanalysis in Europe, 30°-70°S and Darwin, but moist biases in N.H. Mountains. The moist bias in the mountain region is likely due to the difference between the point value for the GPS and the grid box average for the reanalysis.

During FY08, more and detailed analysis will be done to compare PW in other regions and for other analysis products and understand the differences.

Community Service:

• Editor - Journal of Atmospheric and Oceanic Technology
• Lecture for "Measurements and Instruments", Colorado State University, Fort Collins, CO

Presentations:

• A global, 2-hourly atmospheric precipitable water dataset from ground-based GPS measurements for climate and weather studies, Boulder USA, November 2006
• AMS Editors Panel: How to Write Publishable Papers for the AMS, other, Boulder USA, May 2007
• Diurnal variation of atmospheric precipitable water over the globe from ground-based GPS measurements, Beijing CHN, July 2007
• Diurnal variation of atmospheric precipitable water over the globe from ground-based GPS measurements, Qingdao CHN, July 2007
• Monitoring the quality of global radiosonde humidity record using ground-based GPS measurements of precipitable water, San Antonio USA, January 2007
• Monitoring the quality of global radiosonde humidity record using ground-based GPS measurements of precipitable water, Boulder USA, April 2007
• Understanding warm-season precipitation diurnal cycle in the central U.S. from North American Regional Analysis and a regional climate model, Boulder USA, December 2006

TIIMES External Collaborators:

Linnea Avallone, University of Colorado
Paul Ciesielski, Colorado State University
Vanda Grubisic, Desert Research Institute
Dick Johnson, Colorado State University
Xing-Zhong Liang, Illinois State Water Survey
Siming Liu, Chinese Academy of Sciences
Joel Van Baelen, Laboratoire de Meteorologie Physique
Paquita Zuidema, University of Miami

Publications:

Wang, J., L. Zhang, A. Dai, T. VanHove, J. Van Baelen, 2007: A near-global, 2-hourly data set of atmospheric precipitable water from ground-based GPS measurements. J. Geophys. Res., 112, D11107, doi: 10.1029/2006JD007529.

Young, K., J. Wang, 2007: Comparison of 10-Year (1996-2005) Operational Radiosonde Data with ARM Radiosonde and Remote Sensing Data. 14th Symp. Meteorol. Obs. Instrum., San Antonio, TX, US, American Meteorological Society.

Poulos, G. S., J. Wang, D. K. Lauritsen, H. L. Cole, 2007: A note on the use of targeted dropwindsondes in complex terrain. J. Atmos. Ocean. Technol., 24, 1489-1494, doi: 10.1175/JTECH2065.1.

Behrendt, A., V. Wufmeyer, P. D. Girolamo, C. Kiemle, H.-S. Bauer, T. Schaberl, D. Summa, D. N. Whiteman, B. B. Demoz, E. V. Browell, S. Ismail, R. Ferrare, S. Kooi, G. Ehret, J. Wang, 2007: Intercomparison of water vapor data measured with lidar during IHOP_2002, Part 1: Airborne to ground-based lidar systems and comparisons with chilled-mirror hygrometer radiosondes. J. Atmos. Ocean. Technol., 24, 37700, doi: 10.1175/JTECH1924.1.