A composite analysis of diurnal cycle of GPS precipitable water vapor in central Japan during Calm Summer Days

2007 ◽  
Vol 92 (1-2) ◽  
pp. 15-29 ◽  
Author(s):  
G. Li ◽  
F. Kimura ◽  
T. Sato ◽  
D. Huang
Keyword(s):  
Water Vapor ◽  
Diurnal Cycle ◽  
Precipitable Water ◽  
Precipitable Water Vapor ◽  
Composite Analysis ◽  
Central Japan

scholarly journals On the Diurnal Cycle of GPS-Derived Precipitable Water Vapor over Sumatra

2019 ◽  
Vol 76 (11) ◽  
pp. 3529-3552
Author(s):  
Giuseppe Torri ◽  
David K. Adams ◽  
Huiqun Wang ◽  
Zhiming Kuang
Keyword(s):  
Water Vapor ◽  
Diurnal Cycle ◽  
Wrf Model ◽  
Precipitable Water ◽  
Active Phase ◽  
Precipitable Water Vapor ◽  
Tectonic Activity ◽  
Western Coast ◽  
The Impact ◽  
Spectrometer Data

Abstract Convective processes in the atmosphere over the Maritime Continent and their diurnal cycles have important repercussions for the circulations in the tropics and beyond. In this work, we present a new dataset of precipitable water vapor (PWV) obtained from the Sumatran GPS Array (SuGAr), a dense network of GPS stations principally for examining seismic and tectonic activity along the western coast of Sumatra and several offshore islands. The data provide an opportunity to examine the characteristics of convection over the area in greater detail than before. In particular, our results show that the diurnal cycle of PWV on Sumatra has a single late afternoon peak, while that offshore has both a midday and a nocturnal peak. The SuGAr data are in good agreement with GPS radio occultation data from the Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) mission, as well as with imaging spectrometer data from the Ozone Measuring Instrument (OMI). A comparison between SuGAr and the NASA Water Vapor Project (NVAP), however, shows significant differences, most likely due to discrepancies in the temporal and spatial resolutions. To further understand the diurnal cycle contained in the SuGAr data, we explore the impact of the Madden–Julian oscillation (MJO) on the diurnal cycle with the aid of the Weather Research and Forecasting (WRF) Model. Results show that the daily mean and the amplitude of the diurnal cycle appear smaller during the suppressed phase relative to the developing/active MJO phase. Furthermore, the evening/nighttime peaks of PWV offshore appear later during the suppressed phase of the MJO compared to the active phase.

scholarly journals Verification of NWP Model Analyses and Radiosonde Humidity Data with GPS Precipitable Water Vapor Estimates during AMMA

2009 ◽  
Vol 24 (4) ◽  
pp. 1085-1101 ◽  
Author(s):  
O. Bock ◽  
M. Nuret
Keyword(s):  
Water Vapor ◽  
Diurnal Cycle ◽  
Bias Correction ◽  
Precipitable Water ◽  
Precipitable Water Vapor ◽  
Precipitation Forecast ◽  
Weather Forecasts ◽  
Multidisciplinary Analysis ◽  
Correction Scheme ◽  
Nwp Model

Abstract This paper assesses the performance of the European Centre for Medium-Range Weather Forecasts-Integrated Forecast System (ECMWF-IFS) operational analysis and NCEP–NCAR reanalyses I and II over West Africa, using precipitable water vapor (PWV) retrievals from a network of ground-based GPS receivers operated during the African Monsoon Multidisciplinary Analysis (AMMA). The model analyses show reasonable agreement with GPS PWV from 5-daily to monthly means. Errors increase at shorter time scales, indicating that these global NWP models have difficulty in handling the diurnal cycle and moist processes at the synoptic scale. The ECMWF-IFS analysis shows better agreement with GPS PWV than do the NCEP–NCAR reanalyses (the RMS error is smaller by a factor of 2). The model changes in ECMWF-IFS were not clearly reflected in the PWV error over the period of study (2005–08). Radiosonde humidity biases are diagnosed compared to GPS PWV. The impacts of these biases are evidenced in all three model analyses at the level of the diurnal cycle. The results point to a dry bias in the ECMWF analysis in 2006 when Vaisala RS80-A soundings were assimilated, and a diurnally varying bias when Vaisala RS92 or Modem M2K2 soundings were assimilated: dry during day and wet during night. The overall bias is offset to wetter values in NCEP–NCAR reanalysis II, but the diurnal variation of the bias is observed too. Radiosonde bias correction is necessary to reduce NWP model analysis humidity biases and improve precipitation forecast skill. The study points to a wet bias in the Vaisala RS92 data at nighttime and suggests that caution be used when establishing a bias correction scheme.

scholarly journals Diurnal cycle of precipitable water vapor over Spain

2011 ◽  
Vol 137 (657) ◽  
pp. 948-958 ◽  
Author(s):  
J. P. Ortiz de Galisteo ◽  
V. Cachorro ◽  
C. Toledano ◽  
B. Torres ◽  
N. Laulainen ◽  
...  
Keyword(s):  
Water Vapor ◽  
Diurnal Cycle ◽  
Precipitable Water ◽  
Precipitable Water Vapor

scholarly journals The Amazon Dense GNSS Meteorological Network: A New Approach for Examining Water Vapor and Deep Convection Interactions in the Tropics

2015 ◽  
Vol 96 (12) ◽  
pp. 2151-2165 ◽  
Author(s):  
David K. Adams ◽  
Rui M. S. Fernandes ◽  
Kirk L. Holub ◽  
Seth I. Gutman ◽  
Henrique M. J. Barbosa ◽  
...  
Keyword(s):  
Water Vapor ◽  
Diurnal Cycle ◽  
Numerical Models ◽  
Deep Convection ◽  
Precipitable Water ◽  
Sea Breeze ◽  
Tropical Meteorology ◽  
Precipitable Water Vapor ◽  
Gnss Meteorology ◽  
The Tropics

Abstract The complex interactions between water vapor fields and deep atmospheric convection remain one of the outstanding problems in tropical meteorology. The lack of high spatial–temporal resolution, all-weather observations in the tropics has hampered progress. Numerical models have difficulties, for example, in representing the shallow-to-deep convective transition and the diurnal cycle of precipitation. Global Navigation Satellite System (GNSS) meteorology, which provides all-weather, high-frequency (5 min), precipitable water vapor estimates, can help. The Amazon Dense GNSS Meteorological Network experiment, the first of its kind in the tropics, was created with the aim of examining water vapor and deep convection relationships at the mesoscale. This innovative, Brazilian-led international experiment consisted of two mesoscale (100 km × 100 km) networks: 1) a 1-yr (April 2011–April 2012) campaign (20 GNSS meteorological sites) in and around Manaus and 2) a 6-week (June 2011) intensive campaign (15 GNSS meteorological sites) in and around Belem, the latter in collaboration with the Cloud Processes of the Main Precipitation Systems in Brazil: A Contribution to Cloud-Resolving Modeling and to the Global Precipitation Measurement (CHUVA) Project in Brazil. Results presented here from both networks focus on the diurnal cycle of precipitable water vapor associated with sea-breeze convection in Belem and seasonal and topographic influences in and around Manaus. Ultimately, these unique observations may serve to initialize, constrain, or validate precipitable water vapor in high-resolution models. These experiments also demonstrate that GNSS meteorology can expand into logistically difficult regions such as the Amazon. Other GNSS meteorology networks presently being constructed in the tropics are summarized.

scholarly journals Observed and Modeled Growing-Season Diurnal Precipitable Water Vapor in South-Central Canada

2010 ◽  
Vol 49 (11) ◽  
pp. 2301-2314 ◽  
Author(s):  
John Hanesiak ◽  
Mark Melsness ◽  
Richard Raddatz
Keyword(s):  
Water Vapor ◽  
Diurnal Cycle ◽  
Deep Convection ◽  
Precipitable Water ◽  
Precipitable Water Vapor ◽  
High Temporal Resolution ◽  
Forecast Period ◽  
Growing Seasons ◽  
South Central ◽  
Mean Square Errors

Abstract High-temporal-resolution total-column precipitable water vapor (PWV) was measured using a Radiometrics Corporation WVR-1100 Atmospheric Microwave Radiometer (AMR). The AMR was deployed at the University of Manitoba in Winnipeg, Canada, during the 2003 and 2006 growing seasons (mid-May–end of August). PWV data were examined 1) to document the diurnal cycle of PWV and to provide insight into the various processes controlling this cycle and 2) to assess the accuracy of the Canadian regional Global Environmental Multiscale (GEM) model analysis and forecasts (out to 36 h) of PWV. The mean daily PWV was 22.6 mm in 2003 and 23.8 mm in 2006, with distinct diurnal amplitudes of 1.5 and 1.8 mm, respectively. It was determined that the diurnal cycle of PWV about the daily mean value was controlled by evapotranspiration (ET) and the occurrence/timing of deep convection. The PWV in both years reached its hourly maximum later in the afternoon as opposed to at solar noon. This suggested that the surface and atmosphere were well coupled, with ET primarily being controlled by the vapor pressure deficit between the vegetation/surface and atmosphere. The decrease in PWV during the evening and overnight periods of both years was likely the result of deep convection, with or without precipitation, which drew water vapor out of the atmosphere, as well as the nocturnal decline in ET. The results did not change for days on which low-level winds were light (i.e., maximum winds from the surface to 850 hPa were below 20 km h−1), which supports the notion that the diurnal PWV pattern was associated with the daily cycles of local ET and convection/precipitation and was not due to advection. Comparison of AMR PWV with the Canadian GEM model for the growing seasons of 2003 and 2006 indicated that the model error was 3 mm (13%) or more even in the first 12 h, with mean absolute errors ranging from 2 to 3.5 mm and root-mean-square errors from 3 to 4.5 mm over the full 36-h forecast period. It was also found that the 3–9-h forecast period of GEM had better error scores in 2006 than in 2003.

Diurnal Cycle of Precipitation in the Tropics Simulated in a Global Cloud-Resolving Model

2009 ◽  
Vol 22 (18) ◽  
pp. 4809-4826 ◽  
Author(s):  
Tomonori Sato ◽  
Hiroaki Miura ◽  
Masaki Satoh ◽  
Yukari N. Takayabu ◽  
Yuqing Wang
Keyword(s):  
Water Vapor ◽  
Diurnal Cycle ◽  
Precipitable Water ◽  
Sea Breeze ◽  
Horizontal Resolution ◽  
Precipitable Water Vapor ◽  
Satellite Observations ◽  
Cold Pool ◽  
Cloud Resolving Model ◽  
Diurnal Cycle Of Precipitation

Abstract This study analyzes the diurnal cycle of precipitation simulated in a global cloud-resolving model (GCRM) named the Nonhydrostatic Icosahedral Atmospheric Model (NICAM). A 30-day integration of NICAM successfully simulates the precipitation diurnal cycle associated with the land–sea breeze and the thermally induced topographic circulations as well as the horizontal propagation of diurnal cycle signals. The first harmonic of the diurnal cycle of precipitation in the 7-km run agrees well with that from satellite observations in its geographical distributions although its amplitude is slightly overestimated. The NICAM simulation revealed that the precipitation diurnal cycle over the Maritime Continent is strongly coupled with the land–sea breeze that controls the convergence/divergence pattern in the lower troposphere around the islands. The analysis also suggests that the cold pool often forms over the open ocean where the precipitation intensity is high, and the propagation of the cold pool events is related to the precipitation diurnal cycle as well as the land–sea breeze. Sensitivity experiments suggest a prominent horizontal resolution dependence of the simulated precipitation diurnal cycle. Over continental areas the 14-km run induces the diurnal peak about three hours later than the 7-km run. The 3.5-km run produces the peak time and amplitude that are very similar to those in Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) observations. Meanwhile, the resolution dependence in phase and amplitude is negligibly small over the open oceans. This contrast sensitivity to the horizontal resolution is attributed to the differences in structure and life cycle of convective systems over land and ocean. Diurnal peaks of precipitable water vapor, precipitation, and outgoing longwave radiation (OLR) are compared over land areas using the NICAM 7-km run. The daily precipitable water vapor maximum appears around 1500 local time (LT), which is followed by the precipitation peak around 1630 LT. The diurnal cycle of high clouds tends to peak around 1930 LT, three hours later than the precipitation peak. These results from NICAM simulations can explain the cause of the phase differences among precipitation products based on several satellite observations. The authors demonstrate that the GCRM is a promising tool for realistically simulating the precipitation diurnal cycle and could be quite useful for studying the role of the diurnal cycle in the climate systems in a global context.

KORELASI MUSIMAN ANTARA ZENITH WET DELAY (ZWD) DAN DEBIT SUNGAI DI DAS CIKAPUNDUNG HULU, KAWASAN BANDUNG UTARA, JAWA BARAT

2019 ◽  
Vol 3 ◽  
pp. 741
Author(s):  
Wedyanto Kuntjoro ◽  
Z.A.J. Tanuwijaya ◽  
A. Pramansyah ◽  
Dudy D. Wijaya
Keyword(s):  
Water Vapor ◽  
Precipitable Water ◽  
Precipitable Water Vapor ◽  
Zenith Wet Delay

Kandungan total uap air troposfer (precipitable water vapor) di suatu tempat dapat diestimasi berdasarkan karakteristik bias gelombang elektromagnetik dari satelit navigasi GPS, berupa zenith wet delay (ZWD). Pola musiman deret waktu ZWD sangat penting dalam studi siklus hidrologi khususnya yang terkait dengan kejadian-kejadian banjir. Artikel ini menganalisis korelasi musiman antara ZWD dan debit sungai Cikapundung di wilayah Bandung Utara berdasarkan estimasi rataan pola musimannya. Berdasarkan rekonstruksi sejumlah komponen harmonik ditemukan bahwa pola musiman ZWD memiliki kemiripan dan korelasi yang kuat dengan pola musiman debit sungai. Pola musiman ZWD dan debit sungai dipengaruhi secara kuat oleh fenomena pertukaran Monsun Asia dan Monsun Australia. Korelasi linier di antara keduanya menunjukkan hasil yang sangat kuat, dimana hampir 90% fluktuasi debit sungai dipengaruhi oleh kandungan uap air di troposfer dengan level signifikansi 95%. Berdasarkan spektrum amplitudo silang dan koherensi, kedua kuantitas ini nampak didominasi oleh siklus monsun satu tahunan disertai indikasi adanya pengaruh siklus tengah tahunan dan 4 bulanan.

scholarly journals HGPT2: An ERA5-Based Global Model to Estimate Relative Humidity

2021 ◽  
Vol 13 (11) ◽  
pp. 2179
Author(s):  
Pedro Mateus ◽  
Virgílio B. Mendes ◽  
Sandra M. Plecha
Keyword(s):  
Water Vapor ◽  
Relative Humidity ◽  
Real Time ◽  
Prediction Models ◽  
Weather Prediction ◽  
Precipitable Water ◽  
Precipitable Water Vapor ◽  
Global Navigation Satellite Systems ◽  
International Gnss Service ◽  
Weighted Mean Temperature

The neutral atmospheric delay is one of the major error sources in Space Geodesy techniques such as Global Navigation Satellite Systems (GNSS), and its modeling for high accuracy applications can be challenging. Improving the modeling of the atmospheric delays (hydrostatic and non-hydrostatic) also leads to a more accurate and precise precipitable water vapor estimation (PWV), mostly in real-time applications, where models play an important role, since numerical weather prediction models cannot be used for real-time processing or forecasting. This study developed an improved version of the Hourly Global Pressure and Temperature (HGPT) model, the HGPT2. It is based on 20 years of ERA5 reanalysis data at full spatial (0.25° × 0.25°) and temporal resolution (1-h). Apart from surface air temperature, surface pressure, zenith hydrostatic delay, and weighted mean temperature, the updated model also provides information regarding the relative humidity, zenith non-hydrostatic delay, and precipitable water vapor. The HGPT2 is based on the time-segmentation concept and uses the annual, semi-annual, and quarterly periodicities to calculate the relative humidity anywhere on the Earth’s surface. Data from 282 moisture sensors located close to GNSS stations during 1 year (2020) were used to assess the model coefficients. The HGPT2 meteorological parameters were used to process 35 GNSS sites belonging to the International GNSS Service (IGS) using the GAMIT/GLOBK software package. Results show a decreased root-mean-square error (RMSE) and bias values relative to the most used zenith delay models, with a significant impact on the height component. The HGPT2 was developed to be applied in the most diverse areas that can significantly benefit from an ERA5 full-resolution model.

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