A New Global Water Vapor Dataset

Randel, David L.; Greenwald, Thomas J.; Haar, Thomas H. Vonder; Stephens, Graeme L.; Ringerud, Mark A.; Combs, Cynthia L.

doi:10.1175/1520-0477(1996)077<1233:angwvd>2.0.co;2

Cited by 317 publications

(202 citation statements)

References 21 publications

(31 reference statements)

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“…An evaluation of the precipitable water field is given by Bromwich et al (2000). In comparison with the European Centre for Medium-range Weather Forecasts (ECMWF) reanalysis and the National Aeronautics and Space Administration Water Vapor Product (NVAP; Randel et al, 1996), mean values for the north polar cap were found to be comparable. However, significant spatial discrepancies were noted, particularly over lower latitude land surfaces.…”

Section: Computations and Approachmentioning

confidence: 99%

The annual cycle and interannual variability of atmospheric pressure in the vicinity of the North Pole

Cullather

Lynch

2003

Intl Journal of Climatology

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A comparison of National Centers for Environmental Prediction-National Center for Atmospheric Research reanalysis six-hourly sea-level pressure data with former Soviet drifting station observations over the central Arctic Basin reveals high monthly correlations throughout the period 1950-91, but also a preferred winter season negative bias of about 1.4 hPa. Using the reanalysis, supplemented by Arctic Ocean Buoy Program fields and in situ observations, a generalized depiction of the annual cycle of pressure fields over the Arctic may be constructed. Above the Canada Basin-Laptev Sea side of the Arctic, the annual cycle of surface pressure is dominated by the first harmonic, which has an amplitude of about 5 hPa and maximum pressure occurring in March. Along the periphery of northern Greenland and extending to the North Pole, a weak semiannual cycle is found in surface pressure with maxima in May and November. The presence of the semiannual variation over time is highly variable.Dynamically, this progression of the annual cycle may be attributed to the transfer of atmospheric mass from Eurasia and into the Canadian Archipelago in spring and the reverse condition in autumn. Over the central Arctic Basin, springtime pressure increases result from an enhanced poleward mass transport from Eurasia. An increase of equatorward transport over the Canadian Archipelago in May and June results in central Arctic pressure decreases into summer. A less distinct temporal separation between the poleward Canadian transport and the equatorward Eurasian transport results in the weaker second pressure maximum in autumn.On interannual time-scales, atmospheric mass over the central Arctic is exchanged with the storm track centres of action in the North Atlantic and North Pacific. In particular, the large decrease in central Arctic Basin sea-level pressure during the late 1980s is due to a large transfer of atmospheric mass into the North Pacific.

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Section: Computations and Approachmentioning

confidence: 99%

The annual cycle and interannual variability of atmospheric pressure in the vicinity of the North Pole

Cullather

Lynch

2003

Intl Journal of Climatology

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“…The CPC Merged Analysis of Precipitation (CMAP) is a global monthly precipitation dataset on a 2.5 degree grid, covering the period 1979(Xie and Arkin 1997. The National Aeronautics and Space Administration Water Vapor Project global water vapor dataset (NVAP) is a water vapor and liquid water path archive at 1 degree resolution that extends from 1988-1999 (Randel et al 1996).…”

Section: Introductionmentioning

confidence: 99%

Simulation of the Global Hydrological Cycle in the CCSM Community Atmosphere Model Version 3 (CAM3): Mean Features

et al. 2006

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The seasonal and annual climatological behavior of selected components of the hydrological cycle are presented from coupled and uncoupled configurations of the atmospheric component of the Community Climate System Model (CCSM), the Community Atmosphere Model Version 3 (CAM3). The formulations of processes that play a role in the hydrological cycle are significantly more complex when compared with earlier versions of the atmospheric model.Major features of the simulated hydrological cycle will be compared against available observational data, and the strengths and weaknesses will be discussed in the context of the fully-coupled model simulation.

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“…Pemantauan ruang berbasis seperti Global Positioning System (GPS) dan penginderaan jauh dari satelit adalah satu-satunya cara yang efektif untuk menilai tingkat uap air secara global dan berbagai misi telah dilaksanakan untuk pengukuran precipitable water vapor (PWV) atau total kandungan uap air [3,[10][11].…”

Section: Pendahuluanunclassified

“…Sehingga dapat disimpulkan bahwa keadaan topografi memperngaruhi pola distribusi PWV. Hasil analisis ini sesuai dengan teori [7][8][9][10][11][12].…”

Section: Hasil Pola Distribusi Pwv Secara Spasialunclassified

Analisa Penentuan Water Vapor Terhadap Pengaruh Erupsi Gunung Sinabung Menggunakan Data SUGAR Dan Citra Satelit Terra MODISs

Audah¹,

Cahyadi

Taufik

2017

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The eruption of Mount Sinabung in 2010 caused bursts of volcanic ash particles into the atmosphere layer to impact the weather. This is because volcanic ash is hydrocopic which can cause condensation process and block the process of solar radiation earth surface. Precivitable Water vapor (PWV) as one of the parameters of the atmosphere that can be used as information to determine the weather conditions in an area. Utilization of data Sumatran GPS Array (SUGAR) and data satellite Terra sensors MODIS (Moderate Resolution Imaging Spektroradiometer) can be used to find out PWV through GPS inversion method by utilizing estimated estimation of slowing and rotating GPS signals overlaid with troposphere. While the transmittance method is performed by comparing the surface reflectance between the channel absorption and the channel non absorption contained in the sensor MODIS. The results showed that spatial variation of PWV distribution pattern showed wetness pattern during eruption. This was indicated by some areas that have PWV distribution pattern almost in each region and PWV verification result from GPS showed ± 47.65 mm-66.81 mm, while PWV value from MODIS ranges from ± 13.02 mm -80.05 mm. Based on the results of PWV-GPS correlation test from June to October of 2010 has a correlation coefficient of 0.0173 to PWV from MODIS and explains the positive relationship between PWV of GPS with PWV value from MODIS, but correlation value of the variable variables including low category because of location points Station SUGAR are spread unevenly and are more likely to spread along the western coast of Sumatra, which borders the Indian Ocean.Keywords: Mount Sinabung, Precipitable Water Vapor, SUGAR, MODIS. PendahuluanAtmosfer adalah suatu lapisan udara yang mengelilingi bumi. 75% dari massa atmosfer yang terdapat awan, hujan dan konversi udara. Lapisan ini mempunyai pengaruh yang besar terhadap kehidupan semesta, seperti meredam panas matahari, merambatkan gelombang -gelombang suara, menimbulkan gejala senja, dan memegang peranan yang sangat penting dalam perubahan cuaca [16].Gejala fisis atmosfer yang terjadi akibat letusan gunung merapi yang mengeluarkan awan panas dalam bentuk abu vulkanik yang menyembur ke lapisan atmosfer bumi dapat menyebabkan dampak yang cukup signifikan. Partikel debu vulkanik yang dikeluarkan dalam lapisan troposfer bumi akan menghalangi proses radiasi matahari dan tidak dapat masuk kepermukaan bumi sehingga menyebabkan suhu di daerah tersebut rendah (menurun), lebih dari itu partikel debu vulkanik tersebut bersifat higroskopis, yakni dapat mengikat uap air, sehingga dapat memicu proses terjadinya kondensasi dan terbentuklah awan dengan (kelembaban) tinggi. Hal ini tente saja akan mempengaruhi pola sistem cuaca, karena radiasi matahari merupakan salah satu unsur utama dari unsur-unsur yang mempengaruhi cuaca.Pada peristiwa letusan gunung berapi ratusan ton sulfur yang menyembur ke atmosfer dengan kecepatan vertical tertentu sehingga dapat menembus ke lapisan tropofer dan lapisan stratosfer ya...

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A New Global Water Vapor Dataset

Cited by 317 publications

References 21 publications

The annual cycle and interannual variability of atmospheric pressure in the vicinity of the North Pole

The annual cycle and interannual variability of atmospheric pressure in the vicinity of the North Pole

Simulation of the Global Hydrological Cycle in the CCSM Community Atmosphere Model Version 3 (CAM3): Mean Features

Analisa Penentuan Water Vapor Terhadap Pengaruh Erupsi Gunung Sinabung Menggunakan Data SUGAR Dan Citra Satelit Terra MODISs

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