scholarly journals Snowfall Retrievals Using Millimeter-Wavelength Cloud Radars

2008 ◽  
Vol 47 (3) ◽  
pp. 769-777 ◽  
Author(s):  
Sergey Y. Matrosov ◽  
Matthew D. Shupe ◽  
Irina V. Djalalova
Keyword(s):  
Water Cycle ◽  
Precipitation Radar ◽  
Millimeter Wavelength ◽  
Microphysical Properties ◽  
Global Water Cycle ◽  
Arctic Regions ◽  
W Band ◽  
Gauge Data ◽  
Atmospheric Radiation Measurement ◽  
Typical Difference

Abstract It is demonstrated that millimeter-wavelength radars that are designed primarily for cloud studies can be also used effectively for snowfall retrievals. Radar reflectivity–liquid equivalent snowfall rate (Ze–S) relations specifically tuned for Ka- and W-band radar frequencies are applied to measurements taken by vertically pointing ground-based 8-mm cloud radars (MMCR) that are designed for the U.S. Department of Energy’s Atmospheric Radiation Measurement (ARM) Program and by the nadir-pointing spaceborne 94-GHz CloudSat radar. Comparisons of the MMCR-based snowfall accumulations estimated during experimental events with no significant snowflake riming and controlled gauge measurements indicated an 87% standard deviation between radar and gauge data that is consistent with the uncertainties in the coefficients of the Ze–S relations resulting from variability in snowflake microphysical properties. Comparisons of CloudSat-based snowfall-rate retrievals in heavy snowfall were consistent with estimates from surface S-band precipitation surveillance radars made using algorithms that were specifically designed for use with these radars. A typical difference between the CloudSat and the S-band precipitation radar estimates of snowfall rate for approximately collocated resolution pixels was within a factor of 2, which is of the order of the uncertainty of each estimate. The results of this study suggest that the ground-based and satellite-borne radars operating at Ka and W bands can provide valuable retrieval information on vertical profiles of snowfall, which is an important component of the global water cycle. This information is particularly important in Arctic regions where precipitation information from other sources is scarce.

Modeling Backscatter Properties of Snowfall at Millimeter Wavelengths

2007 ◽  
Vol 64 (5) ◽  
pp. 1727-1736 ◽  
Author(s):  
Sergey Y. Matrosov
Keyword(s):  
Rayleigh Scattering ◽  
Spherical Model ◽  
Size Distributions ◽  
Fall Velocity ◽  
Millimeter Wavelength ◽  
Millimeter Wavelengths ◽  
W Band ◽  
Mass Size ◽  
Atmospheric Radiation Measurement ◽  
The Common

Abstract Ground-based vertically pointing and airborne/spaceborne nadir-pointing millimeter-wavelength radars are being increasingly used worldwide. Though such radars are primarily designed for cloud remote sensing, they can also be used for precipitation measurements including snowfall estimates. In this study, modeling of snowfall radar properties is performed for the common frequencies of millimeter-wavelength radars such as those used by the U.S. Department of Energy’s Atmospheric Radiation Measurement Program (Ka and W bands) and the CloudSat mission (W band). Realistic snowflake models including aggregates and single dendrite crystals were used. The model input included appropriate mass–size and terminal fall velocity–size relations and snowflake orientation and shape assumptions. It was shown that unlike in the Rayleigh scattering regime, which is often applicable for longer radar wavelengths, the spherical model does not generally satisfactorily describe scattering of larger snowflakes at millimeter wavelengths. This is especially true when, due to aerodynamic forcing, these snowflakes are oriented primarily with their major dimensions in the horizontal plane and the zenith/nadir radar pointing geometry is used. As a result of modeling using the experimental snowflake size distributions, radar reflectivity–liquid equivalent snowfall rates (Ze–S) relations are suggested for “dry” snowfalls that consist of mostly unrimed snowflakes containing negligible amounts of liquid water. Owing to uncertainties in the model assumptions, these relations, which are derived for the common Ka- and W-band radar frequencies, have significant variability in their coefficients that can exceed a factor of 2 or so. Modeling snowfall attenuation suggests that the attenuation effects in “dry” snowfall can be neglected at the Ka band for most practical cases, while at the W band attenuation may need to be accounted for in heavier snowfalls observed at longer ranges.

scholarly journals Snowfall retrieval at X, Ka and W band: consistency of backscattering and microphysical properties using BAECC ground-based measurements

2018 ◽  
Author(s):  
Marta Tecla Falconi ◽  
Annakaisa von Lerber ◽  
Davide Ori ◽  
Frank Silvio Marzano ◽  
Dmitri Moisseev
Keyword(s):  
Cross Sections ◽  
Dipole Approximation ◽  
Microphysical Properties ◽  
Aspect Ratios ◽  
Millimeter Wavelengths ◽  
W Band ◽  
Atmospheric Radiation Measurement ◽  
Using Data ◽  
Biogenic Aerosols

Abstract. Radar-based snowfall intensity retrieval is investigated at centimeter and millimeter wavelengths using high-quality collocated ground-based multi-frequency radar and video-disdrometer observations. Using data from four snowfall events, recorded during the Biogenic Aerosols Effects on Clouds and Climate (BAECC) campaign in Finland, measurements of liquid-water-equivalent snowfall rate S are correlated to radar equivalent reflectivity factors Ze, measured by the Atmospheric Radiation Measurement (ARM) cloud radars operating at X, Ka and W frequency bands. From these coupled observations power-law Ze-S relationships are derived for all considered frequencies and distinguishing fluffy from rimed snowfall. Interestingly fluffy-snow events show a spectrally distinct signature of Ze-S with respect to rimed-snow cases. In order to understand the connection between snowflake microphysical and multi-frequency backscattering properties, numerical simulations are also performed by using the particle size distribution provided by the in-situ video-disdrometer. The latter are carried out by using both the T-matrix method (TMM) for soft-spheroids with different aspect ratios and exploiting a pre-computed discrete dipole approximation (DDA) database for complex-shape snowflakes. Based on the presented results, it is concluded that the soft-spheroid approximation can be adopted to explain the observed multi-frequency Ze-S relations if a proper spheroid aspect ratio is selected. The latter may depend on the snowfall type. A further analysis of the backscattering simulations reveals that TMM cross-sections are higher than the DDA ones for small ice particles, but lower for larger particles. These differences may explain why the soft-spheroid approximation is satisfactory for radar reflectivity simulations, the errors of computed cross-sections for larger and smaller particles compensating each other.

The global water cycle and continental erosion during Phanerozoic time (570 my)

1989 ◽  
Vol 289 (4) ◽  
pp. 455-483 ◽  
Author(s):  
Y. Tardy ◽  
R. N'Kounkou ◽  
J.-L. Probst
Keyword(s):  
Water Cycle ◽  
Global Water Cycle ◽  
Continental Erosion ◽  
Global Water

scholarly journals Micropollutant-loaded powdered activated carbon released from waste water treatment plants: a risk for sediment-dwelling organisms?

2021 ◽  
Vol 33 (1) ◽  
Author(s):  
Marion Woermann ◽  
Julios Armand Kontchou ◽  
Bernd Sures
Keyword(s):  
Activated Carbon ◽  
Wastewater Treatment Plants ◽  
Water Cycle ◽  
Waste Water Treatment ◽  
Additional Treatment ◽  
Powdered Activated Carbon ◽  
Lumbriculus Variegatus ◽  
Negative Effects ◽  
Global Water Cycle ◽  
Receiving Waters

Abstract Background In order to protect aquatic environments and to reduce the presence of micropollutants in the global water cycle, wastewater treatment plants (WWTPs) often implement an additional treatment step. One of the most effective measures is the use of powdered activated carbon (PAC) as an adsorbent for micropollutants. This method provides sufficient elimination rates for several micropollutants and has been successfully employed in many WWTPs. Despite this success, there might be a drawback as the retention of the PAC in the WWTP can be challenging and losses of micropollutant-loaded PAC into the aquatic environment may occur. Upon emission, micropollutant-loaded PAC is expected to settle to the benthic zone of receiving waters, where sediment-dwelling organisms may ingest these particles. Therefore, the present study investigated possible adverse effects of micropollutant-loaded PAC from a WWTP as compared to unloaded (native) and diclofenac-loaded PAC on the sediment-dwelling annelid Lumbriculus variegatus. Results Native PAC induced the strongest effects on growth (measured as biomass) and reproduction of the annelids. The corresponding medium effective concentrations (EC50) were 1.7 g/kg and 1.8 g/kg, respectively. Diclofenac-loaded PAC showed lower effects with an EC50 of 2.5 g/kg for growth and EC50 of 3.0 g/kg for reproduction. Although tested at the same concentrations, the micropollutant-loaded PAC from the WWTP did not lead to obvious negative effects on the endpoints investigated for L.variegatus and only a slight trend of a reduced growth was detected. Conclusion We did not detect harmful effects on L. variegatus caused by the presence of MP-loaded PAC from a WWTP which gives an auspicious perspective for PAC as an advanced treatment option.

scholarly journals Transferability Intercomparison: An Opportunity for New Insight on the Global Water Cycle and Energy Budget

2007 ◽  
Vol 88 (3) ◽  
pp. 375-384 ◽  
Author(s):  
E. S. Takle ◽  
J. Roads ◽  
B. Rockel ◽  
W. J. Gutowski ◽  
R. W. Arritt ◽  
...  
Keyword(s):  
Energy Budget ◽  
Climate Models ◽  
Climate Model ◽  
Water Cycle ◽  
Regional Climate ◽  
Climate Conditions ◽  
Continental Scale ◽  
Global Water Cycle ◽  
Wide Range ◽  
Global Water

A new approach, called transferability intercomparisons, is described for advancing both understanding and modeling of the global water cycle and energy budget. Under this approach, individual regional climate models perform simulations with all modeling parameters and parameterizations held constant over a specific period on several prescribed domains representing different climatic regions. The transferability framework goes beyond previous regional climate model intercomparisons to provide a global method for testing and improving model parameterizations by constraining the simulations within analyzed boundaries for several domains. Transferability intercomparisons expose the limits of our current regional modeling capacity by examining model accuracy on a wide range of climate conditions and realizations. Intercomparison of these individual model experiments provides a means for evaluating strengths and weaknesses of models outside their “home domains” (domain of development and testing). Reference sites that are conducting coordinated measurements under the continental-scale experiments under the Global Energy and Water Cycle Experiment (GEWEX) Hydrometeorology Panel provide data for evaluation of model abilities to simulate specific features of the water and energy cycles. A systematic intercomparison across models and domains more clearly exposes collective biases in the modeling process. By isolating particular regions and processes, regional model transferability intercomparisons can more effectively explore the spatial and temporal heterogeneity of predictability. A general improvement of model ability to simulate diverse climates will provide more confidence that models used for future climate scenarios might be able to simulate conditions on a particular domain that are beyond the range of previously observed climates.

Self-validating deep learning of continental hydrology through satellite gravimetry and altimetry

2021 ◽  
Author(s):  
Christopher Irrgang ◽  
Jan Saynisch-Wagner ◽  
Robert Dill ◽  
Eva Boergens ◽  
Maik Thomas
Keyword(s):  
Neural Network ◽  
Satellite Altimetry ◽  
Water Cycle ◽  
Global Water Cycle ◽  
Network Training ◽  
The Neural Network ◽  
Continental Hydrology ◽  
Terrestrial Water ◽  
Combine Machine ◽  
Groundwater Basins

<p>Space-borne observations of terrestrial water storage (TWS) are an essential ingredient for understanding the Earth's global water cycle, its susceptibility to climate change, and for risk assessments of ecosystems, agriculture, and water management. However, the complex distribution of water masses in rivers, lakes, or groundwater basins remains elusive in coarse-resolution gravimetry observations. We combine machine learning, numerical modeling, and satellite altimetry to build and train a downscaling neural network that recovers simulated TWS from synthetic space-borne gravity observations. The neural network is designed to adapt and validate its training progress by considering independent satellite altimetry records. We show that the neural network can accurately derive TWS anomalies in 2019 after being trained over the years 2003 to 2018. Specifically for validated regions in the Amazonas, we highlight that the neural network can outperform the numerical hydrology model used in the network training.</p><p>https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2020GL089258</p>

Multiscale Convective Organization and the YOTC Virtual Global Field Campaign

2012 ◽  
Vol 93 (8) ◽  
pp. 1171-1187 ◽  
Author(s):  
Mitchell W. Moncrieff ◽  
Duane E. Waliser ◽  
Martin J. Miller ◽  
Melvyn A. Shapiro ◽  
Ghassem R. Asrar ◽  
...  
Keyword(s):  
Time Scales ◽  
Climate Models ◽  
Water Cycle ◽  
Building Blocks ◽  
Tropical Convection ◽  
Global Water Cycle ◽  
Weather And Climate ◽  
Impact Phenomena ◽  
Meteorological Systems ◽  
The Tropics

The Year of Tropical Convection (YOTC) project recognizes that major improvements are needed in how the tropics are represented in climate models. Tropical convection is organized into multiscale precipitation systems with an underlying chaotic order. These organized systems act as building blocks for meteorological events at the intersection of weather and climate (time scales up to seasonal). These events affect a large percentage of the world's population. Much of the uncertainty associated with weather and climate derives from incomplete understanding of how meteorological systems on the mesoscale (~1–100 km), synoptic scale (~1,000 km), and planetary scale (~10,000 km) interact with each other. This uncertainty complicates attempts to predict high-impact phenomena associated with the tropical atmosphere, such as tropical cyclones, the Madden–Julian oscillation, convectively coupled tropical waves, and the monsoons. These and other phenomena influence the extratropics by migrating out of the tropics and by the remote effects of planetary waves, including those generated by the MJO. The diurnal and seasonal cycles modulate all of the above. It will be impossible to accurately predict climate on regional scales or to comprehend the variability of the global water cycle in a warmer world without comprehensively addressing tropical convection and its interactions across space and time scales.

scholarly journals Ocean Salinities Reveal Strong Global Water Cycle Intensification During 1950 to 2000

Science ◽  
2012 ◽  
Vol 336 (6080) ◽  
pp. 455-458 ◽  
Author(s):  
P. J. Durack ◽  
S. E. Wijffels ◽  
R. J. Matear
Keyword(s):  
Water Cycle ◽  
Global Water Cycle ◽  
Global Water
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