Checking precipitation gauge performance

Abstract A total of 62 winter-storm events in the period 1964–99 over the Folsom Lake watershed located at the windward slope of the Sierra Nevada were simulated with a 9-km resolution using the fifth-generation Pennsylvania State University–NCAR Mesoscale Model (MM5). Mean areal precipitation (MAP) over the entire watershed and each of four subbasins was estimated based on gridded simulated precipitation. The simulated MAP was verified with MAP estimated (a) by the California Nevada River Forecast Center (CNRFC) for the four subbasins based on eight operational precipitation stations, and (b) for the period from 1980 to 1986, on the basis of a denser precipitation observing network deployed by the Sierra Cooperative Pilot Project (SCPP). A number of sensitivity runs were performed to understand the dependence of model precipitation on boundary and initial fields, cold versus warm start, and microphysical parameterization. The principal findings of the validation analysis are that (a) MM5 achieves a good percentage bias score of 103% in simulating Folsom basin MAP when compared to MAP derived from dense precipitation gauge networks; (b) spatial grid resolution higher than 9 km is necessary to reproduce the spatial MAP pattern among subbasins of the Folsom basin; and (c) the model performs better for heavy than for light and moderate precipitation. The analysis also showed significant simulation dependence on the spatial resolution of the boundary and initial fields and on the microphysical scheme used.

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PRECIPITATION MEASUREMENTS WITH VARIOUS PRECIPITATION GAUGE INSTALLATIONS

Hydrology Research ◽

10.2166/nh.1972.0006 ◽

1972 ◽

Vol 3 (2) ◽

pp. 80-106 ◽

Cited By ~ 3

Author(s):

JOHN SANDSBORG

Keyword(s):

Ground Surface ◽

Spatial Variations ◽

Snow Surface ◽

Great Loss ◽

Extrapolation Procedure ◽

Solid Precipitation ◽

Precipitation Gauge

An account is given of precipitation measurements taken with various precipitation gauge installations at Ultuna, Sweden during 1957-1960. A new gauge constructed to measure small spatial variations in rainfall is described and tested. The difficulty in measuring both rain and snow with the same elevated gauge is demonstrated. An extrapolation procedure is used in an attempt to estimate the snowfall at the snow surface. The great loss in the catch of snow when using elevated gauges (40-50 % at 1.5 m over the ground surface) indicates that this method is very unsatisfactory for measuring solid precipitation.

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Testing and Development of Transfer Functions for Weighing Precipitation Gauges in WMO-SPICE

10.5194/hess-2017-228 ◽

2017 ◽

Author(s):

John Kochendorfer ◽

Rodica Nitu ◽

Mareile Wolff ◽

Eva Mekis ◽

Roy Rasmussen ◽

...

Keyword(s):

Transfer Functions ◽

Precipitation Amount ◽

Wind Speeds ◽

Small Manufacturer ◽

Lower Porosity ◽

Precipitation Gauge ◽

Reference Amount ◽

First Time ◽

High Winds ◽

Better Than

Abstract. Adjustments for the undercatch of solid precipitation caused by wind were developed for different weighing gauge/wind shield combinations tested in WMO-SPICE. These include several different manufacturer-provided unshielded and single-Alter shielded weighing gauges, a MRW500 precipitation gauge within a small, manufacturer-provided shield, and host-provided precipitation gauges within double-Alter, Belfort double-Alter, and small Double-Fence Intercomparison Reference (SDFIR) shields. Previously-derived adjustments were also tested on measurements from each weighing gauge/wind shield combination. The transfer functions developed specifically for each of the different types of unshielded and single-Alter shielded weighing gauges did not perform significantly better than the more generic and universal transfer functions developed previously using measurements from eight different WMO-SPICE sites. This indicates that wind shield type (or lack thereof) is more important in determining the magnitude of wind-induced undercatch than the type of weighing precipitation gauge. It also demonstrates the potential for widespread use of the previously-developed, multi-site single-Alter shielded and unshielded transfer functions. In addition, corrections for the lower-porosity Belfort double-Alter shield and a standard double-Alter shield were developed and tested using measurements from two separate sites for the first time. Among all of the manufacturer-provided shields tested, with an average undercatch of about 5 %, the Belfort double Alter shield required the least amount of correction, and caught ~ 80 % of the reference amount of precipitation even in snowy conditions with wind speeds greater than 5 m s−1. The SDFIR-shielded gauge accumulated 98 % of the Double-Fence Automated Reference (DFAR) precipitation amount on average, accumulated 90 % of the DFAR accumulation in high winds, and was almost indistinguishable from the full-sized DFAR used as a reference. In general, the more effective wind shields, that were associated with smaller unadjusted errors, also produced more accurate measurements after adjustment.

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Preliminary analysis and main problems of instrumental measurement complex at the Vernadsky Antarctic Station

10.5194/egusphere-egu21-13591 ◽

2021 ◽

Author(s):

Denys Pishniak ◽

Svitlana Krakovska ◽

Anastasia Chyhareva ◽

Sergii Razumnyi

Keyword(s):

Measurement Data ◽

Bias Reduction ◽

Small Scale ◽

High Temporal Resolution ◽

Monthly Precipitation ◽

Polar Regions ◽

Indirect Methods ◽

Precipitation Measurement ◽

Precipitation Gauge ◽

The Antarctic

Measurements of precipitation has always had well known difficulties that caused inaccuracies. This is especially acute in Polar regions where prevailing solid precipitation is accomplished with strong winds. Alternatively some indirect methods of precipitation measurements still in development and numerous meteorological instruments have been created on their basis.The Akademik Vernadsky station is located in the Antarctic Peninsula region with a large amount of precipitation and &#160;the problem of its measuring has always been relevant here. Although the data of monthly precipitation have been found for Vernadsky (Faraday) station since 1964, the first standard Tretyakov precipitation gauge was set up there only in 1997. But in recent years, several new instruments for indirect precipitation measurement have been installed at the meteorological site. The consistency of their data are the subject for this study.&#160;Direct comparison of all measurement devices as well as investigation of their estimations dependencies from other meteorological parameters are analysed and will be presented for the period 2019-2020. Originally various instruments showed huge differences in precipitation estimates. Deep analysis and correction of the measurement results according to weather conditions is obviously needed for bias reduction. But the local features of the extremely heterogeneous underlying surface of the region affect the vertical component of the wind, and can cause the natural small scale precipitation variability.&#160;The advantages of indirect methods for precipitation measuring is a high sensitivity to registering even individual falling precipitation particles and, hence, the really high temporal resolution of the data. Therefore, it can be used for investigation of physical atmospheric processes. As an example, the case study of a cyclone with precipitation phase transition over Vernadsky station on December 5-6, 2020 is investigated and will be presented. A comparison of the measurement data of various devices (Tretyakov Precipitation Gauge, Snow Stick, Vaisala PWD22, Lufft WS100, METEK MRR-PRO) and the ERA-5 reanalysis was carried out. A vertical radar MRR-PRO is of special interest as a measuring instrument for polar regions because it can ignore surface snow transport and has proved reliability in the Antarctic environment recently. In Marine Antarctica this device can identify the height of precipitation melting and also show a number of other useful parameters. This complex of precipitation measurement instruments is planned to be used in the frames of the forthcoming YOPP-SH field campayne.

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Reliability of global gridded precipitation products in assessing extremes

10.5194/egusphere-egu21-3246 ◽

2021 ◽

Author(s):

Chandra Rupa Rajulapati ◽

Simon Michael Papalexiou ◽

Martyn P Clark ◽

Saman Razavi ◽

Guoqiang Tang ◽

...

Keyword(s):

Spatial Variability ◽

Extreme Precipitation ◽

Probability Distributions ◽

Extreme Precipitation Events ◽

Return Levels ◽

Time Period ◽

Precipitation Gauge ◽

Global Precipitation ◽

Surface Observations ◽

Precipitation Events

Assessing extreme precipitation events is of high importance to hydrological risk assessment, decision making, and adaptation strategies. Global gridded precipitation products, constructed by combining various data sources such as precipitation gauge observations, atmospheric reanalyses and satellite estimates, can be used to estimate extreme precipitation events. Although these global precipitation products are widely used, there has been limited work to examine how well these products represent the magnitude and frequency of extreme precipitation. In this work, the five most widely used global precipitation datasets (MSWEP, CFSR, CPC, PERSIANN-CDR and WFDEI) are compared to each other and to GHCN-daily surface observations. The spatial variability of extreme precipitation events and the discrepancy amongst datasets in predicting precipitation return levels (such as 100- and 1000-year) were evaluated for the time period 1979-2017. &#160;The behaviour of extremes, that is the frequency and magnitude of extreme precipitation, was quantified using indices of the heaviness of the upper tail of the probability distribution. Two parameterizations of the upper tail, the power and stretched-exponential, were used to reveal the probabilistic behaviour of extremes. The analysis shows strong spatial variability in the frequency and magnitude of precipitation extremes as estimated from the upper tails of the probability distributions. This spatial variability is similar to the K&#246;ppen-Geiger climate classification. The predicted 100- and 1000-year return levels differ substantially amongst the gridded products, and the level of discrepancy varies regionally, with large differences in Africa and South America and small differences in North America and Europe. The results from this work reveal the shortcomings of global precipitation products in representing extremes. The work shows that there is no single global product that performs best for all regions and climates.

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Accuracy of NWS 8" Standard Nonrecording Precipitation Gauge: Results and Application of WMO Intercomparison

Journal of Atmospheric and Oceanic Technology ◽

10.1175/1520-0426(1998)015<0054:aonsnp>2.0.co;2 ◽

1998 ◽

Vol 15 (1) ◽

pp. 54-68 ◽

Cited By ~ 163

Author(s):

Daqing Yang ◽

Barry E. Goodison ◽

John R. Metcalfe ◽

Valentin S. Golubev ◽

Roy Bates ◽

...

Keyword(s):

Precipitation Gauge

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Hotplate precipitation gauge calibrations and field measurements

Atmospheric Measurement Techniques ◽

10.5194/amt-11-441-2018 ◽

2018 ◽

Vol 11 (1) ◽

pp. 441-458 ◽

Cited By ~ 1

Author(s):

Nicholas Zelasko ◽

Adam Wettlaufer ◽

Bujidmaa Borkhuu ◽

Matthew Burkhart ◽

Leah S. Campbell ◽

...

Keyword(s):

Energy Conversion ◽

Surface Area ◽

Conversion Factor ◽

Field Measurements ◽

Radiative Properties ◽

Shortwave Radiation ◽

Actual Surface ◽

Precipitation Gauge ◽

Radiation Sensors ◽

S Application

Abstract. First introduced in 2003, approximately 70 Yankee Environmental Systems (YES) hotplate precipitation gauges have been purchased by researchers and operational meteorologists. A version of the YES hotplate is described in Rasmussen et al. (2011; R11). Presented here is testing of a newer version of the hotplate; this device is equipped with longwave and shortwave radiation sensors. Hotplate surface temperature, coefficients describing natural and forced convective sensible energy transfer, and radiative properties (longwave emissivity and shortwave reflectance) are reported for two of the new-version YES hotplates. These parameters are applied in a new algorithm and are used to derive liquid-equivalent accumulations (snowfall and rainfall), and these accumulations are compared to values derived by the internal algorithm used in the YES hotplates (hotplate-derived accumulations). In contrast with R11, the new algorithm accounts for radiative terms in a hotplate's energy budget, applies an energy conversion factor which does not differ from a theoretical energy conversion factor, and applies a surface area that is correct for the YES hotplate. Radiative effects are shown to be relatively unimportant for the precipitation events analyzed. In addition, this work documents a 10 % difference between the hotplate-derived and new-algorithm-derived accumulations. This difference seems consistent with R11's application of a hotplate surface area that deviates from the actual surface area of the YES hotplate and with R11's recommendation for an energy conversion factor that differs from that calculated using thermodynamic theory.

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The NCAR–FAA Snow Machine: An Artificial Snow-Generation System

Journal of Atmospheric and Oceanic Technology ◽

10.1175/jtech-d-18-0006.1 ◽

2018 ◽

Vol 35 (11) ◽

pp. 2159-2168

Author(s):

Scott D. Landolt ◽

Roy M. Rasmussen ◽

Alan J. Hills ◽

Warren Underwood ◽

Charles A. Knight ◽

...

Keyword(s):

Mass Balance ◽

Size Distribution ◽

Liquid Water ◽

Generation System ◽

Fall Velocity ◽

Atmospheric Research ◽

Controlled Conditions ◽

Precipitation Gauge ◽

Cold Chamber ◽

Over Time

AbstractThe National Center for Atmospheric Research (NCAR) developed an artificial snow-generation system designed to operate in a laboratory cold chamber for testing aircraft anti-icing fluids under controlled conditions. Flakes of ice are produced by shaving an ice cylinder with a rotating carbide bit; the resulting artificial snow is dispersed by turbulent airflows and falls approximately 2.5 m to the bottom of the device. The resulting fine ice shavings mimic snow in size, distribution, fall velocity, density, and liquid water equivalent (LWE) snowfall rate. The LWE snowfall rate can be controlled using either a mass balance or a precipitation gauge, which measures the snowfall accumulation over time, from which the computer derives the LWE rate. LWE snowfall rates are calculated every 6 s, and the rate the ice cylinder is fed into the carbide bit is continually adjusted to ensure that the LWE snowfall rate matches a user-selected value. The system has been used to generate LWE snowfall rates ranging from 0 to 10 mm h−1 at temperatures from −2 to −30°C and densities of approximately 0.1–0.5 g cm−3. Comparisons of the snow-machine fluid tests with the outdoor fluid tests have shown that the snow machine can mimic natural outdoor rates under a broad range of conditions.

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Quantifying snowfall from orographic cloud seeding

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.1917204117 ◽

2020 ◽

Vol 117 (10) ◽

pp. 5190-5195 ◽

Cited By ~ 4

Author(s):

Katja Friedrich ◽

Kyoko Ikeda ◽

Sarah A. Tessendorf ◽

Jeffrey R. French ◽

Robert M. Rauber ◽

...

Keyword(s):

Climate Change ◽

Population Growth ◽

Arid Regions ◽

Temporal Evolution ◽

Cloud Seeding ◽

Cloud Systems ◽

Physically Based ◽

Statistical Approaches ◽

Orographic Cloud ◽

Precipitation Gauge

Climate change and population growth have increased demand for water in arid regions. For over half a century, cloud seeding has been evaluated as a technology to increase water supply; statistical approaches have compared seeded to nonseeded events through precipitation gauge analyses. Here, a physically based approach to quantify snowfall from cloud seeding in mountain cloud systems is presented. Areas of precipitation unambiguously attributed to cloud seeding are isolated from natural precipitation (<1 mm h−1). Spatial and temporal evolution of precipitation generated by cloud seeding is then quantified using radar observations and snow gauge measurements. This study uses the approach of combining radar technology and precipitation gauge measurements to quantify the spatial and temporal evolution of snowfall generated from glaciogenic cloud seeding of winter mountain cloud systems and its spatial and temporal evolution. The results represent a critical step toward quantifying cloud seeding impact. For the cases presented, precipitation gauges measured increases between 0.05 and 0.3 mm as precipitation generated by cloud seeding passed over the instruments. The total amount of water generated by cloud seeding ranged from 1.2 × 105 m3 (100 ac ft) for 20 min of cloud seeding, 2.4 × 105 m3 (196 ac ft) for 86 min of seeding to 3.4 x 105 m3 (275 ac ft) for 24 min of cloud seeding.

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Dependence of Snow Gauge Collection Efficiency on Snowflake Characteristics

Journal of Applied Meteorology and Climatology ◽

10.1175/jamc-d-11-0116.1 ◽

2012 ◽

Vol 51 (4) ◽

pp. 745-762 ◽

Cited By ~ 59

Author(s):

Julie M. Thériault ◽

Roy Rasmussen ◽

Kyoko Ikeda ◽

Scott Landolt

Keyword(s):

Wind Speed ◽

Theoretical Study ◽

Collection Efficiency ◽

Weather Conditions ◽

Systematic Errors ◽

Lagrangian Model ◽

Field Observations ◽

Research Fields ◽

Different Types ◽

Precipitation Gauge

AbstractAccurate snowfall measurements are critical for a wide variety of research fields, including snowpack monitoring, climate variability, and hydrological applications. It has been recognized that systematic errors in snowfall measurements are often observed as a result of the gauge geometry and the weather conditions. The goal of this study is to understand better the scatter in the snowfall precipitation rate measured by a gauge. To address this issue, field observations and numerical simulations were carried out. First, a theoretical study using finite-element modeling was used to simulate the flow around the gauge. The snowflake trajectories were investigated using a Lagrangian model, and the derived flow field was used to compute a theoretical collection efficiency for different types of snowflakes. Second, field observations were undertaken to determine how different types, shapes, and sizes of snowflakes are collected inside a Geonor, Inc., precipitation gauge. The results show that the collection efficiency is influenced by the type of snowflakes as well as by their size distribution. Different types of snowflakes, which fall at different terminal velocities, interact differently with the airflow around the gauge. Fast-falling snowflakes are more efficiently collected by the gauge than slow-falling ones. The correction factor used to correct the data for the wind speed is improved by adding a parameter for each type of snowflake. The results show that accurate measure of snow depends on the wind speed as well as the type of snowflake observed during a snowstorm.

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