Rain Gauge Precipitation Research Articles

Real-time areal precipitation determination from radar by means of statistical objective analysis

Precipitation measurement by radar allows for areal rainfall determination with a high spatial and temporal resolution. However, hydrological applications require an accuracy of the precipitation quantification which cannot be obtained by today’s weather radar devices. The quality of the radar-derived precipitation can be significantly improved with the aid of ground measurements. In this paper, a complete processing pipeline for real-time radar precipitation determination using a modified statistical objective analysis method is presented. Thereby, several additional algorithms, such as a dynamical use of Z–R relationships, a bias correction and an advection correction scheme are employed. The performance of the algorithms is tested for several case studies. For an error analysis, an eight months data set of X-band radar scans and rain gauge precipitation measurements is used. We show a reduction in the radar–rain gauge RMS difference of up to 59% for the optimal combination of the different algorithms.

Considerations for interpolating rain gauge precipitation onto a regular grid

The aim of this study is to used heavy precipitation data from Slovenia to find the highest resolution from the Numerical Weather Prediction model where the model cell averaged interpolated fields of 24hour rain gauge precipitation which was independent of the interpolation method. 20 out of 104 observed heavy precipitation cases from the period of 1995-2002 in Slovenia were selected, in which 10 were convective and 10 stratiform. Three different interpolation methods were used: Universal Kriging, Inverse Distance Weighted and Radial Basis Functions. Each method was aggregated and direct interpolation was performed. The cross-validation results showed that the interpolation errors were as large as 50 % of the observed precipitation maximum (in our case from 50 to 110 mm). This indicates that an interpolation into high resolution or into a point is not reliable. Also, the interpolation cross-validation errors, the Root Mean Squared Error and Mean Absolute Error, were larger for stratiform precipitation than for convective precipitation. The reason for these errors seems to be that for the convective cases there was a smaller area with heavy precipitation and a large area with weak or no precipitation. The smaller area with spatially very variable precipitation contributed significantly to errors while the larger did not. Conversely, this was not the case for stratiform precipitation cases where precipitation and corresponding errors occurred all over the domain. Model grids were interpolated with three different resolutions of 4, 8 and 16 km. The condition for a method-independent interpolation entitled that every model grid cell had to have at least one to two rain gauges inside and possibly more in the very near vicinity. The highest possible model resolution should therefore be close or lower as the double of average distance to the closest neighbor in the rain gauge network, which in our case occurred at 16 km. Also, a certain procedure for interpolation was followed: first, the interpolation into high resolution and secondly, aggregation into the final resolution. A simple interpolation into a point in the middle of the model grid cell did not produce interpolation independent results even at a lower resolution. When using the right procedure at 16 km, the maximum differences between interpolation methods were usually less than 15 % of the observed precipitation maximum.

Atmospheric-hydrological modeling of severe precipitation and floods in the Huaihe River Basin, China

Our study focuses on the simulation of heavy precipitation and floods over the Huaihe River Basin (270,000 km2), one of the seven major river basins in China. The simulation covers two periods in 1998 (June 28–July 3, July 28–August 17) and a third period in 2003 (June 26–July 22). The former two periods, with eight meteorological cases each of duration 72-h, correspond to the Intensive Observation Period of HUBEX/MAGE (Huaihe River Basin Experiment/Monsoon Asian GEWEX Experiment). The period in 2003 with 10 cases is the second most severe flooding event on record. The Canadian atmospheric Mesoscale Compressible Community Model (MC2) is used for precipitation simulation in the hindcast mode for all cases. The Chinese Xinanjiang hydrological model driven by either rain gauge or MC2 precipitation is used to simulate hydrographs at the outlet of the Shiguanhe sub-basin (5930 km2), part of the Huaihe River Basin. The MC2 precipitation is also evaluated using observations from rain gauges. Over the Huaihe River Basin, MC2 generally overestimates the basin-averaged precipitation. Three of the eight 1998 cases have a percentage error less than 50% with the fourth having an error of 54%, while six of the ten 2003 cases have errors less than 50%. The precipitation over five different sub-regions and the Shiguanhe sub-basin of the Huaihe River Basin from MC2 are also compared with values from the Chinese operational weather prediction model; the latter data are only available for the ten 2003 cases. An excellent result is obtained in the hydrological simulation using rain gauge precipitation as revealed by the Nash–Sutcliffe coefficients of 0.91 for both summers of 1998 and 2003. The simulation using MC2 precipitation shows a reasonable agreement of flood timing and peak discharges with Nash–Sutcliffe coefficients of 0.63 and 0.87 for the two 1998 periods, and 0.60 for 2003. The encouraging results demonstrate the potential of using mesoscale model precipitation for flood forecast, which provides a longer lead time compared to traditional methods such as those based on rain gauges, statistical forecast or radar nowcasts.

A Numerical Study of the 1996 Saguenay Flood Cyclone: Effect of Assimilation of Precipitation Data on Quantitative Precipitation Forecasts

Abstract A one-dimensional variational (1DVAR) technique is applied to assimilate rain gauge precipitation data to extend the predictability of the Saguenay flood cyclone associated with a trough-merger event on 19–21 July 1996 in the Saguenay-Lac-Saint-Jean region of Quebec, Canada. Two 60-h simulations initialized at 0000 UTC 19 July were performed with the Canadian Mesoscale Compressible Community (MC2) model. The control (CTL) and NCEP simulations were initialized with the enhanced temperature and moisture profiles obtained from the 1DVAR scheme and the NCEP reanalysis data, respectively. Compared to observations, the CTL simulation reasonably reproduced the observed mass and wind fields and showed a marked improvement in the threat scores for heavy precipitation. The CTL run captured the observed spatial and temporal distribution of precipitation but overpredicted the area of precipitation. Sensitivity experiments showed that the threat (bias) scores are less (somewhat) sensitive to the specification of the observation error of the precipitation data. Of the four precipitation systems present at model initial time, the systems in the vicinity of the southern trough had the biggest impact on the threat score. Potential vorticity diagnostics of the CTL simulation suggested that the initial temperature and moisture field near the southern trough decreased the condensational heating relative to NCEP. This resulted in a stronger zonal wind component in the upper levels associated with the southern trough in CTL that retarded the eastward propagation of the northern trough, resulting in a correct placement of the surface precipitation and an improvement in the threat scores relative to NCEP.

Impacts of different precipitation data sources on water budgets

Radar and rain-gauge precipitation datasets are used to explore the impacts of different precipitation data sources on water budgets simulated by the Three-Layer Variable Infiltration Capacity (VIC-3L) land surface model over the watershed of the Illinois River at Watts, Oklahoma. Hourly grid-based NEXRAD (Next Generation Radar) Stage III precipitation data (approximately 4×4 km 2) were aggregated in time and space to daily precipitation at 1/8 degree and compared to the University of Washington (UW) daily precipitation data, which were gridded at 1/8 degree based on rain-gauge precipitation data. Comparisons of the temporal cumulative precipitation magnitudes indicate that the NEXRAD precipitation is smaller than the UW data and the rain gauge measurements. Hyetographs obtained from the NEXRAD data in general appear to be narrower with higher peaks. In addition, the NEXRAD data are better in capturing the precipitation spatial distributions than the UW data. Investigations of water fluxes based on simulations forced by the two types of precipitation datasets suggest that realistic streamflow simulations, compared to the observed daily streamflow at the outlet of the Illinois River at Watts, can be obtained if model parameters are calibrated. Compared to soil moisture of the total zone, runoff and evapotranspiration are more sensitive to the temporal and spatial distributions of precipitation, with runoff being most sensitive. Also, runoff and evapotranspiration obtained based on the NEXRAD precipitation data show more spatial heterogeneities than those obtained by using the UW precipitation data. Moreover, the magnitudes of the components of the water budget can be strongly impacted by the VIC-3L calibrated parameters, but their spatial distribution patterns may not be significantly affected.

Impact on Short-Range Precipitation Forecasts from Assimilation of Ground-Based GPS Zenith Total Delay and Rain Gauge Precipitation Observations

This paper assesses the impact on short-range quantitative precipitation forecasts (QPFs) of assimilating zenith total delay (ZTD) and rainfall observations associated with a winter storm that occurred from 5-6 December 1997 in southern California. Assimilation of hourly rainfall improves the threat score by more than 300% within the assimilation window, but such an improvement drops quickly to 30% or lower beyond this window. The assimilation of ZTD observations does not produce a rainfall distribution as close to the observations as does the assimilation of rainfall within the assimilation window (only a 34% improvement). However, improvement in the QPFs beyond the window from the ZTD experiment is comparable to that from the rainfall experiment. Assimilation of ZTD and rainfall observations modifies the thermodynamic structures of the atmosphere, favoring development of precipitation in the observed rainy areas. The horizontal and vertical wind velocities are also adjusted consistent with the precipitation process. A spectral analysis of observed and simulated hourly rainfall, as well as the model forecast difference with and without data assimilation, indicates that rainfall assimilation adjusts the model variables on smaller scales (25 to 50 km) while the ZTD assimilation adjusts the model variables mainly on larger scales (> 50 km).

A Student-Centered Field Project Comparing Nexrad and Rain Gauge Precipitation Values in Mountainous Terrain

A team of undergraduate geoscience students compared Next Generation Weather Radar (NEXRAD) estimates of storm total precipitation to measurements from a network of 20 rain gauges. Student researchers gained valuable experience in field data collection, global positioning systems (GPS), geographic information systems (GIS), Internet data access and downloading, computer graphic analysis, descriptive statistics, and conference presentation. The project emphasized problem-solving techniques, positive interdependence and individual accountability.The study evaluated 31 storms delivering >= 0.30 inches total precipitation to one or more gauges in the 51.8 km2 Burd Run watershed, which drains a low mountainous area of south-central Pennsylvania. Rain gauge measurements fell within the corresponding range of radar estimates in less than half (46.8%) of all cases. Departures between rain gauge and radar estimates were more common for large storms (total precipitation >= 1.00 in at one or more gauges) than for smaller storms (0.30 - 0.99 in). Students explored the environmental reasons for data departures.SI units are used throughout this paper except in the case of precipitation measurements. We maintain the National Weather Service standard of using English units (inches) when discussing precipitation values.

Observed versus forecasted precipitation in the South East Alps

Intense precipitation events are common on the SE slopes of the Alps and the climatological maximum of precipitation is located in the area of the Julian and Carnic Alps. Mesoscale intensification of rainfall in the area is explained. Two cases of intense precipitation were studied with fine mesh mesometeorological modelling using the ALADIN-SI model and verifying its results with all available ground-based raingauge measurements. For the first case of 5-8 November 1997 mesoscale topographically induced direct lifting was the main reason for precipitation intensification in the area. For the second case of 3-5 November 1998 this forcing was further modified by a mesofront moving along the eastern edge of the Alps in the opposite direction to the flow at upper levels. In the predicted precipitation the most noticeable feature was the shift of the forecasted precipitation fields by some 20 km with respect to the measured one leading to overestimation at the SW side, and underestimation at the NE side of the mountain ridge. The role of discrepancy sources of differences between the forecasted and raingauge precipitation are evaluated.

RCCM2–BATS Model over Tropical South America: Applications to Tropical Deforestation

A multiyear simulation of the global climate uses a revised version of the National Center for Atmospheric Research (NCAR) Community Climate Model Version 2 (CCM2) coupled to the Biosphere‐Atmosphere Transfer Scheme (BATS). It is compared with global and rain gauge precipitation climatologies to evaluate precipitation fields and European Centre for Medium-Range Forecasts analyses to evaluate the atmospheric circulation. The near-surface climate is compared with data from Amazonian field campaigns. The model simulation of the South American climate agrees closely with the observational record and is much improved from past simulations with previous versions of the NCAR Community Climate Model over this portion of the Tropics. The model is then used to study the local and regional response to tropical deforestation over Amazonia. In addition to the standard deforestation forcing, consisting mainly of increased albedo and decreased roughness length, two additional sensitivity experiments were conducted to assess the individual contributions from these forcings to the deforestation changes. The standard deforestation simulation shows slight increases in annually averaged surface temperature (118C) and reductions in annually averaged precipitation and evaporation (2363 and 2149 mm yr21, respectively). As expected, increases in surface albedo over Amazonia produce a reduction in net downward solar radiation at the surface and consequently a reduction in net surface radiation and surface latent heat flux. The roughness decrease, on the other hand, reduces the surface latent heat fluxes through decreases in the surface drag coefficient. The regional changes in moisture convergence and precipitation during the Amazonian wet season display a shift in the area of maximum precipitation rather than an overall decrease over the deforested area. These shifts are evidently produced by a combination of the changes in the low-level circulation and a decrease in the efficiency of precipitation recycling within Amazonia.

Recent Trends in Rain Gauge Precipitation Measurements from the Tropical Pacific: Evidence for an Enhanced Hydrologic Cycle

Analysis of recently compiled tropical Pacific rain gauge measurements shows a trend toward increased precipitation in the central tropical Pacific during the period 1971-90. Previous studies of precipitation trends in this region have used satellite data and shipboard measurements, which have been demonstrated to contain a variety of known and unknown biases that could artificially produce a trend. Using rain gauge data, an independent and direct measure of the precipitation trends in the Pacific corroborates previous results based on satellite measurements, estimates of oceanic evaporation from shipboard meteorological observations, and results from numerical models. Furthermore, the result is consistent with suggestions that an enhancement of the tropical hydrologic cycle has been responsible for the increases in globally averaged tropospheric temperatures during the past two decades. 34 refs., 5 figs., 1 tab.

A STUDY ON PROBABILITY RUN-OFF FORECASTING METHOD FOR FLOOD CONTROL USING RADAR RAIN GAUGE

Only the average precipitation in a few hours preceding to the forecast usually has been used as input data for flood forecasting models. However, this method does not correctly evaluate the difference between expected value and actual observed value of discharge.This paper proposes a method which evaluates the discharge and the water level in probability, by studying the forecast rainfalls probability distribution by means of Radar Rain Gauge (including Digitized Weather Radar) precipitation forecast methods, and by inputting the result into the run-off models as a group of forecast rainfalls.The examination on the application led to the coviction that this new method can bring about practical and useful information.