Errors and Correction of Precipitation Measurements in China

In order to discover the range of various errors in Chinese precipitation measurements and seek a correction method, 30 precipitation evaluation stations were set up countrywide before 1993. All the stations are reference stations in China. To seek a correction method for wind-induced error, a precipitation correction instrument called the ＂horizontal precipitation gauge＂ was devised beforehand. Field intercomparison observations regarding 29,000 precipitation events have been conducted using one pit gauge, two elevated operational gauges and one horizontal gauge at the above 30 stations. The range of precipitation measurement errors in China is obtained by analysis of intercomparison measurement results. The distribution of random errors and systematic errors in precipitation measurements are studied in this paper. A correction method, especially for wind-induced errors, is developed. The results prove that a correlation of power function exists between the precipitation amount caught by the horizontal gauge and the absolute difference of observations implemented by the operational gauge and pit gauge. The correlation coefficient is 0.99. For operational observations, precipitation correction can be carried out only by parallel observation with a horizontal precipitation gauge. The precipitation accuracy after correction approaches that of the pit gauge. The correction method developed is simple and feasible.

Error analysis of non-spherical raindrops on precipitation measurement

Radar cross section （RCS） of non-sphericai raindrops is calculated by using the software CST based on finite integral method and compared with RCS of spherical raindrops. The revised factor of non-spherical raindrops is obtained. The radar reflectivity with precipitation change of four distribution models of M-P, Gamma, JD and JT combining the revised factor is gotten using trapezoidal integration. When the infuence of non-spherical raindrops is considered, the accuracy of precipitation measurement of four distribution models can be separately improved 8.77%, 8.47%, 10.53% and 8.04% in the case of rain intensity is 100 mm/h.

A Thorough Evaluation of the Passive Microwave Radiometer Measurements onboard Three Fengyun-3 Satellites

Microwave Radiometer Imager(MWRI) is a key payload of China’s second generation polar meteorological satellite, i.e., Fengyun-3 series(FY-3). Up to now, 5 satellites including FY-3A(2008), FY-3B(2010), FY-3C(2013), FY-3D(2018), and FY-3E(2021) have been launched successfully to provide multiwavelength, all-weather, and global data for decades. Much progress has been made on the calibration of MWRI and a recalibrated MWRI brightness temperature(BT) product(V2) was recently released. This study thoroughly evaluates the accuracy of this new product from FY-3B, 3C, and 3D by using the simultaneous collocated Global Precipitation Measurement(GPM)Microwave Imager(GMI) measurements as a reference. The results show that the mean biases(MBEs) of the BT between MWRI and GMI are generally less than 0.5 K and the root mean squares(RMSs) between them are less than1.5 K. The previous notable ascending and descending difference of the MWRI has disappeared. This indicates that the new MWRI recalibration procedure is very effective in removing potential errors associated with the emission of the hot-load reflector. Analysis of the dependence of MBE on the latitude and earth scene temperature shows that MBE decreases with decreasing latitude over ocean. Furthermore, MBE over ocean decreases linearly with increasing scene temperature for almost all channels, whereas this does not occur over land. A linear regression fitting is then used to modify MWRI, which can reduce the MBE over ocean to be within 0.2 K. The standard deviation of error of GMI, FY-3B, and FY-3D MWRI BT data derived by using the three-cornered hat method(TCH) shows that GMI has the best overall performance over ocean except at 10.65 GHz where its standard deviation of error is slightly larger than that of FY-3D. Over land, the standard deviation of error of FY-3D is the lowest at almost all channels except at 89V. MWRI onboard FY-3 series satellites would serve as an important passive microwave radiometer member of the constellation to monitor key surface and atmospheric properties.

EXPERIMENT OF QUANTITATIVE MEASUREMENTS OF PRECIPITATION BY USE OF WEATHER RADAR IN THE HUAIHE RIVER BASIN

With the scheme of the variation analysis and Kalman filter,the radar data were adjusted by the real-time rain gauge data.The accuracy of areal rainfall calculation was improved and the results can be basically used for flood forecasting.It is concluded that the scheme is suitable in the upper and middle reaches of the Huaihe River.

Refined Spatialization of 10-Day Precipitation in China Based on GPM IMERG Data and Terrain Decomposition Using the BEMD Algorithm

Continuous high spatial-resolution 10-day precipitation data are essential for crop growth services and phenological research.In this study,we first use the bidimensional empirical mode decomposition(BEMD)algorithm to decompose the digital elevation model(DEM)data and obtain high-frequency(OR3),intermediate-frequency(OR5),and low-frequency(OR8)margin terrains.Then,we propose a refined precipitation spatialization model,which uses ground-based meteorological observation data,integrated multi-satellite retrievals for global precipitation measurement(GPM IMERG)satellite precipitation products,DEM data,terrain decomposition data,prevailing precipitation direction(PPD)data,and other multisource data,to construct China's high-resolution 10-day precipitation data from2001 to 2018.The decomposition results show mountainous terrain from fine to coarse scales;and the influences of altitude,slope,and aspect on precipitation are better represented in the model after topography is decomposed.Moreover,terrain decomposition data can be added to the model simulation to improve the quality of the simulation product;the simulation quality of the model in summer is better than that in spring and autumn,and is relatively poor in winter;and OR5 and OR8 can be improved in the simulation,with better OR5 and OR8 dynamically selected.In addition,preprocessing the data before precipitation spatialization is particularly important.For example,adding 0.01to the 0 value of precipitation,multiplying the small value of precipitation less than 1 by 10,and performing the normal distributions transform(e.g.,Yeo–Johnson)on the data can improve the simulation quality.

Assessment of the GPM and TRMM Precipitation Products Using the Rain Gauge Network over the Tibetan Plateau

Using high-quality hourly observations from national-level ground-based stations, the satellite-based rainfall products from both the Global Precipitation Measurement（GPM） Integrated Multisatellit E Retrievals for GPM（IMERG） and its predecessor, the Tropical Rainfall Measuring Mission（TRMM） Multi-satellite Precipitation Analysis（TMPA）, are statistically evaluated over the Tibetan Plateau（TP）, with an emphasis on the diurnal variation.The results indicate that：（1） the half-hourly IMERG rainfall product can explicitly describe the diurnal variation over the TP, but with discrepancies in the timing of the greatest precipitation intensity and an overestimation of the maximum rainfall intensity over the whole TP. In addition, the performance of IMERG on the hourly timescale, in terms of the correlation coefficient and relative bias, is different for regions with sea level height below or above 3500 m;（2） the IMERG products, having higher correlation and lower root-mean-square error, perform better than the TMPA products on the daily and monthly timescales; and（3） the detection ability of IMERG is superior to that of TMPA, as corroborated by a higher Hanssen and Kuipers score, a higher probability of detection, a lower false alarm ratio, and a lower bias. Compared to TMPA, the IMERG products ameliorate the overestimation across the TP. In conclusion,GPM IMERG is superior to TRMM TMPA over the TP on multiple timescales.

Assessing 10 Satellite Precipitation Products in Capturing the July 2021 Extreme Heavy Rain in Henan, China

On 20 July 2021,a sudden rainstorm happened in central and northern Henan Province,China,killing at least 302people.This extreme precipitation event incurred substantial socioeconomic impacts and resulted in serious losses.Accurate monitoring of such rainstorm events is crucial.In this study,qualitative and quantitative methods are used to comprehensively evaluate the abilities of 10 high-resolution satellite precipitation products[CMORPH-Raw(Climate Prediction Center morphing technique),CMORPH-RT,PERSIANN-CCS(Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks),GPM IMERG-Early(Integrated Multisatellite Retrievals for Global Precipitation Measurement),GPM IMERG-Late,GSMaP-Now(Global Satellite Mapping of Precipitation),GSMaP-NRT,FY-2F,FY-2G,and FY-2H]in capturing this extreme rainstorm event,as well as their performances in monitoring different precipitation intensities.The results show that these satellite precipitation products are able to capture the spatial distributions of the rainstorm(e.g.,its location in central and northern Henan),but all products have underestimated the amount of precipitation in the rainstorm center.With the increase in precipitation intensity,the hit rate decreases,the threat score decreases,and the false alarm rate increases.CMORPH-RT is better at capturing the rainstorm than CMORPH-Raw,and it depictes the rainstorm process well;GPM IMERG-Late is more accurate than GPM IMERG-Early;GSMaP-NRT has performed better than GSMaP-Now;and PERSIANNCCS and FY-2F perform poorly.Among the products,CMORPH-RT performs the best,which has accurately captured the center of the rainstorm,and is also the closest to the station-based observations.In general,the satellite precipitation products that integrate infrared and passive microwave data are found to be better than those that only make use of infrared data.The satellite precipitation retrieval algorithm and the amount of passive microwave data have a relatively greater impact on the accuracy of satellite precipitation products.

Fundamental Characteristics of Tropical Rain Cell Structures as Measured by TRMM PR

Rain cells are the most elementary unit of precipitation system in nature.In this study,fundamental geometric and physical characteristics of rain cells over tropical land and ocean areas are investigated by using 15-yr measurements of the Tropical Rainfall Measuring Mission(TRMM)Precipitation Radar(PR).The rain cells are identified with a minimum bounding rectangle(MBR)method.The results indicate that about 50%of rain cells occur at length of about 20 km and width of 15 km.The proportion of rain cells with length>200 km and width>100 km is less than1%.There is a a log-linear relationship between the mean length and width of rain cells.Usually,for the same horizontal geometric parameters,rain cells tend to be square horizontally and lanky vertically over land,while vertically squatty over ocean.The rainfall intensity of rain cells varies from 0.4 to 10 mm h-1 over land to 0.4–8 mm h-1 over ocean.Statistical results indicate that the occurrence frequency of rain cells decreases as the areal fraction of convective precipitation in rain cells increases,while such frequency remains almost invariant when the areal fraction of stratiform precipitation varies from 10%to 80%.The relationship between physical and geometric parameters of rain cells shows that the mean rain rate of rain cells is more frequently associated with the increase of their area,with the increasing rate over land greater than that over ocean.The results also illustrate that heavy convective rain rate prefers to occur in larger rain cells over land while heavy stratiform rain rate tends to appear in larger rain cells over ocean.For the same size of rain cells,the areal fraction and the contribution of convective precipitation are about10%–15%higher over land than over ocean.

Evaluation of CLDAS and GPM Precipitation Products over the Tibetan Plateau in Summer 2005–2021 Based on Hourly Rain Gauge Observations

Accurate,reliable,and high spatiotemporal resolution precipitation products are essential for precipitation research,hydrological simulation,disaster warning,and many other applications over the Tibetan Plateau(TP).The Global Precipitation Measurement(GPM) data are widely recognized as the most reliable satellite precipitation product for the TP.The China Meteorological Administration(CMA) Land Data Assimilation System(CLDAS) precipitation fusion dataset(CLDAS-Prcp),hereafter referred to as CLDAS,is a high-resolution,self-developed precipitation product in China with regional characteristics.Focusing on the TP,this study provides a long-term evaluation of CLDAS and GPM from various aspects,including characteristics on different timescales,diurnal variation,and elevation impacts,based on hourly rain gauge data in summer from 2005 to 2021.The results show that CLDAS and GPM are highly effective alternatives to the rain gauge records over the TP.They both perform well for precipitation amount and frequency on multiple timescales.CLDAS tends to overestimate precipitation amount and underestimate precipitation frequency over the TP.However,GPM tends to overestimate both precipitation amount and frequency.The difference between them mainly lies in the trace precipitation.CLDAS and GPM effectively capture rainfall events,but their performance decreases significantly as intensity increases.They both show better accuracy in diurnal variation of precipitation amount than frequency,and their performance tends to be superior during nighttime compared to the daytime.Nevertheless,there are some differences of the two against rain gauge observations in diurnal variation,especially in the phase of the diurnal variation.The performance of CLDAS and GPM varies at different elevations.They both have the best performance over 3000–3500 m.The elevation dependence of CLDAS is relatively minor,while GPM shows a stronger elevation dependence in terms of precipitation amount.GPM tends to overestimate the precipitation amount at lower elevations and underestimate it at higher elevations.CLDAS and GPM exhibit unique strengths and weaknesses;hence,the choice should be made according to the specific situation of application.