A New Algorithm of Rain Type Classification for GPM Dual-Frequency Precipitation Radar in Summer Tibetan Plateau

In this study, a new rain type classification algorithm for the Dual-Frequency Precipitation Radar(DPR) suitable over the Tibetan Plateau(TP) was proposed by analyzing Global Precipitation Measurement(GPM) DPR Level-2 data in summer from 2014 to 2020. It was found that the DPR rain type classification algorithm(simply called DPR algorithm) has mis-identification problems in two aspects in summer TP. In the new algorithm of rain type classification in summer TP,four rain types are classified by using new thresholds, such as the maximum reflectivity factor, the difference between the maximum reflectivity factor and the background maximum reflectivity factor, and the echo top height. In the threshold of the maximum reflectivity factors, 30 d BZ and 18 d BZ are both thresholds to separate strong convective precipitation, weak convective precipitation and weak precipitation. The results illustrate obvious differences of radar reflectivity factor and vertical velocity among the three rain types in summer TP, such as the reflectivity factor of most strong convective precipitation distributes from 15 d BZ to near 35 d BZ from 4 km to 13 km, and increases almost linearly with the decrease in height. For most weak convective precipitation, the reflectivity factor distributes from 15 d BZ to 28 d BZ with the height from 4 km to 9 km. For weak precipitation, the reflectivity factor mainly distributes in range of 15–25 d BZ with height within 4–10 km. It is also shows that weak precipitation is the dominant rain type in summer TP, accounting for 40%–80%,followed by weak convective precipitation(25%–40%), and strong convective precipitation has the least proportion(less than 30%).

Evaluation of high-resolution satellite precipitation products with surface rain gauge observations from Laohahe Basin in northern China

Three high-resolution satellite precipitation products, the Tropical Rainfall Measuring Mission （TRMM） standard precipitation products 3B42V6 and 3B42RT and the Climate Precipitation Center＇s （CPC） morphing technique precipitation product （CMORPH）, were evaluated against surface rain gauge observations from the Laohahe Basin in northern China. Widely used statistical validation indices and categorical statistics were adopted. The evaluations were performed at multiple time scales, ranging from daily to yearly, for the years from 2003 to 2008. The results show that all three satellite precipitation products perform very well in detecting the occurrence of precipitation events, but there are some different biases in the amount of precipitation. 3B42V6, which has a bias of 21%, fits best with the surface rain gauge observations at both daily and monthly scales, while the biases of 3B42RT and CMORPH, with values of 81% and 67%, respectively, are much higher than a normal receivable threshold. The quality of the satellite precipitation products also shows monthly and yearly variation： 3B42RT has a large positive bias in the cold season from September to April, while CMORPH has a large positive bias in the warm season from May to August, and they all attained their best values in 2006 （with 10%, 50%, and -5% biases for 3B42V6, 3B42RT, and CMORPH, respectively）. Our evaluation shows that, for the Laohahe Basin, 3B42V6 has the best correspondence with the surface observations, and CMORPH performs much better than 3B42RT. The large errors of 3B42RT and CMORPH remind us of the need for new improvements to satellite precipitation retrieval algorithms or feasible bias adjusting methods.

Evaluation of latest TMPA and CMORPH satellite precipitation products over Yellow River Basin

The main objective of this study was to evaluate four latest global high-resolution satellite precipitation products(TMPA 3B42 RT, CMORPH,TMPA 3B42V7, and CMORPH_adj) against gauge observations of the Yellow River Basin from March 2000 to December 2012. The assessment was conducted with several commonly used statistical indices at daily and monthly scales. Results indicate that 3B42V7 and CMORPH_adj perform better than the near real-time products(3B42RT and CMORPH), particularly the 3B42V7 product. The adjustment by gauge data significantly reduces the systematic biases in the research products. Regarding the near real-time datasets, 3B42 RT overestimates rainfall over the whole basin, while CMORPH presents a mixed pattern with negative and positive values of relative bias in low- and high-latitude regions,respectively, and CMORPH performs better than 3B42 RT on the whole. According to the spatial distribution of statistical indices, these values are optimized in the southeast and decrease toward the northwest, and the trend is similar for the spatial distribution of the mean annual precipitation during the period from 2000 to 2012. This study also reveals that all the four products can effectively detect rainfall events. This study provides useful information about four mainstream satellite products in the Yellow River Basin, and the findings can facilitate the use of global precipitation measurement(GPM) data in the future.

A Case Study of Impact of FY-2C Satellite Data in Cloud Analysis to Improve Short-Range Precipitation Forecast

Chinese FengYun-2C(FY-2C) satellite data were combined into the Local Analysis and Prediction System(LAPS) model to obtain three-dimensional cloud parameters and rain content. These parameters analyzed by LAPS were used to initialize the Global/Regional Assimilation and Prediction System model(GRAPES) in China to predict precipitation in a rainstorm case in the country. Three prediction experiments were conducted and were used to investigate the impacts of FY-2C satellite data on cloud analysis of LAPS and on short range precipitation forecasts. In the first experiment, the initial cloud fields was zero value. In the second, the initial cloud fields were cloud liquid water, cloud ice, and rain content derived from LAPS without combining the satellite data. In the third experiment, the initial cloud fields were cloud liquid water, cloud ice, and rain content derived from LAPS including satellite data. The results indicated that the FY-2C satellite data combination in LAPS can show more realistic cloud distributions, and the model simulation for precipitation in 1–6 h had certain improvements over that when satellite data and complex cloud analysis were not applied.

Ground validation of Fengyun-4A and Global Precipitation Measurement satellite observations over an alpine and canyon basin of the southeastern Tibetan Plateau

Satellite-based precipitation observations with high spatiotemporal resolution are essential for studying rainfall-induced natural hazards,especially in alpine and canyon areas of the southeastern Tibetan Plateau,which are prone to such hazards yet sparsely gauged.Here,we evaluated precipitation estimated from the Chinese Fengyun-4A meteorological satellite(FY-4A AGRI)versus the Integrated Multi-satellitE Retrievals for GPM(IMERG),by using rain gauge data collected in the Parlung Zangbo Basin from May through September in both 2018 and 2019.Our results showed that(1)FY-4A AGRI generated smaller values of RMSE(root mean square error)on hourly to daily scales,and larger correlation coefficients(R-values)and smaller RMSE values for both moderate and heavy rain,indicating its greater accuracy at rainfall estimation,which is most likely due to the denser rain gauge network at a finer temporal scale used when calibrating FY-4A AGRI;(2)Both satellite products underestimated the volume of moderate and heavy rain,with the larger degree of underestimation by FY-4A AGRI,which could lower their performance in flood monitoring and forecasting;(3)Worse performance and greater inconsistency between the two products were observed in high-elevation areas,perhaps because of orographic cloud effects in these mountainous areas;and(4)Both products revealed that the Gangrigabu Range blocked incoming water vapor from the southwest monsoon,with a better representation of the spatial pattern and spatial variability produced by IMERG.To improve precipitation estimation,the effects of complex terrain should be explicitly incorporated into the retrieval algorithms,with more gauged observations in a denser network and at a finer temporal scale needed to robustly calibrate the satellite-based estimates.

Disintegration of uncertainties associated with real-time multi-satellite precipitation products in diverse topographic and climatic area in Pakistan

Satellite-based Precipitation Estimates(SPEs)have gained importance due to enhanced spatial and temporal resolution,particularly in Indus basin,where raingauge network has fewer observation stations and drainage area is laying in many countries.Formulation of SPEs is based on indirect mechanism,therefore,assessment and correction of associated uncertainties is required.In the present study,disintegration of uncertainties associated with four prominent real time SPEs,IMERG,TMPA,CMORPH and PERSIANN has been conducted at grid level,regional scale,and summarized in terms of regions as well as whole study area basis.The bias has been disintegrated into hit,missed,false biases,and Root Mean Square Error(RMSE)into systematic and random errors.A comparison among gauge-and satellite-based precipitation estimates at annual scale,showed promising result,encouraging use of real time SPEs in the study area.On grid basis,at daily scale,from box plots,the median values of total bias(-0.5 to 0.5 mm)of the used SPEs were also encouraging although some under/over estimations were noted in terms of hit bias(-0.15 to 0.05 mm/day).Relatively higher values of missed(0.3 to 0.5 mm/day)and false(0.5 to 0.7 mm/day)biases were observed.The detected average daily RMSE,systematic errors,and random errors were also comparatively higher.Regional-scale spatial distribution of uncertainties revealed lower values of uncertainties in plain areas,depicting the better performance of satellite-based products in these areas.However,in areas of high altitude(>4000 m),due to complex topography and climatic conditions(orographic precipitation and glaciated peaks)higher values of biases and errors were observed.Topographic barriers and point scale gauge data could also be a cause of poor performance of SPEs in these areas,where precipitation is more on ridges and less in valleys where gauge stations are usually located.Precipitation system’s size and intensity can also be a reason of higher biases,because Microwave Imager underestimate precipitation in small systems(<200 km^(2))and overestimate in large systems(>2000 km^(2)).At present,use of bias correction techniques at daily time scale is compulsory to utilize real time SPEs in estimation of floods in the study area.Inter comparison of satellite products indicated that IMERG gave better results than the others with the lowest values of systematic errors,missed and false biases.

Validation of Three Satellite Precipitation Products in Two South-Western African Watersheds: Bandama (Ivory Coast) and Mono (Togo)

Satellite precipitation products are widely used in different domain, in area where there is a lack in observation. These have different spatio-temporal resolutions consequently resulting in different precipitation amounts depending on the product. The present study validates three satellite products, namely the Climate Hazard group Infrared Precipitation with Stations (CHIRPS), the Climate Research Unit (CRU) and the Global Precipitation Climatology Project (GPCP) over Bandama and Mono river basins for 1981-2005 and 1981-2016 respectively by comparing them to the observation precipitation of the basin. The available studies are focused on the regional scale but not on a watershed scale for hydrological studies. The analysis reveals that all the products are strongly correlated to each other as well as to the observed data at basin level. The Lamb coefficient test shows that most all the chosen basin namely Bandama and Mono presents the same climatic indices. All the products present the same variability and trend as the observation at basins scale. By comparing those products to observation, CHIRPS product following by GPCP give the lowest mean absolute error (MAE) at annual and seasonal time scales while CHIRPS is followed by CRU at monthly scale. Overall, all products overestimate the precipitation at Bandama basin while they underestimate it over Mono river basin. The comparison over 1981-2017 period of the total annual precipitation increasing southern ward (from Sahel to the coastal zone) for all the three studied products which varies from 300 mm to 2400 mm/year. All the three products are not significantly different from one another and they all highlight the same areas of hotspot rainfall in the region. The same conclusion is made at monthly and seasonal scales. Therefore, any of these products especially CHIRPS can be used for study in this region due to its lowest bias and MAE.

Spacecraft potential variations of the Swarm satellites at low Earth orbital altitudes

In this study, we provide the first detailed analysis of variations in the spacecraft potential (Vs) of the three Swarm satellites, which are flying at about 400-500 km. Unlike previous studies that have investigated extreme charging events, usually with spacecraft potentials as negative as −100 V, this study is focused on variations of Swarm Vs readings, which fall within a few negative volts. The Swarm observations show that spacecraft at low Earth orbital (LEO) altitudes are charged only slightly negatively, varying between −7 V and 0 V, with the majority of recorded potentials at these altitudes clustering close to −2 V. However, a second peak of Vs data is found at −5.5 V, though the event numbers for these more-negative observations are less, by an order of magnitude, than for incidents near the −2 V peak. These two distinct Vs peaks suggest two different causes. We have thus divided the Swarm spacecraft Vs data into two categories: less-negatively charged (−5 < Vs < 0 V) and more-negatively-charged (−6.5 < Vs < −5 V). These two Vs categories exhibit different spatial and temporal distributions. The Vs observations in the first category remain relatively closer to 0 V above the magnetic equator, but become much more negative at low and middle latitudes on the day side;at high latitudes, these first-category Vs readings are relatively more-negative during local summer. Second-category Vs events cluster into two bands at the middle latitudes (between ±20°-50° magnetic latitude), but with slightly more negative readings at the South Atlantic Anomaly (SAA) region;at high latitudes, these rarer but more-negative second-category Vs events exhibit relatively more-negative values during local winter, which is opposite to the seasonal pattern seen in the first category. By comparing Vs data to the distributions of background plasma density at Swarm altitudes, we find for the first category that more-negative Vs readings are recorded at regions with higher background plasma density, while for the second category the more-negative Vs data are observed at regions with lower background plasma density. This can be explained as follows: the electron and ion fluxes incident on Swarm surface, whose differences determine the potential of Swarm, are dominated by the background “cold” plasma (due to ionization) and “hot” plasma (due to precipitated particles from magnetosphere) for the two Vs categories, respectively.

A Short-Range Quantitative Precipitation Forecast Algorithm Using Back-Propagation Neural Network Approach

A back-propagation neural network （BPNN） was used to establish relationships between the shortrange （0-3-h） rainfall and the predictors ranging from extrapolative forecasts of radar reflectivity, satelliteestimated cloud-top temperature, lightning strike rates, and Nested Grid Model （NGM） outputs. Quan- titative precipitation forecasts （QPF） and the probabilities of categorical precipitation were obtained. Results of the BPNN algorithm were compared to the results obtained from the multiple linear regression algorithm for an independent dataset from the 1999 warm season over the continental United States. A sample forecast was made over the southeastern United States. Results showed that the BPNN categorical rainfall forecasts agreed well with Stage Ⅲ observations in terms of the size and shape of the area of rainfall. The BPNN tended to over-forecast the spatial extent of heavier rainfall amounts, but the positioning of the areas with rainfall ≥25.4 mm was still generally accurate. It appeared that the BPNN and linear regression approaches produce forecasts of very similar quality, although in some respects BPNN slightly outperformed the regression.

A study on the energetic electron precipitation observed by CSES

High energy particles are the main target of satellite space exploration; particle storm events are closely related to solar activity,cosmic ray distribution, and magnetic storms. The commonly seen energetic particle(electron) precipitation anomalies include mainly the inner and outer Van Allen radiation belts, the South Atlantic Anomaly, and the anomalous stripes excited by artificial electromagnetic waves. The China Seismo-Electromagnetic Satellite(CSES), launched in February of 2018, provides a platform for studying ionospheric particle disturbances. This paper reports the first studies of electron precipitation phenomenon based on high energy particle data from the CSES. We find that the global distribution of electron fluxes in the low energy band(0.1–3 MeV) can relatively well reflect the anomalous precipitation belt, which is consistent with results based on the DEMETER satellite, indicating that the quality of the lowenergy band payload of the CSES is good. In addition, this paper makes an in-depth study of the electron precipitation belt excited by the NWC artificial VLF electromagnetic transmitter located in Australia, which appears as a typical wisp structure on the energy spectrum. The magnetic shell parameter L corresponding to the precipitation belt ranges from 1.44 to 1.74, which is close to the L value(～1.45) of the NWC transmitter; the energy of the precipitation electrons is between 100 keV and 361.57 keV, among which the precipitation of 213.73 keV electrons is most conspicuous.

Evaluation of Latest TMPA and CMORPH Precipitation Products with Independent Rain Gauge Observation Networks over High-latitude and Low-latitude Basins in China

The Tropical Rainfall Measuring Mission （TRMM） Multi-satellite Precipitation Analysis （TMPA） and National Oceanic and Atmospheric Administration （NOAA） Climate Prediction Center （CPC） morphing technique （CMORPH） are two important multi-satellite precipitation products in TRMM-era and perform important functions in GPM-era. Both TMPA and CMORPH systems simultaneously upgraded their retrieval algorithms and released their latest version of precipitation data in 2013. In this study, the latest TMPA and CMORPH products （i.e., Version-7 real-time TMPA （T-rt） and gauge-adjusted TMPA （T-adj）, and Version- 1.0 real-time CMORPH （C-rt） and Version-l.0 gauge-adjusted CMORPH （C-adj）） are evaluated and intercompared by using independent rain gauge observations for a 12-year （2000--2011） period over two typical basins in China with different geographical and climate conditions. Results indicate that all TMPA and CMORPH products tend to overestimate precipitation for the high-latitude semiarid Laoha River Basin and underestimate it for the low-latitude humid Mishui Basin. Overall, the satellite precipitation products exhibit superior performance over Mishui Basin than that over Laoha River Basin. The C-adj presents the best performance over the high-latitude Laoha River Basin, whereas T-adj showed the best performance over the low-latitude Mishui Basin. The two gauge-adjusted products demonstrate potential in water resource management. However, the accuracy of two real-time satellite precipitation products demonstrates large variability in the two validation basins. The C-rt reaches a similar accuracy level with the gauge-adjusted satellite precipitation products in the high-latitude Laoha River Basin, and T-rt performs well in the low-latitude Mishui Basin. The study also reveals that all satellite precipitation products obviously overestimate light rain amounts and events over Laoha River Basin, whereas they underestimate the amount and events over Mishui Basin. The findings of the precision characteristics associated with the latest TMPA and CMORPH precipitation products at different basins will offer satellite pre- cipitation users an enhanced understanding of the applicability of the latest TMPA and CMORPH for water resource management, hydrologic process simulation, and hydrometeorological disaster prediction in other similar regions in China. The findings will also be useful for IMERG algorithm development and update in GPM-era.

Effects of land use/cover change(LUCC) on the spatiotemporal variability of precipitation and temperature in the Songnen Plain,China

Understanding the effects of land use/cover change(LUCC) on regional climate is critical for achieving land use system sustainability and global climate change mitigation. However, the quantitative analysis of the contribution of LUCC to the changes of climatic factors, such as precipitation & temperature(P&T), is lacking. In this study, we combined statistical methods and the gravity center model simulation to quantify the effects of long-term LUCC on P&T in the Songnen Plain(SNP) of Northeast China from 1980–2018. The results showed the spatiotemporal variability of LUCC. For example, paddy field had the largest increase(15 166.43 km2) in the SNP, followed by dry land, while wetland had the largest decrease(19 977.13 km;) due to the excessive agricultural utilization and development. Annual average precipitation decreased at a rate of –9.89 mm per decade, and the warming trends were statistically significant with an increasing rate of 0.256°C per decade in this region since 1980. The model simulation revealed that paddy field, forestland, and wetland had positive effects on precipitation, which caused their gravity centers to migrate towards the same direction accompanied by the center of precipitation gravity, while different responses were seen for building land, dry land and unused land. These results indicated that forestland had the largest influence on the increase of precipitation compared with the other land use types.The responses in promoting the temperature increase differed significantly, being the highest in building land, and the lowest in forestland. In general, the analysis of regional-scale LUCC showed a significant reduction of wetland, and the increases in building land and cropland contributed to a continuous drying and rapid warming in the SNP.

Hydrological Simulation Using TRMM and CHIRPS Precipitation Estimates in the Lower Lancang-Mekong River Basin

Satellite-based products with high spatial and temporal resolution provide useful precipitation information for data-sparse or ungauged large-scale watersheds. In the Lower Lancang-Mekong River Basin, rainfall stations are sparse and unevenly distributed, and the transboundary characteristic makes the collection of precipitation data more difficult, which has restricted hydrological processes simulation. In this study, daily precipitation data from four datasets(gauge observations, inverse distance weighted(IDW) data, Tropical Rainfall Measuring Mission(TRMM) estimates, and Climate Hazards Group InfraRed Precipitation with Stations(CHIRPS) estimates), were applied to drive the Soil and Water Assessment Tool(SWAT) model, and then their capability for hydrological simulation in the Lower Lancang-Mekong River Basin were examined. TRMM and CHIRPS data showed good performances on precipitation estimation in the Lower Lancang-Mekong River Basin, with the better performance for TRMM product. The Nash-Sutcliffe efficiency(NSE) values of gauge, IDW, TRMM, and CHIRPS simulations during the calibration period were 0.87, 0.86, 0.95, and 0.93 for monthly flow, respectively, and those for daily flow were 0.75, 0.77, 0.86, and 0.84, respectively. TRMM and CHIRPS data were superior to rain gauge and IDW data for driving the hydrological model, and TRMM data produced the best simulation performance. Satellite-based precipitation estimates could be suitable data sources when simulating hydrological processes for large data-poor or ungauged watersheds, especially in international river basins for which precipitation observations are difficult to collect. CHIRPS data provide long precipitation time series from 1981 to near present and thus could be used as an alternative precipitation input for hydrological simulation, especially for the period without TRMM data. For satellite-based precipitation products, the differences in the occurrence frequencies and amounts of precipitation with different intensities would affect simulation results of water balance components, which should be comprehensively considered in water resources estimation and planning.

Evaluation of surface temperature and pressure derived from MERRA-2 and ERA5 reanalysis datasets and their applications in hourly GNSS precipitable water vapor retrieval over China

Temperature and pressure play key roles in Global Navigation Satellite System(GNSS) precipitable water vapor(PWV) retrieval. The National Aeronautics and Space Administration(NASA) and European Center for Medium-Range Weather Forecasts(ECMWF) have released their latest reanalysis product: the modern-era retrospective analysis for research and applications, version 2(MERRA-2) and the fifthgeneration ECMWF reanalysis(ERA5), respectively. Based on the reanalysis data, we evaluate and analyze the accuracy of the surface temperature and pressure products in China using the the measured temperature and pressure data from 609 ground meteorological stations in 2017 as reference values.Then the accuracy of the two datasets and their performances in estimating GNSS PWV are analyzed. The PWV derived from the pressure and temperature products of ERA5 and MERRA-2 has high accuracy. The annual average biases of pressure and temperature for ERA5 are-0.07 hPa and 0.45 K, with the root mean square error(RMSE) of 0.95 hPa and 2.04 K, respectively. The annual average biases of pressure and temperature for MERRA-2 are-0.01 hPa and 0.38 K, with the RMSE of 1.08 h Pa and 2.66 K, respectively.The accuracy of ERA5 is slightly higher than that of MERRA-2. The two reanalysis data show negative biases in most regions of China, with the highest to lowest accuracy in the following order: the south,north, northwest, and Tibet Plateau. Comparing the GNSS PWV calculated using MERRA-2(GNSS MERRA-2 PWV) and ERA5(GNSS ERA5 PWV) with the radiosonde-derived PWV from 48 co-located GNSS stations and the measured PWV of the co-location radiosonde stations, it is found that the accuracy of GNSS ERA5 PWV is better than that of GNSS MERRA-2 PWV. These results show the different applicability of surface temperature and pressure products from MERRA-2 and ERA5 data, indicating that both have important applications in meteorological research and GNSS water vapor monitoring in China.

Drought monitoring and reliability evaluation of the latest TMPA precipitation data in the Weihe River Basin, Northwest China

The high resolution satellite precipitation products bear great potential for large-scale drought monitoring, especially for those regions with sparsely or even without gauge coverage. This study focuses on utilizing the latest Version-7 TRMM Multi-satellite Precipitation Analysis （TMPA 3B42V7） data for drought condition monitoring in the Weihe River Basin （0.135×10^6 km2）. The accuracy of the monthly TMPA 3B42V7 satellite precipitation data was firstly evaluated against the ground rain gauge observations. The statistical characteristics between a short period data series （1998-2013） and a long period data series （1961-2013） were then compared. The TMPA 3B42V7-based SPI （Standardized Precipitation Index） sequences were finally validated and analyzed at various temporal scales for assessing the drought conditions. The results indicate that the monthly TMPA 3B42V7 precipitation is in a high agreement with the rain gauge observations and can accurately capture the temporal and spatial characteristics of rainfall within the Weihe River Basin. The short period data can present the characteristics of long period record, and it is thus acceptable to use the short period data series to estimate the cumulative probability function in the SPI calculation. The TMPA 3B42V7-based SPI matches well with that based on the rain gauge observations at multiple time scales （i.e., 1-, 3-, 6-, 9-, and 12-month） and can give an acceptable temporal distribution of drought conditions. It suggests that the TMPA 3B42V7 precipitation data can be used for monitoring the occurrence of drought in the Weihe River Basin.

Tropical Rainfall Measuring Mission Performance in the Measurement of Precipitation for the MuriaéSub-basin

Correct precipitation data are essential for a hydrological study.However,the pluviometric stations provide us quite doubtful data.More satellites have explored this area.Therefore,the spatial estimates of precipitation can be extremely useful,since they present data of the whole surface,since the pluviometers do not exist in areas of difficult access.The objective of this work is to analyze the precipitation data obtained by the rain gauges and the Tropical Rainfall Measuring Mission(TRMM)satellite for the Muriaésub-basin,which belongs to the Paraíba do Sul Basin.It was used Thissen method and free software R for the manipulation of the data and its comparison.The results were satisfactory,showing that the estimates of this satellite can be an alternative source of data.

Precipitation Detection and Retrieving Based on FY-3C MWHTS

The paper develops a passive sub-millimeter precipitation retrievals algorithm for Microwave Humidity and Temperature Sounder(MWHTS)onboard the Chinese Feng Yun 3C(FY-3C)satellite.The retrieval algorithm employs a number of neural network estimators trained and evaluated using the validated global reference physical model NCEP/WRF/ARTS,and works for seawater.NCEP data per 6 hours are downloaded to run the Weather Research and Forecast model WRF,and derive the typical precipitation data from the whole world.The Atmospheric Radiative Transfer Simulator ARTS is feasible for performing simulations of atmospheric radiative transfer.Rain detection algorithm has been used to generate level 2 products.Retrievals are reliable for surface precipitation rate higher than 0.1 mm/h at 15km resolution,which is in good agreement with those retrieved using the Precipitation retrieval algorithm version 1(ATMP-1)for Advanced Technology Microwave Sounder(ATMS)aboard Suomi NPP satellite.

长江上游卫星反演与再分析降水数据的适用性评估

为评估不同降水数据在长江上游的适用性,基于气象站点观测数据,采用多种评价指标,定量评估了卫星反演降水数据(IMERG-Final、GSMaP-Gauge)及再分析降水数据(ERA5-Land)在长江上游的应用精度,并分析了各降水数据在不同等级降水的误差结构。结果表明:3套降水数据均能准确捕捉流域降水东高西低的空间格局,与观测降水有着良好的相关性,且2015—2019年表现平稳,有可长期应用的潜力;各降水数据时间分辨率越高,误差相对越大,在流域地形变化剧烈的中部误差更大;对弱降水易错报高估,对强降水的低估随降水强度上升而加剧;两套卫星反演降水数据总体误差较小,适用性良好,IMERG-Final有更好的误差控制能力,GSMaP-Gauge对降水发生的识别更为准确;ERA5-Land明显高估流域降水,尤其在西南部地区。

基于新安江模型的老挝南俄河流域径流变化贡献率分析

为分析20世纪60年代以来气候变化和人类活动对老挝南俄河流域径流变化的贡献率,基于流域内地面站点实测降水数据,对广泛应用于湄公河流域的APHRODITE和MSWEP两种卫星降水产品日降水数据进行了偏差校正,采用经校正的基准期卫星日降水和白冠洪、欣赫普两站点实测日径流资料构建了新安江模型,模拟还原了流域水库影响期的天然日径流过程,定量分析了气候变化和人类活动对径流变化的贡献率。结果表明:南俄河流域年径流总体呈下降趋势;白冠洪站两个水库影响期气候变化对径流变化的贡献率分别为-429%和-399%,欣赫普站水库影响期气候变化对径流变化的贡献率为-380%,而对应的人类活动贡献率分别为529%、499%和480%,人类活动是流域径流变化的主要原因;以水库运行为主的人类活动对径流年内分配影响显著,丰水期人类活动影响量的绝对值超过气候变化影响量绝对值的2倍。

基于多套卫星资料的ERA5全球小时降水频率评估

最近发布的新一代全球再分析资料集ERA5,提供了全球小时降水再分析值,为全球小时降水研究提供又一个数据参考。然而,目前针对ERA5小时降水频率的评估工作还较为有限。本研究采用多套全球卫星观测小时降水对ERA5小时降水的频率进行了评估。对比分析发现:尽管ERA5总降水量与卫星资料出现较好的一致性,但ERA5的小时降水频率约为卫星资料的2~3倍,呈现系统性偏高。进一步分析表明,这主要是由于ERA5大大高估了中、低强度降水事件的数量。其中,ERA5对弱降水频率的高估尤为明显,平均可达卫星降水频率的6倍;此外,ERA5对海洋降水频率的高估程度也大于陆地。ERA5小时降水频率的系统性高估问题对相关研究的潜在影响,尚在进一步评估中。