Estimation of Precipitation Area Using S-Band Dual-Polarization Radar Measurements

Estimating precipitation area is important for weather forecasting as well as real-time application. This paper aims to develop an analytical framework for efficient precipitation area estimation using S-band dual-polarization radar measurements. Several types of factors, such as types of sensors, thresholds, and models, are considered and compared to form a data set. After building the appropriate data set, this paper yields a rigorous comparison of classification methods in statistical (logistic regression and linear discriminant analysis) and machine learning (decision tree, support vector machine, and random forest). To achieve better performance, spatial classification is considered by incorporating latitude and longitude of observation location into classification, compared with non-spatial classification. The data used in this study were collected by rain detector and present weather sensor in a network of automated weather systems (AWS), and an S-band dual-polarimetric weather radar during ten different rainfall events of varying lengths. The mean squared prediction error (MSPE) from leave-one-out cross validation (LOOCV) is computed to assess the performance of the methods. Of the methods, the decision tree and random forest methods result in the lowest MSPE, and spatial classification outperforms non-spatial classification. Particularly, machine-learning-based spatial classification methods accurately estimate the precipitation area in the northern areas of the study region.

The impact of diurnal precipitation over Sumatra Island, Indonesia, on synoptic disturbances and its relation to the Madden-Julian Oscillation

<p>The impact of diurnal precipitation over Sumatra Island, the Indonesian Maritime Continent (MC), on synoptic disturbances over the eastern Indian Ocean is examined using high-resolution rainfall data from the Global Satellite Mapping of Precipitation project and the Japanese 55-year Reanalysis data during the rainy season from September to April for the period 2000–2014. When the diurnal cycle is strong, the high precipitation area observed over Sumatra in the afternoon migrates offshore during nighttime and reaches 500 km off the coast on average. The strong diurnal events are followed by the development of synoptic disturbances over the eastern Indian Ocean for several days, and apparent twin synoptic disturbances straddling the equator develop only when the convective center of the Madden–Julian Oscillation (MJO) lies over the Indian Ocean (MJO-IO). Without the MJO, the synoptic disturbances develop mainly south of the equator. The differences in the locations and behaviors of active synoptic disturbances are related to the strength of mean horizontal winds in the lower troposphere. During the MJO-IO, the intensification of mean northeasterly winds in the northern hemisphere blowing into the organized MJO convection in addition to mean southeasterly winds in the southern hemisphere facilitate the formation of the twin disturbances. These results suggest that seed disturbances arising from the diurnal offshore migration of precipitation from Sumatra develop differently depending on the mean states over the eastern Indian Ocean. Furthermore, it is shown that the MJO events with the strong diurnal cycle tend to have longer duration and continuing eastward propagation of active convection across the MC, whereas the convective activities of the other MJO events weaken considerably over the MC and develop again over the western Pacific. These results suggest that the strong diurnal cycle over Sumatra facilitates the smooth eastward propagation of the intraseasonal convection across the MC.</p>

The effect of different contributing sensors in IMERG-Final precipitation estimates

<p>Ground observation absence in many parts of the world highlights the importance of merged satellite precipitation products. In this study, we aim to evaluate the effect of different sources of data in the uncertainties of a merged satellite product, by comparing the Integrated Multi-satellitE Retrievals for GPM (IMERG) final-product V06B with a ground-radar product, Multi-Radar Multi-Sensor (MRMS), over eastern United-States during the hurricane days that occurred in 2016-2018 using both pixel-based and object-based approaches. The results showed that IMERG had better agreement in terms of the average precipitation intensity and area when the passive microwave (PMW) sensor overpass is matched instantaneously with MRMS in comparison with the temporally averaged MRMS data (MRMS-Averaged) with a bias reduction of 75% and 65%, respectively. PMW observations tend to show storms with smaller areas in the IMERG final product in comparison with MRMS, possibly due to the effect of light precipitation not detected properly by PMW sensors. However, by removing the light precipitation (less than 1mm/hr) in the object-based approach, hurricane objects in the IMERG final product tend to be larger during the PMW observations, which might be related to different viewing angles of sensors contributing to MRMS and IMERG products. Precipitation estimates in the IMERG final product have smaller areas with higher average intensity during the PMW observations compared to data estimated by Morph or IR (morph/IR) observations. It is probably related to the effect of morphing technique, leading to homogenization of the varying rainstorm characteristics. The quality of IMERG data changes with the longer absence of the PMW observations. IMERG data estimated by morph/IR observations, with a 30-minute time-distance to the nearest PMW observation, showed the best agreement with MRMS-Averaged even in comparison with PMW estimates, possibly due to the time-lag in recording the precipitation between satellites and ground-radars. It is also possible to be related to the homogenizing nature of morphing technique in IMERG and averaging MRMS data in time in MRMS-Averaged, relaxing the differences between PMW observations and MRMS. However, the morph/IR data quality deteriorates with the longer absence of PMW sensors. The inter-comparison of PMW sensors showed the priority of imagers over sounders with GMI as the best among imagers and MHS as the best among sounders in terms of correlation and average intensity compared to MRMS; however, SSMIS was the best in capturing the precipitation area.</p>

Drought analysis with different indices for the Asi Basin (Turkey)

Today, within the scope of planning, development and management of water resources affected adversely by climate change, the issue of minimization of the adverse effects of drought has become very important. In this study, drought risk analyses were performed using meteorological, hydrogeological and hydrological data of the Asi basin and as a result of the determination of different indices and indicators available in the literature. First, the missing data was completed by regional analyses. The DI (Deciles Index), SPI (Standardized Precipitation Index), SPEI (Standardized Precipitation Evapotranspiration Index) and SRI (Standardized Runoff Index) indices were described. Drought severity and magnitude were found according to these indices. Based on 1, 3, 6, 9, 12, 48-month recurrence intervals, analyses were made. Classification of droughts and their threshold values were determined. For some places, drought incidence rates were presented according to each index. The indices were compared, the correlation between them was examined and a common conclusion was reached. The drought severities, which has a precipitation area of 7800 m2, were evaluated for certain recurrence intervals. For this purpose, based on meteorological, hydrological and hydrogeological data for the years between 1970 and 2016, DI, SPI, SPEI, and SRI indices were analyzed and compared.

Numerical Simulation and Mechanism Analysis of an Extreme Precipitation in Ili Valley, Xinjiang

<p>The Ili Valley is an area with frequent heavy rain in Xinjiang. In this paper, a heavy rainstorm process in this area on June 26, 2015 is taken as an example. The observational data and WRF high-resolution numerical simulation results are used to analyze the synoptic background and the process of the precipitation. The results show that: (1) The Central Asian low vortex and the upper-level jet provides a favorable circulation background for this heavy rain. Northerly winds and westerly winds forms a low-level convergence line in Ili Valley. (2) In addition to the convergence of low-level airflow, the uplifting effect of the terrain on the westerly winds also intensifies the low-level ascending motion. At the same time, the uplifting effect of the terrain on the northerly winds causes the middle-level ascending motion. After the low-level ascending motion is connected with that of the middle level, precipitation begins to occur. The convection further develops, superimposed with the upwards phase of upper-level wave, and the precipitation increases strongly. (3) Through spectral analysis methods, the characteristics of the upper-level wave are obtained, and the wave is an inertial gravity wave. It is further obtained from the mesoscale three-dimensional Eliassen-Palm (EP) flux that during the period of heavy precipitation, the energy of the upper-level inertial gravity wave is transported down to the low level of the precipitation area. (4) Convective instability plays an important role in the enhancement of the precipitation in the Ili Valley. The analysis of potential divergence further indicates that the convective instability in the precipitation area is mainly caused by the vertical shear part of potential divergence, while the divergence part of the potential divergence can strengthen the convective instability in the leeward slope of the terrain. It indicates that the dynamic and thermodynamic factors are coupled with each other, which affects the precipitation location, intensity and evolution.</p>

Precipitation Retrieval over the Tibetan Plateau from the Geostationary Orbit—Part 1: Precipitation Area Delineation with Elektro-L2 and Insat-3D

The lack of long term and well distributed precipitation observations on the Tibetan Plateau (TiP) with its complex terrain raises the need for other sources of precipitation data for this area. Satellite-based precipitation retrievals can fill those data gaps. Before precipitation rates can be retrieved from satellite imagery, the precipitating area needs to be classified properly. Here, we present a feasibility study of a precipitation area delineation scheme for the TiP based on multispectral data with data fusion from the geostationary orbit (GEO, Insat-3D and Elektro-L2) and a machine learning approach (Random Forest, RF). The GEO data are used as predictors for the RF model, extensively validated by independent GPM (Global Precipitation Measurement Mission) IMERG (Integrated Multi-satellitE Retrievals for GPM) gauge calibrated microwave (MW) best-quality precipitation estimates. To improve the RF model performance, we tested different optimization schemes. Here, we find that (1) using more precipitating pixels and reducing the amount of non-precipitating pixels during training greatly improved the classification results. The accuracy of the precipitation area delineation also benefits from (2) changing the temporal resolution into smaller segments. We particularly compared our results to the Infrared (IR) only precipitation product from GPM IMERG and found a markedly improved performance of the new multispectral product (Heidke Skill Score (HSS) of 0.19 (IR only) compared to 0.57 (new multispectral product)). Other studies with a precipitation area delineation obtained a probability of detection (POD) of 0.61, whereas our POD is comparable, with 0.56 on average. The new multispectral product performs best (worse) for precipitation rates above the 90th percentile (below the 10th percentile). Our results point to a clear strategy to improve the IMERG product in the absence of MW radiances.

Environmental Conditions for Nighttime Offshore Migration of Precipitation Area as Revealed by In Situ Observation off Sumatra Island

The diurnal cycle over tropical coastal waters is characterized by offshore migration of precipitation area during nighttime. This study analyzes in situ observational data collected during the YMC-Sumatra 2017 field campaign around the western coast of Sumatra Island, Indonesia, to examine the offshore migration phenomenon during 5–31 December 2017, when the Research Vessel Mirai was deployed about 90 km off the coast to perform observation. The offshore migration is observed in only less than a half of the 27 days. A comparison of radiosonde data at the vessel between days with and without the offshore migration reveals that vertical wind shear in the lower troposphere is a key environmental condition. In late afternoon of the days with the offshore migration, offshore (northeasterly) wind shear with height with considerable magnitude is observed, which is due to weaker daily mean southwesterly wind in the lower free troposphere, stronger southwesterly wind in the boundary layer, and sea breeze. As this condition is considered favorable for regeneration of convective cells to the offshore side of old ones, these results support an idea that the regeneration process is critical for the offshore migration. The Madden–Julian oscillation and cold surges play some roles in the weakening of the free-tropospheric wind. The migration speed is estimated at 2–3 m s−1, which is lower than that observed in another field campaign conducted in 2015 (Pre-YMC 2015). This difference is partly due to the difference in the environmental wind in the lower to midtroposphere.

Precipitation Enhancement via the Interplay between Atmospheric Rivers and Cutoff Lows

A significant enhancement of precipitation can result from the interplay between two independent, large-scale phenomena: an atmospheric river (AR) and a cutoff low. An AR is a long, narrow region with a deep moist layer. A cutoff low is an upper-level cyclonic eddy isolated from the meandering upper-level westerly jet. Herein, we construct composites of cutoff lows both close to an AR (AR-close category) and distant from an AR (AR-distant category) over a 14-yr period across the western North Pacific region. A comparison between the two categories shows an enhanced precipitation area to the northwest of the cutoff low and to the south of the AR axis in the AR-close category. The horizontal formation among the AR, cutoff low, and enhanced precipitation area in the composite coincides with that in a disastrous flood event that occurred in Hiroshima, Japan, in 2014. The deep moist layer associated with the AR, and the destabilization and isentropic up-gliding effect associated with the cutoff low are also observed in both the composite and the Hiroshima cases. We further evaluate the distribution of quasigeostrophic forcing (Q vector) for vertical motion. This shows that warm air advection associated with the AR overcomes the descending forcing inherent in the northwest of the cutoff low and makes the instability and up-gliding effect in that region more effective. These results indicate that the interplay between ARs and cutoff lows is a common mechanism in the enhancement of precipitation and the Hiroshima case is an extreme precipitation event caused by this interplay.

The pattern of bird distribution along the elevation gradient of the Sutlej River basin, western Himalaya, India

We examined the species richness of birds along the elevation gradient of the Sutlej River basin in Himachal Pradesh in the western Himalaya of India. Birds were sampled at 318 sites categorized into 16 elevation bands ranging from 498 to 3700 m between June 2012 and April 2013. A total of 203 bird species were recorded. Species richness showed a monotonic decline with increasing elevation, with 27% of species recorded within a narrow elevation range. We tested the roles of explanatory variables such as environment (temperature, precipitation, area, & Mid-domain Effect (MDE) richness) and habitat (Normalized Differential Vegetation Index (NDVI): July, November & March) on the observed distribution pattern. The observed species richness pattern was strongly correlated with temperature, while three other variables—precipitation, area, and MDE richness—contributed negligibly to the observed pattern. The present study indicates that climatic conditions and vegetation are the major contributors for determining species richness along the Sutlej River basin. Thus, a customized approach is crucial for conservation of species in the elevation range.