Hydrometeorology

Development of an accurate precipitation dataset is of primary importance for regional hydrological process studies and water resources management. Here, four regional precipitation products are evaluated for the Heihe River basin (HRB): 1) a spatially and temporally disaggregated Climate Prediction Center Merged Analysis of Precipitation (CMAP) at 0.25° spatial resolution (DCMAP); 2) a fusion product obtained by merging China Meteorological Administration station data and Tropical Rainfall Measuring Mission precipitation data at 0.1° spatial resolution supported by the Institute of Tibetan Plateau Research (ITP), Chinese Academy of Sciences (ITP-F); 3) a disaggregated CMAP downscaled by a statistical meteorological model tool at 1-km spatial resolution (DCMAP–MicroMet); and 4) a Weather Research and Forecasting (WRF) Model simulation with 5-km resolution (WRF-P). The validation metrics include spatial pattern, temporal pattern, error analysis with respect to observation data, and p...

The Hindukush Karakoram Himalayan mountains contain some of the largest glaciers of the world, and supply melt water from perennial snow and glaciers to the Upper Indus Basin (UIB) upstream of Tarbela dam, which constitutes greater than 80% of the annual flows, and caters to the needs of millions of people in the Indus Basin. It is therefore important to study the response of perennial snow and glaciers in the UIB under changing climatic conditions, using improved hydrological modeling, glacier mass balance, and observations of glacier responses. However, the available glacier inventories and datasets only provide total perennial-snow and glacier cover areas, despite the fact that snow, clean ice and debris covered ice have different melt rates and densities. This distinction is vital for improved hydrological modeling and mass balance studies. This study, therefore, presents a separated perennial snow and glacier inventory (perennial snow-cover on steep slopes, perennial snow-cover...

An Analytic model which describes properly the energy liberated or dissipated by a hurricane is
presented. Nowadays exists some kind of information related to the energy liberated by a hurricane, which
we can nd with a non safe source at all at the internet. This model can give numerical values which
represents the amount of energy liberated per time unit by a hurricane. Also there are presented some
specic examples of the functioning of this model with the information of a few hurricanes, and a data
base containing the energy values for the energy liberated by the same list of hurricanes calculated with
the model. Mathematically speaking, the model is represented by an integral equation which is ought to be
solved numerically, and it was nd also a way to calculate this energy values thru the integral just solving
this integral rst and then substitute the respective values in this last expression.

Xülasə. Məqalədə son 100 il ərzində Xəzər dənizində baş verən mühüm gəmi qəzalarının statistikası (təsviri, nəticələri) təhlil edilir. Qəzaların əsasən 3 faktordan asılı olduğu göstərilir (insan,texniki, hidrometeoroloji). Hidrometeoroloji faktorların 40%-dən çox olduğu qeyd edilir.

Аннотация. Анализирована статистика судовых аварий на Каспийском море за последние 100 лет. Выяснилось что причины аварий вызвано  в основным
тремя факторами: человеческим, техническим, гидрометеорологическим. Гидрометеорологические факторы составляет более 40% из всех аварии.

Abstract. In this article, period of last 100 years statistic of ships accident on Caspian Sea are analyzed. Additionally, shown that accidents depend on the following three factors: human, technical and hydro meteorological factors. Noted that the hydro meteorological factors are mentioned to be higher than 40 percent of all accidents.

Denser observation data (1 precipitation gauging station per 548km2) were used.Regional trend analysis found increasing precipitation in mountain and coastal.Precipitations are correlated with the decadal Oscillation.The present study performs the spatial and temporal trend analysis of the annual and seasonal time-series of a set of uniformly distributed 249 stations precipitation data across the state of North Carolina, United States over the period of 1950–2009. The Mann–Kendall (MK) test, the Theil–Sen approach (TSA) and the Sequential Mann–Kendall (SQMK) test were applied to quantify the significance of trend, magnitude of trend, and the trend shift, respectively. Regional (mountain, piedmont and coastal) precipitation trends were also analyzed using the above-mentioned tests. Prior to the application of statistical tests, the pre-whitening technique was used to eliminate the effect of autocorrelation of precipitation data series. The application of the above-mentioned procedures has shown very notable statewide increasing trend for winter and decreasing trend for fall precipitation. Statewide mixed (increasing/decreasing) trend has been detected in annual, spring, and summer precipitation time series. Significant trends (confidence level ≥ 95%) were detected only in 8, 7, 4 and 10 nos. of stations (out of 249 stations) in winter, spring, summer, and fall, respectively. Magnitude of the highest increasing (decreasing) precipitation trend was found about 4 mm/season (− 4.50 mm/season) in fall (summer) season. Annual precipitation trend magnitude varied between − 5.50 mm/year and 9 mm/year. Regional trend analysis found increasing precipitation in mountain and coastal regions in general except during the winter. Piedmont region was found to have increasing trends in summer and fall, but decreasing trend in winter, spring and on an annual basis. The SQMK test on “trend shift analysis” identified a significant shift during 1960 − 70 in most parts of the state. Finally, the comparison between winter (summer) precipitations with the North Atlantic Oscillation (Southern Oscillation) indices concluded that the variability and trend of precipitation can be explained by the Oscillation indices for North Carolina.

Floods in the western part of Java Island area, including the Jakarta City, Bandung, Sumedang and Garut Regency is the most extreme incident like the incident in 2007. In 2016, flood occurred in March that caused the Citarum river overflowed. The overflowed of the Citarum river resulted in 15 regions in Bandung Regency were flooded (BNPB) and as many as 5,900 heads of households consisting of 24,000 inhabitants affected by the floods and more than 3,000 people displaced (BPBD Bandung). With this background, further analysis related to floods, especially from remote sensing is needed. This study was conducted to analyze the incidence of flooding in the western part of Java Island on March 12-13, 2016 with atmospheric parameters. The data used is the MODIS Near Real Time (NRT) Global Flood Mapping data with a resolution of 250m and daily rainfallsatellite data with GSMaP and reanalysis data from CHIRPS for the analysis of rainfall intensity during a flood. While the software used areQGIS, Google Earth, and GrADS. Observations flood MODIS image folder averaging 2 days (March, 12-13 2016) shows the floods are marked with red color found in Jakarta, Bandung, and partly in the area of Garut, Subang, Sumedang and Cirebon. MODIS image analysis in accordance with the spatial distribution of rainfall intensity averaging 2 days of GSMaP, which shows rainfall in these areas ranged from 20-80 mm/day were classified in the category of moderate to heavy rainfall by BMKG. Thus, the results of this study show that MODIS NRT imagery is good enough to analyze the flooding event in the western part of Java Island on March 2016.

Keywords: Floods, CHIRPS, GSMaP, MODIS

The Global Flood Awareness System (GloFAS) is a preoperational suite performing daily streamflow simulations to detect severe floods in large river basins. GloFAS defines the severity of a flood event with respect to thresholds estimated based on model-simulated streamflow climatology. Hence, determining accurate and consistent critical thresholds is important for its skillful flood forecasting. In this work, streamflow climatologies derived from two global meteorological inputs were compared, and their impacts on global flood forecasting were assessed. The first climatology is based on precipitation-corrected reanalysis data (ERA-Interim), which is currently used in the operational GloFAS forecast, while the second is derived from reforecasts that are routinely produced using the latest weather model. The results of the comparison indicate that 1) flood thresholds derived from the two datasets have substantial dissimilarities with varying characteristics across different regions of...

The reference evapotranspiration (ET0) is an essential variable in the agrohydrological systems and its estimation on a regional scale is limited to its spatial variability. This study compares two approaches for preparation of spatial distribution maps of ET0 in Mazandaran province of Iran. In the first approach, ET0 was calculated using climatic data and Hargreaves-Samani equation in weather stations locations and then were interpolated. In the second approach, the components of the Hargreaves-Samani equation were interpolated and then ET0 maps were prepared by applying the Hargreaves-Samani equation and suitable commands in GIS. The 10-year climatic data for 51 weather stations (46 stations for preparing ET0 maps and 5 stations as validation station) were gathered over Mazandaran province. Semivariograms were calculated and the best semivariogram model was selected on the basis of the least value of Residual Sums of Squares (RSS). The spatial correlation of the data was compared on the basis of Nugget to Sill ratio. The data were interpolated using Ordinary Kriging method and the interpolation error was computed by cross validation technique based on Root Mean Square Standardized Error (RMSSE). The predicted ET0 values were compared to the computed ET0 in validation stations and sensitivity analysis was conducted. Results show the second approach had better spatial correlation and lower interpolation error and the difference between these two approaches were not significant. Therefore , the accuracy of the ET0 maps is more related to the method of computing ET0 than the type of climatic data is being interpolated.

Xülasə. Müasir dövrdə iqtisadi cəhətdən sərfəli keçid marşrutlarının seçilməsi və gəminin bu kurslar üzrə təyinat limanına aparılması mühüm əhəmiyyət kəsb edir. Xüsusilə okean səfərləri zamanı gəminin iki məntəqə arasında ən qısa məsafə hesab edilən böyük çevrə qövsü ilə aparılması gəmi sahiblərinə əlavə məsrəflərdən xilas olmağa kömək edir. Məqalədə gəmi sürücüləri üçün bu qısa və optimal keçid marşrutunun seçilməsi üsulları göstərilmişdir.

Аннотация. В современное время очень важно выбрать экономически выгодные маршруты и вести судна по этим курсам до порта назначение. Особенно важно во время пересечения океана вести судна по дуге большого круга, которая считается самым коротким путем между двумя пунктами и  помогает судовладельцем избежать дополнительных расходов. В статье показан метод выбора этих коротких и оптимальных маршрутов для судоводителей.

Abstract. Nowadays, it’s very important to choose advantageous economic passage routes and operate vessel on these courses to the port of destination. İt helps to escape shipping owners from additionally expense, especially during crossing ocean, when the vessels sailing on the course of arch of great circle, considered the shortest distance between the two ports. The article deals with methods of choosing the shortest and optimal passage route for navigators.

ABSTRACT When evaluating the reliability of an ensemble prediction system, it is common to compare the root-mean-square error of the ensemble mean to the average ensemble spread. While this is indeed good practice, two different and inconsistent methodologies have been used over the last few years in the meteorology and hydrology literature to compute the average ensemble spread. In some cases, the square root of average ensemble variance is used, and in other cases, the average of ensemble standard deviation is computed instead. The second option is incorrect. To avoid the perpetuation of practices that are not supported by probability theory, the correct equation for computing the average ensemble spread is obtained and the impact of using the wrong equation is illustrated.

Xülasə. Məqalədə hidrometeoroloji faktorların təsiri nəticəsində dreyf bucağının yaranması məsələsi araşdırılmış və su oturumundan asılı olaraq müxtəlif gəmilər üçün dreyf əmsalının tapılması yolları göstərilmişdir.
Аннотация. В статье исследовано влияние гидрометеорологических факторов на образование угла дрейфа судна, даны методы расчета коэффициента дрейфа судна с различной осадкой.

Abstract. The article deals with the influence of hydro meteorological factors on the formation of drift angle and methods of calculation of drift coefficient depending on the draught of vessels.

The estimation of rainfall is very important in increasing the accuracy of the weather forecast. An accurate weather forecast will reduce the impactof disaster risks. Jayapura was chosen as the stufy are because in recent times there was heavy rain for three consecutive days which caused various losses. Estimation of rainfall by applying various estimators have been widely carried out but specifically discussing the phenomenon of heavy rainfall is still small. This research was carried out by utilizing the Himawari-8 channel 13 (Infrared1) satellite data as input to estimate rainfall and compared to Authomatic Weather Station Digitation Dok II Jayapura rainfall data. The estimator methods used are Autoestimator, Insat Multispectral Rainfall Algorithm (IMSRA), Non-Linear Relation, Non-Linear Inversion. Cloud top temperature data for three heavy rain events (16-18 March 2019) are converted into rainfall data every hour during the convection process. Phase of cloud develompment (growing, mature, extinct) based on time series cloud top temperature which indicates a decreace in temperature at growing phase, low maximum in mature phase, and increase in extinct phase. The result of this study show that the best estimation method for heavy rain in Jayapura base on ranking point (higest correlation and lowest RMSE) is IMSRA.

Gridded estimates of precipitation using both satellite and observational station data are regularly used as reference products in the evaluation of basic climate fields and derived indices as simulated by regional climate models (RCMs) over the current period. One of the issues encountered in RCM evaluation is the fact that RCMs and reference fields are usually on different grids and often at different horizontal resolutions. A proper RCM evaluation requires remapping on a common grid. For the climate indices or other derived fields, the remapping can be done in two ways: either as a first-step operation on the original field with the derived index computed on the final/common grid in a second step, or to compute first the climate index on the original grid before remapping or regridding it as a last-step operation on the final/common grid. The purpose of this paper is to illustrate how the two approaches affect the final field, thus contributing to one of the Coordinated Regional ...

Urbanization modifies surface energy and water budgets, and has significant impacts on local and regional hydroclimate. In recent decades, a number of urban canopy models have been developed and implemented into the Weather Research and Forecasting (WRF) model to capture urban land-surface processes. Most of these models are inadequate due to the lack of realistic representation of urban hydrological processes. Here, we imple- ment physically-based parametrizations of urban hydrological processes into the single layer urban canopy model in the WRF model. The new single-layer urban canopy model features the integration of, (1) anthropogenic latent heat, (2) urban irrigation, (3) evaporation from paved surfaces, and (4) the urban oasis effect. The new WRF–urban modelling system is evaluated against field measurements for four different cities; results show that the model performance is substantially improved as compared to the current schemes, especially for latent heat flux. In particular, to evaluate the performance of green roofs as an urban heat island mitigation strategy, we integrate in the urban canopy model a multilayer green roof system, enabled by the physical urban hydrological schemes. Simulations show that green roofs are capable of reducing surface temperature and sensible heat flux as well as enhancing building energy efficiency.

Abstrak.Hujan ekstrem telah terjadi di Sibolga yang terletak pada koordinat 01°33'15"LU dan 098°53'26" BT pada hari Minggu tanggal 6 Maret 2016. Menurut data observasi stasiun Meteorologi Pinangsori Sibolga tercatat intensitas curah hujan sebesar 190 mm selama 24 jam. Hal ini mengindikasikan adanya gangguan fisis atmosfer yang menyebabkan kejadian hujan ekstrem tersebut terjadi. Untuk itu, penulis meninjau kondisi fisis atmosfer serta gangguan cuaca secara deskriptif untuk dapat menjelaskan penyebab hujan ekstrem tersebut terjadi. Analisis ini menggunakan data ECMWF (European Centre for Medium-Range Weather Forecast) dan citra satelit serta data observasi Stasiun Meteorologi Pinangsori Sibolga tanggal 6 Maret 2016 untuk verifikasi kejadian. Dari penelitian ini, menunjukan bahwa kejadian hujan lebat di Sibolga ini dipengaruhi beberapa faktor seperti nilai kelembapan (RH) yang tinggi, suhu permukaan laut (SPL) yang menghangat di sekitar Sibolga serta adanya gerakan udara ke atas (updraft) yang memicu pertumbuhan awan-awan konvektif dan menyebabkan hujan ekstrem. Kata kunci : Hujan ekstrem, ECMWF, citra satelit, kondisi fisis atmosfer Abstract. Extreme rain has occurred in Sibolga located at coordinates 01°33'15"LU and 098°53'26"BT on Sunday, March 6 th , 2016. According to observation data of Pinangsori Sibolga Meteorological station recorded rainfall intensity of 190 mm for 24 hours. This indicates the existence of atmospheric physical disturbances that cause the occurrence of extreme rain. Hence, the authors review the condition of atmospheric physics and weather disorder descriptively to be able to explain the cause of the extreme rain. This analysis uses ECMWF (European Center for Medium-Range Weather Forecast) data and satellite imagery and observation data of Pinangsori Sibolga Meteorological Station on March 6 th , 2016 for the event verification. From this research, it shows that the occurrence of heavy rain in Sibolga is influenced by several factors such as high relative humidity (RH) value, sea surface temperature (SPL) warmed up around Sibolga as well as an upward updraft Triggering the growth of convective clouds and causing extreme rain.

Penggunaan sumber daya air pada akhir-akhir ini banyak sekali dilakukan, bahkan secara besar-besaran tanpa memedulikan dampak buruknya terhadap keberlanjutan lingkungan, hingga dapat dikatakan sudah masuk ke dalam tahap eksploitasi. Mungkin kita tidak pernah menyadari bahwa dalam kehidupan sehari-hari saja kita telah menggunakan air dalam jumlah yang cukup banyak. Padahal apabila kita membeli 1 kg daging sapi saja, hal itu setara dengan kita membeli 15.000 liter air dan apabila kita meminum secangkir kopi, hal itu setara dengan kita meminum 140 liter air. Sektor pertanian ini merupakan sektor yang paling banyak menggunakan air dalam setiap proses dan kegiatannya, yang mencapai 70% dari penggunaan rata-rata air setiap harinya oleh seluruh penduduk di dunia. Krisis air dunia saat ini sudah masuk pada tahap genting, tidak terkecuali di pulau Jawa, yang menjadi sentral dari seluruh kegiatan perekonomian Indonesia termasuk pertanian (POKJA AMPL 2012). Untuk dapat mengembangkan sektor pertanian di pulau Jawa ini, ada beberapa tantangan dan masalah yang harus dihadapi. Sumber daya air untuk kegiatan pertanian menjadi langka karena dampak penurunan tanah dan sumber daya air serta persaingan penggunaan air untuk sektor rumah tangga dan industri pula. Oleh karena itu, langkah-langkah untuk menjamin keamanan pangan dan kesejahteraan masyarakat harus diambil oleh pemerintah. Salah satunya dengan menggunakan indikator “tapak air/water footprint” dan “perdagangan air virtual/virtual water trade”. Penulisan karya tulis ilmiah ini dimaksudkan untuk mengukur arus air virtual di provinsi-provinsi di pulau Jawa terkait dengan perdagangan produk tanaman dan menentukan tapak air yang berkaitan dengan konsumsi produk tanaman di provinsi-provinsi di pulau Jawa.

Accurate precipitation forecasts are required for accurate flood forecasting. The structures of different precipitation forecasting systems are constantly evolving, with improvements in forecasting techniques, increases in spatial and temporal resolution, improvements in model physics and numerical techniques, and better understanding of, and accounting for, predictive uncertainty. Hence, routine verification is necessary to understand the quality of forecasts as inputs to hydrologic modeling. In this study, we verify precipitation forecasts from the National Centers for Environmental Prediction (NCEP) 11-member Global Ensemble Forecast System Reforecast version 2 (GEFSRv2), as well as the 21-member Short Range Ensemble Forecast (SREF) system. Specifically, basin averaged precipitation forecasts are verified for different basin sizes (spatial scales) in the operating domain of the Middle Atlantic River Forecast Center (MARFC), using multi-sensor precipitation estimates (MPEs) as the observed data. The quality of the ensemble forecasts is evaluated conditionally upon precipitation amounts, forecast lead times, accumulation periods, and seasonality using different verification metrics. Overall, both GEFSRv2 and SREF tend to overforecast light to moderate precipitation and underforecast heavy precipitation. In addition, precipitation forecasts from both systems become increasingly reliable with increasing basin size and decreasing precipitation threshold, and the 24-hourly forecasts show slightly better skill than the 6-hourly forecasts. Both systems show a strong seasonal trend, characterized by better skill during the cool season than the warm season. Ultimately, the verification results lead to guidance on the expected quality of the precipitation forecasts, together with an assessment of their relative quality and unique information content, which is useful and necessary for their application in hydrologic forecasting.

The Hindukush Karakoram Himalayan mountains contain some of the largest glaciers of the world, and supply melt water from perennial snow and glaciers to the Upper Indus Basin (UIB) upstream of Tarbela dam, which constitutes greater than 80% of the annual flows, and caters to the needs of millions of people in the Indus Basin. It is therefore important to study the response of perennial snow and glaciers in the UIB under changing climatic conditions, using improved hydrological modeling, glacier mass balance, and observations of glacier responses. However, the available glacier inventories and datasets only provide total perennial-snow and glacier cover areas, despite the fact that snow, clean ice and debris covered ice have different melt rates and densities. This distinction is vital for improved hydrological modeling and mass balance studies. This study, therefore, presents a separated perennial snow and glacier inventory (perennial snow-cover on steep slopes, perennial snow-covered ice, clean and debris covered ice) based on a semi-automated method that combines Landsat images and surface slope information in a supervised maximum likelihood classification to map distinct glacier zones, followed by manual post processing. The accuracy of the presented inventory falls well within the accuracy limits of available snow and glacier inventory products. For the entire UIB, estimates of perennial and/or seasonal snow on steep slopes, snow-covered ice, clean and debris covered ice zones are 7,238 ± 724, 5,226 ± 522, 4,695 ± 469 and 2,126 ± 212 km2 respectively. Thus total snow and glacier cover is 19,285 ± 1,928 km2, out of which 12,075 ± 1,207 km2 is glacier cover (excluding steep slope snow-cover). Equilibrium Line Altitude (ELA) estimates based on the Snow Line Elevation (SLE) in various watersheds range between 4,800-5,500 m, while the Accumulation Area Ratio (AAR) ranges between 7-80%. 0°C isotherms during peak ablation months (July and August) range between ∼ 5,500-6,200m in various watersheds. These outputs can be used as input to hydrological models, to estimate spatially-variable degree day factors for hydrological modeling, to separate glacier and snow-melt contributions in river flows, and to study glacier mass balance, and glacier responses to changing climate.