Judul: Asimilasi Model Weather Research And Forecasting (WRF) Dengan Data Observasi Untuk Prediksi Curah Hujan di Wilayah Jawa.
Abstrak: Asimilasi data merupakan metode memperbaiki data kondisi awal atmosfer sebagai input model dengan memperhitungkan data observasi ke dalam sistem grid model. Weather Research And Forecasting (WRF) adalah salah satu model prediksi cuaca numeric. Salah satu pilihan untuk meningkatkan akurasi prediksi model WRF adalah dengan meningkatkan akurasi kondisi awal model dengan asimilasi data. Metode asimilasi data yang digunakan dalam penelitian ini adalah Three Dimensional Variation (3D-Var). Penelitian ini melakukan 3 skema percobaan. Pertama, model tanpa proses asimilasi data. Kedua, model asimilasi data observasi cuaca permukaan dan data cuaca udara atas yang kemudian disebut asimilasi data konvensional. Ketiga, model asimilasi data observasi cuaca permukaan, data cuaca udara atas, dan data observasi radiasi dari sensor AMSU-A yang kemudian disebut asimilasi data radiasiobs. Tujuan penelitian ini adalah mengidentifikasi pengaruh asimilasi data pada kondisi awal model dan hasil prediksi curah hujan. Kondisi awal model pada ketiga skema percobaan memiliki perbedaan nilai pada parameter suhu permukaan, tekanan permukaan, angin zonal dan angin meridional pada ketinggian 10 meter. Asimilasi data radiasiobs menghasilkan kondisi awal model yang lebih baik dari 2 skema percobaan yang lain, karena dapat meningkatan koefisien korelasi estimasi suhu permukaan sebesar 0.2 – 0.3 terhadap data observasi. Metode yang digunakan untuk verifikasi prediksi curah hujan secara spasial adalah Root Mean Square Error (RMSE), korelasi dan Forecast Skill Score. Forecast Skill Score merupakan metode untuk mengidentifikasi perubahan nilai RMSE setelah asimilasi data. Meskipun verifikasi prediksi curah hujan secara spasial menunjukkan kenaikan nilai RMSE untuk asimilasi data radiasiobs di wilayah laut, namun asimilasi data radiasiobs dapat memperbaiki distribusi intensitasi hujan lebat di wilayah darat dan mengurangi korelasi negatif prediksi model terhadap observasi curah hujan TRMM. Metode yang digunakan untuk verifikasi titik observasi di beberapa stasiun adalah diagram Taylor dan kurva Receiver-Operating Characteristic (ROC). Diagram Taylor merupakan diagram yang menggambarkan 3 parameter statistik: RMSE, korelasi, dan rasio standar deviasi antara model dan observasi. Kurva ROC merupakan kurva yang menggambarkan hubungan seberapa besar keakuratan model dalam memprediksi suatu kejadian dengan ketidakakuratan model dalam memprediksi suatu kejadian. Verifikasi titik observasi di beberapa stasiun meteorologi menunjukkan kenaikan nilai akumulasi curah hujan pada skema percobaan model asimilasi data konvensional dan asimilasi data radiasiobs terhadap model tanpa asimilasi. Nilai diagram Taylor berkisar dari 0 hingga 1, semakin mendekati nilai 1 menunjukkan model memiliki kemampuan yang lebih baik dalam memprediksi. Skema percobaan asimilasi data konvensional menunjukkan kenaikan nilai diagram Taylor hingga 0.09 dan skema percobaan asimilasi data radiasiobs menunjukkan kenaikan nilai diagram Taylor hingga 0.13 terhadap model tanpa asimilasi untuk nilai diagram Taylor. Verifikasi kurva ROC menunjukkan asimilasi data radiasiobs memiliki kemampuan prediksi curah hujan dengan threshold ≥ 1 mm, ≥ 5 mm, ≥ 10 mm, dan ≥ 20 mm lebih baik dari 2 skema percobaan yang lain. Hal itu semua menunjukkan model asimilasi data radiasiobs memberikan hasil prediksi curah hujan secara spasial dan titik lokasi lebih baik dari model tanpa proses asimilasi data dan model asimilasi data konvensional.
Keyword: asimilasi data, kondisi awal, prediksi curah hujan harian, WRF

Judul: Pemanfaatan Model Weather Research and Forecasting Environmental Modeling System (WRF-EMS) untuk Memprediksi Hujan
Abstrak: Numerical models can be used to predict the weather. Numerical model used in this study is a model of Weather Research and Forecasting Environmental Modeling System (WRF-EMS). The purpose of this study is to examine the output prediction of rain on 1 or two days ahead using the WRF-EMS model at 6 weather observations stations and the TRMM Data on 8 initials and boundary conditions, and to examine the output prediction of rain spatially using the WRFEMS model on the initial and boundary conditions that are different. In this study, the configuration of the standard scheme using the WRF-EMS model is maintained; however, the cumulus scheme is changed to the Betts-Miller-Janjic cumulus scheme. The accuracy of rainfall prediction results were assessed by comparing the model results with the rainfall synoptic data and TRMM. The accuracy of the model can also be seen in the range of the threat values score (TS) of rain predicted on the 1 and 2 days later. The result shows that the model predictions of rain using WRF-EMS is good enough to simulate a no-rain events on the island of Sumatra and Kalimantan. This is shown by the results of the rainfall prediction intensity and the data shown on TRMM. The WRF-EMS model can predicts rain in the morning, while the result of the prediction is over estimated in the afternoon and evening. The model can produce a fairly well prediction in the territorial waters of south Sumatra and Java Island. The WRFEMS model has a consistent high TS value at Citeko station and horizontal resolution of 27 and 3 km for the prediction of rain on the next couple of days. The TS value at Citeko weather observation station of the model with a horizontal resolution of 27 km for the prediction of 1 and 2 days in advance of each ranged from 0 – 0.33, and 0 – 0.30, while the TS value of the model with a horizontal resolution of 3 km for rainfall predictions 1 and 2 days in advance each ranged from 0.17 to 0.75 and 0.38 - 0.63. The increased of horizontal resolution from 27 km to 3 km can also increase the value of TS. This indicates that the model with a horizontal resolution of 3 km is more accurate for predicting rain compared to the model horizontal resolution of 27 km. The rainfall prediction was spatially over estimated when using the WRF-EMS Model, and this model is more sensitive in predicting rain at Citeko Station.
Keyword: Bogor Agricultural University (IPB), over-estimated, threat score, a model WRF-EMS, cumulus scheme Betts-Miller-Janjic

Judul: Case Study of Gallbladder Mucocele and Treatment Used In Small Animals
Abstrak: Gallbladder mucocele (GM) is defined as distention of the gallbladder caused by an inappropriate accumulation or deposition of high concentrations of bile. The purpose of this case study is to study GM conditions in small animals and to report the clinical sign and characteristics of GM through the sonogram interpretation and blood chemistry test evaluation, and studies related to the therapy given and other treatments recommended. A 14-year-old Toy Poodle dog has been diagnosed with severe GM and cholecystitis. No pain signs were shown during the physical examination as asymptomatic is a common characteristic in the early stage of biliary related diseases. In this study Abdominal ultrasonography interpretation and blood chemistry evaluation was conducted in 2021-2022 and analyzed as a secondary data source. Ultrasonography results showed presence of hyperechoic, immobile deposits in gallbladder accompanied by wall thickening and enlarged in size, followed by a significant increase in the enzyme alkaline phosphatase (ALP). This study has summarized mainly the diagnosis and treatments of GM in small animals and suitable alternatives treatments were recommended to encounter the GM conditions in small animals. The effectiveness of combined therapy shows the positive impact on the patient, the condition of GM has been under control.
Keyword: ultrasound, gallbladder, biliary sludge, abdominal ultrasonography