Judul: Inter – Relasi Keluaran Model NWP untuk Potensi Prakiraan Cuaca Jangka Pendek Tiga Wilayah Tipe Hujan di Indonesia.
Abstrak: Prakiraan cuaca jangka pendek di Indonesia saat ini memanfaatkan keluaran model NWP. Model NWP merupakan prediksi cuaca harian yang rutin dengan komputer menggunakan persamaan matematik. Banyak orang mengakui bahwa sistem cuaca skala meso belum disimulasikan secara memuaskan oleh model NWP. Tujuan dari penelitian ini yaitu untuk mempelajari dan memahami teknik prediksi cuaca jangka pendek dan membuat suatu analisis statistik sebagai upaya pemanfaatan data output model NWP untuk prediksi cuaca. Parameter cuaca yang akan dibahas dan diprediksi dalam penelitian ini yaitu CH, T max, T min, RH max dan RH min dengan daerah kajian adalah tiga wilayah tipe hujan di Indonesia yaitu Padang, Jakarta dan Ambon. Kota Ambon merupakan kota yang paling baik untuk pemaanfaatan model NWP dalam penelitian ini dilihat dari plot nilai output model dengan hasil observasi lapangan yang berpola sama. Nilai output model NWP (prediksi) dengan nilai observasi lapangan tidak sama atau terdapat error antara keduanya, untuk itu dicari faktor koreksi untuk meminimalisasi nilai error tersebut. Untuk model hujan, nilai RMSE berkurang hingga 8.9 % sementara nilai MAE berkurang hingga 25 % karena menggunakan faktor koreksi. Untuk model suhu nilai RMSE berkurang hingga 80 % sementara nilai MAE berkurang hingga 84 % setelah menggunakan faktor koreksi. Sedangkan untuk model RH nilai RMSE berkurang hingga 81% sementara nilai MAE berkurang hingga 85% setelah menggunakan faktor koreksi. Hasil ini menunjukkan bahwa penggunaan faktor koreksi lebih berpengaruh nyata pada model regresi suhu (Tmax dan Tmin) dan RH (RHmax dan RH min) daripada model regresi CH. Kata kunci: Numerical Weather Prediction (NWP), prakiraan cuaca jangka pendek, pola curah hujan, faktor koreksi
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Judul: Potensi pemanfaatan keluaran model nwp untuk prediksi cuaca jangka pendek (Studi kasus: Pontianak, Pekanbaru, Semarang, Surabaya, dan Palu)
Abstrak: Numerical weather prediction (NWP) is an operational daily weather forecasting using mathematical equations by super-computer. The skill of NWP has improved significantly since it was first generated fourty years ago. The urgent needs for daily weather forecasting in Indonesia has led to the utilization of NWP model outputs to be incorporated into the forecasting scheme. NWP provides the basic guidance for weather forecasting beyond the first few hours. Unfortunately, spatial resolution of NWP model is still too rough to describe local conditions. Model output statistics (MOS) technique may be used to reduce error and increase accuracy of NWP model ouputs. The objective of this study includes the selection of the best combination of atmospheric predictors for daily precipitation, relative humidity, maximum temperature, and minimum temperature in five locations, namely, Pontianak, Pekanbaru, Semarang, Surabaya, and Palu which characterized three dominant rainfall regions in Indonesia, for the wet and dry seasons. The subsequent objective is to identify locations where NWP model outputs resemble observational data. Model outputs patterns are compared with observational data to analyze consistency, and whenever necessary some forms of correction factor is applied. The results indicate that humidity at the surface (at z=2m) and at mid-tropospheric levels (rh0 and rh8), and pressure vertical velocity at mid-tropospheric levels (vv7 and vv5) are the relevant variables for daily precipitation in all of the locations and all seasons analyzed. The most potential location to utilize NWP model is Palu. In Palu, surface air temperature (T0) and surface dew point temperature (DP0) are the relevant variables for relative humidity; humidity at the surface (rh0) is the relevant variable for maximum temperature; while surface dew point temperature (DP0) is the relevant variable for minimum temperature. Closeness of model outputs with observational data is inferred using error indicators, namely, Root Mean Square Error (RMSE) and Mean Absolute Error (MAE).
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Judul: Sarcosporidiasis in slaughter animals
Abstrak: Sarcocystis which belong to the generally occuring parasites for they are found almost all over the countries of the world. Infection of Sarcocystis usually throught inges- tion of feces or flesh of infected animals. The pathogenesis of Sarcosporidiasis is considered as benign but when the Sarcocystis die in a host, sarcocystin or sarcosporidin is liberated thereby which lead to condemnation of meat in the abattoir. Besides condemnation of meat, Sarcocystis also causes: loss of appetite, anemia, lameness, weakness in the lion, diarrhea, fever, pyrexia, paralysis, emaciation, neuro logical disturbances, etc. " Amprolium "at the rate of 100 mg/Kg body weight per day has been practiced for prevention or to minimize Sarco- sporidiasis. Treatment must be started during incubation period. Shedding of Sarcocystis sporocysts in the feces of carnivores is the key factor in the spread of Sarcocystis infection. Therefore, control efforts must be based primarily on measures designed to break the cycle of Sarcocystis.
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