Ảnh hưởng của Sự Tham Gia Ngẫu Nhiên trong Thành Phần Đối Lưu Sâu NCAR CAM Đến Mô Phỏng Mùa Mưa Hè Nam Á

Springer Science and Business Media LLC - Tập 57 - Trang 3365-3384 - 2021
Raju Pathak1, Sandeep Sahany1,2, Saroj Kanta Mishra1
1Centre for Atmospheric Sciences, Indian Institute of Technology, Delhi, Hauz Khas, New Delhi, India
2Centre for Climate Research Singapore, Singapore, Singapore

Tóm tắt

Các mô phỏng mô hình rất nhạy cảm với cách thức diễn giải quá trình trộn khí quyển hoặc sự tham gia trong các phép phân loại đối lưu sâu được sử dụng trong các thành phần khí quyển của chúng. Trong bài báo này, chúng tôi đã thực hiện sự tham gia ngẫu nhiên trong sơ đồ đối lưu sâu của NCAR CAM5 và phân tích những cải tiến trong mô phỏng mô hình, tập trung vào Mùa Mưa Hè Nam Á (SASM), so với cách diễn giải tham gia xác định trong phiên bản mặc định của mô hình. Các mô phỏng sử dụng sự tham gia ngẫu nhiên (StochCAM5) đã vượt trội hơn so với các mô phỏng mô hình mặc định (DefCAM5), như suy ra từ nhiều chỉ số liên quan đến SASM. StochCAM5 đã giảm thiểu đáng kể một số sai lệch kéo dài của SASM mà DefCAM5 gặp phải, như mô hình hóa lượng mưa và độ lớn trên Biển Ả Rập và Ấn Độ Dương phía tây xích đạo, việc rút lui sớm của mùa mưa, cũng như sự ước lượng cao quá về tần suất mưa nhẹ và sự ước lượng thấp về tần suất mưa lớn đến cực đoan. Các đặc điểm động lực và nhiệt động lực liên quan đến SASM, như Gió Somali, gió tây tầng thấp, và độ dốc nhiệt độ trong khí quyển (MTTG), cũng được cải thiện trong StochCAM5. Hơn nữa, việc mô phỏng dao động nội mùa của mùa mưa (MISO), Dao động Madden Julian (MJO), và sóng Kelvin xích đạo cũng được cải thiện trong StochCAM5. Nhiều biến khí hậu thiết yếu, như lực hấp dẫn mây ngắn và dài, che phủ mây, độ ẩm tương đối và độ ẩm tuyệt đối, và nước có thể ngưng tụ cho thấy sự cải thiện đáng kể trong StochCAM5.

Từ khóa

#mô phỏng mô hình #đối lưu sâu #Mùa Mưa Hè Nam Á #sự tham gia ngẫu nhiên #sai lệch khí hậu

Tài liệu tham khảo

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