Numerical weather prediction
Data assimilation
Forecast verification
Wavelet and spectral analysis
Climate variability
9
Scopus Publications
66
Scholar Citations
5
Scholar h-index
2
Scholar i10-index
Scopus Publications
Variability analysis of effective teleconnection signals on Iran's climate ابوالفضل نیستانی Journal of the Earth and Space Physics, 2025 سیگنالهای دورپیوند باعث نوسان در سامانه اقلیم میشوند. در این زمینه شاخصهایی مانند الگوی دورپیوند شرق اطلس-غرب روسیه (EA-WR)، نوسان مدیترانه(MO)، نوسان اطلس شمالی (NAO)، نوسان شبه دوسالانه(QBO) و نوسان ENSO میتوانند بر وردایی کمیتهای جوی در منطقه ایران تأثیر قابلتوجه داشته باشند. در این تحقیق با استفاده از پالایههای رقومی سیگنالهای خامِ ماهانه در نوارهای بسامدی گوناگون جداسازی و موردمطالعه قرار گرفتهاند و با استفاده از تحلیل همبستگی، ارتباط خطی بین نوسانهای همبسامدِ شامل در این سیگنالها مورد آزمایش قرار گرفت. علاوهبر این، توان هر سیگنال بر اساس روش چگالی طیف توان در نوارهای بسامدی انتخاب شده استخراج شد و نوسانهای با بیشترین توان در هر سیگنال شناسایی شد. نتایج گویای همبستگی قابلتوجه و معنادار بین وردشِ موجود در سیگنالها در بعضی از مقیاسهای زمانی است. بهطور نمونه در مقیاس زمانی سالانه، مؤلفه متناظر در سیگنالهای EA-WR و NAO همبستگی مستقیم و بااهمیتی را در تأخیر زمانی صفر نشان میدهند (ضریب همبستگی: 564/0). علاوهبر این، توزیع توانِ وردش برای هر کدام از شاخصها در هر نوار بسامدی کاملاً منحصر به فرد است. بهطور خاص، بیش از %80 وردایی سیگنال ماهانه QBO در مقیاس زمانی 14 ماه تا 3 سال بهطور شبهچرخهای رخ میدهد. برای سیگنالهای EA-WR و NAO بخش زیادی از وردایی (%45-55%) در مقیاس 2-5 ماه روی میدهد که همبستگی ناچیزی بین این نوسانهای تصادفی مشاهده شد. اُفت و خیزهای بالابسامد در سیگنال MO غالب هستند و برای سیگنالSOI به استثنای مقیاس سالانه، باقی مقیاسهای زمانی دارای اهمیت قابل ملاحظهای در تعیین اقلیم منطقه ایران هستند.
Application of Machine and Deep Learning Models to Forecast Daily Precipitation Over the Western Part of Iran Abolfazl Neyestani, Farid Asgari, Vahid Asgari Meteorological Applications, 2025 Accurate forecasting of daily precipitation is critical for agricultural planning and effective water resource management. This study evaluates the capability of machine learning (ML) and deep learning (DL) models to predict daily precipitation using 40 years (1983–2023) of data from five synoptic stations in western Iran. Seven models were tested: Multiple Linear Regression (MLR), Polynomial Regression (PR), Support Vector Regression (SVR), Decision Tree (DT), Random Forest (RF), Extreme Gradient Boosting (XGBoost), and Q‐learning with Long Short‐Term Memory (DQN‐LSTM). Each model was trained on 10‐day input sequences to predict precipitation with a one‐day lead time, capturing short‐term temporal dependencies. Model performance, assessed using R 2 and RMSE, varied across stations, with DQN‐LSTM achieving the best results, explaining over 84% of daily precipitation variability and yielding the lowest RMSE values. Although PR, RF, and XGBoost provided reasonable accuracy, DT and SVR underperformed. However, it is important to note that the models that achieved the best RMSE and R 2 may not necessarily perform as well in predicting maximum precipitation values at stations. In general, all forecasting methods tend to underestimate the R95p index across stations. Nevertheless, the DQN‐LSTM model demonstrates superior overall skill in predicting extreme precipitation indices such as R95p and RX1day. However, for the frequency of extreme precipitation days, the predictions from PR, DT, RF, and XGBoost exhibit closer agreement with the observed values. These findings demonstrate the potential of hybrid DL models like DQN‐LSTM to improve both overall forecast accuracy and extreme event prediction, providing valuable insights for water management and disaster mitigation in regions with variable climates such as western Iran.
Short range precipitation forecasts evaluation of WRF model over IRAN Journal of the Earth and Space Physics, 2013
Planetary and tidal wave-type oscillations in the ionospheric sporadic E layers over Tehran region K. Karami, S. Ghader, A. A. Bidokhti, M. Joghataei, A. Neyestani, A. Mohammadabadi Journal of Geophysical Research Space Physics, 2012 [1] It is believed that in the lower ionosphere, particularly in the ionospheric sporadic E (Es) layers (90–130 km), the planetary and tidal wave-type oscillations in the ionized component indicate the planetary and tidal waves in the neutral atmosphere. In the present work, the presence of wave-type oscillations, including planetary and tidal waves in the ionospheric sporadic E layers over Tehran region is examined. Data measured by a digital ionosonde at the ionospheric station of the Institute of Geophysics, University of Tehran, from July 2006 to June 2007 are used to investigate seasonal variations of planetary and tidal waves activities. For the purpose of accurate comparison between different seasons, wavelet transform is applied to time series of foEs and h′Es, namely, the critical frequency and virtual height of Es layers, respectively. The results show that the sporadic E layers over Tehran region are strongly under the influence of upward propagation of waves from below. More specifically, among diverse range of periodicities in the sporadic E layers, we found that diurnal (24 hours) and semidiurnal (12 hours) oscillations in all seasons for both parameters. Moreover, terdiurnal (8 hours) tide-like variation is observed during spring and summer for foEs parameter and summer and winter for h′Es. Furthermore, the results show that diurnal tidal waves obtain their maximum activities during autumn and winter seasons, and their activities decrease during the late spring and summer. In addition, periods of about 2, 4, 6, 10, 14, and 16 days in our observation verifies the hypothesis of upward propagation of planetary waves from lower atmosphere to the ionosphere. Moreover, planetary waves have their maximum activities during equinox.
RECENT SCHOLAR PUBLICATIONS
Application of Machine and Deep Learning Models to Forecast Daily Precipitation Over the Western Part of Iran A Neyestani, F Asgari, V Asgari Meteorological Applications 32 (6), e70143 , 2025 2025 Citations: 1
The relationship between surface pressure and temperature fields over Iran: An approach based on multiple time-scales analysis of NCEP/NCAR reanalysis data A Neyestani Journal of the Earth and Space Physics 50 (3), 707-729 , 2024 2024
Multiple-scale Temporal Variability of Climatic Time Series in the Western Region of Iran A Neyestani Sustainable Earth Trends 3 (3), 27-44 , 2023 2023
Study of the interrelationship between global climate indices at different time scales. A Neyestani Iranian Journal of Geophysics (IJG) 17 (2) , 2023 2023
On the design and implementation of digital filters to process meteorological signals A Neyestani Journal of the Earth and Space Physics 48 (2), 361-380 , 2022 2022
Exploring the possible linkage between the precipitation and temperature over Iran and their association with the large-scale circulations: Cumulative spectral power and … A Neyestani, K Karami, S Gholami Atmospheric Research 274, 106187 , 2022 2022 Citations: 20
Operational convective-scale data assimilation over Iran: A comparison between WRF and HARMONIE-AROME A Neyestani, N Gustafsson, S Ghader, AR Mohebalhojeh, H Körnich Dynamics of Atmospheres and Oceans 95, 101242 , 2021 2021 Citations: 5
Inter-comparison of HARMONIE and WRF model simulations in convective-permitting scale over western area of Iran A Neyestani, S Ghader, N Gustafsson, A Mohebalhojeh Iranian Journal of Geophysics 12 (1), 1-18 , 2018 2018 Citations: 3
Application of data assimilation using WRF model to simulate precipitations caused by synoptic systems in the western regions of Iran A Neyestani, S Ghader, A Mohebalhojeh Iranian Journal of Geophysics 11 (1), 101-123 , 2017 2017 Citations: 1
Spectral Analysis of GCM Output using Digital Filtering Techniques F Taghavi, D Yazgi, A Neyestani American Meteorological Society Meeting Abstracts 95, 71 , 2015 2015
Short range precipitation forecasts evaluation of WRF model over IRAN F Taghavi, A Neyestani, S Ghader Journal of the EATH AND SPACE PHYSICS 39 (2), 145-170 , 2013 2013 Citations: 6
Evaluation of short-term precipitation forecasts of WRF numerical model in Iran in a one-month period F Taghavi, A Neyestani, S Qader Journal of Earth and Space Physics 39 (2) , 2013 2013 Citations: 2
Spatial and temporal study of precipitation characteristics over Iran M Moghbel, M Davoudi, A Neyestani, F Taghavi Geography and Environmental Planning 24 (351), 129-140 , 2013 2013 Citations: 1
Planetary and tidal wave‐type oscillations in the ionospheric sporadic E layers over Tehran region K Karami, S Ghader, AA Bidokhti, M Joghataei, A Neyestani, ... Journal of Geophysical Research: Space Physics 117 (A4) , 2012 2012 Citations: 15
Application of wavelet analysis to investigate precipitation variability at western regions of Iran F Taghavi, A Neyestani, H Mohammadi, S Rostami Jalilian Iranian Journal of Geophysics 5 (4), 13-30 , 2012 2012 Citations: 5
Identifying the changes in precipitation regime over Iran during recent decades M Moghbel, M Davoudi, A Neyestani, F Taghavi Nivar 35, 55-66 , 2011 2011 Citations: 7
MOST CITED SCHOLAR PUBLICATIONS
Exploring the possible linkage between the precipitation and temperature over Iran and their association with the large-scale circulations: Cumulative spectral power and … A Neyestani, K Karami, S Gholami Atmospheric Research 274, 106187 , 2022 2022 Citations: 20
Planetary and tidal wave‐type oscillations in the ionospheric sporadic E layers over Tehran region K Karami, S Ghader, AA Bidokhti, M Joghataei, A Neyestani, ... Journal of Geophysical Research: Space Physics 117 (A4) , 2012 2012 Citations: 15
Identifying the changes in precipitation regime over Iran during recent decades M Moghbel, M Davoudi, A Neyestani, F Taghavi Nivar 35, 55-66 , 2011 2011 Citations: 7
Short range precipitation forecasts evaluation of WRF model over IRAN F Taghavi, A Neyestani, S Ghader Journal of the EATH AND SPACE PHYSICS 39 (2), 145-170 , 2013 2013 Citations: 6
Operational convective-scale data assimilation over Iran: A comparison between WRF and HARMONIE-AROME A Neyestani, N Gustafsson, S Ghader, AR Mohebalhojeh, H Körnich Dynamics of Atmospheres and Oceans 95, 101242 , 2021 2021 Citations: 5
Application of wavelet analysis to investigate precipitation variability at western regions of Iran F Taghavi, A Neyestani, H Mohammadi, S Rostami Jalilian Iranian Journal of Geophysics 5 (4), 13-30 , 2012 2012 Citations: 5
Inter-comparison of HARMONIE and WRF model simulations in convective-permitting scale over western area of Iran A Neyestani, S Ghader, N Gustafsson, A Mohebalhojeh Iranian Journal of Geophysics 12 (1), 1-18 , 2018 2018 Citations: 3
Evaluation of short-term precipitation forecasts of WRF numerical model in Iran in a one-month period F Taghavi, A Neyestani, S Qader Journal of Earth and Space Physics 39 (2) , 2013 2013 Citations: 2
Application of Machine and Deep Learning Models to Forecast Daily Precipitation Over the Western Part of Iran A Neyestani, F Asgari, V Asgari Meteorological Applications 32 (6), e70143 , 2025 2025 Citations: 1
Application of data assimilation using WRF model to simulate precipitations caused by synoptic systems in the western regions of Iran A Neyestani, S Ghader, A Mohebalhojeh Iranian Journal of Geophysics 11 (1), 101-123 , 2017 2017 Citations: 1
Spatial and temporal study of precipitation characteristics over Iran M Moghbel, M Davoudi, A Neyestani, F Taghavi Geography and Environmental Planning 24 (351), 129-140 , 2013 2013 Citations: 1
The relationship between surface pressure and temperature fields over Iran: An approach based on multiple time-scales analysis of NCEP/NCAR reanalysis data A Neyestani Journal of the Earth and Space Physics 50 (3), 707-729 , 2024 2024
Multiple-scale Temporal Variability of Climatic Time Series in the Western Region of Iran A Neyestani Sustainable Earth Trends 3 (3), 27-44 , 2023 2023
Study of the interrelationship between global climate indices at different time scales. A Neyestani Iranian Journal of Geophysics (IJG) 17 (2) , 2023 2023
On the design and implementation of digital filters to process meteorological signals A Neyestani Journal of the Earth and Space Physics 48 (2), 361-380 , 2022 2022
Spectral Analysis of GCM Output using Digital Filtering Techniques F Taghavi, D Yazgi, A Neyestani American Meteorological Society Meeting Abstracts 95, 71 , 2015 2015
