scholarly journals Long-range prediction of monsoon onset over Kerala

MAUSAM ◽  
2022 ◽  
Vol 46 (3) ◽  
pp. 287-290
Author(s):  
M. RAJEEVAN ◽  
D. P. DUBEY
Keyword(s):  
Surface Temperature ◽  
Snow Cover ◽  
Long Range ◽  
Late Onset ◽  
Central India ◽  
Monsoon Onset ◽  
Onset Date ◽  
Eurasian Snow Cover ◽  
Eurasian Snow ◽  
Long Range Prediction

ABSTRACT. Using the data of 33 years ( 1961-1993) the effect of the intensity of heat low over central India during the Month of April and Winter (December to February) Eurasian snow cover on interannual variation of monsoon date over Kerala were examined. Composite mean surface temperature over central India during the month of April was higher during early onset years by 3.5° C. April mean surface temperature index (MST) and Winter (December to February) Eurasian snow cover (WSC) are significantly correlated with Monsoon onset dates al 1% and 5% significant levels respectively. Lower surface temperature and excessive snow cover indicate a late onset. A regression equation was developed for long range prediction of onset date over Kerala using MST and WSC as independent variables. The root mean square error (RMSE) of the relationship was found to be 4.6 days. The model was tested using independent data of five years and was found performing well. Contingency tables were developed between the pairs MOD and WSC and MOD and MST. The tables can be used for probability forecasts of early and late onset years.  

scholarly journals A Skillful Prediction Model for Winter NAO Based on Atlantic Sea Surface Temperature and Eurasian Snow Cover

2015 ◽  
Vol 30 (1) ◽  
pp. 197-205 ◽  
Author(s):  
Baoqiang Tian ◽  
Ke Fan
Keyword(s):  
Prediction Model ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Snow Cover ◽  
Correlation Coefficient ◽  
Cross Validation ◽  
Sea Surface ◽  
Interdecadal Variability ◽  
Eurasian Snow Cover ◽  
Eurasian Snow

Abstract A new statistical forecast scheme, referred to as scheme 1, is developed using observed autumn Atlantic sea surface temperature (SST) and Eurasian snow cover in the preceding autumn to predict the upcoming winter North Atlantic Oscillation (NAO) using the year-to-year increment prediction approach (i.e., DY approach). Two predictors for the year-to-year increment are identified that are available in the preceding autumn. Cross-validation tests for the period 1950–2011 and independent hindcasts for the period 1990–2011 are performed to validate the prediction ability of the proposed technique. The cross-validation test results for 1950–2011 reveal a high correlation coefficient of 0.52 (0.58) between the predicted and observed NAO indices (DY of the NAO). The model also successfully predicts the independent hindcasts for the period 1990–2011 with a correlation coefficient of 0.55 (0.74). In addition, scheme 0 (i.e., anomaly approach) is established using the SST and snow cover anomalies during the preceding autumn. Compared with scheme 0, this new prediction model has higher predictive skill in reproducing the interdecadal variability of NAO. Therefore, this study provides an effective climate prediction scheme for the interannual and interdecadal variability of NAO in boreal winter.

scholarly journals EMPIRICAL ORTHOGONAL FUNCTIONS ASSOCIATED WITH PARAMETERS USED IN LONG RANGE FORECASTING OF INDIAN SUMMER MONSOON

MAUSAM ◽  
2021 ◽  
Vol 44 (1) ◽  
pp. 29-34
Author(s):  
H. N. SRIVASTAVA ◽  
S. S. SINGH
Keyword(s):  
Snow Cover ◽  
Long Range ◽  
Northern Hemisphere ◽  
Summer Monsoon ◽  
Indian Summer Monsoon ◽  
Monsoon Onset ◽  
Empirical Orthogonal Functions ◽  
Onset Date ◽  
Orthogonal Functions ◽  
Summer Monsoon Onset

EEmpirical Orthogonal Functions (EOF),. associated with the; parameters for long range forecasting of Indian summer monsoon onset and seasonal. rainfall have been discussed. It was found that the percentage of variance explained was 77 and 67 respectively through the first four EOF. The highest correlation coefficient with the onset date was found for the first function which showed the maximum influence of Cobar (Australia) and Darwin (Australia) zonal winds on the onset date. It was interesting to note that for rainfall prediction predominant effect on the first EOF was noticed of 50 hPa ridge over northern hemisphere, Eurasian snow cover, Argentina pressure (negatively correlated) and 500 hpa ridge, 10 hPa Balboa wind, north, central India and east coast  minimum temperatures, and northern hemisphere temperature. However, the Influence of EI-Nino, equatorial pressure and Darwin pressure (Including Tahiti minus Darwin) and Himalayan snow cover was almost negligible. The eigen index for the onset date suggests a complementary method for its application In long range prediction of summer monsoon onset date.

scholarly journals Variability of the Cold Season Climate in Central Asia. Part II: Hydroclimatic Predictability

2019 ◽  
Vol 32 (18) ◽  
pp. 6015-6033 ◽  
Author(s):  
Lars Gerlitz ◽  
Eva Steirou ◽  
Christoph Schneider ◽  
Vincent Moron ◽  
Sergiy Vorogushyn ◽  
...  
Keyword(s):  
Central Asia ◽  
Snow Cover ◽  
Large Scale ◽  
Cold Season ◽  
Hadley Cell ◽  
Quasi Biennial Oscillation ◽  
Large Variability ◽  
Forecast Performance ◽  
Eurasian Snow Cover ◽  
Eurasian Snow

Abstract Central Asia (CA) is subjected to a large variability of precipitation. This study presents a statistical model, relating precipitation anomalies in three subregions of CA in the cold season (November–March) with various predictors in the preceding October. Promising forecast skill is achieved for two subregions covering 1) Uzbekistan, Turkmenistan, Kyrgyzstan, Tajikistan, and southern Kazakhstan and 2) Iran, Afghanistan, and Pakistan. ENSO in October is identified as the major predictor. Eurasian snow cover and the quasi-biennial oscillation further improve the forecast performance. To understand the physical mechanisms, an analysis of teleconnections between these predictors and the wintertime circulation over CA is conducted. The correlation analysis of predictors and large-scale circulation indices suggests a seasonal persistence of tropical circulation modes and a dynamical forcing of the westerly circulation by snow cover variations over Eurasia. An EOF analysis of pressure and humidity patterns allows separating the circulation variability over CA into westerly and tropical modes and confirms that the identified predictors affect the respective circulation characteristics. Based on the previously established weather type classification for CA, the predictors are investigated with regard to their effect on the regional circulation. The results suggest a modification of the Hadley cell due to ENSO variations, with enhanced moisture supply from the Arabian Gulf during El Niño. They further indicate an influence of Eurasian snow cover on the wintertime Arctic Oscillation (AO) and Northern Hemispheric Rossby wave tracks. Positive anomalies favor weather types associated with dry conditions, while negative anomalies promote the formation of a quasi-stationary trough over CA, which typically occurs during positive AO conditions.

Sign in / Sign up

Export Citation Format

Share Document