scholarly journals The potential benefit of the use of seasonal forecast during the agricultural economic year 2019-2020 in Bulgaria

2021 ◽  
Vol 13 (30) ◽  
pp. 64-73
Author(s):  
Ilian Gospodinov ◽  
◽  
Valentin Kazandjiev ◽  
Veska Georgieva ◽  
◽  
...  
Keyword(s):  
General Circulation ◽  
General Circulation Models ◽  
Seasonal Forecast ◽  
Ensemble Prediction ◽  
Seasonal Temperature ◽  
Current Standard ◽  
Middle Latitudes ◽  
Chaotic Nature ◽  
Seasonal Time Scale ◽  
Prediction Systems

Seasonal forecasting gained ground in the last decades by building up knowledge on the processes staying behind the climate variability at the seasonal time scale, constructing ever more sophisticated general circulation models and ensemble prediction systems and thus enhancing forecast skill. The seasonal forecast is a climate forecast and is therefore probabilistic in nature. The predictability of the atmospheric circulation at the seasonal scale is limited in the middle latitudes, where Europe and Bulgaria are situated, by its chaotic nature. The current standard is to give forecast of the potential anomalies of the mean seasonal temperature and the seasonal amount of precipitation. The National Institute of Meteorology and Hydrology of Bulgaria has been issuing operationally seasonal forecast for the country since 2005. The goal of this work is to discuss the seasonal forecast for the last agricultural year 2019-2020. The year was characterized by its drought conditions especially in Eastern Bulgaria. This work would show the extent to which it was successfully predicted and how the seasonal forecast could have been used for decision making. The use of agrometeorological indices for the analysis of the skill of the seasonal forecast has been shown.

Filtering of Milankovitch Cycles by Earth's Geography

1991 ◽  
Vol 35 (2) ◽  
pp. 157-173 ◽  
Author(s):  
David A. Short ◽  
John G. Mengel ◽  
Thomas J. Crowley ◽  
William T. Hyde ◽  
Gerald R. North
Keyword(s):  
Time Series ◽  
General Circulation ◽  
Climate Model ◽  
Temperature Response ◽  
General Circulation Models ◽  
Complex Model ◽  
Milankovitch Cycles ◽  
Seasonal Temperature ◽  
Orbital Forcing ◽  
Model Response

AbstractEarth's land-sea distribution modifies the temperature response to orbitally induced perturbations of the seasonal insolation. We examine this modification in the frequency domain by generating 800,000-yr time series of maximum summer temperature in selected regions with a linear, two-dimensional, seasonal energy balance climate model. Previous studies have demonstrated that this model has a sensitivity comparable to general circulation models for the seasonal temperature response to orbital forcing on land. Although the observed response in the geologic record is sometimes significantly different than modeled here (differences attributable to model limitations and feedbacks involving the ocean-atmosphere-cryosphere system), there are several results of significance: (1) in mid-latitude land areas the orbital signal is translated linearly into a large (>10°C) seasonal temperature response; (2) although the modeled seasonal response to orbital forcing on Antarctica is 6°C, the annual mean temperature effect (<2°C) is only about one-fifth that inferred from the Vostok ice core, and primarily restricted to periods near 41,000 yr; (3) equatorial regions have the richest spectrum of temperature response, with a 3000-yr phase shift in the precession response, plus some power near periods of 10,000–12,000 yr, 41,000 yr, 100,000 yr, and 400,000 yr. Peaks at 10,000–12,000 yr and 100,000 and 400,000 yr result from the twice-yearly passage of the sun across the equator. The complex model response in equatorial regions has some resemblance to geologic time series from this region. The amplification of model response over equatorial land masses at the 100,000-yr period may explain some of the observed large variance in this band in geologic records, especially in pre-Pleistocene records from times of little or no global ice volume.

Late Cenozoic plateau uplift and climate change

1990 ◽  
Vol 81 (4) ◽  
pp. 301-314 ◽  
Author(s):  
William F. Ruddiman ◽  
John E. Kutzbach
Keyword(s):  
General Circulation ◽  
Large Scale ◽  
General Circulation Models ◽  
Lapse Rate ◽  
Regional Differentiation ◽  
Late Cenozoic ◽  
Local Responses ◽  
Climatic Trends ◽  
Middle Latitudes ◽  
Physical Impact

ABSTRACTSensitivity experiments with general circulation models show that uplift of plateau and mountain regions in Southern Asia and the American west during the late Cenozoic was an important factor in the evolution of Northern Hemisphere climate. The climatic trends simulated in the uplift experiments agree in direction with most trends observed in the geological record, including the tendencies toward greater regional differentiation of climate, and particularly the fragmentation into wetter and drier climatic patterns at middle latitudes. These climatic trends result from (1) increased orographic diversion of the mid-latitude westerlies, and (2) increased summer heating and winter cooling over the plateaus, which enhances seasonally reversing (monsoonal) changes in wind directions.Most previous hypotheses addressing the physical impact of orography on climate have focused on mountain ranges and have stressed relatively local responses such as upslope precipitation maxima, cooling of mountain crests due to lapse-rate effects on rising terrain, and lee-side rainshadow effects. In contrast, our results emphasise the importance of large-scale plateau orography. By redirecting the basic directions of wind flow both at surface and upper-tropospheric levels, these rising plateaux cause far-reaching climatic changes that extend across the continents as well as over the oceans.

scholarly journals A Comparative Analysis of Change in the First and Second Moment of the PDF of Seasonal Mean 200-mb Heights with ENSO SSTs

2009 ◽  
Vol 22 (6) ◽  
pp. 1412-1423 ◽  
Author(s):  
Bhaskar Jha ◽  
Arun Kumar
Keyword(s):  
Interannual Variability ◽  
General Circulation ◽  
General Circulation Models ◽  
Seasonal Forecast ◽  
Seasonal Predictability ◽  
Second Moment ◽  
Sst Variability ◽  
Atmospheric General Circulation Models ◽  
The Mean ◽  
Probability Density Function Pdf

Abstract Based on simulations from nine different atmospheric general circulation models (AGCMs), a comparative assessment of the influence of ENSO SST variability on the first and second moment of the probability density function (PDF) of 200-mb seasonal mean height is made. This comparison is quantified by regressing the interannual variability in the mean and the spread of the seasonal means against the Niño-3.4 SSTs. Based on the analysis of simulations from multiple AGCMs, it is concluded that the relative impact of interannual variability of SSTs is larger, and more systematic, on the mean of the PDF of 200-mb heights than on its spread. This result implies that seasonal predictability due to SSTs is predominantly a function of its influence on the seasonal mean. Further, for the practice of seasonal predictions, it might be pragmatic to assume that spread of seasonal means stays constant and that the seasonal forecast information resides entirely in the shift of the seasonal mean PDF.

scholarly journals The Role of Temperature Variability on Seasonal Electricity Demand in the Southern US

2021 ◽  
Vol 3 ◽  
Author(s):  
Dylan Cawthorne ◽  
Anderson Rodrigo de Queiroz ◽  
Hadi Eshraghi ◽  
Arumugam Sankarasubramanian ◽  
Joseph F. DeCarolis
Keyword(s):  
Time Scales ◽  
General Circulation ◽  
General Circulation Models ◽  
Electricity Demand ◽  
Temperature Variability ◽  
Seasonal Temperature ◽  
Power Demand ◽  
Southern Us ◽  
Demand Forecasts

The reliable and affordable supply of energy through interconnected systems represent a critical infrastructure challenge. Seasonal and interannual variability in climate variables—primarily precipitation and temperature—can increase the vulnerability of such systems during climate extremes. The objective of this study is to understand and quantify the role of temperature variability on electricity consumption over representative areas of the Southern United States. We consider two states, Tennessee and Texas, which represent different climate regimes and have limited electricity trade with adjacent regions. Results from regression tests indicate that regional population growth explains most of the variability in electricity demand at decadal time scales, whereas temperature explains 44–67% of the electricity demand variability at seasonal time scales. Seasonal temperature forecasts from general circulation models are also used to develop season-ahead power demand forecasts. Results suggest that the use of climate forecasts can potentially help to project future residential electricity demand at the monthly time scale.Capsule Summary: Seasonal temperature forecasts from GCMs can potentially help in predicting season-ahead residential power demand forecasts for states in the Southern US.

scholarly journals The benefit of seamless forecasts for hydrological predictions over Europe

2017 ◽  
Author(s):  
Fredrik Wetterhall ◽  
Francesca Di Giuseppe
Keyword(s):  
Seasonal Forecast ◽  
Ensemble Prediction ◽  
Prediction System ◽  
Seamless Integration ◽  
Ensemble Prediction System ◽  
Model Version ◽  
Extended Range ◽  
Forecasting System ◽  
Seasonal Time Scale ◽  
Awareness System

Abstract. Two different systems provide long range forecasts at ECMWF. On the sub-seasonal time scale, ECMWF issues an extended-range ensemble prediction system (ENS-ER) which runs a 46-day forecast integration issued twice weekly. On longer time scales the current seasonal forecasting system (SYS4) produces a 7-month outlook starting from the first of each month. SYS4 uses an older model version and has lower spatial and temporal resolution than ENS-ER. Given the substantial differences between the ENS-ER and the SYS4 configurations and the difficulties of creating a seamless integration, applications that rely on weather forcing as input such as the European Flood Awareness System (EFAS) often follow the route of the creation of two separate systems for different forecast horizons. This study evaluates the benefit of a seamless integration of the two systems for hydrological applications and shows that the benefit of the new seamless system when compared to the seasonal forecast can be attributed to (1) the use of a more recent model version in the sub-seasonal range (first 46 days) and (2) the much more frequent updates of the meteorological forecast.

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