Maize Drought Hazard in the Northeast Farming Region of China: Unprecedented Events in the Current Climate

2019 ◽  
Vol 58 (10) ◽  
pp. 2247-2258 ◽  
Author(s):  
Chris Kent ◽  
Edward Pope ◽  
Nick Dunstone ◽  
Adam A. Scaife ◽  
Zhan Tian ◽  
...  
Keyword(s):  
Large Scale ◽  
Agricultural Sector ◽  
Climate Model ◽  
Height Anomaly ◽  
Climate Services ◽  
Climate Conditions ◽  
Drought Hazard ◽  
Climate Exposure ◽  
Near Term ◽  
Climate Model Simulations

AbstractThe Northeast Farming Region (NFR) of China is a critically important area of maize cultivation accounting for ~30% of national production. It is predominantly rain fed, meaning that adverse climate conditions such as drought can significantly affect productivity. Forewarning of such events, to improve contingency planning, could therefore be highly beneficial to the agricultural sector. For this, an improved estimate of drought exposure, and the associated large-scale circulation patterns, is of critical importance. We address these important questions by employing a large ensemble of initialized climate model simulations. These simulations provide 80 times as many summers as the equivalent observational dataset and highlight several limitations of the recent observational record. For example, the chance of a drought greater in area than any current observed event is approximately 5% per year, suggesting the risk of a major drought is significantly underestimated if based solely on recent events. The combination of a weakened East Asian jet stream and intensified subpolar jet are found to be associated with severe NFR drought through enhanced upper-level convergence and anomalous descent, reducing moisture and suppressing precipitation. We identify a strong 500-hPa geopotential height anomaly dipole pattern as a useful metric to identify this mechanism for relevance to seasonal predictability. This work can inform policy planning and decision-making through an improved understanding of the near-term climate exposure and form the basis of new climate services.

Plan for the development of specialized climate forecasting in NEACC

2021 ◽  
pp. 101-111
Author(s):  
S.V. Emelina ◽  
◽  
V.M. Khan ◽  
Keyword(s):  
Large Scale ◽  
Regional Climate ◽  
Optimal Strategies ◽  
Economic Sectors ◽  
Climate Services ◽  
Climate Conditions ◽  
Climate Risks ◽  
The North ◽  
Weather And Climate ◽  
North Eurasia

The possibility of developing specialized seasonal forecasting within the framework of the North Eurasia Climate Centre is discussed. The purpose of these forecasts is to access the impacts of significant large-scale anomalies of meteorological elements on various economic sectors for the timely informing of government services and private businesses to select optimal strategies for planning preventive measures. A brief overview of the groups of climatic risks in the context of the impacts on the socio-economic sphere is given according to the Russian and foreign bibliographic sources. Examples of the activities of some Regional Climate Centers that produce forecast information with an assessment of possible impacts of weather and climate conditions at seasonal scales on various human activities are given. Keywords: climate services, regional climate forums, weather and climate risks, North Eurasia Climate Centre

Skill assessment of post-processing methods for ECMWF SEAS5 seasonal forecasts over Europe

2021 ◽  
Author(s):  
Alice Crespi ◽  
Marcello Petitta ◽  
Lucas Grigis ◽  
Paola Marson ◽  
Jean-Michel Soubeyroux ◽  
...  
Keyword(s):  
Large Scale ◽  
Production Management ◽  
Spatial Scales ◽  
Research Field ◽  
Skill Assessment ◽  
Post Processing ◽  
Seasonal Forecasts ◽  
Climate Services ◽  
Local Climate ◽  
Climate Conditions

<p>Seasonal forecasts provide information on climate conditions several months ahead and therefore they could represent a valuable support for decision making, warning systems as well as for the optimization of industry and energy sectors. However, forecast systems can be affected by systematic biases and have horizontal resolutions which are typically coarser than the spatial scales of the practical applications. For this reason, the reliability of forecasts needs to be carefully assessed before applying and interpreting them for specific applications. In addition, the use of post-processing approaches is recommended in order to improve the representativeness of the large-scale predictions of regional and local climate conditions. The development and evaluation downscaling and bias-correction procedures aiming at improving the skills of the forecasts and the quality of derived climate services is currently an open research field. In this context, we evaluated the skills of ECMWF SEAS5 forecasts of monthly mean temperature, total precipitation and wind speed over Europe and we assessed the skill improvements of calibrated predictions.</p><p>For the calibration, we combined a bilinear interpolation and a quantile mapping approach to obtain corrected monthly forecasts on a 0.25°x0.25° grid from the original 1°x1° values. The forecasts were corrected against the reference ERA5 reanalysis over the hindcast period 1993–2016. The processed forecasts were compared over the same domain and period with another calibrated set of ECMWF SEAS5 forecasts obtained by the ADAMONT statistical method.</p><p>The skill assessment was performed by means of both deterministic and probabilistic verification metrics evaluated over seasonal forecasted aggregations for the first lead time. Greater skills of the forecast systems in Europe were generally observed in spring and summer, especially for temperature, with a spatial distribution varying with the seasons. The calibration was proved to effectively correct the model biases for all variables, however the metrics not accounting for bias did not show significant improvements in most cases, and in some areas and seasons even small degradations in skills were observed.</p><p>The presented study supported the activities of the H2020 European project SECLI-FIRM on the improvement of the seasonal forecast applicability for energy production, management and assessment.</p>

scholarly journals Comparison and assessment of large-scale surface temperature in climate model simulations

2019 ◽  
Vol 5 (1) ◽  
pp. 67-85
Author(s):  
Raquel Barata ◽  
Raquel Prado ◽  
Bruno Sansó
Keyword(s):  
Surface Temperature ◽  
Seasonal Changes ◽  
Large Scale ◽  
Climate Model ◽  
Internal Variability ◽  
Temperature Variability ◽  
Data Driven ◽  
Model Simulations ◽  
Climate Model Simulations

Abstract. We present a data-driven approach to assess and compare the behavior of large-scale spatial averages of surface temperature in climate model simulations and in observational products. We rely on univariate and multivariate dynamic linear model (DLM) techniques to estimate both long-term and seasonal changes in temperature. The residuals from the DLM analyses capture the internal variability of the climate system and exhibit complex temporal autocorrelation structure. To characterize this internal variability, we explore the structure of these residuals using univariate and multivariate autoregressive (AR) models. As a proof of concept that can easily be extended to other climate models, we apply our approach to one particular climate model (MIROC5). Our results illustrate model versus data differences in both long-term and seasonal changes in temperature. Despite differences in the underlying factors contributing to variability, the different types of simulation yield very similar spectral estimates of internal temperature variability. In general, we find that there is no evidence that the MIROC5 model systematically underestimates the amplitude of observed surface temperature variability on multi-decadal timescales – a finding that has considerable relevance regarding efforts to identify anthropogenic “fingerprints” in observational surface temperature data. Our methodology and results present a novel approach to obtaining data-driven estimates of climate variability for purposes of model evaluation.

scholarly journals Constraining the temperature history of the past millennium using early instrumental observations

2012 ◽  
Vol 8 (3) ◽  
pp. 1653-1685 ◽  
Author(s):  
P. Brohan ◽  
R. Allan ◽  
E. Freeman ◽  
D. Wheeler ◽  
C. Wilkinson ◽  
...  
Keyword(s):  
Temperature Change ◽  
Large Scale ◽  
Climate Model ◽  
Ice Cores ◽  
East India Company ◽  
Temperature History ◽  
British Library ◽  
Model Simulations ◽  
Climate Model Simulations ◽  
Proxy Reconstructions

Abstract. The current assessment that twentieth-century global temperature change is unusual in the context of the last thousand years relies on estimates of temperature changes from natural proxies (tree-rings, ice-cores etc.) and climate model simulations. Confidence in such estimates is limited by difficulties in calibrating the proxies and systematic differences between proxy reconstructions and model simulations. As the difference between the estimates extends into the relatively recent period of the early nineteenth century it is possible to compare them with a reliable instrumental estimate of the temperature change over that period, provided that enough early thermometer observations, covering a wide enough expanse of the world, can be collected. One organisation which systematically made observations and collected the results was the English East-India Company (EEIC), and their archives have been preserved in the British Library. Inspection of those archives revealed 900 log-books of EEIC ships containing daily instrumental measurements of temperature and pressure, and subjective estimates of wind speed and direction, from voyages across the Atlantic and Indian Oceans between 1789 and 1834. Those records have been extracted and digitised, providing 273 000 new weather records offering an unprecedentedly detailed view of the weather and climate of the late eighteenth and early nineteenth centuries. The new thermometer observations demonstrate that the large-scale temperature response to the Tambora eruption and the 1809 eruption was modest (perhaps 0.5 °C). This provides a powerful out-of-sample validation for the proxy reconstructions – supporting their use for longer-term climate reconstructions. However, some of the climate model simulations in the CMIP5 ensemble show much larger volcanic effects than this – such simulations are unlikely to be accurate in this respect.

scholarly journals On the use of composite analyses to form physical hypotheses: An example from heat wave – SST associations

2016 ◽  
Vol 6 (1) ◽  
Author(s):  
Ghyslaine Boschat ◽  
Ian Simmonds ◽  
Ariaan Purich ◽  
Tim Cowan ◽  
Alexandre Bernardes Pezza
Keyword(s):  
Large Scale ◽  
Climate Model ◽  
Heat Waves ◽  
South Indian Ocean ◽  
South Indian ◽  
Sensitivity Tests ◽  
Pattern Correlation ◽  
Southwest Australia ◽  
Climate Model Simulations

Abstract This paper highlights some caveats in using composite analyses to form physical hypotheses on the associations between environmental variables. This is illustrated using a specific example, namely the apparent links between heat waves (HWs) and sea surface temperatures (SSTs). In this case study, a composite analysis is performed to show the large-scale and regional SST conditions observed during summer HWs in Perth, southwest Australia. Composite results initially point to the importance of the subtropical South Indian Ocean, where physically coherent SST dipole anomalies appear to form a necessary condition for HWs to develop across southwest Australia. However, sensitivity tests based on pattern correlation analyses indicate that the vast majority of days when the identified SST pattern appears are overwhelmingly not associated with observed HWs, which suggests that this is definitely not a sufficient condition for HW development. Very similar findings are obtained from the analyses of 15 coupled climate model simulations. The results presented here have pertinent implications and applications for other climate case studies, and highlight the importance of applying comprehensive statistical approaches before making physical inferences on apparent climate associations.

scholarly journals Impacts of Dynamical Downscaling on Circulation type Statistics: Potential added Value in the Euro-CORDEX Ensemble

2021 ◽  
Author(s):  
Julie Røste ◽  
Oskar A Landgren
Keyword(s):  
Large Scale ◽  
Climate Model ◽  
Dynamical Downscaling ◽  
Regional Climate ◽  
Circulation Type ◽  
Global Model ◽  
Added Value ◽  
Classification Methods ◽  
Circulation Types ◽  
Climate Model Simulations

Abstract Atmospheric circulation type classification methods were applied to an ensemble of 57 regional climate model simulations from Euro-CORDEX, their 11 boundary models from CMIP5 and the ERA5 reanalysis. We compared frequencies of the different circulation types in the simulations with ERA5 and found that the regional models add value especially in the summer season. We applied three different classification methods (the subjective Grosswettertypes and the two optimisation algorithms SANDRA and distributed k-means clustering) from the cost733class software and found that the results are not particularly sensitive to choice of circulation classification method. There are large differences between models. Simulations based on MIROC-MIROC5 and CNRM-CERFACS-CNRM-CM5 show an over-representation of easterly flow and an under-representation of westerly. The downscaled results retain the large-scale circulation from the global model most days, but especially the regional model IPSL-WRF381P changes the circulation more often, which increases the error relative to ERA5. Simulations based on ICHEC-EC-EARTH and MPI-M-MPI-ESM-LR show consistently smaller errors relative to ERA5 in all seasons. The ensemble spread is largest in the summer and smallest in the winter. Under the future RCP8.5 scenario, more than half of the ensemble shows an increase in frequency of north-easterly flow and decrease in the Central-Eastern European high and south-easterly flow. There is in general a strong agreement in the sign of the change between the regional simulations and the data from the corresponding global model.

scholarly journals Increased variability in Greenland Ice Sheet runoff from satellite observations

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Thomas Slater ◽  
Andrew Shepherd ◽  
Malcolm McMillan ◽  
Amber Leeson ◽  
Lin Gilbert ◽  
...  
Keyword(s):  
Ocean Circulation ◽  
Large Scale ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate Model ◽  
Regional Climate ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Model Simulations ◽  
Climate Model Simulations

AbstractRunoff from the Greenland Ice Sheet has increased over recent decades affecting global sea level, regional ocean circulation, and coastal marine ecosystems, and it now accounts for most of the contemporary mass imbalance. Estimates of runoff are typically derived from regional climate models because satellite records have been limited to assessments of melting extent. Here, we use CryoSat-2 satellite altimetry to produce direct measurements of Greenland’s runoff variability, based on seasonal changes in the ice sheet’s surface elevation. Between 2011 and 2020, Greenland’s ablation zone thinned on average by 1.4 ± 0.4 m each summer and thickened by 0.9 ± 0.4 m each winter. By adjusting for the steady-state divergence of ice, we estimate that runoff was 357 ± 58 Gt/yr on average – in close agreement with regional climate model simulations (root mean square difference of 47 to 60 Gt/yr). As well as being 21 % higher between 2011 and 2020 than over the preceding three decades, runoff is now also 60 % more variable from year-to-year as a consequence of large-scale fluctuations in atmospheric circulation. Because this variability is not captured in global climate model simulations, our satellite record of runoff should help to refine them and improve confidence in their projections.

scholarly journals Anthropogenic drying in central-southern Chile evidenced by long-term observations and climate model simulations

Elem Sci Anth ◽  
2018 ◽  
Vol 6 ◽  
Author(s):  
Juan P. Boisier ◽  
Camila Alvarez-Garreton ◽  
Raúl R. Cordero ◽  
Alessandro Damiani ◽  
Laura Gallardo ◽  
...  
Keyword(s):  
Large Scale ◽  
Climate Model ◽  
Stratospheric Ozone ◽  
Emission Rates ◽  
Southern Chile ◽  
Adaptation Measures ◽  
Model Simulations ◽  
Drying Trend ◽  
Climate Model Simulations

The socio-ecological sensitivity to water deficits makes Chile highly vulnerable to global change. New evidence of a multi-decadal drying trend and the impacts of a persistent drought that since 2010 has affected several regions of the country, reinforce the need for clear diagnoses of the hydro-climate changes in Chile. Based on the analysis of long-term records (50+ years) of precipitation and streamflow, we confirm a tendency toward a dryer condition in central-southern Chile (30–48°S). We describe the geographical and seasonal character of this trend, as well as the associated large-scale circulation patterns. When a large ensemble of climate model simulations is contrasted to observations, anthropogenic forcing appears as the leading factor of precipitation change. In addition to a drying trend driven by greenhouse gas forcing in all seasons, our results indicate that the Antarctic stratospheric ozone depletion has played a major role in the summer rainfall decline. Although average model results agree well with the drying trend’s seasonal character, the observed change magnitude is two to three times larger than that simulated, indicating a potential underestimation of future projections for this region. Under present-day carbon emission rates, the drying pathway in Chile will likely prevail during the next decades, although the summer signal should weaken as a result of the gradual ozone layer recovery. The trends and scenarios shown here pose substantial stress on Chilean society and its institutions, and call for urgent action regarding adaptation measures.

scholarly journals North American Winter Dipole: Observed and Simulated Changes in Circulations

Atmosphere ◽  
2019 ◽  
Vol 10 (12) ◽  
pp. 793 ◽  
Author(s):  
Yu-Tang Chien ◽  
S.-Y. Simon Wang ◽  
Yoshimitsu Chikamoto ◽  
Steve L. Voelker ◽  
Jonathan D. D. Meyer ◽  
...  
Keyword(s):  
North America ◽  
North American ◽  
Large Scale ◽  
Climate Model ◽  
Model Simulations ◽  
The North ◽  
Weather Events ◽  
The Pacific ◽  
Climate Model Simulations ◽  
Northwestern North America

In recent years, a pair of large-scale circulation patterns consisting of an anomalous ridge over northwestern North America and trough over northeastern North America was found to accompany extreme winter weather events such as the 2013–2015 California drought and eastern U.S. cold outbreaks. Referred to as the North American winter dipole (NAWD), previous studies have found both a marked natural variability and a warming-induced amplification trend in the NAWD. In this study, we utilized multiple global reanalysis datasets and existing climate model simulations to examine the variability of the winter planetary wave patterns over North America and to better understand how it is likely to change in the future. We compared between pre- and post-1980 periods to identify changes to the circulation variations based on empirical analysis. It was found that the leading pattern of the winter planetary waves has changed, from the Pacific–North America (PNA) mode to a spatially shifted mode such as NAWD. Further, the potential influence of global warming on NAWD was examined using multiple climate model simulations.

scholarly journals Heat Waves in Florida: Climatology, Trends, and Related Precipitation Events

2019 ◽  
Vol 58 (3) ◽  
pp. 447-466 ◽  
Author(s):  
Shealynn R. Cloutier-Bisbee ◽  
Ajay Raghavendra ◽  
Shawn M. Milrad
Keyword(s):  
Heat Wave ◽  
Large Scale ◽  
Climate Model ◽  
Heat Waves ◽  
Heavy Precipitation ◽  
Daily Maximum ◽  
Recent Climate ◽  
Climate Model Simulations ◽  
Southern Florida ◽  
Precipitation Events

AbstractHeat waves are increasing in frequency, duration, and intensity and are strongly linked to anthropogenic climate change. However, few studies have examined heat waves in Florida, despite an older population and increasingly urbanized land areas that make it particularly susceptible to heat impacts. Heavy precipitation events are also becoming more frequent and intense; recent climate model simulations showed that heavy precipitation in the three days after a Florida heat wave follow these trends, yet the underlying dynamic and thermodynamic mechanisms have not been investigated. In this study, a heat wave climatology and trend analysis are developed from 1950 to 2016 for seven major airports in Florida. Heat waves are defined based on the 95th percentile of daily maximum, minimum, and mean temperatures. Results show that heat waves exhibit statistically significant increases in frequency and duration at most stations, especially for mean and minimum temperature events. Frequency and duration increases are most prominent at Tallahassee, Tampa, Miami, and Key West. Heat waves in northern Florida are characterized by large-scale continental ridging, while heat waves in central and southern Florida are associated with a combination of a continental ridge and a westward extension of the Bermuda–Azores high. Heavy precipitation events that follow a heat wave are characterized by anomalously large ascent and moisture, as well as strong instability. Light precipitation events in northern Florida are characterized by advection of drier air from the continent, while over central and southern Florida, prolonged subsidence is the most important difference between heavy and light events.

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