Correction of monthly SST forecast in CFSv2 using the Local Dynamical Analog method

2021 ◽  
Author(s):  
Zhaolu Hou ◽  
Jianping Li ◽  
Bin Zuo
Keyword(s):  
Climate Model ◽  
Southern Oscillation ◽  
Correction Method ◽  
Forecast Skill ◽  
Forecast Errors ◽  
Model Forecast ◽  
Seasonal Forecasts ◽  
Probability Forecast ◽  
Central Pacific ◽  
Correction Scheme

AbstractNumerical seasonal forecasts in Earth science always contain forecast errors that cannot be eliminated by improving the ability of the numerical model. Therefore, correction of model forecast results is required. Analog-correction is an effective way to reduce model forecast errors, but the key question is how to locate analogs. In this paper, we updated the Local Dynamical Analog (LDA) algorithm to find analogs and depicted the process of model error correction as the LDA-correction scheme. The LDA-correction scheme was firstly applied to correct the operational seasonal forecasts of sea surface temperature (SST) over the period 1982–2018 from the state-of-the-art coupled climate model named NCEP Climate Forecast System version 2.The results demonstrated that the LDA-correction scheme improves forecast skill in many regions as measured by the correlation coefficient and Root Mean Square Error, especially over the extratropical eastern Pacific and tropical Pacific, where the model has high simulation ability. El Niño-Southern Oscillation (ENSO) as the focused physics process is also improved. The seasonal predictability barrier of ENSO is in remission and the forecast skill of Central Pacific ENSO also increases due to the LDA-correction method. The intensity of ENSO mature phases is improved. Meanwhile, the ensemble forecast results are corrected, which proves the positive influence from this LDA-correction scheme on the probability forecast of cold and warm events. Overall, the LDA-correction scheme, combining statistical and model dynamical information, is demonstrated to be readily integrable with other advanced operational models and has the capability to improve forecast results.

scholarly journals Prospects for Dynamical Prediction of Meteorological Drought

2012 ◽  
Vol 51 (7) ◽  
pp. 1238-1252 ◽  
Author(s):  
Xiao-Wei Quan ◽  
Martin P. Hoerling ◽  
Bradfield Lyon ◽  
Arun Kumar ◽  
Michael A. Bell ◽  
...  
Keyword(s):  
Great Plains ◽  
Climate Model ◽  
Southern Oscillation ◽  
Standardized Precipitation Index ◽  
Summer Rainfall ◽  
Northern Great Plains ◽  
Seasonal Forecasts ◽  
Wet Season ◽  
Antecedent Soil Moisture ◽  
Drought Prediction

AbstractThe prospects for U.S. seasonal drought prediction are assessed by diagnosing simulation and hindcast skill of drought indicators during 1982–2008. The 6-month standardized precipitation index is used as the primary drought indicator. The skill of unconditioned, persistence forecasts serves as the baseline against which the performance of dynamical methods is evaluated. Predictions conditioned on the state of global sea surface temperatures (SST) are assessed using atmospheric climate simulations conducted in which observed SSTs are specified. Predictions conditioned on the initial states of atmosphere, land surfaces, and oceans are next analyzed using coupled climate-model experiments. The persistence of the drought indicator yields considerable seasonal skill, with a region’s annual cycle of precipitation driving a strong seasonality in baseline skill. The unconditioned forecast skill for drought is greatest during a region’s climatological dry season and is least during a wet season. Dynamical models forced by observed global SSTs yield increased skill relative to this baseline, with improvements realized during the cold season over regions where precipitation is sensitive to El Niño–Southern Oscillation. Fully coupled initialized model hindcasts yield little additional skill relative to the uninitialized SST-forced simulations. In particular, neither of these dynamical seasonal forecasts materially increases summer skill for the drought indicator over the Great Plains, a consequence of small SST sensitivity of that region’s summer rainfall and the small impact of antecedent soil moisture conditions, on average, upon the summer rainfall. The fully initialized predictions for monthly forecasts appreciably improve on the seasonal skill, however, especially during winter and spring over the northern Great Plains.

scholarly journals Reducing Forecast Errors of a Regional Climate Model Using Adaptive Filters

2021 ◽  
Vol 11 (17) ◽  
pp. 8001
Author(s):  
Michel Pompeu Tcheou ◽  
Lisandro Lovisolo ◽  
Alexandre Ribeiro Freitas ◽  
Sin Chan Chou
Keyword(s):  
Regional Climate Model ◽  
Adaptive Filters ◽  
Climate Model ◽  
Learning Algorithm ◽  
Regional Climate ◽  
Absolute Error ◽  
Recursive Least Squares ◽  
Forecast Errors ◽  
Climate Variables ◽  
Seasonal Forecasts

In this work, the use of adaptive filters for reducing forecast errors produced by a Regional Climate Model (RCM) is investigated. Seasonal forecasts are compared against the reanalysis data provided by the National Centers for Environmental Prediction. The reanalysis is used to train adaptive filters based on the Recursive Least Squares algorithm in order to reduce the forecast error. The K-means unsupervised learning algorithm is used to obtain the number of filters to employ from the climate variables. The proposed approach is applied to some climate variables such as the meridional wind, zonal wind, and the geopotential height. The forecast is produced by the Eta RCM at 40-km resolution in a domain covering most of Brazil. Results show that the proposed approach is capable of reducing the forecast errors, according to evaluation metrics such as normalized mean square error, maximum absolute error, and maximum normalized absolute error, thus improving the seasonal climate forecasts.

scholarly journals The Canadian Seasonal to Interannual Prediction System Version 2 (CanSIPSv2)

2020 ◽  
Vol 35 (4) ◽  
pp. 1317-1343 ◽  
Author(s):  
Hai Lin ◽  
William J. Merryfield ◽  
Ryan Muncaster ◽  
Gregory C. Smith ◽  
Marko Markovic ◽  
...  
Keyword(s):  
Sea Ice ◽  
Climate Model ◽  
Southern Oscillation ◽  
Weather Prediction ◽  
Coupled Model ◽  
Seasonal Forecast ◽  
Forecast Skill ◽  
Boreal Winter ◽  
Prediction System ◽  
Sea Ice Concentration

AbstractThe second version of the Canadian Seasonal to Interannual Prediction System (CanSIPSv2) was implemented operationally at Environment and Climate Change Canada (ECCC) in July 2019. Like its predecessors, CanSIPSv2 applies a multimodel ensemble approach with two coupled atmosphere–ocean models, CanCM4i and GEM-NEMO. While CanCM4i is a climate model, which is upgraded from CanCM4 of the previous CanSIPSv1 with improved sea ice initialization, GEM-NEMO is a newly developed numerical weather prediction (NWP)-based global atmosphere–ocean coupled model. In this paper, CanSIPSv2 is introduced, and its performance is assessed based on the reforecast of 30 years from 1981 to 2010, with 10 ensemble members of 12-month integrations for each model. Ensemble seasonal forecast skill of 2-m air temperature, 500-hPa geopotential height, precipitation rate, sea surface temperature, and sea ice concentration is assessed. Verification is also performed for the Niño-3.4, the Pacific–North American pattern (PNA), the North Atlantic Oscillation (NAO), and the Madden–Julian oscillation (MJO) indices. It is found that CanSIPSv2 outperforms the previous CanSIPSv1 system in many aspects. Atmospheric teleconnections associated with the El Niño–Southern Oscillation (ENSO) are reasonably well captured by the two CanSIPSv2 models, and a large part of the seasonal forecast skill in boreal winter can be attributed to the ENSO impact. The two models are also able to simulate the Northern Hemisphere teleconnection associated with the tropical MJO, which likely provides another source of skill on the subseasonal to seasonal time scale.

Asymmetric impact of CP ENSO on the significant reduction of tropical cyclone genesis frequency over the WNP since the late 1990s

2020 ◽  
Author(s):  
Han-Kyoung Kim ◽  
Sang-Wook Yeh ◽  
Nam-Young Kang ◽  
Byung-Kwon Moon
Keyword(s):  
Tropical Cyclone ◽  
Climate Model ◽  
Model Simulation ◽  
Southern Oscillation ◽  
Underlying Mechanism ◽  
Tropical Cyclone Genesis ◽  
Central Pacific ◽  
Asymmetric Impact ◽  
Cyclone Genesis ◽  
Genesis Frequency

<p>Tropical cyclone (TC) genesis frequency over the western North Pacific (WNP) is reduced significantly since the late 1990s, coinciding with a Pacific decadal oscillation (PDO) phase change from positive to negative. In this study, the underlying mechanism for this reduction is investigated through analysis of asymmetric central Pacific (CP) El Niño-Southern Oscillation (ENSO) properties induced by the negative PDO phase. Results suggest that the significant reduction is caused by asymmetric CP ENSO properties, in which the CP La Niña is more frequent than the CP El Niño during negative PDO phases; furthermore, stronger CP La Niña occurs during a negative PDO phase than during a positive PDO phase. CP La Niña (El Niño) events generate an anticyclonic (cyclonic) Rossby wave response over the eastern WNP, leading to a significant decrease (increase) in eastern WNP TC genesis. Therefore, more frequent CP La Niña events and the less frequent CP El Niño events reduce the eastern WNP mean TC genesis frequency during a negative PDO phase. In addition, stronger CP La Niña events during a negative PDO phase reinforce the reduction in eastern WNP TC genesis. The dependency of CP ENSO properties on the PDO phase is confirmed using a long-term climate model simulation, which supports our observational results. </p><p>Acknowledgements: This work was supported by a National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT; No. 2019R1A2C1008549).</p>

scholarly journals Comparing Forecast Skill

2014 ◽  
Vol 142 (12) ◽  
pp. 4658-4678 ◽  
Author(s):  
Timothy DelSole ◽  
Michael K. Tippett
Keyword(s):  
Climate Model ◽  
Permutation Test ◽  
Statistical Significance ◽  
Forecast Skill ◽  
Sign Test ◽  
Rank Test ◽  
Basic Question ◽  
Seasonal Forecasts ◽  
The North ◽  
Signed Rank Test

Abstract A basic question in forecasting is whether one prediction system is more skillful than another. Some commonly used statistical significance tests cannot answer this question correctly if the skills are computed on a common period or using a common set of observations, because these tests do not account for correlations between sample skill estimates. Furthermore, the results of these tests are biased toward indicating no difference in skill, a fact that has important consequences for forecast improvement. This paper shows that the magnitude of bias is characterized by a few parameters such as sample size and correlation between forecasts and their errors, which, surprisingly, can be estimated from data. The bias is substantial for typical seasonal forecasts, implying that familiar tests may wrongly judge that differences in seasonal forecast skill are insignificant. Four tests that are appropriate for assessing differences in skill over a common period are reviewed. These tests are based on the sign test, the Wilcoxon signed-rank test, the Morgan–Granger–Newbold test, and a permutation test. These techniques are applied to ENSO hindcasts from the North American Multimodel Ensemble and reveal that the Climate Forecast System, version 2, and the Canadian Climate Model, version 3 (CanCM3), outperform other models in the sense that their squared error is less than that of other single models more frequently. It should be recognized that while certain models may be superior in a certain sense for a particular period and variable, combinations of forecasts are often significantly more skillful than a single model alone. In fact, the multimodel mean significantly outperforms all single models.

scholarly journals Synchronized spatial shifts of Hadley and Walker circulations

2020 ◽  
Author(s):  
Kyung-Sook Yun ◽  
Axel Timmermann ◽  
Malte F. Stuecker
Keyword(s):  
El Niño ◽  
Climate Model ◽  
El Nino ◽  
Southern Oscillation ◽  
Walker Circulation ◽  
Warm Pool ◽  
Central Pacific ◽  
Spatial Shift ◽  
Southern Central ◽  
Spatio Temporal

Abstract. The El Niño-Southern Oscillation (ENSO) influences the most extensive tropospheric circulation cells on our planet, known as Hadley and Walker circulations. Previous studies have largely focused on the effect of ENSO on the strength of these cells. However, what has remained uncertain is whether interannual sea surface temperature anomalies can also cause synchronized spatial shifts of these circulations. Here, by examining the spatio-temporal relationship between Hadley and Walker cells in observations and climate model experiments, we demonstrate that the seasonally evolving warm pool SST anomalies in the decay phase of an El Niño event generate a meridionally asymmetric Walker circulation response, which couples the zonal and meridional atmospheric overturning circulations. This process, which can be characterized as a phase-synchronized spatial shift in Walker and Hadley cells, is accompanied by cross-equatorial northwesterly low-level flow that diverges from an area of anomalous drying in the western North Pacific and converges towards a region with anomalous moistening in the southern central Pacific. Our results show that the SST-induced concurrent spatial shifts of the two circulations are climatically relevant as they can further amplify extratropical precipitation variability on interannual timescales.

scholarly journals CFSv2-based sub-seasonal precipitation and temperature forecast skill over the contiguous United States

2016 ◽  
Author(s):  
Di Tian ◽  
Eric F. Wood ◽  
Xing Yuan
Keyword(s):  
United States ◽  
Southern Oscillation ◽  
Forecast Skill ◽  
Precipitation Forecast ◽  
Climate Forecast ◽  
Seasonal Forecasts ◽  
Precipitation Indices ◽  
Temperature Indices ◽  
Precipitation And Temperature ◽  
Rainy Days

Abstract. Forecasts from global seasonal climate forecast models can be potentially exploited for sub-seasonal forecasts of precipitation and 2-m temperature. The probabilistic sub-seasonal forecast skill of ten precipitation and temperature indices is investigated using the 28-years’ hindcasts of the Climate Forecast System version 2 (CFSv2) over the contiguous United States (CONUS). The forecast skill is highly dependent on the forecast indices, regions, seasons, leads, and methods. Indices characterizing mean precipitation and temperature as well as measuring frequency or duration of precipitation and temperature extremes for 7-, 14-, and 30-day forecasts were skillful depending on seasons, regions, and forecast leads. Forecasts for 7- and 14-day temperature indices showed skill even at weeks 3 and 4, and generally more skillful than precipitation indices. Overall, temperature indices showed higher skill than precipitation indices over the entire CONUS region. While the forecast skill related to mean precipitation indices were low in summer over the CONUS, the number of rainy days, number of consecutive rainy days, and the number of consecutive dry days showed considerable high skill for the west coast region. The 30-day forecasts of precipitation and temperature indices calculated from the downscaled monthly CFSv2 forecasts are less skillful than those calculated from the daily CFSv2 forecasts, suggesting the potential usefulness of the CFSv2 daily forecasts for hydrological applications relative to the temporally disaggregated CFSv2 monthly forecasts. While the presence of active Madden-Julian Oscillation (MJO) events improves CFSv2 weekly mean precipitation forecast skill over major areas of CONUS, MJO or El Niño Southern Oscillation did not have same strong effects on weekly mean temperature forecasts.

Impact of ENSO on stratospheric ozone

2021 ◽  
Author(s):  
Samuel Benito-Barca ◽  
Natalia Calvo ◽  
Marta Abalos
Keyword(s):  
Climate Model ◽  
Southern Oscillation ◽  
Global Climate ◽  
Stratospheric Ozone ◽  
Boreal Winter ◽  
Residual Circulation ◽  
Central Pacific ◽  
Large Variability ◽  
Enso Events ◽  
Middle Latitudes

<p>El Niño‐Southern Oscillation (ENSO) is the main source of interannual variability in the global climate. Previous studies have shown ENSO has impacts on stratospheric ozone concentrations through changes in stratospheric circulation. The aim of this study is to extend these analysis by examining the anomalies in residual circulation and mixing associated with different El Niño flavors (Eastern Pacific (EP) and Central Pacific (CP)) and La Niña in boreal winter. For this purpose, we use four 60-year ensemble members of the Whole Atmospheric Community Climate Model version 4, reanalysis and satellite data.</p><p>Significant ozone anomalies are identified in both tropics and extratropics. In the northern high-latitudes (70-90N), significant positive ozone anomalies appear in the middle stratosphere in early winter during both CP and EP El Niño, which propagates downward during winter to the lower stratosphere only during EP-El Niño events. Anomalies during La Niña events are opposite to EP-El Niño. The analysis of the different terms in the continuity equation for zonal-mean ozone concentration reveals that Arctic ozone changes during ENSO events  are mainly driven by advection due to residual circulation, although contributions of mixing and chemistry are not negligible, especially in upper stratosphere.</p><p>The ENSO impact on total ozone column (TOC) is also investigated. During EP-El Niño, a significant reduction of TOC appears in the tropics and an increase in the middle latitudes. During La Niña the response is the opposite. The TOC response to CP El Niño events is not as robust. In the Northern Hemisphere polar region the TOC anomalies are not significant, probably due to its large variability associated with sudden stratospheric warmings in this region.</p>

scholarly journals Synchronized spatial shifts of Hadley and Walker circulations

2021 ◽  
Vol 12 (1) ◽  
pp. 121-132
Author(s):  
Kyung-Sook Yun ◽  
Axel Timmermann ◽  
Malte F. Stuecker
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
El Niño ◽  
Climate Model ◽  
El Nino ◽  
Southern Oscillation ◽  
Walker Circulation ◽  
Warm Pool ◽  
Sea Surface ◽  
Central Pacific

Abstract. The El Niño–Southern Oscillation (ENSO) influences the most extensive tropospheric circulation cells on our planet, known as Hadley and Walker circulations. Previous studies have largely focused on the effect of ENSO on the strength of these cells. However, what has remained uncertain is whether interannual sea surface temperature anomalies can also cause synchronized spatial shifts of these circulations. Here, by examining the spatiotemporal relationship between Hadley and Walker cells in observations and climate model experiments, we demonstrate that the seasonally evolving warm-pool sea surface temperature (SST) anomalies in the decay phase of an El Niño event generate a meridionally asymmetric Walker circulation response, which couples the zonal and meridional atmospheric overturning circulations. This process, which can be characterized as a phase-synchronized spatial shift in Walker and Hadley cells, is accompanied by cross-equatorial northwesterly low-level flow that diverges from an area of anomalous drying in the western North Pacific and converges towards a region with anomalous moistening in the southern central Pacific. Our results show that the SST-induced concurrent spatial shifts of the two circulations are climatically relevant as they can further amplify extratropical precipitation variability on interannual timescales.

scholarly journals Rethinking Indian monsoon rainfall prediction in the context of recent global warming

2015 ◽  
Vol 6 (1) ◽  
Author(s):  
Bin Wang ◽  
Baoqiang Xiang ◽  
Juan Li ◽  
Peter J. Webster ◽  
Madhavan N. Rajeevan ◽  
...  
Keyword(s):  
Global Warming ◽  
Monsoon Rainfall ◽  
Southern Oscillation ◽  
Summer Monsoon Rainfall ◽  
Forecast Skill ◽  
Central Pacific ◽  
Central Pacific El Niño ◽  
Rainfall Prediction ◽  
Operational Forecasts ◽  
North And South

Abstract Prediction of Indian summer monsoon rainfall (ISMR) is at the heart of tropical climate prediction. Despite enormous progress having been made in predicting ISMR since 1886, the operational forecasts during recent decades (1989–2012) have little skill. Here we show, with both dynamical and physical–empirical models, that this recent failure is largely due to the models’ inability to capture new predictability sources emerging during recent global warming, that is, the development of the central-Pacific El Nino-Southern Oscillation (CP–ENSO), the rapid deepening of the Asian Low and the strengthening of North and South Pacific Highs during boreal spring. A physical–empirical model that captures these new predictors can produce an independent forecast skill of 0.51 for 1989–2012 and a 92-year retrospective forecast skill of 0.64 for 1921–2012. The recent low skills of the dynamical models are attributed to deficiencies in capturing the developing CP–ENSO and anomalous Asian Low. The results reveal a considerable gap between ISMR prediction skill and predictability.

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