MJO Propagation Processes and Mean Biases in the SubX and S2S Reforecasts

Kim, Hye‐Mi; Janiga, Matthew A.; Pegion, Kathy

doi:10.1029/2019jd031139

Cited by 58 publications

(68 citation statements)

References 60 publications

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“…Second, the MJO loses its amplitude very quickly in the models considered here, a common problem in forecast models (Kim et al, 2018;Kim et al, 2019;Vitart , 2017). It may be the case that the MJO signal is too weak to be modulated by the QBO.…”

Section: Summary and Discussionmentioning

confidence: 97%

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Insignificant QBO‐MJO Prediction Skill Relationship in the SubX and S2S Subseasonal Reforecasts

2019

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The impact of the stratospheric quasi‐biennial oscillation (QBO) on the prediction of the tropospheric Madden‐Julian oscillation (MJO) is evaluated in reforecasts from nine models participating in subseasonal prediction projects, including the Subseasonal Experiment (SubX) and Subseasonal to Seasonal (S2S) projects. When MJO prediction skill is analyzed for December to February, MJO prediction skill is higher in the easterly phase of the QBO than the westerly phase, consistent with previous studies. However, the relationship between QBO phase and MJO prediction skill is not statistically significant for most models. This insignificant QBO‐MJO skill relationship is further confirmed by comparing two subseasonal reforecast experiments with the Community Earth System Model v1 using both a high‐top (46‐level) and low‐top (30‐level) version of the Community Atmosphere Model v5. While there are clear differences in the forecasted QBO between the two model top configurations, a negligible change is shown in the MJO prediction, indicating that the QBO in this model may not directly control the MJO prediction and supporting the insignificant QBO‐MJO skill relationship found in SubX and S2S models.

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Section: Summary and Discussionmentioning

confidence: 97%

“…NCAR‐CESM1 reforecasts were carried out using the SubX protocol, but NCAR‐CESM1 does not produce real‐time forecasts. The MJO prediction skills in SubX reforecasts are comparable to those in the S2S project (Kim et al, ).…”

Section: Introductionmentioning

confidence: 99%

Insignificant QBO‐MJO Prediction Skill Relationship in the SubX and S2S Subseasonal Reforecasts

2019

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“…Forecasts less than a month, such as real-time information or near real-time, daily, weekly, and ten-day, are vital for agricultural decision-making. To date, many forecasting models struggle with predictivity below 10 days [36]. Gensini et al [37], found that forecast skills are higher between two-versus three-week lead-time.…”

Section: Introductionmentioning

confidence: 99%

Hydroclimatic Information Needs of Smallholder Farmers in the Lower Bengal Delta, Bangladesh

et al. 2020

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Hydroclimatic information services are vital for sustainable agricultural practices in deltas. They advance adaptation practices of farmers that lead to better economic benefit through increased yields, reduced production costs, and minimized crop damage. This research explores the hydroclimatic information needs of farmers by addressing (1) what kind of information is needed by the periurban delta farmers, and (2) whether information needs have any temporal dimension that changes with time following capacity building during coproduction of information services. Results reveal that the attributes of weather and water-related forecasts most affecting the farmers are rainfall, temperature, water, and soil salinity, along with extreme events such as cyclone and storm surges. The majority of the male farmers prefer one- to two-week lead-time forecasts for strategic and tactical decision-making; while female farmers prefer short-time forecasts with one-day to a week lead time that suggests the difference of purpose of the forecasts between male and female farmers. Contrarily, there is little preference for monthly, seasonal, and real-time forecasts. Information communication through a smartphone app is preferred mostly because of its easy accessibility and visualization. Farmers foresee that capacity building on acquiring hydroclimatic information is vital for agricultural decision-making. We conclude that a demand-driven coproduction of a hydroclimatic information service created through iterative interaction with and for farmers will enable the farmers to understand their information needs more explicitly.

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“…Unfortunately, modern developments garner little improvement. The Kim et al (2019) analyses of eight world-class GCMs feature too frequent light precipitation, underestimated heavy precipitation, and early onset of precipitation compared to observations.…”

Section: Introductionmentioning

confidence: 87%

Toward a Dynamical Foundation for Organized Convection Parameterization in GCMs

Moncrieff

2019

Geophysical Research Letters

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A dynamically based parameterization of organized moist convection in the form of multiscale coherent structures and slantwise layer overturning principles provides upscale heat and counter-gradient momentum transports distinct from diffusive down-gradient mixing by unorganized cumulus. Implementation of a minimalist version of this new parameterization in a state-of-the-art global climate model (GCM) improves the Madden-Julian Oscillation and convectively coupled waves and generates large-scale patterns of tropical precipitation consistent with Tropical Rainfall Measuring Mission satellite measurements. A question on the need to parameterize mesoscale convective organization to mitigate mean state biases is addressed. Plain Language SummaryA new paradigm adds mesoscale convective systems and tropical superclusters to contemporary GCMs where they are presently missing being neither parameterized nor resolved. Important effects of a prototype parameterization in a leading global climate model include large-scale patterns of tropical precipitation consistent with Tropical Rainfall Measuring Mission satellite measurements and improved convectively coupled tropical waves including the Madden-Julian Oscillation. These considerations address the Ahn et al. (2019) question on the need to parameterize mesoscale convective organization and mitigate mean state biases, which are affected differently by cumulus and organized convection parameterizations.

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MJO Propagation Processes and Mean Biases in the SubX and S2S Reforecasts

Cited by 58 publications

References 60 publications

Insignificant QBO‐MJO Prediction Skill Relationship in the SubX and S2S Subseasonal Reforecasts

Insignificant QBO‐MJO Prediction Skill Relationship in the SubX and S2S Subseasonal Reforecasts

Hydroclimatic Information Needs of Smallholder Farmers in the Lower Bengal Delta, Bangladesh

Toward a Dynamical Foundation for Organized Convection Parameterization in GCMs

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