Multireanalysis Comparison of Variability in Column Water Vapor and Its Analysis Increment Associated with the Madden–Julian Oscillation

2015 ◽  
Vol 28 (2) ◽  
pp. 793-808 ◽  
Author(s):  
Satoru Yokoi
Keyword(s):  
Water Vapor ◽  
Forecast Model ◽  
Precipitation Anomaly ◽  
Boreal Winter ◽  
Madden Julian Oscillation ◽  
Radiative Feedback ◽  
Feedback Strength ◽  
Advection Term ◽  
Forecast Models ◽  
Cloud Radiative Feedback

Abstract This study conducts a multireanalysis comparison of variability in column water vapor (CWV) represented in three reanalysis products [Japanese 55-year Reanalysis Project (JRA-55), JRA-25, and ECMWF Interim Re-Analysis (ERA-Interim)] associated with the Madden–Julian oscillation (MJO) in boreal winter, with emphasis on CWV tendency simulated by forecast models and analysis increment calculated by data assimilation systems. Analyses of these variables show that, while the JRA-55 forecast model is able to simulate eastward propagation of the CWV anomaly, this model tends to weaken its amplitude. The multireanalysis comparison of the analysis increment further reveals that this weakening bias is related to excessively weak cloud radiative feedback represented by the model. This bias in the feedback strength makes anomalous moisture supply by the vertical advection term in the CWV budget equation too insensitive to precipitation anomaly, resulting in reduction of the amplitude of CWV anomaly. ERA-Interim has a nearly opposite feature: the forecast model represents excessively strong feedback. These results imply the necessity of accurate representation of the cloud radiative feedback strength for a short-term MJO forecast and may be evidence to support the argument that this feedback is essential for the existence of MJO. Furthermore, this study demonstrates that the multireanalysis comparison of the analysis increment will provide useful information for examining model biases and potentially for estimating parameters that are difficult to estimate from observational data, such as gross moist stability.

scholarly journals Sensitivities of the Madden–Julian oscillation forecasts to configurations of physics in the ECMWF global model

2021 ◽  
Vol 21 (6) ◽  
pp. 4759-4778
Author(s):  
Jun-Ichi Yano ◽  
Nils P. Wedi
Keyword(s):  
Forecast Model ◽  
Global Model ◽  
Madden Julian Oscillation ◽  
Forecast Performance ◽  
Theoretical Investigations ◽  
Forecast Models ◽  
Forecasting System ◽  
The Rich ◽  
The Tropics ◽  
Original Motivation

Abstract. The sensitivities of the Madden–Julian oscillation (MJO) forecasts to various different configurations of the parameterized physics are examined with the global model of ECMWF's Integrated Forecasting System (IFS). The motivation for the study was to simulate the MJO as a nonlinear free wave under active interactions with higher-latitude Rossby waves. To emulate free dynamics in the IFS, various momentum-dissipation terms (“friction”) as well as diabatic heating were selectively turned off over the tropics for the range of the latitudes from 20∘ S to 20∘ N. The reduction of friction sometimes improves the MJO forecasts, although without any systematic tendency. Contrary to the original motivation, emulating free dynamics with an operational forecast model turned out to be rather difficult, because forecast performance sensitively depends on the specific type of friction turned off. The result suggests the need for theoretical investigations that much more closely follow the actual formulations of model physics: a naive approach with a dichotomy of with or without friction simply fails to elucidate the rich behaviour of complex operational models. The paper further exposes the importance of physical processes other than convection for simulating the MJO in global forecast models.

Assessing the Skill of an All-Season Statistical Forecast Model for the Madden–Julian Oscillation

2008 ◽  
Vol 136 (6) ◽  
pp. 1940-1956 ◽  
Author(s):  
Xianan Jiang ◽  
Duane E. Waliser ◽  
Matthew C. Wheeler ◽  
Charles Jones ◽  
Myong-In Lee ◽  
...  
Keyword(s):  
Real Time ◽  
Longwave Radiation ◽  
Forecast Model ◽  
Boreal Winter ◽  
Madden Julian Oscillation ◽  
Predictive Skill ◽  
Regression Parameters ◽  
Extended Range ◽  
Forecast Time

Abstract Motivated by an attempt to augment dynamical models in predicting the Madden–Julian oscillation (MJO), and to provide a realistic benchmark to those models, the predictive skill of a multivariate lag-regression statistical model has been comprehensively explored in the present study. The predictors of the benchmark model are the projection time series of the leading pair of EOFs of the combined fields of equatorially averaged outgoing longwave radiation (OLR) and zonal winds at 850 and 200 hPa, derived using the approach of Wheeler and Hendon. These multivariate EOFs serve as an effective filter for the MJO without the need for bandpass filtering, making the statistical forecast scheme feasible for the real-time use. Another advantage of this empirical approach lies in the consideration of the seasonal dependence of the regression parameters, making it applicable for forecasts all year-round. The forecast model exhibits useful extended-range skill for a real-time MJO forecast. Predictions with a correlation skill of greater than 0.3 (0.5) between predicted and observed unfiltered (EOF filtered) fields still can be detected over some regions at a lead time of 15 days, especially for boreal winter forecasts. This predictive skill is increased significantly when there are strong MJO signals at the initial forecast time. The analysis also shows that predictive skill for the upper-tropospheric winds is relatively higher than for the low-level winds and convection signals. Finally, the capability of this empirical model in predicting the MJO is further demonstrated by a case study of a real-time “hindcast” during the 2003/04 winter. Predictive skill demonstrated in this study provides an estimate of the predictability of the MJO and a benchmark for the dynamical extended-range models.

Scanning 10-W Water Vapor DIAL for the Investigation of Atmospheric Turbulence and Land-Atmosphere Feedback

2021 ◽  
Author(s):  
Andreas Behrendt ◽  
Florian Spaeth ◽  
Volker Wulfmeyer
Keyword(s):  
Heat Flux ◽  
Water Vapor ◽  
Latent Heat ◽  
Atmospheric Turbulence ◽  
Latent Heat Flux ◽  
Climate Models ◽  
Weather Forecast ◽  
Surface Characteristics ◽  
Scanning System ◽  
Forecast Models

<p>We will present recent measurements made with the water vapor differential absorption lidar (DIAL) of University of Hohenheim (UHOH). This scanning system has been developed in recent years for the investigation of atmospheric turbulence and land-atmosphere feedback processes.</p><p>The lidar is housed in a mobile trailer and participated in recent years in a number of national and international field campaigns. We will present examples of vertical pointing and scanning measurements, especially close to the canopy. The water vapor gradients in the surface layer are related to the latent heat flux. Thus, with such low-elevation scans, the latent heat flux distribution over different surface characteristics can be monitored, which is important to verify and improve both numerical weather forecast models and climate models.</p><p>The transmitter of the UHOH DIAL consists of a diode-pumped Nd:YAG laser which pumps a Ti:sapphire laser. The output power of this laser is up to 10 W. Two injection seeders are used to switch pulse-to-pulse between the online and offline signals. These signals are then either directly sent into the atmosphere or coupled into a fiber and guided to a transmitting telescope which is attached to the scanner unit. The receiving telescope has a primary mirror with a dimeter of 80 cm. The backscatter signals are recorded shot to shot and are typically averaged over 0.1 to 1 s.</p>

Drought spatiotemporal propagation via land feedbacks

2021 ◽  
Author(s):  
Diego G. Miralles ◽  
Dominik L. Schumacher ◽  
Jessica Keune ◽  
Paul A. Dirmeyer
Keyword(s):  
Soil Moisture ◽  
Water Vapor ◽  
Mitigation Strategies ◽  
Soil Drought ◽  
The Usa ◽  
Forecast Models ◽  
Atmospheric Feedbacks ◽  
Dry Out ◽  
Water And Food Security ◽  
The Impact

<p>The predicted increase in drought occurrence and intensity will pose serious threats to global future water and food security. This was hinted by several historically unprecedented droughts over the last two decades, taking place in Europe, Australia, Amazonia or the USA. It has been hypothesised that the strength of these events responded to self-reinforcement processes related to land–atmospheric feedbacks: as rainfall deficits dry out soil and vegetation, the evaporation of land water is reduced, then the local air becomes too dry to yield rainfall, which further enhances drought conditions. Despite the 'local' nature of these feedbacks, their consequences can be remote, as downwind regions may rely on evaporated water transported by winds from drought-affected locations. Following this rationale, droughts may not only self-reinforce locally, due to land atmospheric feedbacks, but <em>self-propagate</em> in the downwind direction, always conditioned on atmospheric circulation. This propagation is not only meteorological but relies on soil moisture drought, and may lead to a downwind cascading of impacts on water resources. However, a global capacity to observe these processes is lacking, and thus our knowledge of how droughts start and evolve, and how this may change as climate changes, remains limited. Furthermore, climate and forecast models are still immature when it comes to representing the influences of land on rainfall.</p><p>Here, the largest global drought events are studied to unravel the role of land–atmosphere feedbacks during the spatiotemporal propagation of these events. We based our study on satellite and reanalysis records of soil moisture, evaporation, air humidity, winds and precipitation, in combination with a Lagrangian framework that can map water vapor trajectories and explore multi-dimensional feedbacks. We estimate the reduction in precipitation in the direction of drought propagation that is caused by the upwind soil moisture drought, and isolate this effect from the influence of potential evaporation and circulation changes. By doing so, the downwind lack of precipitation caused by upwind soil drought via water vapor deficits, and hence the impact of drought self-propagation, is determined. We show that droughts occurring in dryland regions are particularly prone to self-propagate, as evaporation there tends to respond strongly to enhanced soil stress and precipitation is frequently convective. This kind of knowledge may be used to improve climate and forecast models and can be exploited to develop geo-engineering mitigation strategies to help prevent drought events from aggravating during their early stages.</p>

A Statistical Extended-Range Tropical Forecast Model Based on the Slow Evolution of the Madden–Julian Oscillation

1999 ◽  
Vol 12 (7) ◽  
pp. 1918-1939 ◽  
Author(s):  
Duane E. Waliser ◽  
Charles Jones ◽  
Jae-Kyung E. Schemm ◽  
Nicholas E. Graham
Keyword(s):  
Forecast Model ◽  
Madden Julian Oscillation ◽  
Model Based ◽  
Extended Range ◽  
Slow Evolution

scholarly journals Diversity of the Global Teleconnections Associated with the Madden–Julian Oscillation

2021 ◽  
Vol 34 (1) ◽  
pp. 397-414
Author(s):  
Guosen Chen
Keyword(s):  
Rossby Wave ◽  
Potential Vorticity ◽  
Wave Train ◽  
Boreal Winter ◽  
Madden Julian Oscillation ◽  
The Pacific ◽  
Weather And Climate ◽  
Baroclinic Model ◽  
Rossby Wave Train ◽  
Upper Level

AbstractA recent study has revealed that the Madden–Julian oscillation (MJO) during boreal winter exhibits diverse propagation patterns that consist of four archetypes: standing MJO, jumping MJO, slow eastward propagating MJO, and fast eastward propagating MJO. This study has explored the diversity of teleconnection associated with these four MJO groups. The results reveal that each MJO group corresponds to distinct global teleconnections, manifested as diverse upper-tropospheric Rossby wave train patterns. Overall, the teleconnections in the fast and slow MJO are similar to those in the canonical MJO constructed by the real-time multivariate MJO (RMM) indices, while the teleconnections in the jumping and standing MJO generally lose similarities to those in the canonical MJO. The causes of this diversity are investigated using a linearized potential vorticity equation. The various MJO tropical heating patterns in different MJO groups are the main cause of the diverse MJO teleconnections, as they induce assorted upper-level divergent flows that act as Rossby-wave sources through advecting the background potential vorticity. The variation of the Asian jet could affect the teleconnections over the Pacific jet exit region, but it plays an insignificant role in causing the diversity of global teleconnections. The numerical investigation with a linear baroclinic model shows that the teleconnections can be interpreted as linear responses to the MJO’s diabatic heating to various degrees for different MJO groups, with the fast and slow MJO having higher linear skill than the jumping and standing MJO. The results have broad implications in the MJO’s tropical–extratropical interactions and the associated impacts on global weather and climate.

scholarly journals Surface and top-of-atmosphere radiative feedback kernels for CESM-CAM5

2018 ◽  
Vol 10 (1) ◽  
pp. 317-324 ◽  
Author(s):  
Angeline G. Pendergrass ◽  
Andrew Conley ◽  
Francis M. Vitt
Keyword(s):  
Water Vapor ◽  
Greenhouse Gases ◽  
Surface Temperature ◽  
Radiative Forcing ◽  
Surface Albedo ◽  
Large Ensemble ◽  
Radiative Fluxes ◽  
Radiative Feedback ◽  
Ensemble Simulations ◽  
Temperature Water

Abstract. Radiative kernels at the top of the atmosphere are useful for decomposing changes in atmospheric radiative fluxes due to feedbacks from atmosphere and surface temperature, water vapor, and surface albedo. Here we describe and validate radiative kernels calculated with the large-ensemble version of CAM5, CESM1.1.2, at the top of the atmosphere and the surface. Estimates of the radiative forcing from greenhouse gases and aerosols in RCP8.5 in the CESM large-ensemble simulations are also diagnosed. As an application, feedbacks are calculated for the CESM large ensemble. The kernels are freely available at https://doi.org/10.5065/D6F47MT6, and accompanying software can be downloaded from https://github.com/apendergrass/cam5-kernels.

The Apparent Water Vapor Sinks and Heat Sources Associated with the Intraseasonal Oscillation of the Indian Summer Monsoon

2011 ◽  
Vol 24 (16) ◽  
pp. 4466-4479 ◽  
Author(s):  
Sun Wong ◽  
Eric J. Fetzer ◽  
Baijun Tian ◽  
Bjorn Lambrigtsen ◽  
Hengchun Ye
Keyword(s):  
Remote Sensing ◽  
Water Vapor ◽  
Heat Source ◽  
Summer Monsoon ◽  
Indian Summer Monsoon ◽  
Intraseasonal Oscillation ◽  
Precipitation Anomaly ◽  
Specific Humidity ◽  
Heat Sources ◽  
Test Bed

Abstract The possibility of using remote sensing retrievals to estimate apparent water vapor sinks and heat sources is explored. The apparent water vapor sinks and heat sources are estimated from a combination of remote sensing, specific humidity, and temperature from the Atmospheric Infrared Sounder/Advanced Microwave Sounding Unit (AIRS) and wind fields from the National Aeronautics and Space Administration (NASA)’s Goddard Space Flight Center (GSFC)’s Modern Era Retrospective-Analysis for Research and Applications (MERRA). The intraseasonal oscillation (ISO) of the Indian summer monsoon is used as a test bed to evaluate the apparent water vapor sink and heat source. The ISO-related northward movement of the column-integrated apparent water vapor sink matches that of precipitation observed by the Tropical Rainfall Measuring Mission (TRMM) minus the MERRA surface evaporation, although the amplitude of the variation is underestimated by 50%. The diagnosed water vapor and heat budgets associated with convective events during various phases of the ISO agree with the moisture–convection feedback mechanism. The apparent heat source moves northward coherently with the apparent water vapor sink associated with the deep convective activity, which is consistent with the northward migration of the precipitation anomaly. The horizontal advection of water vapor and dynamical warming are strong north of the convective area, causing the northward movement of the convection by the destabilization of the atmosphere. The spatial distribution of the apparent heat source anomalies associated with different phases of the ISO is consistent with that of the diabatic heating anomalies from the trained heating (TRAIN Q1) dataset. Further diagnostics of the TRAIN Q1 heating anomalies indicate that the ISO in the apparent heat source is dominated by a variation in latent heating associated with the precipitation.

Influence of the Madden–Julian Oscillation on Forecasts of Extreme Precipitation in the Contiguous United States

2011 ◽  
Vol 139 (2) ◽  
pp. 332-350 ◽  
Author(s):  
Charles Jones ◽  
Jon Gottschalck ◽  
Leila M. V. Carvalho ◽  
Wayne Higgins
Keyword(s):  
United States ◽  
Extreme Precipitation ◽  
Western Hemisphere ◽  
Boreal Winter ◽  
Lead Times ◽  
Madden Julian Oscillation ◽  
Extreme Precipitation Events ◽  
Skill Scores ◽  
Probabilistic Forecasts ◽  
Precipitation Events

Abstract Extreme precipitation events are among the most devastating weather phenomena since they are frequently accompanied by loss of life and property. This study uses reforecasts of the NCEP Climate Forecast System (CFS.v1) to evaluate the skill of nonprobabilistic and probabilistic forecasts of extreme precipitation in the contiguous United States (CONUS) during boreal winter for lead times up to two weeks. The CFS model realistically simulates the spatial patterns of extreme precipitation events over the CONUS, although the magnitudes of the extremes in the model are much larger than in the observations. Heidke skill scores (HSS) for forecasts of extreme precipitation at the 75th and 90th percentiles showed that the CFS model has good skill at week 1 and modest skill at week 2. Forecast skill is usually higher when the Madden–Julian oscillation (MJO) is active and has enhanced convection occurring over the Western Hemisphere, Africa, and/or the western Indian Ocean than in quiescent periods. HSS greater than 0.1 extends to lead times of up to two weeks in these situations. Approximately 10%–30% of the CONUS has HSS greater than 0.1 at lead times of 1–14 days when the MJO is active. Probabilistic forecasts for extreme precipitation events at the 75th percentile show improvements over climatology of 0%–40% at 1-day lead and 0%–5% at 7-day leads. The CFS has better skill in forecasting severe extremes (i.e., events exceeding the 90th percentile) at longer leads than moderate extremes (75th percentile). Improvements over climatology between 10% and 30% at leads of 3 days are observed over several areas across the CONUS—especially in California and in the Midwest.

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