scholarly journals Surface fluxes and tropical intraseasonal variability: A reassessment

2010 ◽  
Vol 2 ◽  
Author(s):  
Adam H. Sobel ◽  
Eric D. Maloney ◽  
Gilles Bellon ◽  
Dargan M. Frierson
Keyword(s):  
Intraseasonal Variability ◽  
Surface Fluxes

scholarly journals Intraseasonal Variability in MERRA Energy Fluxes over the Tropical Oceans

2012 ◽  
Vol 25 (17) ◽  
pp. 5629-5647 ◽  
Author(s):  
Franklin R. Robertson ◽  
Jason B. Roberts
Keyword(s):  
Deep Convection ◽  
Intraseasonal Variability ◽  
Tropical Rainfall Measuring Mission ◽  
Precipitation Anomaly ◽  
Surface Fluxes ◽  
State Variables ◽  
Cloud Forcing ◽  
Tropical Oceans ◽  
Fractional Cloud ◽  
Moderate Resolution Imaging Spectroradiometer

Abstract This paper investigates intraseasonal variability as represented by the recent NASA Global Modeling and Assimilation Office (GMAO) reanalysis, the Modern-Era Retrospective analysis for Research and Applications (MERRA). The authors examine the behavior of heat, moisture, and radiative fluxes emphasizing their contribution to intraseasonal variations in heat and moisture balance integrated over the tropical oceans. MERRA successfully captures intraseasonal signals in both state variables and fluxes, though it depends heavily on the analysis increment update terms that constrain the reanalysis to be near the observations. Precipitation anomaly patterns evolve in close agreement with those from the Tropical Rainfall Measuring Mission (TRMM) though locally MERRA may occasionally be smaller by up to 20%. As in the TRMM observations, tropical convection increases lead tropospheric warming by approximately 7 days. Radiative flux anomalies are dominated by cloud forcing and are found to replicate the top-of-the-atmosphere (TOA) energy loss associated with increased convection found by other observationally based studies. However, MERRA’s convectively produced clouds appear to deepen too soon as precipitation increases. Total fractional cloud cover variations appear somewhat weak compared to observations from the Moderate Resolution Imaging Spectroradiometer (MODIS). Evolution of the surface fluxes, convection, and TOA radiation is consistent with the “discharge–recharge” paradigm that posits the importance of lower-tropospheric moisture accumulation prior to the expansion of organized deep convection. The authors conclude that MERRA constitutes a very useful representation of intraseasonal variability that will support a variety of studies concerning radiative–convective–dynamical processes and will help identify pathways for improved moist physical parameterization in global models.

Bay of Bengal Intraseasonal Oscillations and the 2018 Monsoon Onset

2021 ◽  
pp. 1-44
Author(s):  
Emily Shroyer ◽  
Amit Tandon ◽  
Debasis Sengupta ◽  
Harindra J.S. Fernando ◽  
Andrew J. Lucas ◽  
...  
Keyword(s):  
Bay Of Bengal ◽  
Large Scale ◽  
Intraseasonal Variability ◽  
Intraseasonal Oscillation ◽  
Active Phase ◽  
Monsoon Onset ◽  
Surface Fluxes ◽  
The Us ◽  
Intraseasonal Oscillations ◽  
Accumulated Rainfall

AbstractIn the Bay of Bengal, the warm, dry boreal spring concludes with the onset of the summer monsoon and accompanying southwesterly winds, heavy rains, and variable air-sea fluxes. Here, we summarize the 2018 monsoon onset using observations collected through the multinational Monsoon Intraseasonal Oscillations in the Bay of Bengal (MISO-BoB) program between the US, India, and Sri Lanka. MISO-BoB aims to improve understanding of monsoon intraseasonal variability, and the 2018 field effort captured the coupled air-sea response during a transition from active-to-break conditions in the central BoB. The active phase of the ~20-day research cruise was characterized by warm sea surface temperature (SST > 30°C), cold atmospheric outflows with intermittent heavy rainfall, and increasing winds (from 2 to 15 m s−1). Accumulated rainfall exceeded 200 mm with 90% of precipitation occurring during the first week. The following break period was both dry and clear, with persistent 10−12 m s−1 wind and evaporation of 0.2 mm h−1. The evolving environmental state included a deepening ocean mixed layer (from ~20 to 50 m), cooling SST (by ~ 1°C), and warming/drying of the lower to mid-troposphere. Local atmospheric development was consistent with phasing of the large-scale intraseasonal oscillation. The upper ocean stores significant heat in the BoB, enough to maintain SST above 29°C despite cooling by surface fluxes and ocean mixing. Comparison with reanalysis indicates biases in air-sea fluxes, which may be related to overly cool prescribed SST. Resolution of such biases offers a path toward improved forecasting of transition periods in the monsoon.

scholarly journals Intraseasonal Latent Heat Flux Based on Satellite Observations

2009 ◽  
Vol 22 (17) ◽  
pp. 4539-4556 ◽  
Author(s):  
Semyon A. Grodsky ◽  
Abderrahim Bentamy ◽  
James A. Carton ◽  
Rachel T. Pinker
Keyword(s):  
Heat Flux ◽  
Latent Heat ◽  
Latent Heat Flux ◽  
Mixed Layer ◽  
Heat Budget ◽  
Mixed Layer Depth ◽  
Intraseasonal Variability ◽  
Surface Fluxes ◽  
Tropical Region ◽  
Surprising Result

Abstract Weekly average satellite-based estimates of latent heat flux (LHTFL) are used to characterize spatial patterns and temporal variability in the intraseasonal band (periods shorter than 3 months). As expected, the major portion of intraseasonal variability of LHTFL is due to winds, but spatial variability of humidity and SST are also important. The strongest intraseasonal variability of LHTFL is observed at the midlatitudes. It weakens toward the equator, reflecting weak variance of intraseasonal winds at low latitudes. It also decreases at high latitudes, reflecting the effect of decreased SST and the related decrease of time-mean humidity difference between heights z = 10 m and z = 0 m. Within the midlatitude belts the intraseasonal variability of LHTFL is locally stronger (up to 50 W m−2) in regions of major SST fronts (like the Gulf Stream and Agulhas). Here it is forced by passing storms and is locally amplified by unstable air over warm SSTs. Although weaker in amplitude (but still significant), intraseasonal variability of LHTFL is observed in the tropical Indian and Pacific Oceans due to wind and humidity perturbations produced by the Madden–Julian oscillations. In this tropical region intraseasonal LHTFL and incoming solar radiation vary out of phase so that evaporation increases just below the convective clusters. Over much of the interior ocean where the surface heat flux dominates the ocean mixed layer heat budget, intraseasonal SST cools in response to anomalously strong upward intraseasonal LHTFL. This response varies geographically, in part because of geographic variations of mixed layer depth and the resulting variations in thermal inertia. In contrast, in the eastern tropical Pacific and Atlantic cold tongue regions intraseasonal SST and LHTFL are positively correlated. This surprising result occurs because in these equatorial upwelling areas SST is controlled by advection rather than by surface fluxes. Here LHTFL responds to rather than drives SST.

Surface Fluxes and Ocean Coupling in the Tropical Intraseasonal Oscillation

2004 ◽  
Vol 17 (22) ◽  
pp. 4368-4386 ◽  
Author(s):  
Eric D. Maloney ◽  
Adam H. Sobel
Keyword(s):  
Mixed Layer ◽  
Mixed Layer Depth ◽  
Intraseasonal Variability ◽  
Intraseasonal Oscillation ◽  
Sensitivity Study ◽  
Ocean Model ◽  
Surface Fluxes ◽  
Boreal Winter ◽  
Layer Depth ◽  
Idealized Model

Abstract Sensitivity of tropical intraseasonal variability to mixed layer depth is examined in the modified National Center for Atmospheric Research Community Atmosphere Model 2.0.1 (CAM), with relaxed Arakawa–Schubert convection, coupled to a slab ocean model (SOM) whose mixed layer depth is fixed and geographically uniform, but varies from one experiment to the next. Intraseasonal west Pacific precipitation variations during boreal winter are enhanced relative to a fixed-SST (infinite mixed layer depth) simulation for mixed layer depths from 5 to 50 m, with a maximum at 20 m [interestingly, near the observed value in the regions where the Madden– Julian oscillation (MJO) is active], but are strongly diminished in the 2-m depth simulation. This nonmonotonicity of intraseasonal precipitation variance with respect to mixed layer depth was predicted by Sobel and Gildor using a highly idealized model. Further experiments with the same idealized model help to interpret results derived from the modified NCAR CAM. A sensitivity study shows that the convection–surface flux feedback [wind-induced surface heat exchange (WISHE)] is important to the intraseasonal variability in the CAM. This helps to explain the behavior of the 2-m SOM simulation and the agreement with the idealized model. Although intraseasonal SST variations are stronger in the 2-m SOM simulation than in any of the other simulations, these SST variations are phased in such a way as to diminish the amplitude of equatorial latent heat flux variations. Reducing the mixed layer depth is thus nearly equivalent to eliminating WISHE, which in this model reduces intraseasonal variability. The WISHE mechanism in the model is nonlinear and occurs in a region of mean low-level westerlies. Since a very shallow mixed layer is effectively similar to wet land, it is suggested that the mechanism described here may explain the local minimum in MJO amplitude observed over the Maritime Continent region.

The Impact of Climate Change on Storage-Yield Curves for Multi-Reservoir Systems

1999 ◽  
Vol 30 (2) ◽  
pp. 129-146 ◽  
Author(s):  
N. R. Nawaz ◽  
A. J. Adeloye ◽  
M. Montaseri
Keyword(s):  
Climate Change ◽  
Surface Fluxes ◽  
Runoff Coefficient ◽  
Impact Study ◽  
Yield Functions ◽  
Reservoir Systems ◽  
English System ◽  
Multiple Reservoir ◽  
The Impact ◽  
Impacts Of Climate Change

In this paper, we report on the results of an investigation into the impacts of climate change on the storage-yield relationships for two multiple-reservoir systems, one in England and the other in Iran. The impact study uses established protocol and obtains perturbed monthly inflow series using a simple runoff coefficient approach which accounts for non-evaporative losses in the catchment, and a number of recently published GCM-based scenarios. The multi-reservoir analysis is based on the sequent-peak algorithm which has been modified to analyse multiple reservoirs and to accommodate explicitly performance norms and reservoir surface fluxes, i.e. evaporation and rainfall. As a consequence, it was also possible to assess the effect of including reservoir surface fluxes on the storage-yield functions. The results showed that, under baseline conditions, consideration of net evaporation will require lower storages for the English system and higher storages for the Iranian system. However, with perturbed hydroclimatology different impacts were obtained depending on the systems' yield and reliability. Possible explanations are offered for the observed behaviours.

scholarly journals Anthropogenic warming and intraseasonal summer monsoon variability amplify the risk of future flash droughts in India

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Vimal Mishra ◽  
Saran Aadhar ◽  
Shanti Shwarup Mahto
Keyword(s):  
Soil Moisture ◽  
Summer Monsoon ◽  
Crop Production ◽  
Monsoon Rainfall ◽  
Root Zone ◽  
Monsoon Season ◽  
Intraseasonal Variability ◽  
Positive Temperature ◽  
Groundwater Abstraction ◽  
Increased Risk

AbstractFlash droughts cause rapid depletion in root-zone soil moisture and severely affect crop health and irrigation water demands. However, their occurrence and impacts in the current and future climate in India remain unknown. Here we use observations and model simulations from the large ensemble of Community Earth System Model to quantify the risk of flash droughts in India. Root-zone soil moisture simulations conducted using Variable Infiltration Capacity model show that flash droughts predominantly occur during the summer monsoon season (June–September) and driven by the intraseasonal variability of monsoon rainfall. Positive temperature anomalies during the monsoon break rapidly deplete soil moisture, which is further exacerbated by the land-atmospheric feedback. The worst flash drought in the observed (1951–2016) climate occurred in 1979, affecting more than 40% of the country. The frequency of concurrent hot and dry extremes is projected to rise by about five-fold, causing approximately seven-fold increase in flash droughts like 1979 by the end of the 21st century. The increased risk of flash droughts in the future is attributed to intraseasonal variability of the summer monsoon rainfall and anthropogenic warming, which can have deleterious implications for crop production, irrigation demands, and groundwater abstraction in India.

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