Subhadeep Halder

Modulation of ISOs by land-atmosphere feedback and contribution to the interannual variability of Indian summer monsoon

A mechanism of internal variability of Indian summer monsoon through the modulation of intraseasonal oscillation (ISO) by land-atmosphere feedback is proposed. Evidence of feedback between surface soil moisture and ISOs is seen in the soil moisture data from GSWP-2 and rainfall data from observations. Using two sets of internal simulation by a regional climate model (RCM), it is shown that internally generated anomalous soil moisture interacts with the following ISO and generates interannual variability. To gain further insight, 27 years of sensitivity experiment by prescribing wet (dry) soil moisture condition during break (active) period along with a control simulation are carried out. The sensitivity experiment reveals the large-scale nature of soil moisture and ISO feedback which takes place through the changes in atmospheric stability by altering lower-level atmospheric conditions. The feedback is inherent to the monsoon system and a part of it acts through the intraseasonal varying memory of soil moisture. The RCM used to test the hypothesis is constrained by one-way interactions at the lateral boundary. Experiments with a much larger domain upheld the findings and hence suggest the true nature of soil moisture and ISO feedback present in the monsoon system.

Improvements in the representation of the Indian summer monsoon in the NCEP climate forecast system version 2

A new triggering mechanism for deep convection based on the heated condensation framework (HCF) is implemented into the National Centers for Environmental Prediction climate forecast system version 2 (CFSv2). The new trigger is added as an additional criterion in the simplified Arakawa–Schubert scheme for deep convection. Seasonal forecasts are performed to evaluate the influence of the new triggering mechanism in the representation of the Indian summer monsoon in the CFSv2. The HCF trigger improves the seasonal representation of precipitation over the Indian subcontinent. The new triggering mechanism leads to a significant, albeit relatively small, improvement in the bias of seasonal precipitation totals. In addition, the new trigger improves the representation of the seasonal precipitation cycle including the monsoon onset, and the probability distribution of precipitation intensities. The mechanism whereby the HCF improves convection over India seems to be related not only to a better representation of the background state of atmospheric convection but also to an increase in the frequency in which SAS is triggered. As a result, there was an increase in convective precipitation over India favored by the availability of moist convective instability. The increase in precipitation intensity leads to a reduction in the dry bias.

Relation of Eurasian Snow Cover and Indian Summer Monsoon Rainfall: Importance of the Delayed Hydrological Effect

AbstractThis observationally based study demonstrates the importance of the delayed hydrological response of snow cover and snowmelt over the Eurasian region and Tibet for variability of Indian summer monsoon rainfall during the first two months after onset. Using snow cover fraction and snow water equivalent data during 1967–2003, it is demonstrated that, although the snow-albedo effect is prevalent over western Eurasia, the delayed hydrological effect is strong and persistent over the eastern part. Long soil moisture memory and strong sensitivity of surface fluxes to soil moisture variations over eastern Asia and Tibet provide a mechanism for soil moisture anomalies generated by anomalies in winter and spring snowfall to affect rainfall during the initial months in summer. Dry soil moisture anomalies over the eastern Eurasian region associated with anomalous heating at the surface and midtroposphere help in anchoring of an anomalous upper-tropospheric “blocking” ridge around 100°E and its persistence. T...

The heated condensation framework as a convective trigger in the NCEP Climate Forecast System version 2

An updated version of the Heated Condensation Framework (HCF) is implemented as a convective triggering criterion into the National Centers for Environmental Prediction (NCEP) Climate Forecast System version 2 (CFSv2). The new trigger replaces the original criteria in both the deep (Simplified Arakawa-Schubert – SAS) and shallow (SAS based) convective schemes. The performance of the original and new triggering criteria is first compared against radiosonde observations. Then, a series of hindcasts are performed to evaluate the influence of the triggering criterion in the CFSv2 representation of summer precipitation, the diurnal cycle of precipitation, and hurricanes that made landfall. The observational analysis shows that the HCF trigger better captures the frequency of convection, where the original SAS trigger initiates convection too often. When implemented in CFSv2, the HCF trigger improves the seasonal forecast of the Indian summer monsoon rainfall, including the representation of the onset dates of the rainy season over India. On the other hand, the HCF trigger increases error in the seasonal forecast of precipitation over the eastern United States. The HCF trigger also improves the representation of the intensity of hurricanes. Moreover, the simulation of hurricanes provides insights on the mechanism whereby the HCF trigger impacts the representation of convection.

Application of the Land–Atmosphere Coupling Paradigm to the Operational Coupled Forecast System, Version 2 (CFSv2)

AbstractRetrospective forecasts from CFSv2 are evaluated in terms of three elements of land–atmosphere coupling at subseasonal to seasonal time scales: sensitivity of the atmosphere to variations in land surface states, the magnitude of variability of land states and fluxes, and the memory or persistence of land surface anomalies. The Northern Hemisphere spring and summer seasons are considered for the period 1982–2009. Ensembles are constructed from all available pairings of initial land and atmosphere/ocean states taken from the Climate Forecast System Reanalysis at the start of April, May, and June among the 28 years, so that the effect of initial land states on the evolving forecasts can be assessed. Finally, improvement and continuance of forecast skill derived from accurate land surface initialization is related to the three coupling elements. It is found that soil moisture memory is the most broadly important element for significant improvement of realistic land initialization on forecast skill. Ho...

Influence of preonset land atmospheric conditions on the Indian summer monsoon rainfall variability

A possible link between preonset land atmospheric conditions and the Indian summer monsoon rainfall (ISMR) is explored. It is shown that, the preonset positive (negative) rainfall anomaly over northwest India, Pakistan, Afghanistan, and Iran is associated with decrease (increase) in ISMR, primarily in the months of June and July, which in turn affects the seasonal mean. ISMR in the months of June and July is also strongly linked with the preonset 2 m air temperature over the same regions. The preonset rainfall/2 m air temperature variability is linked with stationary Rossby wave response, which is clearly evident in the wave activity flux diagnostics. As the predictability of Indian summer monsoon relies mainly on the El Nino–Southern Oscillation (ENSO), the found link may further enhance our ability to predict the monsoon, particularly during a non-ENSO year.

Sensitivity of Numerical Weather Forecasts to Initial Soil Moisture Variations in CFSv2

AbstractWhen initial soil moisture is perturbed among ensemble members in the operational NWS global forecast model, surface latent and sensible fluxes are immediately affected much more strongly, systematically, and over a greater area than conventional land–atmosphere coupling metrics suggest. Flux perturbations are likewise transmitted to the atmospheric boundary layer more formidably than climatology-based metrics would indicate. Impacts are not limited to the traditional land–atmosphere coupling hot spots, but extend over nearly all ice-free land areas of the globe. Key to isolating this effect is that initial atmospheric states are identical among quantities correlated, pinpointing soil moisture and snow cover. A consequence of this high sensitivity is that significant positive impacts of realistic land surface initialization on the skill of deterministic near-surface temperature and humidity forecasts are also immediate and nearly universal during boreal spring and summer (the period investigated) ...

Reforecasting the ENSO Events in the Past 57 Years (1958–2014)

AbstractA set of ensemble seasonal reforecasts for 1958–2014 is conducted using the National Centers for Environmental Prediction (NCEP) Climate Forecast System, version 2. In comparison with other current reforecasts, this dataset extends the seasonal reforecasts to the 1960s–70s. Direct comparison of the predictability of the ENSO events occurring during the 1960s–70s with the more widely studied ENSO events since then demonstrates the seasonal forecast system’s capability in different phases of multidecadal variability and degrees of global climate change. A major concern for a long reforecast is whether the seasonal reforecasts before 1979 provide useful skill when observations, particularly of the ocean, were sparser. This study demonstrates that, although the reforecasts have lower skill in predicting SST anomalies in the North Pacific and North Atlantic before 1979, the prediction skill of the onset and development of ENSO events in 1958–78 is comparable to that for 1979–2014. In particular, the EN...

Impact of Land Surface Initialization and Land-Atmosphere Coupling on the Prediction of the Indian Summer Monsoon with the CFSv2

The impact of initial land-surface states on monthly to seasonal prediction skill of the Indian summer monsoon (June- September) is investigated using a suite of hindcasts made with the Climate Forecast System version 2 (CFSv2) operational forecast model. The modern paradigm of land-atmosphere coupling is applied to quantify biases in different components of the land-atmosphere coupled system and their effect on systematic errors. Three sets of hindcasts are performed for the period spanning 1982-2009 initialized at the start of April, May and June. For a particular initial date of a given year, one member (Control run) has the analyzed land initial state consistent with the atmosphere, sea ice and ocean states for that year; the other 27 members have land states taken from each of the remaining 27 years. There is significant improvement in the deterministic prediction skill of near surface temperature and soil moisture on monthly and seasonal time scales due to realistic land initial conditions. The improvement occurs in those areas where the land-atmosphere coupling is strongest. Improvements in the prediction skill of precipitation are confined to relatively small areas. The pattern of skill differences resembles patterns of land-atmosphere coupling strength, while biases in the representation of land-atmosphere coupling affect the skill of temperature and rainfall. The re-emergence of skill in temperature and precipitation towards the end of the season over northwest India within April and June IC hindcasts may be attributed to better simulation of the withdrawal phase of the monsoon as well as increased land-atmosphere coupling. For May IC hindcasts, increased skill in air temperature on the sub-seasonal time scales could be due to other large-scale factors. Errors in the parameterization of radiation, convection, boundary layer processes, surface moisture fluxes and the representation of vegetation contribute to decay in potential predictability and skill attributable to land initial conditions. Furthermore, incorrect representation of daily and sub-daily precipitation statistics over land also likely lead to errors in land-atmosphere coupling. Above all, the importance of accurate land surface initialization and land-atmosphere coupling in improving the Indian summer monsoon prediction on sub-seasonal to seasonal time scales is emphasized.