Precipitation Recycling in the Indian Subcontinent during Summer Monsoon

Precipitation Recycling in the Indian Subcontinent during Summer Monsoon

AMEY PATHAK

Department of Civil Engineering, Indian Institute of Technology Bombay, Mumbai, India

SUBIMAL GHOSH

Department of Civil Engineering, and Interdisciplinary Program in Climate Studies, Indian Institute of

Technology Bombay, Mumbai, India

PRAVEEN KUMAR

Civil and Environmental Engineering, University of Illinois at Urbana–Champaign, Urbana, Illinois

(Manuscript received 24 October 2013, in final form 13 June 2014)

ABSTRACT

The Indian summer monsoon rainfall is dominated by oceanic sources of moisture. However, land surface

processes also have a significant role in the generation of precipitation within the Indian subcontinent.

Evapotranspiration over a region supplies moisture to the atmosphere, which may lead to precipitation in the

same region. This is known as recycled precipitation. The role of evapotranspiration as an additional source of

moisture to precipitation has been investigated in earlier studies at continental scales; however, the amount of

monsoon precipitation generated from evapotranspiration has not been quantified at the daily scale for the

Indian subcontinent. To examine the role of land surface hydrology in regional precipitation and to quantify

recycled precipitation, the dynamic recycling model at a daily scale with NCEP Climate Forecast System

Reanalysis (CFSR) data for the period of 1980–2010 is used. A high precipitation recycling ratio, that is, the

ratio of recycled precipitation to total precipitation, is found at the end of the monsoon (September). As the

monsoon progresses in India, enhanced soil moisture and vegetation cover lead to increased evapotranspiration

and recycled precipitation. The recycling ratio is highest (around 25%) in northeastern India, which has high

vegetation cover leading to high evapotranspiration. Recycled precipitation over central and northeastern India

in September is responsible for delaying the withdrawal of the summer monsoon over these regions. A trend

analysis of recycled precipitation shows a statistically significant decreasing trend in northeastern India.

1. Introduction

The Indian summer monsoon rainfall (ISMR) during

June–September (JJAS) is part of the Asian monsoon

(Rajeevan et al. 2010) and is the major source of annual

precipitation over the Indian subcontinent. A large

population relying on agriculture is highly dependent on

the seasonal characteristics of ISMR. Though ISMR is

dominated by an oceanic source, evapotranspiration

from terrestrial sources is also an important contributor

to precipitation. The development of low pressure over

subcontinental land during premonsoon months (i.e.,

April and May), owing to the land–sea thermal con-

trast between Indian land regions and the Indian

Ocean, results in advection of evaporated oceanic

moisture toward the Indian region (Krishnamurthy

and Kinter 2003). Although the land–sea thermal

contrast is one of the major mechanisms influencing

summer monsoon precipitation characteristics, several

land surface processes, such as soil moisture, evapo-

transpiration, and topography and land use, are also

associated with seasonal monsoon precipitation dy-

namics (Meehl 1994; Yasunari 2007; Bellon 2010; Saha

et al. 2012). The spatial and temporal variability of

rainfall is often regulated by the strength of land sur-

face feedbacks (Shukla and Mintz 1982; Yasunari

2007). For example, evapotranspiration over a region

provides additional moisture to the atmosphere, which

leads to precipitation in the same region, and this is

Corresponding author address: Subimal Ghosh, Department of

Civil Engineering, Indian Institute of Technology Bombay,Mumbai

400 076, India.

E-mail: [email protected]

2050 JOURNAL OF HYDROMETEOROLOGY VOLUME 15

DOI: 10.1175/JHM-D-13-0172.1

� 2014 American Meteorological Society

mailto:[email protected]

known as recycled precipitation. Significant variations

in the strength of these feedbacks through evapo-

transpiration can affect regional precipitation charac-

teristics during the monsoon season. Therefore,

understanding and modeling of the feedback processes

from the land surface to the atmosphere are of major

importance for the study of any regional climate system.

Here, we model precipitation recycling in the Indian

subcontinent during a monsoon to understand the

feedback processes with the land surface and their

strength and variability.

Land surface interacts with the adjoining atmosphere

by exchanging energy,mass, andmomentum (Dominguez

and Kumar 2008), and this significantly affects the

characteristics of regional climate system (Dirmeyer and

Shukla 1993; Higgins and Gochis 2007;Watts et al. 2007).

Moreover, recent studies (Wang 2006, and references

therein; Yasunari 2007; Bellon 2010; Saha et al. 2012)

have also revealed that the geophysical processes asso-

ciated with ISMR originate from land, ocean, and

atmospheric interactions. Unlike ocean–atmosphere

interactions through sea surface temperature (SST) var-

iations, the role of land–atmosphere interaction in ISMR

at the regional scale has not been extensively investigated

and quantified.

To get a holistic view of the regional precipitation

process during summer monsoon, the quantification of

precipitation generated by local evapotranspiration is

required. The impact of precipitation recycling on total

precipitation has been identified through a variety of

approaches using analytical models that are derived

from the principle of conservation of atmospheric wa-

ter vapor (Budyko 1974; Lettau et al. 1979; Brubaker

et al. 1993; Eltahir and Bras 1996; Burde and Zangvil

2001; Dominguez et al. 2006). Eltahir and Bras (1996)

studied the potential impacts of local land surface

processes on the regional water cycle over the Amazon

basin. The study explained that the amount of precipitable

water contained in the atmospheric control volume over

any particular land region is mainly composed of two

components: (i) the advected component that includes

both oceanic as well as remote terrestrial sources and (ii)

the internal component that includes local terrestrial

sources. The partitioning of precipitable water, based on

geographic locations of their evaporative sources, can

give detailed information about the role of local land

surface characteristics in regional precipitation (Eltahir

and Bras 1994).

In the context of ISMR, literature shows the possi-

bility of impacts of land surface hydrology on ISMR

through feedback mechanisms (Meehl 1994; Yasunari

2007; Asharaf et al. 2011; Tuinenburg et al. 2012; Saha

et al. 2012). Bosilovich and Schubert (2002) identified

local and remote sources of moisture used in summer

monsoon precipitation over North America and India

by implementing three-dimensional water vapor tracers

(WVTs) in general circulation model (GCM) simula-

tions. It was observed that the southern and western

Indian Ocean significantly contribute to the monsoon

precipitation over the Indian subcontinent, with the

highest amount in June and lowest amount in August.

Gimeno et al. (2010) used a three-dimensional Lagrang-

ian transport model, Flexible Particle Dispersion Model

(FLEXPART; Stohl and James 2004, 2005), to identify

the oceanic moisture sources for the continental pre-

cipitation. Six different oceanic sources (i.e., Indian

Ocean, Arabian Sea, Zanzibar Current, Agulhas Cur-

rent, tropical SouthAfrica, andRed Sea) were identified

for the Indian monsoon rainfall during June–August

(JJA). Gimeno et al. (2012) studied the oceanic and

terrestrial sources of continental precipitation. The au-

thors investigated the source and sink regions of atmo-

spheric water vapor using an analytical box model,

numerical water vapor tracers, and isotopes. Different

terrestrial and oceanic regions across the globe were

identified as sources or sinks. The source of water vapor

for monsoon precipitation over the Indian subcontinent

is mainly from local recycling over the continent and

moisture inflow from neighboring oceanic sources.

However, the impact of local terrestrial sources is ob-

served to be less as compared to the oceanic sources.

Van der Ent et al. (2010) used a water accounting model

to study the importance of terrestrial evaporation

through moisture recycling. The study demonstrated

the importance of terrestrial moisture sources (i.e.,

continental evaporation) in the monsoon precipitation,

with a maximum continental moisture recycling ratio

(;20%–40%), which is observed during July. Tuinenburg

et al. (2012) studied the moisture recycling for the

Ganges River basin using the Interim European Centre

for Medium-Range Weather Forecasts (ECMWF) Re-

Analysis (ERA-Interim) data corresponding to the

period of 1990–2009. A moisture recycling ratio of al-

most 5% was observed during the monsoon season for

this basin. Asharaf et al. (2011) performed a perturbation-

based simulation using the Consortium for Small-Scale

Modelling in Climate Mode (COSMO-CLM), where

a nonhydrostatic regional climatemodel was forced with

ERA-Interim data to investigate the soil moisture–

precipitation feedback over the Indian region. Both

positive and negative feedbacks were observed during

the summer monsoon period. The existence of a domi-

nant negative feedback mechanism over western and

northern regions was the most important conclusion of

their study. The study was based on numerical experi-

ments of atmospheric circulations under simulated

OCTOBER 2014 PATHAK ET AL . 2051

conditions with or without perturbation of soil moisture

and evaporation from land surface. The quantification of

the feedbacks of land surface processes on ISMR at daily

time scales was not addressed by that study.

Themain objective of the present work is to investigate

and quantify the role of precipitation recycling in ISMR

and the associated intraseasonal rainfall variability.

ISMR has huge variability in both spatial and temporal

scales (Gadgil and Joseph 2003; Krishnamurthy and

Shukla 2007; Rajeevan et al. 2010). The subseasonal

rainfall variability during themonsoon is associated with

active (wet spell) and break (dry spell) phases with a

duration of about 3–8 days (Lawrence and Webster

2001; Gadgil 2003; Rajeevan et al. 2010). The changes in

land surface energy exchanges during these periods can

induce significant variability in the monsoon rainfall

characteristics over a region. Hence, the time scale to be

used for recycling studies of ISMR should be shorter

than a week. Most of the earlier recycling models (e.g.,

Budyko 1974; Brubaker et al. 1993; Eltahir and Bras

1994) are based on the common assumption that the

change in the storage of atmospheric water vapor is

small and hence can be neglected. This assumption is

valid for monthly or longer time scales, and this restricts

the applicability of these models to a shorter time scale

such as daily or weekly. The importance of moisture

storage at the daily scale in precipitation recycling anal-

ysis was addressed by Dominguez et al. (2006) through

the development of a dynamic recycling model (DRM).

This approach facilitated the recycling analysis at various

time scales ranging from daily to seasonal. The dynamic

recycling model is derived from the equation of conser-

vation of atmospheric water vapor with the assumption of

a well-mixed atmosphere. The dynamic recycling model

is a simple and computationally efficient approach for

analyzing the potential impact of regional evapotranspi-

ration on regional precipitation. The model is best suited

for the present study analyzing daily recycled pre-

cipitation for Indian monsoon. Here, we use DRM at

a spatial resolution of 0.58 3 0.58 and daily temporal

resolution. The dataset from the National Centers for

Environmental Prediction (NCEP) Climate Forecast

System Reanalysis (CFSR; Saha et al. 2010) corre-

sponding to the period of 1980–2010 is used in the present

study. The entire area of Indian subcontinent is first

subdivided into 11 different rectangular zones (Fig. 1) to

study the proportion of the precipitation within each

zone, originating from the evapotranspiration of the same

zone. The analysis is performed at the daily scale for

JJAS. The analysis is also performed considering the

subcontinent as one region to study the impacts of the

entire subcontinental land evapotranspiration on ISMR.

Trends and intraseasonal variations of the computed

recycled precipitation are studied to understand their

association with the temporal variability of ISMR.

This paper is organized as follows. Section 2 provides

detailed information about the datasets used in the

present study and illustrates a detailed methodology of

dynamic recycling model used for ISMR. Section 3 dis-

cusses the important results obtained from this analysis.

Finally, a summary and the conclusions of the major

results of this study are presented in section 4.

2. Data and methodology

a. CFSR

The Indian subcontinent has large topographic and

climatic variations with six different climate subtypes

(Peel et al. 2007). Monsoon precipitation characteristics

over India show significant spatial and temporal vari-

ability (Gadgil 2003). A high-resolution reanalysis data-

set is thus required to study the impacts of land surface

feedbacks on regional precipitation. In the present

analysis, we use NCEP CFSR, version ds093.0, for the

time period 1980–2010 at 0.58 3 0.58 spatial resolution.The spatial resolution of other reanalysis data, such as

NCEP reanalysis (2.58 3 2.58), 15-yr ECMWF Re-

Analysis (ERA-15; T106, 2.58 3 2.58), 40-yr ECMWF

Re-Analysis (ERA-40; 1.1258 3 1.1258 and 2.58 3 2.58),Japanese 25-year Reanalysis Project (JRA-25; 1.1258 31.1258 and 2.58 3 2.58), and National Aeronautics and

Space Administration (NASA) Modern-Era Retrospec-

tive Analysis for Research and Applications (MERRA;

0.58 3 0.6678), are coarse (Dee et al. 2014), and hence, we

do not use them for the present study. CFSR is a third-

generation reanalysis product that provides the best es-

timate of the land–ocean–atmosphere coupled domain at

high resolution and for a long duration (Saha et al. 2010).

The CFSR atmospheric model considers observed var-

iations in carbon dioxide (CO2), together with changes

in aerosols, other trace gases, and solar variations. The

model also considers inputs from all available conven-

tional and satellite observations. The output data from

the Noah land surface model in terms of mean vegeta-

tion percentage and vegetation type are also included in

NCEP CFSR. The dataset is available at 6-hourly,

monthly, and selected hourly time scales. Table 1 shows

the detailed description of NCEP CFSR variables used

in the study. We consider precipitation and evapo-

transpiration at the surface level. Zonal and meridional

wind and specific humidity are vertically integrated at

1000–300mb pressure levels. The 6-hourly CFSR data

are averaged to daily mean values and are used at 0.58 30.58 spatial resolutions. The variables that are not at 0.58 30.58 spatial resolutions are brought to this resolution

using bilinear interpolation.


b. Study area

We first subdivide the Indian subcontinent study re-

gion into 11 different rectangular boxes (hereafter re-

ferred as zones), as presented in Fig. 1.These 11 zones

are different from the regions specified by the Indian

Meteorological Department (IMD) or global climatic

zones based on latitudes. We keep areas of all the zones

nearly the same to avoid the impact of the size of the

area on the estimation of recycling ratio (Dominguez

et al. 2006). Since the Indian subcontinent has a long

coastline, the zones are created in such a way that each

of the zones cover maximum land area and retain uni-

form climate properties to the maximum extent possi-

ble. Table 2 shows the percentage area of different

climate subtypes, as specified by IMD, under each zone.

We also apply the same recycling model separately by

considering the entire subcontinent as one zone.

c. Precipitation recycling

The total amount of water vapor present in a zone’s

atmospheric column (i.e., precipitable water) has two

sources: advective water vapor from a different zone and

evapotranspiration from the same zone. The total pre-

cipitation P is the sum of advective Pa and recycled Pr

components of water vapor:

P5Pa1Pr . (1)

The locally evaporated and advective water vapors are

assumed to be well mixed in the atmospheric column,

and therefore,

TABLE 1. Description of NCEP CFSR data used in the present

study.

Variable Notation Source Units

Evapotranspiration E NCEP CFSR mm

Total precipitation P NCEP CFSR mmday21

Specific humidity q NCEP CFSR kgkg21

Precipitable water w NCEP CFSR kgm22

Zonal component

of wind

u NCEP CFSR ms21

Meridional component

of wind

y NCEP CFSR ms21

FIG. 1. Zonation of India for modeling precipitation recycling. The Indian subcontinent is di-

vided into 11 equal-sized zones in such a way that each zone covers the max land region. Zones 6

and 7 cover the northeastern part,whereas zone 3 covers the northwestern part of the subcontinent.


Pr

Pa

5locally evaporated water vapor

advective water vapor. (2)

Figure 2 illustrates various fluxes associated with pre-

cipitation processes in a region. The upward evaporative

flux is represented by E. The precipitation over the re-

gion is composed of recycled and advective pre-

cipitation. The inflow and outflow of advective moisture

is represented by Fin and Fout, respectively.

The relative contributions of advective and recycled

water vapor to precipitation depend on the location,

season, and size of the zone (or region) considered. The

local recycling ratio denoted by Rl is given by ratio of

recycled precipitation to the total precipitation at

a particular grid (here, the CFSR grids with spatial res-

olution 0.58 3 0.58). For instance, in a uniformly spaced

gridded zone (or region), the recycling ratio Rln in

a particular grid n is given as

Rln 5Prn

Pn

5wrn

wn

. (3)

Here, Pn and Prn are the total precipitation and recycled

precipitation, respectively. Following the grid-based

approach similar to Eltahir and Bras (1994), the regional

recycling ratio, a representative value of precipitation

recycling within a zone (composed of n 5 1, 2, . . . , N,

number of grids) of size [N(DA)] is given by

Rz 5Pr

P5

�N

n51

(RlnPnDA)

�N

n51

(PnDA)

. (4)

The time period during which water vapor stays in

a zone provides important information about the po-

tential role of precipitation recycling in the precipitation

TABLE 2. Percentage area under different climate subtypes for each zone [classification source: Peel et al. (2007)].

Zone

1 2 3 4 5 6 7 8 9 10 11

Land area (%) 100 100 95.02 100 100 97.29 100 52.49 91.9 38.01 46.15

Sea area (%) 0 0 4.98 0 0 2.71 0 47.51 8.14 61.99 53.85

1. Humid subtropical (Cwa) 5.88 10.4 0 31.221 74.67 27.6 33.48 0.9 8.14 6.33 2.71

2. Warm semiarid (BWh) 13.12 7.23 28.05 28.5 0 0 0 28.05 22.2 0 3.16

3. Tropical monsoon (Am) 0 0 0 0 0 6.78 10.4 5.88 0 0 6.33

4. Highland subtropical (CWb) 0 7.69 0 5.42 21.27 13.57 24.88 0 0 0 5.43

5. Warm desert (Bwk) 23.07 2.26 57.91 9.95 0 0 0 0 0 0 0

6. Warm Mediterranean (Csa) 0 2.71 4.52 0 0 0 0 0 0 0 0

7. Cold desert (Bwk) 19 50.22 0 0 0 3.62 3.16 0 0 0 0

8. Cold semiarid (Bsk) 24.89 0 0.45 0 0 7.7 3.16 0 0 0 0

9. Tropical savanna (Aw) 0 1.35 3.61 24.88 4.07 24.88 21.26 19.45 60.6 33.48 29.41

10. Cold dry region (Dwc) 0 0 0 0 0 4.52 0 0 0 0 0

11. Cold dry region (Dwb) 5.43 2.71 0 0 0 10.4 3.62 0 0 0 0

12. Polar tundra (ET) 0 0 0 0 0 0 0 0 0 0 0

13. Cool continental (Dsc) 8.6 15.38 0 0 0 0 0 0 0 0 0

TABLE 3. A list of derived variables with their derivation equation. [See model derivation in Dominguez et al. (2006) for detailed

explanation.]

Variable Notation Equation

Moisture-weighted zonal flux:

moisture-weighted vertically

integrated zonal wind.

um um 51

wgð ðp0

0

qbu dp1 ðp00

q0 bu0 dpÞMoisture-weighted meridional flux:

moisture-weighted vertically

integrated meridional wind.

ym ym 51

wgð ðp0

0

qby dp1 ðp00

q0 by0 dpÞLocal recycling ratio Rl Rl 5

Recycled precipitation at nth grid

Total precipitation at nth grid5 12 exp

�2

ðt0

�(x, j, t)

v(x, j, t)›t0

�

Regional recycling ratio Rz Rz 5Total recycled precipitation over zone

Total precipitation over zone5

�N

n5 1

(RlnpnDA)

�N

n5 1

(pnDA)


process. The length of this period is known as the

moisture residence time. We use a numerical scheme,

following the method used by Merrill et al. (1986), to

trace the path traversed by the water vapor within the

zone’s geographical boundary before precipitation.

d. Dynamic recycling model

The vertically integrated moisture balance equation

for total atmospheric water vapor as well as locally

evaporated water vapor are expressed as (Dominguez

et al. 2006)

›w

›t1

›(wum)

›x1

›(wym)

›y5E2P , (5)

›wr

›t1

›(wrum)

›x1

›(wrym)

›y5E2Pr, and (6)

w›Rl

›t1wum

›Rl

›x1wym

›Rl

›y5E(12Rl) . (7)

The amount of total water vapor and locally evaporated

water vapor present in the atmospheric column is rep-

resented by w and wr, respectively. The moisture-

weighted zonal and meridional winds are represented

by um and ym, respectively. The local recycling ratio at

a certain grid is estimated as

R(x, j, t)5 12 exp

�2

ðt0

�(x, j, t)

v(x, j, t)›t0

�. (8)

Here, �(x, j, t),v(x, j, t), and R(x, j, t) represent the

evapotranspiration, precipitable water, and local re-

cycling ratio in a grid. The regional recycling ratio Rz is

calculated for each zone by using Eq. (4). Table 3 shows

a list of derived variables with their derivation equation.

The recycling ratio expressed in Eq. (8) is analytically

derived and, hence, computationally efficient [see model

derivation in Dominguez et al. (2006) for detailed ex-

planation]. The recycling ratio increases with the increase

of moisture residence time over the region. The estimate

of local recycling ratio at any grid shows the precipitation

contribution of land evapotranspiration from the zone to

which the grid point belongs. The recycling ratio com-

puted with Eq. (8) is used to assess the regional recycling

ratio and recycled precipitation [Eqs. (3) and (4)]. Here,

we calculate the recycling ratio for two cases, first by di-

viding the subcontinent into 11 different zones and

then by considering the entire Indian subcontinent as

one zone. The first case provides information about the

contribution of local/zonal evapotranspiration toward

precipitation, whereas the second case computes the

contribution of entire subcontinental evapotranspiration.

3. Results and discussion

Here, we present the variability of precipitation recy-

cling estimates and their impact on monsoon precipitation

for different months and zones. First, we discuss the

recycling estimates computed with DRM by considering

11 different zones that cover the Indian subcontinent.

a. Spatial and temporal variation of recycling

To study the spatial and temporal variability of recy-

cling estimates, the climatological mean of regional

recycled precipitation and regional recycling ratio for

different zones are presented in Fig. 3. Here, day 1

corresponds to 1 June, the first day of JJAS. The regional

recycled precipitation increases almost in all the zones

after the onset of the monsoon and decreases toward the

end of the monsoon because of the reduction of pre-

cipitable water in the atmosphere. We observe high re-

gional recycled precipitation in zones 5 (maximum

FIG. 2. Schematic representation of zonal atmospheric fluxes for a single zone. The area of

individual grid is represented by DA.


1.5mmday21), 6 (maximum 1.5mmday21), and 7 (max-

imum 2.5mmday21). The seasonal variation of regional

recycled precipitation in zone 7 is relatively low com-

pared to the other zones, indicating that the regional

source of moisture (i.e., local recycling) during monsoon

season in this zone is stable. High regional recycling ratios

are observed in zones 2, 5, 6, and 7 during JJAS. Higher

values of regional recycling ratio in zones 5 (maximum

0.2), 6 (maximum 0.16), and 7 (maximum 0.17) are due to

the strong land surface feedback through evapotranspi-

ration, whereas the same in zone 2 (maximum 0.25) is due

to low precipitable water. The regional recycling ratio

also increases aftermonsoon onset, with the highest value

during September.

To study the spatial variability of recycling estimates

across different zones, we compare them (Fig. 4) for

summermonsoonmonths.Wefindhigh spatial variability

of the recycling estimates, with the highest amount ob-

served in the northeastern part of the subcontinent and

the lowest amount in northwestern India. High values of

recycled precipitation in zones 6 and 7 (i.e., northeastern

India) indicate the possible influence of land surface

feedback on regional precipitation (Fig. 4). On the con-

trary, such dominant influence of precipitation recycling

is not observed in the remaining zones (Fig. 4). The

precipitation over the Western Ghats (zones 8 and 11),

which receives high monsoon rainfall throughout the

summer monsoon season, is also influenced by pre-

cipitation recycling, but this is not as prominent as in

northeastern India. This is probably because of the

proximity of these zones (i.e., zones 8 and 11) to the

Arabian Sea and the orography of Western Ghats.

Consistently high values of local recycling ratio (.0.15)

aswell as high recycled precipitation (;3mmday21; Fig. 4)

are observed over almost the entire northeastern zones

(zones 6 and 7) during JJAS. These results demonstrate

the influence of local land surface processes in regional

precipitation for these zones. Although the local re-

cycling ratios during September show higher values in

central (;0.15) as well as northern (;0.25) zones, the

amounts of recycled precipitation are comparatively low

in these zones (Fig. 4). Low recycled precipitation in

central India (zone 4) is due to the dominance of ad-

vection of locally evaporated water from other zones.

The northern zones (i.e., zones 1 and 2) receive rela-

tively low recycled precipitation (Fig. 4); however, the

recycling ratio is high because of low precipitable water

(Fig. 5), which is the denominator inEq. (8). The recycled

precipitation in the northwestern zone is very low, and

hence, the recycling ratio is also low. Even the low value

FIG. 3. Climatological mean of (top) recycled precipitation and (bottom) recycling ratio, over

different zones during JJAS. The peak of recycling ratios is observed during September.


of total precipitable water is not sufficient to improve the

ratio for this region. The overall high evapotranspiration

rate (Fig. 5) over northeastern India (zones 6 and 7), in

comparison to the other zones, during the entire summer

monsoon is responsible for high recycling.

The advective moisture from the oceanic sources is

responsible for the monsoon initiation, but the local

moisture through evapotranspiration may enhance the

total amount of precipitation. The peak of total pre-

cipitation is observed during July and August, followed

by a reduction in September. However, the local recy-

cling ratio shows a slightly different pattern of intra-

seasonal variations among different monsoon months

(Fig. 4). The local recycling ratio increases as monsoon

season progresses over the Indian subcontinent, with the

highest amount in September due to increased evapo-

transpiration (Fig. 5). The high recycling ratio (.0.10 in

Fig. 4) over most of the Indian region during September

indicates that local evapotranspiration is an important

factor in sustaining the monsoon. The relatively low

recycling ratio during June and July (when compared

with September) over the northeastern zone (Fig. 4) of

the Indian subcontinent is because of a stronger in-

fluence of oceanic sources with a high amount of ad-

vective moisture.

Figure 6 shows the estimates of regional recycled pre-

cipitation and recycling ratio in different zones for sum-

mer monsoon months. High values of regional recycled

precipitation (;200–400mmday21) as well as regional

recycling ratio (;10%–15%) are observed over zones 5–

7. The low recycling ratio over zones 8–11 (southwestern,

southeastern, and southern regions) are due to the

dominance of oceanic sources (Arabian Sea and Bay of

Bengal) of moisture in the precipitation process. The

total recycled precipitation over the western and north-

ern parts of the Indian subcontinent (i.e., zones 1–3) is

relatively low in comparison to the other zones (Fig. 6).

However, the recycling ratios are on the higher side.

The results for the interior of India, that is, zones 4–7,

do not fully represent the impacts of the entire sub-

continental evapotranspiration. The above-mentioned

results for a specific zone only show the impacts of

FIG. 4. (top) Recycled precipitation (mmday21), (middle) recycling ratio, and (bottom) total precipitation (mmday21) over different

zones during the summer monsoon months (JJAS).


evapotranspiration from the same zone and not the

evapotranspiration from the entire subcontinent. This

motivates us to applyDRMto the entire subcontinent as a

single zone.

b. Impact of the subcontinent’s evapotranspiration onprecipitation recycling

The contribution of the entire subcontinent’s evapo-

transpiration to the monsoon precipitation is studied by

applying DRM and considering the entire subcontinent

as a single zone. The results are compared with those

obtained earlier that considered the entire subcontinent

as 11 different zones. We observe a similar pattern of

intraseasonal variability in recycled precipitation

amount, with an increase during the later half (August

and September) of the monsoon (Fig. 7). Overall, we

find a higher amount of recycled precipitation with this

present approach, specifically in central India and the

Gangetic Plain. However, significant differences are not

observed in northeastern India.

Analyzing the path followed by atmospheric moisture

(water vapor) prior to precipitation is important for

understanding the role of monsoon circulation on pre-

cipitation. Figure 8 shows the mean moisture flux vectors

during the monsoon season (i.e., JJAS) over the entire

subcontinent. The increased moisture circulation over

central India and the Gangetic Plain promotes the use of

water vapor from subcontinental evapotranspiration in

the precipitation process. This explains the occurrences of

high recycled precipitation over the Gangetic Plain dur-

ing August and September (Fig. 7). Small differences

between recycled precipitation in northeastern India

obtained from zonal (Fig. 4) and subcontinental (Fig. 7)

analyses suggest that the higher amount of moisture

resulting from evapotranspiration comes from the same

zone, which is not true for Gangetic Plain. For south-

western India, the source of moisture is theArabian Sea,

and hence, the recycled precipitation is very low. On the

western coast of India, low recycled precipitation and

high total precipitation result in a very low recycling

ratio. The direction of moisture flux vectors over north-

eastern India changes as the monsoon season progresses.

We find that during June and July, it originates from the

Bay of Bengal and propagates toward the continental

FIG. 5. (top) Evapotranspiration (mmday21), (middle) precipitable water (mm), and (bottom) moisture residence time (mmday21) in

the Indian subcontinent during summer monsoon months (JJAS). The overall high values of evapotranspiration over the northeastern

region during JJAS contribute to the higher recycling ratio over this region.


interior, whereas during September it originates from the

western parts of Southeast Asia. Hence, during Septem-

ber a larger amount of land area is being traversed by the

moisture flux prior to the actual precipitation event.

c. Precipitation recycling and monsoon withdrawal

The precipitable water available in the atmosphere is

relatively low during September as compared to June,

July, and August (Fig. 5). However, a higher amount of

evapotranspiration is observed over the entire sub-

continent during September (Fig. 5), which supplies

additional moisture to the atmosphere and hence pro-

vides additional strength to the weakened monsoon. To

investigate the impact of precipitation recycling on mon-

soon withdrawal, we calculate the withdrawal dates of

the southwest monsoon separately by considering total

precipitation (actual) and advective precipitation in-

dependently. Here, we define monsoon withdrawal as

the cessation of rainfall activity over the area for a con-

tinuous 5 days after 1 September. Figure 9 shows the

mean difference in days, that is, prolongation, between

advective precipitation withdrawal and total pre-

cipitation withdrawal. Here, the method for computing

withdrawal date has the limitation that it does not con-

sider important factors and indicators such as wind

shear, vertically integrated moisture transport, outgoing

longwave radiation, etc. The result (Fig. 9) shows that

precipitation recycling is responsible for delaying of

southwest monsoon withdrawal over the northeastern

(;3–5 days) and eastern regions (;2–3 days). Hence, it

prolongs the monsoon over these regions for a few more

days. We do not find the impact of precipitation recycling

in delaying the monsoon withdrawal for other regions.

d. Trends of recycled precipitation

We study the trends of recycling estimates at the 95%

significance level. Figure 10 shows the trends of recycled

precipitation, moisture residence time, and total pre-

cipitation.Weobserve increasing trends for June and July

recycled precipitation at the 95% significance level in

zones 5 and 6. This shows that the impacts of land sur-

face feedbacks on monsoon rainfall are becoming more

prominent in these zones. We find a decreasing trend of

recycled precipitation in zone 7 despite the absence of

any trend in total precipitation, which indicates the

weakening of land surface feedback in northeastern In-

dia. Decreasing trends of recycled precipitation, total

precipitation, and moisture residence time (Fig. 10) are

observed during August over the central region. The re-

cycled precipitation andmoisture residence time (Fig. 10)

in the central zone (i.e., zone 4) during September also

have a decreasing trend, but the same is not present in

total precipitation.

e. Precipitation recycling during the strongest andweakest monsoon years

To understand the sensitivity of the strength of mon-

soon on recycled precipitation, we analyze the results for

the strongest and weakest monsoon years from the se-

lected duration of 1980–2010. Figure 11 shows the vari-

ation in monsoon rainfall for different years. We observe

that 1987 is the weakest monsoon year and 1988 is the

strongest. Figure 12 shows the local recycling ratio and

recycled precipitation for September during these two

years. We observe a higher local recycling ratio over the

entire subcontinent during September of the weakest

FIG. 6. Interzonal variation of (top) recycled precipitation and (bottom) regional recycling ratio during the summermonsoon. Zone 7 has the

highest recycled precipitation in northeastern India. Higher recycling ratios are observed during September in all the zones except 1 and 2.


monsoon year in comparison with the strongest mon-

soon year. It is important to note that the year 1987 was

an El Niño year, as described by the National WeatherService Climate Prediction Center (Climate Prediction

Center 2014), as well as a drought year, as classified

by the IMD. The year 1988 was a La Niña year withabove-normal summermonsoon rainfall. Here, we selectSeptember for comparison because of high recyclingestimates during this month. A relatively high amount ofrecycled precipitation is observed during the strongestmonsoon year. Although, the amount of recycled pre-cipitation is low during the weakest monsoon, the re-cycling ratio is on the higher side.The results obtained in the present study show a sim-

ilar pattern, when compared with the results presented

in earlier literature for the United States. Dirmeyer and

Brubaker (1999) investigated the source of moisture for

precipitation over the Mississippi River basin during

1988 (drought) and 1993 (flood) using a quasi-isentropic

back trajectories scheme. It was observed that terrestrial

moisture plays a significant role in precipitation with

contributions of 41% (1988) and 33% (1993). Bosilovich

et al. (2003) showed the importance of local moisture

sources over the United States using water vapor

tracers. The wettest monsoon observed has more con-

tinental evaporative sources than a drier monsoon.

Bosilovich and Schubert (2001) investigated precipitation

recycling over the central United States during the

wettest and driest years, using the bulk recycling model

of Eltahir and Bras (1994). The authors indicated that

the wettest period (flood during 1993) is associated with

a relatively low recycling ratio (maximum 30%) as

compared to the dry period (maximum 60% during the

drought of 1988). The present study shows a similar

pattern of recycling ratio over the Indian subcontinent

(Fig. 12), where weaker oceanic moisture transport in

the weakest monsoon year 1987 is associated with a high

recycling ratio and vice versa. Dominguez and Kumar

(2008) used DRM and showed that the feedback

through evapotranspiration during the low rainfall pe-

riod provides the extra moisture for the precipitation

over the U.S. plains ecoregion, and hence, precipitation

FIG. 7. As in Fig. 4, but for application of DRM considering the entire subcontinent as one zone.


recycling provides the stability to the seasonal rainfall.

Similarly, evapotranspiration over the Indian sub-

continent during a low rainfall period (i.e., September)

is responsible for a higher recycling ratio, and thus, it

strengthens the monsoon rainfall (Fig. 7).

4. Conclusions

We analyze the impact of local and subcontinental

evapotranspiration on regional precipitation character-

istics. The results show the potential impacts of land

surface feedbacks through evapotranspiration on re-

gional precipitation variability. This analysis reveals that

precipitation recycling is an integral part of monsoon

rainfall. The increase in soil wetness after the onset of

monsoon increases evapotranspiration in the summer

monsoon season, which in turn is responsible for a

higher recycling ratio.We find that the significant amount

of precipitation comes from precipitation recycling in the

Gangetic Plain and northeastern India. However, south-

ern, western, and southeastern parts receive less recycled

precipitation, owing to dominance of oceanic moisture

and high advective moisture transport. The high regional

recycling ratios for almost all years over zones 6 and 7

(eastern and northeastern India) suggest a strong role of

land surface in the generation of precipitation over that

zone. The recycling ratio as well as recycled precipitation

over northeastern India is found to be consistently higher

(during JJAS) as compared to other zones, with the

highest value observed during September. The increased

recycled precipitation during September provides addi-

tional strength to the weakened monsoon, and it is also

FIG. 8. Moisture flux vectors during JJAS over the Indian subcontinent. Local moisture contributes significantly to

precipitation over central and northeastern India.


responsible for delaying the monsoon withdrawal over

the eastern and northeastern zones.

The role of precipitation recycling in providing

strength to the overall rainfall, as discussed by Dirmeyer

and Brubaker (1999), Bosilovich and Schubert (2001),

Bosilovich et al. (2003), and Dominguez and Kumar

(2008) over the central U.S. region and Dominguez et al.

(2008) over the North American monsoon region, is also

observed over the Indian subcontinent. Furthermore,

the weakest monsoon is observed to have a high re-

cycling ratio when compared with strongest monsoon,

consistent with prior studies. The high recycling ratio

during the weakest period is due to the low availability of

precipitable water.

The DRM used in this study is based on the assump-

tion of well-mixed atmospheric conditions. This may not

be always true for the Indian monsoon, and this is a

possible limitation of the present study. Lettau et al.

(1979), Burde (2006), and Burde et al. (2006) addressed

the issue of incomplete vertical mixing of water vapor in

the atmosphere by using a dimensionless parameter K

[Eqs. (3.5) and (3.13) in Burde (2006)]. The estimation of

parameterK involves usage of the ratios Pm/P andwm/w,

which are generally obtained from a GCM WVT exper-

iment. The involvement of a GCM WVT experiment

output may increase the accuracy of the recycling esti-

mate, but they are computationally expensive.

The DRM, like any other two-dimensional approxima-

tion model, neglects the effect of the vertical distribution

of moisture. The inhomogeneities in wind are normally

generated because of the presence of directional wind

shear, and as a result, there can be incomplete or weak

mixing ofwater vapor.Goessling andReick (2012) showed

the importance of incomplete vertical mixing due to di-

rectional wind shear in vertical levels. The study showed

that the two-dimensional approximation models are less

accurate over tropical regions than extratropical regions,

where the effect of directional shear is at its maximum.

FIG. 9. Impacts of precipitation recycling on summer monsoon withdrawal. Precipitation

recycling delays the monsoon withdrawal in northeastern and eastern India.


Van der Ent et al. (2013) also showed that the as-

sumption of well-mixed water vapor has the largest in-

fluence on the results over the tropics, when compared

using three different tracking methods, namely, regional

climate model (RCM) tagging, water accounting model

(WAM), and three-dimensional trajectories analysis.

RCM tagging, which includes all of the atmospheric

processes, gives more accurate results when compared

with the other two approaches that are based on the

well-mixed assumption. However, the study also con-

cluded that the effect due to incomplete mixing

of water vapor is not significant over the Indian

region. The modification of the well-mixed atmosphere

assumption by allowing the effect due to ‘‘fast recycling’’

FIG. 10. Trends of (top) recycled precipitation, (middle) moisture residence time, and (bottom) total precipitation in India during the

summer monsoon months. The trends are computed at the 95% significance level. Decreasing trends of recycled precipitation are

observed over northeastern India during JJAS.

FIG. 11. JJAS total recycled precipitation and total precipitation for the period 1980–2010. Highest and lowest

monsoon rainfalls are observed during 1988 and 1987, respectively.


(Lettau et al. 1979, page 231) can further improve the

accuracy; hence, a future attempt can bemade to improve

the analysis.

The topography of the region may also play an im-

portant role in enhancing the recycling ratio and recy-

cled precipitation. The Himalayan mountain ranges are

possibly responsible for moisture circulation within the

subcontinent resulting in a high recycling ratio in the

central and northeastern regions. Such a hypothesis may

be tested with model-based analysis. It should be noted

that, while computing the moisture flux, we have con-

sidered the pressure levels from 1000 to 300mb. How-

ever, for the Himalayan mountainous region, the

elevation is too high as compared to 1000mb. This is a

major limitation of the present analysis, and consider-

ation of orography in DRM may be considered as an

area of future research.

The recycling ratio for mountainous regions (western

coast and northeastern India), with a high precipitation

amount and spatial variability, may be sensitive to the

spatial resolution, and coarse-resolution data may fail to

capture orographic effects. However, precipitation on the

western coast (Western Ghats mountainous region) pri-

marily results from oceanic sources, and hence, a major

difference in recycled precipitation may not be expected

with changes in spatial resolution. The effect of resolution

may be prominent in the computed recycled precipitation

of the northeastern region because of high orography and

FIG. 12. (a),(b) Recycling ratio and (c),(d) recycled precipitation in India during September of the weakest (1987)

and strongest monsoon (1988) years. A higher amount of recycled precipitation is observed during the strongest

monsoon year over all of India.


recycling ratio, and the study of such sensitivity may be

considered as a potential future research area.

Acknowledgments.The authors sincerely acknowledge

Francina Dominguez, University of Arizona, for her

suggestions on this work. The first author thanks Beas

Barik for her help in editing the manuscript.

REFERENCES

Asharaf, S., A. Dobler, and B. Ahrens, 2011: Soil moisture ini-

tialization effects in the Indian monsoon system. Adv. Sci.

Res., 6, 161–165, doi:10.5194/asr-6-161-2011.

Bellon, G., 2010: Monsoon intraseasonal oscillation and land–

atmosphere interaction in an idealized model. Climate Dyn.,

37, 1081–1096, doi:10.1007/s00382-010-0893-0.

Bosilovich,M. G., and S. D. Schubert, 2001: Precipitation recycling

over the central United States diagnosed from the GEOS-1

Data Assimilation System. J. Hydrometeor., 2, 26–35,

doi:10.1175/1525-7541(2001)002,0026:PROTCU.2.0.CO;2.

——, and ——, 2002: Water vapor tracers as diagnostics of the

regional hydrologic cycle. J. Hydrometeor., 3, 149–165,

doi:10.1175/1525-7541(2002)003,0149:WVTADO.2.0.CO;2.

——,Y. C. Sud, S. D. Schubert, andG. K.Walker, 2003: Numerical

simulation of the large-scale North American monsoon water

sources. J.Geophys. Res., 108, 8614, doi:10.1029/2002JD003095.

Brubaker, K. L., D. Entekhabi, and P. S. Eagleson, 1993: Estima-

tion of continental precipitation recycling. J. Climate, 6, 1077–

1089, doi:10.1175/1520-0442(1993)006,1077:EOCPR.2.0.CO;2.

Budyko, M. I., 1974: Climate and life. Academic Press, 508 pp.

Burde, G. I., 2006: Bulk recycling models with incomplete vertical

mixing. Part I: Conceptual framework and models. J. Climate,

19, 1461–1472, doi:10.1175/JCLI3687.1.——, and A. Zangvil, 2001: The estimation of regional precipitation

recycling. Part II: A new recycling model. J. Climate, 14, 2509–

2527, doi:10.1175/1520-0442(2001)014,2509:TEORPR.2.0.CO;2.

——, C. Gandush, and Y. Bayarjargal, 2006: Bulk recycling models

with incomplete vertical mixing. Part II: Precipitation re-

cycling in the Amazon basin. J. Climate, 19, 1473–1489,

doi:10.1175/JCLI3688.1.

Climate Prediction Center, cited 2014: Historical El Niño/La Niñaepisodes (1950–present). [Available online at www.cpc.ncep.noaa.

gov/products/analysis_monitoring/ensostuff/ensoyears.shtml.]

Dee, D., and Coauthors, cited 2014: The Climate Data Guide: At-

mospheric reanalysis: Overview and comparison tables. [Avail-

able online at https://climatedataguide.ucar.edu/climate-data/

atmospheric-reanalysis-overview-comparison-tables.]

Dirmeyer, P. A., and J. Shukla, 1993: Observational and modeling

studies of the influence of soil moisture anomalies on the atmo-

spheric circulation.Predictions of Interannual Climate Variations,

J. Shukla, Ed., NATO Series: I, Vol. 6, Springer-Verlag, 1–23.

——, and K. L. Brubaker, 1999: Contrasting evaporative moisture

sources during the drought of 1988 and the flood of 1993.

J.Geophys. Res., 104, 19 383–19 398, doi:10.1029/1999JD900222.

Dominguez, F., and P. Kumar, 2008: Precipitation recycling vari-

ability and ecoclimatological stability—A study using NARR

data. Part I: Central U.S. plains ecoregion. J. Climate, 21,

5165–5186, doi:10.1175/2008JCLI1756.1.

——, ——, X. Liang, and M. Ting, 2006: Impact of atmospheric

moisture storage on precipitation recycling. J. Climate, 19,

1513–1530, doi:10.1175/JCLI3691.1.

——, ——, and E. R. Vivoni, 2008: Precipitation recycling vari-

ability and ecoclimatological stability—A study using NARR

data. Part II: North American monsoon region. J. Climate, 21,

5187–5203, doi:10.1175/2008JCLI1760.1.

Eltahir, E. A. B., and L. B. Bras, 1994: Precipitation recycling in the

Amazon basin. Quart. J. Roy. Meteor. Soc., 120, 861–880,

doi:10.1002/qj.49712051806.

——, and ——, 1996: Precipitation recycling. Rev. Geophys., 34,

367–378, doi:10.1029/96RG01927.

Environmental Modeling Center, 2010: NCEP Climate Forecast

System Reanalysis (CFSR) selected hourly time-series

products, January 1979 to December 2010. Research Data

Archive at the National Center for Atmospheric Research,

Computational and Information Systems Laboratory, Boul-

der, CO. [Available online at http://rda.ucar.edu/datasets/

ds093.1.]

Gadgil, S., 2003: Indian monsoon and its variability.

Annu. Rev. Earth Planet. Sci., 31, 429–467, doi:10.1146/

annurev.earth.31.100901.141251.

——, and P. V. Joseph, 2003: On breaks of the Indian monsoon.

J. Earth Syst. Sci., 112, 529–558, doi:10.1007/BF02709778.

Gimeno, L., A. Drumond, R. Nieto, R. M. Trigo, and A. Stohl,

2010: On the origin of continental precipitation.Geophys. Res.

Lett., 37, L13804, doi:10.1029/2010GL043712.

——, and Coauthors, 2012: Oceanic and terrestrial sources of con-

tinental precipitation. Rev. Geophys., 50, RG4003, doi:10.1029/

2012RG000389.

Goessling, H. F., and C. H. Reick, 2012: Atmospheric water

vapour tracers and the significance of the vertical dimension.

Atmos. Chem. Phys. Discuss., 12, 30 119–30 176, doi:10.5194/

acpd-12-30119-2012.

Higgins, W., and D. Gochis, 2007: Synthesis of results from the

North American Monsoon Experiment (NAME) process

study. J. Climate, 20, 1601–1607, doi:10.1175/JCLI4081.1.Krishnamurthy, V., and J. L. Kinter III, 2003: The Indian mon-

soon and its relation to global climate variability. Global

Climate, X. Rodó and F. A. Comín, Eds., Springer-Verlag,186–236.

——, and J. Shukla, 2007: Intraseasonal and seasonally persisting

patterns of Indian monsoon rainfall. J. Climate, 20, 3–20,

doi:10.1175/JCLI3981.1.

Lawrence, D. M., and P. J. Webster, 2001: Interannual varia-

tions of the intraseasonal oscillation in the South Asian

summer monsoon region. J. Climate, 14, 2910–2922,

doi:10.1175/1520-0442(2001)014,2910:IVOTIO.2.0.CO;2.

Lettau, H., K. Lettau, and L. C. B. Molion, 1979: Amazonia’s

hydrologic cycle and the role of atmospheric recycling in as-

sessing deforestation effects. Mon. Wea. Rev., 107, 227–238,

doi:10.1175/1520-0493(1979)107,0227:AHCATR.2.0.CO;2.

Meehl, G. A., 1994: Influence of land surface in the Asian summer

monsoon: External conditions versus internal feedbacks.

J. Climate, 7, 1033–1049, doi:10.1175/1520-0442(1994)007,1033:

IOTLSI.2.0.CO;2.

Merrill, J. T., R. Bleck, and D. Boudra, 1986: Techniques of La-

grangian trajectory analysis in isentropic coordinates. Mon.

Wea. Rev., 114, 571–581, doi:10.1175/1520-0493(1986)114,0571:

TOLTAI.2.0.CO;2.

Peel, M. C., B. L. Finlayson, and T. A. McMahon, 2007: Updated

worldmapof theKoppen–Geiger climate classification.Hydrol.

Earth. Syst. Sci., 11, 1633–1644, doi:10.5194/hess-11-1633-2007.

Rajeevan,M., S. Gadgil, and J. Bhate, 2010:Active and break spells

of Indian summer monsoon. J. Earth. Syst. Sci., 119, 229–247,

doi:10.1007/s12040-010-0019-4.


http://dx.doi.org/10.5194/asr-6-161-2011

http://dx.doi.org/10.1007/s00382-010-0893-0

http://dx.doi.org/10.1175/1525-7541(2001)002<0026:PROTCU>2.0.CO;2

http://dx.doi.org/10.1175/1525-7541(2002)003<0149:WVTADO>2.0.CO;2

http://dx.doi.org/10.1029/2002JD003095

http://dx.doi.org/10.1175/1520-0442(1993)006<1077:EOCPR>2.0.CO;2

http://dx.doi.org/10.1175/JCLI3687.1

http://dx.doi.org/10.1175/1520-0442(2001)014<2509:TEORPR>2.0.CO;2


http://www.cpc.ncep.noaa.gov/products/analysis_monitoring/ensostuff/ensoyears.shtml

http://www.cpc.ncep.noaa.gov/products/analysis_monitoring/ensostuff/ensoyears.shtml

https://climatedataguide.ucar.edu/climate-data/atmospheric-reanalysis-overview-comparison-tables

https://climatedataguide.ucar.edu/climate-data/atmospheric-reanalysis-overview-comparison-tables

http://dx.doi.org/10.1029/1999JD900222

http://dx.doi.org/10.1175/2008JCLI1756.1


http://dx.doi.org/10.1175/2008JCLI1760.1

http://dx.doi.org/10.1002/qj.49712051806

http://dx.doi.org/10.1029/96RG01927

http://rda.ucar.edu/datasets/ds093.1

http://rda.ucar.edu/datasets/ds093.1

http://dx.doi.org/10.1146/annurev.earth.31.100901.141251

http://dx.doi.org/10.1146/annurev.earth.31.100901.141251

http://dx.doi.org/10.1007/BF02709778

http://dx.doi.org/10.1029/2010GL043712

http://dx.doi.org/10.1029/2012RG000389

http://dx.doi.org/10.1029/2012RG000389

http://dx.doi.org/10.5194/acpd-12-30119-2012

http://dx.doi.org/10.5194/acpd-12-30119-2012



http://dx.doi.org/10.1175/1520-0442(2001)014<2910:IVOTIO>2.0.CO;2

http://dx.doi.org/10.1175/1520-0493(1979)107<0227:AHCATR>2.0.CO;2

http://dx.doi.org/10.1175/1520-0442(1994)007<1033:IOTLSI>2.0.CO;2

http://dx.doi.org/10.1175/1520-0442(1994)007<1033:IOTLSI>2.0.CO;2

http://dx.doi.org/10.1175/1520-0493(1986)114<0571:TOLTAI>2.0.CO;2

http://dx.doi.org/10.1175/1520-0493(1986)114<0571:TOLTAI>2.0.CO;2

http://dx.doi.org/10.5194/hess-11-1633-2007

http://dx.doi.org/10.1007/s12040-010-0019-4

Saha, S., and Coauthors, 2010: TheNCEPClimate Forecast System

Reanalysis. Bull. Amer. Meteor. Soc., 91, 1015–1057,

doi:10.1175/2010BAMS3001.1.

Saha, S.K., S.Halder,A. Suryachandrarao, andB.N.Goswami, 2012:

Modulation of ISOs by land–atmosphere feedback and contri-

bution to the interannual variability of Indian summermonsoon.

J. Geophys. Res., 117, D13101, doi:10.1029/2011JD017291.

Shukla, J., and Y. Mintz, 1982: Influence of land-surface evapo-

transpiration on the earth’s climate. Science, 215, 1498–1501,

doi:10.1126/science.215.4539.1498.

Stohl, A., and P. James, 2004: A Lagrangian analysis of the

atmospheric branch of the global water cycle. Part I:

Method description, validation, and demonstration for

the August 2002 flooding in central Europe. J. Hydrome-

teor., 5, 656–678, doi:10.1175/1525-7541(2004)005,0656:

ALAOTA.2.0.CO;2.

——, and ——, 2005: A Lagrangian analysis of the atmospheric

branch of the global water cycle. Part II: Moisture trans-

ports between Earth’s ocean basins and river catchments.

J. Hydrometeor., 6, 961–984, doi:10.1175/JHM470.1.

Tuinenburg, O.A., R.W.A.Hutjes, and P. Kabat, 2012: The fate of

evaporated water from the Ganges basin. J. Geophys. Res.,

117, D01107, doi:10.1029/2011JD016221.

van der Ent, R. J., H. G. Savenije, B. Schaefli, and S. C. Steele-

Dunne, 2010: Origin and fate of atmospheric moisture over

continents. Water Resour. Res., 46, W09525, doi:10.1029/

2010WR009127.

——, O. Tuinenburg, H.-R. Knoche, H. Kunstmann, and

H. Savenije, 2013: Should we use a simple or complex model

for moisture recycling and atmospheric water tracking?

Hydrol. Earth Syst. Sci., 17, 4869–4884, doi:10.5194/

hess-17-4869-2013.

Wang, B., 2006: The Asian Monsoon. Praxis Publishing, 459 pp.

Watts, C. J., R. Scott, J. Garatuza-Payan, J. C. Rodriguez, J. H.

Prueger, W. P. Kustas, and M. Douglas, 2007: Changes in

vegetation condition and surface fluxes during NAME 2004.

J. Climate, 20, 1810–1820, doi:10.1175/JCLI4088.1.

Yasunari, T., 2007: Role of land–atmosphere interaction on Asian

monsoon climate. J. Meteor. Soc. Japan, 85B, 55–75,

doi:10.2151/jmsj.85B.55.


http://dx.doi.org/10.1175/2010BAMS3001.1

http://dx.doi.org/10.1029/2011JD017291

http://dx.doi.org/10.1126/science.215.4539.1498

http://dx.doi.org/10.1175/1525-7541(2004)005<0656:ALAOTA>2.0.CO;2

http://dx.doi.org/10.1175/1525-7541(2004)005<0656:ALAOTA>2.0.CO;2

http://dx.doi.org/10.1175/JHM470.1

http://dx.doi.org/10.1029/2011JD016221

http://dx.doi.org/10.1029/2010WR009127

http://dx.doi.org/10.1029/2010WR009127




http://dx.doi.org/10.2151/jmsj.85B.55

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