Short Paper Journal of Agricultural Meteorology 71 (1): 15-23, 2015

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Sunshine duration is declining in Nepal across the period from 1987 to 2010 Neelam NIROULA a , Kazuhiko KOBAYASHI a, , and Jianqing XU b

a Graduate school of Agricultural and Life Sciences, The University of Tokyo, Yayoi 1-1-1, Bunkyo-Ku, Tokyo 113-8657, Japan b Center for Research in Isotopes and Environmental Dynamics (CRiED), University of Tsukuba, Tennoudai 1-1-1, Tsukuba 305-

8577, Japan

Abstract We analyzed temporal changes of sunshine duration (SSD) and number of rainy days (NRD) in Nepal across its three

physiographic regions: plains, low-hills, and high-hills and mountains for the period from 1987 to 2010 from records at 13 meteorological stations. We found declining trends in SSD (i.e., solar dimming) across Nepal at a rate of 0.20% per year, with the highest decline occurring during the post-monsoon season (0.33% per year), followed by the pre-monsoon season (0.24% per year). A close look at individual stations indicated that declines in pre- and post-monsoon seasons are common regional phenomena. By region, dimming was pronounced (0.56% per year) in the plains at 0300 m above sea level and gradually diminished as elevation rose. The NRD for the same 13 stations showed a significant de-clining trend (0.20% per year), which suggests that the change in NRD is not a major driver of the decreased SSD in Nepal. We argue that the decline in SSD might be influenced by transboundary air pollution from the Indian subcontinent and biomass burning across the region as suggested by other studies.

Key words: Air pollution, Atmospheric brown clouds, Biomass burning, Nepal, Solar radiation.

1. Introduction

Solar radiation (SR) is the ultimate source of energy for life on Earth. It governs a wide range of physical and ecological process-es such as surface energy exchange, snow and glacier melt, photo-synthesis, and associated plant growth (Wild, 2009). On a more applied level, SR knowledge is crucial for solar energy technolo-gies and agricultural production.

Long-term observations of SR flux at the Earths surface across the globe have revealed significant changes in SR on decadal time scales: a widespread reduction in SR, or global dimming, from the 1950s to the late 1980s (Stanhill and Cohen, 2001; Liepert, 2002) followed by a sustained increase, or global brightening (Wild et al., 2005; Wild, 2009). Atmospheric aerosols from anthropogenic air pollution, as well as the subsequent change in the optical prop-erties of clouds and aerosol-cloud interactions, are considered to be the most probable cause of these changes (Stanhill and Cohen, 2001; Streets et al., 2006). Despite global brightening, dimming has persisted in the rapidly developing country of India, coherent with its increased aerosol emissions (Padma Kumari et al., 2007; Wild et al., 2009). These aerosols form thick layers of haze, termed atmospheric brown clouds (ABC), particularly during dry seasons, and block SR from reaching the surface, thereby causing dimming in India (Ramanathan et al., 2001; Padma Kumari et al., 2007). ABC from India are further transported to reach the Hima-layas in Nepal (Ramanathan et al., 2007; Bonasoni et al., 2008), where they possibly alter the regions climate and hydrology (Bonasoni et al., 2012). In addition to transboundary pollution, local air pollution has also increased in major cities in Nepal. Vehicular emissions in urban areas have, for example, increased

drastically, given the 20-fold increase in the number of vehicles from 1990 to 2013 (Department of Transport Management, 2014). Despite evidence of dimming due to increased air pollution (Qian et al., 2007; Soni et al., 2012), changes in Nepals SR have not yet been studied under the intensifying local and regional air pol-lution. Changes in SR, if any, are particularly crucial for Nepal, where the livelihood of a majority of the population depends on the local ecosystem provisions, for which the solar input is the sole energy source.

Though global dimming and brightening have been detected primarily by SR measurements, proxies such as sunshine duration (SSD), cloud cover, and pan-evaporation corroborate the pres-ence of these effects (Sanchez-Lorenzo et al., 2008; Kitsara et al., 2012; Raichijk, 2012). SSD, defined as the period during which direct solar irradiance exceeds 120 W m2 each day (WMO, 2003), is one of the oldest, most robust measures to use as a proxy of SR. Since it can be recorded without using electricity or auto-matic data loggers, its observation is far more prevalent than that of SR in developing countries such as Nepal. This paper is the first attempt to study temporal changes in SR by analyzing SSD over an extended period in Nepal.

2. Methodology

2.1 The study area Located between 26.2530.5 north and 80.088.25 east, Ne-

pal is a landlocked mountainous country in South Asia. With the exception of the Himalayas as its northern border with China, Nepal is bordered by India on all other sides (Fig. 1). Elevation across Nepal ranges from 65 m above sea level (m a.s.l.) in the plains to more than 8,000 m a.s.l. in the high Himalayas, including Mount Everest (8,848 m a.s.l.). The mountains that cover about 83% of the total land area in Nepal play a vital role in the Indian summer monsoon environment by protecting the Indian subconti-nent from the dry, cold air masses of central Asia and blocking the

Received; June 16, 2014. Accepted; October 9, 2014. Corresponding Author: aclasman@mail.ecc.u-tokyo.ac.jp DOI: 10.2480/agrmet.D-14-00025

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warm, moist airflow from the Indian Ocean (Shrestha et al., 2012). This monsoon is crucial for the climate and agriculture of Nepal, which experiences four distinct seasons: the winter (De-cemberFebruary), pre-monsoon (MarchMay), monsoon (JuneSeptember), and post-monsoon (October and November) seasons.

2.2 Weather records and analysis Records of SSD from the start of measurements taken in 1987

up to 2010 were obtained from 16 meteorological stations within the Department of Hydrology and Meteorology (DHM) in Nepal. In this study, we used data from 13 of the 16 stations (Fig. 1). Data from three other stations were omitted due to the brevity of

Fig. 1. Map of Nepal, showing location of the meteorological stations, the three physiographic regions and five development regions. The names of the stations are abbreviated with the first three characters except for the station Dhankuta (DHK). See Table 1 for details of the stations.

Table 1. Details of the observation records of precipitation and sunshine duration.

Station name Elevation (m a.s.l.)

Latitude (degree decimal North)

Longitude (degree decimal East)

Duration of pre-cipitation record

Duration of SSD record

Fraction of miss-ing data in SSD

Biratnagar 72 26.48 87.27 1980-2009 1990-2010 23%

Bhairawaha 109 27.52 83.43 1980-2009 1997-2010 28%

Simara 130 27.17 84.98 1980-2009 1997-2010 6%

Dhangadi 187 28.80 80.55 1980-2009 1994-2010 17%

Dipayal 720 29.23 80.93 1982-2009 1997-2010 26%

Surkhet 720 28.60 81.62 1980-2009 1991-2010 19%

Pokhara 827 28.22 84.00 1980-2009 1987-2010 24%

Dhankuta 1210 26.98 87.35 1980-2009 1991-2009 31%

Kathmandu 1337 27.70 85.37 1980-2009 1991-2010 2%

Okhaldhunga 1720 27.32 86.50 1980-2009 1991-2010 24%

Taplejung 1732 27.35 87.67 1980-2009 1991-2010 26%

Dadeldhura 1848 29.30 80.58 1980-2009 1991-2010 30%

Jumla 2300 29.28 82.17 1980-2009 1988-2010 26%

SSD: sunshine duration; m a.s.l.: meters above sea level.

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the observation periods in Nepalgunj and Khumaltar, as well as to obstruction in sunshine observation caused by trees surrounding the Ghorai station. Since the span of records varies by station and given the limited number of stations, we have used all data regard-less of the length of the observation period (Table 1). SSD data used in this study were available as daily total of SSD in hours.

As preliminary quality control, SSD data from the 13 stations were inspected (1) to remove gross errors (e.g., SSD registered for more than the maximum possible duration), (2) to evaluate the consistency of calendar dates (days per year or month), and (3) to remove suspicious values (e.g., negative or continuous values of 0 or 0.1 for an entire month). Some gaps in the SSD data records during the study period (Table 1) ranged from a few days to a few years. For months with complete daily values, monthly SSD was calculated as the sum of daily values (WMO, 2011). However, for months with missing daily values, up to two missing daily values were tolerated, which is consistent with Good (2009). Each monthly total was adjusted to account for the

missing day(s) by using average SSD across all other days in the month. Each monthly total was then calculated as the sum of available daily values and filled missing values. Months with more than two missing daily values were excluded and considered to be missing. SSD should be affected by cloud cover whose in-crease reduces SR (Dessler, 2010). To understand the influence of cloud cover on SSD, number of days with > 0 mm rainfall was used as a proxy of cloud cover since such data were unavailable. NRD was calculated from precipitation records obtained from the DHM for all 13 stations (Table 1). There were no gaps in precipi-tation data, and monthly total NRD was calculated as the total number of rainy days per month.

For the geographical analysis of this study, we classified the study area into three physiographic regions based on elevation: plains (below 300 m a.s.l.), low hills (LH; 3011500 m a.s.l.) and high hills and mountains (HHM; above 1500 m a.s.l.), as shown in Fig. 1. The division by elevation was adapted from the Water and Energy Commission Secretariat (2010), which is

Table 2. All-Nepal annual mean of daily total sunshine duration (SSD, hour), monthly total SSD (hour) and inter-annual trends (%/year) in SSD and number of rainy days (NRD) across the stations and physiographic regions for the period 1987-2010 (SSD) and 1980-2009 (NRD).

Regions Station name Mean daily total SSD (hour) Mean monthly total SSD (hour)

Inter-annual trend of monthly total SSD (%/year)a

Inter-annual trend of monthly total NRD (%/year) a

Biratnagar 7.0 212.9 0.71** 0.15

Bhairawaha 7.2 220.3 0.35 0.18

Simara 7.4 224.8 0.19 0.25

Dhangadi 7.2 217.9 0.95*** 0.30

Plains 7.2 219.0 0.56*** 0.01

Dipayal 6.9 210.8 0.53 0.32

Surkhet 7.4 223.9 0.36** 0.72***

Pokhara 6.5 198.1 0.06 0.11

Dhankuta 6.8 207.3 0.17 0.62**

Kathmandu 6.1 186.1 0.32* 0.16

Low-hills 6.7 205.3 0.09 0.35***

Okhaldhunga 6.2 188.7 0.30 0.06

Taplejung 6.1 185.4 0.03 0.02

Dadeldhura 7.3 221.5 0.09 0.42

Jumla 7.1 216.4 0.31* 0.27

High-hills & moun-tains

6.7 203.0 0.05 0.17

All-Nepal 6.9 209.1 0.20*** 0.20***

a. Statistical significance of the trends are shown by *** for P

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widely accepted among similar divisions proposed for Nepal. All stations were then categorized by physiographic region based on elevation. Trend analysis for both SSD and NRD was performed for individual stations and physiographic regions across all four seasons. Statistical analysis was performed using JMP statistical software (SAS Institute, Cary, NC, USA). Monthly total SSD and NRD values were used to generate annual, regional, and seasonal trends by fitting linear models. Trend significance was confirmed at a p value of 0.05. While fitting the model, the interaction be-tween stations and years was tested; a lack of significant interac-tion suggested a trend common across stations, while significant interaction suggested a difference in trends among them. Trends were ultimately expressed as percentage changes in SSD and NRD. All maps presented in this study were created using ArcGIS 10.1 (ESRI, Redlands, CA, USA). The Kriging interpolation technique was applied to create the distribution maps. It is a geo-statistical method involving statistical techniques to analyze and predict spatial distribution pattern of a variable and is recom-mended as the best interpolation algorithm for environmental variables (Fortner, 1995; Gorai et al., 2014).

3. Results

3.1 Station-based, regional, and all-Nepal annual SSD trends Table 2 shows the annual means of daily total, monthly total,

and inter-annual trends for all individual stations, for the three physiographic regions, and for Nepal in general. For individual stations, daily total SSD varied from 6.1 h at Taplejung in the HHM to 7.4 h at Simara in the plains. Regionally, daily total and monthly total SSD were highest in the plains, followed by those in the LH and HHM. All-Nepal values for daily total and monthly total SSD were 6.9 h and 209.1 h, respectively.

Most stations showed decreasing trends in monthly total SSD, though a few showed increasing trends. Among stations, Bi-ratnagar and Dhangadi in the plains and Surkhet and Kathmandu in the LH showed maximum decline, with the highest decrease rate of 0.95% per year occurring in Dhangadi. By contrast, Jumla in the HHM showed a significant increasing trend. Regionally, the highest decline in SSD was observed in the plains, followed by the LH, while the HHM showed increasing trends. These regional trends indicate that a reduction in SSD has been prominent in the plains and that the decline gradually diminished with increasing elevation. From 19872010, Nepal experienced a significant de-cline in SSD at an average rate of 0.20% per year.

Stations in the plains and LH showed a common declining trend (Figs. 2a and 2b), which lacked a significant interaction between years and stations in both the plains (P = 0.088) and LH (P = 0.076) (Table 3). These results indicate that the declines in SSD at stations in the plains and LH have been influenced by a phe-nomenon occurring on not a local, but a regional scale. By con-trast, a significant interaction was observed in the HHM, suggest-ing a difference in temporal trends among the stations (Fig. 2c). In the HHM, Okhaldhunga showed a decline while Jumla showed a significant increase. 3.2 Seasonal SSD trends and distribution across regions

Significant variation in SSD was observed in all months across Nepal. Mean daily total SSD ranged from 4.5 h in July to a peak of 8.4 h in April (Fig. 3). All-Nepal and regional SSD trends varied from season to season (Table 4). For all of Nepal, dim-ming was observed in all seasons except winter, whereas among regions, the plains experienced a decreasing trend in all seasons. Overall, dimming was most pronounced in the post- and pre-monsoon seasons. The gradual shift from a negative to a positive trend as we moved from the plains to regions of higher altitude was distinct in the winter. The significant positive trend in the winter also contributed to the regional positive trend in the HHM, while for the monsoon season, a decline in SSD was seen in all regions, though neither trend was significant. As observed among regional trends, the station-by-year interaction for seasonal trends was also not significant, which suggests that changes in SSD ob-served in different seasons might have also been induced by a common regional phenomenon.

The spatial distribution of SSD trends from 1987 to 2010 ap-pears in Fig. 4. Mean annual SSD implied dimming trends (< 0.25% per year) at most locations in the plains and LH. in most of the regions in the plains and LH. An anomalously high decline of SSD (< 0.70% per year) was observed in Dhangadi and Bi-ratnagar, both of which are located in the plains. In the HHM, an increasing SSD trend (> 0.25% per year) was observed in the far-western and mid-western mountain regions, while declining trends were observed for most of the eastern and central mountain re-gions. The contrast in SSD trends between the regions was promi-nent for the winter (Fig. 4). The SSD trend distribution for pre- and post-monsoon closely resembled that of the annual SSD dis-tribution, while the post-monsoon season showed the maximum rate of decline. The monsoon SSD trend was strikingly different from that of other seasons, for negative and positive trends were

Table 3. Inter-annual trends in sunshine duration (SSD) and interaction between stations and years in the three physiographic regions for the period 1987-2010.

Region Inter-annual SSD trend (%/year)a P-value for year-by-station interaction

Plains 0.56*** 0.088

Low-hills 0.09 0.076

High-hills & mountains 0.05 0.048

All-Nepal 0.20***

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observed in both the plains and LH (Fig. 4). 3.3 Annual NRD trends and their relation to SSD

The influences of NRD on SSD are evident in their monthly variations (Fig. 3), particularly from June to September, when the monsoon season peaks and mean SSD is at its lowest. Mean NRD ranged from 1.2 d in November to 23.5 d in July. Temporal trends in NRD were compared with those in SSD for each station, region,

and season to examine how the temporal trend in NRD relates to the decline in SSD. Most stations with dimming trends revealed declining NRD trends, among which Surkhet showed significant decline for both trends (Table 2). Stations with highest rate of dimming (Biratnagar and Dhangadi) showed increased NRD, whereas Jumlathe station with the highest rate of brighteninghad decreased NRD. However, neither of these trends was signifi-

Fig. 2. Estimated trends in annual mean monthly total sunshine duration (SSD, hour/month) at individual stations in plains (a), low-hills (b), and high-hills and mountains (c) for the period from 1987 to 2010. Symbols are the observations and lines are the linear-model fit. See Fig. 1 for the location of the stations and Table 1 for their details. Note: BHA- Bhairawaha, BIR- Biratnagar, DHA- Dhangadi, SIM- Simara, DHK- Dhankuta, DIP- Dipayal, KTM- Kathman-du, POK- Pokhara, SUR- Surkhet, DAD- Dadeldhura, JUM- Jumla, OKH- Okhaldhunga and TAP- Taplejung.

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cant. On a regional basis, annual NRD showed declining trends in

the LH and HHM but no trends in the plains (Table 2). The change in NRD therefore cannot be the major contributor to the dimming in the plains and LH, yet could explain the increasing SSD trends in the HHM. To clarify this issue, Table 4 compares SSD and NRD trends in different regions and seasons. Among the four seasons, the winter and monsoon seasons exhibited signifi-cant declines in NRD in the LH, followed by the HHM. In these regions, the NRD trend could explain the brightening observed in winter, but in the plains, NRD trends were not significant and could not have made any major contribution to dimming in the pre- or post-monsoon season. Overall, Nepal shows a significant decline in NRD at a rate of 0.20% per year (Table 2).

4. Discussion and Conclusions

Despite the partial recovery from dimming across the world (Wild, 2009), our study found a continuing decline in SSD, which is consistent with reports for India. Soni et al. (2012) found a decline in SSD of 0.28% per year on average across 12 stations in India for 19712005, whereas the dimming rate has become greater in recent decades at 5% on average per two dec-ades (Padma Kumari et al., 2007). In this study, the rate of SSD decline was 3.5% for two decades (19912010) in Kathmandu (results not shown). The significant decline in SSD observed in other cities such as Biratnagar, Dhangadi, and Surkhet (Table 2) are also comparable to SSD declines reported for major cities in India such as Delhi (0.63% per year), Kolkata (0.35% per year), and Visakhapatnam (0.57% per year) (Soni et al., 2012). This

Table 4. Regional and all-Nepal trends in sunshine duration (SSD, %/year) and number of rainy days (NRD, %/year) by season for the period 1987-2010 (SSD) and 1980-2009 (NRD).

SSD and NRD trends by season (%/year)a

Winter Pre-monsoon Monsoon Post-monsoon

Regions Parameters Dec-Feb Mar-May Jun-Sep Oct-Nov

Plains SSD 0.80** 0.51*** 0.31 0.70**

NRD 0.75 0.23 0.01 0.27

Low-hills SSD 0.26 0.21 0.24 0.16

NRD 1.58*** 0.17 0.31*** 0.09

High-hills & mountains SSD 0.54* 0.02 0.27 0.17

NRD 0.97* 0.04 0.17 0.25

All-Nepal SSD 0.05 0.24*** 0.28 0.33***

NRD 1.16*** 0.04 0.18** 0.12 a. Statistical significance of the trends are shown by *** for P

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study thus confirms the persistence of dimming in Nepal at a rate similar to that in India.

The coincident declines in SSD and NRD across Nepal (Table 2) imply other drivers of the dimming than NRD, and anthropo-genic aerosols appear the likely one. The emission of pollutants in an area is a function of population density and the areas level of economic development (Alpert et al., 2005), for both of which Kathmandu tops the list of cities in Nepal. Nevertheless, the SSD decline more than doubled in Biratnagar and Dhangadi than in Kathmandu. Notably, these smaller cities are located in the plains at the northern-most extension of the Indo-Gangetic plain (IGP), which is one of the most polluted regions of the world (Guttikun-da et al., 2003). The decline in SSD observed for the plains in this study is indeed close to that of the IGP during the longer period of 19702006 (Jaswal, 2009). Studies have reported a continuous increase in the emissions of black carbon (BC) and sulfates in the IGP during the 1990s and 2000s (Sahu et al., 2008; Lu et al., 2011). Thus, reduced SSD in the plains might be explained by the increased loading of aerosols and large-scale pollution across the IGP.

Air pollution in Nepal is largely controlled by seasonal cycles of local urban-industrial pollutants and aerosol loading by region-al air masses. During the post-monsoon and winter seasons, local emissions are aggravated by air pollution in the IGP and the flow of air masses from the north and northwest, which bring finer continental aerosols (Singh, 2004). In the plains, ABC (Rama-nathan and Ramana, 2005), persistent dense fog, and resulting cold waves are observed every winter. Such phenomena have caused a reduction in SR of approximately 32 (5) Wm-2 in IGP and Himalayan foothills during the dry season from October to May, 20012003 (Ramanathan and Ramana, 2005) and 25 Wm-2 in Kathmandu valley during the winter of 2003 (Ramana et al., 2004). Our finding of high dimming during the winter and post-monsoon seasons (Table 4) is supported by reports of increased wintertime fog, as shown by declining trends in visibility (Jaswal et al., 2013) and increasing trends in aerosol optical depth (AOD) in IGP (Kaskaoutis et al., 2012).

During the pre-monsoon season, the burning of open vegetation and agricultural fires occur at low elevations in Nepal and may significantly influence aerosols, as indicated by a peak AOD of more than 0.7 in April (Vadrevu et al., 2012). The presence of strongly absorbing carbonaceous aerosols such as BC has been confirmed in the foothills and elevated Himalayan slopes of Nepal (Gautam et al., 2011; Putero et al., 2014). The preliminary results of our on-going study show an increase in biomass burning during the pre-monsoon season, especially in the low-altitude regions of Nepal (Neelam, unpublished results). Thus, biomass burning within the study regions could have also contributed to aerosol loading and large-scale air pollution over the IGP.

Air pollutants are reduced by the Indian summer monsoon. En-tering from the east, the monsoon rainfall in Nepal results in fewer aerosols and clearer days. The declining trend in monsoon NRD in this study may suggest the inefficient removal of pollutants during the period. Since approximately 80% of the rainfall in Nepal oc-curs during the monsoon season (Shrestha et al., 2000), the sig-nificant decline of NRD may indicate a general weakening of monsoon rainfall in Nepal. In addition, a microphysical phenome-

non involving indirect interactions between aerosols and clouds could increase cloud lifetime or suppress precipitation (Rama-nathan et al., 2001, 2005). Winter in Nepal is marked by the win-ter monsoon, which is dominated by westerly circulations entering from the west and delivers markedly increasing precipitation as elevation rises (Shrestha et al., 2000; Bolch et al., 2012; Sigdel and Ikeda, 2012). Decreased NRD in the winter thus seems to be consistent with increased SSD in the LH and HHM during the same season (Table 4). A change in SR could alter the diurnal temperature range by influencing maximum temperatures (Padma Kumari et al., 2007; Ye et al., 2009). The increasing trend in maximum temperatures during the winter season in the Himalayan

Fig. 4. Trends (%/year) in annual and seasonal means of sunshine duration in Nepal over the period from 1987 to 2010. (-plains, -low-hills and -high-hills and mountains)

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regions (Shrestha et al., 1999) is therefore consistent with the increasing trends of SSD in the HHM regions in the present study.

The mechanisms of SSD trends are yet to be understood. On this point, research on SSD and SR trends in clear versus cloudy sky conditions could clarify current understandings of the influ-ence of aerosols and clouds on SR. Research on the effects of strongly absorbing aerosols produced by biomass burning on SR is also warranted. Global dimming has a profound impact on agri-culture, since SR plays a key role in plant growth (Ballar et al., 2012) and crop production (Shuai et al., 2012; Yang et al., 2013). Most studies of climate change impact on agriculture have fo-cused on temperature rise and precipitation change, whereas our study has shown that decreasing SR should also be considered in designing strategies to counter anthropogenic changes in climate.

Acknowledgments

The authors are grateful to Mr. Ram Chandra Karki of Nepals DHM for the meteorological data used in the study. Comments from the two anonymous reviewers helped the authors to clarify the manuscript. The first author was supported by Japans Minis-try of Education, Culture, Sports, Science and Technology (MEXT).

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Sunshine duration is declining in Nepal across the period from 1987 to 2010Neelam NIROULA a , Kazuhiko KOBAYASHI a, , and Jianqing XU b

1. Introduction2. Methodology2.1 The study area2.2 Weather records and analysis

3. Results3.1 Station-based, regional, and all-Nepal annual SSD trends3.2 Seasonal SSD trends and distribution across regions3.3 Annual NRD trends and their relation to SSD

4. Discussion and ConclusionsAcknowledgmentsReferences