Satellite Based Temporal Analysis of Local Weather Elements along N–S Transect across Jharkhand, Bihar and Eastern Nepal ^†

Abstract

The study shows the variation in the most important climatic variables i.e., Net Surface Radiation (Rn), Temperature, Rainfall, Evapotranspiration (ET), etc. during 2000–2016 along the North–South transect across Jharkhand, Bihar and Eastern Nepal. The Tropical Rainfall Measuring Mission (TRMM) monthly average precipitation (0.25° × 0.25°), Moderate Resolution Imaging Spectroradiometer (MODIS) 8 day average Land Surface Temperature (LST) product (1 km × 1 km), Modern-Era Retrospective analysis for Research and Applications, Version-2 (MERRA-2) radiation (0.5° × 0.625°) and Global Land Data Assimilation System (GLDAS) reanalysis model data (0.25° × 0.25°) have been used to study and analysed the spatial variability and distribution of rainfall, surface temperature, energy fluxes and evapotranspiration, respectively. The results have shown that the overall annual average rainfall has a gradual decreasing trend. Results have suggested that the regions with low rainfall (<1000 mm) have to witness warmer temperature conditions (>43 °C). The east–west central line of the Bihar, along the river Ganga is found to be the line of division for the comparatively higher (towards south) and lower (towards north) temperature zones. The results for Rn have shown an overall increasing trend over the period of time. Nepal has a wider stretch of Rn concluded by its mountain topography followed by the Jharkhand (plateau) and Bihar (plain). ET values have also shown an increasing trend and the results are noticeable for western Bihar-Jharkhand. There is an upward latitudinal shifting of the low rainfall bands in both the pre-monsoon and monsoon conditions. Due to the lack of availability of ground truth data, we have to restrict with the remotely sensed dataset only.

1. Introduction

During the past century, especially after the industrial revolution, human activities have had a lot of impact at the regional level, which are mainly attributed to greenhouse gases, aerosols, and land use activities [1]. It has been seen that the global climate variability is a major phenomenon occurring worldwide that has caused the major changes in climate variables such as precipitation, air temperature, relative humidity, and solar radiation [2,3,4]. Studies have shown that the analysis of seasonal and annual surface air temperatures over the central east India has a significant warming trend of 0.57 °C per hundred years [5]. The climate variability has also led to increased evapotranspiration rates, a decline in soil moisture, and socio-economic consequences with longer dry periods, and a greater number of extreme events, which is governed by the variation in the solar insolation [6,7]. Evapotranspiration (ET) of higher or lower rainfall or changes in its spatial and seasonal distribution influence the spatial and temporal distribution of runoff, soil moisture and groundwater reserves, and thereby affects the frequency of droughts and floods [8,9,10]. Therefore, this study has been carried out to know the actual rate of alterations of the climatic variables along with their spatial variability. An ET study has been carried out to determine the impact of climatic variability on trends of annual and seasonal rainfall and its intensity during the pre-monsoon and post-monsoon season. The topography has been taken as a controlling factor to study the latitudinal distribution of ET and Rn.

2. Experiments

2.1. Study Area

The study has been conducted for the region enclosed by 20° N to 30° N latitude and 80° E to 90° E longitude. The study area basically consists of all of Jharkhand, Bihar and eastern Nepal, i.e., the North/South transect across the Himalaya, Gangetic plains and Chotanagpur plateau. It is having a total geographic area of around 230,204 sq·km and has a total perimeter of 4137 km (Figure 1a). Topography is one of the major factors that governs local climatic variability. Three major different topographic regions within the study area have been shown below (Figure 1b).

2.2. Materials Used

The TRMM monthly average precipitation (0.25° × 0.25°), MODIS-Terra 8 day average LST product (1 km × 1 km), MERRA-2 radiation (0.5° × 0.625°) and GLDAS reanalysis model data (0.25° × 0.25°) have been downloaded for the duration of 2000–2016, which has been used to study and analysed the spatial variability and distribution of rainfall, surface temperature, energy fluxes and evapotranspiration, respectively (

Table 1. Details and specifications of the data used.

Sl.No.	Sensor	Resolution	Purpose	Source
1.	TRMM	0.25° × 0.25° monthly 3B43v7	Rainfall analysis	http://www.geovanni.nasa.gov/
2.	MODIS-Terra	1 km × 1 km, 8 day average	Temperature analysis	http://www.geovanni.nasa.gov/
3.	GLDAS	0.25° × 0.25°, monthly average	Radiation analysis	http://disc.sci.gsfc.nasa.gov/mdisc/
4.	SRTM DEM	90 m	Relief analysis	http://www.jpl.nasa.gov/srtm/
5.	MERRA-2	0.625° × 0.5° monthly	Radiation analysis	http://gmao.gsfc.nasa.gov/

).

2.3. Method Adopted

Temporal mapping of precipitation (rainfall) and land surface temperature has been done for the desired years and spatial distribution and variability has been observed. The amount and distribution pattern of precipitation have been further analysed by putting a temperature threshold of 35 °C and more in summer. The Surface Energy Balance Algorithm for Land (SEBAL) (Equation (1) has been used to extract the net surface radiation (Rn), which quantifies the energy balance using satellite data as an input [11,12]. The distributional pattern and amount of net solar radiation (Rn) received and evapotranspitation (ET) has been mapped in a GIS environment and linked with the pre-monsoon and monsoon rainfall events. A detailed work flowchart has given in Figure 2:

Rn = (1 − α) RS↓ + RL↓ − RL↑ − (1 − εo) RL↓,

(1)

where RS↓ = incoming short wave radiation (W/m²); α = surface albedo (dimensionless); RL↓ = incoming long wave radiation (W/m²); RL↑ = outgoing long wave radiation (W/m²) and εo = surface thermal emissivity (dimensionless). (dimensionless); RL↓ = incoming long wave radiation (W/m²); and RL↑ = outgoing long wave radiation (W/m²) and εo = surface thermal emissivity (dimensionless).

3. Results

3.1. Rainfall Analysis

The prepared maps for the above-mentioned period have shown that the average annual rainfall of the study area has decreased over the past three pentad, mainly over the E–E Nepal and N–E Bihar region (Figure 3a).

3.2. Temperature Analysis

The trend has shown a maximum-minimum temperature difference of 64 °C for the duration of years from 2001 to 2006. It has reached 65 °C in the next five years, 2007 to 2011, and further increased to 66 °C in the years from 2012 to 2016. It is believed that the trend will follow a similar pattern in the coming years (Figure 3b).

3.3. Temperature versus Rainfall Correlation

The East-West central line passing through the centre of the Bihar region (say the river Ganga) is found to be the dividing line for threshold temperature. Below this line (i.e., towards the Jharkhand), the entire area witnesses a temperature greater than or equal to 35 °C, whereas, on the other hand (i.e., towards Nepal), there are very few areas that witness temperatures greater than or equal to 35 °C (Figure 3c).

3.4. Net Surface Radiation (Rn) Analysis

The results have shown that the Rn has an overall increasing trend during a period of years. The surface over Bihar and Jharkhand is absorbing more heat than the higher latitude in Nepal. It has been found that the Nepal region has a wider range of Rn, which ranges from 200 W/m² to 260 W/m² (difference of 60 W/m²). This may basically be due to the huge variation in the surface topography (i.e., entire mountain range) ranging from 500 m to more than 6000 m. Bihar has the least stretch of Rn ranging from 265 W/m² to 275 W/m² (difference of 10 W/m²) due much less variation in the topography, (i.e., entire plain region) ranging from 50 m to 200 m, whereas the Jharkhand region has a moderately less stretch of Rn ranging from 275 W/m² to 295 W/m² (difference of 20 W/m²), which may be due to the moderate surface topographic variation (i.e., some plains and Plateau) ranging from 300 m to 700 m (Figure 4a,b).

3.5. Surface Evapotranspiration (ET) Analysis

The western Bihar-Jharkhand region has had a significant increase (an increase of 8 × 10⁻⁵ Kg/m²/s) in the rate of evapotranspiration (Figure 5a). Similar to that of Rn analysis, the ET values have also been analysed and it was found that the trend of ET is approximately the same for Bihar and Jharkhand, whereas Nepal has a slightly different trend with lower ET values (Figure 5b). The ET values for the Bihar and Jharkhand ranges from 0.000023 to 0.000029 Kg/m²/s, whereas this is from 0.000019 to 0.000022 Kg/m²/s for Nepal (Figure 5c).

3.6. Pre-Monsoon and Monsoon Rainfall Analysis w.r.t Net Surface Radiation (Rn) and Evapotranspiration (ET)

The average rainfall maps of pre-monsoon and monsoon season on an interval of four years (2001–2003, 2004–2008, 2009–2012 and 2013–2016) has been plotted and it has been found that there is an upward latitudinal shifting in the low rainfall bands in both the pre-monsoon and monsoon conditions (Figure 6a,b).

4. Discussion

Over a period of time, the rate of surface ET is getting higher and, for some reasons (e.g., Central Bihar), continuously receiving less rainfall then normal in the monsoon season. This may convert the good agricultural land into fallow land in future, which will be a serious issue for both farmers and local livelihoods of that region.

5. Conclusions

It can be concluded that the maximum-minimum temperature difference is increasing at a rate of 1 °C per every five years. Nepal has been found to have a wider stretch of Rn values due to its highly undulating topography (mountain) followed by the Jharkhand (plateau) and Bihar (plain). The surface ET also has an increasing trend over the period of time and the results are noticeable for western Bihar-Jharkhand. The four year average pre-monsoon and monsoon rainfall analysis results have shown that there is an upward latitudinal shifting of the low rainfall bands in both the pre-monsoon and monsoon conditions.