Kireet Kumar

New data-driven estimation of terrestrial CO2 fluxes in Asia using a standardized database of eddy covariance measurements, remote sensing data, and support vector regression

The lack of a standardized database of eddy covariance observations has been an obstacle for data-driven estimation of terrestrial CO2 fluxes in Asia. In this study, we developed such a standardized database using 54 sites from various databases by applying consistent postprocessing for data-driven estimation of gross primary productivity (GPP) and net ecosystem CO2 exchange (NEE). Data-driven estimation was conducted by using a machine learning algorithm: support vector regression (SVR), with remote sensing data for 2000 to 2015 period. Site-level evaluation of the estimated CO2 fluxes shows that although performance varies in different vegetation and climate classifications, GPP and NEE at 8days are reproduced (e.g., r2=0.73 and 0.42 for 8day GPP and NEE). Evaluation of spatially estimated GPP with Global Ozone Monitoring Experiment 2 sensor-based Sun-induced chlorophyll fluorescence shows that monthly GPP variations at subcontinental scale were reproduced by SVR (r2=1.00, 0.94, 0.91, and 0.89 for Siberia, East Asia, South Asia, and Southeast Asia, respectively). Evaluation of spatially estimated NEE with net atmosphere-land CO2 fluxes of Greenhouse Gases Observing Satellite (GOSAT) Level 4A product shows that monthly variations of these data were consistent in Siberia and East Asia; meanwhile, inconsistency was found in South Asia and Southeast Asia. Furthermore, differences in the land CO2 fluxes from SVR-NEE and GOSAT Level 4A were partially explained by accounting for the differences in the definition of land CO2 fluxes. These data-driven estimates can provide a new opportunity to assess CO2 fluxes in Asia and evaluate and constrain terrestrial ecosystem models. (Less)

Summer monsoon rainfall trends in the Indian Himalayan region

Impacts of the changing climatic regime on the trends of Indian summer monsoon rainfall (ISMR) are explored in this study for the Indian Himalayan region (IHR). The analysis is carried out for the period of 1951–2007 using a daily high resolution gridded data from APHRODITE project. At first, the percent departures of decadal rainfall are estimated from the long-term June to September rainfall values for the western, central, and eastern Himalayan (WH, CH, and EH) regions. Next, changes in the frequency of strong and weak phases of monsoon intra-seasonal oscillation are investigated. A non-parametric statistical method (Sen’s slope estimator) is applied to the seasonal (i) mean rainfall, (ii) maximum rainfall, and (iii) frequency of extreme rainfall events of WH, CH, and EH regions to identify changes in their decadal, multiple year normals (NY1; 1951–1980 and NY2; 1981–2007) and long-term (NY3; 1951–2007) trends. The inter annual to inter decadal variabilities of the frequency of extreme rainfall events are explored by analyzing statistically significant intrinsic mode functions of the empirical mode decomposition (EMD) method. Results of our analyses have revealed existence of an alternative decadal oscillation of scanty and excessive summer monsoon rainfall trends for the WH, whereas excessive rainfall is observed in the last three decades (1980–2007) over the CH region. It is also observed that the frequencies of both monsoon strong and weak phases are decreasing for the entire Himalayan region. No significant trend is observed for the WH and CH regions for the normal periods NY1, NY2, and NY3 when seasonal average rainfall is considered. However, a significant (p value < 0.05) negative trend of −0.04 mm/day rain is observed for the EH region during NY1 period. Similarly, the seasonal maximum rainfall trends for all the normal periods are found to be negative of which trends of −0.12 and −0.43 mm/day during NY3 and NY1 are observed for WH and EH regions, respectively (p value < 0.05). No significant enhancement in the extreme rainfall event frequencies is observed for the entire IHR during 1951–2007. However, a statistically insignificant positive trend in the extreme event frequencies is observed for the EH region. A dominant cycle of ∼ 2.7 years of high frequency of extreme rainfall events is observed for all the regions whereas, a 12.2-, 15.3-, and 5.8-year cycles are observed for the WH, CH, and EH regions, respectively.

Investigation of dominant modes of monsoon ISO in the northwest and eastern Himalayan region

This study investigates the altitudinal variation of dominant modes of summer monsoon intra-seasonal oscillation (ISO) over the Northwest (NWH) and Eastern Himalayan (EH) region using (i) spatially scattered 133 number of station rainfall observations and (ii) latitudinal transect-wise (LT) rainfall variation, obtained from an observed interpolated gridded rainfall data for the period 1995–2004. The altitudinal variation of dominant modes of monsoon ISO were investigated by exploring the strong and weak phases of the principal components of 10–90 days bandpass rainfall data of June to September with respect to location specific station height. Investigation of frequency of days for light and moderate rainfall along with the occurrence of total seasonal rainy days has revealed existence of a rainfall maximum around 2100 m height for the NWH region. Similarly, the total seasonal rainy days of EH region was found to have maxima between 1100 and 1400 m height. Analyses of the spatially scattered station rainfall observation for the NWH region showed that the strong periods of ISO modes exist around 747.9 (±131.7) m and 2227.2 (±100.2) m heights. Over the EH region, the dominant modes of the monsoon ISO were found to be centred around 1200 m. Significant alterations of strong and weak phases of monsoon ISO as a response to altitudinal variation in the mountain surface were observed when latitudinal transect-wise variation of monsoon ISO modes were investigated.

Simulated projection of ISMR over Indian Himalayan region: assessment from CSIRO-CORDEX South Asia experiments

In view of a significant lacuna in the Himalaya-specific knowledge of forthcoming expected changes in the rainfall climatology, this study attempts to assess the expected changes in the Indian summer monsoon rainfall (ISMR) pattern exclusively over the Indian Himalayan Region (IHR) during 2020–2070 in comparison to a baseline period of 1970–2005 under two different warming scenarios, i.e., representative concentration pathways 4.5 and 8.5 (RCP 4.5 and RCP 8.5). Five climate model products from the Commonwealth Scientific and Industrial Research Organization initiated Coordinated Regional Climate Downscaling Experiment of World Climate Research Programme over south Asia region are used for this purpose. Among the several different features of ISMR, this study attempts to investigate expected changes in the average summer monsoon rainfall and percent monthly rainfall to the total monsoon seasonal rainfall using multimodel averages. Furthermore, this study attempts to identify the topographical ranges which are expected to be mostly affected by the changing average monsoon seasonal rainfall over IHR. Results from the multimodel average analysis indicate that the rainfall climatology is expected to increase by >0.75xa0mm/day over the foothills of northwest Himalaya during 2020–2070, whereas the rainfall climatology is expected to decrease for the flood plains of Brahmaputra under a warmer climate. The monthly percent rainfall of June is expected to rise by more than 1% over the northwestern Himalaya during 2020–2040 (although insignificant at p value <0.05), whereas the same for August and September is expected to decrease over the eastern Himalaya under a warmer climate. In terms of rainfall changes along the altitudinal gradient, this study indicates that the two significant rainfall regions, one at around 900xa0m and the other around 2000xa0m of the northwestern Himalaya are expected to see positive changes (>1%) in rainfall climatology during 2020–2070, whereas regions more than 1500xa0m in eastern Himalaya are expected to experience inconsistent variation in rainfall climatology under a warmer climate scenario.

Erratum to: Summer monsoon rainfall trends in the Indian Himalayan region

The original version of this article unfortunately contained mistakes. The latitude and longitude values of Fig. 4a(i-vi) should be read as: 31.0-36.0 N and 73.0-80.0 E; for Fig. 4c(ivi) as: 23.0-29.5 N and 88.0-97.5 E. The italic values of Table 3 are for: Year 1991-2000: CH: Average rainfall trend (0.18); Year 1951-1980: EH: Average rainfall trend (-0.04); Year 1951-1980: EH: Maximum rainfall trend (-0.43); Year 1951-1980: CH: Extreme rainfall trend (-0.20); Year 19511980: EH: Extreme rainfall trend (-0.29); Year 1951-2007: WH: Maximum rainfall trend (-0.12); and Year 1951-2007: WH: Extreme rainfall trend (-0.08).

Variations in the Seasonal Snow Cover Area (SCA) for Upper Bhagirathi Basin, India

Satellite based remote sensing is a convenient tool for the study of cryosphere that allows to carry out investigations over large and inaccessible areas. The present investigation has been carried out to monitor seasonal variation in the Snow Cover Area (SCA) for the upper Bhangirathi basin, located in the Garhwal region of Indian Himalaya . This analysis has been done using Moderate-Resolution Imaging Spectroradiometer (MODIS) satellite data for the past 11 years (2000–2010); the temporal snow cover being derived using the Normalized Difference Snow Index (NDSI ). The entire study basin has been divided into nine elevation zones, on the basis of Digital Elevation Model (DEM), for estimating the SCA for each zone. Zones 1–9 cover different elevation ranges: (1) above 6,500 m, (2) between 6,000 and 6500 m, (3) 5,500–6000 m, (4) 5,000–5500 m, (5) 4,500–5000 m, (6) 4,000–4500 m, (7) 3,500–4000 m, (8) 3,000–3500 m, and (9) below 3,000 m. Mann Kendall and linear regression methods have been employed to identify trends in the SCA during the period 2000–2010. The snow cover depletion analysis depicts a shift in the duration of ablation and accumulation during the study period in the basin. The analysis indicated 13–21 % increase in SCA in the middle elevation zones (4 and 5) and 2–9 % decline in SCA in the lower elevation zones during autumn. SCA was found to increase across all the elevation zones in winter; the rate of increase was particularly high (14–21 %) in the lower elevation zones as compared to higher (2–3 %) and middle elevation zones (4–10 %). Similarly, an increase of 2–3 % in the higher elevation zones, 6–14 % increase in the middle elevation zones and 2–6 % decline in the lower elevation zones was observed in respect of SCA during spring. However, no significant variation in SCA was observed during the summer season. Decadal variation in SCA showed mean annual increase of 8–15 % in the middle elevation zones (3–5). In the lower elevation zones (<4,500 m), mean annual SCA showed increase of 11–14 % between 2000 and 2005, followed by 6–8 % decrease in the upper Bhagirathi Basin.