220
• Temperature and precipitation trends pre and post 2000 revealed comparative
slowdown in warming/rate of precipitation decline after year 2000 which was
linked with reported findings about increased snow-cover area (SCA) and comparatively less negative glacier mass budget in westerly dominated areas like
NWH.
Keywords Climate change · Gridded dataset · ERA-I and CRU-TS · Warming
hiatus
1 Introduction
Climate change has initiated a transition in many earth systems due to which issues
related to water resources, ecosystem and natural hazards have surfaced worldwide
(Dobreva et al. 2017). Stark transitions are reflected in the cryosphere since it is
regulated by energy and water fluxes that have changed lately due to climatic
changes (Stocker et al. 2013). Such observed changes have given an impetus to
climate change studies worldwide to assess the gravity of impacts and ensuring
prompt implementation of mitigation measures. But meteorological and hydrological studies in high Himalaya are impeded by scarcity of data since complex terrain
renders such areas inaccessible (Tong et al. 2013). Snow and Avalanche Study
Establishment (SASE), India has a good network of observatories in Northwest
Himalaya (NWH) which were established to facilitate avalanche studies at different
altitudes, that is why much of attention is laid to collection and analysis of wintertime data. However, due to non-uniform distribution of observatories, the need for
observations with better spatial coverage cannot be overlooked. The need for data
with reasonable spatial and temporal coverage has led to generation of gridded datasets by many modelling centres of the world (Sun et al. 2018). The gridded datasets
are obtained by various methods e.g. In-situ measurements are interpolated using
suitable methods to grids (APHRODITE, CRU-TS, GPCC and UDEL). However,
for locations where no observatories are installed, the estimations bear some uncertainties (Kidd et al. 2017). Sensors like advanced Infrared (IR) and Microwave
(MW) on-board a satellite help overcoming the issue of monitoring of inaccessible
locations at regular intervals (Kidd and Levizzani 2011). One such satellite-based
product is Tropical Rainfall Measuring Mission (TRMM) Multi-satellite
Precipitation Analysis (TMPA) V07-3B43TRMM (Huffman et al. 2007). However,
the retrieval algorithms used for processing of these datasets often have inherent
uncertainties. Despite ongoing evolution of advanced algorithms, merged datasets
are seen as a reliable option. Merged datasets incorporate in-situ observations with
satellite retrieved information thereby increasing the fidelity of these datasets (Xie
et al. 2003). Global Precipitation Climatology Project (GPCP) is one such product
(Adler et al. 2003). Reanalysis datasets are synthesized by merging of irregular
observations with outputs of Weather Research Forecast (WRF) models in pursuit
H. S. Negi and N. Kanda
• Temperature and precipitation trends pre and post 2000 revealed comparative
slowdown in warming/rate of precipitation decline after year 2000 which was
linked with reported findings about increased snow-cover area (SCA) and comparatively less negative glacier mass budget in westerly dominated areas like
NWH.
Keywords Climate change · Gridded dataset · ERA-I and CRU-TS · Warming
hiatus
1 Introduction
Climate change has initiated a transition in many earth systems due to which issues
related to water resources, ecosystem and natural hazards have surfaced worldwide
(Dobreva et al. 2017). Stark transitions are reflected in the cryosphere since it is
regulated by energy and water fluxes that have changed lately due to climatic
changes (Stocker et al. 2013). Such observed changes have given an impetus to
climate change studies worldwide to assess the gravity of impacts and ensuring
prompt implementation of mitigation measures. But meteorological and hydrological studies in high Himalaya are impeded by scarcity of data since complex terrain
renders such areas inaccessible (Tong et al. 2013). Snow and Avalanche Study
Establishment (SASE), India has a good network of observatories in Northwest
Himalaya (NWH) which were established to facilitate avalanche studies at different
altitudes, that is why much of attention is laid to collection and analysis of wintertime data. However, due to non-uniform distribution of observatories, the need for
observations with better spatial coverage cannot be overlooked. The need for data
with reasonable spatial and temporal coverage has led to generation of gridded datasets by many modelling centres of the world (Sun et al. 2018). The gridded datasets
are obtained by various methods e.g. In-situ measurements are interpolated using
suitable methods to grids (APHRODITE, CRU-TS, GPCC and UDEL). However,
for locations where no observatories are installed, the estimations bear some uncertainties (Kidd et al. 2017). Sensors like advanced Infrared (IR) and Microwave
(MW) on-board a satellite help overcoming the issue of monitoring of inaccessible
locations at regular intervals (Kidd and Levizzani 2011). One such satellite-based
product is Tropical Rainfall Measuring Mission (TRMM) Multi-satellite
Precipitation Analysis (TMPA) V07-3B43TRMM (Huffman et al. 2007). However,
the retrieval algorithms used for processing of these datasets often have inherent
uncertainties. Despite ongoing evolution of advanced algorithms, merged datasets
are seen as a reliable option. Merged datasets incorporate in-situ observations with
satellite retrieved information thereby increasing the fidelity of these datasets (Xie
et al. 2003). Global Precipitation Climatology Project (GPCP) is one such product
(Adler et al. 2003). Reanalysis datasets are synthesized by merging of irregular
observations with outputs of Weather Research Forecast (WRF) models in pursuit
H. S. Negi and N. Kanda