Does precipitation pattern foretell climatic shift over Punjab state ?

ABSTRACT. Statistical analysis of 82-years (1901-1982) record of precipitation from 27 rain-recording stations in Punjab state of lndia has been carried out to assess the climate shift if any in the state. The central part of the study is the trend and spectrum analysis of annual. monsoon and winter rainfall of different stations in the region. It is seen that frequency distribution of 19 rainfall series out of 81 series is normally distributed. Maikov linear type of persistence is observed in some of the rainfall series. Marin-Kendall test indicates the decreasing trend in winter rainfall of all the stations and is found to be significant in case of Amritsar, Taran Taran, Tanda, Ludhiana and Ranike. Low-pass filter reveals that trend is not linear but oscillatory consisting of periods of 10 years or more. It is seen that winter rainfall of most of the stations exhibits the decreasing trend from 1935-40 to 1965-70. It is also revealed by the low-pass filter curves that winter rainfall of all t1le sla1ions remained below average from 1960 till the end of the study period. The spectral analysis indicates a significant cycle of 4.1 to 27 years in some of the stations and Quasi-Biennial Oscillations (QBO) over many stations.

Climate Change Effects, Adaptation, and Mitigation Techniques in Tropical Dry Forests

Tropical dry forests is one of the most unique forest types. It differs from other tropical forests with its climatic behavior like a prominent dry period, little annual rainfall, and high evapotranspiration. Out of six global bioclimatic zones, the forests are distributed in four. Climate change is now the most challenging issue regarding the fate of tropical dry forests. A severe climatic change is estimated to occur between 2040 and 2069 that could drastically change the precipitation pattern, temperature, aridity, and distribution of biodiversity. It could alter the forest type permanently. With a large number of heat-tolerant species, tropical dry forests have a great potentiality to conservationists with the prediction of a large area that could attain the climatic condition favorable for extension of tropical dry forests. But many of the species of tropical dry forests could be extinct due to changing climate at the same time. Proper adaptation and mitigation techniques could minimize the severity of climate change effects.

Climate Change and Its Impact on Terrestrial Ecosystems

This chapter provides a general overview of the effects of climate change on the terrestrial ecosystem and is meant to set the stage for the specific papers. The discussion in this chapter focuses basically on the effects of climatic disturbances on terrestrial flora and fauna, including increasing global temperature and changing climatic patterns of terrestrial areas of the globe. Basically, climate disturbances derived increasing temperature and greenhouse gases have the ability to induce this phenomenon. Greenhouse gases are emitted by a number of sources in the atmosphere such as urbanization, industrialization, transportation, and population growth, so these contributing factors and its effects on climatic events like temperature rise, change precipitation pattern, extreme weather events, survival and shifting of biodiversity, seasonal disturbances, and effects on glaciers are relatively described in this chapter.

Spatial Pattern of Precipitation in GPM-Era Satellite Products against Rain Gauge Measurements over Nepal

Precipitation in a mountainous region is highly variable due to the complex terrain. Satellite-based precipitation estimates are potential alternatives to gauge measurements in these regions, as these typical measurements are not available or are scarce in high elevation areas. However, the accuracy of these gridded precipitation datasets need to be addressed before further usage. In this study, an evaluation of the spatial precipitation pattern in satellite-based precipitation products is provided, including satellite-only (Integrated Multi satellite Retrievals for GPM IMERG-UCORR and Global Satellite Mapping of Precipitation (GSMaP-MVK) and gauge calibrated (IMERG-CORR and GSMaP-Gauge) products, with a spatial resolution of 0.1°, which is compared to 387-gauge measurements in Nepal from April 2014 to December 2016. The major results are as follows: (1) The gauge calibrated version 5 IMERG-CORR and version 6 GSMaP-Gauge are relatively better than the satellite-only datasets, although they all underestimate the observed precipitation. (2) The daily gauge calibrated GSMaP-Gauge performs fairly well in low and mid-elevation areas, whereas the monthly gauge calibrated IMERG-C performs better in high-elevation areas. (3) For the daily time scale, IMERG-CORR shows a better ability to detect the true precipitation (higher Probability of Detection (POD)) and (lowest False Alarm Ratio (FAR)) events among all datasets. However, all four satellite-based precipitation datasets accurately detect (Critical Success Index (CSI) >40%) precipitation and no-precipitation events. The results of this work provide the systematic quantification of IMERG and GSMaP of satellite precipitation products over Nepal using station observations and delivers a helpful statistical basis for the selection of these datasets for future scientific research.

Biophysical Effects of Temperate Forests in Regulating Regional Temperature and Precipitation Pattern across Northeast China

The temperate forests in Northeast China are an important ecological barrier. However, the way in which temperate forests regulate the regional temperature and water cycling remains unclear. In this study, we quantitatively evaluated the role that temperate forests play in the regulation of the regional temperature and precipitation by combining remote sensing observations with a state-of-the-art regional climate model. Our results indicated that the forest ecosystem could slightly warm the annual air temperature by 0.04 ± 0.02 °C and bring more rainfall (17.49 ± 3.88 mm) over Northeast China. The temperature and precipitation modification function of forests varies across the seasons. If the trees were not there, our model suggests that the temperature across Northeast China would become much colder in the winter and spring, and much hotter in the summer than the observed climate. Interestingly, the temperature regulation from the forest ecosystem was detected in both forested regions and the adjacent agricultural areas, suggesting that the temperate forests in Northeast China cushion the air temperature by increasing the temperature in the winter and spring, and decreasing the temperature in the summer over the whole region. Our study also highlights the capacity of temperate forests to regulate regional water cycling in Northeast China. With high evapotranspiration, the forests could transfer sufficient moisture to the atmosphere. Combined with the associated moisture convergence, the temperate forests in Northeast China brought more rainfall in both forest and agricultural ecosystems. The increased rainfall was mainly concentrated in the spring and summer; these seasons accounted for 93.82% of the total increase in rainfall. These results imply that temperate forests make outstanding contributions to the maintainance of the sustainable development of agriculture in Northeast China.

Sustainable Water Flows in Era of Climate Change

The flow of water in rivers is of paramount importance to maintain supply of food and energy requirements to a great extent. The minimum flow in perennial rivers is subjected to groundwater availability, it is further replenished by the water added through precipitation. Climate change not only increases the melting of glaciers and sea level rise, but also influences the surface water flow and quality. As agriculture is directly affected by changing precipitation pattern, the reduction in water resources and untimely addition of water, both act havoc to the food production process. This interconnection makes agriculture even more vulnerable to the scenarios of global warming and climate change. Studies on food-energy-water nexus has opened new avenues of research in sustainable water management. The role of sustainable flow of water in rivers is highlighted which needs to be understood in era of climate change.

Precipitation Pattern Alters the Effects of Nitrogen Deposition on the Growth of Alien Species Robinia Pseudoacacia

Aims Nitrogen (N) supply and precipitation pattern (amount and frequency) both affect plant growth. However, N deposition is increasing and precipitation regimes are changing in the context of global change. An experiment was conducted to determine the effect of precipitation pattern and N supplies on the growth of a widely distributed and planted N2-fixing alien species Robinia pseudoacacia. Methods Seedlings were grown in a glasshouse at four different N levels combined with different precipitation regimes, including three precipitation amounts, and two precipitation frequencies. After treatment for 75 days, plant height, biomass allocation, leaf and soil nutrient concentrations were measured. Results Plants under high precipitation frequency had greater biomass compared with plants lower precipitation frequency with the same amount of precipitation. Higher N supply decreased biomass allocation to nodules. Nodule growth and N2 fixation of R. pseudoacacia with low precipitation amount was more inhibited by high N deposition compared with plants received higher precipitation amount. Slightly N deposition under higher precipitation inhibited N2 fixation but did not fulfil the N need in plants. Conclusions Nitrogen deposition might inhibit N2 fixation of plants even in low level but low nitrogen in soil cannot fulfil the N need of plants, and caused N2 fixation limitation in plants during seedling stage. There was likely a shift from acquiring N mainly from N2 fixation to acquisition of N directly with root when N supply was increased. High N deposition level, and increased precipitation frequency might increase the invasion risk of R. pseudoacacia.

Preliminary assessment for sub-seasonal to seasonal precipitation model on four specific conditions over western Indonesia

Preliminary assessment of sub-seasonal to seasonal reforecast precipitation model (S2S) was conducted to analyze the model's performance over western Indonesia on four conditions. The ECMWF S2S model was compared to quality controlled daily precipitation data from 645 observation points over the region. The control and perturbed model for the first three time steps and the last three were utilized to obtain the best performance comparison. The analysis was conducted in monthly period, MJO events, NCS events, and when both of them were active during period of November-December-January-February (NDJF) from 1998 to 2017. The results show that the first three time steps perform much better than the last one with a slightly higher correlation coefficient from the control model with relatively similar RMSE in Natuna Islands. Spatial analysis indicates that both of the control and perturbed models can catch the variation brought by the wet season in the NDJF period, by the MJO, show a hint of NCS effect, and the combination when MJO and NCS were active at the same time. The models can depict the precipitation pattern pretty well with the tendency to overestimate low rainfall intensity and underestimate the high one. The models relatively overestimate the intensity in Sumatra for the whole period. Meanwhile, consistently good spatial performance is shown by the models over Java, both in NDJF periods or MJO events.

Precipitation extremes and anomalies of the Indian Sundarban 1984-2018

Gridded precipitation data products of 0.5º × 0.5º spatial resolution were analysed to understand the climatic variability in a spatial and temporal context. Data reliability of processed gridded data products were examined in the absence of gauge station data observations in the study area. However, the implementations of comparative analysis of the spatial and temporal data products in this study area are missing. The NASA Power Data (NPD) and Climate Research Unit (CRU TS 4.03) Data were scrutinized from 1984-2018. The data products were selected, compared, and interpreted grid wise. Annual and monsoonal precipitation pattern was also studied. Data variability has been analyzed using the Coefficient of Variation (CV), Anomaly, and Precipitation Concentration Index (PCI). The statistical analysis of R2, MAE, RMSE, MAPE and BIAS was performed to quantify the error and differences. Considering the independent grid point, the MAPE and BIAS indicate that only grid 4 performed better than the rest with 12.7% and 17%, respectively. The results regarding the data products illustrate significant differences both in averaged and grid wise context. The NPD shows an increasing trend, whereas CRU represents a decreasing trend from the year 1984-2018. Before the implementation of any processed secondary gridded data products in complex terrain, the critical evaluation and quantification of the magnitude of error is a prerequisite, like the Sundarbans, where the gauge stationed data is unavailable.