Recent trends in climate of Bangalore

The linear trends in the monthly, seasonal and annual mean maximum temperature, minimum temperature, average temperature, diurnal range of temperature, rainfall, relative humidities at 0830 & 1730 hr IST of Bangalore city and airport have been analysed based on the data for the period from 1960-95. The variation in surface wind over Bangalore during above period has also been studied to find out impact of urbanisation on weather parameters. It is found that Bangalore city is becoming warmer in terms of mean maximum & mean minimum temperatures. Rate of increase is significantly higher over Bangalore city (central observatory) than that over airport during winter months. Similarly the rising trend of average temperature of Bangalore city is higher than of Bangalore airport during October to April being significantly so during winter season. Also the diurnal range of temperature of Bangalore is becoming larger in winter months with the rising trend being higher over Bangalore city than over airport. Even though rainfall does not show any significant trend, the rising trend during monsoon & falling trend during post monsoon season over Bangalore city are higher than that of Bangalore airport. Also though both Bangalore city & airport show maximum rising trend in mean relative humidity at 0830 hr IST during winter, the rate of rise is less over Bangalore city. Similarly though the relative humidity at 1730 hr IST shows decreasing trend during all the seasons, the rate of decrease is less over Bangalore city for all seasons except post monsoon season. The mean maximum, minimum and average temperatures and relative humidities show cyclic variation of their monthly trend coefficients during the year.

Climate Change Increases the Expansion Risk of Helicoverpa zea in China According to Potential Geographical Distribution Estimation

Helicoverpa zea, a well-documented and endemic pest throughout most of the Americas, affecting more than 100 species of host plants. It is a quarantine pest according to the Asia and Pacific Plant Protection Commission (APPPC) and the catalog of quarantine pests for plants imported to the People’s Republic of China. Based on 1781 global distribution records of H. zea and eight bioclimatic variables, the potential geographical distributions (PGDs) of H. zea were predicted by using a calibrated MaxEnt model. The contribution rate of bioclimatic variables and the jackknife method were integrated to assess the significant variables governing the PGDs. The response curves of bioclimatic variables were quantitatively determined to predict the PGDs of H. zea under climate change. The results showed that: (1) four out of the eight variables contributed the most to the model performance, namely, mean diurnal range (bio2), precipitation seasonality (bio15), precipitation of the driest quarter (bio17) and precipitation of the warmest quarter (bio18); (2) PGDs of H. zea under the current climate covered 418.15 × 104 km2, and were large in China; and (3) future climate change will facilitate the expansion of PGDs for H. zea under shared socioeconomic pathways (SSP) 1-2.6, SSP2-4.5, and SSP5-8.5 in both the 2030s and 2050s. The conversion of unsuitable to low suitability habitat and moderately to high suitability habitat increased by 8.43% and 2.35%, respectively. From the present day to the 2030s, under SSP1-2.6, SSP2-4.5 and SSP5-8.5, the centroid of the suitable habitats of H. zea showed a general tendency to move eastward; from 2030s to the 2050s, under SSP1-2.6 and SSP5-8.5, it moved southward, and it moved slightly northward under SSP2-4.5. According to bioclimatic conditions, H. zea has a high capacity for colonization by introduced individuals in China. Customs ports should pay attention to host plants and containers of H. zea and should exchange information to strengthen plant quarantine and pest monitoring, thus enhancing target management.

Diurnal variation of outgoing longwave radiation derived from I NSA T-I B data

In this paper, 3-hourly values of Outgoing Long wave Radiation (OLR) for the years 1987 .to 1990 over the Indian Ocean region, derived from'1NSAT-IB VHRR observations, have been used to study the patterns of diurnal variation of OLR. The nature of the diurnal variations over different regions such as desert, ocean, monsoon area and equatorial trough in four representative months of the year is discussed. The variations in the diurnal range of OLR and the hours of occurrence of OLR minimum and maximum, are also presented.Daily means of TNSAT OLR using all.eight 3-hour samples and four different pairs of. 12-hour samples were computed. Results show that they are highly correlated. However, averages made with OLR values corresponding to 0230 and 1430 local time are slight underestimates compared to the 8-sample averages, whereas averages based upon 0830 and 2030 local time are slight overestimates.

Modeling the Potential Distribution of Three Taxa of Akebia Decne. under Climate Change Scenarios in China

Akebia trifoliata (Thunb.) Koidz., Akebia trifoliata subsp. australis (Diels) T. Shimizu and Akebia quinata (Houtt.) Decne. are the source plants of the traditional Chinese medicines AKEBIAE CAULIS and AKEBIAE FRUCTUS, and have high pharmaceutical value. However, the resource reserve of these plants has dramatically declined due to habitat destruction, which has seriously affected their adequate supply and sustainable utilization. A poor knowledge of the potential distribution of these medicinal materials would seriously constrain the protective exploitation of wild resources and the establishment of new cultivations. In this study, based on the scenarios of SSP1-2.6, SSP2-4.5, SSP3-7.0 and SSP5-8.5, the maximum entropy model was used to predict the potential distribution of these three Akebia taxa under current and future (2030s, 2050s, 2070s and 2090s) climate conditions. Our findings showed that the potentially suitable areas of these three Akebia taxa were mainly distributed in China at 101.8–121.9° E and 23.5–34.6° N. Temperature played a more significant role than precipitation in affecting the distribution. The dominant bioclimatic variable that affected the distribution of A. trifoliata and A. quinata in China was the minimum temperature of the coldest month (BIO06). For A. trifoliata subsp. australis, the mean diurnal range (BIO02) was the dominant variable influencing its distribution. Compared with current conditions, the moderate- and high-suitability areas of these three Akebia taxa were predicted to shrink towards the core areas, while the low-suitability areas were all observed to increase from the 2030s to the 2090s. With the increase in radiative forcing of SSP, the low-impact areas of these three Akebia taxa showed a decreasing trend as a whole. Our results illustrate the impact of climate change on the distribution of Akebia, and would provide references for the sustainable utilization of Akebia’s resources.

Reforestation enhanced landscape connectivity for thermal buffering in China

Deforestation-induced landscape fragmentation causes habitat loss and isolation, modifies local climate, and therefore threatens biodiversity. While, on the contrary, how large-scale reforestation may improve the connectivity and thermal buffers of habitats is not well understood. We show that decades long large-scale reforestation in China has effectively increased the size and connectivity of forest patches by gradually filling gaps among isolated patches and creating more core forests. The core forests have a stronger capacity to cool the land surface, leading to a daily mean cooling effect of -0.42±0.23°C relative to nearby marginal forests. Moreover, the core forests reduce diurnal range and seasonal variation of land surface temperature by 1.41±0.23°C and 0.42±0.55°C, respectively, relative to nearby marginal forests. The thermal buffering capacity of large size core forest (>100km2) is more than twice that of small size (≤10km2). Despite their relatively low thermal buffering capacity, the marginal forests contribute about 73% to the increase of forest area in China during the last two decades and create buffer zones for the core forests to resist external disturbances, maintaining the internal stability of the forest ecosystem. We highlight that improving the integrity and connectivity of the forests with ecological restoration and succession can further enhance potential of forests to buffer local thermal environment under the current reforestation efforts, and thereby providing better connected thermal habitats for species to survive under climate change.

Geographical Distribution and Relationship with Environmental Factors of Paphiopedilum Subgenus Brachypetalum Hallier (Orchidaceae) Taxa in Southwest China

The determination of the geographic distributions of orchid species and their relationships with environmental factors are considered fundamental to their conservation. Paphiopedilum subgenus Brachypetalum is one of the most primitive, ornamental, and threatened groups of Orchidaceae. However, little is known about the distribution of Brachypetalum orchids and how they are influenced by environmental factors. In this study, we developed a database on the geographical distribution of Brachypetalum orchids based on a large-scale field investigation in the Guangxi, Guizhou, and Yunnan provinces of southwest China (2019–2020). Using this database, we first adopted the nonparametric Mann–Whitney U test to analyze the differences in the geographical distributions and growth environments of Brachypetalum orchids. In addition, we also used the method of principal component analysis (PCA) to explore distribution patterns of Brachypetalum orchids in relation to environmental factors (topography, climate, anthropogenic disturbance, productivity, and soil) in southwest China. Our results indicated that Brachypetalum orchid species were mainly distributed in the karst limestone habitats of southwest China. In general, there were 194 existing localities with the occurrence of seven target orchids in the investigated area. Of the discovered species in our study, 176 locations (~90.7%) were distributed primarily in the karst habitat. Among them, the range of 780–1267 m was the most concentrated elevation of Brachypetalum orchids. In addition, the findings also suggested that the distribution of Brachypetalum orchids in southwest China was relatively scattered in geographical space. However, the density of the distribution of Brachypetalum orchids was high, between 104° and 108° E and between 25° and 26° N. The results of the Mann–Whitney U test revealed that there are obviously different geographical distributions and growth environments of Brachypetalum in southwest China. More specifically, we found some extremely significant differences (p < 0.001) in elevation, mean diurnal range, precipitation of coldest quarter, solar radiation, and exchangeable Ca2+ between the provinces of southwest China. The PCA analysis revealed that elevation, solar radiation, temperature (mean diurnal range, annual temperature range) and precipitation (precipitation seasonality, precipitation of the warmest quarter) were found to be the most significant factors in determining Brachypetalum orchids’ distribution. These findings have implications in assessing conservation effectiveness and determining niche breadth to better protect the populations of these Brachypetalum orchid species in the future.

Prediction of Potentially Suitable Distributions of Codonopsis pilosula in China Based on an Optimized MaxEnt Model

Species distribution models are widely used in conservation biology and invasive biology. MaxEnt models are the most widely used models among the existing modeling tools. In the MaxEnt modeling process, the default parameters are used most often to build the model. However, these models tend to be overfit. Aiming at this problem, this study uses an optimized MaxEnt model to analyze the impact of past, present and future climate on the distributions of Codonopsis pilosula, an economic species, to provide a theoretical basis for its introduction and cultivation. Based on 264 distribution records and eight environmental variables, the potential distribution areas of C. pilosula in the last interglacial, middle Holocene and current periods and 2050 and 2070 were simulated. Combined with the percentage contribution, permutation importance, and jackknife test, the environmental factors affecting the suitable distribution area of this species were discussed. The results show that the parameters of the optimal model are: the regularization multiplier is 1.5, and the feature combination is LQHP (linear, quadratic, hinge, product). The main temperature factors affecting the distribution of C. pilosula are the annual mean temperature, mean diurnal range, and isothermality. The main precipitation factors are the precipitation seasonality, precipitation in the wettest quarter, and precipitation in the driest quarter, among which the annual average temperature contributes the most to the distribution area of this species. With climate warming, the suitable area of C. pilosula exhibits a northward expansion trend. It is estimated that in 2070, the suitable area of this species will expand to its maximum, reaching 2.5108 million square kilometers. The highly suitable areas of C. pilosula are mainly in Sichuan, Gansu, Shaanxi, Shanxi, and Henan Provinces. Our findings can be used to provide theoretical support related to avoiding the blind introduction of C. pilosula.

Diurnal Cycles of Synthetic Microwave Sounding Lower-Stratospheric Temperatures from Radio Occultation Observations, Reanalysis, and Model Simulations

An observationally-based global climatology of the temperature diurnal cycle in the lower stratosphere is derived from eleven different satellites with Global Positioning System-Radio Occultation (GPS-RO) measurements from 2006-2020. Methods used in our analysis allow for accurate characterization of global stratospheric temperature diurnal cycles, even in the high latitudes where the diurnal signal is small but longer timescale variability is large. A climatology of the synthetic Microwave Sounding Unit (MSU) and Advanced MSU (AMSU) Temperature in the Lower Stratosphere (TLS) is presented to assess the accuracy of diurnal cycle climatologies for the MSU and AMSU TLS observations, which have traditionally been generated by model data. The TLS diurnal temperature ranges are typically less than 0.4 K in all latitude bands and seasons investigated. It is shown that the diurnal range (maximum minus minimum temperature) of TLS is largest over southern hemisphere tropical land in the boreal winter season, indicating the important role of deep convection. The range, phase, and seasonality of the TLS diurnal cycle are generally well captured by the WACCM6 simulation and ERA5 reanalysis. We also present an observationally-based diurnal cycle climatology of temperature profiles from 300-10 hPa for various latitude bands and seasons and compare the ERA5 reanalysis with the observations.

The Effect of Geographical and Climatic Factors on the Distribution of Phlebotomus papatasi (Diptera: Psychodidae) in Golestan Province, an Endemic Focus of Zoonotic Cutaneous Leishmaniasis in Iran, 2014

Background: Phlebotomus papatasi is known as the main vector of zoonotic cutaneous leishmaniasis. This study aimed to investigate the effect of geographical and bioclimatic factors on the Ph. papatasi distribution. Methods: A total of 34 villages were selected, and sampling was performed three times using 120 sticky traps in each selected village. All the collected species were mounted and identified their species. The densities of Ph. papatasi were measured in all the villages and entered into ArcMap as a point layer. The required bioclimatic and environmental vari- ables were extracted from the global climate database and The normalized difference vegetation index was obtained from the MODIS satellite imagery, also, all variables entered into ArcMap as raster layers, so The numerical value of each independent variable in the cell where the selected village is located in this, was extracted using spatial analyst tools and the value to point submenu. All the data were finally entered into IBM SPSS, and the relationship was exam- ined between the number of collected Ph. papatasi and the independent variables using Spearman's correlation test. Results: A total of 1773 specimens of Ph. papatasi were collected. The findings of this study showed that max tem­perature of warmest month, temperature annual range, temperature seasonality, mean diurnal range, precipitation sea­sonality, mean temperature of driest and warmest quarter were positively associated with the density of Ph. papatasi. Conclusion: Air temperature and precipitation were shown as the most significant factors in the distribution of Ph. pa­patasi.

22 Years of Near-zero Cloud Cover Variability across Varying Geographical Landscapes of Southern Africa: A Surprising Anomaly

In physical geography, clouds are known to dictate global energy budgets and to have crucial ripple effects on other climatic variables such as diurnal range of temperature (DTR), a key indicator of climate change. Here, a 115-year state-of-the-art station based gridded dataset from the Climatic Research Unit (CRU) is interrogated to understand the evolution of cloud cover across southern Africa for the period 1901 - 2016. Results show near-constant variability from 1901 – 1922. It was therefore hypothesised that the observed near-constant variability would result in a similar pattern for some climatic variables such as DTR as the opposite would bring into question our current knowledge of geographical mechanisms underlying DTR control across the region. Further analyses showed little to no association between cloud cover and other climatological variables (including DTR) for the period 1901 – 1922 but strong and significant association from 1923 – 2016. This is the first observational evidence of near-constant cloud cover variability; it is surprising, and counterintuitive. This constant variation can be attributed to limited ground-based observations that went into the construction of the CRU gridded dataset during the 1901 – 1922 period and therefore, caution needs to be exercised by studies that need to use the data for the said period. This is a crucial area of scientific enquiry, and a lack of caution can lead to misleading conclusions on cloud cover evolution and how that relates to climate change.