Increase In Mean Precipitation Research Articles

Qualifying uncertainty of precipitation projections over China: mitigating uncertainty with emergent constraints

Predicting future mean precipitation poses significant challenges due to uncertainties among climate models, complicating water resource management. In this study, we introduce a novel methodology to mitigate uncertainty in future mean precipitation projections over China on a grid-by-grid basis. By constraining precipitation parameters of the Gamma distribution, we establish emergent constraints on parameters, revealing significant correlations between historical and future simulations. Our analysis spans the periods 2040–2069 and 2070–2099 under low-to-moderate and high emission scenarios. We observe reductions in uncertainty across most regions of China, with constrained mean precipitation indicating increases in monsoon regions and decreases in non-monsoon zones relative to raw projections. Notably, the observed 30%–40% increase in mean precipitation for the whole of China underscores the efficacy of our methodology. These observationally constrained results provide valuable insights into current precipitation projections, offering actionable information for water resource planning and climate adaptation strategies amidst future uncertainties.

Future changes in crop yield over Poland driven by climate change, increasing atmospheric CO2 and nitrogen stress

CONTEXTCrop production is strongly affected by climate-related factors that are predicted to become more severe in the future due to significant changes in temperature, rainfall patterns, and increase in the intensity and frequency of extreme events. Understanding potential future crop yield response to a changing climate is of great importance for food production stability and safety. OBJECTIVEThe overall objective of this study is to assess the impact of projected climate change on crop yield in Poland. METHODSThis study employed an agro-hydrological Soil and Water Assessment Tool (SWAT) model forced by EURO-CORDEX downscaled and bias-corrected climate model outputs to simulate future changes in yield of spring barley (Hordeum vulgare), rapeseed (Brassica napus), maize silage (Zea mays), and potato (Solanum tuberosum) over Poland driven by climate change, an increase in atmospheric CO2 concentrations, and plant growth stress factors. We looked into two future horizons: near future (NF; 2041–2060), and far future (FF; 2081–2100) under two different Representative Concentration Pathways (RCP4.5 and 8.5). RESULTS AND CONCLUSIONSClimate projections revealed that by the end of century, Poland will experience an increase of mean precipitation (by up to 10.3%) and mean temperature (+3.4 °C) under RCP8.5. We tested two different nitrogen fertilisation scenarios under changing climatic conditions, namely auto fertilisation which adjusted the nitrogen doses according to actual plant requirements in each climatic scenario, and constant doses corresponding to current use throughout the entire simulation period. The results showed that crops in Poland will experience an increase in nitrogen stress and a decrease in water stress in the future. Temperature stress is projected to increase for spring barley, rapeseed, and potato, and decrease for thermophilic maize silage. Auto fertilisation scenario application that eliminated nitrogen stress in future horizons resulted in a significant increase in yield of all crops under consideration. The comparison of the RCP scenarios showed a higher increase for RCP8.5, reaching 13% for NF and 17% for FF as an average value for all crops. For RCP4.5, the corresponding values were 10% (NF) and 13% (FF). Nitrogen stress reported under the constant nitrogen rate scenario offseted potential yield increase in future horizons caused by elevated CO2.The multi-annual average yield of the analysed crops in future increased by <5%. SIGNIFICANCEOur study indicated that future changes in crop yield in Poland are mostly related to CO2 enhancement, and benefitting fully from that will require an adjustment of nitrogen fertiliser rates. Otherwise, a potential increase in biomass production will be restricted by nitrogen availability.

Extreme climatic events to intensify over the Lake Victoria Basin under global warming

This paper presents an analysis of future precipitation patterns over the Lake Victoria Basin, East Africa, using bias-corrected CMIP6 model projections. A mean increase of about 5% in mean annual (ANN) and seasonal [March–May (MAM), June–August (JJA), and October–December (OND)] precipitation climatology is expected over the domain by mid-century (2040–2069). The changes intensify towards the end of the century (2070–2099) with an increase in mean precipitation of about 16% (ANN), 10% (MAM), and 18% (OND) expected, relative to the 1985–2014 baseline period. Additionally, the mean daily precipitation intensity (SDII), the maximum 5-day precipitation values (RX5Day), and the heavy precipitation events—represented by the width of the right tail distribution of precipitation (99p–90p)—show an increase of 16%, 29%, and 47%, respectively, by the end of the century. The projected changes have a substantial implication for the region—which is already experiencing conflicts over water and water-related resources.

Future Seasonal Changes in Extreme Precipitation Scale With Changes in the Mean

AbstractAtmospheric warming results in an intensification of annual precipitation over the globe but large uncertainties remain regionally and at seasonal scales, especially for extremes. Using 29 models from the Sixth Phase of the Coupled Model Intercomparison Project (CMIP6), we investigate future seasonal changes in extreme precipitation (under the scenario SSP5‐8.5) and how it compares to changes in mean precipitation. Over land, we find a strong intensification of the wettest day in all seasons over the mid and high latitudes of the Northern Hemisphere and over India during the monsoon. Extreme intensity decreases in the subtropics for some seasons, including over large regions around the Mediterranean basin and Southern Africa, and these drying patterns are not apparent in annual results. The key finding is that the CMIP6 multi‐model mean always shows that seasonal changes in mean and extreme precipitation align where there is high model agreement. That is, in all seasons by the end of the 21st century, extremes intensify in regions where mean precipitation increases and decline where mean precipitation decreases. This should not hide inherent uncertainties associated, namely the large range of changes intensity that can be found across the models, and an important modulation of the changes by internal variability. Yet, this study shows that the multi‐model mean shows broad consistency such that future seasonal changes in mean precipitation could be used to infer future changes in extremes (and vice versa), thus providing valuable information for risk planning and mitigation strategies.

More Intense, Organized Deep Convection With Shrinking Tropical Ascent Regions

AbstractChanges in the frequency and morphology of convection in a warming climate have major implications for the hydrologic cycle and continue to be a large source of variability in climate models. Recent studies of model output indicate a narrowing and intensification of the ascending branch of the Hadley circulation (i.e., the Intertropical Convergence Zone). The present work uses tropical ascent area fraction (Au) and Tropical Rainfall Measurement Mission precipitation features to study global tropical variability in convection with ascent area changes in the current climate. Ascent region convection becomes more intense and organized when Au is low. Overall increases in mean precipitation as the tropical ascent regions shrink are primarily driven by an increase in the areal extent of convective systems, rather than intensity of the convective system rainfall, suggesting an increase in the organization and aggregation of convection as the climate continues to warm.

Multi-model ensemble of statistically downscaled GCMs over southeastern South America: historical evaluation and future projections of daily precipitation with focus on extremes

High-resolution rainfall information is of great value, particularly over southeastern South America (SESA) where the observed and projected climate changes pose a substantial threat to socio-economic activities and the hydrological sector. Consequently, this work focuses on the construction of an unprecedented multi-model ensemble of statistically downscaled (ESD) global climate models (GCMs) for daily precipitation. Different statistical techniques were employed - including analogs, stochastic versions of regression-based models involving neural networks and generalised linear models and linear regressions conditioned by weather types - and a variety of CMIP5 and CMIP6 models. In general, most of the models added value in the representation of the main features of daily precipitation, especially in the spatial and intra-annual variability of extremes. The statistical models were sensible to the driving GCMs, although the ESD family choice also introduced differences among the simulations. The ESD projections depicted increases in mean precipitation associated with a rising frequency of extreme events - mostly during the warm season - following the observed trends over SESA. Change rates were consistent among downscaled models up to mid-21st century, when model spread started to emerge. Furthermore, these projections were compared to the available CORDEX-CORE RCM simulations, evidencing a consistent agreement between statistical and dynamical downscaling procedures in terms of the sign of the changes, presenting the main differences in their intensity. Overall, this study evidences the potential of statistical downscaling in a changing climate and contributes to its undergoing development over SESA.

Future Changes in Drought Frequency Due To Changes in the Mean and Shape of the PDSI Probability Density Function Under RCP4.5 Scenario

This study investigates the changes in the drought frequency in 2070–2099 relative to 1970–1999, due to the mean and shape changes of the probability density function (PDF) of the self-calibrated Palmer Drought Severity Index (PDSI), using CMIP5 multi-model historical simulations and projections under the RCP4.5 scenario. For severe droughts defined with PDSIs less than the 10th percentile, it is shown that over 41% of the global land, the increase in the severe drought frequency due to the shape change exacerbates the increase due to the mean change. Over 28% of the global land, the decrease in the drought frequency due to the shape change partially offsets the increase due to the mean change. Over 31% of the global land, the drought frequency increases due to the shape changes, but decreases due to the mean changes. The severe drought frequency due to both PDSI PDF mean and shape changes increases over almost the entire global land. We show that the PDSI standard deviation change is mainly determined by the mean precipitation change, while the PDSI mean change is determined by both mean precipitation and potential evapotranspiration changes. In particular, the PDSI standard deviation increases with the increase in mean precipitation which broadens the PDSI PDF, and thus enhances the severe drought frequency, and vice versa. On the other hand, the PDSI mean decreases with the decrease (increase) in mean precipitation (mean potential evapotranspiration). The difference in the attribution of drought frequency changes to the mean and shape changes over different regions can thus be largely explained by the mean precipitation and potential evapotranspiration changes. We also examine the moderate droughts defined with PDSIs between 10th and 20th percentiles in this study. For the moderate drought frequency, the spatial pattern of its changes due to the PDSI mean changes is similar to that of severe drought but with much smaller magnitudes, while its change in the spatial pattern due to the shape changes differs from severe drought with no significant changes. The moderate drought frequency due to both PDSI PDF mean and shape changes increases over 71% of the global land but decreases over 29% of the land.

Future urban heat island influence on precipitation

Urbanization and global warming are two of the major human impacts on the environment. The Urban Heat Island (UHI) effect can change precipitation patterns. Global warming also leads to changes in precipitation and especially an increase in intensity and frequency of extreme precipitation. With urbanization expected to grow in the future, the role of UHI in a warmer climate is an important research question. We present results from 20-year long regional convection-permitting model simulations that include the UHI effect, run for historical and future climates for two megacities, Paris and Shanghai. In the warmer future climate, urban-induced precipitation is found to decrease compared to the historical climate, for both mean and extreme precipitation, with large uncertainties due to natural variability. The mean precipitation increase due to UHI in Paris is 2.2± 1.4% and 1.8 ± 1.3% for historical and future conditions, respectively. Shanghai has slightly weaker mean precipitation change than Paris at present and no change in the future. The future reduction of the urban effect is found to be caused by a decrease in summer precipitation for both cities. Interannual variability in precipitation due to UHI is larger for Shanghai than Paris. The UHI effect on extreme precipitation is also reduced in the future climate and the area with precipitation increase is more concentrated. The general increase in extreme precipitation due to global warming, in combination with the precipitation redistribution due to UHI, underline the importance for future urban planning to mitigate damage caused by extreme precipitation events.

General characteristics of climate change over China and associated dynamic mechanisms during the Last Interglacial based on PMIP4 simulations

Investigation of climate change during the Last Interglacial (LIG, ~130–115 ka BP) may deepen our understanding of the response of climate to Earth's orbit. Here we examine climate change over China and associated mechanisms during the LIG using the lig127k experiments from the Paleoclimate Modeling Intercomparison Project Phase 4. We illustrate that annual mean surface air temperature over China decreases by 0.22 °C during the LIG relative to the preindustrial, with a colder climate in winter and spring, whereas a warmer climate in summer and autumn. Annual mean precipitation increases (up to 54%) over northern and southwestern China during the LIG, whereas it decreases (up to 11%) over the other parts. This pattern largely holds for precipitation change in summer during the LIG, but precipitation generally decreases in winter. According to the moisture budget equation, the nonlinear and horizontal dynamic terms contribute largely to the drier (wetter) conditions in summer over the south (north) of eastern China, whereas the horizontal dynamic term and the horizontal thermodynamic term is more important in regulating drier conditions over south and north of eastern China in winter, respectively. Furthermore, East Asian summer monsoon is intensified during the LIG manifested by anomalous southerly at 850 hPa, a westward shift of western North Pacific subtropical high, and poleward migration of East Asian westerly jet. East Asian winter monsoon also gets stronger during the LIG, with anomalous northerly at low-level troposphere, enhanced mid-tropospheric East Asian trough, and an equatorward shift of westerly jet at upper troposphere. Additionally, we note obvious data-model discrepancies in annual temperature change over China during the LIG, with cooling seen in the models but warming suggested by multiproxies. This highlights close collaboration between model and data communities in future to deepen our understanding of climate change during the LIG.

Assessment of observed and projected climate changes in Bačka (Serbia) using trend analysis and climate modeling

Climate change is one of the largest environmental issues causing hydroclimatological extremes such as floods, droughts, and aridity. The aim of this study is to assess the observed and projected climate changes in Bačka (Serbia). Detailed trend analyses and possible climate scenarios over Bačka has not been presented up to now. In this paper, four data sets were extracted and calculated: mean annual air temperature, mean air temperatures during the vegetation period, mean annual precipitation and total precipitation during the vegetation period. The presented parameters were obtained from the annual meteorological reports of the Republic Hydrometeorological Service of Serbia. Trend equation based on linear regression, trend magnitude according to the trend equation, and Mann-Kendall statistics have been used for trend analysis of climatic parameters. A GIS modeling of the possible climate scenario was created according to the Beijing Climate Center Climate System Model (BCC-CSM2-MR). Based on the trend equations, positive trends related to air temperature and precipitation variables are dominant. The trend magnitude shows the largest mean increase in all time series related to air temperature during the vegetation period. The highest mean precipitation increase occurs only in two time series. The Mann-Kendall statistics showed significantly positive trends in 11 cases and no changes in 9 cases. According to BCC-CSM2-MR, changes will be especially dominant in case of air temperatures. The expected changes in the total precipitation during the vegetation period show a tendency towards semiarid conditions. The presented results of observed and projected climate changes demand adaptation measures, especially from the aspect of sustainable agriculture.

Projected Changes in South Asian Monsoon Low Pressure Systems

AbstractMonsoon low pressure systems (MLPSs) are among the most important synoptic-scale disturbances of the South Asian summer monsoon. Potential changes in their characteristics in a warmer climate would have broad societal impacts. Yet, the findings from a few existing studies are inconclusive. We use the Geophysical Fluid Dynamics Laboratory (GFDL) coupled climate model CM4.0 to examine the projected changes in the simulated MLPS activity under a future emission scenario. It is shown that CM4.0 can skillfully simulate the number, genesis location, intensity, and lifetime of MLPSs. Global warming gives rise to a significant decrease in MLPS activity. An analysis of several large-scale environmental variables, both dynamic and thermodynamic, suggests that the decrease in MLPS activity can be attributed mainly to a reduction in low-level relative vorticity over the core genesis region. The decreased vorticity is consistent with weaker large-scale ascent, which leads to less vorticity production through the stretching term in the vorticity equation. Assuming a fixed radius of influence, the projected reduction in MLPSs would significantly lower the associated precipitation over north-central India, despite an overall increase in mean precipitation.

Differing precipitation response between solar radiation management and carbon dioxide removal due to fast and slow components

Abstract. Solar radiation management (SRM) and carbon dioxide removal (CDR) are geoengineering methods that have been proposed to mitigate global warming in the event of insufficient greenhouse gas emission reductions. Here, we have studied temperature and precipitation responses to CDR and SRM with the Representative Concentration Pathway 4.5 (RCP4.5) scenario using the MPI-ESM and CESM Earth system models (ESMs). The SRM scenarios were designed to meet one of the two different long-term climate targets: to keep either global mean (1) surface temperature or (2) precipitation at the 2010–2020 level via stratospheric sulfur injections. Stratospheric sulfur fields were simulated beforehand with an aerosol–climate model, with the same aerosol radiative properties used in both ESMs. In the CDR scenario, atmospheric CO2 concentrations were reduced to keep the global mean temperature at approximately the 2010–2020 level. Results show that applying SRM to offset 21st century climate warming in the RCP4.5 scenario leads to a 1.42 % (MPI-ESM) or 0.73 % (CESM) reduction in global mean precipitation, whereas CDR increases global precipitation by 0.5 % in both ESMs for 2080–2100 relative to 2010–2020. In all cases, the simulated global mean precipitation change can be represented as the sum of a slow temperature-dependent component and a fast temperature-independent component, which are quantified by a regression method. Based on this component analysis, the fast temperature-independent component of the changed atmospheric CO2 concentration explains the global mean precipitation change in both SRM and CDR scenarios. Based on the SRM simulations, a total of 163–199 Tg S (CESM) or 292–318 Tg S (MPI-ESM) of injected sulfur from 2020 to 2100 was required to offset global mean warming based on the RCP4.5 scenario. To prevent a global mean precipitation increase, only 95–114 Tg S was needed, and this was also enough to prevent global mean climate warming from exceeding 2∘ above preindustrial temperatures. The distinct effects of SRM in the two ESM simulations mainly reflected differing shortwave absorption responses to water vapour. Results also showed relatively large differences in the individual (fast versus slow) precipitation components between ESMs.

To what extent can cirrus cloud seeding counteract global warming?

The idea of modifying cirrus clouds to directly counteract greenhouse gas warming has gained momentum in recent years, despite disputes over its physical feasibility. Previous studies that analyzed modifications of cirrus clouds by seeding of ice nucleating particles showed large uncertainties in both cloud and surface climate responses, ranging from no effect or even a small warming to a globally averaged cooling of about 2.5 °C. We use two general circulation models that showed very different responses in previous studies, ECHAM6-HAM and CESM-CAM5, to determine which radiative and climatic responses to cirrus cloud seeding in a 1.5 × CO2 world are common and which are not. Seeding reduces the net cirrus radiative effect for −1.8 W m−2 in CESM compared with only −0.8 W m−2 in ECHAM. Accordingly, the surface temperature decrease is larger in CESM, counteracting about 70% of the global mean temperature increase due to CO2 and only 30% in ECHAM. While seeding impacts on mean precipitation were addressed in past studies, we are the first to analyze extreme precipitation responses to cirrus seeding. Seeding decreases the frequency of the most extreme precipitation globally. However, the extreme precipitation events occur more frequently in the Sahel and Central America, following the mean precipitation increase due to a northward shift of the Intertropical Convergence Zone. In addition, we use a quadratic climate damage metric to evaluate the amount of CO2-induced damage cirrus seeding can counteract. Seeding decreases the damage by about 50% in ECHAM, and by 85% in CESM over the 21 selected land regions. Climate damage due to CO2 increase is significantly reduced as a result of seeding in all of the considered land regions.

Climate State Dependence of Arctic Precipitation Variability

AbstractArctic precipitation is projected to increase more rapidly than the global mean in warming climates. However, warming‐induced changes in the variability of Arctic precipitation, which are related to surface evaporation and poleward moisture transport (PMT), are currently largely unknown. This study compares the precipitation variability in different quasi‐equilibrium climates simulated by a global climate model (EC‐Earth) and studies the underlying mechanisms. Five quasi‐equilibrium simulations of 400 years length forced with a broad range of CO2 concentrations (0.25, 0.5, 1, 2, and 4 times the current global mean) were analyzed. PMT is the dominant source of Arctic precipitation variability in colder climates when the ocean in the Arctic basin is completely covered by sea ice year‐round. Arctic precipitation variability increases from colder to warmer climates, primarily in summer. In summer, the increasingly stronger relation between Arctic sea level pressure variability and precipitation variability toward warmer climates enhances variability. In winter, the severe increase in mean precipitation (due to enhanced evaporation) exerts a comparatively small increase in variability, and precipitation variability is modulated by both PMT and evaporation, which oppose each other as they both affect the vertical and meridional moisture gradients.

Significant climate impacts of aerosol changes driven by growth in energy use and advances in emission control technology

Abstract. Anthropogenic aerosols have increased significantly since the industrial revolution, driven largely by growth in emissions from energy use in sectors including power generation, industry, and transport. Advances in emission control technologies since around 1970, however, have partially counteracted emissions increases from the above sectors. Using the fully coupled Community Earth System Model, we quantify the effective radiative forcing (ERF) and climate response to 1970–2010 aerosol changes associated with the above two policy-relevant emission drivers. Emissions from energy-use growth generate a global mean aerosol ERF (mean ± 1 standard deviation) of -0.31±0.22 W m−2 and result in a global mean cooling (-0.35±0.17 K) and a precipitation reduction (-0.03±0.02 mm d−1). By contrast, the avoided emissions from advances in emission control technology, which benefit air quality, generate a global mean ERF of +0.21±0.23 W m−2, a global warming of +0.10±0.13 K, and global mean precipitation increase of +0.01±0.02 mm d−1. Despite the relatively small changes in global mean precipitation, these two emission drivers have profound impacts at regional scales, in particular over Asia and Europe. The total net aerosol impacts on climate are dominated by energy-use growth, from Asia in particular. However, technology advances outweigh energy-use growth over Europe and North America. Various non-linear processes are involved along the pathway from aerosol and their precursor emissions to radiative forcing and ultimately to climate responses, suggesting that the diagnosed aerosol forcing and effects must be interpreted in the context of experiment designs. Further, the temperature response per unit aerosol ERF varies significantly across many factors, including location and magnitude of emission changes, implying that ERF, and the related metrics, needs to be used very carefully for aerosols. Future aerosol-related emission pathways have large temporal and spatial uncertainties; our findings provide useful information for both assessing and interpreting such uncertainties, and they may help inform future climate change impact reduction strategies.

Projected Change and Variability Assessment of Indian Summer Monsoon Precipitation in South Asia CORDEX Domain Under High-Emission Pathway

The regional climate model version 4 (RegCM4) is analyzed in this study to assess Indian summer monsoon precipitation (ISMP) over six homogeneous precipitation regions and various meteorological subdivisions of India embedded therein during a reference period (1976–2005) and mid- (2031–2060) and far-future (2070–2099) periods under the RCP8.5 scenario over the South Asia CORDEX domain. A Coupled Model Intercomparison Project (CIMIP5) global model GFDL-ESM2M provides initial and boundary conditions to the RegCM4 under the high-emission scenario RCP8.5. RegCM4 precipitation fields are validated against observed India Meteorological Department (IMD) and Asian Precipitation-Highly Resolved Observational Data Integration Toward Evaluation (APHRODITE) precipitation datasets, while wind and specific humidity fields obtained from RegCM4 are validated against National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysis and the parent GFDL model integrated fields. Model comparisons indicate that RegCM4 captures the regional characteristics of ISMP satisfactorily in terms of biases, trends, interannual variability, and circulation patterns. RegCM4 precipitation fields show high correlations of 0.9 and 0.8 with those of IMD and APHRODITE, respectively, and RegCM shows better skill in comparison with GFDL over about 68% of meteorological subdivisions. RegCM4 projects increases in precipitation by about 15.3% (28.4%), 5.1% (16.2%), and 5.4% (18.4%) respectively over the Northwest (NW), Northeast (NE) and Hilly Regions (HR) in the mid-(far-)future but decreases in precipitation over the Peninsular (PE) region by about −1.5% (−15.7%) during the same period. A similar precipitation change pattern is also found when analyzing the probability distribution functions (PDFs) over the same regions. The precipitation intensity (95th percentile) shows increases above 40% over numerous subdivisions of the West Central (WC), NW, and HR regions. The present analysis also reveals significant increases of more than 50% in mean precipitation over several meteorological subdivisions. Analysis of the circulation fields depicts a northward shift of the high-precipitation belt while high-pressure systems dominate the peninsular region when approaching the central India global warming scenario. It is interesting to note that the extreme precipitation index Rx5day exactly follows the pattern of projected increase in mean precipitation. In addition, it is noted that the projected variability and change in the mean precipitation are less frequent than for RX5day, while a consistently stronger spread in variability is projected in the mid- to far-future under the warming scenario.

Drought Event Analysis and Projection of Future Precipitation Scenario in Abaya Chamo Sub-Basin, Ethiopia

Monthly observed and future precipitation magnitudes were subjected to statistical trend analysis to examine possible time series behavior. Future precipitation was downscaled from large-scale output through statistical downscaling. The observed and downscaled future precipitation was analyzed for drought events using the Standardized Precipitation Index (SPI) method. In the Abaya Chamo sub-basin, Ethiopia precipitation is explained by below average magnitudes in most of the low land area, characterized by moderate to extreme drought episodes. Nine drought events were discerned during the period of 1988 to 2015, i.e. once in three years, resulting in harvest failure and subsequent food insecurity. The NCEP-NCAR and CanESM2 model predictors were used to statistically downscale the precipitation data. The monthly observed and downscaled precipitation magnitudes were in good agreement. The RCP-2.6, RCP-4.5 and RCP-8.5 long-term future scenarios were computed to evaluate future drought patterns. The mean annual precipitation scenario decreased by 0.2% to 13.7%, 0.5% to 6.4% and 0.1% to 1.3% for the period from 2016 to 2040, 2050s and 2080s respectively. The increase in mean precipitation was projected to be 0.7% to 12.2%, 0.2% to 11.7% and 0.1% to 17.8% for the period from 2016 to 2040, 2050s and 2080s respectively. The present analysis may provide useful information associated to drought events to decision makers and can be used as a basis for future research in this area.

Precipitation Trends over the Indus Basin

A large population relies on water input to the Indus basin, yet basinwide precipitation amounts and trends are not well quantified. Gridded precipitation data sets covering different time periods and based on either station observations, satellite remote sensing, or reanalysis were compared with available station observations and analyzed for basinwide precipitation trends. Compared to observations, some data sets tended to greatly underestimate precipitation, while others overestimate it. Additionally, the discrepancies between data set and station precipitation showed significant time trends in such cases, suggesting that the precipitation trends of those data sets were not consistent with station data. Among the data sets considered, the station-based Global Precipitation Climatology Centre (GPCC) gridded data set showed good agreement with observations in terms of mean amount, trend, and spatial and temporal pattern. GPCC had average precipitation of about 500 mm per year over the basin and an increase in mean precipitation of about 15% between 1891 and 2016. For the more recent past, since 1958 or 1979, no significant precipitation trend was seen. Among the remote sensing based data sets, the Tropical Rainfall Measuring Mission Multi-Satellite Precipitation Analysis (TMPA) compared best to station observations and, though available for a shorter time period than station-based data sets such as GPCC, may be especially valuable for parts of the basin without station data. The reanalyses tended to have substantial biases in precipitation mean amount or trend relative to the station data. This assessment of precipitation data set quality and precipitation trends over the Indus basin may be helpful for water planning and management.

Trends in Drought over the Northeast United States

The Northeast United States is a generally wet region that has had substantial increases in mean precipitation over the past decades, but also experiences damaging droughts. We evaluated drought frequency, intensity, and duration trends in the region over the period 1901–2015. We used a dataset of Standardized Precipitation Evapotranspiration Index (SPEI), a measure of water balance based on meteorology that is computed at multiple timescales. It was found that the frequency of droughts decreased over this period, but their average intensity and duration did not show consistent changes. There was an increase in mean SPEI, indicating mostly wetter conditions, but also in an increase in SPEI variance, which kept the likelihood of extremely dry conditions from decreasing as much as would be expected from the wetter mean state. The changes in the SPEI mean and variance, as well as the decrease in drought frequency, were most pronounced for longer timescales. These results are consistent with the paradigm of hydrologic intensification under global warming, where both wet and dry extremes may increase in severity alongside changes in mean precipitation.

Height-Diameter Allometry for Tree Species in Tanzania Mainland

Total tree height (H) and diameter at beast height (D) are important independent variables in predicting volume, biomass, and other forest stand attributes. However, unlikeDmeasurement, which is easy to measure with high accuracy,Hmeasurement is laborious. This study, therefore, developedH-Drelationships for ten different forest types in Tanzania Mainland. Extents in which climate and forest stand variables explain the variation inH-Dallometry were also assessed. A total of 31782 sample trees covering miombo woodlands, humid montane, lowland forests, bushlands, grasslands, mangroves, cultivated land, wetlands forests, and pines andEucalyptusspecies plantations were used for model development. TheHestimating model without climate and forest stand variables referred herein as “base model” was first developed followed by “generalized model” which included climate and stand variables. All the data were fitted using nonlinear mixed effect modelling approach. Results indicated that generalizedHestimating models had better fit than the base models. We therefore confirm a significant contribution of climate and forest structure variables in improvingH-Dallometry. Among the forest structure variables, basal area (BA) was far more important explanatory variable than other variables. In addition, it was found that the mean treeHtends to increase with the increase of mean precipitation (PRA). We therefore conclude that forest specific generalizedHmodel is to be applied when predictingH. When forest type information is not available, generalized regional model may be applied. Base model may be applied when forest stand or climate information are missing.