Middle east warming in spring enhances summer rainfall over Pakistan

Domain: earth_science
Published: 2023-11-22
Editorial outcome: major_revision

Abstract
The edge of a monsoon region is usually highly sensitive to climate change. Pakistan, which is located on the northern edge of the Indian monsoon, is highly vulnerable to heavy rainfall and has witnessed several debilitating floods exacerbated by global warming in recent years. However, the mechanisms for the frequent Pakistan floods are yet not fully understood. Here, we show that the Middle East is undergoing an increase in land heating during spring, which is responsible for 46% of the intensified rainfall over Pakistan and northwestern India during 1979–2022. This springtime land warming causes a decline in sea level pressure (SLP), which strengthens the meridional SLP gradient between the Middle East and the southern Arabian Sea and drives the changes of low-level jet (LLJ) subsequently. The impact persists into summer and results in a northwards shift of the monsoonal LLJ, accompanied by strong positive vorticity in the atmosphere and enhanced moisture supply to Pakistan. Consequently, the transition region between the summer monsoon in South Asia and the desert climate in West Asia is shifted northwestward, posing significantly enhanced risk of flood over Pakistan and northwestern India.

Introduction
In the past four decades, record-breaking floods have been reported over Pakistan and northwestern India frequently1,2. Climatologically, Pakistan is an arid to semi-arid region (Supplementary Fig. 1). Nevertheless, it has experienced flooding every year since 2010 as reported by the Ministry of Water Resources of Pakistan. In 2010, Pakistan suffered an unprecedented flooding due to heavy monsoon rainfall. Twenty million people were affected, and the death toll was nearly 20003. In 2022, the devastating flood in Pakistan caused by abnormal summer rainfall became the worst natural disaster in the country’s history4. According to the Pakistan National Disaster Management Authority, the flood left one-third of the country submerged, at least 1739 dead, and 8 million displaced5. The damages and economic losses were over 30 billion U.S. Dollars (Pakistan’s GDP was 310 billion U.S. Dollars in 2022) and the reconstruction required more than 16 billion U.S. Dollars. This event is a poster-child for climate extremes, climate change impacts, and consequences of climate vulnerability. The satellite imagery reveals a 20–50% increase in the proportion of the population exposed to floods from 2000 to 2015 in Pakistan, and the proportion is expected to continue to increase out to 20306. Since 1979, the summer monsoon rainfall has increased by 46% over Pakistan and northwestern India (black box in Fig. 1a; see Methods), with a significantly increasing trend of 0.4–0.6 mm day−1 decade−1. The rainfall increases over Pakistan are pronounced and robust among different satellite products (Supplementary Fig. 2). Thus, there is an urgent need to understand the physical mechanism that is responsible for the debilitating heavy rainfall events over Pakistan.

Moisture supply for the summer rainfall along the west coast of the Indian subcontinent is mainly transported from the Arabian Sea by the low-level jet (LLJ)7,8. The LLJ is sustained by the land-sea thermal contrast around the Indian Ocean, with the orography of the East African highlands helping to channel the cross-equatorial flow into a jet9,10. That results in the strong southwesterly winds from the ocean to the land. The southwesterly winds associated with LLJ that sweep across the Arabian Sea onto the Indian subcontinent are a quintessential signature of the Indian summer monsoon (ISM)11. The LLJ also feeds on the cross-equatorial southerly winds, which transport moisture and support the convection over the entire Indian monsoon region. It accounts for nearly half of the global interhemispheric transport of air in the lower troposphere during ISM12,13.

In this study, we show that the enhanced Middle East warming under global warming leads to a persistent poleward shift of LLJ and thrusts the moisture supplies northward, bringing unprecedented rainfall to Pakistan. The Middle East warming is almost two times faster than other inhabited parts of the world14,15. The consequent poleward shift of the LLJ over the Arabian Sea causes a dramatic increase in atmospheric instability and rainfall over Pakistan and northwestern India. Unlike the wet-get-wetter paradigm16,17, the mechanism proposed here tends to turn the arid region into a rainy one. However, the observed increase in the devastating rainfall over Pakistan is largely missed by the historical climate simulations of most CMIP6 models. Such inadequate warning will leave millions of people unprepared in terms of adaptation to global warming risks.

Results
Northward shift of low-level jet induces Pakistan’s rainfall under global warming
Over Pakistan and nearby northwestern India (black box in Fig. 1; 20°N-30°N; 65°E-78°E), the regional rainfall has increased by 46% or equivalent to 0.37 mm day−1 decade−1 (Lines in Fig. 1b) from 1979 to 2022. The regressed vorticity anomaly onto the Pakistan’s summer rainfall index for all summers from 1979 to 2022. The locations where the regressed vorticity is zero are marked with a red line. The red line represents the position of Low-level jet (LLJ) maxima in summer. b The regression coefficient of the absolute vorticity (shading; unit: day−1) onto the normalized Pakistan’s summer rainfall index in summer during the period of 1979–2022. The rainfall index displays the typical characteristics of LLJ18, since LLJ is defined as the line with zero absolute vorticity at 850 hPa (see Methods). Positive (negative) vorticity lies over northern (southern) Arabian Sea (Fig. 2a). The climatological LLJ location (see Methods) is around 10°N over the Arabian Sea with positive vorticity just to the north over the ocean and western-southwestern India (Supplementary Fig. 3a). The regressed positive vorticity anomaly extends into northwestern India and Pakistan, which shares a similar spatial pattern with the trends in LLJ (Supplementary Fig. 3b). Since 1979, the LLJ has shown a northward shift over the Arabian Sea as previously reported19,20. The northernmost latitudinal location is shifted to approximately 18°N off western India. In addition, the trend in the LLJ location index (see Methods) is approximately 0.27° latitudes per decade from 1979 to 2022 (red bars and the red line in Fig. 3c). Correspondingly, the regressed summer rainfall anomaly onto the LLJ location index displays a pronounced increase over Pakistan and northwestern India (Fig. 2b). This suggests that the LLJ shift is vital to rainfall enhancement over Pakistan.

Middle East heating in spring leads to northward shift of Low-Level Jet
To understand the mechanism of the northward shift of LLJ, we regress the spring land skin temperature onto the summer LLJ location index and find significant positive changes over the Middle East (30°N-50°N; 45°E-70°E; Fig. 3a). From 1979 to 2022, the spring heating over the Middle East has a significant increasing trend (Fig. 3b). It implies that the intensified surface heating over the Middle East has pulled the LLJ northward. We employ the mean skin temperature in spring within the Middle East as the land heating index, which displays a notably increasing trend of 0.5°C decade−1 (blue bars and the blue line in Fig. 3c). We examine the scatter plot between the land heating over the Middle East in spring and the LLJ location in summer in past 44 years from 1979 to 2022 (Fig. 3d). The correlation coefficient between these two components is 0.82, which is statistically significant at the 99% confidence level. The significant relationship indicates that a warmer Middle East during spring is favorable for the northward shift of summer LLJ. In summary, the northward shift of LLJ due to the continuous Middle East heating in spring causes heavy summer rainfall over Pakistan and northwestern India.

Dynamical bounds between Middle East warming and increasing rainfall in Pakistan
Under global warming, the Middle East heating pulls the entire dynamical system responsible for the excess Pakistan’s rainfall via LLJ northward. During boreal spring, a large-scale meridional surface temperature gradient develops due to the different heat capacities of the land and the adjoining ocean through the seasonal cycle of solar radiation21. Due to the net effect of anthropogenic forcing22,23, the Middle East is warming faster during spring starting around 1979, as shown by the land heating differences between the earlier period (1979–2000) and the recent period (2000–2022) (Fig. 4a). The maximum temperature difference is 2°C (shading over land in Fig. 4a). As a result of the land warming in spring, the sea level pressure (SLP) over the nearby landmasses to the north of the Arabian Sea reduces by ~120–200 Pa by increasing the sensible heat fluxes (contours in Fig. 4a; Supplementary Fig. 4a), which enhances the northward pressure gradient force from the southern to the northern Arabian Sea. This meridional pressure gradient drives geostrophic winds in the lower troposphere along isobars (vectors in Fig. 4a) resulting in a weak cyclonic gyre at 10°N over the Arabian Sea (shading over sea in Fig. 4a). The land heating persists from spring to early summer. Its impacts on SLP, horizontal winds, and low-level vorticities also persist coherently until the southwesterly wind anomalies penetrate far to the north of 20°N (vectors in Fig. 4b). Consequently, the LLJ lies over the Arabian Sea (red contour in Fig. 4b) as a cyclonic (anticyclonic) gyre is reinforced over northern (southern) Arabian Sea (shading over sea in Fig. 4b; Supplementary Fig. 4b). Consistently, we see pronounced kinetic energy (Supplementary Fig. 4c) in the western Indian Ocean and prevailing southwesterly winds over the Arabian Sea. As a result, the cyclonic gyre associated with LLJ in summer is significantly strengthened to the north of the Arabian Sea, in particular over Pakistan (Fig. 4c). The moisture instability and atmospheric barotropic instability are both increased over Pakistan due to the northward shifted LLJ (Supplementary Fig. 5). Consequently, the regions become unstable and favorable for deep convection24,25. In addition, the LLJ is accompanied by strong westerly winds and a pronounced positive vorticity, which provide a track for the invasion of the low-pressure systems into Pakistan, and transport moisture from the BoB to further nourish the floods26,27. Meanwhile, vertically integrated moisture transport (VIMT; shading over sea in Fig. 4d; see Methods) yields distinct positive moisture anomalies over Pakistan. By decomposing the VIMT, the southwest direction of VIMT is evidenced (vectors in Fig. 4d) and mainly corresponds to the LLJ. It indicates that the intensified moisture supply is largely transported from the Arabian Sea by the LLJ to Pakistan and northwestern India in the recent period of 2000–2022. As a consequence, the summer rainfall (shading over land in Figs. 2b and 4d) is intensified over Pakistan and northwestern India, which is roughly confined to 20°N−30°N and 65°E−78°E. In summary, the sustained effects of spring land heating push the LLJ to the north, leading to an increase in vorticity and moisture supply to northwestern India and Pakistan, which eventually leads to enhanced rainfall over these regions during summer.

Methods
Datasets
Monthly atmospheric horizontal and vertical winds, specific humidity, sea level pressure, and skin temperature are obtained from ERA5 reanalysis provided by the European Center for Medium-Range Weather Forecasts31. The period is from 1979 to 2022 and the spatial resolution is 0.25° latitude × 0.25° longitude. The reanalysis products from NCEP-NCAR32 are also employed to ensure the robustness of the results, which are not shown in the main text because the results are qualitatively the same as ERA5. Monthly precipitation data are obtained from the Global Precipitation Climatology Project (GPCP)33 and the CPC Merged Analysis of Precipitation (CMAP)34, with a horizontal resolution of 2.5°. Monthly precipitation data with a horizontal resolution of 0.25° from the Tropical Rainfall Measuring Mission (TRMM)35 are also employed in the analyses. The skin temperatures are used to represent land heating. The spring season is defined as March to May (MAM), and the summer season corresponds to the monsoon, i.e., June to September (JJAS). The early summer season corresponds to May–June (MJ). All analyses using observations are conducted for the period from 1979 to 2022.

Twenty coupled atmosphere-ocean general circulation models (CGCMs) of the sixth phase of Coupled Model Inter-comparison Project (CMIP6) are used (Supplementary Table 2). Monthly outputs of surface temperature, rainfall and horizontal winds are obtained from the selected models, including the historical simulations and the projections under three scenarios, namely the Shared Socioeconomic Pathway 2-4.5 (SSP2-4.5), SSP3-7.0, and SSP5-8.5. To compare with observations over the same period, the outputs for the period of 1979–2014 are selected. The resulting fields from each model are interpolated to a grid of 2.5° latitude × 2.5° longitude to calculate the multi-model ensemble mean (MMEM). To clarify the relative impacts of external forcing and internal variability on the rainfall trend, the MMEM of 192 model members from the CMIP6 is used to estimate the contribution of external forcing, whereas the contribution of internal variability is estimated by the difference between the observed trend and the MMEM trend. The uncertainty is evaluated with one standard deviation of the trend in each member. For more details about the CMIP6 models, see https://esgf-node.llnl.gov/projects/cmip6/.

LLJ definition
The LLJ maxima are considered as the zero absolute wind vorticity anomalies at 850 hPa18. Accordingly, positive and negative absolute vorticities are observed on the northern and the southern sides of LLJ, respectively. Therefore, the location of the LLJ maximum, that is zero absolute vorticity, is taken as the proxy for the LLJ location. The LLJ shift is determined by the change in the zonally averaged LLJ location over the Arabian Sea using the location of absolute vorticity being zero. As the pronounced LLJ shift occurs over the eastern Arabian Sea, the LLJ location index is determined by the zonal mean between 60°E and 75°E within 5°N and 25°N. It is consistent with the distinct changes in positive vorticity anomalies over Pakistan and nearby regions.

Trend and its statistical significance
The Sen’s slope method is applied to obtain linear trends, which is the most popular non-parametric technique for determining linear trends36. Accordingly, the trends in summer rainfall (Fig. 1), spring land heating (Fig. 3b), and summer LLJ (Supplementary Fig. 3b) are determined from 1979 to 2022 by the Sen’s slope method. Similarly, the simulated trends in summer rainfall over Pakistan and spring land heating over the Middle East are also obtained by the Sen’s slope method during 1979–2014. The Mann–Kendall test is applied to evaluate the 95% significance level of the linear trends. In addition, changes in variables are also explored by dividing the study period of 1979–2022 into two subperiods: the earlier period of 1979–2000 and the recent period of 2001–2022. The composite differences are used to explore the changes in each variable (Fig. 4), and the significance is determined using a standard two-tailed Student’s t-test. Moreover, the Student’s t-test is also applied to assess the significance of regression analyses.

Moisture transport
The vertically integrated moisture transport (VIMT) is used to measure the moisture supply. Following Chen37, Godfred-Spenning and Reason38, the VIMT is calculated by

VIMT = 1/g ∫ps ptop qV dp, (1)

where V = (u, v) and u and v are the zonal and meridional winds; q is the specific humidity; g is the acceleration due to gravity; ps and ptop are 1000 hPa and 300 hPa, respectively. In the tropics, the specific humidity above 300 hPa is at least two orders of magnitude smaller than near the surface, and the moisture transports therefore contribute little to the total VIMT39. In this way, the zonal and meridional components of VIMT are calculated by 1/g ∫ps ptop qu dp and 1/g ∫ps ptop qv dp, respectively.

Data availability
The data that support the findings of this study are freely available. The ERA5 reanalysis products are provided by the European Centre for Medium-range Weather Forecast (ECMWF), which can be obtained from their website at https://cds.climate.copernicus.eu/. The NCEP/NCAR reanalysis product, the GPCP and the CMAP datasets are all publicly available from the National Oceanic and Atmospheric Administration (NOAA; https://psl.noaa.gov/data/gridded/. The TRMM dataset is available at https://disc.gsfc.nasa.gov/datasets/TRMM_3B42_7/. The CGCM outputs from CMIP6 are produced by the World Climate Research Programme’s Working Group at https://esgf-node.llnl.gov/projects/cmip6/.

Code availability
The data in this study were analyzed with NCAR Command Language (NCL; http://www.ncl.ucar.edu/). All relevant codes used in this study are available, upon request, from the corresponding author.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "Dear Authors,\nI appreciate the efforts taken by the authors to find out the reason for the frequent Pakistan flood.\nHowever, the present study failed in cifing some relevant works and lacking in-depth analysis.\nPlease find my comments and suggesfions below to improve the arficle\n1. The present study links the middle east land warming to the increasing rainfall over Pakistan and\nnorth-west India, which can intensify the floods over Pakistan. The proposed mechanism is the land\nwarming causes a reducfion in the surface pressure, which enhances the meridional pressure gradient\nbetween the Middle East and the Southern Arabian Sea, causing a poleward shift in the locafion of the\nLLJ. The northward shifted LLJ enhances the atmospheric vorficity and moisture supply to north-west\nIndia as well as Pakistan and thereby enhances the monsoon rainfall. However, a similar mechanism is\nalready explained by Sandeep and Ajayamohan, (2015). How the mechanism explained in the present\nstudy differ from Sandeep and Ajayamohan’s, (2015) mechanism?\n2. The locafion and intensity of LLJ are influenced by the deep convecfion over India and nearby oceans\n(Joseph and Sijikumar, 2004; Sijikumar and Aneesh, 2022). What is the role played by the recent changes\nin the convecfion paftern over the Indian land region and the nearby oceanic parts in the observed\nnorthward propagafion of LLJ?\n3. According to Ofto et al., 2023, the flood during the monsoon season in Pakistan is mainly caused by\nthe advecfion of moisture from the Bay of Bengal and the Arabian Sea, associated with the dynamic\nfeatures in the atmosphere, such as the mid-lafitudinal jet stream (E.g.- 2010 flood). The floods are also\ncaused by the movement of monsoonal depressions originafing in the Bay of Bengal and travelling over\nthe Indo-Gangefic plains or central India, thereby causing high rainfall over Pakistan (E.g.- 2022 flood).\nThus, the root cause of the floods in Pakistan is the episodes of heavy rainfall events caused by the\nabove-menfioned mechanisms. How the formafion of depressions and the mid-lafitudinal jet streams\nhave changed due to the middle east land warming and how has it influenced the flood over Pakistan?\n4. Is the regression coefficient calculated after removing the linear trend from the variable?\nIf regression coefficients are not calculated after removing the linear trend, then replot all the figures\nshowing the regression coefficients after detrending the variables.\n5. Line 129: How surface warming can cause ~120-200 hPa Sea level pressure change?\n6. The unit of summer monsoon rainfall trend in Figure 1 and Supplementary Figure 2 is mm decade-1.\nThe unit mm decade-1 or mm day-1 decade-1?\n7. Please add the following relevant references to the arficle\nJoseph, P.V., Sijikumar, S. (2004) Intraseasonal variability of the low-level jet stream of the Asian summer\nmonsoon. J Clim 17(7):1449–1458\nOfto et. Al., (2023). Climate change increased extreme monsoon rainfall, flooding highly vulnerable\ncommunifies in Pakistan. Environ. Res.: Climate 2 025001. hftps://doi.org/10.1088/2752-5295/acbfd5\nSandeep, S., & Ajayamohan, R.S. (2015). Poleward shift in Indian summer monsoon low level jetstream\nunder global warming. Clim Dyn 45, 337–351. hftps://doi.org/10.1007/s00382-014-2261-y\nSijikumar, S., & Aneesh, S. (2022) Role of deep convecfion in regulafing the Indian summer monsoon\ndynamics: a regional scale modelling study. Meteorol Atmos Phys 134, 84.\nhftps://doi.org/10.1007/s00703-022-00917-2\nAs a substanfial amount of work is required before publicafion, I have suggested a major revision or\nrejecfion as per Editor's choice due to fime restricfions.", "reviewer_2": "Title: Middle East Warming in Spring Enhances Summer Floods over Pakistan\nAuthors: Baosheng Li, Lei Zhou, Jianhuang Qin, Tianjun Zhou, Dake Chen, Raghu Murtugudde\nJournal: Nature Communicafions\nRecommendafion: Major Revision\nManuscript Summary:\nThis arficle invesfigates the relafionship between summer floods over Pakistan with surface warming\nover Middle East from 1979 to 2022. It highlights the importance of understanding the possible causes of\nextreme precipitafion that leads to anomalous summer floods. First, the authors explain the physical\nprocesses of moisture transport over the Arabian Sea. It is the low-level jet (LLJ) that is responsible for\nthe channeling the moisture-rich air mass from the Arabian Sea to Pakistan and nearby western India.\nOver 44 years, the LLJ has been shifting northward and thus bringing more moisture to Pakistan. A\nstafisfical analysis shows a close relafionship between the surface warming over the Middle East and the\nlocafion of the LLJ. Second, there is also data-driven evidence that the mean rainfall over Pakistan has\nbeen increasing from 1979 to 2022. The comparison between the data of the first period and the second\nperiod shows this increase quanfitafively.\nThis study is interesfing and suitable for Nature Communicafions. However, I am concerned with the low\ncorrelafion coefficient (0.4) between the surface heafing over the Middle East and the low-level jet (LLJ)\nlocafion. My final decision is major revisions specially to address the correlafion issue for this round of\nreview.\nMajor Comments:\n1. The fitle clearly says that the study has something to do with summer floods. In the text however the\nanalysis is more on the increased precipitafion, not floods. I also think there is a jump from rainfall to\nfloods. In reality, there are processes that translate rainfall into floods. This may include for instance the\ntexture (type) of the soil in Pakistan, that maybe has low absorpfion capacity like in many semi-arid\nregions. I believe it is the case. The soil perhaps similar to that in the Arabian Peninsula or the Southwest\nUS. To avoid misleading, it would be befter to revise the fitle to directly describe what is being discussed\nin the text. For instance, the fitle is “Middle East Warming in Spring Enhances Summer Rainfall over\nPakistan”.\n2. Lines 77 to 79. I am not sure if this sentence is fair to climate models. First, I do not think that flood is\none of the variables in many climate models (unless there is a hydrological model that runs climate\npredicfion). Second, climate model spafial resolufion is generally coarse. Extreme rainfall can only best\nbe captured in high-resolufion model such as a convecfive-permifting model.\n3. Lines 112 to 114. I am a bit surprised that the correlafion coefficient between the surface heafing over\nthe Middle East and the LLJ locafion is 0.4. I do not think that it is a good correlafion score and I do not\nthink we can claim this a close relafionship. Will this correlafion coeff increase if you use another level\nlike temperature at 850 mb? Or will this be different if you use SLP? I think this is the quanfitafive\nevidence that mainly supports your argument.\n4. Lines 124 to 126. I am concerned with the beginning of this sentence (“Due to the net effect of\nanthropogenic forcing, …”). Reader will ask how the authors know that it is the net effect of\nanthropogenic forcing. If you want to keep this claim, I think you will need another dataset such as CO2\nemission and its stafisfical analyses in the period of 1979 to 2022. It would be easy if there is already a\npublished study that show this anthropogenic forcing over the Middle East in that period.\nMinor comments:\nSummary:\nNo comment.\nMain Text:\nLines 48, 49, 50: Please change USD to U.S. Dollars (and put it after the billion).\nLines 62 to 64: Please add one or two references at the end of the sentence.\nLine 76: Please add a reference (or two) after “Unlike the wet-get-wefter paradigm”.\nResults:\nLine 85: Please remove the ~ (filde sign) so that it is consistent with the one in Summary.\nLine 85: Please change to “… increased by 46% or equivalent to 0.37 mm decade-1 (Lines in Fig. 1b) …”\nLine 97: change per decade to decade-1.\nLine 108: remove the lafitude and longitude since you have it already in line 104.\nDiscussion:\nLine 166: As menfioned in major comment, I am concerned with the statement “close relafionship”.\nLines 173 to 174: Please add a reference (or two) for this sentence.\nLine 184: Is 0.28 mm decade-1 the observed trend? If so, please make it clear.\nMethods:\nLine 252: Please change qudp to qu dp"}, "author_response": "Responses to Reviewers\nReviewer #1:\nI appreciate the efforts taken by the authors to find out the reason for the frequent\nPakistan flood. However, the present study failed in citing some relevant works and\nlacking in-depth analysis.\nResponse:\nThank you. We greatly appreciate the insightful suggestion. The manuscript is\nrevised accordingly. We hope all issues are satisfactorily addressed.\nPlease find my comments and suggestions below to improve the article\n1. The present study links the middle east land warming to the increasing rainfall over\nPakistan and north-west India, which can intensify the floods over Pakistan. The\nproposed mechanism is the land warming causes a reduction in the surface pressure,\nwhich enhances the meridional pressure gradient between the Middle East and the\nSouthern Arabian Sea, causing a poleward shift in the location of the LLJ. The\nnorthward shifted LLJ enhances the atmospheric vorticity and moisture supply to\nnorth-west India as well as Pakistan and thereby enhances the monsoon rainfall.\nHowever, a similar mechanism is already explained by Sandeep and Ajayamohan,\n(2015). How the mechanism explained in the present study differ from Sandeep and\nAjayamohan’s, (2015) mechanism?\nResponse:\nnorthward shift of low-level jet (LLJ), and this paper was cited in our original\nmanuscript. However, there are significant and meaningful differences between the\ncurrent study and Sandeep and Ajayamohan (2015). We explain these here;\n1) We highlight the remarkably rapid warming and the influence of surface\nwarming over the Middle East. Sandeep and Ajayamohan (2015) argued that\nthe LLJ shift was a response to the land-sea temperature contrast between the\nSoutheast Asian landmass and the surrounding Indian Ocean, and we agree with\nthat. In this study, we argue that surface warming in the Middle East is the main\ncause for the land-sea contrast, as the warming there is twice as significant as\nin all other regions over the world.\n2) The seasons are different in the two studies. Sandeep and Ajayamohan (2015)\nfocused on the summer monsoon, and we show consistent results with them\nduring boreal summer. In addition, we extend the story to spring, i.e., we unveil\nthe seasonal lead relationship between spring land heating and summer rainfall.\nThe spring heating in the Middle East is a precursor for the summer flooding,\nwhich helps to predict climate hazards on the northern edge of Indian monsoon.\nFor example, the Middle East was unusually warm during the spring of 2023,\nwhich has led to anomalously high rainfall over Pakistan and northwest India\nfrom June onwards this summer (Fig. A1).\n3) The northward shift of the monsoonal LLJ directly leading to the enhancement\nof Pakistan rainfall is discussed in this study, which was not covered in Sandeep\n2\nand Ajayamohan (2015). In the revised manuscript, we examine the instabilities\nover Pakistan and northwest India in more detail and more evidence is provided.\nAs shown in Fig. A2a-b, the Middle East warming and LLJ northward shift\n(cid:3105)(cid:3118)(cid:3048)\ninduces a meridional gradient of quasi-geostrophic potential vorticity ((cid:2010)− )\n(cid:3105)(cid:3052)(cid:3118)\nto change signs within the study region. The regressed pattern agrees with the\n(cid:3105)(cid:3118)(cid:3048)\ntrend in (cid:2010)− (Fig. A2c), with a zonal belt of a negative–positive–negative\n(cid:3105)(cid:3052)(cid:3118)\npattern in Pakistan and northwest India. The changes of signs satisfy the\nnecessary condition for barotropic instability. In addition, the difference in\nmoist static energy (MSE) between 1000 and 500 hPa is a good index for static\ninstability. Out results show that the Middle East warming and LLJ shift, cause\na positive difference in MSE in the study region (Fig. A3), which enhances the\natmospheric instability over Pakistan. Overall, the changes in the instabilities\ndue to the Middle East warming and the LLJ northward shift, favor the onset of\nheavy rainfall.\nIn summary, in this study, we present a novel and important phenomenon, i.e., the\nfrequent and severe rainfall in the past few decades over Pakistan, which is\nclimatologically an arid to semi-arid region on the northern edge of Indian monsoon.\nThe whole process originates from the Middle East heating in spring which is likely\nattributable to global warming and includes the northward shift of LLJ, the increase of\nmoisture transport from the Arabian Sea to land, and the reinforcement of atmospheric\ninstabilities over Pakistan. The entire process of the Middle East warming influence is\n3\nillustrated in Fig. A4. The mechanisms for the entire chain of processes are examined.\nSandeep and Ajayamohan (2015) proposed a mechanism for the northward shift of LLJ.\nOur results extend their results significantly while being consistent with theirs, and their\nconclusions also support our findings. The new findings are further clarified in the\nrevision.\nFigure A1 (a) Spring land heating anomalies in 2023 (unit: °C) from the climatological\nmean of 1979-2022 from March to May. (b) Monthly precipitation in June of 2023 (unit:\nmm day-1) from the climatological mean of 1979-2022 during June.\nFigure A2 Regression coefficients of the meridional gradient of quasi-geostrophic\n(cid:3105)(cid:3118)(cid:3048)\npotential vorticity ((cid:2010)− ; unit: m-1 day-1) in summer (JJAS) onto the normalized (a)\n(cid:3105)(cid:3052)(cid:3118)\nspring land heating and (b) summer LLJ index over the 1979-2022. (c) Trend in the\n4\nmeridional gradient of quasi-geostrophic potential vorticity from 1979 to 2022 (unit:\nm-1 day-1 decade-1). The dotted areas are significant at the 95% confidence level using\nthe Students' t-test.\nFigure A3 Regression coefficients of the vertical difference of moist static energy\nbetween 1000 and 500 hPa (unit: J kg-1) in early summer onto the normalized (a)\nspring land heating and (b) summer LLJ index over the 1979-2022. (c) Trend in the\nvertical difference of moist static energy between 1000 and 500 hPa from 1979 to 2022 (unit: J\nkg-1 decade-1). The dotted areas are significant at the 95% confidence level using the\nStudents' t-test.\nin Pakistan.\n2. The location and intensity of LLJ are influenced by the deep convection over India\nand nearby oceans (Joseph and Sijikumar, 2004; Sijikumar and Aneesh, 2022).\nWhat is the role played by the recent changes in the convection pattern over the\nIndian land region and the nearby oceanic parts in the observed northward\npropagation of LLJ?\nResponse:\nWe thank the reviewer for the heuristic comment. Joseph and Sijikumar (2004)\nshowed that atmospheric heating by convection over the Bay of Bengal (BoB) is able\nto accelerate the LLJ. Sijikumar and Aneesh (2022) re-examined the relationship with\nthe regional model experiments, and further pointed out that the lack of convective\nheating in the Western Ghats and BoB weakened the LLJ over the Peninsular India. We\nagree that deep convection can alter the LLJ activity.\nWe have also previously analyzed the relationship between LLJ and convection\nunder climate change. In our previous study (Li et al. 2022), we revealed that the deep\nconvection starts to move deeper into the subtropics in comparison with the\nclimatological state (Fig. A5). It leads to the enhancement in convective rainfall over\nPakistan and northwest India. Through the diagnosis of the moisture budget, we\nproposed that the northward shift of the LLJ is responsible for the deep convection\nmovement in that study. The specific physical process can be found in Li et al. (2022).\n(Fig. A6). In early summer (May-July), the deep convection is roughly confined to\nnorthwest India. Theoretically, convective heating can trigger circulation adjustments\nand accelerate the LLJ, as reported by Joseph and Sijikumar (2004) and Sijikumar and\nAneesh (2022). In this way, the enhanced LLJ can shift northward and cause deep\nconvection over Pakistan during mid-summer (June-August). Accordingly, the deep\nconvection will be pushed further north during later summer (July-September).\nTherefore, the positive feedback between the summer LLJ and deep convection is\nestablished during the ISM season.\nHowever, it must be recognized that the enhancement of deep convection in\nPakistan is a consequence of the northward shift of LLJ. Their relationship only exists\nin summer, but not at the seasonal lead timescale. This study elicits the main cause of\nthe northward shift of LLJ, that is the spring time interaction between climate change\nmanifest in the Middle East warming and natural variability in terms of the seasonal\nmonsoon evolution. In other words, we have proposed a positive feedback between\ndeep convection and the LLJ that is initiated in spring itself. In all, the reason for the\nseasonal change of LLJ is mainly demonstrated in the manuscript.\nthe period of 1982–2017: (a) rainfall (mm day-1 decade-1) and (b) OLR (W m-2 decade-\n1). The dotted areas are significant at the 95% confidence level using the Mann-Kendall\ntest. (Adapted from Figure 1 of Li et al. 2022)\nsummer LLJ index over the 1979-2022 period: (a) MJJ; (b) JJA; (c) JAS. The dotted\nareas are significant at the 95% confidence level using the Students' t-test.\n9\n3. According to Otto et al., 2023, the flood during the monsoon season in Pakistan is\nmainly caused by the advection of moisture from the Bay of Bengal and the Arabian\nSea, associated with the dynamic features in the atmosphere, such as the mid-\nlatitudinal jet stream (E.g.- 2010 flood). The floods are also caused by the\nmovement of monsoonal depressions originating in the Bay of Bengal and travelling\nover the Indo-Gangetic plains or central India, thereby causing high rainfall over\nPakistan (E.g.- 2022 flood). Thus, the root cause of the floods in Pakistan is the\nepisodes of heavy rainfall events caused by the above-mentioned mechanisms. How\nthe formation of depressions and the mid-latitudinal jet streams have changed due\nto the middle east land warming and how has it influenced the flood over Pakistan?\nResponse:\nWe agree that Pakistan floods need sufficient moisture from both Bay of Bengal\n(BoB) and Arabian Sea. As the reviewer states, the major difference between the two\nflood events in 2010 and 2022 (Fig. A7), besides the moisture from the BoB, is the\nmore abundant moisture supply from the Arabian Sea in 2022 (Fig. A7b). Therefore,\nthe change in moisture supply from the Arabian Sea is the most important cause of\nextreme flooding in Pakistan, which is closely related to the LLJ shift. It inspired us to\nexamine the changes in LLJ in recent years. In addition, the LLJ is accompanied by the\nstrong westerly wind and pronounced positive vorticity, which could provide a track\nfor the low-pressure systems (LPSs) to propagate (e.g., Krishnamurthy and\nAjayamohan, 2010; You and Tian et al. 2021). Therefore, the northward-shifted LLJ\nfavors the invasion of LPSs into Pakistan, and transport some moisture from the BoB\nto further nourish the floods. It has been further discussed on Lines 150-152 in the\nrevised manuscript.\n(vectors) in (a) 2010 and (b) 2022 from the climatological mean of 1979-2022 during\nJJAS.\nIt is well established that in 2010, the changes in the mid-latitude jet stream caused\nflooding in Pakistan. Figure A8a displays the summer mean geopotential heights at 200\nhPa in 2010 with a prominent trough over Afghanistan (black dotted line in Fig. A8a).\nHong et al. (2010) found that the southward penetration of the deep trough was vital to\nthe 2010 Pakistan flooding. It was due to the cold temperature anomaly with the deep\ntrough extended southward along the Northern Arabian Sea. The upper-level trough\ntended to cause ascending motions on its fore-side, which favor the convection\ndevelopment. However, the Middle East warming cannot be expected to induce a\npronounced negative anomaly in the upper troposphere (Fig. A8b). It is not likely that\nthe mid-latitude jet stream is an effective way to link Pakistan's rainfall and the Middle\nEast warming.\nSome previous studies (Hong et al. 2010; Webster 2011; Otto et al. 2023) did\npoint out that that the mid-latitude jet stream tended to cause a flood in the northern\n11\nmountainous region in Pakistan, such as the northern province of Khyber Pakhtunkhwa\nand northwestern Balochistan. However, we focus on the rainfall change centered in\nsouthern and central low-elevation regions. Therefore, the mid-latitude jet stream is not\nentirely relevant for our study here.\nFigure A8 (a) The seasonal mean geopotential heights in 200 hPa during JJAS of 2010.\n(b) Regression of seasonal mean 200 hPa geopotential heights onto the normalized\nspring heating index. The black dotted line denotes the pressure trough. The blue boxes\ndenote the rainfall maximum in Pakistan and northwest India.\nReferences:\nKrishnamurthy, V., and R. S. Ajayamohan, 2010: Composite Structure of Monsoon Low\nPressure Systems and Its Relation to Indian Rainfall. J. Climate, 23, 4285–4305.\nand Rainfall Extremes Since the Late 1970s. Geophys Res Lett 48,\ndoi:10.1029/2021gl092378 (2021).\nHong, C.-C., H.-H. Hsu, N.-H. Lin, and H. Chiu, 2011: Roles of European blocking and\ntropical-extratropical interaction in the 2010 Pakistan flooding. Geophys Res Lett,\n38.\nOtto et. Al., (2023). Climate change increased extreme monsoon rainfall, flooding\nhighly vulnerable communities in Pakistan. Environ. Res.: Climate 2 025001.\nhttps://doi.org/10.1088/2752-5295/acbfd5.\nWebster, P., V. E. Toma, and H.-M. Kim, 2011: Were the 2010 Pakistan floods\npredictable? Geophysical Research Letters, 38 (4).\n4. Is the regression coefficient calculated after removing the linear trend from the\nvariable? If regression coefficients are not calculated after removing the linear\ntrend, then replot all the figures showing the regression coefficients after detrending\nthe variables.\nResponse:\nWe regret the error in the original statement. Our study focuses on the impact of\nthe Middle East warming, rather than the variability between the Middle East warming\nand summer rainfall over Pakistan. As can be seen from Fig. A9, the relationship\nbetween the Middle East and LLJ becomes much stronger if the interannual variability\nis removed, which denotes that the impact of the Middle East on Pakistan through LLJ\nis mainly reflected at the lower frequency.\nnormalized summer LLJ location index during the period of 1979-2022. (b) Same as (a)\nbut by applying a 7-year moving average. The dotted areas are significant at the 95%\nconfidence level using the Student’s t-test.\n5. Line 129: How surface warming can cause ~120-200 hPa Sea level pressure change?\nResponse:\nWe regret the typo. The unit should be Pa. To add further details, Figure A10\ndisplays that the Middle East warming can decrease the sea level pressure by increasing\nthe sensible heat fluxes. Thank you for your comment, this is explained in detail in the\nrevised manuscript (Line 131).\nFigure A10 Regression coefficients of the spring sensible heat flux (unit: W m-2) onto\nthe normalized spring land heating index during the period of 1979-2022. The dotted\nareas are significant at the 95% confidence level using the Student’s t-test.\n14\n6. The unit of summer monsoon rainfall trend in Figure 1 and Supplementary Figure\n2 is mm decade-1. The unit mm decade-1 or mm day-1 decade-1?\nResponse:\nThank you for your eye to the details. The unit should be mm day-1 decade-1 and it\nis revised accordingly.\n7. Please add the following relevant references to the article\nJoseph, P.V., Sijikumar, S. (2004) Intraseasonal variability of the low-level jet stream\nof the Asian summer monsoon. J Clim 17(7):1449–1458\nOtto et. Al., (2023). Climate change increased extreme monsoon rainfall, flooding\nhighly vulnerable communities in Pakistan. Environ. Res.: Climate 2 025001.\nhttps://doi.org/10.1088/2752-5295/acbfd5\nSandeep, S., & Ajayamohan, R.S. (2015). Poleward shift in Indian summer monsoon\nlow level jetstream under global warming. Clim Dyn 45, 337–351.\nhttps://doi.org/10.1007/s00382-014-2261-y\nSijikumar, S., & Aneesh, S. (2022) Role of deep convection in regulating the Indian\nsummer monsoon dynamics: a regional scale modelling study. Meteorol Atmos Phys\n134, 84. https://doi.org/10.1007/s00703-022-00917-2\nResponse:\nThey have been cited in the revised manuscript. Thank you very much.\nTitle: Middle East Warming in Spring Enhances Summer Floods over Pakistan\nAuthors: Baosheng Li, Lei Zhou, Jianhuang Qin, Tianjun Zhou, Dake Chen, Raghu\nMurtugudde\nJournal: Nature Communications\nRecommendation: Major Revision\nManuscript Summary:\nThis article investigates the relationship between summer floods over Pakistan with\nsurface warming over Middle East from 1979 to 2022. It highlights the importance of\nunderstanding the possible causes of extreme precipitation that leads to anomalous\nsummer floods. First, the authors explain the physical processes of moisture transport\nover the Arabian Sea. It is the low-level jet (LLJ) that is responsible for the channeling\nthe moisture-rich air mass from the Arabian Sea to Pakistan and nearby western India.\nOver 44 years, the LLJ has been shifting northward and thus bringing more moisture\nto Pakistan. A statistical analysis shows a close relationship between the surface\nwarming over the Middle East and the location of the LLJ. Second, there is also data-\ndriven evidence that the mean rainfall over Pakistan has been increasing from 1979 to\n2022. The comparison between the data of the first period and the second period shows\nthis increase quantitatively. This study is interesting and suitable for Nature\nCommunications. However, I am concerned with the low correlation coefficient (0.4)\nbetween the surface heating over the Middle East and the low-level jet (LLJ) location.\nMy final decision is major revisions specially to address the correlation issue for this\n16\nround of review.\nResponse：\nThank you for your insightful suggestions. We have revised the manuscript\naccordingly. The correlation coefficient has increased to above 0.8 after a more careful\nexamination, and the specific analysis can be found in the third response below. We\nhope that all changes are to the satisfaction of the reviewer.\nMajor Comments:\n1. The title clearly says that the study has something to do with summer floods. In the\ntext however the analysis is more on the increased precipitation, not floods. I also\nthink there is a jump from rainfall to floods. In reality, there are processes that\ntranslate rainfall into floods. This may include for instance the texture (type) of the\nsoil in Pakistan, that maybe has low absorption capacity like in many semi-arid\nregions. I believe it is the case. The soil perhaps similar to that in the Arabian\nPeninsula or the Southwest US. To avoid misleading, it would be better to revise the\ntitle to directly describe what is being discussed in the text. For instance, the title is\n“Middle East Warming in Spring Enhances Summer Rainfall over Pakistan”.\nResponse:\nWe regret the inaccurate title. The title is revised according to the suggestion of the\nreviewer.\n2. Lines 77 to 79. I am not sure if this sentence is fair to climate models. First, I do\n17\nnot think that flood is one of the variables in many climate models (unless there is\na hydrological model that runs climate prediction). Second, climate model spatial\nresolution is generally coarse. Extreme rainfall can only best be captured in high-\nresolution model such as a convective-permitting model.\nResponse:\nThe reviewer is correct that flooding is not one of the model outputs. Precipitation\nis still the variable that we analyze in the model section. We have revised the\nexpressions in the new manuscript, hopefully, avoiding any confusion.\n3. Lines 112 to 114. I am a bit surprised that the correlation coefficient between the\nsurface heating over the Middle East and the LLJ location is 0.4. I do not think that\nit is a good correlation score and I do not think we can claim this a close\nrelationship. Will this correlation coeff increase if you use another level like\ntemperature at 850 mb? Or will this be different if you use SLP? I think this is the\nquantitative evidence that mainly supports your argument.\nResponse:\nAs the reviewer suggests, we re-consider the definition of the LLJ index. The\nmoisture supply and the dynamic instability for enhanced rainfall over Pakistan are\nmuch more tightly associated with the eastern side of LLJ. Therefore, we define a new\nLLJ index as zonally averaged between 60°E and 75°E. Accordingly, the correlation\ncoefficient of this newly defined LLJ index for spring land heating rises to above 0.7,\nbeing significant in the Middle East region of our interest (blue rectangle in Fig. B1a).\nthe northward movement of the LLJ. The correlation coefficient of these two indices\nreaches 0.9 and it is statistically significant at a 99% confidence level. Moreover, since\nwe focus on the changes on a long timescale, the correlation coefficient is as high as\n0.82 after removing the high-frequency interannual signals (Fig. B1b). Overall, we\nthink these boosted quantitative relationships only better support the arguments in this\nstudy. Thank you once again.\nFigure B1 (a) Correlation coefficients of the spring skin temperature (unit: °C) onto\nthe normalized summer LLJ location index during the period of 1979-2022. The dotted\nareas are significant at the 95% confidence level using the Student’s t-test. (b) The\nscatter plot between the Middle East land heating in spring (x-axis; unit: °C) and\nsummer LLJ location (y-axis; unit: degree) in each year from 1979 to 2022. The time\nseries are run through a 7-year moving average. The black line shows the least squares\nregression of the scattered dots.\n19\n4. Lines 124 to 126. I am concerned with the beginning of this sentence (“Due to the\nnet effect of anthropogenic forcing, …”). Reader will ask how the authors know that\nit is the net effect of anthropogenic forcing. If you want to keep this claim, I think\nyou will need another dataset such as CO2 emission and its statistical analyses in\nthe period of 1979 to 2022. It would be easy if there is already a published study\nthat show this anthropogenic forcing over the Middle East in that period.\nResponse:\nWe thank the reviewer for the comments. Several recent studies have been cited\nto support the statement (e.g., Cramer et al. 2018; Eyring et al. 2021; Zittis et al. 2016).\nEyring et al. (2021) argued that the pronounced warming is related to anthropogenic\nactivities and is mostly driven by elevated global concentrations of greenhouse gases\nin the atmosphere. IPCC (2021) reported that there is an increase in land warming in\nthe Middle East and Central Asia, with high confidence in human contribution to the\nobserved change. Furthermore, Zittis et al. (2022) pointed out that the warming trends\nare projected to continue and intensify depending on future tendencies of greenhouse\ngas concentrations which, in turn, are subject to societal and technological\ndevelopments. In all, the relevant references are cited here to support the claim, as Line\n127 in the revision.\nEyring, V., Gillett, N. P., Achutarao, K., Barimalala, R., Barreiro Parrillo, M., Bellouin,\nN., et al. (2021). Human influence on the climate system: Contribution of working\ngroup I to the sixth assessment report of the Intergovernmental panel on climate\n20\nchange. IPCC Sixth Assessment Report.\nCramer, W., Guiot, J., Fader, M. et al. Climate change and interconnected risks to\nsustainable development in the Mediterranean. Nature Clim Change 8, 972–980\n(2018).\nIPCC. (2021). Summary for policymakers. In V. Masson-Delmotte, P. Zhai, A. Pirani,\nS. L. Connors, C. Péan, S. Berger, et al. (Eds.), Climate change 2021: The physical\nscience basis. Contribution of working group I to the sixth assessment report of\nthe intergovernmental panel on climate change. Cambridge University Press.\nZittis, G., Hadjinicolaou, P., Fnais, M., & Lelieveld, J. (2016). Projected changes in\nheat wave characteristics in the Eastern Mediterranean and the Middle East.\nRegional Environmental Change, 16(7), 1863–1876.\nZittis, G., Almazroui, M., Alpert, P., Ciais, P., Cramer, W., Dahdal, Y., et al. (2022).\nClimate change and weather extremes in the Eastern Mediterranean and Middle\nEast. Reviews of Geophysics, 60, e2021RG000762.\nMain Text:\nLines 48, 49, 50: Please change USD to U.S. Dollars (and put it after the billion).\nResponse:\nThe unit is corrected in the revision. Thank you for your eye to the details.\nLines 62 to 64: Please add one or two references at the end of the sentence.\nResponse:\nChakraborty, A., Nanjundiah, R., & Srinivasan, J. (2002). Role of Asian and African\norography in Indian summer monsoon. Geophysical Research Letters, 29(20),\n501–504.\nKrishnamurti, T. N., Molinari, J., & Pan, H. L. (1976). Numerical simulation of the\nSomali jet. Journal of the Atmospheric Sciences, 33(12), 2350–2362.\nLine 76: Please add a reference (or two) after “Unlike the wet-get-wetter paradigm”.\nResponse:\nThe following references have been cited here. Thank you.\nChou, C., and J. D. Neelin, 2004: Mechanisms of Global Warming Impacts on Regional\nTropical Precipitation*. Journal of Climate, 17, 2688-2701.\nChou, C., J. D. Neelin, C.-A. Chen, and J.-Y. Tu, 2009: Evaluating the “Rich-Get-\nRicher” Mechanism in Tropical Precipitation Change under Global Warming.\nJournal of Climate, 22, 1982-2005.\nResults:\nLine 85: Please remove the ~ (tilde sign) so that it is consistent with the one in Summary.\nResponse:\nIt is removed in the revision. Thank you for your eye to the details.\nLine 85: Please change to “… increased by 46% or equivalent to 0.37 mm decade-1\n22\n(Lines in Fig. 1b) …”\nResponse:\nWe thank the reviewer for the suggestion. It is revised in the new manuscript.\nLine 97: change per decade to decade-1.\nResponse:\nIt is corrected accordingly.\nLine 108: remove the latitude and longitude since you have it already in line 104.\nResponse:\nAs per your suggestion, they have been removed for clarity.\nDiscussion:\nLine 166: As mentioned in major comment, I am concerned with the statement “close\nrelationship”.\nResponse:\nThe correlation coefficient has been improved in the revised manuscript. In\naddition, it is significant at the 99% confidence level using the Student’s t-test. Based\non the analysis, they have a close statistical relationship with each other.\nLines 173 to 174: Please add a reference (or two) for this sentence.\nResponse:\nnumerical models on the simulation of summer precipitation. In the new manuscript,\nwe have repositioned it to follow the analysis in Supplement Figure 5.\nLine 184: Is 0.28 mm decade-1 the observed trend? If so, please make it clear.\nResponse:\nYes, 0.28 mm day-1 decade-1 is the observed trend, which is used here to compare\nwith the simulated intensity. The expression is modified accordingly in the revision.\nMethods:\nLine 252: Please change qudp to qu dp\nResponse:\nThank you for your eye to the details. It is revised.\n24"}, {"round": 2, "reviewer_comments": {"reviewer_1": "Comments to the Authors:\nThe authors have aftempted to address most of the raised concerns, which improved the quality of the\nmanuscript. I'm lisfing some comments below that I would like to be addressed in a revised manuscript\nbefore considering it for publicafion in Nature Communicafion.\n1.Sandeep and Ajayamohan (2015) has shown that the enhanced land-sea thermal contrast\nstrengthened the cross-equatorial sea level pressure gradient over the Indian Ocean, which caused the\nnorthward shift of the LLJ. To calculate the land-sea thermal gradient, they used a northern box (20°N–\n35°N and 40°E–80°E) which includes parts of the Middle East, Pakistan and north-west India (See Fig. 7\nto 9 in Sandeep and Ajayamohan (2015)).\nSince the strengthening and the poleward shift of LLJ in the recent decades have already been reported\nin the literature, please cite those arficles (Sandeep and Ajaymohan (2015); Aneesh and Sijikumar (2016)\netc.) in the ‘Result session’. Also, highlights the uniqueness of the present study in comparison with the\nprevious studies.\n2. Studies have shown that the Middle East confinues to warm under the future global warming\nscenario. The projected Middle East warming may cause a further northward shift of LLJ and\nenhancement of Pakistan's summer rainfall. Evaluate the future changes of LLJ and its contribufion to\nthe changes in the Pakistan rainfall, under the different future projecfion scenarios.\n3. The changes in the rainfall paftern can be due to the combined effect of anthropogenic forcing and the\ninternal variability of the climate system. Find out the relafive contribufion of internal variability and the\nexternal forcing in the observed changes of Pakistan's summer rainfall.\nReferences\nAneesh S, Sijikumar S (2016) Changes in the South Asian monsoon low level jet during recent decades\nand its role in the monsoon water cycle. J Atmos Solar Terr Phys 138–139:47–53.\nSandeep, S., and R. S. Ajayamohan (2015), Poleward shift in Indian summer monsoon low level jetstream\nunder global warming, Climate Dynamics, 45(1-2), 337–351.", "reviewer_2": "My decision is to accept this manuscript for publicafion with pending for minor revision. Please see the\naftachment.\nAftachment:\nTitle: Middle East Warming in Spring Enhances Summer Rainfall over Pakistan\nAuthors: Baosheng Li, Lei Zhou, Jianhuang Qin, Tianjun Zhou, Dake Chen, Raghu Murtugudde\nJournal: Nature Communicafions\nRecommendafion: Accept with pending for minor revision\nMinor comments:\nLine 192: Is the observed precipitafion here from GPCP, and referred to Supplement Figure 6?\nIf yes, in my opinion, you should menfion it here and also menfion it in the capfion of Supplement\nFigure 6."}, "author_response": "Responses to Reviewers\nReviewer #1:\nThe authors have attempted to address most of the raised concerns, which improved the\nquality of the manuscript. I'm listing some comments below that I would like to be\naddressed in a revised manuscript before considering it for publication in Nature\nCommunication.\nResponse:\nThank you. We greatly appreciate the insightful suggestion. The manuscript is\nrevised accordingly. Please see our point-by-point response below. We hope all issues\nare satisfactorily addressed.\n1.Sandeep and Ajayamohan (2015) has shown that the enhanced land-sea thermal\ncontrast strengthened the cross-equatorial sea level pressure gradient over the Indian\nOcean, which caused the northward shift of the LLJ. To calculate the land-sea thermal\ngradient, they used a northern box (20°N–35°N and 40°E–80°E) which includes parts\nof the Middle East, Pakistan and north-west India (See Fig. 7 to 9 in Sandeep and\nAjayamohan (2015)). Since the strengthening and the poleward shift of LLJ in the recent\ndecades have already been reported in the literature, please cite those articles (Sandeep\nand Ajaymohan (2015); Aneesh and Sijikumar (2016) etc.) in the ‘Result session’. Also,\nhighlights the uniqueness of the present study in comparison with the previous studies.\nResponse:\nThe related articles have been cited in the result session of the revised manuscript.\nThe significant and meaningful differences between the current and the previous studies\nare listed here for convenience;\n1) We highlight surface warming in the Middle East as the main cause for the land-\nsea temperature contrast, rather than the relationship between the LLJ and land-\nsea contrast proposed in Sandeep and Ajayamohan (2015).\n2) We unveil the seasonal lead relationship between spring land heating and\nsummer rainfall. The seasons are different from the previous studies. Both\nSandeep and Ajaymohan (2015), and Aneesh and Sijikumar (2016) only\nfocused on the summer season. We deem that the lead relationship will advance\npredictive capabilities and hence a significant advance. We hope the reviewer\nagrees.\n3) The consequence of the northward shifted LLJ in causing the enhancement of\nPakistan rainfall is the new finding of this study and has not been reported in\nprevious literature. The northward shift of LLJ is critical to the understanding\nof the frequent and severe floods over Pakistan since it is a severely climate\nvulnerable country.\nIn summary, we have developed a novel physical framework that reasonably\nexplains how the Middle East warming affects rainfall over Pakistan by the northward\nshift of LLJ. The new findings are further clarified in the revision.\n2. Studies have shown that the Middle East continues to warm under the future global\nwarming scenario. The projected Middle East warming may cause a further northward\nshift of LLJ and enhancement of Pakistan's summer rainfall. Evaluate the future\nchanges of LLJ and its contribution to changes in the Pakistan rainfall, under the\ndifferent future projection scenarios.\nResponse:\nFollowing the reviewer’s suggestion, future changes of LLJ and its contribution to\nchanges in Pakistan rainfall are evaluated under three scenarios, namely the Shared\nSocioeconomic Pathway 2-4.5 (SSP2-4.5), SSP3-7.0 and SSP5-8.5. The results are\npresented in Lines 186-192 of the revised manuscript. We also briefly summarized the\nmajor results of the new analysis below for your convenience. We thank the reviewer\nfor this excellent suggestion which has expanded the scope of our study.\nIn our original manuscript, we have evaluated 20 CMIP models in simulating the\ntrend in summer rainfall over Pakistan during 1979-2014 (Fig. A1). Fourteen models\nhave the ability to simulate an increasing trend as that in observations. Among these\nmodels, only 11 models are available for scenario projections, which are shown in bold\nin Table A1. Thereby, the monthly rainfall and horizontal winds from these eleven\nmodels under SSP2-4.5, SSP3-7.0, and SSP5-8.5 scenarios are selected. The multi-\nmodel ensemble mean (MMEM) is calculated by the average of the trend (LLJ and\nrainfall) for each model in the period of 2015-2100.\nAs shown in Table 2, the summer LLJ is projected to move northward in all three\nscenarios. The northward shift rates are 0.06o decade-1 under SSP2-4.5, 0.12o decade-1\nunder SSP3-7.0, and 0.17o decade-1 under SSP5-8.5, respectively. They become larger\nfrom the lowest-emission (SSP2–4.5) to the highest-emission (SSP5–8.5) scenario,\nwhich is consistent with the trends in Pakistan summer rainfall. The trend of rainfall is\n0.02 mm day-1 decade-1 under SSP2-4.5, 0.05 mm day-1 decade-1 under SSP3-7.0, and\n0.1 mm day-1 decade-1 under SSP5-8.5.\nThe square of the correlation coefficient (R2) between the LLJ and Pakistan from\n2015 to 2100 is used to represent the contribution of LLJ to the Pakistan rainfall.\nAccordingly, the LLJ contributes 44% of the change in Pakistan rainfall under SSP2-\n4.5, 59% under SSP3-7.0 and 88% under SSP5-8.5. Therefore, the LLJ and its\nnorthward shift play an important role in Pakistan rainfall under all future scenarios.\nFigure A1 Dependence of the model simulations between the trend in Pakistan rainfall\nin summer and the trend in Middle East land heating in spring. The x-axis denotes the\ntrend in Middle East land heating in spring from 1979 to 2014. The y-axis is the trend\nin Pakistan's rainfall in summer from 1979 to 2014. All models from the CMIP6 are\nlabeled by different markers.\nTable A1 Institutions, horizontal resolutions for atmospheric components, and the\nnumber of realizations of the 20 models analyzed from the CMIP6. The bold are 11\nmodels used to determine the future changes in horizontal winds and rainfall with\nSSP2-4.5, SSP3-7.0, and SSP5-8.5 provided.\nNumber of\nModel Name Resolution Institution\nRealizations\nACCESS-CM2 144 x 192 Commonwealth Scientific and Industrial Research 2\nACCESS-ESM1-5 145 x 192 Organization (Australia) 3\nBCC-CSM2-MR 160 x 320 3\nBeijing Climate Center (China)\nBCC-ESM1 64 x 128 3\nCAS-ESM2-0 128 x 256 Chinese Academy of Sciences (China) 50\nCanadian Centre for Climate Modelling and Analysis\nCanESM5 64 x 128 4\n(Canada)\nCESM2 192 x 288 10\nNational Center for Atmospheric Research,\nCESM2-FV2 96 x 144 3\nClimate and Global Dynamics Laboratory\nCESM2-WACCM 192 x 288 3\n(USA)\nCESM2-WACCM-\n96 x 144 3\nFV2\nE3SM1-0 180 x 360 E3SM-Project, Department of Energy (USA) 5\nEC-Earth3-Veg 256 x 512 European Centre for Medium-Range Weather Forecasts 5\nFGOALS-f3L 180 x 288 Institute of Atmospheric Physics, Chinese Academy of 3\nFGOALS-g3 80 x 180 Sciences (China) 3\nNational Oceanic and Atmospheric Administration,\nGFDL-ESM4 180 x 288 3\nGeophysical Fluid Dynamics Laboratory (USA)\nGISS-E2-1-G 90 x 144 Goddard Institute for Space Studies (USA) 38\nIPSL-CM6A-LR 143 x 144 Institute Pierre-Simon Laplace (France) 32\nAtmosphere and Ocean Research Institute, National\nMIROC6 128 x 256 Institute for Environmental Studies and Japan Agency for 10\nMarine-Earth Science and Technology (Japan)\nMRI-ESM2-0 160 x 320 Meteorological Research Institute (Japan) 6\nNorESM2-LM 96 x 144 Norwegian Climate Centre (Norway) 3\nTable A2 Trend in the northward movement in LLJ (unit: o decade-1) and Pakistan\nrainfall (mm day-1 decade-1) under three scenarios. R2 is the square of the correlation\ncoefficient of the time series between LLJ movement and Pakistan rainfall. It denotes\nthe contribution of LLJ movement to the rainfall changes.\nSSP2-4.5 SSP3-7.0 SSP5-8.5\nLLJ movement 0.06 0.12 0.17\nPakistan rainfall 0.02 0.05 0.1\nR2 44% 59% 88%\n3. The changes in the rainfall pattern can be due to the combined effect of\nanthropogenic forcing and the internal variability of the climate system. Find out the\nrelative contribution of internal variability and the external forcing in the observed\nchanges of Pakistan's summer rainfall.\nResponse:\nThank you for raising this important issue. The relative contributions of internal\nvariability and the external forcing to the changes in Pakistan summer rainfall are\nestimated by the multi-models from the CMIP6. The results are included in the revised\nmanuscript (Lines 193-200) and they are briefly summarized below.\nWe use historical runs from 20 CMIP6 coupled models. There are 192 members\nin total (see detailed in Table. A1). The contribution of external forcing to rainfall is\nestimated by averaging the MMEM of CMIP6 members, whereas the contribution of\ninternal variability is estimated by the difference between the observed trend and the\nMMEM trend. The uncertainty is evaluated with one standard deviation of the trend in\neach member. Besides, the linear trend in Pakistan rainfall is calculated for each model\nsimulation and, subsequently, averaged across all ensemble members.\nAs shown in Fig. A2, the summer rainfall in Pakistan has increased in observations\n(GPCP), the MMEM, and their difference over the time period of 1979-2014. It\nsuggested that that both external forcing and internal variability contribute to the\nrainfall enhancement in the past decades. Meanwhile, the observed regional mean of\nthe Pakistan rainfall trend is about 0.28 mm day-1 decade-1 (Fig. A4a). The trend is 0.1\nmm day-1 decade-1 in MMEM (Fig. A4b), which means that the external forcing\ncontributes 36% to the observed trend. In contrast, the contribution of internal\nvariability to the rainfall trend reaches 64% as the regional averaged trend is 0.18 mm\nday-1 decade-1. In addition, the external forcing and internal variability contribute 81%\nand 19% to the observed spring land heating in the Middle East, respectively. In\nsummary, the relative contributions of internal variability and external forcing are\nquantified in the revised manuscript.\nFigure A2 Trends in (a) Pakistan summer rainfall (unit: mm day-1 decade-1) and (b)\nspring skin temperature over the Middle East (unit: °C decade-1) for 1979-2014. The\nbars with black dots indicate the average of trends in all model members, and the\nobservations as certain values are obtained from the GPCP (rainfall) and the ERA5\n(skin temperature). The upper and bottom dashed lines indicate the uncertainty of the\ntrends in all 192 model members, which is calculated by one standard deviation of\ntrends. The multi-model ensemble means (MMEM) denote the contribution of external\nforcing and the differences between the observation and the MMEM denote the\ncontribution of internal variability.\nReferences\nAneesh S, Sijikumar S (2016) Changes in the South Asian monsoon low level jet during\nrecent decades and its role in the monsoon water cycle. J Atmos Solar Terr Phys 138–\n139:47–53.\nSandeep, S., and R. S. Ajayamohan (2015), Poleward shift in Indian summer monsoon\nlow level jetstream under global warming, Climate Dynamics, 45(1-2), 337–351.\nReviewer #2:\nRecommendation: Accept with pending for minor revision\nMinor comments:\nLine 192: Is the observed precipitation here from GPCP, and referred to Supplement\nFigure 6? If yes, in my opinion, you should mention it here and also mention it in the\ncaption of Supplement Figure 6.\nResponse:\nThank you for your keen eyes. The observed precipitation here is obtained from\nthe GPCP dataset. It is modified in the revised manuscript."}]

Decision letter
REVIEWERS' COMMENTS
Reviewer #1 (Remarks to the Author):
Thank you for addressing the reviewers' comments and making the necessary revisions, I am pleased to
recommend accepfing the manuscript for publicafion in Nature Communicafion.
I look forward to seeing your work in print.